Publicaciones Académicas

Ambiental

Production of (R)-3-hydroxybutyric acid from methane by in vivo depolymerization of polyhydroxybutyrate in Methylocystis parvus OBBP

Yañez L., Y. Rodríguez, F. Scott, A. Vergara-Fernández, R. Muñoz

Bioresource Technology, 2022

Methylocystis parvus OBBP accumulates polyhydroxybutyrate (PHB) using methane as the sole carbon and energy source. In this work, the feasibility of producing (R)-3-hydroxybutyric acid (R3HBA) via intracellularly accumulated PHB through depolymerization (in-vivo) was investigated. Results showed that a PHB to R3HBA conversion of 77.2 ± 0.9% (R3HBA titer of 0.153 ± 0.002 g L-1) can be attained in a mineral medium containing 1 g L-1 KNO3 at 30 °C with shaking at 200 rpm and a constant pH of 11 for 72 h. Nitrogen deprivation and neutral or acidic pHs strongly reduced the excreted R3HBA concentration. Reduced oxygen availability negatively affected the R3HBA yield, which decreased to 73.6 ± 4.9% (titer of 0.139 ± 0.01 g L-1) under microaerobic conditions. Likewise, the presence of increasing concentrations of R3HBA in the medium before the onset of PHB depolymerization reduced the initial R3HBA release rate and R3HBA yield.

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Production of (R)-3-hydroxybutyric acid from methane by in vivo depolymerization of polyhydroxybutyrate in Methylocystis parvus OBBP

Yañez L., Y. Rodríguez, F. Scott, A. Vergara-Fernández, R. Muñoz | Bioresource Technology | 2022

Methylocystis parvus OBBP accumulates polyhydroxybutyrate (PHB) using methane as the sole carbon and energy source. In this work, the feasibility of producing (R)-3-hydroxybutyric acid (R3HBA) via intracellularly accumulated PHB through depolymerization (in-vivo) was investigated. Results showed that a PHB to R3HBA conversion of 77.2 ± 0.9% (R3HBA titer of 0.153 ± 0.002 g L-1) can be attained in a mineral medium containing 1 g L-1 KNO3 at 30 °C with shaking at 200 rpm and a constant pH of 11 for 72 h. Nitrogen deprivation and neutral or acidic pHs strongly reduced the excreted R3HBA concentration. Reduced oxygen availability negatively affected the R3HBA yield, which decreased to 73.6 ± 4.9% (titer of 0.139 ± 0.01 g L-1) under microaerobic conditions. Likewise, the presence of increasing concentrations of R3HBA in the medium before the onset of PHB depolymerization reduced the initial R3HBA release rate and R3HBA yield. Keywords: (R)-3-hydroxybutyrate; Chiral compounds; Greenhouse gas valorization; Methanotrophic bacteria; Polyhydroxybutyrate

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Antarctic Rahnella inusitata: A Producer of Cold-Stable β-Galactosidase Enzymes.

Núñez-Montero K.; Salazar R.; Santos A.; Olman Gómez E.; Farah S.; Troncoso C.; Hoffmann C.; Melivilu D.; Scott F.; Barrientos-Díaz L. | International journal of molecular sciences. | 2021

There has been a recent increase in the exploration of cold-active β-galactosidases, as it offers new alternatives for the dairy industry, mainly in response to the current needs of lactose-intolerant consumers. Since extremophilic microbial compounds might have unique physical and chemical properties, this research aimed to study the capacity of Antarctic bacterial strains to produce cold-active β-galactosidases. A screening revealed 81 out of 304 strains with β-galactosidase activity. The strain Se8.10.12 showed the highest enzymatic activity. Morphological, biochemical, and molecular characterization based on whole-genome sequencing confirmed it as the first Rahnella inusitata isolate from the Antarctic, which retained 41–62% of its β-galactosidase activity in the cold (4 °C–15 °C). Three β-galactosidases genes were found in the R. inusitata genome, which belong to the glycoside hydrolase families GH2 (LacZ and EbgA) and GH42 (BglY). Based on molecular docking, some of these enzymes exhibited higher lactose predicted affinity than the commercial control enzyme from Aspergillus oryzae. Hence, this work reports a new Rahnella inusitata strain from the Antarctic continent as a prominent cold-active β-galactosidase producer. View Full-Text

Keywords: β-galactosidase; Antarctica; lactose; cold-adapted bacteria; extremozymes

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Characterization of the microbial community in a biotrickling filter treating a complex mixture of gaseous compounds causing odor nuisance.

Aguirre A.; Gentina JC.; Malhautier L.; Fanlo JL.; Vergara-Fernández A.; Scott F.; Aroca G. | Journal of Chemical Technology & Biotechnology | 2021

BACKGROUND

Industrial gaseous emissions causing odor nuisance has become a major environmental issue in many countries. Biotrickling filters are suitable for treating mixtures of gaseous compounds with high removal efficiencies. The aim of this work was to determine the vertical distribution of microbial communities established in a biotrickling filter treating a mixture of gaseous compounds causing odor nuisance, and to correlate its performance with the spatial and temporal distribution of inoculated bacteria.

RESULTS

In the long-term operation, at day 538, the removal efficiencies were 100% for ammonia and H2S, 73% for methanol, 63% for trimethylamine, 41% for dimethylsulphide, and 32% for 2,5-dimethylpirazyne; the elimination capacities were 1.5 [g NH3 m−3bed h−1], 0.7 [g H2S m−3bed h−1], 0.7 [g MeOH m−3bed h−1], 3.3 [g TMA m−3bed h−1], 0.21 [g DMS m−3bed h−1], and 0.6 [g 2,5-DMP m−3bed h−1]. A stratification pattern of pollutants degradation along the biotrickling filter (BTF) was identified, where most of the removal of NH3, TMA, and H2S occurred at the lower level of the column, the removal of methanol and 2,5-dimethylpyrazine occurred at low and medium levels, and the removal of dimethylsulphide occurred mainly at the upper levels. High-throughput DNA sequencing analysis showed a colonization by bacteria genera different from the inoculated and a stratification of these bacteria along the BTF.

CONCLUSION

There is stratification in the biofilm of a biotrickling filter during its long-term operation, and a relationship between the stratification of the microbial communities and the removal of the complex mixture of gases was identified. © 2021 Society of Chemical Industry

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Two internal bottlenecks cause the overflow metabolism leading to poly (3-hydroxybutyrate) production in Azohydromonas lata DSM1123.

Scott, F.; Yáñez L.; Conejeros R.; Araya B.; Vergara-Fernández F | Journal of Environmental Chemical Engineering. | 2021

Polyhydroxybutyrate production in the bacteria Azohydromonas lata DSM1123 has been regarded as growth-associated based on batch experiments. However, growth association can only be confirmed under chemostat culture. In this work, an experimental approach followed by Flux Balance Analysis (FBA) modeling was used to analyze the behavior of this strain under glucose, oxygen, and nitrogen-limited conditions. The model allowed the identification of candidate enzymes constraining the flux through the tricarboxylic acid cycle, and the role of ATP synthase as the key flux controlling enzyme for the respiratory metabolism, in terms of its share of the total metabolically active protein. The results presented in this work and the model developed could assist in the economic and environmental assessment of new continuous processes to produce PHB and other metabolites in A. lata DSM1123, a strain capable of hydrogen use and CO2 fixation. Keywords: Polyhydroxybutyrate; Overflow metabolism; Flux balance analysis; Azohydromonas lata; Biopolymers

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Improvement of thermal stability of highly active species on SiO2 supported copper-ceria catalysts.

Aguila, G.; Calle, R.; Guerrero, S.; Baeza, P.; Araya, P. | RSC Advances, 11 (2021), 33271-33275. | 2021

CuO–CeO2/SiO2 catalysts lose activity when they are calcined at 600 °C and temperatures above. This loss of activity was related to a decrease in the amount of highly dispersed Cu species interacting with Ce (CuO–CeO2 interface) over the SiO2 support. These species are highly active in CO oxidation, so this reaction was selected to conduct this study. In order to avoid the activity loss in CuO–CeO2/SiO2 catalysts, the effect of high Ce loads (8, 16, 24, and 36%) on the thermal stability of these catalysts was studied. The results reveal that when increasing calcination temperature from 500 to 700 °C, the catalysts with Ce load equal to or higher than 24% increase the formation of highly dispersed Cu interacting with Ce and therefore the activity (90% of CO conversion at 120 °C). In catalysts with Ce load below 24%, Cu species agglomerate and decrease the activity (less than 5% of CO conversion at 120 °C).

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Biofiltration of volatile organic compounds and polycyclic aromatic hydrocarbons

Vergara-Fernández, A.; Scott, F.; Moreno-Casas, P. | From Biofiltration to Promising Options in Gaseous Fluxes Biotreatment | 2021

Indoor and outdoor air pollution is a complex and multifactorial problem involving particulate matter (PM), biological agents, and gaseous pollutants. Several organizations, such as the World Health Organization, the United States Environmental Protection Agency, or the French Indoor Air Quality Observatory, have established acceptable levels for indoor air pollutants including volatile organic compounds (VOCs, such as benzene and formaldehyde) and polycyclic aromatic hydrocarbons (PAHs), among many other compounds, based on their ubiquity, concentration and sources, being motor vehicle emissions, cooking, smoking, and residential heating the chief sources of VOCs and PAHs.

Despite the abundance of studies demonstrating the potential of biological methods to eliminate VOCs in laboratory scale, less is known regarding the elimination of PAH vapors by biological systems at concentrations typically found in polluted environments.

This chapter introduces the problem of VOCs and PAHs as air contaminants and the fundamentals of biofiltration as a technology for their elimination. Research in this area has been active during the last decades, and a thorough revision of the discoveries is provided before introducing the most important considerations in the design and operation of biofilters for the treatment of VOCs and PAHs, including pH, temperature, selection of the packing media, and the microorganisms used for inoculation. The later might influence the mass transfer, solubility, and biodegradation of this type of contaminants as the use of filamentous fungi (along with bacteria forming a consortium) can promote the direct absorption of VOCs and PAHs, from the gas phase. Keywords: Volatile organic compounds; polycyclic aromatic hydrocarbons; fixed bed biofilters; bioscrubbers; fungi; bacteria

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Biodegradation of 2,5-dimethylpyrazine in gas and liquid phase by the fungus Fusarium solani

Araya, B; Diaz, C; San Martin, J; Vergara-Fernández, A; Aroca, G; Scott, F. | Journal of Chemical Technology & Biotechnology. (2021). DOI 10.1002/jctb.6903 | 2021

BACKGROUND

Alkylpyrazines are odorous compounds conferring pleasant aromas to baked and roasted foods. However, they are also emitted during food processing, creating a nuisance for the operators and the community. Only a few bacterial isolates have been shown to degrade 2,5-methylpyrazine (DMP), as a model alkylpyrazine. This work aimed to study the ability of DMP biodegradation by the filamentous fungus Fusarium solani.

RESULTS

Evidence of the degradation of DMP was collected in axenic cultures of F. solani in liquid mineral medium and over a saturated solid support using DMP as the sole carbon and energy source. DMP was used for growth as evidenced by the formation of an abundant aerial mycelium over a solid support, accompanied by the production of 70 ppm CO2 mg−1 dry biomass, and by its consumption in liquid media at a rate of 58.3 mg g−1 biomass h−1, a value comparable to those reported for bacteria. A non-axenic biofilter was mounted, fed with a DMP-laden air stream, and operated for 40 days. The maximum DMP elimination capacity achieved was 8.5 g m−3 h−1 at an inlet load of 11.3 g m−3 h−1 (an 80% relative efficiency).

CONCLUSION

Fusarium solani uses DMP as a carbon source, showing great potential for its abatement in a biofilter. High-throughput DNA sequencing of biofilter samples showed that it was the most representative member of the community, with a relative abundance surpassing 97%, indicating that it played a pivotal role in the biofilter. © 2021 Society of Chemical Industry (SCI).

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Optimal control in chemical engineering: Past, present and future.

Nolasco, Eduardo; Vassiliadis, Vassilios S; Kähm, Walter; Adloor, Sai Darshan; Al Ismaili, Riham; Conejeros, Raúl; Espaas, Thomas; Gangadharan, Nishanthi; Mappas, Vasileios; Scott, Felipe. | Computers & Chemical Engineering, 155(),107528, doi: 10.1016/j.compchemeng.2021.107528. | 2021

Roger W.H. Sargent (1926–2018) was an unprecedented pioneer who foresaw the role that mathematical and computational tools would have in chemical engineering. His visionary work created the multidisciplinary field of Process Systems Engineering (PSE), a field that acts as a central hub influencing all subfields of chemical engineering. His particular interest in optimal control applied to industrial processes led him to develop numerical techniques to solve large-scale optimal control problems. In this work, a brief overview of the theory of optimal control is offered, spanning from its roots in calculus of variations to Pontryagin’s maximum principle and some of its extensions. Furthermore, important contributions made by Sargent and his students are presented. Selected applications currently found in literature are presented as well–ranging from classical chemical engineering systems to bioprocesses. Some future perspectives of the field are also presented in the concluding section. Keywords: Roger W.H. Sargent; Optimal control; Process systems engineering; Calculus of variations; Model predictive control; Multistage optimal control problems; Dynamic flux balance analysis; Maintenance of decaying performance processes; Global optimization

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The Effect of the ZrO2 Loading in [email protected] Catalysts for Transesterification Reaction

D. Salinas, S. Guerrero, C.H. Campos, T. Bustamante, G. Pecchi | Materials 13(1): 221, 2020 | 2020

The effect of the ZrO2 loading was studied on spherical [email protected] structures synthetized by a simple route that combines the Stöber and sol-gel methods. The texture of these materials was determined using SBET by N2 adsorption, where the increment in SiO2 spheres’ surface areas was reached with the incorporation of ZrO2. Combined the characterization techniques of using different alcoholic dissolutions of zirconium (VI) butoxide 0.04 M, 0.06 M, and 0.08 M, we obtained [email protected] materials with 5.7, 20.2, and 25.2 wt % of Zr. Transmission electron microscopy (TEM) analysis also uncovered the shape and reproducibility of the SiO2 spheres. The presence of Zr and Ca in the core–shell was also determined by TEM. X-ray diffraction (XRD) profiles showed that the c-ZrO2 phase changed in to m-ZrO2 by incorporating calcium, which was confirmed by Raman spectroscopy. The purity of the SiO2 spheres, as well as the presence of Zr and Ca in the core–shell, was assessed by the Fourier transform infrared (FTIR) method. CO2 temperature programmed desorption (TPD-CO2) measurements confirmed the increment in the amount of the basic sites and strength of these basic sites due to calcium incorporation. The catalyst reuse in FAME production from canola oil transesterification allowed confirmation that these calcium [email protected] catalysts turn out to be actives and stables for this reaction. View Full-Text

Keywords: [email protected]; catalyst; ZrO2; CaO; FAME

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Alternatives for gas treatment.

Vergara-Fernández, A., F. Scott, P. Moreno-Casas | Biofiltration to Featured Options in Gaseous Fluxes Biotratment: Recent Developments, New Trends, Advances, and Opportunities. Ed. Gabriela Soreanu and Eric Dumont. Elsevier Book. | 2020

From Biofiltration to Promising Options in Gaseous Fluxes Biotreatment: Recent Developments, New Trends, Advances, and Opportunities provides an overview on the biological tools used for the treatment of the gaseous fluxes, with emphasis on traditional and perspective options, opening new horizons for research and implementation in practice. It is known that air pollution is an emergent global issue and a priority within the international environmental programs. Moreover, technologies based on biological methods are significantly contributing to the sustainable development concept. Thus this book provides tools for solving air pollution issues in a sustainable manner. These issues can be solved at different levels (e.g., “end-of-pipe” gaseous streams, indoor/outdoor air, closed environments), which can be approached by the different biotechniques presented in the book, from classical biofiltration techniques (part 1) to phytotreatment and microalgae-based techniques (part 2). Although all options have their particularities that make them special for certain applications, a special attention is drawn to the potential of the last one, which offers multiple possibilities for biomass valorization. Scientists from worldwide with relevant experience in their field have been contributed to the development of this book.

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Mechanistic Description of Convective Gas-Liquid Mass Transfer in Biotrickling Filters Using CFD Modeling

Moreno-Casas, P.A.; Scott, F.; Delpiano, J.; Abell, J.A.; Caicedo, F.; Muñoz, R.; Vergara-Fernández, A | Environmental Science & Technology 54, no. 1 (2019): 419-426. | 2020

The gas–liquid mass transfer coefficient is a key parameter to the design and operation of biotrickling filters that governs the transport rate of contaminants and oxygen from the gas phase to the liquid phase, where pollutant biodegradation occurs. Mass transfer coefficients are typically estimated via experimental procedures to produce empirical correlations, which are only valid for the bioreactor configuration and range of operational conditions under investigation. In this work, a new method for the estimation of the gas–liquid mass transfer coefficient in biotrickling filters is presented. This novel methodology couples a realistic description of the packing media (polyurethane foam without a biofilm) obtained using microtomography with computational fluid dynamics. The two-dimensional analysis reported in this study allowed capturing the mechanisms of the complex processes involved in the creeping porous air and water flow in the presence of capillary effects in biotrickling filters. Model predictions matched the experimental mass transfer coefficients (±30%) under a wide range of operational conditions.

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Experimental Study on Hydrothermal Carbonization of Lignocellulosic Biomass with Magnesium Chloride for Solid Fuel Production

Carrasco S., J. Silva, E. Pino-Cortés, J. Gomez, F. Vallejo, L. Díaz-Robles, V. Campos, F. Cubillos, S. Pelz, S. Paczkowski, F. Cereceda-Balic, A. Vergara-Fernández, M. Lapuerta, A. Pazo, E. Monedero, K. Hoekman | Processes. 8:1-12. | 2020

The effect of magnesium chloride as an additive of hydrothermal carbonization (HTC) of lignocellulosic biomass (Pinus radiata sawdust) was studied. The HTC tests were carried out at fixed conditions of temperature and residence time of 220 °C and 1 h, respectively, and varying the dose of magnesium chloride in the range 0.0–1.0 g MgCl2/g biomass. The carbonized product (hydrochar) was tested in order to determine its calorific value (HHV) while using PARR 6100 calorimeter, mass yield by gravimetry, elemental analysis using a LECO TruSpec elemental analyzer, volatile matter content, and ash content were obtained by standardized procedures using suitable ovens for it. The results show that using a dose of 0.75 g MgCl2/g biomass results in an impact on the mass yield that was almost equal to change operating conditions from 220 to 270 °C and from 0.5 to 1 h, without additive. Likewise, the calorific value increases by 33% for this additive dose, resulting in an energy yield of 68%, thus generating a solid fuel of prominent characteristics.

Keywords: hydrothermal carbonization; waste to energy; additives; lignocellulosic biomass; magnesium chloride

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Computational tomography and CFD simulation of a biofilter treating a toluene, formaldehyde and benzo[a]pyrene vapor mixture

Moreno, P.; Scott, F.; Delpiano, J.; Vergara, A. | Chemosphere. 240: 124924. | 2020

In this work, a 3D computational tomography (CT) of the packing material of a laboratory column biofilter is used to model airflow containing three contaminants. The degradation equations for toluene, formaldehyde and benzo[α]pyrene (BaP), were one-way coupled to the CFD model. Physical validation of the model was attained by comparing pressure drops with experimental measurement, while experimental elimination capacities for the pollutants were used to validate the biodegradation kinetics. The validated model was used to assess the existence of channeling and to predict the impact of the three-dimensional porous geometry on the mass transfer of the contaminants in the gas phase.

Our results indicate that a physically meaningful simulation can be obtained using the techniques and approach presented in this work, without the need of performing experiments to obtain macroscopic parameters such as gas-phase axial and radial dispersion coefficients and porosities. Keywords: Volatile organic compounds; Biofiltration; Modeling; CFD; Computational tomography

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Beyond Intracellular Accumulation of Polyhydroxyalkanoates: Chiral Hydroxyalkanoic Acids and Polymer Secretion

Yañez, L.; Conejeros, R.; Vergara-Fernández, A.; Scott, F. | Frontiers in Bioengineering and Biotechnology 2020; 8: 248. | 2020

Polyhydroxyalkanoates (PHAs) are ubiquitous prokaryotic storage compounds of carbon and energy, acting as sinks for reducing power during periods of surplus of carbon source relative to other nutrients. With close to 150 different hydroxyalkanoate monomers identified, the structure and properties of these polyesters can be adjusted to serve applications ranging from food packaging to biomedical uses. Despite its versatility and the intensive research in the area over the last three decades, the market share of PHAs is still low. While considerable rich literature has accumulated concerning biochemical, physiological, and genetic aspects of PHAs intracellular accumulation, the costs of substrates and processing costs, including the extraction of the polymer accumulated in intracellular granules, still hampers a more widespread use of this family of polymers. This review presents a comprehensive survey and critical analysis of the process engineering and metabolic engineering strategies reported in literature aimed at the production of chiral (R)-hydroxycarboxylic acids (RHAs), either from the accumulated polymer or by bypassing the accumulation of PHAs using metabolically engineered bacteria, and the strategies developed to recover the accumulated polymer without using conventional downstream separations processes. Each of these topics, that have received less attention compared to PHAs accumulation, could potentially improve the economy of PHAs production and use. (R)-hydroxycarboxylic acids can be used as chiral precursors, thanks to its easily modifiable functional groups, and can be either produced de-novo or be obtained from recycled PHA products. On the other hand, efficient mechanisms of PHAs release from bacterial cells, including controlled cell lysis and PHA excretion, could reduce downstream costs and simplify the polymer recovery process.

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A comparative assessment of the performance of fungal-bacterial and fungal biofilters for methane abatement

Vergara-Fernández, A; F.Scott, F. Carreño-López, G. Aroca, P. Moreno-Casas, A. González-Sánchez, R. Muñoz | Journal of Environmental Chemical Engineering. 8: 104421 | 2020

Methane is an important contributor to global warming and especially for dilute emissions, its oxidation to carbon dioxide can be difficult and expensive. Methane abatement was studied in a biofilter inoculated solely with the filamentous fungus Fusarium solani and compared to a biofilter inoculated with a consortium of methanotrophic bacteria (Methylomicrobium album and Methylocystis sp.) and F. solani.

Results showed that F. solani degrade methane as the sole carbon source, achieving a maximum elimination capacity of 42.2 g m−3 h-1, nearly half of the maximum elimination capacity of the fungal-bacterial consortium. The second Damköhler number indicates that under the prevailing operational conditions, the fungal biofilter performance was bioreaction limited meanwhile external mass transport limitation was found on the fungal/methanotrophic bacteria biofilter.

Results support the hypothesis that the beneficial effect of F. solani during CH4 biofiltration is mediated by biomass hydrophobicity rather than by an increase in the mass transfer area. Keywords: Methane abatement; Fusarium solani; Biofiltration; Mass transfer coefficient; Mathematical modeling

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The transient reduction of NO with CO and naphthalene in the presence of oxygen using a core-shell [email protected] copper catalyst.

Venegas, F.; López, N.; Sánchez-Calderón, L.; Aguila, G.; Araya, P.; Guo, X.; Zhu, Y.; Guerrero, S. | Catalysis Science & Technology. 9:3408 | 2019

This work studied the reaction of common pollutants on a catalytic surface under oxidizing conditions. CO and naphthalene were used to reduce NO in the presence of oxygen during the transient heating of metal oxide nanoparticles. The latter consisted of a core–shell [email protected] support with a TiO2 core and a samarium-stabilized CeO2 shell, impregnated with copper and potassium. The addition of potassium simulated the gradual accumulation of an alkali metal during biomass combustion, which can poison the catalyst. The Cu/[email protected] catalyst achieved the complete conversions of NO, CO and naphthalene at 225, 236 and 255 °C, respectively. Even though the inclusion of potassium had the expected negative effect, the K/Cu/[email protected] catalyst was still able to fully convert NO and CO at 323 and 299 °C, respectively, whereas a maximum naphthalene conversion of only 66% was obtained at 350 °C.

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Study of the influence of the Cu/Ce loading ratio in the formation of highly active species on ZrO2 supported copper-ceria catalysts

G. Aguila, S. Guerrero, P. Baeza, P. Araya. | Materials Chemistry and Physics, volume 223, pages 666-675 | 2019

This work studies the effect of different Cu/Ce loading ratios in the formation of highly dispersed copper species being interacting with CeO2 on zirconia-supported CuOsingle bondCeO2 catalysts. These species have a strong effect on the CO oxidation reaction and for this reason such reaction was selected to conduct the present study. Catalysts with different metal loads were prepared by the co-impregnation method of Cu and Ce nitrates on ZrO2 support. It was found that the influence of the two metals occurs cooperatively. The type of copper species formed on the ZrO2 support depends on the Cu and Ce loads, with the existence of an optimum in activity when the Cu/Ce loading ratio being around 0.5. The incorporation of CeO2 increases the dispersion capacity of ZrO2 and facilitates the reduction of surface CuO species. Maintaining the Cu/Ce loading ratio constant at the optimal ratio (0.5) and increasing the total metal load (Cu+Ce) gave no significant increase in the catalytic activity above 6%. The latter suggests that higher metal loadings (Cu+Ce) does not lead to an increment of highly dispersed copper species interacting with CeO2, which is the most active species on the surface of this catalysts. Keywords: Copper; Cerium; Zirconia; CO oxidation

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Simultaneous reduction of NO with CO and oxidation of naphthalene using a potassium promoted copper catalyst supported on Ce/TiO2-SiO2.

Morales, C.; López, N. ;Aguila, G. ; Araya, P. ;Scott, F. ; Vergara-Fernández, A. ; Guerrero, S. | Materials Chemistry and Physics. 222:294-299 | 2019

A set of Cu/Ce/TiO2-SiO2 and K/Cu/Ce/TiO2-SiO2 catalysts was used for the simultaneous use of CO and naphthalene as reducing agents for the reduction of NO in the presence of oxygen. Only 5% of TiO2 greatly increase the activity of the catalysts. It was also found that the addition of potassium is able to tune down these oxidation reactions allowing the reduction of NO. The Cu/Ce/TiO2-SiO2 catalyst achieves the full conversion of naphthalene at 302 °C, 96% of CO conversion at the same temperature, and negligible conversion of NO. On the other hand, the K/Cu/Ce/TiO2-SiO2 catalyst reaches the full conversion of CO at 330 °C, 90% conversion of NO at 342 °C, and 70% conversion of naphthalene at the latter temperature. Keywords: Selective NO reduction; CeO2; TiO2-SiO2; Copper; Potassium

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Removal of Gaseous Pollutants from Air by Fungi

Vergara-Fernández, A.; Scott, F.; Moreno-Casas, P.; Revah, S. | Fungal Bioremediation: Fundamentals and Application | 2019

Air quality represents a worldwide concern, with consequences not only for the health of those exposed to the polluted environments, but also to the future of global economic development. The existent technologies to improve air quality can be classified as physical, chemical, or biological. This chapter presents the state of the art and the technical advances in the research of biofiltration of gaseous contaminants using filamentous fungi. It is organized as follows: first, an outline of the basic and technological aspects of biofiltration is given in section 2, next the research topics in fungal biofiltration are reviewed, and finally, in section 4, the most important operational considerations in fungal biofilters are analyzed.

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Methane biodegradation and enhanced methane solubilization by the filamentous fungi Fusarium solani.

Vergara, A.; Morales, P.; Scott, F.; Guerrero, S.; Yanez, L.; Mau, S.; Aroca, G. | Chemosphere. 226: 24-35. | 2019

Methane is one of the most important greenhouse gases emitted from natural and human activities. It is scarcely soluble in water; thus, it has a low bioavailability for microorganisms able to degrade it. In this work, the capacity of the fungus Fusarium solani to improve the solubility of methane in water and to biodegrade methane was assayed. Experiments were performed in microcosms with vermiculite as solid support and mineral media, at temperatures between 20 and 35 °C and water activities between 0.9 and 0.95, using pure cultures of F. solani and a methanotrophic consortium (Methylomicrobium album and Methylocystis sp) as a control. Methane was the only carbon and energy source. Results indicate that using thermally inactivated biomass of F. solani, decreases the partition coefficient of methane in water up to two orders of magnitude. Moreover, F. solani can degrade methane, in fact at 35 °C and the highest water activity, the methane degradation rate attained by F. solani was 300 mg m−3 h−1, identical to the biodegradation rate achieved by the consortium of methanotrophic bacteria. Keywords: Methane abatement; Fusarium solani; Biofiltration; Methane partition coefficient; Methanotroph

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Thermal stability of the Cu-CeO2 interface on silicia and alumina, and its relation with activity in the oxidation reaction of CO and the decomposition of N2O.

Alvarez, P.; Aguila, G.; Guerrero, S.; Araya, P. | Journal of Chilean Chemical Society. 63, 3, 4032-4038. | 2018

The effect of the support on the formation of the Cu-CeO2 interface and its thermal stability after calcination at 500, 700 and 900 °C is studied. The supports used are SiO2, because of its inert character, and A2O3, because it can interact with the Cu and Ce species on the surface. The catalysts were characterized by BET, XRD, UV-vis DRS, and TPR with H2. The catalytic activity in the CO oxidation reactions with O2 at low temperature and the decomposition of N2O were selected to visualize the effect of temperature on the concentration of Cu-CeO2 interfacial sites. The results show that at a calcination temperature of 500 °C the formation of the Cu-CeO2 interface is favored over the SiO2 support. However, the stability of the Cu-CeO2 interface on SiO2 is much lower than on Al2O3, causing a substantial decrease of the interfacial sites calcining at 700 °C, and segregation of the Cu and Ce species on the surface of the silica, with complete loss of the catalytic activity in both reactions when calcining at 900 °C. In contrast, on alumina the Cu-CeO2 interface is more stable and presents a significant catalytic activity in both reactions, even when calcining at 900 °C. The characterization results show that the sintering process of Cu species and CeO2 particles is less on the alumina support due to the greater interaction of the Cu and Ce with this support.

Palabras clave : Cu; Ce; silica; alumina; CO oxidation; N2O decomposition.

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Simulation and optimization of dynamic flux balance analysis models using an interior point method reformulation.

Scott, F.; Wilson, P.; Conejeros, R.; Vassiliadis, V.S. | Comput. Chem. Eng. 119, 152-170. doi:10.1016/j.compchemeng.2018.08.041 | 2018

This work presents a novel, differentiable, way of solving dynamic Flux Balance Analysis (dFBA) problems by embedding flux balance analysis of metabolic network models within lumped bulk kinetics for biochemical processes. The proposed methodology utilizes transformation of the bounds of the embedded linear programming problem of flux balance analysis via a logarithmic barrier (interior point) approach. By exploiting the first-order optimality conditions of the interior-point problem, and with further transformations, the approach results in a system of implicit ordinary differential equations. Results from four case studies, show that the CPU and wall-times obtained using the proposed method are competitive with existing state-of-the art approaches for solving dFBA simulations, for problem sizes up to genome-scale. The differentiability of the proposed approach allows, using existing commercial packages, its application to the optimal control of dFBA problems at a genome-scale size, thus outperforming existing formulations as shown by two dynamic optimization case studies. Keywords: Dynamic flux balance analysis; Ordinary differential equations with embedded optimization; Linear programming; Genome-scale metabolic network

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Highly active Cu/[email protected] catalyst for the simultaneous reduction of NO with CO and naphthalene in the presence of oxygen.

López, N.; Aguila, G.; Araya, P.; Guerrero, S. | Catalysis Communications. 104,17-21. | 2018

The transient combustion of biomass leads to the evolution of a variety of pollutants (NO, CO, organic compounds, and many others) that can react with each other on a suitable catalyst to generate compounds of lower toxicity. Here, the transient reduction of NO with CO and naphthalene in the presence of oxygen was studied on a Ca/Cu/YCeO2–TiO2 catalyst. Response surface methodology was used to identify the optimum amounts of calcium, copper, and cerium. The optimized Ca/Cu/YCeO2–TiO2 catalyst was then extensively studied and characterized. The coupling of yttrium-stabilized ceria with TiO2 provided an active support that effectively activated naphthalene. When calcium and copper were added to the support, the obtained Ca/Cu/YCeO2–TiO2 catalyst achieved the full conversion of CO and naphthalene and 72% conversion of NO. The Ca/Cu/YCeO2–TiO2 catalyst possessed labile oxygen species, which might be related to the high catalytic activity.

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Biofiltration of volatile organic compounds using fungi and its conceptual and mathematical modeling.

Vergara, A.; Revah, S. ; Moreno, P.; Scott, F. | Biotechnology Advances. 36: 1079-1093. | 2018

Volatile organic compounds (VOCs) are ubiquitous contaminants that can be found both in outdoor and indoor air, posing risks to human health and the ecosystems. The treatment of air contaminated with VOCs in low concentrations can be effectively performed using biofiltration, especially when VOCs are hydrophilic. However, the performance of biofilters inoculated with bacteria has been found to be low with sparsely water soluble molecules when compared to biofilters where fungi develop. Using conceptual and mathematical models, this review presents an overview of the physical, chemical and biological mechanisms that explain the differences in the performance of fungal and bacterial biofilters. Moreover, future research needs are proposed, with an emphasis on integrated models describing the biological and chemical reactions with the mass transfer using high-resolution descriptions of the packing material. Keywords: Biofiltration; VOC; Fungi; Bacteria; Modeling; Computational fluid dynamics

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Biofiltration of benzo[a]pyrene, toluene and formaldehyde in air by a consortium of Rhodococcus erythropolis and Fusarium solani: Effect of inlet loads, gas flow and temperature.

Vergara-Fernández, A.; Yánez, D.; Morales, P.; Scott, F.; Aroca, G.; Diaz-Robles, L.; Moreno-Casas, P. | Chemical Engineering Journal. 332: 702-710. (2018). DOI: 10.1016/j.cej.2017.09.095 | 2018

Volatile organic compounds (VOCs) and polycyclic aromatic hydrocarbons (PAHs) are air contaminants with serious effects on human health. They include compounds with very different physicochemical properties, ranging from low to high volatility and low to high hydrophobicity. The objective of this research is to assess the feasibility of the simultaneous abatement of formaldehyde, a soluble and slightly polar VOC, toluene a hydrophobic and volatile VOC and benzo[α]pyrene (BaP), a representative PAH in a biofiltration reactor inoculated with the fungi Fusarium solani and the bacteria Rhodococcus erythropolis. Results obtained at an extended range of inlet loads: 3.7 to 447.7, 9.0 to 273.1 and 6.9 to 247.4 g m−3 h−1 of toluene, formaldehyde and BaP, respectively, show that the elimination capacity and removal efficiencies of the contaminants were largely independent of each other. Moreover, the system can accommodate a fivefold increase in inlet gas flow maintaining removal efficiencies close to 60% for all the contaminants tested when the inlet loads of contaminants were kept constant. The most dramatic decrease in elimination capacity and removal efficiency in the system was obtained by changing the temperature of the system, where a decrease from 25 °C to 17 °C reduced the formaldehyde removal efficiency from 67% to 43%. BaP and toluene removal efficiencies were less affected by the decrease in system’s temperature. This study shows the high flexibility of a biofiltration system inoculated with F. solani and R. erythropolis for the abatement of toluene, formaldehyde and BaP. Keywords: Biofiltration; Toluene; Formaldehyde; Benzo[α]pyrene; Fusarium solani; Rhodococcus erythropolis

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Study of the effect of the incorporation of TiO2 nanotubes on the mechanical and photodegradation properties of polyethylenes

Zenteno, A.; Lieberwirth, I. ; Catalina, F. ; Corrales, T. ; Guerrero, S. ; Vasco, D.A.; Zapata, P. | Composites Part B. 112 66-73. | 2017

TiO2 nanotubes (TiO2-Ntbs) synthesized by a hydrothermal method with a diameter of ca. 5 nm were used as filler to prepare polyethylene (PE) and linear low density polyethylene (LLDPE) composites by melt blending. Nanotubes were used either as synthesized or organically modified with hexadecyltrimethoxysilane (Mod-TiO2-Ntbs). In some cases nanoparticles form secondary structures with sizes around 100 nm and agglomerates larger than 2 μm are also seen by transmission electron microscopy (TEM). In terms of mechanical properties, the addition of TiO2-Ntbs resulted in a composite, LLDPE/TiO2-Ntbs, with improved properties. Compared with the pure polymer, Young’s modulus increased by ca. 50%, while yield stress increased by ca. 35%. On the other hand, PE/Mod-TiO2-Ntbs and LLDPE/Mod-TiO2-Ntbs with 5 wt% filler loading showed higher E′ values in the storage modulus at low temperatures than either neat PE and LLDPE.

The photodegradation properties of the PE/Mod-TiO2-Ntbs and LLDPE/Mod-TiO2-Ntbs composites were studied. The largest increase of chemiluminescence emission (CL) and carbonyl index (CI) was found for LLDPE/Mod-TiO2-Ntbs during photoaging. That behavior may be due to large branching of the polymer, and to the presence of the nanotubes incorporated into the LLDPE, which promoted and accelerated its photodegradation due to reactive species generated during irradiation.

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On the solution of differential-algebraic equations through gradient flow embedding.

del Rio, E.; Bakker, C.; Fiorelli, F.; Paraskevopoulos, M.; Scott, F.; Conejeros, R.; Vassiliadis, V. | Comput. Chem. Eng. 103, 165-175. | 2017

In this paper Gradient Flow methods are used to solve systems of differential-algebraic equations via a novel reformulation strategy, focusing on the solution of index-1 differential-algebraic equation systems. A reformulation is first effected on semi-explicit index-1 differential-algebraic equation systems, which casts them as pure ordinary differential equation systems subject to an embedded pointwise least-squares problem. This is then formulated as a gradient flow optimization problem. Rigorous proofs for this novel scheme are provided for asymptotic and epsilon convergence. The computational results validate the predictions of the effectiveness of the proposed approach, with efficient and accurate solutions obtained for the case studies considered. Beyond the theoretical and practical value for the solution of DAE systems as pure ODE ones, the methodology is expected to have an impact in similar cases where an ODE system is subjected to algebraic constraints, such as the Hamiltonian necessary conditions of optimality in optimal control problems. Keywords: Differential-algebraic equations; Gradient flow; Semi-explicit index-1; DAE; Ordinary differential equations

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Development of an acetic acid tolerant Spathaspora passalidarum strain through evolutionary engineering with resistance to inhibitors compounds of autohydrolysate of Eucalyptus globulus.

Paulina Morales, Juan Carlos Gentina, Germán Aroca, Solange I. Mussatto. | Industrial Crops and Products. 106 (1): 5-11. | 2017

Evolutionary engineering strategy based on mutagenesis by UV irradiation and subsequent selection by continuous cultivation at increasing concentrations of acetic acid in synthetic medium with glucose and xylose mixtures was used to develop an evolved strain of the yeast Spathaspora passalidarum with improved resistance to acetic acid. After 380 generations, the yeast was able to produce 5.8 g/L ethanol in the presence of 3.5 g/L acetic acid in synthetic medium with mixture of 15 g L−1 glucose and 15 g L−1 xylose. To demonstrate the improved resistance to acetic acid of the evolved strain compared to the native strain, growth kinetics and bioethanol production of both strains in batch cultures under microaerobic condition were performed. The evolved strain reached an ethanol volumetric productivity of 0.23 g/L h and ethanol yield of 0.48 g/g in the presence of 4.5 g/L acetic acid. These results were 7-fold and 2-fold higher than those obtained with the native strain, respectively. Inhibitors composition present in Eucalyptus globulus autohydrolysate were (g L−1): acetic acid, 4.7; furfural, 1.0; HMF, 0.36; formic acid, 0.6; syringaldehyde, 0.14 and vanillin, 0.017. When Eucalyptus globulus autohydrolysate was used as culture medium, the evolved strain of S. passalidarum showed complete consumption of glucose and cellobiose, and 56% of xylose. In contrast, the wild type strain was unable to completely consume any of these sugars and showed a lag phase of 46 h. In brief, evolutionary engineered strain of S. passalidarum presented an improved resistance to inhibitors usually found in Eucalyptus globulus autohydrolysate and was able to co-ferment glucose, xylose and cellobiose under microaerobic condition without lag phase.

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Constrained NLP via Gradient Flow Penalty Continuation: Towards Self-TuningRobust Penalty Schemes.

Scott, F.; Conejeros, R.; Vassiliadis, V. | Comput. Chem. Eng. 101, 243-258. | 2017

This work presents a new numerical solution approach to nonlinear constrained optimization problems based on a gradient flow reformulation. The proposed solution schemes use self-tuning penalty parameters where the updating of the penalty parameter is directly embedded in the system of ODEs used in the reformulation, and its growth rate is linked to the violation of the constraints and variable bounds. The convergence properties of these schemes are analyzed, and it is shown that they converge to a local minimum asymptotically. Numerical experiments using a set of test problems, ranging from a few to several hundred variables, show that the proposed schemes are robust and converge to feasible points and local minima. Moreover, results suggest that the GF formulations were able to find the optimal solution to problems where conventional NLP solvers fail, and in less integration steps and time compared to a previously reported GF formulation. Keywords: Gradient flow; Nonlinear programming problem; Convergence analysis

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Biodegradation of benzo[α]pyrene, toluene, and formaldehyde from the gas phase by a consortium of Rhodococcus erythropolis and Fusarium solani.

Morales, P.; Cáceres, M.; Scott, F.; Díaz-Robles, L.; Aroca, G.; Vergara-Fernández, A. | Microbiol. Biotechnol. 101, 6765-6777. | 2017

Polycyclic aromatic hydrocarbons (PAHs) and volatile organic compounds (VOCs) are important indoor contaminants. Their hydrophobic nature hinders the possibility of biological abatement using biofiltration. Our aim was to establish whether the use of a consortium of Fusarium solani and Rhodococcus erythropolis shows an improved performance (in terms of mineralization rate and extent) towards the degradation of formaldehyde, as a slightly polar VOC; toluene, as hydrophobic VOC; and benzo[α]pyrene (BaP) as PAH at low concentrations compared to a single-species biofilm in serum bottles with vermiculite as solid support to mimic a biofilter and to relate the possible improvements with the surface hydrophobicity and partition coefficient of the biomass at three different temperatures. Results showed that the hydrophobicity of the surface of the biofilms was affected by the hydrophobicity of the carbon source in F. solani but it did not change in R. erythropolis. Similarly, the partition coefficients of toluene and BaP in F. solani biomass (both as pure culture and consortium) show a reduction of up to 38 times compared to its value in water, whereas this reduction was only 1.5 times in presence of R. erythropolis. Despite that increments in the accumulated CO2 and its production rate were found when F. solani or the consortium was used, the mineralization extent of toluene was below 25%. Regarding BaP degradation, the higher CO2 production rates and percent yields were obtained when a consortium of F. solani and R. erythropolis was used, despite a pure culture of R. erythropolis exhibits poor mineralization of BaP.

Keywords: Biodegradability; Fusarium solani; PAHs; Rhodococcus erythropolis; VOCs.

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A generalized disjunctive programming framework for the optimal synthesis and analysis of processes for ethanol production from corn stover.

Scott, F.; Aroca, G.; Caballero, J.; Conejeros, R. | Bioresour. Technol. 236, 212-224. | 2017

The aim of this study is to analyze the techno-economic performance of process configurations for ethanol production involving solid-liquid separators and reactors in the saccharification and fermentation stage, a family of process configurations where few alternatives have been proposed. Since including these process alternatives creates a large number of possible process configurations, a framework for process synthesis and optimization is proposed. This approach is supported on kinetic models fed with experimental data and a plant-wide techno-economic model. Among 150 process configurations, 40 show an improved MESP compared to a well-documented base case (BC), almost all include solid separators and some show energy retrieved in products 32% higher compared to the BC. Moreover, 16 of them also show a lower capital investment per unit of ethanol produced per year. Several of the process configurations found in this work have not been reported in the literature.

Keywords: Biofuels; Process optimization; Solid-liquid separation; Techno-economic analysis.

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ZrO2 -Supported Alkali Metal (Li, Na, K) Catalysts Biodiesel Production.

Aguila, G.; Salinas, D.; Jiménez, R.; Guerrero, S.; Araya, P. | Journal of Chilean Chemical Society. | 2016


Technical and Economic Analysis of Industrial Production of Lactose-Derived Prebiotics With Focus on Galacto-Oligosaccharides

Scott, F.; Vera, C.; Conejeros, R. | Lactose-Derived Prebiotics, A Process Perspective. | 2016

Galactooligosaccharides (GOS) are the most relevant prebiotics synthesized from lactose. During the last decades, a number of processes have been reported for its industrial production using β-galactosidase as catalyst. However, economic and technical analyses are seldom published. This chapter analyzes a number of processes for GOS production considering two sources of β-galactosidase and several purification strategies from a technical and economic point of view. Among the purification alternatives, simulated moving bed chromatography and removal of unwanted mono and disaccharides by bioconversion with yeast are included. Process alternatives are compared within a common price framework using the minimum product selling price. Results show that the calculated minimum selling prices are well below the market prices for GOS, thus leaving room for marketing and distribution costs. Furthermore, the integration of GOS production to an existing dairy industry is analyzed focusing in plant capacity, installed equipment and market lactose and whey prices. Keywords: Investment costs; Operational costs; Prebiotics minimum selling price; Prebiotics techno-economic analysis; Selective fermentations; Simulated moving bed chromatography

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Potassium titanate for the production of biodiesel.

Salinas, D.; Guerrero, S.; Cross, A.; Araya, P.; Wolf, E. | Fuel. 166: 237-244. | 2016

The temperature effect and basic structural features of a potassium catalyst supported on hydrothermal TiO2 were studied. The calcination of a 20%K/TiHT catalyst at temperatures higher than 600 °C, led to a change of the crystalline phase of potassium oxide into a potassium titanate. Despite the low surface area of the catalyst calcined at high temperature total conversion to methyl esters was achieved at 2 h of reaction. These results are explained by the presence of highly strong basic sites associated with the potassium titanate structure formed on these catalysts. Keywords: TiO2; Potassium oxide; Potassium titanate; Transesterification; Canola oil

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Highly active Rb/Cu/YCeO2 catalyst for the storage of nitric oxide under lean conditions.

Bormann, C.; Rodríguez, N.; Araya, P.; Guerrero, S. | Catalysis Communications. 76: 76-81. | 2016

A novel Pt-free Rb/Cu/YCeO2 catalyst was applied to the adsorption of NO under oxidizing conditions. The results show a much greater performance of this catalyst relative to a Pt/Ba/Al2O3 catalyst. The results suggest that the presence of copper promotes the oxidation of NO to NO2, with the latter molecules being readily adsorbed. Infrared experiments show a variety of nitrate/nitrites on the catalyst surface under reaction conditions. The addition of Rb resulted in copper being more resistant to reduction. The copper phase remained highly dispersed even after the addition of Rb. Keywords: NO adsorption; Copper; CeO2; Y-CeO2; Rb/Cu/CeO2; Rb/Cu/Y-CeO2

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Elucidating the key role of the fungal mycelium on the biodegradation of n-pentane as a model hydrophobic VOC.

Vergara, A.; Scott, F.; Moreno, P.; Díaz, L.; Muñoz, R. | Chemosphere. 157: 89-96. | 2016

The role of the aerial mycelium of the fungus Fusarium solani in the biodegradation of n-pentane was evaluated in a continuous fungal bioreactor (FB) to determine the contribution of the aerial (hyphae) and non-aerial (monolayer) fungal biomass. The experimental results showed that although the aerial biomass fraction represented only 25.9(±3)% on a dry weight basis, it was responsible for 71.6(±4)% of n-pentane removal. The FB attained a maximum elimination capacity (ECmax) of 680(±30) g m−3 h−1 in the presence of fungal hyphae (which supported an interfacial area of 5.5(±1.5) × 106 m2 m−3). In addition, a mathematical model capable of describing n-pentane biodegradation by the filamentous fungus was also developed and validated against the experimental data. This model successfully predicted the influence of the aerial biomass fraction and its partition coefficient on the n-pentane removal, with EC decreasing from 680(±30) g m−3 h−1 to values of 200(±14) g m−3 h−1 when the dimensionless partition coefficient increased from 0.21(±0.09) with aerial biomass to 0.88(±0.06) without aerial biomass. Keywords: Fungal biofilter; Hydrophobic VOCs; Biofilter modeling; Aerial mycelium; Fusarium solani

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A Note on the Log-Alpha-Skew-Normal Model with Geochemical Applications.

Venegas, O.; Bolfarine, H.; Gallardo, D.; Vergara, A.; Gómez, H. | Applied Mathematics & Information Sciences. 10, No. 5, 1697-1703. | 2016

In this paper we introduce an extension of the log-normal distribution, based on the alpha-skew-normal distribution introduced by Elal-Olivero [10]. Basic properties, moments, moment estimators, maximum likelihood estimators and a simulation study are discussed. We apply the approach developed in this paper to data sets related to neodymium and nickel concentrations in soil samples. Model fit indicates good performance of the proposed model when compared with less flexible models. Keywords: Alpha-skew-normal distribution, Bimodality, Log-normal distribution

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Short term health effects of particulate matter: A comparison between wood smoke and multi-source polluted urban areas in Chile.

Díaz-Robles, L.; Cortés, S. ; Vergara-Fernández, A. ; Carlos Ortega, J. | Aerosol and Air Quality Research. Vol 15, 306-318. | 2015

Temuco and Pudahuel are two urban areas in Chile that are among the highest in particulate matter (PM10) air pollution in Chile. In fact, Temuco is also classified as one of the most polluted cities in Latin America by the World Health Organization. Both cities show important differences in the sources of this PM10 pollution. For Temuco, a southern city, the main source is the residential wood combustion (RWC), and for Pudahuel, located in the central zone, the main sources are mobile and point sources. The relationship between PM10 air pollution and health effects measured as the daily number of deaths and hospital admissions for cardiovascular and respiratory causes was determined. The Air Pollution Health Effects European Approach (APHEA-2) protocol was followed, and a multivariate Poisson regression model with gam.exact algorithm was fitted for these cities during 2001–2006. The results show that PM10 had a significant association with daily mortality, where the relative risks (RR) for cardio respiratory mortality of the elderly age group was 1.0126 [95% (CI: 1.0004–1.0250)] at Temuco and 1.0086 [95% (CI: 1.0007–1.0165)] for Pudahuel when PM10 increased by 10 µg/m3. For the hospital admissions due to chronic obstructive pulmonary disease (COPD), the RR were 1.0198 [95% (CI: 1.0030–1.0369)] at Temuco and 1.0097 [95% (CI: 1.0000–1.0204)] at Pudahuel. There is evidence in these cities of positive relationships between ambient particulate levels and the rates of mortality and morbidity for cardiovascular and respiratory causes; being the excess risk 47% and 104.1% higher in Temuco than Pudahuel for cardiorespiratory mortality of the elderly population and COPD hospital admissions, respectively. These results demonstrate that there is greater risk when people are exposed to air polluted with wood smoke.

Keywords: Soot; Residential wood combustion; Mortality; Hospital admissions; Time series

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Sensitivity analysis of biodiesel blends on Benzo[a]pyrene and main emissions using MOVES: A case study in Temuco, Chile.

Pino-Cortés, E. L.A. Díaz-Robles, S. G. ; Cubillos, F.; Fu, J.S. ; Vergara-Fernández, A. | SCIENCE OF THE TOTAL ENVIRONMENT. 537: 352-359. | 2015

Temuco is one of the most highly wood-smoke polluted cities in Chile; however, the diesel mobile sources are growing very fast in the past 10 years and so far very few studies have been done. The main goal of this research was to develop a 2013 emission inventory of criteria pollutants and Benzo[a]pyrene (BaP) and to evaluate the use of six biodiesel blends of 0%, 1%, 4%, 8%, 12%, and 20% by volume of fuel in diesel motors from the vehicle fleet within the mentioned areas using the Motor Vehicle Emission Simulator (MOVES). Input parameters for the base year 2005 were estimated to implement and adapt the model in Chile, while results of NOx, PM10, PM2.5, NH3, CO2 equivalent and SO2 were compared with the Chilean Emission Inventory estimated by the model “Methodology for the Calculation of Vehicle Emissions.” The 2013 emissions reduced with respect to 2005, in the majority of the contaminants analyzed, despite the 47% increase in the annual miles traveled. Using biodiesel blends, an emission reduction was estimated at up to 15% in particulate matter, BaP, and CO for the year 2013, as well as an increment of 2% in NOx emissions, attributed to low sulfur content (50 ppm) in the diesel and the antiquity of the vehicle fleet. The results obtained gave evidence of the influence of the biodiesel use in the pollutant emissions to improve the Chilean air quality, as well as providing a strategy for this air quality management. Keywords: MOVES; Mobile sources; Biodiesel; Temuco; Benzo[a]pyrene

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Photocatalytic inhibition of bacteria by TiO2 nanotubes-doped polyethylene composites.

Yanez, D.; Guerrero, S.; Lieberwirth, I.; Zapata, P. | APPLIED CATALYSIS A-GENERAL. 489: 255-261. | 2015

Polyethylene (PE) and polyethylene-octadecene (LLDPE) composites containing titanium dioxide nanotubes were synthesized and applied to the inhibition of selected bacteria. It was found that polymerization rate of the polymerizations increased with the incorporation of the octadecene compared with bare ethylene, while with modified nanotubes (O–TiO2–Ntbs) the catalytic activity showed a slight decrease compared with the pure polymer. Regarding physical properties, the melting temperature and cristallinity of PE was higher than LLDPE. LLDPE presented lower rigidity than PE and thus lower Young’s modulus. On the other hand, with the incorporation of nanotubes, Young’s modulus did not change significantly with respect to PE. After 2 h of contact, the PE/O–TiO2–Ntbs composite showed a reduction of Escherichia coli of 36.7% under no UVA irradiations. In contrast, LLDPE/O–TiO2–Ntbs showed 63.5%. The photocatalytic reduction (under UVA light) was much higher and after 60 min the LLDPE/O-TiO2-Ntbs composites showed a bacterial reduction of 99.9%, whereas the PE/O-TiO2-Ntbs showed 42.6% of catalytic reduction. Keywords: Nanocomposites; Polyethylene; TiO2 nanotubes; Photocatalytic inhibition

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Effects of Temperature on Steam Explosion Pretreatment of Poplar Hybrids with Different Lignin Contents in Bioethanol Production.

San Martin, J.; Ballesteros, M.; Manzanares, P.; Vergara, A. | INTERNATIONAL JOURNAL OF GREEN ENERGY. 12(8): 832-842. | 2015

The aim of this study is to evaluate the effect of the lignin content in four hybrid poplars for enhancing ethanol production. The study was conducted using steam explosion at 200 and 220°C for 5 min as a pre-treatment and then a simultaneous saccharification and fermentation (SSF) process with Saccharomyces cerevisiae. The composition of raw material, liquid, and solid fraction obtained after pretreatment, enzymatic digestion, and ethanol production under the different experimental conditions was analyzed. The best results for bioethanol production were obtained from steam explosion pre-treatment carried out at 220°C with the hybrid poplar H-29, with cellulose recovery of over 63%, enzymatic hydrolysis yield of approximately 67%, and SSF yield of 70% of the theoretical value. However, the highest enzymatic hydrolysis yield (79%) was obtained for the hybrid poplar H-34, which has the lowest lignin content.

Keywords: Hybrid Poplar; Steam explosion; Lignin; Bioethanol; Lignocellulosic biomass

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Effect of hydrothermally synthesized titanium nanotubes on the behaviour of polypropylene for antimicrobial applications.

Zenteno, A.; Guerrero, S.; Ulloa, T.; Maria; Palza, H.; Zapata, P. | POLYMER INTERNATIONAL. 64(10): 1442-1450. | 2015

TiO2 nanotubes (TiO2-Ntbs) synthesized by a hydrothermal method were used as filler to prepare polypropylene (PP) composites by melt blending. Their structural properties as well as their biocidal potential were studied. Nanotubes were used either as-synthesized or organically modified with hexadecyltrimethoxysilane (Mod-TiO2). These nanoparticles form secondary structures with sizes around 100 nm that are well dispersed in the polymer matrix, but not homogeneously because agglomerates larger than 1 µm are also seen by transmission electron microscopy. Regarding the properties of the composites, the incorporation of the nanoparticles increased the polymer’s crystallinity and thermal stability. The maximum decomposition temperature of the matrix increased by ca 13 °C compared to virgin PP. The nanotubes further increase the spherulite nucleation density, and therefore a reduction in the diameter of spherulites and an increase in their number were observed. Despite the above, the addition of TiO2 nanoparticles did not modify the mechanical properties of PP. The PP/TiO2-Ntb nanocomposites exposed to UVA radiation showed a biocidal behaviour, reducing a colony of Escherichia coli by 81%. © 2015 Society of Chemical Industry

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Assessing Polycyclic Aromatic Hydrocarbons (PAHs) using passive air sampling in the atmosphere of one of the most wood-smoke-polluted cities in Chile: The case study of Temuco.

Pozo, K.; Estellano, V.; Harner, T.; Diaz-Robles, L.; Cereceda-Baliz, F.; Etcharren, P.; Pozo, K.; Guerrero, F.; Vergara-Fernández. A. | CHEMOSPHERE. 134: 475-481. | 2015

This study addresses human health concerns in the city of Temuco that are attributed to wood smoke and related pollutants associated with wood burning activities that are prevalent in Temuco. Polycyclic Aromatic Hydrocarbons (PAHs) were measured in air across urban and rural sites over three seasons in Temuco using polyurethane foam (PUF) disk passive air samplers (PUF-PAS). Concentrations of ΣPAHs (15 congeners) in air ranged from BDL to ∼70 ng m−3 and were highest during the winter season, which is attributed to emissions from residential heating by wood combustion. The results for all three seasons showed that the PAH plume was widespread across all sites including rural sites on the outskirts of Temuco. Some interesting variations were observed between seasons in the composition of PAHs, which were attributed to differences in seasonal point sources. A comparison of the PAH composition in the passive samples with active samples (gas + particle phase) from the same site revealed similar congener profiles. Overall, the study demonstrated that the PUF disk passive air sampler provides a simple approach for measuring PAHs in air and for tracking effectiveness of pollution control measures in urban areas in order to improve public health.

Keywords: Temuco; PAHs; PUF disk; Wood combustion; Public health

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Photocatalytic inhibition of bacteria by TiO2 nanotubes-doped polyethylene composites

Yañez, D., Guerrero, S., Lieberwirth, I., Ulloa, M.T., Gomez, T., Rabagliati, F.M., Zapata, P.A. | Applied Catalysis A: General | 2015

Polyethylene (PE) and polyethylene-octadecene (LLDPE) composites containing titanium dioxide nanotubes were synthesized and applied to the inhibition of selected bacteria. It was found that polymerization rate of the polymerizations increased with the incorporation of the octadecene compared with bare ethylene, while with modified nanotubes (O–TiO2–Ntbs) the catalytic activity showed a slight decrease compared with the pure polymer. Regarding physical properties, the melting temperature and cristallinity of PE was higher than LLDPE. LLDPE presented lower rigidity than PE and thus lower Young’s modulus. On the other hand, with the incorporation of nanotubes, Young’s modulus did not change significantly with respect to PE. After 2 h of contact, the PE/O–TiO2–Ntbs composite showed a reduction of Escherichia coli of 36.7% under no UVA irradiations. In contrast, LLDPE/O–TiO2–Ntbs showed 63.5%. The photocatalytic reduction (under UVA light) was much higher and after 60 min the LLDPE/O-TiO2-Ntbs composites showed a bacterial reduction of 99.9%, whereas the PE/O-TiO2-Ntbs showed 42.6% of catalytic reduction.

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Sensitivity analysis of biodiesel blends on Benzo[a]pyrene and main emissions using MOVES: A case study in Temuco, Chile

Pino-Cortés E., Díaz-Robles L.A., Cubillos, F., Fu, J.S., Vergara-Fernández, A. | Science of The Total Environment | 2015

Temuco is one of the most highly wood-smoke polluted cities in Chile; however, the diesel mobile sources are growing very fast in the past 10 years and so far very few studies have been done. The main goal of this research was to develop a 2013 emission inventory of criteria pollutants and Benzo[a]pyrene (BaP) and to evaluate the use of six biodiesel blends of 0%, 1%, 4%, 8%, 12%, and 20% by volume of fuel in diesel motors from the vehicle fleet within the mentioned areas using the Motor Vehicle Emission Simulator (MOVES). Input parameters for the base year 2005 were estimated to implement and adapt the model in Chile, while results of NOx, PM10, PM2.5, NH3, CO2equivalent and SO2 were compared with the Chilean Emission Inventory estimated by the model “Methodology for the Calculation of Vehicle Emissions.” The 2013 emissions reduced with respect to 2005, in the majority of the contaminants analyzed, despite the 47% increase in the annual miles traveled. Using biodiesel blends, an emission reduction was estimated at up to 15% in particulate matter, BaP, and CO for the year 2013, as well as an increment of 2% in NOx emissions, attributed to low sulfur content (50 ppm) in the diesel and the antiquity of the vehicle fleet. The results obtained gave evidence of the influence of the biodiesel use in the pollutant emissions to improve the Chilean air quality, as well as providing a strategy for this air quality management.

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Effects of Temperature on Steam Explosion Pretreatment of Poplar Hybrids with Different Lignin Contents in Bioethanol Production

San Martin-Davison, Jessica; Ballesteros, Mercedes; Manzanares, Paloma; Vergara-Fernández A | International Journal of Green Energy | 2015

The aim of this study is to evaluate the effect of the lignin content in four hybrid poplars for enhancing ethanol production. The study was conducted using steam explosion at 200 and 220°C for 5 min as a pre-treatment and then a simultaneous saccharification and fermentation (SSF) process with Saccharomyces cerevisiae. The composition of raw material, liquid, and solid fraction obtained after pretreatment, enzymatic digestion, and ethanol production under the different experimental conditions was analyzed. The best results for bioethanol production were obtained from steam explosion pre-treatment carried out at 220°C with the hybrid poplar H-29, with cellulose recovery of over 63%, enzymatic hydrolysis yield of approximately 67%, and SSF yield of 70% of the theoretical value. However, the highest enzymatic hydrolysis yield (79%) was obtained for the hybrid poplar H-34, which has the lowest lignin content.

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Assessing Polycyclic Aromatic Hydrocarbons (PAHs) using passive air sampling in the atmosphere of one of the most wood-smoke-polluted cities in Chile: The case study of Temuco

Pozo K., Estellano V.H., Harner T., Diaz-Robles L., Cereceda-Baliz F., Etcharren P., Pozo K., Guerrero F., Vergara-Fernández A. | Chemosphere | 2015

This study addresses human health concerns in the city of Temuco that are attributed to wood smoke and related pollutants associated with wood burning activities that are prevalent in Temuco. Polycyclic Aromatic Hydrocarbons (PAHs) were measured in air across urban and rural sites over three seasons in Temuco using polyurethane foam (PUF) disk passive air samplers (PUF-PAS). Concentrations of ΣPAHs (15 congeners) in air ranged from BDL to ∼70 ng m−3 and were highest during the winter season, which is attributed to emissions from residential heating by wood combustion. The results for all three seasons showed that the PAH plume was widespread across all sites including rural sites on the outskirts of Temuco. Some interesting variations were observed between seasons in the composition of PAHs, which were attributed to differences in seasonal point sources. A comparison of the PAH composition in the passive samples with active samples (gas + particle phase) from the same site revealed similar congener profiles. Overall, the study demonstrated that the PUF disk passive air sampler provides a simple approach for measuring PAHs in air and for tracking effectiveness of pollution control measures in urban areas in order to improve public health.

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Effects of urban configuration on the wind energy distribution over a building

errmann-Priesnitz, Benjamin; Calderon-Munoz, Williams R.; LeBoeuf, R. | Journal of Renewable and Sustainable Energy | 2015

A numerical study to investigate the wind energy potential for various building configurations is presented. Steady-state incompressible flow simulations were performed using the finite volume method of ANSYS Fluent with the k-ε turbulence model. A simplified city model was used to study the flow behavior over a building rooftop for various configurations of the upwind structure. Results show an increase of up to 29% in the available energy compared to the free stream due to variations in the dimensions of the separation bubble over the rooftop. This study shows the influence of building configuration on the wind resource near buildings and how it can affect the feasibility of a small-scale wind turbine project.

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Health risks caused by short term exposure to ultrafine particles generated by residential wood combustion: a case study of Temuco, Chile.

Díaz-Robles L.A., Fu J.S., Vergara-Fernández A., Etcharren P., Schiappacasse L.N., Reed G.D., Silva M.P. | Environment International. 66, 174-181. (2014). (ISI-Q1)(7/216) (IF:6.022). | 2014

Temuco is one of the most highly wood smoke polluted cities in Chile; however, there is scarce evidence of respiratory morbidity due to fine particulate matter. We aimed to estimate the relationship between daily concentration of ultrafine particles (UFP), with an aerodynamic diameter ≤ 0.1 μm, and outpatient visits for respiratory illness at medical care centers of Temuco, Chile, from August the 20th, 2009 to June the 30th, 2011. The Air Pollution Health Effects European Approach (APHEA2) protocol was followed, and a multivariate semi-parametric Poisson regression model was fitted with GAM techniques using R-Project statistical package; controlling for trend, seasonality, and confounders. The daily UFP were measured by a MOUDI NR-110 sampler. We found that results of the statistical analyses show significant associations between UFP and respiratory outpatient visits, with the elderly (population ≥ 65 years), being the group that presented the greatest risk. An interquartile increase of 4.73 μg/m3 in UFP (lag 5 days) was associated with respiratory outpatient visits with a relative risk (RR) of 1.1458 [95% CI (1.0497–1.2507)] for the elderly. These results show novel findings regarding the relevance of daily UFP concentrations and health risk, especially for susceptible population in a wood smoke polluted city. Keywords: Ultrafine particles; Residential wood combustion; Relative risk; APHEA2; Temuco; Chile

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Effect of initial substrate/inoculum ratio on cell yield in the removal of hydrophobic VOCs in fungal biofilters.

Vergara, A.: San Martín, J.; L.Díaz-R.; Soto, O. | Rev. Mex. Ing. Qca. Vol. 13, No 3, 749-755. (2014). (ISI-Q3)(80/133)(IF: 0.948). | 2014

Different kinetic models have been proposed to describe the elimination of hydrophobic volatile organic compounds (VOCs) by fungal biofiltration. In this process the ratio of the initial substrate concentration (Cpb0) to the initial biomass (X0) has been shown to influence the cell yield. This papers presents a study of the efect of the Cpb0/X0 ratio on observed cell yield (Yobs) in a fixed bed batch system (microcosm) using a gaseous carbon source, as an approximation to its application in the fungal biofiltration of hydrophobic VOCs. Essays were carried out in fixed-bed microcosms using the filamentous fungus Fusarium solani as a biological agent and n-pentane as a carbon and energy source. The results indicated that Yobs in the gas phase is inversely proportional to the Cpb0/X0 ratio, with values of 0.9 to 0.35 gbiomass g-1pentane being obtained when the Cpb0/X0 ratio is changed from 0.1 to 1.0 gpentane g-1biomass. The results indicate that more than 60% of n-pentane was consumed due to energy spilling, and that strong dissociation of catabolism from anabolism occurred at higher Cb0/X0 ratios.

Palabras llave : hydrophobic VOCs; fungal biofiltration; substrate/inoculum ratio; growth yield.

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WGS activity of a novel Cu-ZrO2 catalyst prepared by a reflux 66 method. Comparison with a conventional impregnation method.

Águila, G.; Valenzuela, A.; Guerrero, S.; Araya, P. | Catalysis Communications, 39: 82-85, 2013. | 2014

The activity in the WGS reaction of Cu/ZrO2 catalysts prepared by a method of refluxing in an aqueous NH4OH solution is studied. It is shown that at 3% Cu load the methods of impregnation over monoclinic or tetragonal ZrO2 do not produce active catalysts for the WGS reaction. However, the method of refluxing generates highly active catalysts with Cu loads of 3% (w/w) or higher. The activity of the catalysts prepared by refluxing is associated with the formation of small Cu clusters, which would allow the regrouping of the H atoms to generate molecular H2 in the presence of the crystalline tetragonal ZrO2. Keywords: WGS; Zirconia; Copper

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Wind-driven nearshore sediment resuspension in a deep lake during Winter

Peardon, KE, Bombardelli, FA., Moreno-Casas, PA., Rueda, FJ., Schladow, SG. | Water Resources Research | 2014

Ongoing public concern over declining water quality at Lake Tahoe, California-Nevada (USA) led to an investigation of wind-driven nearshore sediment resuspension that combined field measurements and modeling. Field data included: wind speed and direction, vertical profiles of water temperature and currents, nearbed velocity, lakebed sediment characteristics, and suspended sediment concentration and particle size distribution. Bottom shear stress was computed from ADV-measured nearbed velocity data, adapting a turbulent kinetic energy method to lakes, and partitioned according to its contributions attributed to wind-waves, mean currents, and random motions. When the total shear stress exceeded the critical shear stress, the contribution to overall shear stress was about 80% from wind-waves and 10% each from mean currents and random motions. Therefore, wind-waves were the dominant mechanism resulting in sediment resuspension as corroborated by simultaneous increases in shear stress and total measured sediment concentration. The wind-wave model STWAVE was successfully modified to simulate wind-wave-induced sediment resuspension for viscous-dominated flow typical in lakes. Previous lake applications of STWAVE have been limited to special instances of fully turbulent flow. To address the validity of expressions for sediment resuspension in lakes, sediment entrainment rates were found to be well represented by a modified 1991 García and Parker formula. Last, in situ measurements of suspended sediment concentration and particle size distribution revealed that the predominance of fine particles (by particle count) that most negatively impact clarity was unchanged by wind-related sediment resuspension. Therefore, we cannot assume that wind-driven sediment resuspension contributes to Lake Tahoe’s declining nearshore clarity.

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Effect of initial substrate/inoculum ratio on cell yield in the removal of hydrophobic VOCs in fungal biofilters

Vergara-Fernández A., J. San Martín-Davison, L. Díaz-Robles, O. Soto-Sánchez | Revista Mexicana de Ingeniería Química | 2014

Different kinetic models have been proposed to describe the elimination of hydrophobic volatile organic compounds (VOCs) by fungal biofiltration. In this process the ratio of the initial substrate concentration (Cpb0) to the initial biomass (X0) has been shown to influence the cell yield. This papers presents a study of the efect of the Cpb0/X0 ratio on observed cell yield (Yobs) in a fixed bed batch system (microcosm) using a gaseous carbon source, as an approximation to its application in the fungal biofiltration of hydrophobic VOCs. Essays were carried out in fixed-bed microcosms using the filamentous fungus Fusarium solani as a biological agent and n-pentane as a carbon and energy source. The results indicated that Yobs in the gas phase is inversely proportional to the Cpb0/X0 ratio, with values of 0.9 to 0.35 gbiomass g-1pentane being obtained when the Cpb0/X0 ratio is changed from 0.1 to 1.0 gpentane g-1biomass. The results indicate that more than 60% of n-pentane was consumed due to energy spilling, and that strong dissociation of catabolism from anabolism occurred at higher Cb0/X0 ratios.


Quantitative goals for large-scale fog collection projects as a sustainable fresh water resource in northern Chile

LeBoeuf, R. L., De la Jara, E. | Water International | 2014

The objective of this study was to determine the quantitative goals for a large-scale fog collection project if it were to be an economically competitive source of freshwater in northern Chile. When the initial costs are factored in, the cost of water from such a project would exceed the market price of the alternatives. However, given current costs, the project could be profitable given an average collection rate of about 10 litres per day per square metre. Investment in site selection and system improvements to reduce costs and improve collection rates are essential for making large-scale fog collection an economically competitive source of freshwater.

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Producción Limpia y Núcleos para la Sustentabilidad Territorial NEST: un modelo Chileno para acuerdos voluntarios

Consejo Nacional de Producción Limpia | Consejo Nacional de Producción Limpia, Santiago-Chile. | 2014


Effect of the preparation method and calcination temperature on the oxidation activity of CO at low temperature on CuO-CeO2/ SiO2 catalysts.

Águila, G.; Guerrero, S.; Araya, P. | Applied catalysis A: General: 462-463, 56-63, 2013. | 2013

The effect of preparation method, either coimpregnation or sequential impregnation, and of calcination temperature (between 500 °C and 700 °C) of CuO–CeO2/SiO2 catalysts on the CuO–CeO2 interface and on their activity in the oxidation of CO with O2 at low temperatures is studied. The catalysts are characterized by BET, XRD, TPR and UV–vis DRS. The results show that the preparation method has a substantial effect on the kind of CuO species formed on the surface. At calcination temperatures in the 500–600 °C range, coimpregnation leads to the formation only of Cu species that interact strongly with CeO2, while sequential impregnation leads also to the formation of bulk CuO species that do not interact, or interact weakly, with CeO2. In the case of sequential impregnation the concentration of the different CuO and CeO2 species and of the sites on the interface depends on the impregnation sequence of the support with the precursors of the oxides of both metals. On the other hand, the activity of the catalysts in the oxidation of CO at low temperatures (less than 180 °C) does not differ substantially with the preparation method, provided the calcination temperature remains in the 500–600 °C range. If the catalysts are calcined at 700 °C, the CuO–CeO2 interface, and therefore the activity of the catalysts, is strongly dependent on the preparation method and on the impregnation sequence of both oxides. Using sequential impregnation, impregnating first with the Ce precursor, produces a catalyst whose activity is substantially higher than that of the catalysts prepared by the other methods after calcining at 700 °C. Keywords: Catalysts; Copper; Ceria; Silica; CO oxidation

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Study of potassium supported TiO2 Catalysts for the production of biodiesel.

D.Salinas, S. Guerrero, P. Araya. | Applied Catalysis B, volumen 117-118, pages 260-267. | 2012

A hydrotreated TiO2 supported potassium catalyst, K/TiHT, was studied on the transesterification reaction of canola oil for the production of biodiesel. It was found that the calcination at different temperatures led to the transformation of the supported potassium catalyst into a titanate form of oxide. This was accompanied by a substantial increase in activity. Leaching studies found that although some potassium and titania was left in the products, the reaction mainly occurred in heterogeneous conditions. The contribution of the leached components to the activity was only minor. The recovered catalyst was then used in successive reactions producing stable conversions. A maximum conversion was achieved with the catalyst calcined at 700 °C. Optimum reaction conditions were obtained when using a catalyst loading of 6% (w/w), a methanol to oil ratio of 54:1, and a temperature of reaction of 55 °C. Keywords: Heterogeneous transesterification; Biodiesel; Canola oil; Potassium; TiO2

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Study of Na/Cu/TiO2 catalysts for the storage and reduction of NO.

Guerrero, S.; Guzmán, I.; Águila, G.; Chornik, B.; Araya, P. | Applied Catalysis B: Environmental: 123- 124, 282-295, 2012. | 2012

A Pt-free system based on Na/Cu/TiO2 catalysts was used to study the adsorption of NO under lean conditions. The results show that the NO adsorption activity dramatically increased when both sodium and copper are in intimate contact. Although copper is the active phase in the oxidation of NO to NO2, it was found that the addition of sodium species is of vital importance on the subsequent adsorption of NO2, which mainly occurs on the surface of the alkali in the form of nitrates and nitrites. It was found that a loading increase of the alkali led to an increase in the reduction temperature of the copper phase, which is ascribed to a close interaction between the copper and the sodium phases. Among the Na loadings that were studied, the addition of 5% Na gave the optimum adsorption of NO. After successive cycles of adsorption, the catalysts were fully regenerated at temperatures higher than 250 °C using either CO or H2 as a reducing agent. Keywords: NO oxidation; NO storage; NO reduction; NSRCu/TiO2Na/Cu/TiO2; Cu H2-TPR

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Lean NO adsorption on copper catalysts supported on ceria and promoted with sodium.

S. Guerrero, I. Guzmán, G. Aguila, P. Araya | Catalysis Communications, volume 28, pages 183-190. | 2012

The simultaneous presence of sodium and copper on novel Na/Cu/CeO2 and Na/Cu/CeY catalysts resulted in a dramatic increase in the catalytic adsorption of NO. Copper catalyzes the oxidation of NO to NO2, which is further adsorbed by the sodium phase. The intimate contact of both phases favors the formation of nitrates on the surface. The cooperative effect between the copper and sodium phases increases the reduction temperature of copper. It was found that the addition of copper induced a stabilizing effect on the surface area of the catalysts. Keywords: NO adsorption; NO oxidation; CeO2; CeO2-Y; Na/Cu/CeO2; Na/Cu/CeO2-Y

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Encouraging Sustainable Energy in the Developing World

Westenenk, Nicolás | Science in the News, Harvard University, available online | 2012


Kinetic Monte Carlo Simulation of the Preferential Oxidation of CO using Normally-Distributed Rate Probabilities .

S. Guerrero, E.E. Wolf. | Chemical Engineering Science, volume 66, pages 4477-4487. | 2011

This study presents results from a Kinetic Monte Carlo (KMC) simulation of the catalytic preferential oxidation of CO reaction (PROX) on 3D Pt crystallites. A new method of constructing normal distributions of event probabilities is presented based on the log transformation of calculated kinetic rates (log-KMC). This method allows for solving problems where the time scales of particular events are very different (stiff problems) and it was applied to the simulation of the PROX reaction on supported Pt catalysts to probe the experimental results on a catalyst with different crystallite sizes. It was found that the simulation replicated the trends from experimental results when it was assumed that the limiting step of the PROX reaction was oxygen adsorption. Lower Pt dispersions gave place to catalysts showing higher turnover frequencies, or TOF, which is due to large crystallites having lower numbers of less active base sites. This limiting effect is simulated in larger crystallite sizes with more available sites on (1 1 1) faces. Keywords: Monte Carlo; Stiff problems; Heterogeneous catalysis; Surface reactions; PROX reaction; Crystallite size effects

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Transesterification of Canola Oil on Potassium-supported TiO2 Catalysts.

D. Salinas, S. Guerrero, P. Araya. | Catalysis Communications, volume 11, pages 773-777. | 2010

The transesterification reaction of canola oil was studied on titania-supported catalysts with varying loadings of potassium. It was found that the most active catalysts fall in the range where the adsorption/desorption of CO2 was the highest. Total conversion to methyl esters was achieved on a catalyst with 20% K-loading under air conditions and with no in situ pre-treatment before reaction. Keywords: Heterogeneous transesterification; Biodiesel; Canola oil; Potassium; TiO2

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Study of CuO-CeO2 Catalysts supported on SiO2 on the Low-Temperature Oxidation of CO.

J. Astudillo, G. Aguila, S. Guerrero, P. Araya. | Applied Catalysis A, volume 381, pages 169-176. | 2010

A study was made on the effect of the Cu/Ce ratio and on the total load of both metals on the oxidation activity of CO with O2 using SiO2 as support. It was found that the optimum Cu/Ce ratio for a constant total load of 10% on silica (Aerosil 200) was 0.43 (w/w), which corresponded to a catalyst with 3% Cu and 7% Ce. For that ratio the highly dispersed CuO–CeO2 interface was maximized. The catalyst’s activity increased with increasing the total Cu–Ce load, but it reached a maximum above which the activity kept constant due to a similar concentration of sites at the CuO–CeO2 interface. The higher surface area of the support led to a increase of CuO particles interacting with CeO2 and to a decrease of bulk CuO species not interacting with CeO2. The highly dispersed CuO–CeO2 interface was not affected by a higher available surface area explaining the similar activity in supports with different surface area.

Graphical abstract

SiO2-supported CuO–CeO2 catalysts were studied in the low-temperature oxidation of CO. The optimum Cu/Ce ratio was found for a catalyst with 3% Cu and 7% Ce. The latter catalyst is able to maximize the available CuO–CeO2 interface, which is the active phase in the oxidation of CO. Keywords: CO oxidation; CuO; CeO2; SiO2; Supported catalysts

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Paralell reactor activity studies of the preferential oxidation of CO on transition metals supported on TiO2 and TiO2 nanotubes.

S. Guerrero, M. Di Serio, R.F. Li, E.E. Wolf. | Catalysis Letters, volume 130, number 1-2, pages 19-27. | 2009

The preferential oxidation of carbon monoxide in the presence of hydrogen (PROX reaction) was studied on Cu catalysts promoted with Fe, Nb, Ce, and Ni supported on TiO2 and on TiO2 nanotubes. The surface area of the untreated TiO2 anatase (150 m2/g) support was increase to 350 m2/g when transformed into TiO2 nanotubes (NT). XRD and SEM results confirm the formation of nanotubular structures responsible of the increase in BET surface area. The activity results indicate that a 10% Cu/5% Nb/TiO2-NT catalyst is highly active for this reaction compared to other transition metals and with a catalyst with the same composition supported on untreated TiO2. We found close to 80% CO conversion and 40% selectivity to CO2 formation at 170 °C. The higher activity is ascribed to a higher dispersion of Cu on the TiO2 NT structures.

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In-situ EXAF and FTIR studies of the promotion behavior of Pt-Nb2O5/Al2O3 catalysts during the preferential oxidation of CO.

S. Guerrero, J.T. Miller, E.E. Wolf | Journal of Catalysis, volume 262, pages 102-110. | 2009

The promotional effect of Nb to Pt/Al2O3 supported catalysts during the preferential oxidation of CO (PROX) was studied using various spectroscopic techniques. Addition of small amounts of Nb (<5%) stabilizes 40% of the loaded platinum as Pt2+, which remains oxidized even after reduction treatments. This Nb-promoted catalyst is very active and selective for the PROX reaction. On Pt/Nb2O5 and at high Nb loading for the Pt/Nb/Al2O3 catalysts, the selectivity to CO2 decreases and the selectivity for H2 oxidation increases opposite to the selectivity observed at low Nb loadings. The increase CO2 selectivity due to Nb promotion is ascribed to the inhibition of CO at low temperature which decreases hydrogen oxidation. Operando FTIR results indicate the presence of adsorbed CO as well as carbonates, bicarbonates and formates during the PROX reaction. An IR band at 968 cm−1 indicates the presence of Nbdouble bondO moieties at low Nb loadings. At higher Nb loadings, IR suggests the formation of three-dimensional Nb2O5 aggregates. The surface of the Nb containing catalysts is complex containing reduced and oxidized Pt which is modified by NbOx species either surrounding the Pt crystallites or decorating them.

Graphical abstract

XANES results of the Pt/Nb/Al2O3 catalysts under CO (A) and PROX (B) reaction conditions suggest that their surface is complex, containing reduced and oxidized Pt, which is modified by NbOx species either surrounding the Pt crystallites or decorating them.

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Characterization and oxidation states of Cu and Pd in Pd-CuO/ZnO/ZrO2 catalysts for hydrogen production by methanol partial oxidation.

S. Schuyten, S. Guerrero, J.T. Miller, T. Shibata, E.E. Wolf. | Applied Catalysis A, volume 352, pages 133-144. | 2009

Copper and zinc oxide based catalysts prepared by coprecipitation were promoted with palladium and ZrO2, and their activity and selectivity for methanol oxidative reforming was measured and characterized by N2O decomposition, X-ray absorption spectroscopy, BET, X-ray photoelectron spectroscopy, X-ray diffraction, and temperature programmed reduction. Addition of ZrO2 increased copper dispersion and surface area, with little effect on activity, while palladium promotion significantly enhanced activity with little change of the catalytic structure. A catalyst promoted with both ZrO2 and palladium yielded hydrogen below 150 °C. EXAFS results under reaction conditions showed that the oxidation state of copper was influenced by palladium in the catalyst bulk. A palladium promoted catalyst contained 90% Cu0, while the copper in an unpromoted catalyst was 100% Cu1+ at the same temperature. Palladium preferentially forms an unstable alloy with copper instead of zinc during reduction, which persists during reaction regardless of copper oxidation state. A 100-h time on stream activity measurement showed growth in copper crystallites and change in copper oxidation state resulting in decreasing activity and selectivity. A kinetic model of the reaction pathway showed that palladium and ZrO2 promoters lower the activation energy of methanol combustion and steam reforming reactions.

Graphical abstract

Copper and zinc based catalysts were promoted with palladium and zirconium. The zirconium promoter increased copper dispersion, while the palladium promoter enhanced copper reducibility under reaction conditions. Upon reduction, palladium was found to form alloys with copper, which was reversible on exposure to air. Deactivated catalyst had a greater fraction of copper as Cu1+ under reaction conditions. Keywords: Methanol; Partial oxidation; Copper; Palladium alloy; X-ray absorption spectroscopy

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Computación

FW-SMOTE: A feature-weighted oversampling approach for imbalanced classification

Sebastián Maldonado, Carla Vairetti, Alberto Fernández, Francisco Herrera

Pattern Recognition, 2022

The Synthetic Minority Over-sampling Technique (SMOTE) is a well-known resampling strategy that has been successfully used for dealing with the class-imbalance problem, one of the most challenging pattern recognition tasks in the last two decades. In this work, we claim that SMOTE has an important issue when defining the neighborhood in order to create new minority samples: the use of the Euclidean distance may not be suitable in high-dimensional settings. Our hypothesis is that the use of a weighted metric that does not assume that all features are equally important could improve performance in the presence of noisy/redundant variables. In this line, we present a novel SMOTE-like method that uses the weighted Minkowski distance for defining the neighborhood for each example of the minority class. This methodology leads to a better definition of the neighborhood since it prioritizes those features that are more relevant for the classification task. A complementary advantage of the proposal is performing feature selection since attributes can be discarded when their corresponding weights are below a given threshold. Our experiments on 42 class-imbalance datasets show the virtues of the proposed SMOTE variant, achieving the best predictive performance when compared with the traditional SMOTE approach and other recent variants on low- and high-dimensional settings, handling issues such as class overlap and hubness adequately without increasing the complexity of the method.

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A Transparency Maturity Model for Government Software Tenders

Jorge Hochstetter, Carla Vairetti, Carlos Cares, Mauricio García Ojeda, Sebastián Maldonado. | IEEE Access 9: 45668-45682. | 2021

Over the last two decades, governments have increased their investment in information technology to improve the use of public resources, using public electronic procurement systems to obtain better prices, better solutions and to show transparency in the procurement process. Public procurement of software development projects is specific acquisitions having specific technical, methodological, and management constraints that make transparency an elusive target. This article proposes a maturity model as a tool to measure tendering transparency when government agencies procure software development. We have used a procedural model to support the design of maturity models along four dimensions: Institutionalization, Software procurement process, Communication, and Accountability. We have defined a five-step model, and we have tested it with real government buyers. The model is supported by an appraisal tool that helps to guide the next steps in the transparency of software acquisitions.

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Time-weighted Fuzzy Support Vector Machines for classification in changing environments

Sebastián Maldonado, Julio López, Carla Vairetti. | Inf. Sci. 559: 97-110. | 2021

The predictive performance of classification methods relies heavily on the nature of the environment, as in the joint distribution of inputs and outputs may evolve over time. This issue is known as dataset shift. Given that most statistical and machine learning techniques assume that the training sample is drawn from the same distribution as the test data used for evaluation, an appreciable amount of researchers and practitioners tend to ignore this issue at the model construction stage. In this paper, we propose a novel Fuzzy Support Vector Machine strategy, in which the traditional hinge loss function is redefined to account for dataset shift. Additionally, we propose a general version of this loss function applying aggregation operators in order to improve performance by dealing with dataset shift via fuzzy logic. Originally developed as linear approaches, our proposals are extended to kernel-based classification for non-linear machine learning. Our methods are able to perform best compared to traditional classifiers in terms of out-of-time prediction using simulated and real-world dataset for credit scoring, confirming the theoretical virtues of our approach.

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Applying the concept of implicit HCI to a groupware environment for teaching ethics

Alvarez, C; Zurita, G.; Baloian, N. | Personal and Ubiquitous Computing. | 2021

Implicit HCI is about computers understanding the intentions and needs of the user and proactively triggering functions or adapting the interface to help users achieve their goals. In ubiquitous learning environments, this could mean that the software and hardware settings make relevant learning material available to students; activate proper learning environments, like collaborative authoring tools and/or chatting spaces; find most suitable peers for collaborative learning; etc., at the right time or place. In this research, we report on an experience in which we added implicit HCI to an existing application that supports ethics education called EthicApp. Successful methodologies supporting ethics education include students discussing real-life or simulated cases where ethical dilemmas are presented. It is important that students actively participate in the discussion in order to develop their key abilities for ethical discernment. EthicApp implements a methodology in which students read about a case that presents an ethical dilemma, report on their personal stance about it, and then discuss their opinions anonymously in a small group, and then with the whole class. We included an automatic mechanism of group formation in order to maximize discussion and active participation among the students. For this, we first compared two strategies of forming groups: one random and another maximizing the differences of individual students’ judgments about the presented case within each group. We found that the second strategy was the most appropriate to encourage participation. As a result, EthicApp was modified in order to implicitly generate groups with diverging ethical judgments.

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A Social Platform for Fostering Ethical Education through Role-Playing

Alvarez, Claudio; Zurita, Gustavo; Hasbún, Beatriz; Peñafiel, Sergio; Pezoa, Álvaro. | Factoring Ethics in Technology, Policy Making and Regulation, IntechOpen, London, UK. | 2021

Nowadays the complexity of knowledge, the specialization of labor and the pervasiveness of ICT in human activity, lead individuals to frequently make complex decisions with ethical implications. The educational system has a fundamental role in preparing specialized human capital in every discipline, however, it also faces the challenge of educating individuals with ethical discernment capabilities and behavior. In this book chapter, we describe the design, implementation and validation of EthicApp-RP, a social platform aimed at higher education settings, for fostering reflection and moral reasoning around ethical cases through a role-playing activity. We present an application of EthicApp-RP involving a cohort of undergraduate business students (N = 85), based on a case in which students play political and public leadership roles in the midst of the COVID-19 crisis. The results indicate that students and teachers acknowledge the learning environment’s capacity to stimulate reflection and argumentation around ethical issues, while providing all students with equal opportunities for participation. In addition, the tool offers high technical and pedagogical usability, based on the Systems Usability Scale and the Pedagogically Meaningful Learning Questionnaire. EthicApp-RP can contribute to the improvement of ethics education, especially in scientific and technological disciplines, wherein students are quantitatively inclined by nature, in spite that ethics, a humanistic subject often foreign to them, must live at the core of their preparation. Keywords: educational technology; social platform; human capital; higher education; ethics education

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Automatic content analysis of student moral discourse in a collaborative learning activity

Alvarez, Claudio; Zurita, Gustavo; Carvallo, Andrés; Ramírez, Pablo; Bravo, Eugenio; Baloian, Nelson. | Lecture Notes in Computer Science vol 12856, pp 3-19, Springer, Cham. | 2021

In most computer supported collaborative learning activities, the teacher monitors and/or reviews data generated by students and groups as they complete the learning tasks, in order to provide guidance and feedback. Without appropriate technological means that support the processes of collection and selection of students’ generated responses, these duties can result in a high cognitive load for teachers, especially if students generate textual, qualitative content that requires real-time reviewing. In this research we deal with EthicApp, a collaborative application in which this problem is apparent, as students analyze a given ethics case individually and in small groups and deliver written judgements in each phase of the activity. We present a solution to the problem, based on enhancing EthicApp’s teacher’s interface with automated content analysis capabilities. This includes a dashboard that automatically displays students’ most relevant contributions, and cluster visualizations that permit identifying groups of students with similar responses to activity tasks. Validation of the approach was based on a dataset comprising 4,366 comments about an academic ethics case, which were written by 520 students divided into 19 class groups. Expert judgement was applied to evaluate content analysis effectiveness at selecting comments that are both meaningful and representative of students’ different views. More than 80% of comment selections were found valuable, according to experts’ analysis. Keywords: CSCL; Automated content analysis; Ethics teaching; Higher education

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Enhancing the classification of Social Media Opinions by Optimizing the Structural Information

Carla Vairetti, Eugenio Martinez Cámara, Sebastián Maldonado, M. Victoria Luzon and Francisco Herrera

Future Generation Computer Systems / ELSEVIER, 2020

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Profit-based Churn Prediction based on Minimax Probability Machines

Sebastián Maldonado, Julio López and Carla Vairetti

European Journal of Operational Research / ELSEVIER, 2020

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Efficient n-gram construction for text categorization using feature selection techniques

Maximiliano García, Sebastián Maldonado, and Carla Vairetti

Intelligent Data Analysis IOS Press, 2020


Collaboration Technologies and Social Computing

Nolte, A., Alvarez, C., Hishiyama, R., Chounta, I. A., Rodríguez-Triana, M. J., & Inoue, T. | Lecture Notes in Computer Science, vol. 12324. Springer | 2020

No Abstract Available

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Evolution of students’ interaction using a gamified virtual learning environment in an engineering course

Corvalán, B.; Recabarren, M.; Echeverría, A. | Computer Applications in Engineering Education | 2020

Keeping students engaged can improve their learning. Gamification is a technique that has been shown to improve engagement, transferring the positive effects of videogames. However, the mobile games industry has identified that player retention decreases quickly over time, but it is unclear if this decreasing retention pattern transfers to gamification activities. To check if the behavioral engagement was stable over a 14-week engineering course, we gamified an existing virtual learning environment (VLE), conducting an observational study for two semesters. Actions performed by students within the VLE were used to measure behavioral engagement, which allows us to track student behavior weekly. To analyze the gamification effect, we divided user actions into two groups: academic and gamified. The results showed that the gamified actions performed by students in the VLE decreased every week, which was significantly higher than the decrease in academic actions. This shows that the decreasing retention pattern seen in mobile games was also present in this study. These results suggest that, just like in mobile games, to sustain the behavioral engagement over a long period of time in a gamified class, additional modern game-design techniques should be considered.

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A semantic approach for dynamically determining complex composed ser- vice behaviour

C. Vairetti, R. Alarcon and J. Bellido | Journal of Web Engineering – Rinton Press | 2016

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Facilitating Conditions for Successful Adoption of Inter-Organizational Information Systems in Seaports

Carla Vairetti, Rosa G. González-Ramírez, Sebastián Maldonado and Claudio Álvarez

Transportation Research Part A: Policy and Practice / ELSEVIER, 2019

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An Alternative SMOTE Oversampling Strategy for High-dimensional Datasets

Sebastián Maldonado, Julio López and Carla Vairetti

Applied Soft Computing / ELSEVIER, 2019

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Modeling and Analysis of the Port Logistical Business Processes and Categorization of Main Logistics Costs

Carla Vairetti, Rosa González-Ramirez, Luisa Fernanda Spaggiari and Alejandra Gómez Padilla

Women in Industrial and Systems Engineering: Key Advances and Perspectives on Emerging Topics / Springer Book, 2019

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A CSCL Script for Supporting Moral Reasoning in the Ethics Classroom

Álvarez, C.; Zurita, G.; Baloian, N.; Jerez, O., Peñafiel, S. | Nakanishi H., Egi H., Chounta IA., Takada H., Ichimura S., Hoppe U. (eds) Collaboration Technologies and Social Computing. CRIWG+CollabTech 2019. Lecture Notes in Computer Science, vol 11677. Springer | 2019

In many engineering schools around the world, ethics is a compulsory subject. However, teaching ethics in engineering is not a simple duty, as engineering students usually attribute less value to learning ethics than to other subjects. Hereby, we report on our initial efforts towards developing a CSCL script for fostering meaningful ethical discussions among engineering students in the classroom. The script comprises successive phases in which the students conduct ethical judgments individually, in a small group and in a teacher-mediated class group discussion. The process seeks that students cast their judgments without inhibitions, so it maintains students’ anonymity in all phases. A trial with 35 engineering students confirmed that the tool offers a good usability, averaging a 79.9 score in the System Usability Scale (SUS). Furthermore, the trial cohort highlighted the convenience of anonymity when discussing ethical cases. Analysis of student behavior revealed that ethical judgments tend to be stable across the activity. However, judgments changed mostly in groups where more discussion was generated. In the future, we will study whether group composition that maximizes the heterogeneity of the students in the groups according to their individual ethical appraisals increases the likelihood of students varying their ethical judgments, as a result of argumentative and reflexive processes in discussions.

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SAW-Q: A dynamic composition approach of REST services based on queue

Jesús Bellido, Rosa Alarcón, Cesare Pautasso and Carla Vairetti

IEEE Transactions on Services Computing, 2018

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Promoting Active Learning in Large Classrooms: Going Beyond the Clicker

Álvarez, C.; Baloian, N.; Zurita, G.; Guarini, F. | Gutwin C., Ochoa S., Vassileva J., Inoue T. (eds) Collaboration and Technology. CRIWG 2017. Lecture Notes in Computer Science, vol 10391. Springer, Cham | 2017

Teaching and learning in most current university lectures has remained unchanged for centuries and nowadays, large lecture classes are a fact at universities. Technologies such as Classroom Response Systems have been designed to ease the adoption of new pedagogical practice in these contexts; however, these pose technological, economic and pedagogical limitations to teachers, students and institutions. In this paper, we present a feasibility study of a system that allows students to take snapshots of paper-based, handwritten solutions to a given task with their devices, and then converts this input to vector graphics that are automatically hosted in a cloud-based storage service, such as Google Drive. The teacher can then discuss students’ solutions and provide elaborate formative feedback in class. We report on the findings of a feasibility study with engineering students in Chile, which validate the practicality of the approach. After this validation we plan to integrate optical character recognition capabilities in the system, in order to support programming and physics education. Keywords: BYOD; Classroom Response System (CRS); Active learning.

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Aplicación de Just-in-Time Teaching con ABP en cursos de Ingeniería

Recabarren, M.; Alvarez, C. | “Aprendizaje basado en problemas y educación en ingeniería: Panorama latinoamericano”, Eds. Guerra, A., Rodríguez.-Mesa, F., González, F.A., Ramírez, M.C. Alborg Centre for Problem Based Learning in Engineering Science and Sustainability, Albortg University under the auspices of UNESCO. | 2017

Diversos estudios en educación superior han demostrado los efectos positivos en el aprendizaje que derivan del uso de metodologías centradas en el estudiante. Si bien la enseñanza de las ciencias y la ingeniería se han visto beneficiadas por estas metodologías, el proceso de selección y adopción de una nueva metodología de enseñanza debe observar las particularidades del contexto educacional en donde será aplicada. Las habilidades de resolución de problemas son fundamentales en la formación de los ingenieros y en este sentido el Aprendizaje Basado en Problemas (ABP) resulta propicio para que los estudiantes de ingeniería puedan adquirir conocimientos fundamentales y ponerlos en práctica en escenarios realistas de aplicación. Aun así, la integración del ABP ha sido lenta y poco regular en las metodologías de enseñanza de la ingeniería, lo que a juicio de los docentes se debe a barreras principalmente relacionadas al uso de recursos, tanto humanos (tiempo) como de infraestructura. En este trabajo analizamos la implementación de una metodología Just-in-Time Teaching con ABP en dos cursos de ingeniería relacionados con programación computacional. Este análisis comprende un tiempo prolongado de implementación lo que permite estudiar como se comportan las barreras antes descritas en el mediano plazo. Es así como mostramos que una implementación de metodologías de esta índole coordinadas por las autoridades de una institución puede, en el mediano plazo, reducir la dedicación de tiempo del docente y el uso de infraestructura, a su vez que mejora el aprendizaje. Adicionalmente, el análisis de las intervenciones realizadas permite presentar consideraciones relevantes que se deben tener en cuenta al momento del diseño de estas metodologías, no siendo siempre factible transferir en forma íntegra una experiencia positiva de un curso a otro.

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Analysis and improvement of business process models using spreadsheets

Saldivar, J.; Vairetti, C.; Rodríguez, C.; Daniel, F.; Casati, F.; Alarcón, R. | Information Systems. 57: 1-19. | 2016

Software in general is thoroughly analyzed before it is released to its users. Business processes often are not – at least not as thoroughly as it could be – before they are released to their users, e.g., employees or software agents. This paper ascribes this practice to the lack of suitable instruments for business process analysts, who design the processes, and aims to provide them with the necessary instruments to allow them to also analyze their processes. We use the spreadsheet paradigm to represent business process analysis tasks, such as writing metrics and assertions, running performance analysis and verification tasks, and reporting on the outcomes, and implement a spreadsheet-based tool for business process analysis. The results of two independent user studies demonstrate the viability of the approach.

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Kernel Penalized K-means: A feature selection method based on Kernel K-means

Maldonado, Sebastian; Carrizosa, Emilio; Weber, Richard | Information Sciences | 2015

We present an unsupervised method that selects the most relevant features using an embedded strategy while maintaining the cluster structure found with the initial feature set. It is based on the idea of simultaneously minimizing the violation of the initial cluster structure and penalizing the use of features via scaling factors. As the base method we use Kernel K-means which works similarly to K-means, one of the most popular clustering algorithms, but it provides more flexibility due to the use of kernel functions for distance calculation, thus allowing the detection of more complex cluster structures. We present an algorithm to solve the respective minimization problem iteratively, and perform experiments with several data sets demonstrating the superior performance of the proposed method compared to alternative approaches.

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Robust feature selection for multiclass Support Vector Machines using second-order cone programming

Lopez, Julio; Maldonado, Sebastian | Intelligent Data Analysis | 2015

This work addresses the issue of high dimensionality for linear multiclass Support Vector Machines (SVMs) using second-order cone programming (SOCP) formulations. These formulations provide a robust and efficient framework for classification, while an adequate feature selection process may improve predictive performance. We extend the ideas of SOCP-SVM from binary to multiclass classification, while a sequential backward elimination algorithm is proposed for variable selection, defining a contribution measure to determine the feature relevance. Experimental results with multiclass microarray datasets demonstrate the effectiveness of a low-dimensional data representation in terms of performance.


A multi-class SVM approach based on the l1-norm minimization of the distances between the reduced convex hulls

Carrasco, M., López, J., Maldonado, S. | Pattern Recognition | 2015

Multi-class classification is an important pattern recognition task that can be addressed accurately and efficiently by Support Vector Machine (SVM). In this work we present a novel SVM-based multi-class classification approach based on the center of the configuration, a point which is equidistant to all classes. The center of the configuration is obtained from the dual formulation by minimizing the distances between the reduced convex hulls using the l1-norm, while the decision functions are subsequently constructed from this point. This work also extends the ideas of Zhou et al. (2002) [37] to multi-class classification. The use of l1-norm provides a single linear programming formulation, which reduces the complexity and confers scalability compared with other multi-class SVM methods based on quadratic programming formulations. Experiments on benchmark datasets demonstrate the virtues of our approach in terms of classification performance and running times compared with various other multi-class SVM methods.

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Computational Intelligence Challenges and Applications on Large-Scale Astronomical Time Series Databases

Huijse, P. ; Estevez, P.A. ; Protopapas, P. ; Principe, J.C. ; Zegers, P. | IEEE Computational Intelligence Magazine | 2014

Time-domain astronomy (TDA) is facing a paradigm shift caused by the exponential growth of the sample size, data complexity and data generation rates of new astronomical sky surveys. For example, the Large Synoptic Survey Telescope (LSST), which will begin operations in northern Chile in 2022, will generate a nearly 150 Petabyte imaging dataset of the southern hemisphere sky. The LSST will stream data at rates of 2 Terabytes per hour, effectively capturing an unprecedented movie of the sky. The LSST is expected not only to improve our understanding of time-varying astrophysical objects, but also to reveal a plethora of yet unknown faint and fast-varying phenomena. To cope with a change of paradigm to data-driven astronomy, the fields of astroinformatics and astrostatistics have been created recently. The new data-oriented paradigms for astronomy combine statistics, data mining, knowledge discovery, machine learning and computational intelligence, in order to provide the automated and robust methods needed for the rapid detection and classification of known astrophysical objects as well as the unsupervised characterization of novel phenomena. In this article we present an overview of machine learning and computational intelligence applications to TDA. Future big data challenges and new lines of research in TDA, focusing on the LSST, are identified and discussed from the viewpoint of computational intelligence/machine learning. Interdisciplinary collaboration will be required to cope with the challenges posed by the deluge of astronomical data coming from the LSST.

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Feature Selection for Support Vector Machines via Mixed Integer Linear Programming

Maldonado, S., Pérez, J., Labbé, M., Weber, R. | Information Sciences | 2014

The performance of classification methods, such as Support Vector Machines, depends heavily on the proper choice of the feature set used to construct the classifier. Feature selection is an NP-hard problem that has been studied extensively in the literature. Most strategies propose the elimination of features independently of classifier construction by exploiting statistical properties of each of the variables, or via greedy search. All such strategies are heuristic by nature. In this work we propose two different Mixed Integer Linear Programming formulations based on extensions of Support Vector Machines to overcome these shortcomings. The proposed approaches perform variable selection simultaneously with classifier construction using optimization models. We ran experiments on real-world benchmark datasets, comparing our approaches with well-known feature selection techniques and obtained better predictions with consistently fewer relevant features.

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Imbalanced data classification using second-order cone programming Support Vector Machines

Maldonado, S., López, J. | Pattern Recognition | 2014

Learning from imbalanced data sets is an important machine learning challenge, especially in Support Vector Machines (SVM), where the assumption of equal cost of errors is made and each object is treated independently. Second-order cone programming SVM (SOCP-SVM) studies each class separately instead, providing quite an interesting formulation for the imbalanced classification task. This work presents a novel second-order cone programming (SOCP) formulation, based on the LP-SVM formulation principle: the bound of the VC dimension is loosened properly using the l∞-norm, and the margin is directly maximized using two margin variables associated with each class. A regularization parameter C is considered in order to control the trade-off between the maximization of these two margin variables. The proposed method has the following advantages: it provides better results, since it is specially designed for imbalanced classification, and it reduces computational complexity, since one conic restriction is eliminated. Experiments on benchmark imbalanced data sets demonstrate that our approach accomplishes the best classification performance, compared with the traditional SOCP-SVM formulation and with cost-sensitive formulations for linear SVM.

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Alternative Second-Order Cone Programming Formulations for Support Vector Classification

Maldonado, S., López, J. | Information Sciences | 2014

This paper presents two novel second-order cone programming (SOCP) formulations that determine a linear predictor using Support Vector Machines (SVMs). Inspired by the soft-margin SVM formulation, our first approach (ξ-SOCP-SVM) proposes a relaxation of the conic constraints via a slack variable, penalizing it in the objective function. The second formulation (r -SOCP-SVM) is based on the LP-SVM formulation principle: the bound of the VC dimension is loosened properly using the l∞-norm, and the margin is directly maximized. The proposed methods have several advantages: The first approach constructs a flexible classifier, extending the benefits of the soft-margin SVM formulation to second-order cones. The second method obtains comparable results to the SOCP-SVM formulation with less computational effort, since one conic restriction is eliminated. Experiments on well-known benchmark datasets from the UCI Repository demonstrate that our approach accomplishes the best classification performance compared to the traditional SOCP-SVM formulation, LP-SVM, and to standard linear SVM.

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Feature selection for high-dimensional class-imbalanced data sets using support vector machines

Maldonado, S., Weber, R., Famili, F. | Information Sciences | 2014

Feature selection and classification of imbalanced data sets are two of the most interesting machine learning challenges, attracting a growing attention from both, industry and academia. Feature selection addresses the dimensionality reduction problem by determining a subset of available features to build a good model for classification or prediction, while the class-imbalance problem arises when the class distribution is too skewed. Both issues have been independently studied in the literature, and a plethora of methods to address high dimensionality as well as class-imbalance has been proposed. The aim of this work is to simultaneously explore both issues, proposing a family of methods that select those attributes that are relevant for the identification of the target class in binary classification. We propose a backward elimination approach based on successive holdout steps, whose contribution measure is based on a balanced loss function obtained on an independent subset. Our experiments are based on six highly imbalanced microarray data sets, comparing our methods with well-known feature selection techniques, and obtaining a better prediction with consistently fewer relevant features.

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CollPhoto: A Paper + Smartphone Problem Solving Environment for Science and Engineering Lectures

Álvarez, C.; Milrad, M.; Borie, F.; Luna, M. | Yuizono T., Zurita G., Baloian N., Inoue T., Ogata H. (eds) Collaboration Technologies and Social Computing. CollabTech 2014. Communications in Computer and Information Science, vol 460. Springer, Berlin, Heidelberg. | 2014

Recent studies in science and engineering education support that inductive learning activities encouraging active student involvement may improve students’ motivation, development of soft skills and academic performance, compared to traditional lectures. Until recently, several technology-enhanced learning environments have been proposed to facilitate such activities in classrooms. However, these commonly depend on dedicated hardware devices, such as clickers or tablet PCs. Contrastingly, smartphones are being massively adopted by society as these become increasingly powerful and inexpensive. Even so, the use of smartphones as learning tools in lecture halls has still not been widely adopted. In this paper we present CollPhoto, a paper-plus-smartphone environment that supports face-to-face problem solving activities in the classroom. CollPhoto provides the instructor with instant visibility of students’ work, and facilitates him/her conducting discussions, based on a selection of students’ responses. We report on the design and initial validation of CollPhoto in the context of two computer science courses. Keywords: STEM education; face-to-face problem solving; paper-plussmartphone environment

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Collboard: Fostering New Media Literacies in the Classroom through Collaborative Problem Solving Supported by Digital Pens and Interactive Whiteboards

Alvarez, C.; Salavati, S.; Milrad, M.; Nussbaum, M. | Computers and Education, Vol. 63, 368-379. | 2013

Education systems worldwide must strive to support the teaching of a set of New Media Literacies (NMLs). These literacies respond to the need for educating human capital within participatory cultures in a highly technologized world. In this paper, we present Collboard, a constructivist problem solving activity for fostering the development of specific NMLs in classrooms: collective intelligence, distributed cognition and transmedia navigation. Collboard encompasses successive individual and collaborative work phases that prompt active student participation and engagement. It integrates digitally augmented appliances, namely, digital pens as a means to support individual work, and interactive whiteboards as a collaborative knowledge construction space. We report on the conceptual design of Collboard, its different technological and software components, as well as our findings from experiences we conducted in a Swedish school with 12 students from a 7th grade maths class. Findings from the experience provide an indication that Collboard can be well integrated in classroom teaching, and that it can foster the development of collective intelligence, distributed cognition and transmedia navigation in different knowledge domains.

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Implementing collaborative learning activities in the classroom supported by one-to-one mobile computing: A design-based process

Alvarez, C.; Alarcon, R.; Nussbaum, M. | Journal of Systems and Software, 84(11), 1961-1976. | 2011

Mobile devices such as PDAs, smartphones and tablet computers are becoming increasingly popular, setting out opportunities for new ways of communicating and collaborating. Research initiatives have ascertained the potential of mobile devices in education, and particularly, the benefits of incorporating them in the classroom for eliciting collaborative learning and active student participation. However, the development of technology-supported learning environments poses challenges to education researchers, practitioners, and software technologists in creating educational tools that respond to real needs of instructors and learners, meet clearly defined didactic purposes, and are practical for the intended audience. This article reports on a technology for facilitating the implementation of collaborative learning environments in the classroom supported by one-to-one mobile computing. The approach encompasses a framework supporting the design and implementation of the mobile software, and a design-based process that guides interdisciplinary efforts utilizing the framework, towards creating effective pedagogical models based on collaborative learning. The proposed design-based process allowed us to develop pedagogical models that respond to real needs of learners and instructors, where development is grounded on rigorous scientific research, allowing to reuse both knowledge and software, and showing an improvement of the mobile software built based on continuous experimentation and evaluation. A case study illustrating the application of the technology is presented and plans for future research are discussed.

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Comparative study of netbooks and tablet PCs for fostering face-to-face collaborative learning

Alvarez, C.; Brown, C.; Nussbaum, M. | Computers in Human Behavior, 27, 834-844. | 2011

With the recent appearance of netbooks and low-cost tablet PCs, a study was undertaken to explore their potential in the classroom and determine which of the two device types is more suitable in this setting. A collaborative learning activity based on these devices was implemented in 5 sessions of a graduate engineering course of 20 students, most of whom were aged 22–25 and enrolled in undergraduate computer science and information technology engineering programs. Student behavior attributes indicating oral and gesture-based communication were observed and evaluated. Our findings indicate that in the context in which this study was undertaken, tablet PCs strengthen collective discourse capabilities and facilitate a richer and more natural body language. The students preferred tablet PCs to netbooks and also indicated greater self-confidence in expressing their ideas with the tablet’s digital ink and paper technology than with the netbooks’ traditional vertical screen and keyboard arrangement.

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Exploring the feasibility of web form adaptation to users’ cultural dimension scores

Recabarren, M., Nussbaum, M. | User Modeling and User-Adapted Interaction | 2010

With many daily tasks now performed on the Internet, productivity and efficiency in working with web pages have become transversal necessities for all users. Many of these tasks involve the inputting of user information, obligating the user to interact with a webform. Research has demonstrated that productivity depends largely on users’ personal characteristics, implying that it will vary from user to user. The webform development process must therefore, include modeling of its intended users to ensure the interface design is appropriate. Taking all potential users into account is difficult, however, primarily because their identity is unknown, and some may be effectively excluded by the final design. Such discrimination can be avoided by incorporating rules that allow webforms to adapt automatically to the individual user’s characteristics, the principal one being the person’s culture. In this paper we report two studies that validate this option. We begin by determining the relationships between a user’s cultural dimension scores and their behavior when faced with a webform. We then validate the notion that rules based on these relationships can be established for the automatic adaptation of a webform in order to reduce the time taken to complete it. We conclude that the automatic webform adaptation to the cultural dimensions of users improves their performance.

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Exploring the feasibility of web form adaptation to users’ cultural dimension scores

Recabarren, M.; Nusscaum, M. | User Modeling and User-Adaptated Interaction. | 2010

With many daily tasks now performed on the Internet, productivity and efficiency in working with web pages have become transversal necessities for all users. Many of these tasks involve the inputting of user information, obligating the user to interact with a webform. Research has demonstrated that productivity depends largely on users’ personal characteristics, implying that it will vary from user to user. The webform development process must therefore, include modeling of its intended users to ensure the interface design is appropriate. Taking all potential users into account is difficult, however, primarily because their identity is unknown, and some may be effectively excluded by the final design. Such discrimination can be avoided by incorporating rules that allow webforms to adapt automatically to the individual user’s characteristics, the principal one being the person’s culture. In this paper we report two studies that validate this option. We begin by determining the relationships between a user’s cultural dimension scores and their behavior when faced with a webform. We then validate the notion that rules based on these relationships can be established for the automatic adaptation of a webform in order to reduce the time taken to complete it. We conclude that the automatic webform adaptation to the cultural dimensions of users improves their performance.

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Technology as small group face-to-face Collaborative Scaffolding

Nussbaum, M.; Alvarez, C.; Mcfarlane, A.; Gomez, F.; Claro, S.; Radovic, D. | Computers & Education, 52(1), 147-153. | 2009

There is a wealth of evidence that collaboration between learners can enhance the outcomes for all concerned. This supports the theorization of learning as a socio-cultural practice, framed by Vygotsky and developed by other researchers such as Rogoff, Lave and Wenger. However, there is also evidence that working collaboratively may not be a spontaneous response to working in a group, and that teaching learners how to collaborate, and in particular how to work together to negotiate meaning, is a necessary part of the process of learning collaboratively which can enhance outcomes further. A question for the computer supported collaborative learning community then arises as to whether learning to collaborate can be scaffolded through the use of digital tools, and what such tools might look like. This paper reports on the design of a digital system that aims to support the practice of face-to-face collaboration on open-ended tasks. Findings from trials of the system in classrooms in the UK and Chile show that the model is welcomed both by teachers and pupils, and met its objectives of ensuring greater interaction between class members who did not normally work together, and involvement of all individuals in discussion based activities. Keywords: Cooperative/collaborative learning; Improving classroom teaching; Learning environments; Pedagogical issues; Teaching/learning strategies

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Teaching Communication, Interpersonal and Decision-Making Skills in Engineering Courses Supported by Technology.

Álvarez, C.; Nussbaum, M.; Recabarren, M.; Gomez, F.; Radovic, D. | International Journal of Engineering Education. | 2009

Communication, interpersonal and decision-making skills are essential for engineering work and should be explicitly incorporated in engineering curricula. This article reports on the testing of a constructivist, technology-supported collaborative strategy in engineering courses that is aimed at supporting the teaching of regular subject matter as well as fostering the development of students’ communication and social skills. In this strategy, students communicate face-to-face through a social network while supporting their work with handhelds interconnected through a wireless network. Information transfers from the social network to the handheld network and vice versa, meaning that collaborators maintain face-to-face interaction at all times while also being able to obtain and retrieve information. To implement this strategy, a technology tool named CollPad was created and applied in two computer science courses. The qualitative results of the experience show that students found the tool effective in creating an environment that promotes communication, interpersonal and decision-making skills.

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Developing Cognition with Collaborative Robotic Activities

Mitnik, R.; Nussbaum, M.; Recabarren, M. | Educational Technology & Society. | 2009

Cognition, faculty related to perception, imagination, memory, and problem solving, refers to internal mental processes through which sensorial input is acquired, elaborated, used, and stored. One of its importances relies on the fact that it affects in a direct way the learning potential. It has been shown that, even thou cognitive processes develop side by side with biological maturity, this cognitive development can be enhanced by means of mediated learning as signaled by Feuerstein’s Mediated Learning theory. Based on this theory is that we propose an intervention model that addresses school academic issues using technologically assisted small group collaboration, pursuing a dual academic objective: to thrive students’ cognitive processes while addressing school curriculum topics. The purpose, therefore, is to balance the students’ cognitive differences by means of in-school content-filled classroom activities. Our aim is to make use of peer mediation in a real world setting with a virtual construction of it. In this paper, we describe this novel intervention model along with an in-school usage experience. For this, we present an activity designed for high school students, specifically aimed to assist the learning of kinematics, graph interpretation, and graph plotting. In this activity the students work in groups of three, using a robot and wirelessly interconnected Personal Digital Assistants (PDA). By means of a controlled experiment, we show how technologically-supported peer mediation promotes the students’ enrichment of their cognitive processes in each of the different stages of the mental act (input-elaboration- output), favoring communication skills, insight, and reasoning, while also restraining impulsive conduct and trial-and-error answers.

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Collaborative robotic instruction: A graph teaching experience.

Mitnik, R.; Recabarren, M.; Nussbaum, M.; Soto, A. | Computers & Education. | 2009

Graphing is a key skill in the study of Physics. Drawing and interpreting graphs play a key role in the understanding of science, while the lack of these has proved to be a handicap and a limiting factor in the learning of scientific concepts. It has been observed that despite the amount of previous graph-working experience, students of all ages experience a series of difficulties when trying to comprehend graphs or when trying to relate them with physical concepts such as position, velocity and acceleration. Several computational tools have risen to improve the students’ understanding of kinematical graphs; however, these approaches fail to develop graph construction skills. On the other hand, Robots have opened new opportunities in learning. Nevertheless, most of their educational applications focus on Robotics related subjects, such as robot programming, robot construction, and artificial intelligence. This paper describes a robotic activity based on face-to-face computer supported collaborative learning. By means of a set of handhelds and a robot wirelessly interconnected, the aim of the activity is to develop graph construction and graph interpretation skills while also reinforcing kinematics concepts. Results show that students using the robotic activity achieve a significant increase in their graph interpreting skills. Moreover, when compared with a similar computer-simulated activity, it proved to be almost twice as effective. Finally, the robotic application proved to be a highly motivating activity for the students, fostering collaboration among them. Keywords: Face-to-face computer supported collaborative learning; Robotic assisted teaching; Intelligent tutoring systems; Interactive learning environments

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Robust automated multiple view inspection

Pizarro, L.; Mery, D.; Delpiano, R.; Carrasco, M. | Pattern Analysis and Applications. | 2008

Recently, Automated Multiple View Inspection (AMVI) has been developed for automated defect detection of manufactured objects, and the framework was success- fully implemented for calibrated image sequences. How- ever, it is not easy to be implemented in industrial environments because the calibration is a difficult and an unstable process. To overcome these disadvantages, the robust AMVI strategy, which assumes that an unknown affine transformation exists between each pair of uncali- brated images, is proposed. This transformation is esti- mated using two complementary robust procedures: a global approximation of the affine mapping is computed by creating candidate correspondences via B-splines and selecting those which better satisfy the epipolar constraint for uncalibrated images. Then, we use this approximation as initial estimate of a robust intensity-based matching approach, which is applied locally on each potential defect. The result is that false alarms are discarded, and the defects of an industrial object are actually tracked along the un- calibrated image sequence. The method is successful as shown in our experiments on aluminum die castings.

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Cultural divide and the Internet

Recabarren, M.; Nusscaum, M.; Leiva, C. | Computers in Human Behavior. | 2008

The aim of this paper is to study the relationship between culture and Internet usage. In the light of studies showing the existence of subcultures within a country, an experiment was designed and conducted based on the Hofstede cultural model and Tiwana’s expert knowledge model to determine how social differences affect the Internet usage of first-year university students. Data-mining techniques were then used to find relationships between culture and Internet usage. We conclude that abilities and performance relating to Internet use differs among subcultures not only because of the digital divide but also because of cultural differences. We also show that subcultures tend to converge over time when placed in the same context. Keywords: Culture; Human–computer interaction (HCI); User-interface design; Web sites design

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Cultural Illiteracy and the Internet

Recabarren, M.; Nusscaum, M.; Leiva, C. | CyberPsychology & Behavior | 2007

The Internet has created different expectations regarding its possibilities as a tool for including groups that have heretofore been excluded from the modern world. But mere access to information does not necessarily imply correct and effective use of it. Despite the great increase in Internet access in previously excluded areas, expectations of inclusion have not been fulfilled. Research suggests that the effectiveness of Internet use varies among cultures, but all such studies analyze countries as a whole with no further breakdown. Yet it is known that within a given country there co-exist subcultures that differ both in language and social context. This paper presents a study that shows the correlation between different social subcultures and their Internet knowledge.

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Eléctrica

Algorithmic decoding of dense OAM signal constellations for optical communications in turbulence

J. Anguita; J. Cisternas | Optics Express | 2022

We demonstrate an optical detection and decoding strategy to increase the information rate and spectral efficiency of free-space laser communication links affected by turbulence by means of dense orbital angular momentum (OAM) modulation. Using three candidate receiver architectures–based on a Shack-Hartmann sensor, a Mode Sorter, and a complex conjugate projection scheme as a base case–we demonstrate an algorithmic classification system based on the received OAM spectra produced by these architectures. This classification scheme allows low-error-rate data transmission in turbulence using 16-OAM, 32-OAM, and 64-OAM symbol constellations, with OAM states between −20 and 20. We evaluate and compare their performance under weak to strong atmospheric turbulence conditions using an accuracy metric and confusion matrices.

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Algorithmic decoding of dense OAM signal constellations for optical communications in turbulence

J. Anguita; J. Cisternas | 2022

Optics Express

We demonstrate an optical detection and decoding strategy to increase the information rate and spectral efficiency of free-space laser communication links affected by turbulence by means of dense orbital angular momentum (OAM) modulation. Using three candidate receiver architectures–based on a Shack-Hartmann sensor, a Mode Sorter, and a complex conjugate projection scheme as a base case–we demonstrate an algorithmic classification system based on the received OAM spectra produced by these architectures. This classification scheme allows low-error-rate data transmission in turbulence using 16-OAM, 32-OAM, and 64-OAM symbol constellations, with OAM states between −20 and 20. We evaluate and compare their performance under weak to strong atmospheric turbulence conditions using an accuracy metric and confusion matrices.

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Modular Multilevel Series/Parallel Converter for Bipolar DC Distribution and Transmission.

R. Lizana; S. Rivera; Z. Li; A. Dekka; L. Rosenthal; H. Bahamonde; A. V. Peterchev; S. M. Goetz. | IEEE Journal of Emerging and Selected Topics in Power Electronics | 2021

This article proposes a novel bipolar-type dc system suitable for both distribution and transmission systems based on modular multilevel series/parallel converters (MMSPCs). The system features decoupled operations of each pole of the bipolar system, being able to operate in both asymmetrical and regenerative modes. This enables two independent dc systems by using a single grid-tied converter. The MMSPC is based on a three-switch cell configuration and enables a simple balancing mechanism in combination with a wide range of output voltage frequencies. The simple balancing mechanism is the key to enable the dc operation and lead to simpler scalability for different voltage levels. Theoretical studies and experimental results are provided to verify and characterize the proposed system.

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Electric Vehicle Charging Infrastructure: From Grid to Battery

S. Rivera; S. Kouro; S. Vázquez; S. M. Goetz; R. Lizana F.; E. Romero-Cavadal | IEEE Industrial Electronics Magazine | 2021

Electrification has been a key component of technological progress and economic development since the industrial revolution. It has improved living conditions, spurred innovation, and increased efficiency across all sectors of our economy and all aspects of our lives. During the coming decades, electrification is expected to reach further and deeper into the transportation, building, and industry sectors, mainly motivated by the energy transition to a zero-carbonemission-based economy to mitigate climate change.

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Decentralized Coordinated Cyber-Attack Detection and Mitigation strategy in DC Microgrids based on Artificial Neural Networks

M. Reza; S. Sahoo; S. Rivera; T. Dragičević; F. Blaabjerg | IEEE Journal of Emerging and Selected Topics in Power Electronics | 2021

DC microgrids can be considered as cyber-physical systems (CPSs) and they are vulnerable to cyberattacks. Therefore, it is highly recommended to have effective plans to detect and remove cyberattacks in dc microgrids. This article shows how artificial neural networks can help to detect and mitigate coordinated false data injection attacks (FDIAs) on current measurements as a type of cyberattacks in dc microgrids. FDIAs try to inject the false data into the system to disrupt the control application, which can make the dc microgrid shutdown. The proposed method to mitigate FDIAs is a decentralized approach and it has the capability to estimate the value of the false injected data. In addition, the proposed strategy can remove the FDIAs even for unfair attacks with high domains on all units at the same time. The proposed method is tested on a detailed simulated dc microgrid using the MATLAB/Simulink environment. Finally, real-time simulations by OPAL-RT on the simulated dc microgrid are implemented to evaluate the proposed strategy.

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Bipolar DC Power Conversion: State-of-the-Art and Emerging Technologies

Rivera, S.; Lizana, R.; Kouro, S.; Dragicevic, T.; Wu, B. | IEEE Journal of Emerging and Selected Topics in Power Electronics | 2021

This article provides a detailed analysis of the power electronics solutions enabling bipolar dc grids. The bipolar dc grid concept has proven to be more efficient, flexible, and higher in quality than the conventional unipolar one. However, despite its many features, these systems still have to overcome their issues with asymmetrical loading to avoid voltage imbalances, besides meeting regulatory and safety requirements that are still under development. Advances in power electronics and the large-scale deployment of dc consumer appliances have put this growing architecture in the spotlight, as it has drawn the attention of different research groups recently. The following provides an insightful discussion regarding the topologies that enable these architectures and their regulatory requirements, besides their features and level of development. In addition, some future trends and challenges in the further development of this technology are discussed to motivate future contributions that address open problems and explore new possibilities.

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Singular Warped Beams Controlled by Tangent Phase Modulation.

Funes, G.; Peters, E.; Anguita, J. | Photonics 8 (8), 343. | 2021

We analyze the effect of spatial phase modulation using non-linear functions applied to singular warped beams to control their topological states and intensity distribution. Such beams are candidates for optical trapping and particle manipulation for their controllable pattern of intensities and singularities. We first simulate several kinds of warped beams to analyze their intensity profiles and propagation characteristics. Secondly, we experimentally validate the simulations and investigate the far-field profiles. By calculating the intensity gradients, we describe how these beams are qualified candidates for optical manipulation and trapping.

Keywords: optical vortices; spatial light modulators; singular beams

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Method for measurement of collagen monomer orientation in fluorescence microscopy.

Rodrigo P Alzola, Seyed Mohammad Siadat, Anuj Gajjar, Rickard Stureborg, Jeffrey W Ruberti, Jose Delpiano, Charles A DiMarzio. | Journal of Biomedical Optics 26(7) 076501 1-12. | 2021

Significance: Collagen is the most abundant protein in vertebrates and is found in tissues that regularly experience tension, compression, and shear forces. However, the underlying mechanism of collagen fibril formation and remodeling is poorly understood.

Aim: We explore how a collagen monomer is visualized using fluorescence microscopy and how its spatial orientation is determined. Defining the orientation of collagen monomers is not a trivial problem, as the monomer has a weak contrast and is relatively small. It is possible to attach fluorescence tags for contrast, but the size is still a problem for detecting orientation using fluorescence microscopy.

Approach: We present two methods for detecting a monomer and classifying its orientation. A modified Gabor filter set and an automatic classifier trained by convolutional neural network based on a synthetic dataset were used.

Results: By evaluating the performance of these two approaches with synthetic and experimental data, our results show that it is possible to determine the location and orientation with an error of ∼37  deg of a single monomer with fluorescence microscopy.

Conclusions: These findings can contribute to our understanding of collagen monomers interaction with collagen fibrils surface during fibril formation and remodeling.

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Partial-Power Converter Topology of Type II for Efficient Electric-Vehicle Fast Charging.

Rivera, S.; Rojas, J.; Kouro, S.; Lehn, P. W.; Lizana, R.; Renaudineau, H.; Dragicevic, T. | IEEE Journal of Emerging and Selected Topics in Power Electronics. | 2021

The increasing power levels handled by electric vehicle dc fast chargers will impose additional challenges to the switching devices in order to cope with the efficiency requirements. A cost-effective alternative to achieve highly efficient power conversion is through the partial-power conversion concept. This paper validates the advantages of a step-down Type II partial-power converter (PPC), based on the phase-shifted full-bridge converter, for EV Fast Chargers. By exploiting the reduced voltage range of an EV battery pack along with the reduced power ratio for a Type II PPC, an extremely efficient charging process can be achieved. The concept is validated with the development of a 7 kW demonstrator, hence realistic efficiency measurements are obtained. Results indicate the effectiveness of charging a battery by merely handling 13.32% of the power provided to it, with a peak efficiency of 99.11%.

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Implementation of particle swarm optimization (PSO) algorithm for Tuning of power system stabilizers in multimachine electric power systems

Verdejo, H.; Pino, V.; Kliemann, W.; Becker, C.; Delpiano, J. | Energies 13, no. 8 (2020): 2093. | 2020

The application of artificial intelligence-based techniques has covered a wide range of applications related to electric power systems (EPS). Particularly, a metaheuristic technique known as Particle Swarm Optimization (PSO) has been chosen for the tuning of parameters for Power System Stabilizers (PSS) with success for relatively small systems. This article proposes a tuning methodology for PSSs based on the use of PSO that works for systems with ten or even more machines. Our new methodology was implemented using the source language of the commercial simulation software DigSilent PowerFactory. Therefore, it can be translated into current practice directly. Our methodology was applied to different test systems showing the effectiveness and potential of the proposed technique.

Keywords: power system; power system stabilizer; particle swarm optimization; multimachine system

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High frequency multifractality in return intervals from fading induced by turbulence

Felipe Olivares, Gustavo Funes, and Darío G. Pérez | Fractals | 2020

In this work, we study the multifractal properties of the return intervals between fading events defined as laser intensity drops induced by optical turbulence. A laboratory-controlled experiment was conducted in which the irradiance fluctuations were recorded at a high sampling rate. Return intervals were obtained by identifying fading events under a threshold defined in times of the standard deviation of the measured irradiance. Using multifractal detrended fluctuation analysis, we found a crossover between two different scaling regimes: a spurious multifractal slightly correlated at small scales and a monofractal correlated for large scales. Based on a surrogate analysis and numerical simulations of monofractal processes, we conclude the heavy tail of the probability distribution of the return interval is the origin of the multifractality observed at small scales. Keywords:

Atmospheric Propagation; Turbulence; Time Series Analysis; Stochastic Processes; Multifractality; Generalized Hurst Exponent; Extreme Events

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Detection of Hermite-Gaussian modes in vortex beams affected by convective turbulence

B. Salgado, E. Peters & G. Funes | Waves in Random and Complex Media | 2020

This research present an analysis of the decomposition of Laguerre-Gaussian modes into Hermite-Gaussian modes when propagating through turbulence. This effect can be clearly observed by canceling the original Laguerre-Gaussian beam with another of different topological charge. The results of the propagations of these beams through Kolmogorov turbulence phase masks were analyzed, identifying which ones achieved the decomposition. The turbulences were then decomposed into the first 15 Zernike polynomials and used as new ‘Zernike turbulences’. We show that the turbulence internal process that allows the decomposition has a high correlation with a phase distortion based on a single Zernike polynomial or a combination of them.

Keywords: Vortex; Hermite-Gaussian; Laguerre-Gaussian; Zernike decomposition

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Comparison of Convolutional Neural Networks in Fruit Detection and Counting: a Comprehensive Evaluation

Vasconez, J. P.; Delpiano, J.; Vougioukas, J.; Auat Cheein, F. | Computers and Electronics in Agriculture 173 (2020): 105348. | 2020

Knowing beforehand the amount of fruit to be harvested leads to better logistics and decisions making in the agricultural industry. In the last years, several sensors –mainly artificial vision systems– and sensing techniques have been proposed to address the fruit counting problem with sundry results. Convolutional neural networks (CNN) arise as the current trend in processing imagery information, due to their adaptability and efficiency in object detection. However, there is still missing an insightful analysis of the usability of such technique in fruit counting problems in groves, since the learning process is sensitive to the training input data, the sensor (affected by environmental conditions) and the architecture chosen to process the imagery set. Therefore, in this work we test two of the most common architectures: Faster R-CNN with Inception V2 and Single Shot Multibox Detector (SSD) with MobileNet. These detection architectures were trained and tested on three fruits: Hass avocado and lemon (both from Chile), and apples (from California – USA), under different field conditions. To address the problem of video-based fruit counting, we use multi-object tracking based on Gaussian estimation. Our system achieves fruit counting performances up to 93% (overall for all fruits) using Faster-RCNN with Inception V2, and 90% (overall for all fruits) using SSD with MobileNet. Such results can lead to further improve the decision making process in agricultural practices. Keywords: Precision agriculture; Fruit counting; Faster R-CNN; Single shot multibox detector; Multi-object tracking

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Turbulence-induced power drops as extreme events.

Olivares, F.; Funes, G.; Pérez, D. | Optics and Lasers in Engineering. 116: 111-115. | 2019

Free-space optical communication links through the atmosphere are degraded mainly by the action of scintillation and beam wander. Both phenomena are responsible for fiber coupling misalignments at the receiver. Henceforth, the signal is corrupted by random power drops, which can be identified as extreme events, with particular statistical properties. In this work, we performed experiments and simulations to gain insight into understanding these extremes events and their relation with scintillation and wander at a receiver. Particularly, this sequence also inherits the same long term correlations of the original data. Keywords: Atmospheric optics; Atmospheric propagation; Turbulence

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Singular beams based on tangential phase warp.

Peters, E.; Funes, G.; Anguita, J. | Optics Letters. 44(15):3769-3772 | 2019

We introduce a new kind of singular beam with a controllable topological charge. These beams are created by modulating the spatial phase using a tangent function on the angular coordinate, and a linear function on the radial coordinate. While the angular function controls the topological charge of the beam, the radial function generates a warped intensity profile. We simulate several cases to analyze their evolution with propagation and determine their topological charge. The results are supported with an experiment using a Shack–Hartmann wavefront sensor.

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Modular Multilevel Series/Parallel Converter With Switched-Inductor Energy Transfer Between Modules.

Lizana, R.; Rivera, S.; Li, Z.; Luo, Z.; Peterchev, A.; Sgoetz, S. | IEEE Transactions on Power Electronics. 34(5):4844-4852. | 2019

This paper presents a modular multilevel series/parallel converter (MMSPC) with intermodule switched-inductor power transfer. The switched-inductor voltage conversion feature allows controllable and efficient transfer of energy between modules with nonnegligible voltage difference, providing both step-down and step-up functionalities. Thus, this converter can accurately control and rapidly adjust the voltage of each module to generate an ac output voltage waveform with a controllable number of levels, increasing the quality of the output. Moreover, the intrinsic dc-dc conversion feature can generate a dc controllable output voltage and enable new applications. In this text, we specifically demonstrate how the flexibility of obtaining both ac and dc output with the same setup renders the topology promising for battery energy storage systems and dc microgrid applications. Experimental results validate the topology and concept of an MMSPC with intrinsic switched-inductor conversion.

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A Dynamic Stochastic Hybrid Model to Represent Significant Wave Height and Wave Period for Marine Energy Representation.

Verdejo, H.; Awerkin, A.; Kliemann, W.; Becker, C.; Chávez, H.; Barbosa, K.; Delpiano, J. | Energies. 12(5:887): 1-15. | 2019

This paper presents a methodology to represent ocean wave power generation based on real data observation for significant wave height (SWH or Hs ) and wave period (WP or T). This technique is based on a hybrid model, which considers Fourier series and stochastic differential equations, allowing a continuous time representation of the random changes in the parameters associated with wave power generation ( Hs and T). The methodology is explained, including estimation methods and a validation procedure. The data series generated by the models erre used to create simulated wave power output applying a transformed matrix and a theoretical model. The results validate the utilization of this technique, when the objective is to obtain a robust dynamic representation of a random process, oriented to linear studies.

Keywords: continuous stochastic modeling; wave power; short-term forecast

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Rhythmic activities of the brain: Quantifying the high complexity of beta and gamma oscillations during visuomotor tasks.

Baravalle, R.; Rosso, O.; Montani, F. | Chaos. 28: 075513. | 2018

Electroencephalography (EEG) signals depict the electrical activity that takes place at the surface of the brain and provide an important tool for understanding a variety of cognitive processes. The EEG is the product of synchronized activity of the brain, and variations in EEG oscillations patterns reflect the underlying changes in neuronal synchrony. Our aim is to characterize the complexity of the EEG rhythmic oscillations bands when the subjects perform a visuomotor or imagined cognitive tasks (imagined movement), providing a causal mapping of the dynamical rhythmic activities of the brain as a measure of attentional investment. We estimate the intrinsic correlational structure of the signals within the causality entropy-complexity plane 𝐻×𝐶, where the enhanced complexity in the gamma 1, gamma 2, and beta 1 bands allows us to distinguish motor-visual memory tasks from control conditions. We identify the dynamics of the gamma 1, gamma 2, and beta 1 rhythmic oscillations within the zone of a chaotic dissipative behavior, whereas in contrast the beta 2 band shows a much higher level of entropy and a significant low level of complexity that correspond to a non-invertible cubic map. Our findings enhance the importance of the gamma band during attention in perceptual feature binding during the visuomotor/imagery tasks

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Enforcing energy balance in coherently superimposed optical vortices

Cisternas, J.; Anguita, J.; Funes, G. | IEEE Photonics Journal. 10(2), 1-12. | 2018

The generation of optical beams with multiple, mutually coherent orbital-angular-momentum (OAM) modes using phase gratings is analyzed from the perspective of energy distribution and radial mode composition. We show that phase gratings designed with equally weighted Laguerre-Gauss (LG) modes will generate beams with uneven energy distribution among OAM components. This unwanted outcome cannot be corrected by adjusting the width of the illuminating beam. We propose a way to design phase gratings that will produce a uniform energy distribution among the constituent OAM states after illumination while minimizing the content of high radial modes. This method is based on a generalized definition for the LG modes that take advantage of the freedom to select their radial scales.

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Chapter 10: Bipolar Type DC Microgrids for High-Quality Power Distributio

Rivera, S.; Lizana, R.; Kouro, S.; Wu, B. | DC Distribution Systems and Microgrids | 2018

During the last decades, AC systems dominated the power transmission and distribution applications almost exclusively. However, a recent convergence of needs originated in different sectors (renewable energy conversion, information technology and transportation) have accelerated the development of DC systems. Nowadays, DC systems are present at both transmission and distribution levels, offering high-performance solutions with enhanced efficiency and reliability, besides reducing the number of power conversion stages involved and uninterrupted power delivery. For LVDC active networks, two kinds of architectures are possible: unipolar and bipolar. Despite being a more sophisticated and technically complex solution, bipolar structure provide several advantages over conventional unipolar ones. Higher availability, efficiency and flexibility are just a few advantages featured by bipolar systems. This chapter presented a brief overview covering the different aspects of bipolar LVDC networks. Distribution converter topologies, balancing stages and also their control schemes are discussed in order to highlight the efforts being made in this growing architecture.

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Automated detection of fluorescent cells in in-resin fluorescence sections for integrated light and electron microscopy

Delpiano, J.; Pizarro, L.; Peddie, C.; Jones, M.; Griffin, L.; Collinson, L. | Journal of Microscopy (2018), vol. 271, n. 1, pp. 109-119 | 2018

Integrated array tomography combines fluorescence and electron imaging of ultrathin sections in one microscope, and enables accurate high-resolution correlation of fluorescent proteins to cell organelles and membranes. Large numbers of serial sections can be imaged sequentially to produce aligned volumes from both imaging modalities, thus producing enormous amounts of data that must be handled and processed using novel techniques. Here, we present a scheme for automated detection of fluorescent cells within thin resin sections, which could then be used to drive automated electron image acquisition from target regions via ‘smart tracking’. The aim of this work is to aid in optimization of the data acquisition process through automation, freeing the operator to work on other tasks and speeding up the process, while reducing data rates by only acquiring images from regions of interest. This new method is shown to be robust against noise and able to deal with regions of low fluorescence.

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Normal and tangent force neuro-fuzzy control of a soft-tip robot with unknown kinematics.

Garcia, R.; Parra, V. | Engineering Applications of Artificial Intelligence. 65: 43-50. | 2017

Assuming that contact kinematics is known, there exists many force robot control schemes, however the common practice of placing a deformable pad at contact makes difficult its implementation. The difficulty stems from the fact that the this pad introduces contact kinematics uncertainties due to the unknown deformation. In this paper, considering the full non-linear constrained rigid robot equipped with a hemispherical soft-tip as end-effector, a force regulator is proposed. To compensate the kinematic uncertainty at contact, induced by the unknown soft-tip deformation, a multi-input single-output (MISO) self-tuning fuzzy-rule emulated neural network (MiFRENN) is used. Additionally, the gravity compensation together with a damping injection term in the controller are used to guarantee local convergence of the normal and tangential force errors at a given equilibrium. The stability domain of the system varying depending on the knowledge-based contribution of the MISO-MiFRENN and the damping injection, which amounts for a novel scheme that can be used for other advanced robotic contact tasks, such as tactile exploration, dexterous manipulation or biped locomotion. Representative simulations illustrate the closed-loop numerical behavior. Keywords: Soft-fingertips; Neuro-fuzzy; Force control; Model-free

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Normal and tangent force neuro-fuzzy control of a soft-tip robot with unknown kinematics.

Garcia, R.; Parra, V. | Engineering Applications of Artificial Intelligence. 65: 43-50. | 2017

Assuming that contact kinematics is known, there exists many force robot control schemes, however the common practice of placing a deformable pad at contact makes difficult its implementation. The difficulty stems from the fact that the this pad introduces contact kinematics uncertainties due to the unknown deformation. In this paper, considering the full non-linear constrained rigid robot equipped with a hemispherical soft-tip as end-effector, a force regulator is proposed. To compensate the kinematic uncertainty at contact, induced by the unknown soft-tip deformation, a multi-input single-output (MISO) self-tuning fuzzy-rule emulated neural network (MiFRENN) is used. Additionally, the gravity compensation together with a damping injection term in the controller are used to guarantee local convergence of the normal and tangential force errors at a given equilibrium. The stability domain of the system varying depending on the knowledge-based contribution of the MISO-MiFRENN and the damping injection, which amounts for a novel scheme that can be used for other advanced robotic contact tasks, such as tactile exploration, dexterous manipulation or biped locomotion. Representative simulations illustrate the closed-loop numerical behavior. Keywords: Soft-fingertips; Neuro-fuzzy; Force control; Model-free

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On the cancellation of OAM beams propagating through convective turbulence.

Funes, G.; Anguita, J. | Optics Letters, 42, 1836-1839. | 2017

By means of an experimental setup, we study the time evolution of orbital angular momentum (OAM) crosstalk after a 5 m propagation path with a turbulence perturbation generated by a flat heater. This convective turbulence could simulate the beam passing over hot concrete or building roofs. We study the consequences of using a wide range of transmission OAM states. We also explore the effect of misalignment, and we propose two new different techniques for analyzing the vortex cancellation. Even though results are inconsistent with theoretical predictions, especially for low turbulence regimes, we state that signal-to-noise ratio is the key factor to understanding this discrepancy. Finally, a crosstalk correction method is proposed via image post-processing that would open the possibility of an adaptive optics approach that is different from conventional ones.

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On the cancellation of OAM beams propagating through convective turbulence

Funes, G. and Anguita, J. | Optics Letters | 2017


Synthesis of anisotropic optical turbulence at the laboratory.

Funes, G.; Olivares, F.; Weinberger, C.; Carrasco, Y.; Nuñez, L.; Pérez, D. | Optic Letters. 41: 5696-5699. | 2016

At the foundation of the problem of light propagation through optical turbulence is the classical Obukhov–Kolmogorov theory. It rests in the requirement that the refractive index fluctuations should be homogeneous and isotropic. These, with other necessary assumptions, lead to the very well-known −11/3-power exponent spectrum on the inertial range; although departures have been found, they are usually associated with partially developed turbulence or its intrinsic intermittency. Recently, in optics, the interest in anisotropic fluctuations of the refractive index has gained attention. These studies are mostly theoretical, and reduce anisotropic effects to a dilatation along a coordinate direction in the three-dimensional wavenumber space. Few experimental works exists, but all of them employ simulated turbulence. In this Letter, we describe an experiment to produce anisotropic turbulence under controlled conditions; moreover, we observe anisotropy by studying the spectral power exponent of a temporal series of laser beam wandering.

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Neurofuzzy self-tuning of the dissipation rate gain for model-free force-position exponential tracking of robots.

Parra, V.; García, R.; Armendariz, J. | Neurocomputing. 171: 209-219. | 2016

Simultaneous force and position control of robots interacting with a rigid environment has been broadly studied assuming several contact force models, being the differential algebraic – DAE – model the most complete one, however DAE robots show complex and strong nonlinear couplings that make difficult to achieve tracking, when dynamic model is not available. In this paper, considering the fundamental structural properties of DAE robots, in particular passivity and the orthogonalization of force and velocity vectors, it is proposed a model-free neurofuzzy-based self-tuning robot controller for exponential tracking, which is composed of orthogonalized PID-position plus an I-force (If) control terms, and a feed-forward desired force term. The salient feature of this proposal is a novel neurofuzzy self-tuning scheme aimed at tuning the dissipation rate gain (DRG) so as to enforce dissipativity in closed-loop, rather than the standard scheme of tuning the feedback control gains, or the control structure, which in our case stands for a simple constant feedback gain orthogonalized controller. In fact, in virtue of such orthogonalization, it emerges a simple and low cost parallel structure of the neuro-fuzzy network that targets solely the DRG so as to drive error dynamics to zero with exponential rate, without any knowledge of robot dynamics or carrying out any approximation of inverse dynamics. Thus, this technique can be applied to other class of systems and controllers that ensure passivity in closed-loop. Simulations show the validity and the feasibility of this new approach. Keywords: Self-tuning PID; Neuro-fuzzy; Robot manipulators; Model-free tracking

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Multi-objective optimization for parameter selection and characterization of optical flow methods.

Delpiano, J.; Pizarro, L.; Verschaec, R.; Ruiz-del-Solar, J. | Applied Soft Computing. 46: 1067-1078. | 2016

Optical flow methods are among the most accurate techniques for estimating displacement and velocity fields in a number of applications that range from neuroscience to robotics. The performance of any optical flow method will naturally depend on the configuration of its parameters, and for different applications there are different trade-offs between the corresponding evaluation criteria (e.g. the accuracy and the processing speed of the estimated optical flow). Beyond the standard practice of manual selection of parameters for a specific application, in this article we propose a framework for automatic parameter setting that allows searching for an approximated Pareto-optimal set of configurations in the whole parameter space. This final Pareto-front characterizes each specific method, enabling proper method comparison and proper parameter selection. Using the proposed methodology and two open benchmark databases, we study two recent variational optical flow methods. The obtained results clearly indicate that the method to be selected is application dependent, that in general method comparison and parameter selection should not be done using a single evaluation measure, and that the proposed approach allows to successfully perform the desired method comparison and parameter selection.

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Information Theoretical Measures for Achieving Robust Learning Machines.

Zegers, P.; Frieden, B.; Alarcón, C.; Fuentes, A. | Entropy. 18: 295; doi:10.3390/e18080295. | 2016

Information theoretical measures are used to design, from first principles, an objective function that can drive a learning machine process to a solution that is robust to perturbations in parameters. Full analytic derivations are given and tested with computational examples showing that indeed the procedure is successful. The final solution, implemented by a robust learning machine, expresses a balance between Shannon differential entropy and Fisher information. This is also surprising in being an analytical relation, given the purely numerical operations of the learning machine.

Keywords: information theoretical learning; Shannon entropy; Kullback–Leibler divergence; relative entropy; cross-entropy; Fisher information; relative information

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Dynamic optimal grasping of a circular object with gravity using robotic soft-fingertips.

García-Rodríguez, R.; Segovia-Palacios, V.; Parra-Vega, V.; Villalva-Lucio, M. | International Journal of Applied Mathematics & Computer Science (AMCS). 26(2): 309-323. DOI: 10.1515/amcs-2016-0022 | 2016

Object manipulation usually requires dexterity, encoded as the abilityto roll, which is very difficult to achieve with robotichands based on point contact models (subject to holonomic constraints). As an alternative for dexterous manipulation,deformable contact with hemispherical shape fingertips has been proposed to yield naturally a rolling constraint. It entailsdexterity at the expense of dealing with normal and tangential forces, as well as more elaborated models and controlschemes. Furthermore, the essential feature of the quality ofgrasp can be addressed with this type of robot hands, but ithas been overlooked for deformable contact. In this paper, a passivity-based controller that considers an optimal graspingmeasure is proposed for robotic hands with hemispherical deformable fingertips, to manipulate circular dynamic objects.Optimal grasping that minimizes the contact wrenches is achieved through fingertip rolling until normal forces pass throughthe center of mass of the object, aligning the relative angle between these normal forces. The case of a circular object isdeveloped in detail, though ourproposal can be extended to objects with an arbitrary shape that admit a local decompositionby a circular curvature. Simulation and experimental results show convergence under various conditions, wherein rollingand tangent forces become instrumental to achieve such a quality of grasp. Keywords: Dynamic grasping, soft-fingertips, circular object.

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Multi-objective optimization for parameter selection and characterization of optical flow methods

Delpiano, Jose; Pizarro, Luis; Verschae, Rodrigo; Ruiz-del-Solar, Javier; | APPLIED SOFT COMPUTING | 2016


Turbulence-induced persistence in laser beam wandering.

Zunino, L.; Gulich,.; Funes, G.; Perez D. | Optics Letters. 40(13): 3145-3148. | 2015

We have experimentally confirmed the presence of long-memory correlations in the wandering of a thin Gaussian laser beam over a screen after propagating through a turbulent medium. A laboratory-controlled experiment was conducted in which coordinate fluctuations of the laser beam were recorded at a sufficiently high sampling rate for a wide range of turbulent conditions. Horizontal and vertical displacements of the laser beam centroid were subsequently analyzed by implementing detrended fluctuation analysis. This is a very well-known and widely used methodology to unveil memory effects from time series. Results obtained from this experimental analysis allow us to confirm that both coordinates behave as highly persistent signals for strong turbulent intensities. This finding is relevant for a better comprehension and modeling of the turbulence effects in free-space optical communication systems and other applications related to propagation of optical signals in the atmosphere.

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Orbital-angular-momentum crosstalk and temporal fading in a terrestrial laser link using single-mode fiber coupling.

Funes, G.; Vial, M.; Anguita, J. | OPTICS EXPRESS. 23(18): 23133-23142. | 2015

Using a mobile experimental testbed, we perform a series of measurements on the detection of laser beams carrying orbital angular momentum (OAM) to evaluate turbulent channel distortions and crosstalk among receive states in an 84-m roofed optical link. We find that a receiver assembly using single-mode fiber coupling serves as a good signal selector in terms of crosstalk rejection. From the recorded temporal channel waveforms, we estimate average crosstalk profiles and propose an appropriate probability density function for the fluctuations of the detected OAM signal. Further measurements of OAM crosstalk are described for a horizontal 400-m link established over our campus.

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On the optical flow model selection through metaheuristics.

Pereira, D.; Delpiano, J.; Papa, J. | EURASIP Journal on Image and Video Processing. 11, 1-10. | 2015

Optical flow methods are accurate algorithms for estimating the displacement and velocity fields of objects in a wide variety of applications, being their performance dependent on the configuration of a set of parameters. Since there is a lack of research that aims to automatically tune such parameters, in this work, we have proposed an optimization-based framework for such task based on social-spider optimization, harmony search, particle swarm optimization, and Nelder-Mead algorithm. The proposed framework employed the well-known large displacement optical flow (LDOF) approach as a basis algorithm over the Middlebury and Sintel public datasets, with promising results considering the baseline proposed by the authors of LDOF.

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Fisher Information Properties.

Zegers, P. | ENTROPY. 17(7): 4918-4939. | 2015

A set of Fisher information properties are presented in order to draw a parallel with similar properties of Shannon differential entropy. Already known properties are presented together with new ones, which include: (i) a generalization of mutual information for Fisher information; (ii) a new proof that Fisher information increases under conditioning; (iii) showing that Fisher information decreases in Markov chains; and (iv) bound estimation error using Fisher information. This last result is especially important, because it completes Fano’s inequality, i.e., a lower bound for estimation error, showing that Fisher information can be used to define an upper bound for this error. In this way, it is shown that Shannon’s differential entropy, which quantifies the behavior of the random variable, and the Fisher information, which quantifies the internal structure of the density function that defines the random variable, can be used to characterize the estimation error. View Full-Text

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Estimation of C2n based on scintillation of fixed targets imaged through atmospheric turbulence.

Gulich, D.; Funes, G.; Pérez, D.; Zunino,L. | Optics Letters. 40(23): 5642-5645. | 2015

We define a pixel-based scintillation index for dynamic incoherent imaging of fixed high-contrast targets through atmospheric turbulence. We propose a simple setup to study this parameter varying the 𝐶2𝑛 constant in controlled laboratory conditions (weak fluctuation regime). We find the semi-empirical relationship between the pixel-based scintillation index and the index of refraction structure constant, which we then employ to estimate 𝐶2𝑛 successfully in an independent case in which this value was not known beforehand.

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Effects of urban configuration on the wind energy distribution over a building.

Herrmann-Priesnitz, B.; Calderon-Munoz, W..; LeBoeuf, R. | JOURNAL OF RENEWABLE AND SUSTAINABLE ENERGY. 7(3). | 2015

A numerical study to investigate the wind energy potential for various building configurations is presented. Steady-state incompressible flow simulations were performed using the finite volume method of ANSYS Fluent with the k-ε turbulence model. A simplified city model was used to study the flow behavior over a building rooftop for various configurations of the upwind structure. Results show an increase of up to 29% in the available energy compared to the free stream due to variations in the dimensions of the separation bubble over the rooftop. This study shows the influence of building configuration on the wind resource near buildings and how it can affect the feasibility of a small-scale wind turbine project.

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An Implementation of Combined Local-Global Optical Flow.

Jara-Wilde, J.; Cerda, M.; Delpiano, J.; Härtel S. | Image Processing. 5: 139-158. | 2015

Optical Flow (OF) approaches for motion estimation calculate vector fields for the apparent velocities of objects in image sequences. In 1981 Horn and Schunck (HS) introduced two basic assumptions: ‘brightness value constancy’ and ‘smooth variation’ to estimate a smooth OF field over the entire image -global approach-. In parallel, Lucas and Kanade (LK) assumed constant motion patterns for image patches, estimating piecewise-homogeneous OF fields -local approach-. Several variations of these approaches exist today. Here we present the combined local-global (CLG) approach by Bruhn et al. which encompasses properties of HS-OF and LK-OF, aiming to improve the OF accuracy for small-scale variations, while delivering the HS-OF dense and smooth fields. A multiscale implementation is provided for 2D images, together with two numerical solvers: Successive Over-Relaxation and the faster Pointwise-Coupled Gauss-Seidel by Bruhn et al.. The algorithm works on gray-scale (single channel) images, with color images being converted prior to the OF computation

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An economical dual hot-wire liquid water flux probe design.

LeBoeuf, R.; Rivera, J.; de la Jara, E. | ATMOSPHERIC RESEARCH. 151: 224-235. | 2015

The velocity, liquid water content (LWC) and their product, the liquid water flux (LWF), are of interest for research in environmental sciences, fog collection, and free-space communications. This paper provides a design for an economical dual hot-wire LWF probe, which enables the ground-based measurement of velocity, LWC and LWF. The design accounts for the droplet deposition efficiency, prong conduction, saturation and sensitivity. The operating mode and probe configurations are described. Two 125 μm diameter, 5 cm long platinum wires having 2 and 50 °C wire to air temperature offsets would yield measurement uncertainties of about 6% for velocity and from 8 to 22% for the LWC and from 2 to 17% for the LWF given velocities in the range 2 to 8 m/s and LWC in the range 0.2 to 0.8 g/m3. The lower uncertainties correspond to higher LWF, which is of particular interest in fog collection projects. The recurring costs of the instrument’s mechanical and electrical components would be about US $150 per unit. Therefore, the design presented herein is a viable option for large-scale sensor networks. Keywords: Fog; Liquid water flux; Liquid water content; Velocity; Hot-wire probe

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A NOVEL, Fully automated pipeline for period estimation in the eros 2 data set.

Protopapas, P.; Huijse, P.; Estevez, P.; Zegers, P. | ASTROPHYSICAL JOURNAL SUPPLEMENT SERIES. 216(2). | 2015

We present a new method to discriminate periodic from nonperiodic irregularly sampled light curves. We introduce a periodic kernel and maximize a similarity measure derived from information theory to estimate the periods and a discriminator factor. We tested the method on a data set containing 100,000 synthetic periodic and nonperiodic light curves with various periods, amplitudes, and shapes generated using a multivariate generative model. We correctly identified periodic and nonperiodic light curves with a completeness of ∼90% and a precision of ∼95%, for light curves with a signal-to-noise ratio (S/N) larger than 0.5. We characterize the efficiency and reliability of the model using these synthetic light curves and apply the method on the EROS-2 data set. A crucial consideration is the speed at which the method can be executed. Using a hierarchical search and some simplification on the parameter search, we were able to analyze 32.8 million light curves in ∼18 hr on a cluster of GPGPUs. Using the sensitivity analysis on the synthetic data set, we infer that 0.42% of the sources in the LMC and 0.61% of the sources in the SMC show periodic behavior. The training set, catalogs, and source code are all available at http://timemachine.iic.harvard.edu. Keywords: methods: data analysis; stars: variables: general

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Fisher Information Properties

Zegers, P. | Entropy | 2015

A set of Fisher information properties are presented in order to draw a parallel with similar properties of Shannon differential entropy. Already known properties are presented together with new ones, which include: (i) a generalization of mutual information for Fisher information; (ii) a new proof that Fisher information increases under conditioning; (iii) showing that Fisher information decreases in Markov chains; and (iv) bound estimation error using Fisher information. This last result is especially important, because it completes Fano’s inequality, i.e., a lower bound for estimation error, showing that Fisher information can be used to define an upper bound for this error. In this way, it is shown that Shannon’s differential entropy, which quantifies the behavior of the random variable, and the Fisher information, which quantifies the internal structure of the density function that defines the random variable, can be used to characterize the estimation error.

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A Novel, Fully automated pipeline for period estimation in the eros 2 data set

Protopapas, Pavlos; Huijse, Pablo; Estevez, Pablo A.; Zegers, Pablo | The Astrophysical Journal Supplement Series | 2015

We present a new method to discriminate periodic from nonperiodic irregularly sampled light curves. We introduce a periodic kernel and maximize a similarity measure derived from information theory to estimate the periods and a discriminator factor. We tested the method on a data set containing 100,000 synthetic periodic and nonperiodic light curves with various periods, amplitudes, and shapes generated using a multivariate generative model. We correctly identified periodic and nonperiodic light curves with a completeness of ~90% and a precision of ~95%, for light curves with a signal-to-noise ratio (S/N) larger than 0.5. We characterize the efficiency and reliability of the model using these synthetic light curves and apply the method on the EROS-2 data set. A crucial consideration is the speed at which the method can be executed. Using a hierarchical search and some simplification on the parameter search, we were able to analyze 32.8 million light curves in ~18?hr on a cluster of GPGPUs. Using the sensitivity analysis on the synthetic data set, we infer that 0.42% of the sources in the LMC and 0.61% of the sources in the SMC show periodic behavior. The training set, catalogs, and source code are all available at http://timemachine.iic.harvard.edu.

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Turbulence-induced persistence in laser beam wandering

Luciano Zunino, Damián Gulich, Gustavo Funes, and Darío G. Pérez | Optics Letters | 2015

We have experimentally confirmed the presence of long-memory correlations in the wandering of a thin Gaussian laser beam over a screen after propagating through a turbulent medium. A laboratory-controlled experiment was conducted in which coordinate fluctuations of the laser beam were recorded at a sufficiently high sampling rate for a wide range of turbulent conditions. Horizontal and vertical displacements of the laser beam centroid were subsequently analyzed by implementing detrended fluctuation analysis. This is a very well-known and widely used methodology to unveil memory effects from time series. Results obtained from this experimental analysis allow us to confirm that both coordinates behave as highly persistent signals for strong turbulent intensities. This finding is relevant for a better comprehension and modeling of the turbulence effects in free-space optical communication systems and other applications related to propagation of optical signals in the atmosphere.

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Orbital-angular-momentum crosstalk and temporal fading in a terrestrial laser link using single-mode fiber coupling

Funes, G., Vial, M., Anguita, J.A. | Optics Express | 2015

Using a mobile experimental testbed, we perform a series of measurements on the detection of laser beams carrying orbital angular momentum (OAM) to evaluate turbulent channel distortions and crosstalk among receive states in an 84-m roofed optical link. We find that a receiver assembly using single-mode fiber coupling serves as a good signal selector in terms of crosstalk rejection. From the recorded temporal channel waveforms, we estimate average crosstalk profiles and propose an appropriate probability density function for the fluctuations of the detected OAM signal. Further measurements of OAM crosstalk are described for a horizontal 400-m link established over our campus.

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Neurofuzzy self-tuning of the dissipation rate gain for model-free force-position exponential tracking of robots

Parra-Vega, V., García-Rodríguez, R., Armendariz, J. | Neurocomputing | 2015

Simultaneous force and position control of robots interacting with a rigid environment has been broadly studied assuming several contact force models, being the differential algebraic – DAE – model the most complete one, however DAE robots show complex and strong nonlinear couplings that make difficult to achieve tracking, when dynamic model is not available. In this paper, considering the fundamental structural properties of DAE robots, in particular passivity and the orthogonalization of force and velocity vectors, it is proposed a model-free neurofuzzy-based self-tuning robot controller for exponential tracking, which is composed of orthogonalized PID-position plus an I-force (If) control terms, and a feed-forward desired force term. The salient feature of this proposal is a novel neurofuzzy self-tuning scheme aimed at tuning the dissipation rate gain (DRG) so as to enforce dissipativity in closed-loop, rather than the standard scheme of tuning the feedback control gains, or the control structure, which in our case stands for a simple constant feedback gain orthogonalized PID+If controller. In fact, in virtue of such orthogonalization, it emerges a simple and low cost parallel structure of the neuro-fuzzy network that targets solely the DRG so as to drive error dynamics to zero with exponential rate, without any knowledge of robot dynamics or carrying out any approximation of inverse dynamics. Thus, this technique can be applied to other class of systems and controllers that ensure passivity in closed-loop. Simulations show the validity and the feasibility of this new approach.

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Effects of urban configuration on the wind energy distribution over a building

Herrmann-Priesnitz, Benjamin; Calderon-Munoz, Williams R.; LeBoeuf, R. | Journal of Renewable and Sustainable Energy | 2015

A numerical study to investigate the wind energy potential for various building configurations is presented. Steady-state incompressible flow simulations were performed using the finite volume method of ANSYS Fluent with the k-ε turbulence model. A simplified city model was used to study the flow behavior over a building rooftop for various configurations of the upwind structure. Results show an increase of up to 29% in the available energy compared to the free stream due to variations in the dimensions of the separation bubble over the rooftop. This study shows the influence of building configuration on the wind resource near buildings and how it can affect the feasibility of a small-scale wind turbine project.

Ver enlace externo


An economical dual hot-wire liquid water flux probe design

LeBoeuf, R. L..; de Dios Rivera, J.; de la Jara, E. | Atmospheric Research | 2015

The velocity, liquid water content (LWC) and their product, the liquid water flux (LWF), are of interest for research in environmental sciences, fog collection, and free-space communications. This paper provides a design for an economical dual hot-wire LWF probe, which enables the ground-based measurement of velocity, LWC and LWF. The design accounts for the droplet deposition efficiency, prong conduction, saturation and sensitivity. The operating mode and probe configurations are described. Two 125 μm diameter, 5 cm long platinum wires having 2 and 50 °C wire to air temperature offsets would yield measurement uncertainties of about 6% for velocity and from 8 to 22% for the LWC and from 2 to 17% for the LWF given velocities in the range 2 to 8 m/s and LWC in the range 0.2 to 0.8 g/m3. The lower uncertainties correspond to higher LWF, which is of particular interest in fog collection projects. The recurring costs of the instrument’s mechanical and electrical components would be about US $150 per unit. Therefore, the design presented herein is a viable option for large-scale sensor networks.

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Tuning of Power System Stabilizers using Multiobjective Optimization NSGA II

Verdejo, H; Gonzalez, D; Delpiano, J; Becker, C; | IEEE LATIN AMERICA TRANSACTIONS | 2015


An Implementation of Combined Local-Global Optical Flow

Jara-Wilde, J; Cerda, M; Delpiano, J; Hartel, S; | IMAGE PROCESSING ON LINE | 2015

Optical Flow (OF) approaches for motion estimation calculate vector fields for the apparent velocities of objects in image sequences. In 1981 Horn and Schunck (HS) introduced two basic assumptions: ‘brightness value constancy’ and ‘smooth variation’ to estimate a smooth OF field over the entire image -global approach-. In parallel, Lucas and Kanade (LK) assumed constant motion patterns for image patches, estimating piecewise-homogeneous OF fields -local approach-. Several variations of these approaches exist today. Here we present the combined local-global (CLG) approach by Bruhn et al. which encompasses properties of HS-OF and LK-OF, aiming to improve the OF accuracy for small-scale variations, while delivering the HS-OF dense and smooth fields. A multiscale implementation is provided for 2D images, together with two numerical solvers: Successive Over-Relaxation and the faster Pointwise-Coupled Gauss-Seidel by Bruhn et al.. The algorithm works on gray-scale (single channel) images, with color images being converted prior to the OF computation.

Ver enlace externo


On the optical flow model selection through metaheuristics

Pereira, DR; Delpiano, J; Papa, JP; | EURASIP JOURNAL ON IMAGE AND VIDEO PROCESSING | 2015

Optical flow methods are accurate algorithms for estimating the displacement and velocity fields of objects in a wide variety of applications, being their performance dependent on the configuration of a set of parameters. Since there is a lack of research that aims to automatically tune such parameters, in this work, we have proposed an optimization-based framework for such task based on social-spider optimization, harmony search, particle swarm optimization, and Nelder-Mead algorithm. The proposed framework employed the well-known large displacement optical flow (LDOF) approach as a basis algorithm over the Middlebury and Sintel public datasets, with promising results considering the baseline proposed by the authors of LDOF.

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Quantitative goals for large-scale fog collection projects as a sustainable fresh water resource in northern Chile.

LeBoeuf, R.; De la Jara, E. | Water International, 39(4), 431-450. (ISI-Q3)(84/125)(IF: 0.686). | 2014

The objective of this study was to determine the quantitative goals for a large-scale fog collection project if it were to be an economically competitive source of freshwater in northern Chile. When the initial costs are factored in, the cost of water from such a project would exceed the market price of the alternatives. However, given current costs, the project could be profitable given an average collection rate of about 10 litres per day per square metre. Investment in site selection and system improvements to reduce costs and improve collection rates are essential for making large-scale fog collection an economically competitive source of freshwater.

Keywords: Fog collection; Freshwater; Economics; Sustainability

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Neuro-Fuzzy Self-tuning of PID Control for Semiglobal Exponential Tracking of Robot Arms.

Armendariz, J.; Parra-Vega,V.; García-Rodríguez,R.; Rosales, S. | Applied Soft Computing, 25, pp. 139-148. (2014). (ISI-Q1)(14/102)(IF: 2.97). | 2014

The PID controller with constant feedback gains has withstood as the preferred choice for control of linear plants or linearized plants, and under certain conditions for non-linear ones, where the control of robotic arms excels. In this paper a model-free self-tuning PID controller is proposed for tracking tasks. The key idea is to exploit the passivity-based formulation for robotic arms in order to shape the damping injection to enforce dissipativity and to guarantee semiglobal exponential convergence in the sense of Lyapunov. It is shown that a neuro-fuzzy network can be used to tune dissipation rate gain through a self-tuning policy of a single gain. Experimental studies are presented to confirm the viability of the proposed approach. Keywords: Self-tuning PID; Neuro-fuzzy; Robot arms; Model-free tracking

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Computational Intelligence Challenges and Applications on Large-Scale Astronomical Time Series Databases.

Huijse, P.; Estevez, P.A.; Protopapas, P. ; Principe, J.C. ; Zegers, P. | Computational Intelligence Magazine, IEEE. 9(3). (2014). (ISI-Q1)(19/121)(IF: 3.158). | 2014

Time-domain astronomy (TDA) is facing a paradigm shift caused by the exponential growth of the sample size, data complexity and data generation rates of new astronomical sky surveys. For example, the Large Synoptic Survey Telescope (LSST), which will begin operations in northern Chile in 2022, will generate a nearly 150 Petabyte imaging dataset of the southern hemisphere sky. The LSST will stream data at rates of 2 Terabytes per hour, effectively capturing an unprecedented movie of the sky. The LSST is expected not only to improve our understanding of time-varying astrophysical objects, but also to reveal a plethora of yet unknown faint and fast-varying phenomena. To cope with a change of paradigm to data-driven astronomy, the fields of astroinformatics and astrostatistics have been created recently. The new data-oriented paradigms for astronomy combine statistics, data mining, knowledge discovery, machine learning and computational intelligence, in order to provide the automated and robust methods needed for the rapid detection and classification of known astrophysical objects as well as the unsupervised characterization of novel phenomena. In this article we present an overview of machine learning and computational intelligence applications to TDA. Future big data challenges and new lines of research in TDA, focusing on the LSST, are identified and discussed from the viewpoint of computational intelligence/machine learning. Interdisciplinary collaboration will be required to cope with the challenges posed by the deluge of astronomical data coming from the LSST.

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Coherent Multimode OAM Superpositions for Multidimensional Modulation.

Anguita, J.; Herreros, J.; Djordjevic, I. | IEEE PHOTONICS JOURNAL. 6(2). (2014). (ISI-Q1)(19/83)(2.353). | 2014

The generation, propagation, and detection of high-quality and coherently superimposed optical vortices, carrying two or more orbital angular momentum (OAM) states, is experimentally demonstrated using an optical arrangement based on spatial light modulators. We compare our results with numerical simulations and show that, in the context of turbulence-free wireless optical communication (indoor or satellite), individual OAM state identification at the receiver of an OAM-modulated system can be achieved with good precision, to accommodate for high-dimensional OAM modulation architectures. We apply our results to the simulation of a communication system using low-density parity-check-coded modulation that considers optimal signal constellation design in a channel that includes OAM crosstalk induced by realistic (imperfect) detection.

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Neuro-Fuzzy Self-tuning of PID Control for Semiglobal Exponential Tracking of Robot Arms

Armendariz, J., V. Parra-Vega, R. García-Rodríguez, S. Rosales | Applied Soft Computing | 2014

The PID controller with constant feedback gains has withstood as the preferred choice for control of linear plants or linearized plants, and under certain conditions for non-linear ones, where the control of robotic arms excels. In this paper a model-free self-tuning PID controller is proposed for tracking tasks. The key idea is to exploit the passivity-based formulation for robotic arms in order to shape the damping injection to enforce dissipativity and to guarantee semiglobal exponential convergence in the sense of Lyapunov. It is shown that a neuro-fuzzy network can be used to tune dissipation rate gain through a self-tuning policy of a single gain. Experimental studies are presented to confirm the viability of the proposed approach.

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Computational Intelligence Challenges and Applications on Large-Scale Astronomical Time Series Databases

Huijse, P. ; Estevez, P.A. ; Protopapas, P. ; Principe, J.C. ; Zegers, P. | IEEE Computational Intelligence Magazine | 2014

Time-domain astronomy (TDA) is facing a paradigm shift caused by the exponential growth of the sample size, data complexity and data generation rates of new astronomical sky surveys. For example, the Large Synoptic Survey Telescope (LSST), which will begin operations in northern Chile in 2022, will generate a nearly 150 Petabyte imaging dataset of the southern hemisphere sky. The LSST will stream data at rates of 2 Terabytes per hour, effectively capturing an unprecedented movie of the sky. The LSST is expected not only to improve our understanding of time-varying astrophysical objects, but also to reveal a plethora of yet unknown faint and fast-varying phenomena. To cope with a change of paradigm to data-driven astronomy, the fields of astroinformatics and astrostatistics have been created recently. The new data-oriented paradigms for astronomy combine statistics, data mining, knowledge discovery, machine learning and computational intelligence, in order to provide the automated and robust methods needed for the rapid detection and classification of known astrophysical objects as well as the unsupervised characterization of novel phenomena. In this article we present an overview of machine learning and computational intelligence applications to TDA. Future big data challenges and new lines of research in TDA, focusing on the LSST, are identified and discussed from the viewpoint of computational intelligence/machine learning. Interdisciplinary collaboration will be required to cope with the challenges posed by the deluge of astronomical data coming from the LSST.

Ver enlace externo


Coherent Multimode OAM Superpositions for Multidimensional Modulation

Anguita, JA., Herreros, J, Djordjevic, IB. | IEEE Photonics Journal | 2014

The generation, propagation, and detection of high-quality and coherently superimposed optical vortices, carrying two or more orbital angular momentum (OAM) states, is experimentally demonstrated using an optical arrangement based on spatial light modulators. We compare our results with numerical simulations and show that, in the context of turbulence-free wireless optical communication (indoor or satellite), individual OAM state identification at the receiver of an OAM-modulated system can be achieved with good precision, to accommodate for high-dimensional OAM modulation architectures. We apply our results to the simulation of a communication system using low-density parity-check-coded modulation that considers optimal signal constellation design in a channel that includes OAM crosstalk induced by realistic (imperfect) detection.

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Uncalibrated neurovisual servoing control for multiple robot arms.

García-Rodríguez, R.; Zegers, P. | International Journal of Advanced Robotic System, 10, 2013. | 2013

Diverse image-based tracking schemes for a robot moving in free motion have been proposed and experimentally validated. However, few visual servoing schemes have addressed the tracking of the desired trajectory and the contact forces for multiple robot arms. The main difficulty stems from the fact that camera information cannot be used to drive force trajectories. Recognizing this fact, a unique error manifold that includes position-velocity and force errors in orthogonal complements is proposed. A synergistic scheme that fuses camera, encoder and force sensor signals into a unique error manifold allows proposing a control system which guarantees exponential tracking errors under parametric uncertainty. Additionally a small neural network driven by a second order sliding mode surface is derived to compensate robot dynamics. Residual errors that arise because of the finite size of the neural network are compensated via an orthogonalized second order sliding mode. The performance of the proposed scheme, in two significant applications of the multiple robot arms, is validated through numerical simulations.

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Relative entropy derivative bounds.

Zegers, P.; Fuentes, A.; Alarcón, C. | Entropy, 15 (7): 2861-2873, 2013. | 2013

We show that the derivative of the relative entropy with respect to its parameters is lower and upper bounded. We characterize the conditions under which this derivative can reach zero. We use these results to explain when the minimum relative entropy and the maximum log likelihood approaches can be valid. We show that these approaches naturally activate in the presence of large data sets and that they are inherent properties of any density estimation process involving large numbers of random variables.

Keywords: relative entropy; Kullback-Leibler divergence; Shannon differential entropy; asymptotic equipartition principle; typical set; Fisher information; maximum log likelihood

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Error-correction coded orbital-angular-momentum modulation for FSO channels affected by turbulence.

Djordjevic, I. B.; Anguita, J. A.; Vasic, B. | J. Lightwave Technology, 30 (17): 2846-2852, 2012. | 2012

The performance of LDPC-precoded, orbital-angular-momentum (OAM) modulation is studied over a 1-km free-space laser communication link subject to OAM modal crosstalk induced by atmospheric turbulence. The multidimensional signal constellation is designed as the Cartesian product of a one-dimensional non-negative pulse-amplitude modulation and a set of orthogonal OAM modes. We evaluate the performance of this modulation scheme by first determining conditional probability density functions (PDFs) of the modal crosstalk for each symbol, resulting from the propagation in weak turbulence using a numerical propagation model. It is observed that OAM modulation is more sensitive to atmospheric turbulence as the number of dimensions increases. However, this can be efficiently mitigated by an error-correction code. The coded OAM modulation scheme provides an energy-efficient alternative to single-mode transmission, since a larger rate can be obtained per given bandwidth.

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An information theoretic algorithm for finding periodicities in stellar light curves.

Huijse, P.; Estévez, P.; Zegers, P.; Principe, J.C.; Protopapas, P. | IEEE Transaction on Signal Processing, 60 (10): 5135-5145, 2012. | 2012

We propose a new information theoretic metric for finding periodicities in stellar light curves. Light curves are astronomical time series of brightness over time, and are characterized as being noisy and unevenly sampled. The proposed metric combines correntropy (generalized correlation) with a periodic kernel to measure similarity among samples separated by a given period. The new metric provides a periodogram, called Correntropy Kernelized Periodogram (CKP), whose peaks are associated with the fundamental frequencies present in the data. The CKP does not require any resampling, slotting or folding scheme as it is computed directly from the available samples. CKP is the main part of a fully-automated pipeline for periodic light curve discrimination to be used in astronomical survey databases. We show that the CKP method outperformed the slotted correntropy, and conventional methods used in astronomy for periodicity discrimination and period estimation tasks, using a set of light curves drawn from the MACHO survey. The proposed metric achieved 97.2% of true positives with 0% of false positives at the confidence level of 99% for the periodicity discrimination task; and 88% of hits with 11.6% of multiples and 0.4% of misses in the period estimation task.

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Advances in self-organizing maps.

Estévez, P.; Príncipe, J.; Zegers, P. | Springer, Alemania, 2012. | 2012

This is the third Workshop on Self-Organising Maps (WSOM) and its related techniques. The previous two were held in Helsinki (1997 and 1999) and confIrmed the vitality of the SOM as one of the most popular and powerful concepts for unsupervised pattern recognition and data visualisation. These meetings not only acted as a showcase for the latest advances in SOM theory and for illustrating its vast range of applicability, but also as venues where much informal and fruitful interaction could take place. It is interesting to observe the development of the original SOM, and this remarkable progress confrrms the originality and insight of Teuvo Kohonen’s pioneering work. With the range and quality of the papers in this volume, the stage is set for another very successful meeting. This volume is a permanent record of all the contributions presented during WSOM’OI held at the University of Lincolnshire and Humberside, 13 – 15 June, 2001. The University is the newest of England’s universities but it is situated in the heart of one of our oldest cities – founded by the Romans and overlooked by the towering mass of its medieval cathedral. Primarily Lincoln has always been a centre for the rich agricultural heartland of England; however, it was the birthplace, 186 years ago, of George Boole. So WSOM’OI is continuing Lincoln’s long and honourable tradition of advancing scientific understanding. Keywords: Data mining and visualisation; Image Processing; STATISTICA; Signal Processing; algorithms; classification; optimization; pattern recognition

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Performance of optical flow techniques for motion analysis of fluorescent point signals in confocal microscopy

Delpiano J.; Ruiz-del-Solar J.; Jara J.; Scheer J.; Ramirez OA; Hartel S.; | MACHINE VISION AND APPLICATIONS | 2012

Optical flow approaches calculate vector fields which determine the apparent velocities of objects in time-varying image sequences. They have been analyzed extensively in computer science using both natural and synthetic video sequences. In life sciences, there is an increasing need to extract kinetic information from temporal image sequences which reveals the interplay between form and function of microscopic biological structures. In this work, we test different variational optical flow techniques to quantify the displacements of biological objects in 2D fluorescent image sequences. The accuracy of the vector fields is tested for defined displacements of fluorescent point sources in synthetic image series which mimic protein traffic in neuronal dendrites, and for GABABR1 receptor subunits in dendrites of hippocampal neurons. Our results reveal that optical flow fields predict the movement of fluorescent point sources within an error of 3% for a maximum displacement of 160 nm. Displacement of agglomerated GABABR1 receptor subunits can be predicted correctly for maximum displacements of 640 nm. Based on these results, we introduce a criteria to derive the optimum parameter combinations for the calculation of the optical flow fields in experimental images. From these results, temporal sampling frequencies for image acquisition can be derived to guarantee correct motion estimation for biological objects.

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Period estimation in astronomical time series using slotted correntropy.

Huijse, P.; Estévez, P.; Zegers, P.; Principe, J.C.; Protopapas, P. | IEEE Signal Processing Letters, 18 (6): 371-374, 2011. | 2011

In this letter, we propose a method for period estimation in light curves from periodic variable stars using correntropy. Light curves are astronomical time series of stellar brightness over time, and are characterized as being noisy and unevenly sampled. We propose to use slotted time lags in order to estimate correntropy directly from irregularly sampled time series. A new information theoretic metric is proposed for discriminating among the peaks of the correntropy spectral density. The slotted correntropy method outperformed slotted correlation, string length, VarTools (Lomb-Scargle periodogram and Analysis of Variance), and SigSpec applications on a set of light curves drawn from the MACHO survey.

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Influence of turbulence strength on temporal correlation of scintillation.

Anguita, J. A.; Cisternas, J. E. | Optics Letters, 36 (9): 1725-1727, 2011. | 2011

Through extensive laboratory experimentation we demonstrate that the temporal frequency content of turbulence-induced scintillation strongly depends on the temperature gradient exerted at the propagation path of a collimated laser beam. We find a power law relating the turbulence strength induced by convection with the vertical temperature gradient and we show that the cutoff frequency of scintillation shows an approximately linear growth with turbulence strength, measured by angle-of-arrival fluctuations. The impact of these findings are discussed in the context of free-space optical communications.

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Optimal power flow with SVC and UPFC modeling for longitudinal systems

Palma, R., Vargas, L., Përez, J., Núñez, J., Torres, R. | IEEE Transactions on Power Systems. | 2004

This paper presents a formulation of the Optimal Power Flow problem with an explicit modeling of Static Var Compensator (SVC) and Unified Power Flow Controller (UPFC) devices. The optimization problem is solved by using Sequential Quadratic Programming, where two convergence criteria and four different methods are studied to solve the quadratic subproblems. The proposed model is integrated in an object-oriented based decision support platform for competitive power markets. Validation of the method and practical applications to real longitudinal systems are discussed, where FACTS location and a UPFC-based interconnection are described. Results show the impact of SVC and UPFC FACTS technologies in the physical and economic behavior of a real system.

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Física


Propagation failure in discrete reaction-diffusion system based on the butterfly bifurcation

Kevin Rohe, Jaime Cisternas | Chaos | 2022

Reaction–diffusion systems are used in biology, chemistry, and physics to model the interaction of spatially distributed species. Particularly of interest is the spatial replacement of one equilibrium state by another, depicted as traveling waves or fronts. Their profiles and traveling velocity depend on the nonlinearities in the reaction term and on spatial diffusion. If the reaction occurs at regularly spaced points, the velocities also depend on lattice structures and the orientation of the traveling front. Interestingly, there is a wide region of parameters where the speeds become zero and the fronts do not propagate. In this paper, we focus on systems with three stable coexisting equilibrium states that are described by the butterfly bifurcation and study to what extent the three possible 1D traveling fronts suffer from propagation failure. We demonstrate that discreteness of space affects the three fronts differently. Regions of propagation failure add a new layer of complexity to the butterfly diagram. The analysis is extended to planar fronts traveling through different orientations in regular 2D lattices. Both propagation failure and the existence of preferred orientations play a role in the transient and long-time evolution of 2D patterns.

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High frequency multifractality in return intervals from fading induced by turbulence

Felipe Olivares, Gustavo Funes, and Darío G. Pérez | Fractals Vol. 29, No. 02, 2150049 | 2021

In this work, we study the multifractal properties of the return intervals between fading events defined as laser intensity drops induced by optical turbulence. A laboratory-controlled experiment was conducted in which the irradiance fluctuations were recorded at a high sampling rate. Return intervals were obtained by identifying fading events under a threshold defined in times of the standard deviation of the measured irradiance. Using multifractal detrended fluctuation analysis, we found a crossover between two different scaling regimes: a spurious multifractal slightly correlated at small scales and a monofractal correlated for large scales. Based on a surrogate analysis and numerical simulations of monofractal processes, we conclude the heavy tail of the probability distribution of the return interval is the origin of the multifractality observed at small scales.

Keywords:

Atmospheric Propagation; Turbulence; Time Series Analysis; Stochastic Processes; Multifractality; Generalized Hurst Exponent; Extreme Events

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Stable and unstable trajectories in a dipolar chain

Cisternas, J; Mellado, P; Urbina, F; Portilla, C; Carrasco, M; Concha, A | Physical Review B | 2021

In classical mechanics, solutions can be classified according to their stability. Each of them is part of the possible trajectories of the system. However, the signatures of unstable solutions are hard to observe in an experiment, and most of the times if the experimental realization is adiabatic, they are considered just a nuisance. Here we use a small number of XY magnetic dipoles subject to an external magnetic field for studying the origin of their collective magnetic response. Using bifurcation theory we have found all the possible solutions being stable or unstable, and explored how those solutions are naturally connected by points where the symmetries of the system are lost or restored. Unstable solutions that reveal the symmetries of the system are found to be the culprit that shape hysteresis loops in this system. The complexity of the solutions for the nonlinear dynamics is analyzed using the concept of boundary basin entropy, finding that the damping timescale is critical for the emergence of fractal structures in the basins of attraction. Furthermore, we numerically found domain wall solutions that are the smallest possible realizations of transverse walls and vortex walls in magnetism. We experimentally confirmed their existence and stability showing that our system is a suitable platform to study domain wall dynamics at the macroscale.

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Public disorder and transport networks in the Latin American context.

Cartes, C; Davies T. P. | Chaos, Solitons and Fractals, 153 (2021) 111567. | 2021

We propose an extension of the Davies et al. model, used to describe the London riots of 2011. This addition allows us to consider long travel distances in a city for potential rioting population. This is achieved by introducing public transport networks, which modifies the perceived travel distance between the population and likely targets. Using this more general formulation, we applied the model to the typical Griffin and Ford pattern for population distribution to describe the general features of most large Latin American cities. The possibility of long-range traveling by part of the general population has, for an immediate consequence, the existence of isolated spots more prone to suffer from rioting activity, as they are easier to reach than the rest of the city. These areas finally made it easier to control the eventual disorder by part of police forces. The reason for this outcome is that transport networks turn riots into highly localized and intense events. They are attracting a large police contingent, which will later extinguish the remaining disorder activity on the rest of the city. Therefore, working transport networks in a city effectively reduces the number of police force contingent required to control public disorder. This result, we must remark, is valid only if the model requisites for order forces are satisfied: extra police contingent can be added swiftly as required, and these forces can move around the city with total freedom.

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Interaction of dissipative solitons stabilized by nonlinear gradient terms.

Descalzi O.; Cartes, C.; Brand, H. R. | Physical Review E 103, 422151. | 2021

We study the interaction of stable dissipative solitons of the cubic complex Ginzburg-Landau equation which are stabilized only by nonlinear gradient terms. In this paper we focus for the interactions in particular on the influence of the nonlinear gradient term associated with the Raman effect. Depending on its magnitude, we find up to seven possible outcomes of theses collisions: Stationary bound states, oscillatory bound states, meandering oscillatory bound states, bound states with large-amplitude oscillations, partial annihilation, complete annihilation, and interpenetration. Detailed results and their analysis are presented for one value of the corresponding nonlinear gradient term, while the results for two other values are just mentioned briefly. We compare our results with those obtained for coupled cubic-quintic complex Ginzburg-Landau equations and with the cubic-quintic complex Swift-Hohenberg equation. It turns out that both meandering oscillatory bound states as well as bound states with large-amplitude oscillations appear to be specific for coupled cubic complex Ginzburg-Landau equations with a stabilizing cubic nonlinear gradient term. Remarkably, we find for the large-amplitude oscillations a linear relationship between oscillation amplitude and period.

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Multiplicative noise can induce a velocity change of propagating dissipative solitons.

Descalzi O.; Cartes, C.; Brand, H. R. | Physical Review E 103, 502011. | 2021

We investigate the influence of spatially homogeneous multiplicative noise on propagating dissipative solitons (DSs) of the cubic complex Ginzburg-Landau equation stabilized by nonlinear gradient terms. Here we focus on the nonlinear gradient terms, in particular on the influence of the Raman term and the delayed nonlinear gain. We show that a fairly small amount of multiplicative noise can lead to a change in the mean velocity for such systems. This effect is exclusively due to the presence of the stabilizing nonlinear gradient terms. For a range of parameters we find a velocity change proportional to the noise intensity for the Raman term and for delayed nonlinear gain. We note that the dissipative soliton decreases the modulus of its velocity when only one type of nonlinear gradient is present. We present a straightforward mean field analysis to capture this simple scaling law. At sufficiently high noise strength the nonlinear gradient stabilized DSs collapse.

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Self-organized spiral patterns at the edge of an order-disorder nonequilibrium phase transition.

Italo’Ivo Lima Dias Pinto; Daniel Escaff; Alexandre Rosas. | PHYSICAL REVIEW E | 2021

We present a spatially extended version of the Wood–Van den Broeck–Kawai–Lindenberg stochastic phase-coupled oscillator model. Our model is embedded in two-dimensional (2d) array with a range-dependent interaction. The Wood–Van den Broeck–Kawai–Lindenberg model is known to present a phase transition from a disordered state to a globally oscillatory phase in which the majority of the units are in the same discrete phase. Here we address a parameter combination in which such global oscillations are not present. We explore the role of the interaction range from a nearest neighbor coupling in which a disordered phase is observed and the global coupling in which the population concentrate in a single phase. We find that for intermediate interaction range the system presents spiral wave patterns that are strongly influenced by the initial conditions and can spontaneously emerge from the stochastic nature of the model. Our results present a spatial oscillatory pattern not observed previously in the Wood–Van den Broeck–Kawai–Lindenberg model and are corroborated by a spatially extended mean-field calculation.

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The anatomy of the 2019 Chilean social unrest

Caroca, P.; Cartes, C.; Davies, T.P.; Olivari, J.; Rica, S.; and Vogt, K. | Chaos: An Interdisciplinary Journal of Nonlinear Science | 2020

We analyze the 2019 Chilean social unrest episode, consisting of a sequence of events, through the lens of an epidemic-like model that considers global contagious dynamics. We adjust the parameters to the Chilean social unrest aggregated public data available from the Undersecretary of Human Rights and observe that the number of violent events follows a well-defined pattern already observed in various public disorder episodes in other countries since the 1960s. Although the epidemic-like models display a single event that reaches a peak followed by an exponential decay, we add standard perturbation schemes that may produce a rich temporal behavior as observed in the 2019 Chilean social turmoil. Although we only have access to aggregated data, we are still able to fit it to our model quite well, providing interesting insights on social unrest dynamics

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Synchronization and fluctuations: Coupling a finite number of stochastic units

Rosas, A; Cisternas, J; Escaff, D; Lima Dias Pinto, I; Lindenberg, K | Phys. Rev. E 101, 062140 | 2020

It is well established that ensembles of globally coupled stochastic oscillators may exhibit a nonequilibrium phase transition to synchronization in the thermodynamic limit (infinite number of elements). In fact, since the early work of Kuramoto, mean-field theory has been used to analyze this transition. In contrast, work that directly deals with finite arrays is relatively scarce in the context of synchronization. And yet it is worth noting that finite-number effects should be seriously taken into account since, in general, the limits N→∞ (where N is the number of units) and t→∞ (where t is time) do not commute. Mean-field theory implements the particular choice first N→∞ and then t→∞

. Here we analyze an ensemble of three-state coupled stochastic units, which has been widely studied in the thermodynamic limit. We formally address the finite-N problem by deducing a Fokker-Planck equation that describes the system. We compute the steady-state solution of this Fokker-Planck equation (that is, finite N but t→∞). We use this steady state to analyze the synchronic properties of the system in the framework of the different order parameters that have been proposed in the literature to study nonequilibrium transitions.

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Spatial-diversity detection of distorted vortex superpositions for OAM signal modulation

Anguita, J; Cisternas, J. | Optics Letters 45(19), pp. 5534-5537 | 2020

We propose a method for identifying orbital angular momentum (OAM) states within a vortex superposition using a Shack–Hartmann (SH) sensor as a spatial-diversity detector. We define a local OAM at every pixel of the SH image, from which we construct an OAM spectrum. The topological charges are determined from the OAM spectrum using a low-complexity algorithm, resulting in estimates that are robust to beam wandering. Data from a 200 m experimental transmission are successfully tested using the proposed technique.

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Reaction-diffusion fronts and the butterfly set

Cisternas, J; Rohe, K; Wehner, S | Chaos 30(11) | 2020

A single-species reaction–diffusion model is used for studying the coexistence of multiple stable steady states. In these systems, one can define a potential-like functional that contains the stability properties of the states, and the essentials of the motion of wave fronts in one- and two-dimensional space. Using a quintic polynomial for the reaction term and taking advantage of the well-known butterfly bifurcation, we analyze the different scenarios involving the competition of two and three stable steady states, based on equipotential curves and points in parameter space. The predicted behaviors, including a front splitting instability, are contrasted to numerical integrations of reaction fronts in two dimensions.

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Random walks of trains of dissipative solitons

Cisternas, J; Cartes, C; Descalzi, O; Albers, T; Radons, G | Chaos 30, 073134 | 2020

The propagation of light pulses in dual-core nonlinear optical fibers is studied using a model proposed by Sakaguchi and Malomed. The system consists of a supercritical complex Ginzburg–Landau equation coupled to a linear equation. Our analysis includes single standing and walking solitons as well as walking trains of 3, 5, 6, and 12 solitons. For the characterization of the different scenarios, we used ensemble-averaged square displacement of the soliton trajectories and time-averaged power spectrum of the background waves. Power law spectra, indicative of turbulence, were found to be associated with random walks. The number of solitons (or their separations) can trigger anomalous random walks or totally suppress the background waves

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On the repulsive interaction between localised vegetation patches in scarce environments

E. Berríos-Caro, M. G. Clerc, D. Escaff, C. Sandivari and M. Tlidi | Scientific Reports (2020) 10:5740 | 2020

Fragmentation followed by desertification in water-limited resources and/or nutrient-poor ecosystems is a major risk to the biological productivity of vegetation. By using the vegetation interaction-redistribution model, we analyse the interaction between localised vegetation patches. Here we show analytically and numerically that the interaction between two or more patches is always repulsive. As a consequence, only a single localised vegetation patch is stable, and other localised bounded states or clusters of them are unstable. Following this, we discuss the impact of the repulsive nature of the interaction on the formation and the selection of vegetation patterns in fragmented ecosystems.

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Gapped vegetation patterns: crown/root allometry and snaking bifurcation

Cisternas, J; Escaff, D; Clerc, M; Lefever, R; Tlidi, M | Chaos, Solitons & Fractals 133, 109617 | 2020

Nonuniform spatial distributions of vegetation in scarce environments consist of either gaps, bands often called tiger bush or patches that can be either self-organized or spatially localized in space. When the level of aridity is increased, the uniform vegetation cover develops localized regions of lower biomass. These spatial structures are generically called vegetation gaps. They are embedded in a uniform vegetation cover. The spatial distribution of vegetation gaps can be either periodic or randomly distributed. We investigate the combined influence of the facilitative and the competitive nonlocal interactions between plants, and the role of crow/root allometry, on the formation of gapped vegetation patterns. We characterize first the formation of the periodic distribution of gaps by drawing their bifurcation diagram. We then characterize localized and aperiodic distributions of vegetation gaps in terms of their snaking bifurcation diagram.

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Flocking transition within the framework of Kuramoto paradigm for synchronization: Clustering and the role of the range of interaction

Escaff, D; Delpiano, R. | Chaos: An Interdisciplinary Journal of Nonlinear Science 30 (8), 083137 | 2020

A Kuramoto-type approach to address flocking phenomena is presented. First, we analyze a simple generalization of the Kuramoto model for interacting active particles, which is able to show the flocking transition (the emergence of coordinated movements in a group of interacting self-propelled agents). In the case of all-to-all interaction, the proposed model reduces to the Kuramoto model for phase synchronization of identical motionless noisy oscillators. In general, the nature of this non-equilibrium phase transition depends on the range of interaction between the particles. Namely, for a small range of interaction, the transition is first order, while for a larger range of interaction, it is a second order transition. Moreover, for larger interaction ranges, the system exhibits the same features as in the case of all-to-all interaction, showing a spatially homogeneous flux when flocking phenomenon has emerged, while for lower interaction ranges, the flocking transition is characterized by cluster formation. We compute the phase diagram of the model, where we distinguish three phases as a function of the range of interaction and the effective coupling strength: a disordered phase, a spatially homogeneous flocking phase, and a cluster-flocking phase. Then, we present a general discussion about the applicability of this way of modeling to more realistic and general situations, ending with a brief presentation of a second example (a second model with a conservative interaction) where the flocking transition may be studied within the framework that we are proposing.

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Dissipative soliton stabilization by several nonlinear gradient terms

Descalzi, O.; Brand, H.R. | CHAOS 30, 043119 | 2020

We study a single cubic complex Ginzburg–Landau equation with nonlinear gradient terms analytically and numerically. This single equation allows for the existence of stable dissipative solitons exclusively due to nonlinear gradient terms. We shed new light on the feedback loop, leading to dissipative solitons (DSs) by analyzing a mechanical analog as a function of the magnitude of the amplitude. In addition, we present analytic results incorporating four nonlinear gradient terms and derive necessary conditions for the existence of DSs. We also elucidate in detail for the case of the Raman contribution the scaling behavior for the limit of the vanishing Raman term.

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Competing ternary surface reaction CO+O2+H2 on Ir(111)

Rohe, K; Cisternas, J; Wehner, S | Proc. R. Soc. A 476: 20190712. | 2020

The CO oxidation on platinum-group metals under ultra-high-vacuum conditions is one of the most studied surface reactions. However, the presence of disturbing species and competing reactions are often neglected. One of the most interesting additional gases to be treated is hydrogen, due to its importance in technical applications and its inevitability under vacuum conditions. Adding hydrogen to the reaction of CO and O2 leads to more adsorbed species and competing reaction steps towards water formation. In this study, a model for approaching the competing surface reactions CO+O2 + H2 is presented and discussed. Using the framework of bifurcation theory, we show how the steady states of the extended system correspond to a swallowtail catastrophe set with a tristable regime within the swallowtail. We explore numerically the possibility of reaching all stable states and illustrate the experimental challenges such a system could pose. Lastly, an approximative first-principle approach to diffusion illustrates how up to three stable states balance each other while forming heterogeneous patterns.

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Breaking of symmetry of interacting dissipative solitons can lead to partial annihilation

Descalzi, O.; Brand, H.R. | Physical Review E 101, 040201(R) | 2020

We show that for a large range of approach velocities and over a large interval of stabilizing cubic cross-coupling between counterpropagating waves, a collision of stationary pulses leads to a partial annihilation of pulses via a spontaneous breaking of symmetry. This result arises for coupled cubic-quintic complex Ginzburg-Landau equations for traveling waves for sufficiently large values of the stabilizing cubic cross-coupling and for large enough approach velocities of the pulses. Briefly, we show in addition that the collision of counterpropagating pulses in a system of two coupled cubic Ginzburg-Landau equations with nonlinear gradients (Raman effect) might also lead to partial annihilation, indicating that this breaking of symmetry is generic. Systems of experimental interest include surface reactions, convective onset, biosolitons, and nonlinear optics.

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Spiral vegetation patterns in high-altitude wetlands.

Fernandez-Oto, C.; Escaff, D.; Cisternas, J. | Ecological Complexity. 37: 38-46 | 2019

When plant communities suffer the stress of limited resources, for instance adverse environmental conditions such as extreme aridity, the spatial homogeneity of the biomass is lost and self-organized patterns may arise. Here, we report the observation of spiral-shaped patterns in the biomass of grass (genus deyeuxia), under highland arid conditions in the north of Chile. The spiral arms are a few meters long and a few centimeters wide. These dynamic structures are observed in the grazing area of an herbivore member of the South American camelids, the vicuna, on the border of highland wetlands. These spirals cannot be explained by the well-established mathematical models which describe other vegetation patterns (that emerge from a Turing-type of instability) such as stripes, rings, or fairy circles. We attribute the formation of spirals to the coupling between the growth of vegetation in semiarid regions and the grazing of vicunas. The mathematical analysis of this coupling reveals an excitable behavior, i.e. small perturbations of the equilibrium generate large trajectories before coming back, that is the origin of the spirals.

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Simultaneous influence of additive and multiplicative noise on stationary dissipative solitons.

Cartes, C.; Descalzi, O; Brand, H. | Physical Review E. 100. 012214 | 2019

We investigate the simultaneous influence of spatially homogeneous multiplicative noise as well as of spatially δ-correlated additive noise on the formation of localized patterns in the framework of the cubic-quintic complex Ginzburg-Landau equation. Depending on the ratio between the strength of additive and multiplicative noise we find a number of distinctly different types of behavior including explosions, collapse, filling in, and spatio-temporal disorder as well as intermittent behavior of all types listed. Techniques used to analyze the results include snapshots, x−t plots and plots of the spatially and temporally averaged amplitude as a function of the strength of multiplicative noise while keeping the strength of additive noise fixed. Typically 50 realizations are used for averaging to obtain the corresponding data points in these diagrams. For the widths of these distribution as a function of additive noise we obtain a linear decrease in the limit of fairly large, but fixed values of the multiplicative noise. To summarize our findings concisely we show three-dimensional plots of the mean pattern amplitude and the generalized susceptibility as a function of the strengths of additive and multiplicative noise. We critically compare the results of our investigations with those obtained in the two limiting cases of purely additive and of purely multiplicative noise.

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Mechanism of dissipative soliton stabilization by nonlinear gradient terms.

Descalzi, O.; Cisternas, J.; Brand, H. | Physical Review E. 2200. | 2019

We present a feedback mechanism for dissipative solitons in the cubic complex Ginzburg-Landau (CGL) equation with a nonlinear gradient term. We are making use of a mechanical analog containing contributions from a potential and from a nonlinear viscous term. The feedback mechanism relies on the continuous supply of energy as well as on dissipation of the stable pulse. Our picture is corroborated by the numerical solution of the full equation. A quintic contribution is not necessary for stabilization in the presence of a suitable nonlinear gradient term as we show by using a linear stability analysis for the stationary pulses. We find that the limit of vanishing magnitude of the nonlinear gradient term is singular: For exactly vanishing nonlinear gradient terms stable pulses do not exist. This situation is qualitatively different from that found for the cubic-quintic complex Ginzburg-Landau equation with a nonlinear gradient term: In this case the limit of a vanishing nonlinear gradient contribution is completely smooth. We demonstrate that, for small magnitude of the nonlinear gradient term simple types of scaling behavior are found for the amplitude, the full width at half maximum (FWHM), the velocity, and the effective frequency of the stable pulse as a function of the magnitude of the nonlinear gradient term.

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Interplay between exogenous and endogenous factors in seasonal vegetation oscillations.

Omer Tzuk, Sangeeta R. Ujjwal, Cristian Fernandez-Oto, Merav Seifan and Ehud Meron. | Scientific Reports. 9:354. | 2019

A fundamental question in ecology is whether vegetation oscillations are merely a result of periodic environmental variability, or rather driven by endogenous factors. We address this question using a mathematical model of dryland vegetation subjected to annual rainfall periodicity. We show that while spontaneous oscillations do not exist in realistic parameter ranges, resonant response to periodic precipitation is still possible due to the existence of damped oscillatory modes. Using multiple time-scale analysis, in a restricted parameter range, we find that these endogenous modes can be pumped by the exogenous precipitation forcing to form sustained oscillations. The oscillations amplitude shows a resonance peak that depends on model parameters representing species traits and mean annual precipitation. Extending the study to bistability ranges of uniform vegetation and bare soil, we investigate numerically the implications of resonant oscillations for ecosystem function. We consider trait parameters that represent species with damped oscillatory modes and species that lack such modes, and compare their behaviors. We find that the former are less resilient to droughts, suffer from larger declines in their biomass production as the precipitation amplitude is increased, and, in the presence of spatial disturbances, are likely to go through abrupt collapse to bare soil, rather than gradual, domino-like collapse.

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Front Instabilities Can Reverse Desertification.

Cristian Fernandez-Oto, Omer Tzuk, and Ehud Meron. | Physical Review Letters. 122, 048101 | 2019

Degradation processes in living systems often take place gradually by front propagation. An important context of such processes is loss of biological productivity in drylands or desertification. Using a dryland-vegetation model, we analyze the stability and dynamics of desertification fronts, identify linear and nonlinear front instabilities, and highlight the significance of these instabilities in inducing self-recovery. The results are based on the derivation and analysis of a universal amplitude equation for pattern-forming living systems for which nonuniform instabilities cannot emerge from the nonviable (zero) state. The results may therefore be applicable to other contexts of animate matter where degradation processes occur by front propagation.

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A new kind of chaotic diffusion: anti-persistent random walks of explosive dissipative solitons.

Albers, T.; Cisternas, J.; Radons, G. | New Journal of Physics. 21: 102034. | 2019

The solitons that exist in nonlinear dissipative media have properties very different from the ones that exist in conservative media and are modeled by the nonlinear Schrödinger equation. One of the surprising behaviors of dissipative solitons is the occurrence of explosions: sudden transient enlargements of a soliton, which as a result induce spatial shifts. In this work using the complex Ginzburg–Landau equation in one dimension, we address the long-time statistics of these apparently random shifts. We show that the motion of a soliton can be described as an anti-persistent random walk with a corresponding oscillatory decay of the velocity correlation function. We derive two simple statistical models, one in discrete and one in continuous time, which explain the observed behavior. Our statistical analysis benchmarks a future microscopic theory of the origin of this new kind of chaotic diffusion.

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A hidden Markov model for the dynamics of diffusing dissipative solitons

Albers, T.; Cisternas, J.; Radons, G. | J. Stat. Mech. (2019) 094013 | 2019

We investigate the dynamics of dissipative solitons in the cubic-quintic complex Ginzburg–Landau equation in one spatial dimension for different values of the bifurcation parameter . We consider a certain range of the parameter where dissipative solitons show explosions, i.e. transient enlargements of the soliton that lead to spatial shifts if the explosions are asymmetric. We find that depending on the parameter , the arising sequence of spatial shifts can be modeled by a simple anti-persistent random walk or by a more complicated hidden Markov model. We show with the help of exact analytical calculations that these models are able to reproduce several statistics of the soliton motion such as the distribution of spatial shifts, the correlation of spatial shifts, and the distribution of zig-zag streaks.

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Study of Resting-State Functional Connectivity Networks using EEG electrodes position as seed.

Rojas, G.; Alvarez, C.; Montoya, C.; de la Iglesia-Vayá, M.; Cisternas, J.; Gálvez, M. | Frontiers in Neuroscience 12:235 | 2018

Electroencephalography (EEG) is the standard diagnosis method for a wide variety of diseases such as epilepsy, sleep disorders, encephalopathies, and coma, among others. Resting-state functional magnetic resonance (rs-fMRI) is currently a technique used in research in both healthy individuals as well as patients. EEG and fMRI are procedures used to obtain direct and indirect measurements of brain neural activity: EEG measures the electrical activity of the brain using electrodes placed on the scalp, and fMRI detects the changes in blood oxygenation that occur in response to neural activity. EEG has a high temporal resolution and low spatial resolution, while fMRI has high spatial resolution and low temporal resolution. Thus, the combination of EEG with rs-fMRI using different methods could be very useful for research and clinical applications. In this article, we describe and show the results of a new methodology for processing rs-fMRI using seeds positioned according to the 10-10 EEG standard. We analyze the functional connectivity and adjacency matrices obtained using 65 seeds based on 10-10 EEG scheme and 21 seeds based on 10-20 EEG. Connectivity networks are created using each 10-20 EEG seeds and are analyzed by comparisons to the seven networks that have been found in recent studies. The proposed method captures high correlation between contralateral seeds, ipsilateral and contralateral occipital seeds, and some in the frontal lobe.

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Observation and modelling of vegetation spirals and arcs in isotropic environmental conditions: dissipative structures in arid landscapes

Tlidi, M.; Clerc, M.; Escaff, D.; Couteron, P.; Messaoudi, M.; Khaffou, M.; Makhoute, M. | Philosophical Transactions of the Royal Society A. A 376: 20180026 | 2018

We report for the first time on the formation of spirals like vegetation patterns in isotropic and uniform environmental conditions. The vegetation spirals are not waves and they do not rotate. They belong to the class of dissipative structures found out of equilibrium. Isolated or interacting spirals and arcs observed in South America (Bolivia) and North Africa (Morocco) are interpreted as a result of curvature instability that affects the circular shape of localized patches. The biomass exhibits a dynamical behaviour with arcs that transform into spirals. Interpretation of observations and of the predictions provided by the theory is illustrated by recent measurements of peculiar plant morphology (the alfa plant, or Stipa tenacissima L.) originated from northwestern Africa and the southern part of the Iberian Peninsula. This article is part of the theme issue ‘Dissipative structures in matter out of equilibrium: from chemistry, photonics and biology

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Normal and anomalous random walks of 2-d solitons

Cisternas, J.; Albers; Radons. | Chaos 28(7), 075505 | 2018

Solitons, which describe the propagation of concentrated beams of light through nonlinear media, can exhibit a variety of behaviors as a result of the intrinsic dissipation, diffraction, and the nonlinear effects. One of these phenomena, modeled by the complex Ginzburg-Landau equation, are chaotic explosions, transient enlargements of the soliton that may induce random transversal displacements, which in the long run lead to a random walk of the soliton center. As we show in this work, the transition from non-moving to moving solitons is not a simple bifurcation but includes a sequence of normal and anomalous random walks. We analyze their statistics with the distribution of generalized diffusivities, a novel approach that has been used successfully for characterizing anomalous diffusion.

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Nonlinear dynamics of river runoff elucidated by horizontal visibility graphs.

Holder Lange, Sebastian Sippel, and Osvaldo A. Rosso. | Chaos. 28: 075520. | 2018

Horizontal Visibility Graphs (HVGs) are a recently developed method to construct networks from time series. The values of the time series are considered as the nodes of the network and are linked to each other if there is no larger value between them, such as they can “see” each other. The network properties reflect the nonlinear dynamics of the time series. For some classes of stochastic processes and for periodic time series, analytical results can be obtained for network-derived quantities such as the degree distribution, the local clustering coefficient distribution, the mean path length, and others. HVGs have the potential to discern between deterministic-chaotic and correlated-stochastic time series. Here, we investigate the sensitivity of the HVG methodology to properties and pre-processing of real-world data, i.e., time series length, the presence of ties, and deseasonalization, using a set of around 150 runoff time series from managed rivers at daily resolution from Brazil with an average length of 65 years. We show that an application of HVGs on real-world time series requires a careful consideration of data pre-processing steps and analysis methodology before robust results and interpretations can be obtained. For example, one recent analysis of the degree distribution of runoff records reported pronounced sub-exponential “long-tailed” behavior of North American rivers, whereas another study of South American rivers showed hyper-exponential “short-tailed” behavior resembling correlated noise. We demonstrate, using the dataset of Brazilian rivers, that these apparently contradictory results can be reconciled by minor differences in data-preprocessing (here: small differences in subtracting the seasonal cycle). Hence, data-preprocessing that is conventional in hydrology (“deseasonalization”) changes long-term correlations and the overall runoff dynamics substantially, and we present empirical consequences and extensive simulations to investigate these issues from a HVG methodological perspective. After carefully accounting for these methodological aspects, the HVG analysis reveals that the river runoff dataset shows indeed complex behavior that appears to stem from a superposition of short-term correlated noise and “long-tailed behaviour,” i.e., highly connected nodes. Moreover, the construction of a dam along a river tends to increase short-term correlations in runoff series. In summary, the present study illustrates the (often substantial) effects of methodological and data-preprocessing choices for the interpretation of river runoff dynamics in the HVG framework and its general applicability for real-world time series.

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Introduction to Focus Issue: Nonlinear dynamics of non-equilibrium complex systems.

Descalzi, O.; Rosso, O. | CHAOS. 28(7). 075401. | 2018

No hay Abstract Disponible

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Feature evaluation for unsupervised bioacoustic signal segmentation of anuran calls.

Colonna, J.; Nakamura, E.; Rosso, O. | Expert Systems with Applications. 106: 105-120. | 2018

We present a comprehensive study of temporal Low-Level acoustic Descriptors (LLDs) to automatically segment anuran calls in audio streams. The acoustic segmentation, or syllable extraction, is a key task shared by most of the bioacoustical species recognition systems. Consequently, the syllable extraction has a direct impact on the classification rate. In this work, we assess several new entropy measures including the recently developed Permutation Entropy, Weighted Permutation Entropy, and Permutation Min-Entropy, and compare them to the classical Energy, Zero Crossing Rate and Spectral Entropy. In addition, we propose an algorithm to estimate the optimal segmentation threshold value used to separate deterministic segments from stochastic ones avoiding the creation of thin clusters. To assess the performance of our segmentation approach, we applied a frame-by-frame, a point-to-point and an event-to-event comparisons. We show that in a scenario with severe noise conditions (SNR ≤ 0dB), simple entropy descriptors are robust, achieving 97% of segmentation performance, while keeping a low computational cost. We conclude that there is no LLD that is suitable for all scenarios, and we must adopt multiple or different LLDs, depending on the expected noise conditions. Keywords: Unsupervised bioacoustics signal segmentation; Information theory; Permutation entropy; Colored noise

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Extended patchy ecosystems may increase their total biomass through self-replication

Tlidi, M.; Bordeu, I.; Clerc, M.; Escaff, D. | Ecological Indicators. https://doi.org/10.1016/j.ecolind.2018.02.009. | 2018

Patches of vegetation consist of dense clusters of shrubs, grass, or trees, often found to be circular characteristic size, defined by the properties of the vegetation and terrain. Therefore, vegetation patches can be interpreted as localized structures. Previous findings have shown that such localized structures can self-replicate in a binary fashion, where a single vegetation patch elongates and divides into two new patches, in a process resembling cellular mitosis. Here, we extend these previous results by considering the more general case, where the plants interact non-locally, this extension adds an extra level of complexity and shrinks the gap between the model and real ecosystems, where it is known that the plant-to-plant competition through roots and above-ground facilitating interactions have non-local effects, i.e. they extend further away than the nearest neighbor distance. Through numerical simulations, we show that for a moderate level of aridity, a transition from a single patch to periodic pattern occurs. Moreover, for large values of the hydric stress, we predict an opposing route to the formation of periodic patterns, where a homogeneous cover of vegetation may decay to spot-like patterns. The evolution of the biomass of vegetation patches can be used as an indicator of the state of an ecosystem, allowing to distinguish if a system is in a self-replicating or decaying dynamics. In an attempt to relate the theoretical predictions to real ecosystems, we analyze landscapes in Zambia and Mozambique, where vegetation forms patches of tens of meters in diameter. We show that the properties of the patches together with their spatial distributions are consistent with the self-organization hypothesis. We argue that the characteristics of the observed landscapes may be a consequence of patch self-replication, however, detailed field and temporal data is fundamental to assess the real state of the ecosystems.

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Discriminating imagined and non-imagined tasks in the motor cortex area: Entropy-complexity plane with a wavelet decomposition.

Roman Baravalle, Osvaldo A. Rosso, Fernando Montani. | Physica A: Statistical Mechanics and its Applications. 511: 27-39. | 2018

Electroencephalograms reflect the electrical activity of the brain, which can be considered ruled by a chaotic nonlinear dynamics. We consider human electroencephalogram recordings during different motor type activities, and when imagining that they perform this activity. We characterize the different dynamics of the cortex according to distinct motor and imagined movement tasks using an information theory approach and a wavelet decomposition. More specifically, we use the entropy-complexity plane in combination with the wavelet decomposition to precisely quantify the dynamics of the neuronal activity showing that the current theoretical framework allows us to distinguish realized and imagined tasks within the cortex. Keywords: EEG; Wavelet decomposition; Motor cortex; Motor and imagined movement tasks; Entropy; Complexity

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Detailed analysis of transitions in the CO oxidation on Palladium(111) under noisy conditions.

Cisternas, J.; Wehner, S. | Journal of Chemical Physics 149, 044706 (2018); doi: 10.1063/1.5040704. | 2018

It has been shown that CO oxidation on Pd(111) under ultrahigh vacuum conditions can suffer rare transitions between two stable states triggered by weak intrinsic perturbations. Here we study the effects of adding controlled noise by varying the concentrations of O2 and CO that feed the vacuum chamber, while the total flux stays constant. In addition to the regime of rare transitions between states of different CO2 reaction rates induced by intrinsic fluctuations, we found three distinct effects of external noise depending on its strength: small noise suppresses transitions and stabilizes the upper rate state; medium noise induces bursting; and large noise gives rise to reversible transitions in both directions. To explain some of the features present in the dynamics, we propose an extended stochastic model that includes a global coupling through the gas phase to account for the removal of CO gas caused by the adsorption of the Pd surface. The numerical simulations based in the model show a qualitative agreement with the noise-induced transitions found in experiments, but suggest that more complex spatial phenomena are present in the observed fluctuations.

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Complexity of simple, switched and skipped chaotic maps in finite precision.

Maximiliano Antonelli, Luciana De Micco, Hilda Larrondo and Osvaldo Anibal Rosso. | Entropy. 20:135. | 2018

In this paper we investigate the degradation of the statistic properties of chaotic maps as consequence of their implementation in a digital media such as Digital Signal Processors (DSP), Field Programmable Gate Arrays (FPGA) or Application-Specific Integrated Circuits (ASIC). In these systems, binary floating- and fixed-point are the numerical representations available. Fixed-point representation is preferred over floating-point when speed, low power and/or small circuit area are necessary. Then, in this paper we compare the degradation of fixed-point binary precision version of chaotic maps with the one obtained by using floating point 754-IEEE standard, to evaluate the feasibility of their FPGA implementation. The specific period that every fixed-point precision produces was investigated in previous reports. Statistical characteristics are also relevant, it has been recently shown that it is convenient to describe the statistical characteristic using both, causal and non-causal quantifiers. In this paper we complement the period analysis by characterizing the behavior of these maps from an statistical point of view using cuantifiers from information theory. Here, rather than reproducing an exact replica of the real system, the aim is to meet certain conditions related to the statistics of systems.

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Collisions of non-explosive dissipative solitons can induce explosions.

Descalzi, O.; Brand, HR. | CHAOS. 28(7). 075508. | 2018

We investigate the interaction of stationary and oscillatory dissipative solitons in the framework of two coupled cubic-quintic complex Ginzburg-Landau equation for counter-propagating waves. We analyze the case of a stabilizing as well as a destabilizing cubic cross-coupling between the counter-propagating dissipative solitons. The three types of interacting localized solutions investigated are stationary, oscillatory with one frequency, and oscillatory with two frequencies. We show that there is a large number of different outcomes as a result of these collisions including stationary as well as oscillatory bound states and compound states with one and two frequencies. The two most remarkable results are (a) the occurrence of bound states and compound states of exploding dissipative solitons as outcome of the collisions of stationary and oscillatory pulses; and (b) spatiotemporal disorder due to the creation, interaction, and annihilation of dissipative solitons for colliding oscillatory dissipative solitons as initial conditions.

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Causal Shannon-Fisher Characterization of Motor/Imagery Movements in EEG.

Román Baravalle, Osvaldo A. Rosso and Fernando Montani. | Entropy. 20(9). 660. | 2018

The electroencephalogram (EEG) is an electrophysiological monitoring method that allows us to glimpse the electrical activity of the brain. Neural oscillations patterns are perhaps the best salient feature of EEG as they are rhythmic activities of the brain that can be generated by interactions across neurons. Large-scale oscillations can be measured by EEG as the different oscillation patterns reflected within the different frequency bands, and can provide us with new insights into brain functions. In order to understand how information about the rhythmic activity of the brain during visuomotor/imagined cognitive tasks is encoded in the brain we precisely quantify the different features of the oscillatory patterns considering the Shannon–Fisher plane H × F . This allows us to distinguish the dynamics of rhythmic activities of the brain showing that the Beta band facilitate information transmission during visuomotor/imagined tasks.

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Bandt-Pompe symbolization dynamics for time series with tied values: A data-driven approach.

Francisco Traversaro, Francisco O. Redelico, Marcelo R. Risk, Alejandro C. Frery, and Osvaldo A. Rosso. | Chaos. 28: 075502. | 2018

In 2002, Bandt and Pompe [Phys. Rev. Lett. 88, 174102 (2002)] introduced a successfully symbolic encoding scheme based on the ordinal relation between the amplitude of neighboring values of a given data sequence, from which the permutation entropy can be evaluated. Equalities in the analyzed sequence, for example, repeated equal values, deserve special attention and treatment as was shown recently by Zunino and co-workers [Phys. Lett. A 381, 1883 (2017)]. A significant number of equal values can give rise to false conclusions regarding the underlying temporal structures in practical contexts. In the present contribution, we review the different existing methodologies for treating time series with tied values by classifying them according to their different strategies. In addition, a novel data-driven imputation is presented that proves to outperform the existing methodologies and avoid the false conclusions pointed by Zunino and co-workers.

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Analysis of ischaemic crisis using the informational causal entropy-complexity plane.

Walter Legnani, Francisco Traversaro, Francisco O. Redelico, Leandro J. Cymberknop, Ricardo L. Armentano, and Osvaldo A. Rosso. | Chaos. 28: 075518. | 2018

In the present work an ischaemic process, mainly focused on the reperfusion stage, is studied using the informational causal entropy-complexity plane. Ischaemic wall behavior under this condition was analyzed through wall thickness and ventricular pressure variations, acquired during an obstructive flow maneuver performed on left coronary arteries of surgically instrumented animals. Basically, the induction of ischaemia consisted on the temporary occlusion of left circumflex coronary artery (which supplies blood to the posterior left ventricular wall) for a few seconds. Normal perfusion of the wall was then reestablished while the anterior ventricular wall remained adequately perfused during the entire maneuver. The obtained results showed that system dynamics could be effectively described by entropy-complexity loops, in both abnormally and well perfused walls. These results could contribute to made an objective indicator of the recovery heart tissues after an ischaemic process, in a way to quantifies the restoration of myocardial behavior after the supply of oxygen to the ventricular wall was suppressed for a brief period.

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An analysis of high-frequency cryptocurrencies prices dynamics using permutation-information-theory quantifiers.

Bariviera, A.; Zunino, L.; Rosso, O. | Chaos. 28: 075511. | 2018

This paper discusses the dynamics of intraday prices of 12 cryptocurrencies during the past months’ boom and bust. The importance of this study lies in the extended coverage of the cryptoworld, accounting for more than 90% of the total daily turnover. By using the complexity-entropy causality plane, we could discriminate three different dynamics in the data set. Whereas most of the cryptocurrencies follow a similar pattern, there are two currencies (ETC and ETH) that exhibit a more persistent stochastic dynamics, and two other currencies (DASH and XEM) whose behavior is closer to a random walk. Consequently, similar financial assets, using blockchain technology, are differentiated by market participants.

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A continuous-time persistent random walk model for flocking

Escaff, D.; Toral, R.Van den Broeck, C.; Lindenberg, K. | Chaos: An Interdisciplinary Journal of Nonlinear Science. Chaos 28, 075507 (2018); doi: 10.1063/1.5027734 | 2018

A classical random walker is characterized by a random position and velocity. This sort of random walk was originally proposed by Einstein to model Brownian motion and to demonstrate the existence of atoms and molecules. Such a walker represents an inanimate particle driven by environmental fluctuations. On the other hand, there are many examples of so-called “persistent random walkers,” including self-propelled particles that are able to move with almost constant speed while randomly changing their direction of motion. Examples include living entities (ranging from flagellated unicellular organisms to complex animals such as birds and fish), as well as synthetic materials. Here we discuss such persistent non-interacting random walkers as a model for active particles. We also present a model that includes interactions among particles, leading to a transition to flocking, that is, to a net flux where the majority of the particles move in the same direction. Moreover, the model exhibits secondary transitions that lead to clustering and more complex spatially structured states of flocking. We analyze all these transitions in terms of bifurcations using a number of mean field strategies (all to all interaction and advection-reaction equations for the spatially structured states), and compare these results with direct numerical simulations of ensembles of these interacting active particles.

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“A study of the sensitivity of sequence stacking strategies for the storage location assignment problem for out-bound containers in a maritime terminal”

Guerra, R.; Smith, N.R.; González, R.G.; Cárdenas, L. | International Journal of System Assurance Engineering and Management (2018) 9(5): 1057-1062. | 2018

Recently, a new approach to solve the outbound container location problem motivated by the Shanghai maritime terminals was published. This approach addresses the problem by decomposing it into two stages. The first stage is a mathematical programming model and the second stage is a heuristic algorithm whose objective is to minimize the total reshuffle movements executed during the loading operation. That study reports that the diagonal stacking configuration provides the best performance. Conversely, this paper documents the results of a study to observe the performance of the various staking strategies under different conditions that can occur regularly in real ports. The parameters that are varied are the number of tiers in each stack, the number of container weight levels, and the permitted bay utilization. The results show that although the diagonal stacking strategy does provide the best performance under some conditions, it does not yield the best performance in other parameter combinations. The horizontal strategy is found to perform best for most of the parameter combinations considered in this study.

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Stochastic thermodynamics for Ising chain and symmetric exclusion process.

Toral, R.; Van den Broeck, C.; Escaff, D.; Lindenberg, K. | Physical Review E. 95: 032114. | 2017

We verify the finite-time fluctuation theorem for a linear Ising chain in contact with heat reservoirs at its ends. Analytic results are derived for a chain consisting of two spins. The system can be mapped onto a model for particle transport, namely, the symmetric exclusion process in contact with thermal and particle reservoirs. We modify the symmetric exclusion process to represent a thermal engine and reproduce universal features of the efficiency at maximum power.

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Stochastic and Higher-Order Effects on Exploding Pulses.

Descalzi, O.; Cartes, C. | Applied Science Basel. 7(9): 887. | 2017

The influence of additive noise, multiplicative noise, and higher-order effects on exploding solitons in the framework of the prototype complex cubic-quintic Ginzburg-Landau equation is studied. Transitions from explosions to filling-in to the noisy spatially homogeneous finite amplitude solution, collapse (zero solution), and periodic exploding dissipative solitons are reported.

Keywords: exploding solitons; Ginzburg-Landau equation; mode-locked fiber lasers

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Real-time acquisition of complex optical fields by binary amplitude modulation.

Peters, E.; Clemente, P.; Salvador-Balaguer, E.; Tajahuerce, E.; Andrés, P.; Pérez, D.; Lancis, J. | Optics letters 42 (10), 2030-2033. | 2017

We describe, through simulations and experiments, a real-time wavefront acquisition technique using random binary amplitude masks and an iterative phase retrieval algorithm based on the Fresnel propagator. By using a digital micromirror device, it is possible to recover an unknown complex object by illuminating with this set of masks and simultaneously recording the resulting intensity patterns with a high-speed camera, making this technique suitable for dynamic applications.

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Permutation entropy based time series analysis: Equalities in the input signal can lead to false conclusions.

Luciano Zunino, Felipe Olivares, Felix Scholkmann, Osvaldo A. Rosso. | Physics Letters A. 381(22): 1883-1892. | 2017

A symbolic encoding scheme, based on the ordinal relation between the amplitude of neighboring values of a given data sequence, should be implemented before estimating the permutation entropy. Consequently, equalities in the analyzed signal, i.e. repeated equal values, deserve special attention and treatment. In this work, we carefully study the effect that the presence of equalities has on permutation entropy estimated values when these ties are symbolized, as it is commonly done, according to their order of appearance. On the one hand, the analysis of computer-generated time series is initially developed to understand the incidence of repeated values on permutation entropy estimations in controlled scenarios. The presence of temporal correlations is erroneously concluded when true pseudorandom time series with low amplitude resolutions are considered. On the other hand, the analysis of real-world data is included to illustrate how the presence of a significant number of equal values can give rise to false conclusions regarding the underlying temporal structures in practical contexts. Keywords: Time series analysis; Permutation entropy; Equalities; Spurious temporal correlations

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On the influence of additive and multiplicative noise on holes in dissipative systems.

Descalzi, O.; Cartes, C.; Brand, H. | CHAOS. 27(5). 053101. | 2017

We investigate the influence of noise on deterministically stable holes in the cubic-quintic complex Ginzburg-Landau equation. Inspired by experimental possibilities, we specifically study two types of noise: additive noise delta-correlated in space and spatially homogeneous multiplicative noise on the formation of π-holes and 2π-holes. Our results include the following main features. For large enough additive noise, we always find a transition to the noisy version of the spatially homogeneous finite amplitude solution, while for sufficiently large multiplicative noise, a collapse occurs to the zero amplitude solution. The latter type of behavior, while unexpected deterministically, can be traced back to a characteristic feature of multiplicative noise; the zero solution acts as the analogue of an absorbing boundary: once trapped at zero, the system cannot escape. For 2π-holes, which exist deterministically over a fairly small range of values of subcriticality, one can induce a transition to a π-hole (for additive noise) or to a noise-sustained pulse (for multiplicative noise). This observation opens the possibility of noise-induced switching back and forth from and to 2π-holes.

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Multiscale permutation entropy analysis of laser beam wandering in isotropic turbulence.

Felipe Olivares, Luciano Zunino, Damián Gulich, Darío G. Pérez, Osvaldo A. Rosso. | Physical Review E. 96: 042207. | 2017

We have experimentally quantified the temporal structural diversity from the coordinate fluctua-tions of a laser beam propagating through isotropic optical turbulence. The main focus here is on thecharacterization of the long-range correlations in the wandering of a thin Gaussian laser beam overa screen after propagating through a turbulent medium. To fulfill this goal, a laboratory-controlledexperiment was conducted in which coordinate fluctuations of the laser beam were recorded at asufficiently high sampling rate for a wide range of turbulent conditions. Horizontal and verticaldisplacements of the laser beam centroid were subsequently analyzed by implementing the symbolictechnique based on ordinal patterns to estimate the well-known permutation entropy. We showthat the permutation entropy estimations at multiple time scales evidence an interplay betweendifferent dynamical behaviors. More specifically, a crossover between two different scaling regimesis observed. We confirm a transition from an integrated stochastic process contaminated with elec-tronic noise to a fractional Brownian motion with a Hurst exponent H= 5/6 as the sampling timeincreases. Besides, we are able to quantify, from the estimated entropy, the amount of electronicnoise as a function of the turbulence strength. We have also demonstrated that these experimentalobservations are in very good agreement with numerical simulations of noisy fractional Brownianmotions with a well-defined crossover between two different scaling regimes.

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Model selection: Using information measures from ordinal symbolic analysis to select model sub-grid scale parameterizations.

Pulido, M.; Rosso, O. | Journal of the Atmospheric Science. 10.1175/JAS-D-16-0340.1 | 2017

The use of information measures for model selection in geophysical models with subgrid parameterizations is examined. Although the resolved dynamical equations of atmospheric or oceanic global numerical models are well established, the development and evaluation of parameterizations that represent subgrid-scale effects pose a big challenge. For climate studies, the parameters or parameterizations are usually selected according to a root-mean-square error criterion that measures the differences between the model-state evolution and observations along the trajectory. However, inaccurate initial conditions and systematic model errors contaminate root-mean-square error measures. In this work, information theory quantifiers, in particular Shannon entropy, statistical complexity, and Jensen–Shannon divergence, are evaluated as measures of the model dynamics. An ordinal analysis is conducted using the Bandt–Pompe symbolic data reduction in the signals. The proposed ordinal information measures are examined in the two-scale Lorenz-96 system. By comparing the two-scale Lorenz-96 system signals with a one-scale Lorenz-96 system with deterministic and stochastic parameterizations, the study shows that information measures are able to select the correct model and to distinguish the parameterizations, including the degree of stochasticity that results in the closest model dynamics to the two-scale Lorenz-96 system. Keywords: Lyapunov vectors; Data assimilation; Optimization; Subgrid-scale processes

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Evaluation of the status of rotary machines by time causal Information Theory quantifiers.

Francisco O. Redelico, Francisco Traversaro, Nicolás Oyarzabal, IvanVilaboa, Osvaldo A.Rosso. | Physica A: Statistical Mechanics and its Applications. 470(15): 321-329 | 2017

In this paper several causal Information Theory quantifiers, i.e. Shannon entropy, statistical complexity and Fisher information using the Bandt and Pompe permutation probability distribution, measure are applied to describe the behavior of a rotating machine. An experiment was conducted where a rotating machine runs balanced and then, after a misalignment, runs unbalanced. All the causal Information Theory quantifiers applied are capable to distinguish between both states and grasp the corresponding transition between them. Keywords: Permutation entropy; Permutation statistical complexity; Permutation Fisher information measure; Rotary machines; Fault diagnosis

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Characterization of electric load with Information Theory quantifiers.

Andre L.L. Aquino, Heitor S.Ramos, Alejandro C.Frery, Leonardo P. Viana, Tamer S.G. Cavalcante, Osvaldo A. Rosso. | Physica A: Statistical Mechanics and its Applications. 465(1): 277-284 | 2017

This paper presents a study of the electric load behavior based on the Causality Complexity–Entropy Plane. We use a public data set, namely REDD, which contains detailed power usage information from several domestic appliances. In our characterization, we use the available power data of the circuit/devices of all houses. The Bandt–Pompe methodology combined with the Causality Complexity–Entropy Plane was used to identify and characterize regimes and behaviors over these data. The results showed that this characterization provides a useful insight into the underlying dynamics that govern the electric load. Keywords: Causality Complexity–Entropy Plane (CCEP); Electric load; Information Theory; Signal processing

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Arrays of two-state stochastic oscillators: Roles of tail and range of interactions.

Rosas, A.; Escaff, D.; Lima, I.; Lindenberg, K. | Physical Review E. 95: 032104. | 2017

We study the role of the tail and the range of interaction in a spatially structured population of two-state on-off units governed by Markovian transition rates. The coupling among the oscillators is evidenced by the dependence of the transition rates of each unit on the states of the units to which it is coupled. Tuning the tail or range of the interactions, we observe a transition from an ordered global state (long-range interactions) to a disordered one (short-range interactions). Depending on the interaction kernel, the transition may be smooth (second order) or abrupt (first order). We analyze the transient, which may present different routes to the steady state with vastly different time scales.

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A simple and fast representation space for classifying complex time series.

Luciano Zunino, Felipe Olivares, Aurelio Bariviera, Osvaldo A. Rosso. | Physics Letter A. 381(11): 1021-1028. | 2017

In the context of time series analysis considerable effort has been directed towards the implementation of efficient discriminating statistical quantifiers. Very recently, a simple and fast representation space has been introduced, namely the number of turning points versus the Abbe value. It is able to separate time series from stationary and non-stationary processes with long-range dependences. In this work we show that this bidimensional approach is useful for distinguishing complex time series: different sets of financial and physiological data are efficiently discriminated. Additionally, a multiscale generalization that takes into account the multiple time scales often involved in complex systems has been also proposed. This multiscale analysis is essential to reach a higher discriminative power between physiological time series in health and disease. Keywords: Time series analysis; Abbe value; Turning points; Financial data; Electroencephalogram data; Heart rate variability

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A Path integral approach to the Hodgkin-Huxley Model

Baravalle, R.; Rosso, O.; Montani, F. | Physica A. 486:986-999. | 2017

To understand how single neurons process sensory information, it is necessary to develop suitable stochastic models to describe the response variability of the recorded spike trains. Spikes in a given neuron are produced by the synergistic action of sodium and potassium of the voltage-dependent channels that open or close the gates. Hodgkin and Huxley (HH) equations describe the ionic mechanisms underlying the initiation and propagation of action potentials, through a set of nonlinear ordinary differential equations that approximate the electrical characteristics of the excitable cell. Path integral provides an adequate approach to compute quantities such as transition probabilities, and any stochastic system can be expressed in terms of this methodology. We use the technique of path integrals to determine the analytical solution driven by a non-Gaussian colored noise when considering the HH equations as a stochastic system. The different neuronal dynamics are investigated by estimating the path integral solutions driven by a non-Gaussian colored noise . More specifically we take into account the correlational structures of the complex neuronal signals not just by estimating the transition probability associated to the Gaussian approach of the stochastic HH equations, but instead considering much more subtle processes accounting for the non-Gaussian noise that could be induced by the surrounding neural network and by feedforward correlations. This allows us to investigate the underlying dynamics of the neural system when different scenarios of noise correlations are considered. Keywords: Neuronal model; Path integrals; Stochastic processes; Spiking output; Neural coding

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Arrays of two-state stochastic oscillators: Roles of tail and range of interactions

Alexandre Rosas, Daniel Escaff, Italo’Ivo Lima Dias Pinto and Katja Lindenberg | Physical Review E, 95, 032104 | 2017

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Stochastic thermodynamics for Ising chain and symmetric exclusion process

Raúl Toral, C. Van den Broeck, Daniel Escaff, and Katja Lindenberg. | Physical Review E, 95, 032114 | 2017

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Time series characterization via horizontal visibility graph and Information Theory.

Goncalves, Bruna Amin, Carpi, Laura, Rosso, Osvaldo A., Ravetti, Martin G., | Physica A-Statistical Mechanics and Its Applications. 464: 93-102. | 2016

Complex networks theory have gained wider applicability since methods for transformation of time series to networks were proposed and successfully tested. In the last few years, horizontal visibility graph has become a popular method due to its simplicity and good results when applied to natural and artificially generated data. In this work, we explore different ways of extracting information from the network constructed from the horizontal visibility graph and evaluated by Information Theory quantifiers. Most works use the degree distribution of the network, however, we found alternative probability distributions, more efficient than the degree distribution in characterizing dynamical systems. In particular, we find that, when using distributions based on distances and amplitude values, significant shorter time series are required. We analyze fractional Brownian motion time series, and a paleoclimatic proxy record of ENSO from the Pallcacocha Lake to study dynamical changes during the Holocene. Keywords: Time series analysis; Complex networks; Information Theory quantifiers

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Synchronization of coupled noisy oscillators: Coarse graining from continuous to discrete phases

Daniel Escaff, Alexandre Rosas, Raúl Toral, and Katja Lindenberg. | PHYSICAL REVIEW E 94, 052219. | 2016

The theoretical description of synchronization phenomena often relies on coupled units of continuous time noisy Markov chains with a small number of states in each unit. It is frequently assumed, either explicitly or implicitly, that coupled discrete-state noisy Markov units can be used to model mathematically more complex coupled noisy continuous phase oscillators. In this work we explore conditions that justify this assumption by coarse graining continuous phase units. In particular, we determine the minimum number of states necessary to justify this correspondence for Kuramoto-like oscillators.

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Periodic exploding dissipative solitons.

Cartes, C.; Descalzi, O. | Physical Review A. 93. 031801(R). DOI: 10.1103/PhysRevA.93.031801. | 2016

We show the existence of periodic exploding dissipative solitons. These nonchaotic explosions appear when higher-order nonlinear and dispersive effects are added to the complex cubic-quintic Ginzburg-Landau equation modeling fiber soliton lasers. This counterintuitive phenomenon is the result of period-halving bifurcations leading to order (periodic explosions), followed by period-doubling bifurcations leading to chaos (chaotic explosions).

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Multiplicative noise can lead to the collapse of dissipative solitons.

Descalzi, O.; Cartes, C; Brand, B.; Helmut, R. | Physical Review E. 94(1): 012219. | 2016

We investigate the influence of spatially homogeneous multiplicative noise on the formation of localized patterns in the framework of the cubic-quintic complex Ginzburg-Landau equation. We find that for sufficiently large multiplicative noise the formation of stationary and temporally periodic dissipative solitons is suppressed. This result is characterized by a linear relation between the bifurcation parameter and the noise amplitude required for suppression. For the regime associated with exploding dissipative solitons we find a reduction in the number of explosions for larger noise strength as well as a conversion to other types of dissipative solitons or to filling-in and eventually a collapse to the zero solution.

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Monitoring the informational efficiency of European corporate bond markets with dynamical permutation min-entropy.

Luciano Zunino, Aurelio F. Bariviera, M. Belén Guercio, Lisana B. Martinez, Osvaldo A. Rosso. | Physica A. 456: 1-9. | 2016

In this paper the permutation min-entropy has been implemented to unveil the presence of temporal structures in the daily values of European corporate bond indices from April 2001 to August 2015. More precisely, the informational efficiency evolution of the prices of fifteen sectorial indices has been carefully studied by estimating this information-theory-derived symbolic tool over a sliding time window. Such a dynamical analysis makes possible to obtain relevant conclusions about the effect that the 2008 credit crisis has had on the different European corporate bond sectors. It is found that the informational efficiency of some sectors, namely banks, financial services, insurance, and basic resources, has been strongly reduced due to the financial crisis whereas another set of sectors, integrated by chemicals, automobiles, media, energy, construction, industrial goods & services, technology, and telecommunications has only suffered a transitory loss of efficiency. Last but not least, the food & beverage, healthcare, and utilities sectors show a behavior close to a random walk practically along all the period of analysis, confirming a remarkable immunity against the 2008 financial crisis.

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Libor at crossroads: Stochastic switching detection using information theory quantifiers.

Bariviera, A.; Guercio, B.; Martinez, M.; Lisana, B.; Rosso, B.; Osvaldo, A. | Chaos Solitions & Fractals. 88: 172-182. | 2016

This paper studies the 28 time series of Libor rates, classified in seven maturities and four currencies, during the last 14 years. The analysis was performed using a novel technique in financial economics: the Complexity–Entropy Causality Plane. This planar representation allows the discrimination of different stochastic and chaotic regimes. Using a temporal analysis based on moving windows, this paper unveils an abnormal movement of Libor time series around the period of the 2007 financial crisis. This alteration in the stochastic dynamics of Libor is contemporary of what press called “Libor scandal”, i.e. the manipulation of interest rates carried out by several prime banks. We argue that our methodology is suitable as a market watch mechanism, as it makes visible the temporal redution in informational efficiency of the market.

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Globally coupled stochastic two-state oscillators: synchronization of infinite and finite arrays.

Rosas, A.; Escaff, D.; Lima Dias Pinto, I.; Lindenberg, K. | Journal of Physics A: Mathematical and Theoretical. 49. 095001. | 2016

We consider arrays of the simplest two-state (on–off) stochastic units. The units are Markovian, that is, the transitions between the two states occur at a given rate. We construct arrays of N globally coupled binary units, and observe a remarkable richness of behavior as the control parameter that measures the coupling strength is increased. In the mean field limit as $N\to \infty $ we consider the four simplest polynomial forms of coupling that lead to bifurcations, and characterize the associated phase transitions of the arrays. When N is finite there are fluctuations about the well-defined steady states of the infinite arrays. We study the nature of these fluctuations and their effects on the bifurcations in all cases by constructing the appropriate Langevin equations and the associated Fokker–Planck equations.

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Anomalous Diffusion of Dissipative Solitons in the Cubic-Quintic Complex Ginzburg-Landau Equation in Two Spatial Dimensions

Cisternas, J.; Descalzi, O.; Albers, T.; Radons, G.; | Physical Review Letters 116, 203901. | 2016

We demonstrate the occurrence of anomalous diffusion of dissipative solitons in a “simple” and deterministic prototype model: the cubic-quintic complex Ginzburg-Landau equation in two spatial dimensions. The main features of their dynamics, induced by symmetric-asymmetric explosions, can be modeled by a subdiffusive continuous-time random walk, while in the case dominated by only asymmetric explosions, it becomes characterized by normal diffusion.

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Development of an anisotropic turbulence model for laser propagation in the atmosphere.

Gustavo Funes | FAI | 2016

Nowadays many devices use a laser beam for diff erent purposes, as it has become a common tool in everyday living. In science, laser has become a top instrument not only in optics but also in metrology. The propagation of laser beams in a turbulent atmosphere has become more and more interesting due to the possibility of using high-data-rate optical transmitters for satellite-communication channels and lasercom systems connecting groundairborne- space or space-airborne-ground data links. This subject also o ffers a wide range of possible applications aside from free-space optical telecommunications (FSO), like remote sensing, target pointing and tracking, etc. But all of these applications have one common enemy, Earth’s atmosphere causes serious degradation of the reliability of such optical communication channels. Moreover, theoretical results are often insu fficient to match experimental data. The main problem is that all theoretical approaches have been based on common assumptions about the atmospheric turbulence through which the optical wave travels. For example, it is usual to suppose that the turbulence is homogeneous and isotropic, with a fixed power law spectrum in the inertial range of scales. Also, there are spectrum cutoff s at small and large scales that are quantitatively represented by numerical values of inner and outer scales.

Based on the previous statements the aim of this project is to develop a new theoretical model, that has a strong connection with phenomenology than the regular ones. We expect that this new model could make a good representation of the turbulence under weak conditions and also, could be extended to the other turbulence regimes such as anisotropic behavior or non-Kolmogorov turbulence.

Hypothetically a region of eddies with random variations of the air refraction index could simulate the atmospheric turbulence if certain scaling conditions are applied. This model is called Quasi-wavelets and was applied previously for sound propagation and temperature fluctuations with good results. Recently we have published an article in which we test this model for the propagation of a laser beam and proved to be valid theoretically in ideal conditions.

As mentioned before, the atmosphere has a random behavior and is clearly not stationary since there are considerable transient events that perturb laser beam propagation, creating wavefront distortions and high intensity deviations. This is due to lateral winds or an increment in the energy budget that generates the perturbation.
Since the Quasi-Wavelet model basically builds the region of turbulence, some hypotheses like uniform distribution of fluctuations and isotropy can be changed to more realistic conditions that could be encountered in the real atmosphere. This is the key to creating a new model that can be either calculated analytically or simulated by computers.


Globally coupled stochastic two-state oscillators: synchronization of infinite and finite arrays

Alexandre Rosas, Daniel Escaff, Italo’Ivo Lima Dias Pinto and Katja Lindenberg | Journal of Physics A: Mathematical and Theoretical, 49, 095001 | 2016


Synchronization of coupled noisy oscillators: Coarse graining from continuous to discrete phases

Daniel Escaff, Alexandre Rosas, Raúl Toral, and Katja Lindenberg | Physical Review E, 94, 052219 | 2016


Periodic and Chaotic Exploding Dissipative Solitons.

Cartes, C.; Descalzi, O. | FIBER AND INTEGRATED OPTICS. 34(1-2): 14-22. | 2015

This article shows for the first time the existence of periodic exploding dissipative solitons. These non-chaotic explosions appear when higher-order non-linear and dispersive effects are added to the complex cubic–quintic Ginzburg–Landau equation modeling soliton transmission lines. This counter-intuitive phenomenon is the result of period-halving bifurcations leading to order (periodic explosions), followed by period-doubling bifurcations leading to chaos (chaotic explosions). This periodic behavior is persistent even when small amounts of noise are added to the system. Since for ultrashort optical pulses it is necessary to include these higher-order effects, it is conjectured that the predictions can be tested in mode-locked lasers.

Keywords: chaotic explosionscomplex; cubic–quintic Ginzburg–Landau equations; periodic explosions

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On a quasi-wavelet model of refractive index fluctuations due to atmospheric turbulence.

Perez, D; Funes, G. | Vol. 23, No. 25 | DOI:10.1364/OE.23.031627 | OPTICS EXPRESS 31627 | 2015

When studying light propagation through the atmosphere, it is usual to rely on widely used spectra such as the modified von Kármán or Andrews-Hill. These are relatively tractable models for the fluctuations of the refractive index, and are primarily used because of their mathematical convenience. They correctly describe the fluctuations behaviour at the inertial range yet lack any physical basis outside this range. In recent years, deviations from the Obukhov-Kolmogorov theory (e. g. interminttency, partially developed turbulence, etc.) have been built upon these models through the introduction of arbitrary spectral power laws. Here we introduce a quasi-wavelet model for the refractive index fluctuations which is based on a phenomenological representation of the Richardson cascade. Under this model, the atmospheric refractive index has a correct spectral representation for the inertial range, behaves as expected outside it, and even accounts for non-Kolmogorov behaviour; moreover, it has non-Gaussian statistics. Finally, we are able to produce second order moments under the Rytov approximation for the complex phase; we estimate the angle-of-arrival as an example of application.

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Non-unique results of collisions of quasi-one-dimensional dissipative solitons.

Descalzi, O.; Brand, H. | Philosophical Transactions A. 2015 373 20150115; DOI: 10.1098/rsta.2015.0115. | 2015

We investigate collisions of quasi-one-dimensional dissipative solitons (DSs) for a large class of initial conditions, which are not temporally asymptotic quasi-one-dimensional DSs. For the case of sufficiently small approach velocity and sufficiently large values of the dissipative cross-coupling between the counter-propagating DSs, we find non-unique results for the outcome of collisions. We demonstrate that these non-unique results are intrinsically related to a modulation instability along the crest of the quasi-one-dimensional objects. As a model, we use coupled cubic–quintic complex Ginzburg–Landau equations. Among the final results found are stationary and oscillatory compound states as well as more complex assemblies consisting of quasi-one-dimensional and localized states. We analyse to what extent the final results can be described by the solutions of one cubic–quintic complex Ginzburg–Landau equation with effective parameters.

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Noisy localized structures induced by large noise.

Descalzi, O.; Cartes, C.; Brand, H. | PHYSICAL REVIEW E. 91(2). | 2015

We investigate the influence of large noise on the formation of localized patterns in the framework of the cubic-quintic complex Ginzburg-Landau equation. The interaction of localization and noise can lead to filling in or noisy localized structures for fixed noise strength. To focus on the interaction between noise and localization we cover a region in parameter space, in particular, subcriticality, for which stationary stable deterministic pulses do not exist. Possible experimental tests of the work presented for autocatalytic chemical reactions and bioinspired systems are outlined.

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Localized vegetation patterns, fairy circles, and localized patches in arid landscapes.

Escaff, D.; Fernandez-Oto, C.; Clerc, M. G.; M. Tlidi. | PHYSICAL REVIEW E. 91(2) | 2015

We investigate the formation of localized structures with varying widths in one- and two-dimensional systems. The mechanism of stabilization is attributed to strongly nonlocal coupling mediated by a Lorentzian type of kernel. We show that, in addition to stable dips found recently [see, e.g. Fernandez-Oto et al., Phys. Rev. Lett. 110, 174101 (2013)], there are stable localized peaks which appear as a result of strongly nonlocal coupling. We applied this mechanism to arid ecosystems by considering a prototype model of a Nagumo type. In one dimension, we study the front connecting the stable uniformly vegetated state to the bare one under the effect of strongly nonlocal coupling. We show that strongly nonlocal coupling stabilizes both—dip and peak—localized structures. We show analytically and numerically that the width of a localized structure, which we interpret as a fairy circle, increases strongly with the aridity parameter. This prediction is in agreement with published observations. In addition, we predict that the width of localized patch decreases with the degree of aridity. Numerical results are in close agreement with analytical predictions.

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Localized plateau beam resulting from strong nonlocal coupling in a cavity filled by metamaterials and liquid-crystal cells.

Tlidi, M.; Fernandez-Oto, C.; Clerc, M.; Escaff, D.: Kockaert, P. | Physical Review A, 92, 053838. | 2015

We investigate the formation of a localized plateau beam in the transverse section of a nonlinear optical ring cavity filled with a metamaterial and a nonlocal medium such as a nematic liquid crystal. We show that, far from the modulational instability regime, localized structures with a varying width may be stable in one and two-dimensional settings. The mechanism of stabilization is related with strong nonlocal coupling mediated by a Lorentzian type of kernel. We show that there exists stable bright and dark localized structures. A reduction of Lugiato–Lefever equation in the regime close to the nascent bistability allows us to analytically derive a simple formula for the width of localized structures in one-dimensional systems. Direct numerical simulations of the dynamical model agree with the analytical predictions.

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Interaction of exploding dissipative solitons.

Descalzi, O.; Brand, H. | THE EUROPEAN PHYSICAL JOURNAL B. 88: 219. | 2015

We investigate the collisions of two counter-propagating exploding dissipative solitons (DSs). We demonstrate that six different outcomes can occur as a function of the nonlinear cross-coupling between the counter-propagating waves: complete interpenetration, one compound exploding DS as well as four types of two compound DSs that can be stationary, have one or two frequencies or are exploding. Since exploding DSs have been observed experimentally predominantly in nonlinear optics, we conjecture that our predictions for their interactions can be tested in laser systems.

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Complex wavefront reconstruction from multiple-image planes produced by a focus tunable lens.

Mosso, F.; Peters, E.; Pérez, D. | Optics letters 40 (20), 4623-4626. | 2015

We propose, through simulations and experiments, a wavefront reconstruction technique using a focus-tunable lens and a phase-retrieval technique. A collimated beam illuminates a complex object (amplitude and phase), and a diffuser then modulates the outgoing wavefront. Finally the diffracted complex field reaches the focus-tunable lens, and a CMOS camera positioned at a fixed plane registers the subjective speckle distribution produced by the lens (one pattern for each focal length). We have demonstrated that a tunable lens can replace the translation stage used in the conventional single-beam, multiple-intensity reconstruction algorithm. In other words, through iterations with a modified version of this algorithm, the speckle images produced by different focal lengths can be successfully employed to recover the initial complex object. With no movable elements, (speckle) image sampling can be performed at high frame rates, which is suitable for dynamical reconstruction applications.

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Coarse-grained clustering dynamics of heterogeneously coupled neurons.

Moon, S.J.; Cook, K.A.; Rajendran, K.; Kevrekidis, I.G.; Cisternas, J.; Laing, C. | J. of Mathematical Neuroscience 5:2. | 2015

The formation of oscillating phase clusters in a network of identical Hodgkin–Huxley neurons is studied, along with their dynamic behavior. The neurons are synaptically coupled in an all-to-all manner, yet the synaptic coupling characteristic time is heterogeneous across the connections. In a network of N neurons where this heterogeneity is characterized by a prescribed random variable, the oscillatory single-cluster state can transition—through (possibly perturbed) period-doubling and subsequent bifurcations—to a variety of multiple-cluster states. The clustering dynamic behavior is computationally studied both at the detailed and the coarse-grained levels, and a numerical approach that can enable studying the coarse-grained dynamics in a network of arbitrarily large size is suggested. Among a number of cluster states formed, double clusters, composed of nearly equal sub-network sizes are seen to be stable; interestingly, the heterogeneity parameter in each of the double-cluster components tends to be consistent with the random variable over the entire network: Given a double-cluster state, permuting the dynamical variables of the neurons can lead to a combinatorially large number of different, yet similar “fine” states that appear practically identical at the coarse-grained level. For weak heterogeneity we find that correlations rapidly develop, within each cluster, between the neuron’s “identity” (its own value of the heterogeneity parameter) and its dynamical state. For single- and double-cluster states we demonstrate an effective coarse-graining approach that uses the Polynomial Chaos expansion to succinctly describe the dynamics by these quickly established “identity-state” correlations. This coarse-graining approach is utilized, within the equation-free framework, to perform efficient computations of the neuron ensemble dynamics.

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Localized vegetation patterns, fairy circles, and localized patches in arid landscapes

Escaff, D.; Fernandez-Oto, C.; Clerc, M. G.; M. Tlidi | Physical Review E | 2015


Noisy localized structures induced by large noise

Descalzi, Orazio; Cartes, Carlos; Brand, Helmut R | Physical Review E | 2015

We investigate the influence of large noise on the formation of localized patterns in the framework of the cubic-quintic complex Ginzburg-Landau equation. The interaction of localization and noise can lead to filling in or noisy localized structures for fixed noise strength. To focus on the interaction between noise and localization we cover a region in parameter space, in particular, subcriticality, for which stationary stable deterministic pulses do not exist. Possible experimental tests of the work presented for autocatalytic chemical reactions and bioinspired systems are outlined.


Turbulence-induced persistence in laser beam wandering

Luciano Zunino, Damián Gulich, Gustavo Funes, and Darío G. Pérez | Optics Letters | 2015

We have experimentally confirmed the presence of long-memory correlations in the wandering of a thin Gaussian laser beam over a screen after propagating through a turbulent medium. A laboratory-controlled experiment was conducted in which coordinate fluctuations of the laser beam were recorded at a sufficiently high sampling rate for a wide range of turbulent conditions. Horizontal and vertical displacements of the laser beam centroid were subsequently analyzed by implementing detrended fluctuation analysis. This is a very well-known and widely used methodology to unveil memory effects from time series. Results obtained from this experimental analysis allow us to confirm that both coordinates behave as highly persistent signals for strong turbulent intensities. This finding is relevant for a better comprehension and modeling of the turbulence effects in free-space optical communication systems and other applications related to propagation of optical signals in the atmosphere.

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Periodic and Chaotic Exploding Dissipative Solitons

Cartes, Carlos; Descalzi, Orazio | Fiber and Integrated Optics | 2015

This article shows for the first time the existence of periodic exploding dissipative solitons. These non-chaotic explosions appear when higher-order non-linear and dispersive effects are added to the complex cubic–quintic Ginzburg–Landau equation modeling soliton transmission lines. This counter-intuitive phenomenon is the result of period-halving bifurcations leading to order (periodic explosions), followed by period-doubling bifurcations leading to chaos (chaotic explosions). This periodic behavior is persistent even when small amounts of noise are added to the system. Since for ultrashort optical pulses it is necessary to include these higher-order effects, it is conjectured that the predictions can be tested in mode-locked lasers.

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On a quasi-wavelet model of refractive index fluctuations due to atmospheric turbulence

Pérez DG, Funes G. | Opt Express | 2015

When studying light propagation through the atmosphere, it is usual to rely on widely used spectra such as the modified von Kármán or Andrews-Hill. These are relatively tractable models for the fluctuations of the refractive index, and are primarily used because of their mathematical convenience. They correctly describe the fluctuations behaviour at the inertial range yet lack any physical basis outside this range. In recent years, deviations from the Obukhov-Kolmogorov theory (e. g. interminttency, partially developed turbulence, etc.) have been built upon these models through the introduction of arbitrary spectral power laws. Here we introduce a quasi-wavelet model for the refractive index fluctuations which is based on a phenomenological representation of the Richardson cascade. Under this model, the atmospheric refractive index has a correct spectral representation for the inertial range, behaves as expected outside it, and even accounts for non-Kolmogorov behaviour; moreover, it has non-Gaussian statistics. Finally, we are able to produce second order moments under the Rytov approximation for the complex phase; we estimate the angle-of-arrival as an example of application.

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Estimation of Cn² based on scintillation of fixed targets imaged through atmospheric turbulence

Gulich D, Funes G, Pérez D, Zunino L. | Opt Lett | 2015


Orbital-angular-momentum crosstalk and temporal fading in a terrestrial laser link using single-mode fiber coupling

Funes G, Vial M, Anguita JA. | Opt Express | 2015

Using a mobile experimental testbed, we perform a series of measurements on the detection of laser beams carrying orbital angular momentum (OAM) to evaluate turbulent channel distortions and crosstalk among receive states in an 84-m roofed optical link. We find that a receiver assembly using single-mode fiber coupling serves as a good signal selector in terms of crosstalk rejection. From the recorded temporal channel waveforms, we estimate average crosstalk profiles and propose an appropriate probability density function for the fluctuations of the detected OAM signal. Further measurements of OAM crosstalk are described for a horizontal 400-m link established over our campus.

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Turbulence-induced persistence in laser beam wandering

Zunino L, Gulich D, Funes G, Pérez DG | Opt Lett | 2015


Localized plateau beam resulting from strong nonlocal coupling in a cavity filled by metamaterials and liquid-crystal cells

M. Tlidi, C. Fernandez-Oto, M. G. Clerc, D. Escaff, and P. Kockaert | Physical Review A, 92, 053838 | 2015


Travelling fronts of the CO oxidation on Pd(111) with coverage-dependent diffusion.

Cisternas, J.; Karpitchka, S.; Wehner, S. | J. Chem. Phys. 141, 164106 (2014). (ISI-Q1)(8/33)(3.142). | 2014

In this work, we study a surface reaction on Pd(111) crystals under ultra-high-vacuum conditions that can be modeled by two coupled reaction-diffusion equations. In the bistable regime, the reaction exhibits travelling fronts that can be observed experimentally using photo electron emission microscopy. The spatial profile of the fronts reveals a coverage-dependent diffusivity for one of the species. We propose a method to solve the nonlinear eigenvalue problem and compute the direction and the speed of the fronts based on a geometrical construction in phase-space. This method successfully captures the dependence of the speed on control parameters and diffusivities.

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Symmetry breaking term effects on explosive localized solitons.

Cartes, C.; Descalzi, O. | Eur. Phys. J. Special Topics. 223, 91 (2014). (ISI-Q2)(23/78)(IF: 1.76). | 2014

We study the influence of an analog of self–steepening (SST), which is a term breaking the T →−T symmetry, on explosive localized solutions for the cubic–quintic complex Ginzburg–Landau equation in the anomalous dispersion regime. We find that while this explosive behavior occurs for a wide range of the parameter s, characterizing SST, the mean distance between explosions diverges close to a critical value s c . After this value the explosive solution becomes a fixed shape soliton that moves at constant speed. The transition between explosive and regular behavior is characterized by a transcritical bifurcation controlled by the SST parameter. We also proposed a mechanism which explains and predicts the mean distance between explosions as a function of s. We are glad to dedicate this article to Professor Helmut R. Brand on occasion of his 60th birthday.

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Strong interaction between plants induces circular barren patches: fairy circles.

Fernandez-Oto, C.; Tlidi, M.; Escaff, D.; Clerc, M. G. | Philosophical Transactions of the Royal Society a-Mathematical Physical and Engineering Sciences. 372(2027). (2014). (ISI-Q1)(9/55)(IF:3.13). | 2014

Fairy circles consist of isolated or randomly distributed circular areas devoid of any vegetation. They are observed in vast territories in southern Angola, Namibia and South Africa. We report on the formation of fairy circles, and we interpret them as localized structures with a varying plateau size as a function of the aridity. Their stabilization mechanism is attributed to a combined influence of the bistability between the bare state and the uniformly vegetation state, and Lorentzian-like non-local coupling that models the competition between plants. We show how a circular shape is formed, and how the aridity level influences the size of fairy circles. Finally, we show that the proposed mechanism is model-independent.

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Plant clonal morphologies and spatial patterns as self-organized responses to resource-limited environments.

Couteron, P.; Anthelme, F.; Clerc, M.; Escaff, D.; Fernandez-Oto, C.; Tlidi, M. | Philosophical Transactions of the Royal Society a-Mathematical Physical and Engineering Sciences. 372(2027). (2014). (ISI-Q1)(9/55)(IF: 3.13). | 2014

We propose here to interpret and model peculiar plant morphologies (cushions and tussocks) observed in the Andean Altiplano as localized structures. Such structures resulting in a patchy, aperiodic aspect of the vegetation cover are hypothesized to self-organize thanks to the interplay between facilitation and competition processes occurring at the scale of basic plant components biologically referred to as ‘ramets’. (Ramets are often of clonal origin.) To verify this interpretation, we applied a simple, fairly generic model (one integro-differential equation) emphasizing via Gaussian kernels non-local facilitative and competitive feedbacks of the vegetation biomass density on its own dynamics. We show that under realistic assumptions and parameter values relating to ramet scale, the model can reproduce some macroscopic features of the observed systems of patches and predict values for the inter-patch distance that match the distances encountered in the reference area (Sajama National Park in Bolivia). Prediction of the model can be confronted in the future with data on vegetation patterns along environmental gradients so as to anticipate the possible effect of global change on those vegetation systems experiencing constraining environmental conditions.

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Noisy CO oxidation on Iridium(111) surfaces: Experiments explained by theory under realistic assumptions.

Wehner, S.; Cisternas, J.; Descalzi, O.; Küppers, J. | Eur. Phys. J. Special Topics 223, 21-41 . | 2014

Noise is an everywhere phenomenon. Its influence could be described theoretically quite easily, but is hard to measure in an experiment. Catalytic reactions on surfaces can be described by nonlinear reaction-diffusion equations. For one of such surface reactions – CO oxidation on Iridium(111) surfaces – the probability distribution of CO2 rates around the mean value – showing the influence of noise – could be measured directly in a ultra high vacuum (UHV) experiment. This opens the way to address such a fundamental phenomenon like noise by all three modern methods of physics – experimental, computational and analytical. We show the measured effect of colored noise on a bistable surface reaction and explain all observations directly with the underlying theoretical description – the Langmuir-Hinshelwood reaction scheme – by solving the equations under realistic assumptions. It is a great pleasure to dedicate this work to Prof. Dr. Helmut R. Brand on the occasion of his 60th birthday.

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Mean field model for synchronization of coupled two-state units and the effect of memory.

Escaff, D.; Lindenberg, K. | Eur. Phys. J. Special Topics. 223 (1): 155-166. (2014). (ISI-Q2)(23/78)(1.76). | 2014

A prototypical model for a mean field second order transition is presented, which is based on an ensemble of coupled two-states units. This system is used as a basic model to study the effect of memory. To wit, we distinguish two types of memories: weak and strong, depending on the feasibility of linearizing the generalized mean field master equation. For weak memory we find static solutions that behave much like those of the memoryless (Markovian) system. The latter exhibits a pitchfork bifurcation as the control parameter is increased, with two stable and one unstable solution. The former exhibits an imperfect pitchfork bifurcation to states with the same behaviors. In both cases, the stability of the static solutions is analyzed via the usual linearization around the equilibrium solution. For strong memories we again find an imperfect pitchfork bifurcation, with two stable and one unstable branch. However, it is no longer possible to analyze these behaviors via the usual linearization, which is local in time, because a strong memory requires knowledge of the system for its entire past. Finally, we are pleased to dedicate this publication to Helmut Brand on the occasion of his 60th birthday.

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Localized Structures in Physics and Chemistry.

Descalzi, O.; Rosso, O.; Larrondo, H. | Eur. Phys. J. Special Topics. 223(1): 1-7. (2014). (ISI-Q2)(23/78) (IF: 1.76). | 2014

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Globally coupled stochastic two-state oscillators: Fluctuations due to finite numbers.

Dias, p.; Ivo Lima, i.; Escaff, D.; Upendra, H.; Rosas, A.; Lindenberg, K. | Physical Review E . 89(5). (2014). (ISI-Q1)(6/55)(IF: 2.326). | 2014

Infinite arrays of coupled two-state stochastic oscillators exhibit well-defined steady states. We study the fluctuations that occur when the number N of oscillators in the array is finite. We choose a particular form of global coupling that in the infinite array leads to a pitchfork bifurcation from a monostable to a bistable steady state, the latter with two equally probable stationary states. The control parameter for this bifurcation is the coupling strength. In finite arrays these states become metastable: The fluctuations lead to distributions around the most probable states, with one maximum in the monostable regime and two maxima in the bistable regime. In the latter regime, the fluctuations lead to transitions between the two peak regions of the distribution. Also, we find that the fluctuations break the symmetry in the bimodal regime, that is, one metastable state becomes more probable than the other, increasingly so with increasing array size. To arrive at these results, we start from microscopic dynamical evolution equations from which we derive a Langevin equation that exhibits an interesting multiplicative noise structure. We also present a master equation description of the dynamics. Both of these equations lead to the same Fokker-Planck equation, the master equation via a 1/N expansion and the Langevin equation via standard methods of Itô calculus for multiplicative noise. From the Fokker-Planck equation we obtain an effective potential that reflects the transition from the monomodal to the bimodal distribution as a function of a control parameter. We present a variety of numerical and analytic results that illustrate the strong effects of the fluctuations. We also show that the limits N→∞ and t→∞ (t is the time) do not commute. In fact, the two orders of implementation lead to drastically different results.

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Frentes y formación de estructuras localizadas en sistemas biestables.

Daniel Escaff | Editorial Académica Española. ISBN: 978-3-659-07371-7. | 2014

Este libro corresponde a parte de la investigación doctoral del profesor D. Escaff. El cual fue escrito durante el segundo semestre del año 2006, y muestra el estado del arte, a esa fecha, de su investigación sobre estados localizados en dinámica poblacional bajo interacción nolocal. La presente edición solo tiene algunas pequeñas correcciones de forma, siendo esencialmente lo escrito el 2006. Esto es, como la interacción no-local débil (aquella que decae más rápido que una exponencial) da pie a la estabilización de dominios localizados de población, inmersos en una zona despoblada. El análisis se basa en la interacción de frente que conectan dos estados estables. Por lo cual, se realiza una clara y detallada introducción de la dinámica de este tipo de frentes, que puede ser útil al lector interesado en el tópico, puesto que la mayor parte de la literatura sobre frentes trata la propagación de un estado estable sobre otro inestable. También se revisa la formación de patrones (tanto extendidos como localizados) bajo interacción no-local. Para finalizar, se incluye un resumen con los avances posteriores al 2006 (hasta el 2013), con las respectivas referencias bibliográficas.

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Exploding dissipative solitons in the cubic-quintic complex Ginzburg-Landau equation in one and two spatial dimensions A review and a perspective.

Cartes, C.; Descalzi, O.; Brand, H. | Eur. Phys. J. Special Topics. 223, 2145. (2014). (ISI-Q2)(23/78) (IF: 1.76). | 2014

We review the work on exploding dissipative solitons in one and two spatial dimensions. Features covered include: the transition from modulated to exploding dissipative solitons, the analogue of the Ruelle-Takens scenario for dissipative solitons, inducing exploding dissipative solitons by noise, two classes of exploding dissipative solitons in two spatial dimensions, diffusing asymmetric exploding dissipative solitons as a model for a two-dimensional extended chaotic system. As a perspective we outline the interaction of exploding dissipative solitons with quasi one-dimensional dissipative solitons, breathing quasi one-dimensional solutions and their possible connection with experimental results on convection, and the occurence of exploding dissipative solitons in reaction-diffusion systems.

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CO oxidation on Iridium(111) surfaces Experiments explained by theory under realistic assumptions.

Wehner, S.; Cisternas, J.; Descalzi, O.; Kueppers, J. | Eur. Phys. J. Special Topics. 223, 21 (2014). (ISI-Q2)(23/78)(IF: 1.76). | 2014


Class of compound dissipative solitons as a result of collisions in one and two spatial dimensions.

Descalzi, O.; Brand, H.R. | Physical Review E. 90(2). (ISI-Q1)(6/55)(IF: 2.326). | 2014

We study the interaction of quasi-one-dimensional (quasi-1D) dissipative solitons (DSs). Starting with quasi-1D solutions of the cubic-quintic complex Ginzburg-Landau (CGL) equation in their temporally asymptotic state as the initial condition, we find, as a function of the approach velocity and the real part of the cubic interaction of the two counterpropagating envelopes: interpenetration, one compound state made of both envelopes or two compound states. For the latter class both envelopes show DSs superposed at two different locations. The stability of this class of compound states is traced back to the quasilinear growth rate associated with the coupled system. We show that this mechanism also works for 1D coupled cubic-quintic CGL equations. For quasi-1D states that are not in their asymptotic state before the collision, a breakup along the crest can be observed, leading to nonunique results after the collision of quasi-1D states.

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Arrays of stochastic oscillators: Nonlocal coupling, clustering, and wave formation.

Escaff, D.; Dias, I.; Lindenberg, K. | Physical Review E. 90, 052111 (2014). (ISI-Q1)(6/55)(IF: 2.302). | 2014

We consider an array of units each of which can be in one of three states. Unidirectional transitions between these states are governed by Markovian rate processes. The interactions between units occur through a dependence of the transition rates of a unit on the states of the units with which it interacts. This coupling is nonlocal, that is, it is neither an all-to-all interaction (referred to as global coupling), nor is it a nearest neighbor interaction (referred to as local coupling). The coupling is chosen so as to disfavor the crowding of interacting units in the same state. As a result, there is no global synchronization. Instead, the resultant spatiotemporal configuration is one of clusters that move at a constant speed and that can be interpreted as traveling waves. We develop a mean field theory to describe the cluster formation and analyze this model analytically. The predictions of the model are compared favorably with the results obtained by direct numerical simulations.

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Class of compound dissipative solitons as a result of collisions in one and two spatial dimensions

Descalzi, O. and Brand, H.R. | Physical Review E | 2014

We study the interaction of quasi-one-dimensional (quasi-1D) dissipative solitons (DSs). Starting with quasi-1D solutions of the cubic-quintic complex Ginzburg-Landau (CGL) equation in their temporally asymptotic state as the initial condition, we find, as a function of the approach velocity and the real part of the cubic interaction of the two counterpropagating envelopes: interpenetration, one compound state made of both envelopes or two compound states. For the latter class both envelopes show DSs superposed at two different locations. The stability of this class of compound states is traced back to the quasilinear growth rate associated with the coupled system. We show that this mechanism also works for 1D coupled cubic-quintic CGL equations. For quasi-1D states that are not in their asymptotic state before the collision, a breakup along the crest can be observed, leading to nonunique results after the collision of quasi-1D states.


Localized Structures in Physics and Chemistry

Descalzi, O., Rosso, O. A., Larrondo, H.A. | Eur. Phys. J. Special Topics | 2014


Exploding dissipative solitons in the cubic-quintic complex Ginzburg-Landau equation in one and two spatial dimensions A review and a perspective

Cartes, C., Descalzi, O., Brand, H. R. | he European Physical Journal Special Topics | 2014

We review the work on exploding dissipative solitons in one and two spatial dimensions. Features covered include: the transition from modulated to exploding dissipative solitons, the analogue of the Ruelle-Takens scenario for dissipative solitons, inducing exploding dissipative solitons by noise, two classes of exploding dissipative solitons in two spatial dimensions, diffusing asymmetric exploding dissipative solitons as a model for a two-dimensional extended chaotic system. As a perspective we outline the interaction of exploding dissipative solitons with quasi one-dimensional dissipative solitons, breathing quasi one-dimensional solutions and their possible connection with experimental results on convection, and the occurence of exploding dissipative solitons in reaction-diffusion systems.

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Anomalous diffusion of dissipative solitons in the cubic-quintic complex Ginzburg-Landau equation in two spatial dimensions

Jaime Cisternas, Orazio Descalzi, Tony Albers, and Günter Radons | Phys. Rev. Lett. 116, 203901 (2016) | 2014

We demonstrate the occurrence of anomalous diffusion of dissipative solitons in a “simple” and deterministic prototype model: the cubic-quintic complex Ginzburg-Landau equation in two spatial dimensions. The main features of their dynamics, induced by symmetric-asymmetric explosions, can be modeled by a subdiffusive continuous-time random walk, while in the case dominated by only asymmetric explosions, it becomes characterized by normal diffusion.

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Symmetry breaking term effects on explosive localized solitons

Cartes, C. and O. Descalzi | The European Physical Journal Special Topics | 2014

We study the influence of an analog of self–steepening (SST), which is a term breaking the T →−T symmetry, on explosive localized solutions for the cubic–quintic complex Ginzburg–Landau equation in the anomalous dispersion regime. We find that while this explosive behavior occurs for a wide range of the parameter s, characterizing SST, the mean distance between explosions diverges close to a critical value s c . After this value the explosive solution becomes a fixed shape soliton that moves at constant speed. The transition between explosive and regular behavior is characterized by a transcritical bifurcation controlled by the SST parameter. We also proposed a mechanism which explains and predicts the mean distance between explosions as a function of s. We are glad to dedicate this article to Professor Helmut R. Brand on occasion of his 60th birthday.

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Strong interaction between plants induces circular barren patches: fairy circles

Fernandez-Oto, C., Tlidi, M., Escaff, D., Clerc, M. G. | Philosophical Transactions of the Royal Society A | 2014

Fairy circles consist of isolated or randomly distributed circular areas devoid of any vegetation. They are observed in vast territories in southern Angola, Namibia and South Africa. We report on the formation of fairy circles, and we interpret them as localized structures with a varying plateau size as a function of the aridity. Their stabilization mechanism is attributed to a combined influence of the bistability between the bare state and the uniformly vegetation state, and Lorentzian-like non-local coupling that models the competition between plants. We show how a circular shape is formed, and how the aridity level influences the size of fairy circles. Finally, we show that the proposed mechanism is model-independent.

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Mean field model for synchronization of coupled two-state units and the effect of memory

Escaff, D., Lindenberg, K. | The European Physical Journal Special Topics | 2014

A prototypical model for a mean field second order transition is presented, which is based on an ensemble of coupled two-states units. This system is used as a basic model to study the effect of memory. To wit, we distinguish two types of memories: weak and strong, depending on the feasibility of linearizing the generalized mean field master equation. For weak memory we find static solutions that behave much like those of the memoryless (Markovian) system. The latter exhibits a pitchfork bifurcation as the control parameter is increased, with two stable and one unstable solution. The former exhibits an imperfect pitchfork bifurcation to states with the same behaviors. In both cases, the stability of the static solutions is analyzed via the usual linearization around the equilibrium solution. For strong memories we again find an imperfect pitchfork bifurcation, with two stable and one unstable branch. However, it is no longer possible to analyze these behaviors via the usual linearization, which is local in time, because a strong memory requires knowledge of the system for its entire past. Finally, we are pleased to dedicate this publication to Helmut Brand on the occasion of his 60th birthday.

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Globally coupled stochastic two-state oscillators: Fluctuations due to finite numbers

Dias Pinto, Italo’Ivo Lima, Escaff Daniel, Harbola Upendra, Rosas Alexandre, Lindenberg Katja | Physical Review E | 2014

Infinite arrays of coupled two-state stochastic oscillators exhibit well-defined steady states. We study the fluctuations that occur when the number N of oscillators in the array is finite. We choose a particular form of global coupling that in the infinite array leads to a pitchfork bifurcation from a monostable to a bistable steady state, the latter with two equally probable stationary states. The control parameter for this bifurcation is the coupling strength. In finite arrays these states become metastable: The fluctuations lead to distributions around the most probable states, with one maximum in the monostable regime and two maxima in the bistable regime. In the latter regime, the fluctuations lead to transitions between the two peak regions of the distribution. Also, we find that the fluctuations break the symmetry in the bimodal regime, that is, one metastable state becomes more probable than the other, increasingly so with increasing array size. To arrive at these results, we start from microscopic dynamical evolution equations from which we derive a Langevin equation that exhibits an interesting multiplicative noise structure. We also present a master equation description of the dynamics. Both of these equations lead to the same Fokker-Planck equation, the master equation via a 1/N expansion and the Langevin equation via standard methods of Itô calculus for multiplicative noise. From the Fokker-Planck equation we obtain an effective potential that reflects the transition from the monomodal to the bimodal distribution as a function of a control parameter. We present a variety of numerical and analytic results that illustrate the strong effects of the fluctuations. We also show that the limits N→∞ and t→∞ (t is the time) do not commute. In fact, the two orders of implementation lead to drastically different results.


Travelling fronts of the CO oxidation on Pd(111) with coverage-dependent diffusion

Cisternas, J., Karpitchka, S. and Wehner, S. | The Journal of Chemical Physics | 2014

In this work, we study a surface reaction on Pd(111) crystals under ultra-high-vacuum conditions that can be modeled by two coupled reaction-diffusion equations. In the bistable regime, the reaction exhibits travelling fronts that can be observed experimentally using photo electron emission microscopy. The spatial profile of the fronts reveals a coverage-dependent diffusivity for one of the species. We propose a method to solve the nonlinear eigenvalue problem and compute the direction and the speed of the fronts based on a geometrical construction in phase-space. This method successfully captures the dependence of the speed on control parameters and diffusivities.

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Plant clonal morphologies and spatial patterns as self-organized responses to resource-limited environments

Couteron, P., Anthelme, F., Clerc, M., Escaff, D., Fernandez-Oto, C., Tlidi, M. | Philosophical Transactions of the Royal Society A | 2014

We propose here to interpret and model peculiar plant morphologies (cushions, tussocks) observed in the Andean altiplano as localized structures. Such structures resulting in a patchy, aperiodic aspect of the vegetation cover are hypothesized to self-organize thanks to the interplay between facilitation and competition processes occurring at the scale of basic plant components biologically referred to as ‘ramets’. (Ramets are often of clonal origin.) To verify this interpretation, we applied a simple, fairly generic model (one integro-differential equation) emphasizing via Gaussian kernels non-local facilitative and competitive feedbacks of the vegetation biomass density on its own dynamics. We show that under realistic assumptions and parameter values relating to ramet scale, the model can reproduce some macroscopic features of the observed systems of patches and predict values for the inter-patch distance that match the distances encountered in the reference area (Sajama National Park in Bolivia). Prediction of the model can be confronted in the future to data on vegetation patterns along environmental gradients as to anticipate the possible effect of global change on those vegetation systems experiencing constraining environmental conditions.


Arrays of stochastic oscillators: Nonlocal coupling, clustering, and wave formation

Escaff, D., I.L. Dias Pinto, and K. Lindenberg | Physical Review E | 2014

We consider an array of units each of which can be in one of three states. Unidirectional transitions between these states are governed by Markovian rate processes. The interactions between units occur through a dependence of the transition rates of a unit on the states of the units with which it interacts. This coupling is nonlocal, that is, it is neither an all-to-all interaction (referred to as global coupling), nor is it a nearest neighbor interaction (referred to as local coupling). The coupling is chosen so as to disfavor the crowding of interacting units in the same state. As a result, there is no global synchronization. Instead, the resultant spatiotemporal configuration is one of clusters that move at a constant speed and that can be interpreted as traveling waves. We develop a mean field theory to describe the cluster formation and analyze this model analytically. The predictions of the model are compared favorably with the results obtained by direct numerical simulations.


Experimental confirmation of long-memory correlations in star-wander data

Zunino L, Gulich D, Funes G, Ziad A. | Opt Lett | 2014


Strong nonlocal coupling stabilizes localized structures: An analysis based on front dynamics.

Fernández-Oto, C.; Clerc, M. G.; Escaff, D.; Tlidi, M. | Physical Review Letters, 110: 174101, 2013. | 2013

We investigate the effect of strong nonlocal coupling in bistable spatially extended systems by using a Lorentzian-like kernel. This effect through front interaction drastically alters the space-time dynamics of bistable systems by stabilizing localized structures in one and two dimensions, and by affecting the kinetics law governing their behavior with respect to weak nonlocal and local coupling. We derive an analytical formula for the front interaction law and show that the kinetics governing the formation of localized structures obeys a law inversely proportional to their size to some power. To illustrate this mechanism, we consider two systems, the Nagumo model describing population dynamics and nonlinear optics model describing a ring cavity filled with a left-handed material. Numerical solutions of the governing equations are in close agreement with analytical predictions.

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Quasi-one-dimensional solutions and their interaction with two-dimensional dissipative solitons.

Descalzi, O.; Brand, H.R. | Physical Review E, 87: 022915, 2013. | 2013

We describe the stable existence of quasi-one-dimensional solutions of the two-dimensional cubic-quintic complex Ginzburg-Landau equation for a large range of the bifurcation parameter. By quasi-one-dimensional (quasi-1D) in the present context, we mean solutions of fixed shape in one spatial dimension that are simultaneously fully extended and space filling in a second direction. This class of stable solutions arises for parameter values for which simultaneously other classes of solutions are at least locally stable: the zero solution, 2D fixed shape dissipative solitons, or 2D azimuthally symmetric or asymmetric exploding dissipative solitons. We show that quasi-1D solutions can form stable compound states with 2D stationary dissipative solitons or with azimuthally symmetric exploding dissipative solitons. In addition, we find stable breathing quasi-1D solutions near the transition to collapse. The analogy of several features of the work presented here to recent experimental results on convection by Miranda and Burguete [Phys. Rev. E 78, 046305 (2008); Phys. Rev. E 79, 046201 (2009)] is elucidated.

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Intermittent explosions of dissipative solitons and noise-induced crisis.

Cisternas, J.; Descalzi, O. | Physical Review E, 88: 022903, 2013. | 2013

Dissipative solitons show a variety of behaviors not exhibited by their conservative counterparts. For instance, a dissipative soliton can remain localized for a long period of time without major profile changes, then grow and become broader for a short time—explode—and return to the original spatial profile afterward. Here we consider the dynamics of dissipative solitons and the onset of explosions in detail. By using the one-dimensional complex Ginzburg-Landau model and adjusting a single parameter, we show how the appearance of explosions has the general signatures of intermittency: the periods of time between explosions are irregular even in the absence of noise, but their mean value is related to the distance to criticality by a power law. We conjecture that these explosions are a manifestation of attractor-merging crises, as the continuum of localized solitons induced by translation symmetry becomes connected by short-lived trajectories, forming a delocalized attractor. As additive noise is added, the extended system shows the same scaling found by low-dimensional systems exhibiting crises [J. Sommerer, E. Ott, and C. Grebogi, Phys. Rev. A 43, 1754 (1991)], thus supporting the validity of the proposed picture.

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Exploding dissipative solitons in reaction-diffusion systems.

Descalzi, O.; Akhmediev, N.; Brand, H.R. | Physical Review E, 88: 042911, 2013. | 2013

We show that exploding dissipative solitons can arise in a reaction-diffusion system for a range of parameters. As a function of a vorticity parameter, we observe a sequence of transitions from oscillatory localized states via meandering dissipative solitons to exploding dissipative solitons propagating in one direction for long times followed by the reverse cascade back to oscillatory localized states. While exploding dissipative solitons are known from the cubic-quintic complex Ginzburg-Landau (CGL) equation, propagating exploding dissipative solitons appear to require for their existence a system of lower symmetry such as the reaction-diffusion model studied here.

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Experimental imaging coding system using three-dimensional subjective speckle structures.

Mosso, F.; Peters, E.; Bolognini, N.; Tebaldi, M.; Torroba, R.; Pérez, D. | Journal of Optics 15 (12), 125403. | 2013

We propose, and experimentally demonstrate, an optical encoding system employing a three-dimensional subjective speckle distribution as a secure information carrier. An image mask (containing the information to be sent) is illuminated by randomly distributed light. The outgoing wavefront reaches a lens, and thus three-dimensional subjective speckle distributions are generated in the normal direction of the scattering plane. These speckle structures are sampled by registering consecutive planes along the optical axis with a complementary metal-oxide semiconductor camera. Along with the optical parameters (keys), these intensity patterns are sent through independent channels to a receiver. By replicating the original system with the keys and implementing a single-beam multiple-intensity reconstruction, we show that the message recipient needs a minimum set of speckle images to successfully recover the original information. Moreover, intercepting a partial set of speckle images with the keys may not result in a successful interception.

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Estimating the optimal sampling rate using wavelet transform: an application to optical turbulence

Funes G, Fernández A, Pérez DG, Zunino L, Serrano E. | Opt Express | 2013

Sampling rate and frequency content determination for optical quantities related to light propagation through turbulence are paramount experimental topics. Some papers about estimating properties of the optical turbulence seem to use ad hoc assumptions to set the sampling frequency used; this chosen sampling rate is assumed good enough to perform a proper measurement. On the other hand, other authors estimate the optimal sampling rate via fast Fourier transform of data series associated to the experiment. When possible, with the help of analytical models, cut-off frequencies, or frequency content, can be determined; yet, these approaches require prior knowledge of the optical turbulence. The aim of this paper is to propose an alternative, practical, experimental method to estimate a proper sampling rate. By means of the discrete wavelet transform, this approach can prevent any loss of information and, at the same time, avoid oversampling. Moreover, it is independent of the statistical model imposed on the turbulence.

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The transition to explosive solitons and the destruction of invariant tori.

Cisternas, J., Descalzi, O.; Cartes, C. | Central European Journal of Physics, 12: 11534, 2012. | 2012

We investigate the transition to explosive dissipative solitons and the destruction of invariant tori in the com-plex cubic-quintic Ginzburg–Landau equation in the regime of anomalous linear dispersion as a function ofthe distance from linear onset. Using Poncaré sections, we sequentially find fixed points, quasiperiodicity(two incommesurate frequencies), frequency locking, two torus-doubling bifurcations (from a torus to a 2-fold torus and from a 2-fold torus to a 4-fold torus), the destruction of a 4-fold torus leading to non-explosivechaos, and finally explosive solitons. A narrow window, in which a 3-fold torus appears, is also observedinside the chaotic region.

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Synchronization of globally coupled two-state stochastic oscillators with a state-dependent refractory period.

Escaff, D.; Harbola, U.; Lindenberg, K. | Physical Review E, 86: 011131, 2012. | 2012

We present a model of identical coupled two-state stochastic units, each of which in isolation is governed by a fixed refractory period. The nonlinear coupling between units directly affects the refractory period, which now depends on the global state of the system and can therefore itself become time dependent. At weak coupling the array settles into a quiescent stationary state. Increasing coupling strength leads to a saddle node bifurcation, beyond which the quiescent state coexists with a stable limit cycle of nonlinear coherent oscillations. We explicitly determine the critical coupling constant for this transition.

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Pattern formation via intermittence from microscopic deterministic dynamics.

Escaff, D.; Hernández, M.; Finger R. | Physical Review, E, 85: 056218, 2012. | 2012

We propose a one-dimensional lattice model, inspired by population dynamics interaction. The model combines a variable coupling range with the Allee effect. The system is capable of exhibiting pattern formation that is similar to what occurs in similar continuous models for population dynamics. However, the formation features are quite different; in this case the pattern emerges from a disorder state via intermittence. We analytically estimated the selected wavelength of the formed pattern and numerically studied fluctuations around the mean wavelength. We also comment on the relationship between intermittence and the edge of chaos as well as sensitivity to initial conditions. Next, we present an analytical prediction of the influence of the world size on the intermittent regime which is in good agreement with the numerical observations. Moreover, the last calculation provided us an alternative way to compute the pattern wavelength. Finally, we discuss the continuous limit of our lattice model.

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Noise can induce explosions for dissipative solitons.

Cartes, C.; Descalzi, O.; Brand, HR. | Physical Review E, 85: 0152051, 2012. | 2012

We study the influence of noise on the spatially localized, temporally regular states (stationary, one frequency, two frequencies) in the regime of anomalous dispersion for the cubic-quintic complex Ginzburg-Landau equation as a function of the bifurcation parameter. We find that noise of a fairly small strength η is sufficient to reach a chaotic state with exploding dissipative solitons. That means that noise can induce explosions over a fairly large range of values of the bifurcation parameter μ. Three different routes to chaos with exploding dissipative solitons are found as a function of μ. As diagnostic tools we use the separation to characterize chaotic behavior and the energy to detect spatially localized explosive behavior as a function of time.

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Model of a two-dimensional extended chaotic system: Evidence of diffusing dissipative solitons.

Cartes, C.; Cisternas, J.; Descalzi, O.; Brand, H.R. | Physical Review Letters, 109: 178303, 2012. | 2012

We investigate a two-dimensional extended system showing chaotic and localized structures. We demonstrate the robust and stable existence of two types of exploding dissipative solitons. We show that the center of mass of asymmetric dissipative solitons undergoes a random walk despite the deterministic character of the underlying model. Since dissipative solitons are stable in two-dimensional systems we conjecture that our predictions can be tested in systems as diverse as nonlinear optics, parametric excitation of granular media and clay suspensions, and sheared electroconvection.

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CO oxidation on Ir(111) surfaces under large non-Gaussian noise.

Cisternas, J.; Wehner, S.; Descalzi, O. | Journal of Chemical Physics, 137: 064105, 2012. | 2012

In this article we consider the CO oxidation on Ir(111) surfaces under large external noise with large autocorrelation imposed on the composition of the feed gas, both in experiments and in theory. We report new experimental results that show how the fluctuations force the reaction rate to jump between two well defined states. The statistics of the reaction rate depend on those of the external noise, and neither of them have a Gaussian distribution, and thus they cannot be modeled by white or colored noise. A continuous-time discrete-state Markov process is proposed as a suitable model for the observed phenomena. The model captures the main features of the observed fluctuations and can be modified to accommodate other surface reactions and other systems under non-Gaussian external noise.

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Beam wandering statistics of twin thin laser beam propagation under generalized atmospheric conditions

Pérez DG, Funes G. | Opt Express | 2012

Under the Geometrics Optics approximation is possible to estimate the covariance between the displacements of two thin beams after they have propagated through a turbulent medium. Previous works have concentrated in long propagation distances to provide models for the wandering statistics. These models are useful when the separation between beams is smaller than the propagation path—regardless of the characteristics scales of the turbulence. In this work we give a complete model for these covariances, behavior introducing absolute limits to the validity of former approximations. Moreover, these generalizations are established for non-Kolmogorov atmospheric models.

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Non-local defect interaction in one-dimension: Weak versus strong non-locality.

Escaff, D. | Eur. Phys., J-D (62): 33- 38, 2011. | 2011

Defect interaction (kink-antikink interaction) is studied for a prototypical model for non-local interaction. Mathematically, it is a bistable integrodifferential model, where the non-local interaction is performed due to an integral kernel. The system is able to establish domains where it is in one of its two equilibria, separated by defects. It is shown that the defect interaction depends on the asymptotical behavior of the integral kernel. In the weak non-local regime, when the integral kernel decays faster than an exponential at infinitum, the defect interaction is exponentially weak. Hence, this case is qualitatively similar to the local one. On the other hand, in the strong non-local regime, when the integral kernel decays slower than an exponential at infinitum, the defect interaction is ruled by the asymptotical behavior of the integral kernel. In this case, the defect interaction is stronger, and could be characterized, for instance, by a power law. The effect of this transition (from the weak to strong non-locality) on the domain dynamics is discussed.

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Lurching waves in thalamic neuronal networks.

Cisternas, J.; Wasylenko,T.; Kevrekidis, I. | Localized States in Physics, Springer, Estados Unidos, 2011, Pp. 265-280. | 2011

Numerical bifurcation computations are used to characterize traveling waves for a family of models of thalamic neurons in a network. These models consist of two layers of neurons: one made up of excitatory neurons, and the other of inhibitory ones. The interplay of these two different couplings gives rise to the propagation of activity waves. This article contains some preliminary work on the characterization of the observed waves in a one-dimensional lattice and explores the effects of varying key parameters of the model. The stability of these solutions, as well as the presence of hysteresis and the coexistence of up to three different waves, are most naturally explained in terms of the theory of bifurcations of dynamical systems.

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Localized States in Physics: Solitons and patterns.

Descalzi, O.; Clerc, M.; Residori, S.; Assanto, G. | Springer- Verlag, Heidelberg, 2011. | 2011

Systems driven far from thermodynamic equilibrium can create dissipative structures through the spontaneous breaking of symmetries. A particularly fascinating feature of these pattern-forming systems is their tendency to produce spatially confined states. These localized wave packets can exist as propagating entities through space and/or time. Various examples of such systems will be dealt with in this book, including localized states in fluids, chemical reactions on surfaces, neural networks, optical systems, granular systems, population models, and Bose-Einstein condensates.This book should appeal to all physicists, mathematicians and electrical engineers interested in localization in far-from-equilibrium systems. The authors – all recognized experts in their fields – strive to achieve a balance between theoretical and experimental considerations thereby giving an overview of fascinating physical principles, their manifestations in diverse systems, and the novel technical applications on the horizon.

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Exploding dissipative solitons: The analog of the Ruelle-Takens route for spatially localized solutions.

Descalzi, O.; Cartes, C.; Cisternas, J; Brand, H. | Physical Review E, 83: 056214, 2011. | 2011

We investigate the route to exploding dissipative solitons in the complex cubic-quintic Ginzburg-Landau equation, as the bifurcation parameter, the distance from linear onset, is increased. We find for a large class of initial conditions the sequence: stationary localized solutions, oscillatory localized solutions with one frequency, oscillatory localized solutions with two frequencies, and exploding localized solutions. The transition between localized solutions with one and with two frequencies, respectively, is analyzed in detail. It is found to correspond to a forward Hopf bifurcation for these localized solutions as the bifurcation parameter is increased. In addition, we make use of power spectra to characterize all time-dependent states. On the basis of all information available, we conclude that the sequence oscillatory localized solutions with one frequency, oscillatory localized solutions with two frequencies, and exploding dissipative solitons can be interpreted as the analog of the Ruelle-Takens-Newhouse route to chaos for spatially localized solutions.

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Eulerian-Lagrangian formulation for compressible Navier-Stokes equations.

Cartes, C.; Descalzi, O. | Hydrodynamics – Optimizing Methods and Tools, Intech Ed., Pp.109-128, 2011. | 2011

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Carbon Monoxide Oxidation on Iridium(111) Surfaces driven by strongly colored noise.

Cisternas, J.; Lecaros, R.; Wehner, S. | European Physics Journal D, 62 (1): 91-102, 2011. | 2011

The influence of external colored noise on the carbon monoxide oxidation on Iridium(111) surfaces is examined. The noise is introduced in the reaction by randomly varying the composition of the gas flow that keeps the reaction going on. Colored noise is studied using two models: a simple discrete time Markov chain, and the Ornstein-Uhlenbeck process. We compute the probability distribution and transition times, for medium and large correlation time of the noise. These results extend previous analyses that have been limited to small correlation times and the presence of a slow manifold, both assumptions that are not supported by experiments. As we will see, the correlation and intensity of the noise leads to qualitative changes in the stochastic behavior of the system.

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Transition from modulated to exploding dissipative solitons: Hysteresis, dynamics and analytic aspects.

Descalzi, O.; Brand, H.R. | Physical Review E 82, 026203 (2010). | 2010

We investigate the properties of and the transition to exploding dissipative solitons as they have been found by Akhmediev’s group for the cubic-quintic complex Ginzburg-Landau equation. Keeping all parameters fixed except for the distance from linear onset, μ, we covered a large range of values of μ from very negative values to μ=0, where the zero solution loses its linear stability. We find, with increasing values of μ, stationary pulses, pulses with rapid oscillations, and pulses modulated with an additional small frequency. The transition to exploding solitons arises via a hysteretic transition involving symmetric and asymmetric pulses with two frequencies. As μ is increased in the regime of exploding solitons, the fraction of symmetric exploding solitons is increasing. At the transition from asymmetric two frequency pulses to exploding solitons, only asymmetric exploding solitons are found. We completed our analysis with an analytic study of the collapse time for the exploding solitons and found good agreement with our numerical results.

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Influence of Dirichlet boundary conditions on dissipative solitons in the cubic-quintic complex Ginzburg-Landau equation.

Descalzi, O.; Brand, H.R. | Physical Review E 81, 026210 (2010). | 2010

We investigate the influence of Dirichlet boundary conditions on various types of localized solutions of the cubic-quintic complex Ginzburg-Landau equation as it arises as an envelope equation near the weakly inverted onset of traveling waves. We find that various types of nonmoving pulses and holes can accommodate Dirichlet boundary conditions by having, for holes, two halves of a π hole at each end of the box. Moving pulses of fixed shape as they arise for periodic boundary conditions are replaced by a nonmoving asymmetric pulse, which has half a π hole at the end of the box in the original moving direction to guarantee that Dirichlet boundary conditions are met. Moving breathing pulses as they arise for periodic boundary conditions propagate toward one end of the container and stop moving while the breathing persists indefinitely. Finally breathing and moving holes are replaced by two (nonbreathing) half π holes at each end of the container and one hump in the bulk.

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Carbon Monoxide Oxidation on Iridium(111) Surfaces under Colored Noise.

Cisternas, J.; Escaff, D.; Descalzi, O.; Wehner, S. | International Journal of Bifurcations and Chaos 20 (2):243-254. | 2010

We study the effect of external noise on the catalytic oxidation of CO on an Iridium(111) single crystal under ultrahigh vacuum conditions. This reaction can be considered as a model of catalysis used in the industry. In the absence of noise, the reaction exhibits one or two stable stationary states, depending on the control parameters such as temperature and partial pressures. When noise is added, for instance, by randomly varying the quality of the influx mixture, the system exhibits stochastic reaction rate and switching. In this work, we present the theoretical predictions for the bistable situation using a number of colored-noise approximations that consider the intensity and correlation of the external fluctuations. As we will show, only some of these approximations are suitable for bistable systems. Keywords: Surface reactions, bistability; stochastic processes; colored noise

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Bifurcations of lurching waves in a thalamic neuronal network.

Wasylenko, T.; Cisternas, J.; Laing, C.; Kevrekidis, I.G. | iological Cybernetics, 103(6), 447-462. | 2010

We consider a two-layer, one-dimensional lattice of neurons; one layer consists of excitatory thalamocortical neurons, while the other is comprised of inhibitory reticular thalamic neurons. Such networks are known to support “lurching” waves, for which propagation does not appear smooth, but rather progresses in a saltatory fashion; these waves can be characterized by different spatial widths (different numbers of neurons active at the same time). We show that these lurching waves are fixed points of appropriately defined Poincaré maps, and follow these fixed points as parameters are varied. In this way, we are able to explain observed transitions in behavior, and, in particular, to show how branches with different spatial widths are linked with each other. Our computer-assisted analysis is quite general and could be applied to other spatially extended systems which exhibit this non-trivial form of wave propagation.

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Variational principles in Image Processing and the Regularization of Orientation Fields.

Cisternas, J.; Gálvez, M.; Stieltjes, B.; Laun, F.B. | International Journal of Bifurcations and Chaos 19(8), 2705-2716. | 2009

Variational principles and partial differential equations have proved to be fundamental elements in the mathematical modeling of extended systems in physics and engineering. Of particular interest are the equations that arise from a free energy functional. Recently variational principles have begun to be used in Image Processing to perform basic tasks such as denoising, debluring, etc. Great improvements can be achieved by selecting the most appropriate form for the functional.

In this article we show how these ideas can be applied not just to scalar fields (i.e. grayscale images) but also to curved manifolds such as the space of orientations. This work is motivated by the denoising of images acquired with Magnetic Resonance scanners using diffusion-sensitized magnetic gradients. Keywords: Variational principles; image processing; orientation field; anisotropic diffusion; magnetic resonance imaging

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Transition from pulses to fronts in the cubic-quintic complex Ginzburg-Landau equation.

Gutierrez, P.; Escaff, D.; Descalzi, O. | Philosophical Transactions of the Royal Society A 367, 3227-3238. | 2009

The cubic–quintic complex Ginzburg–Landau is the amplitude equation for systems in the vicinity of an oscillatory sub-critical bifurcation (Andronov–Hopf), and it shows different localized structures. For pulse-type localized structures, we review an approximation scheme that enables us to compute some properties of the structures, like their existence range. From that scheme, we obtain conditions for the existence of pulses in the upper limit of a control parameter. When we study the width of pulses in that limit, the analytical expression shows that it is related to the transition between pulses and fronts. This fact is consistent with numerical simulations.

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Stochastic Model Calculation for the Carbon Monoxide Oxidation on Iridium(111) Surfaces.

Cisternas, J.; Escaff, D.; Descalzi O.; Wehner,S. | International Journal of Bifurcations and Chaos 19 (10), 3461-3472. | 2009

We study the effect of external noise on the catalytic oxidation of CO on an Iridium(111) single crystal under ultrahigh vacuum conditions. This reaction can be considered as a model of catalysis used in industry. In the absence of noise the reaction exhibits one or two stable stationary states, depending on control parameters such as temperature and partial pressures. When noise is added, for instance, by randomly varying the quality of the influx mixture, the system exhibits stochastic reaction rate and switching. In this work, we present two approaches: one for the monostable regime, and another for the bistable situation that relies on a white noise approximation. Both approaches rest on the assumption that spatial patterns of coverage on the Iridium plate can be neglected on a first approximation. Using mathematical models, it is possible to reconstruct stationary probability distribution functions that match experimental observations and provide support for the existence of a thermodynamic potential. Keywords: Surface reactions; bistability; stochastic differential equations; noise

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Shape and size effects in localized hexagonal patterns.

Escaff, D.; Descalzi, O. | International Journal of Bifurcation and Chaos 19 Nª8, 2727-2743. | 2009

We study the process of localization of a hexagonal pattern in a uniform background, specifically, the role played by the shape and size of the domain where the hexagonal pattern is confined. We base our analysis on a numerical study of a Swift–Hohenberg type equation (which exhibits coexistence between hexagons and a uniform state), and in a scale expansion to estimate the stress undergoing by the interface (the curve that separates the hexagonal phase from the uniform one). Our scaling approach supplies us a good physical picture of what we observe numerically. Keywords: Localized structures; pattern formation; hexagons

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Noise induces partial annihilation of colliding dissipative solitons.

Descalzi, O.; Cisternas, J.; Escaff, D.; Brand, H.R. | Physical Review Letters 102, 188302. | 2009

Partial annihilation of two counterpropagating dissipative solitons, with only one pulse surviving the collision, has been widely observed in different experimental contexts, over a large range of parameters, from hydrodynamics to chemical reactions. However, a generic picture accounting for partial annihilation is missing. Based on our results for coupled complex cubic-quintic Ginzburg-Landau equations as well as for the FitzHugh-Nagumo equation we conjecture that noise induces partial annihilation of colliding dissipative solitons in many systems.

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Moving breathing pulses in the one-dimensional complex cubic-quintic Ginzburg-Landau equation.

Gutiérrez, P.; Escaff, D.; Pérez-Oyarzún, S.; Descalzi, O.; Brand, H.R. | Physical Review E 80, 037202. | 2009

We show and characterize numerically moving breathing pulses in the one-dimensional complex cubic-quintic Ginzburg-Landau equation. This class of stable moving breathing pulses has not been described before for this prototype envelope equation as it arises near the weakly hysteretic onset of traveling waves.

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Localized hexagonal pattern: morphological and size aspects.

Escaff, D.; Descalzi, O.; Cisternas, J. | Progress of Theoretical Physics, 121(1). | 2009

A classical geometry, widely observed in systems far from equilibrium, is the formation of hexagonal patterns. Using a prototype Swift-Hohenberg equation for the order parameter we study the localization mechanism for hexagons surrounded by a uniform phase. Numerical simulations show that the existence range for localized structures depends on the size and morphology of the structure. We propose a scale expansion in order to estimate the stress at the interfaces between the hexagons and the uniform phase. This scaling approach supplies a good physical description of the mechanisms involved in the localization of the hexagonal pattern.

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Transversal interface dynamic of a front connecting a stripe pattern to a uniform state.

M. G. Clerc, D. Escaff and R. Rojas. | Europhysics Letters, 83, 28002. | 2008

Interfaces in two-dimensional systems exhibit unexpected complex dynamical behaviors, the dynamics of a border connecting a stripe pattern and a uniform state is studied. Numerical simulations of a prototype isotropic model, the subcritical Swift-Hohenberg equation, show that this interface has transversal spatial periodic structures, zigzag dynamics and complex coarsening process. Close to a spatial bifurcation, an amended amplitude equation and a one-dimensional interface model allow us to characterize the dynamics exhibited by this interface.

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Influence of Boundary Conditions on Localized Solutions of the cubic-quintic Complex Ginzburg-Landau Equation.

O.; Descalzi, O.; Brand, H.R. | Progress of Theoretical Physics 119 Nº5, 725-738. | 2008

We investigate the influence of the boundary conditions and the box size on the existence and stability of various types of localized solutions (particles and holes) of the cubic-quintic complex Ginzburg-Landau equation as it arises as a prototype envelope equation near the weakly hysteretic onset of traveling waves. Two types of boundary conditions are considered for one spatial dimension, both of which can be realized experimentally: periodic boundary conditions, which can be achieved for an annulus and Neumann boundary conditions, which correspond to zero flux, for example in hydrodynamics. We find that qualitative differences between the two types of boundary conditions arise in particular for propagating and breathing localized solutions. While an asymmetry in the localized state is always connected to motion for periodic boundary conditions, this no longer applies for Neumann boundary conditions. In the case of Neumann boundary conditions we observe that breathing localized states can no longer exist below a certain box size, which is comparable to the ‘width’of the localized state.

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Sources and sinks in the vicinity of a weakly inverted instability.

Cisternas, J.; Descalzi, O. | International Journal of Bifurcations and Chaos, 17(8), 2821-2826. | 2007

The dynamics of perturbations around sinks and sources of traveling waves (TW) is studied in the cubic-quintic Ginzburg–Landau equation from an analytical point of view. Perturbations generically propagate in a direction opposite to the TW. Thus, a sink of TW is a source of perturbations and vice versa. For small values of time we predict there is a lower bound for the group velocity. For large values of time we predict the asymptotic value of the group velocity of the wave packet. Both predictions are in good agreement with direct numerical simulations.

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Collisions of counter-propagating pulses in coupled complex cubic-quintic Ginzburg-Landau equations.

Descalzi, O.; Cisternas, J.; Gutierrez, P.; Brand H.R. | European Physical Journal Special Topics 146, 63-70. | 2007

We discuss the results of the interaction of counter-propagating pulses for two coupled complex cubic-quintic Ginzburg–Landau equations as they arise near the onset of a weakly inverted Hopf bifurcation. As a result of the interaction of the pulses we find in 1D for periodic boundary conditions (corresponding to an annular geometry) many different possible outcomes. These are summarized in two phase diagrams using the approach velocity, v, and the real part of the cubic cross-coupling, cr, of the counter-propagating waves as variables while keeping all other parameters fixed. The novel phase diagram in the limit v ↦0, cr ↦0 turns out to be particularly rich and includes bound pairs of 2 π holes as well as zigzag bound pairs of pulses.

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Hysteretic behaviour of stable solutions at the onset of a weakly inverted instability.

Descalzi, O.; Brand H.R.; Cisternas, J. | Physica A 371, 41-45. | 2007

We investigate in the framework of the quintic complex Ginzburg–Landau (CGL) equation in one spatial dimension the dynamics of the transition from moving pulse solutions to moving hole solutions, a new class of solutions found for this equation very recently. We find that the transition between these two classes of solutions is weakly hysteretic and that the velocity of moving pulses and moving holes shows a jump across the transition, that is moving particles and moving holes travel at different speeds on both sides of the transition.

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Collisions of pulses can lead to holes via front interaction in the cubic-quintic complex Ginzburg-Landau equation in an annular geometry.

Descalzi, O.; Cisternas, J.; Brand H.R. | Physical Review E 74, 065201 (R). | 2006

We study the interaction of counterpropagating pulse solutions for two coupled complex cubic-quintic Ginzburg-Landau equations in an annular geometry. For small approach velocity we find as an outcome of such collisions several results including zigzag bound pulses, stationary bound states of 2π holes, zigzag 2π holes, stationary bound states of π holes, zigzag bound states of π holes, propagating 2π holes, and propagating π holes as the real part of the cubic cross coupling between the counterpropagating waves is increased. We characterize in detail the collisions giving rise to the three states involving π holes as an outcome

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On the stable stationary hole solutions in the complex Ginzburg-Landau equation.

Descalzi, O.; During, G.; Tirapegui, E. | Physica A 356, 66-71. | 2005

We show numerically that the one-dimensional quintic complex Ginzburg–Landau equation

admits four different types of stable hole solutions. We present a simple analytic method which

permits to calculate the region of existence and approximate shape of stable hole solutions in

this equation. The analytic results are in good agreement with numerical simulations.

Keywords: Ginzburg–Landau equation; Stable hole solutions

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Localized structures in non-equilibrium systems.

Descalzi, O.; Gutierrez, P.; Tirapegui, E. | International Journal of Modern Physics C 16 N°12, 1909-1916. | 2005

We study numerically a prototype equation which arises generically as an envelope equation for a weakly inverted bifurcation associated to traveling waves: The complex quintic

Ginzburg–Landau equation. We show six different stable localized structures including

stationary pulses, moving pulses, stationary holes and moving holes, starting from localized initial conditions with periodic and Neumann boundary conditions.

Keywords: Oscillatory instability; Ginzburg–Landau equation; localized solutions.

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A simple two-component reaction-diffusion system showing rich dynamic behaviour: spatially homogeneous aspects and selected bifurcation scenarios.

Hayase, O.; Descalzi, O.; Brand, H.R. | Physica A 356, 19-24. | 2005

We present a simple reaction-diffusion model for two variables. The model was originally designed to have a stable localized solution for a range of parameters as a consequence of the coexistence of a stable limit cycle and a stable fixed point. We classify the spatially homogeneous solutions of the model. In addition we describe several bifurcation scenarios for particle-like solutions as a function of two of the parameters. Keywords: Reaction-diffusion systems; Limit cycles; Localized solutions; Particle solutions

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Oscillating localized structures in reaction-diffusion systems.

Descalzi, O.; Hayase, Y.; Brand, H.R. | International Journal of Bifurcation and Chaos 14 N°12, 4097-4104. | 2004

Oscillating localized structures are studied for a simple reaction–diffusion model from an analytical point of view. The result is a particle solution which acts as a source of traveling waves. The analytical expressions obtained are in good agreement with direct numerical simulations. Keywords: Reaction–diffusion models; saddle-node bifurcation; oscillating localized structures

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On the moving pulse solutions in systems with broken parity.

Descalzi, O.; Tirapegui, E. | Physica A 342, 9-15. | 2004

We study analytically a system sustaining stable moving localized structures, namely, the one-dimensional quintic complex Ginzburg–Landau (G–L) equation with non-linear gradients. We obtain approximate solutions for the stable moving pulse and its velocity. The results are in excellent agreement with direct numerical simulations. Keywords: Ginzburg–Landau equation; Moving localized structures

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Coexistence of stable particle and hole solutions for fixed parameters for a simple reaction-diffusion system.

Hayase, O.; Descalzi, O.; Brand, H.R. | Physical Review E 69, 065201(R). | 2004

We present a simple autocatalytic reaction-diffusion model for two variables, which shows for fixed parameter values the simultaneous stable coexistence of particle solutions as well of two types of hole solutions. The associated spatially homogeneous system is characterized by the coexistence of one stable fixed point and a stable limit cycle solution. We compare our results to other dissipative systems which have for fixed parameters either stable particle or stable hole solutions including the quintic complex Ginzburg-Landau equation and the envelope equation for optical bistability as well as other reaction-diffusion models.

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Analytical approach to localized structures in a simple reaction-diffusion system.

Descalzi, O.; Hayase, Y.; Brand, H.R. | Physical Review E 69, 026121. | 2004

We study from an analytical point of view a simple reaction-diffusion model, which admits stable oscillating localized structures as a consequence of the coexistence between a stable limit cycle and a stable fixed point. Using a generalized matching approach we are able to find approximate analytical expressions for localized oscillating structures in this reaction-diffusion model capturing all the essential ingredients of these breathing particlelike solutions.

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Saddle-Node Bifurcation: An Appearance Mechanism of Pulses in the Subcritical Complex Ginzburg-Landau Equation.

Descalzi, O.; Argentina, M.; Tirapegui, E. | Physical Review E 67, 015601 (R). | 2003

We study stationary, localized solutions in the complex subcritical Ginzburg-Landau equation in the region where there exists coexistence of homogeneous attractors. Using a matching approach, we report on the fact that the appearance of pulses are related to a saddle-node bifurcation. Numerical simulations are in good agreement with our theoretical predictions.

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On the stability of localized structures in the complex Ginzburg–Landau equation

Descalzi, O. | Physica A 327, 23-28. | 2003

We study analytically the asymptotic linear stability of fixed-modulus dissipative–dispersive localized solutions of the one-dimensional quintic complex Ginzburg–Landau (GL) equation in the region where there exists a coexistence of homogeneous attractors. The linear analysis gives an indication for the existence of pulses with an oscillating modulus. Keywords: Ginzburg–Landau equation; Bifurcations; Localized structures

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Stationary Localized Solutions in the Subcritical Complex Ginzburg-Landau Equation.

Descalzi, O.; Argentina, M.; Tirapegui, E. | International Journal of Bifurcation and Chaos 12 N°11, 2459-2465. | 2002

It is shown that pulses in the complete quintic one-dimensional Ginzburg–Landau equation with complex coefficients appear through a saddle-node bifurcation which is determined analytically through a suitable approximation of the explicit form of the pulses. The results are in excellent agreement with direct numerical simulations. Keywords: Ginzburg–Landau equation; saddle-node bifurcation; localized structures

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Periodic Nucleation Solutions of the Real Ginzburg-Landau Equation in a Finite Box.

Argentina M.; Descalzi, O.; Tirapegui, E. | International Journal of Bifurcation and Chaos 12 N°10, 2219-2228. | 2002

We study the stationary solutions of the real Ginzburg–Landau equation with periodic boundary

conditions in a finite box. We show explicitly how to construct nucleation solutions allowing

transitions between stable plane waves.

Keywords: Nucleation solutions; real Ginzburg–Landau equation; Eckhaus instability;

Lyapounov functional.

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Thermodynamic Potentials for Non-equilibrium Systems.

Descalzi, O.; Martínez, S.; Tirapegui, E. | Chaos, Solitons and Fractals 12, 2619-2630. | 2001

The notion of non-equilibrium potential for systems far from equilibrium is reviewed and the relation to the reversed process is examined. The potential is constructed in the neighborhood of the homogeneous attractors for a non-variational extended system, namely the subcritical complex Ginzburg–Landau equation. This construction is the second known example of a Lyapunov functional for a non-variational system.

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Non-variational effects in non-equilibrium systems.

Barra, F;, Descalzi, O.; Tirapegui, E. | Physics Letters A 221, 193-196. | 1996

We consider walls connecting symmetric states in nonvariational one dimensional spatially extended systems. We show that the problem can be analyzed in terms of a free energy (nonequilibrium potential), which takes the same value in the asymptotic states (x→±∞). The motion of the walls can be understood as a residual dynamics on an extended attractor in which the free energy takes a constant value.

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Non-equilibrium potential for the Ginzburg-Landau equation in phase-turbulence regime

Descalzi, O.; Graham, R. | Zeitschrift für Physik B 93, 509-513. | 1994

The steady state distribution functional of the supercritical complex Ginzburg-Landau equation with weak noise is determined asymptotically for long-wave-length fluctuations including the phaseturbulent regime. This is done by constructuring a non-equilibrium potential solving the Hamilton-Jacobi equation associated with the Fokker-Planck equation. The non-equilibrium potential serves as a Lyapunov functional. In parameter space it consists of two branches which are joined at the Benjamin-Feir instability. In the Benjamins-Feir stable regime the non-equilibrium potential has minima in the plane-wave attractors and our result generalizes to arbitrary dimension an earlier result for one dimension. Beyond the Benjamin-Feir instability the potential in the function space has a minimum which is degererate with respects to arbirary long-wavelength phase variations. The dynamics on the minimum set obey the generalized Kuramoto-Sivashinsky equation.

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Gradient expansion of the non-equilibrium potential for the supercritical Ginzburg-Landau equation.

Descalzi, O.; Graham, R. | Physics Letters A 170, 84-90. | 1992

A gradient expansion is used to obtain a Lyapunov functional (the nonequilibrium potential) for the supercritical complex Ginzburg-Landau equation. The method simplifies the task of solving the Hamilton-Jacobi equation associated with the steady-state distribution of the stochastic Ginzburg-Landau equation with weak noise and it confirms and extends results obtained previously by a more tedious calculation. The method opens the possibility for studying other situations not yet explored.

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Non-equilibrium Potentials near Instabilities.

Descalzi, O.; Tirapegui, E. | Journal of Statistical Physics 57, 993-1012. | 1989

The existence of polynomial approximations for nonequilibrium potentials determined by a master equation near an instability of arbitrary codimension with diagonalizable linear part is studied. It is shown that the approximations exist, provided some relations are satisfied between the coefficients of the master equation.

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Industrial

Assessment of maritime operations efficiency and its economic impact based on data envelopment analysis: A case study of Chilean ports

Magdiel A.Agüero-Tobar; Marcela C. González-Araya; Rosa G.González-Ramírez | Research in Transportation Business & Management | 2022

Ports are facing several logistical challenges and changes in globalization patterns. For this reason, port operations need to be more efficient than ever. Moreover, they can be classified as maritime operations, terminal operations, and connectivity or land operations. Regarding this, maritime operations represent around 48% of the transport costs and are defined as the processes involved from a vessel’s arrival to a dock until the end of its cargo transference. This research focuses on the efficiency analysis of these operations using data envelopment analysis and proposes a method for estimating economic impacts when efficient maritime operations are achieved. A literature review is carried out in order to present a classification of port variables used in data envelopment analysis. In this way, the variables’ classification supports the selection of maritime operation variables for the efficiency analysis. A case study of twelve Chilean containerized port cargo terminals is used to illustrate the proposed method, where results of the analysis are discussed. For inefficient ports, medium and long-term recommendations (goals) are presented and economic savings are estimated. In this way, the proposed methodological framework can be a useful tool to support policy-making decisions with respect to prioritizing port infrastructure investments.

Keywords: Port efficiency; Maritime operations; Data envelopment analysis; Variable classification; Port case study; Economic impact

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Assessing the implementation of governance best practices by Latin American ports

Maria D. Gracia, Rosa G. González-Ramírez, Luis M. Ascencio & Julio Mar-Ortiz | Maritime Economics & Logistics | 2022

In this paper, a semi-structured interview approach is used to assess governance and institutionalist practices promoted among successful port systems worldwide, in Latin American ports. The aim is to provide recommendations that would allow Latin American ports to reach high performance scores through governance practices, and face the challenges imposed by the COVID-19 pandemic, fostering a more resilient port ecosystem. A three-stage methodological framework, composed of six steps, is proposed. In the first stage, semi-structured interviews were carried out, with a total of 178 participants, to assess the state of implementation of governance practices in 24 Latin American ports. These practices were identified from a literature review and are promoted among successful port systems worldwide. In a second stage, the relationship between governance practices in ports and their performance was analyzed, aiming to identify those governance and institutionalist strategies that are most extensively used by the best performing ports. Finally, in a third stage, we provide recommendations that would allow Latin American ports to reach high performance scores through improved governance practices. The results indicate that digitalization and coordination among the stakeholders of the port logistics community are two of the most cited governance practices in the best performing Latin American ports. This paper contributes to the theory of port governance in Latin America, by empirically relating and identifying those governance practices which contribute to port performance. Keywords: Port governance; Latin American ports; Port logistics communities; Port management; Best practice analysis

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Design of Empty Container Depot Layouts Using Data and Analytics

Erhan Karakaya, Alice E. Smith, Rosa G. González Ramírez & Jimena Pascual | Flexible Services and Manufacturing Journal | 2022

This paper presents an approach using a combination of data-driven and analytical models to design the layout of empty container depots where top-lifters (TLs) are used. A method to determine the optimum number of blocks along with the number of driving lanes is proposed where the size of the blocks is specified by the number of rows, tiers, and bays. For estimating the effects of the design variables on the TL cycle time, formulas to calculate the expected travel distance of these vehicles are derived based on geometry and a Markov chain model is used to obtain the times of retrieval and placement by the TLs using data gathered in an empirical study from a typical empty container yard. Together, the total cycle time (travel, retrieval, and placement) is then used as the objective function to evaluate alternative container yard layout options. Numerical examples from a case study are provided to illustrate the layout design procedure and show its effectiveness and pragmatism. Keywords: Depot layout; Empty shipping container; Maritime logistics; Container yards; Data analytics

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A Decision Support System for container handling operations at a seaport terminal with disturbances: design and concepts

Rosa G. González-Ramírez, Jana Ries, Luis M. Ascencio | Handbook on Decision Making: Volume 3: Trends and Challenges in Intelligent Decision Support Systems, SPRINGER | 2022

Container handling operations at a container terminal are very complex because several stakeholders are involved, requiring different procedures and interactions. In addition, different disturbances may affect daily operations, demanding significant efforts to decision makers to incorporate resiliency as part of the criteria for decision making. In this book chapter we present some concepts and ideas for the design of a Decision Support System (DSS) to support container handling operations at the yard of maritime terminals considering disturbances that may affect daily operations. We also present the results of an empirical analysis to explore what are the main disturbances that affect port operations. For this, four ports in Chile were considered and the study was based on a survey. We derive some conclusions and recommendations.

Keywords: Decision support system; Container handling; Disturbances

Yard management

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Improving debt collection via contact center information: a predictive analytics framework

Catalina Sánchez, Sebastian Maldonado, Carla Vairetti | Decision Support Systems | 2022

Debt collection is a very important business application of predictive analytics. This task consists of foreseeing repayment chances of late payers. In this sense, contact centers have a central role in debt collection since it improves profitability by turning monetary losses into a direct benefit to banks and other financial institutions. In this paper, we study the influence of contact center variables in predictive models for debt collection, which are combined with the financial information of late payers. We explore five different variants of three predictive analytics tasks: (1) the probability of successfully contacting a late payer, (2) the probability of achieving a contact that results in a promise to pay a debt, and (3) the probability that a defaulter repays his/her arrears. Four research questions are developed in the context of debt collection analytics and empirically discussed using data from a Chilean financial institution. Our results show the positive impact of the combination of the two data sources in terms of predictive performance, confirming that valuable information on late payers can be collected from contact centers. Keywords: Debt collection; Contact center; Call center; Predictive analytics; Data integration

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Assessing the implementation of governance best practices by Latin American ports

Maria D. Gracia, Rosa G. González-Ramírez, Luis M. Ascencio & Julio Mar-Ortiz

Maritime Economics & Logistics, 2022

In this paper, a semi-structured interview approach is used to assess governance and institutionalist practices promoted among successful port systems worldwide, in Latin American ports. The aim is to provide recommendations that would allow Latin American ports to reach high performance scores through governance practices, and face the challenges imposed by the COVID-19 pandemic, fostering a more resilient port ecosystem. A three-stage methodological framework, composed of six steps, is proposed. In the first stage, semi-structured interviews were carried out, with a total of 178 participants, to assess the state of implementation of governance practices in 24 Latin American ports. These practices were identified from a literature review and are promoted among successful port systems worldwide. In a second stage, the relationship between governance practices in ports and their performance was analyzed, aiming to identify those governance and institutionalist strategies that are most extensively used by the best performing ports. Finally, in a third stage, we provide recommendations that would allow Latin American ports to reach high performance scores through improved governance practices. The results indicate that digitalization and coordination among the stakeholders of the port logistics community are two of the most cited governance practices in the best performing Latin American ports. This paper contributes to the theory of port governance in Latin America, by empirically relating and identifying those governance practices which contribute to port performance.

Ver enlace externo


Assessment of maritime operations efficiency and its economic impact based on data envelopment analysis: A case study of Chilean ports

Magdiel A.Agüero-Tobar; Marcela C. González-Araya; Rosa G.González-Ramírez

Research in Transportation Business & Management, 2022

Ports are facing several logistical challenges and changes in globalization patterns. For this reason, port operations need to be more efficient than ever. Moreover, they can be classified as maritime operations, terminal operations, and connectivity or land operations. Regarding this, maritime operations represent around 48% of the transport costs and are defined as the processes involved from a vessel’s arrival to a dock until the end of its cargo transference. This research focuses on the efficiency analysis of these operations using data envelopment analysis and proposes a method for estimating economic impacts when efficient maritime operations are achieved. A literature review is carried out in order to present a classification of port variables used in data envelopment analysis. In this way, the variables’ classification supports the selection of maritime operation variables for the efficiency analysis. A case study of twelve Chilean containerized port cargo terminals is used to illustrate the proposed method, where results of the analysis are discussed. For inefficient ports, medium and long-term recommendations (goals) are presented and economic savings are estimated. In this way, the proposed methodological framework can be a useful tool to support policy-making decisions with respect to prioritizing port infrastructure investments.

Ver enlace externo


Optimal bundle composition in competition for continuous attributes

K. Page, J. Pérez, H. López, C. Telha, A. García. | European Journal of Operational Research | 2021

We propose a model to design bundles’ composition under competition, quantifying its effect in terms of profit and market share in a game among competing firms. According to our literature review, no previous models on optimal bundle composition can handle the competition as we do in this paper. Besides, we explain how a firm designing multiple bundles with equal price obtains a replication of identical bundles and an artificially increased estimation of the firm’s profit and market share, which is a consequence of the well-known Independence of Irrelevant Alternatives Property. To mitigate this effect, we use the Constrained Multinomial Logit Model, which induces differentiation in composition through soft constraints that represent the minimum quantity of the attributes offered in bundles. Although this methodology helps, its use implies more effort to estimate its parameters; nevertheless, these are feasible to be assessed. Firms can use our model to identify the bundles in which they should focus their commercial efforts, given the characteristics of their consumers.

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A maximum entropy optimization model for origin-destination trip matrix estimation with fuzzy entropic parameters

H. López-Ospina, C. Cortés, J. Pérez, R. Peña, J. Figueroa, J. Urrutia. | Transportmetrica A: Transport Science | 2021

We formulate a bi-objective distribution model for urban trips constrained by origins and destinations while maximizing entropy. We develop a flexible and consistent approach in which the estimations of generated/attracted parameters are fuzzy with entropic membership functions. Based on a fuzzy-entropy approach, we measure the uncertainty associated with fuzzy variables. We solve the problem by means of compromise programming considering a weighted sum objective function. We compute and extend concepts such as accessibility, attractiveness, and generalized cost, typically obtained in transport economic analyzes. Considering that our formulation is convex, we solve the problem in one step only, maintaining the uniqueness of the the optimization problem solution. We present two numerical examples to illustrate the proposed methodology, analyzing the impact of the results based on strong mathematical and statistical arguments. Finally, we show that our approach has better prediction capabilities than traditional fuzzy models regarding aggregated indicators and structural distribution patterns.

Keywords: Entropy optimization; Origin-destination trip matrix; Transport distribution; Fuzzy sets; Fuzzy entropy

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Telecom traffic pumping analytics via explainable data science

M.E. Irarrázaval. S. Maldonado, J. Pérez, C. Vairetti | Decision Support Systems | 2021

Traffic pumping is a type of fraud committed in several countries, in which small telephone operators inflate the number of incoming calls to their networks, profiting from a higher access charge in relation to the network operator associated with the origin of the call. The identification of traffic pumping is complex due to the lack of labels for performing supervised learning, and the scarce literature on the topic. We propose a decision support system for fraud detection via clustering and decision trees. After data collection and feature engineering, we group the potential fraud cases into various clusters via an unsupervised learning approach. Then, we constructed a decision tree by using the cluster memberships as labels, evolving into the rules of a given variable and a certain label required for filing lawsuits against the suspicious cases. Telecommunication experts validate these rules to seek a legal resource against alleged perpetrators. We present the results of a case study from a Chilean telecommunication provider. All the lawsuits taken by the legal department were granted, confirming our success in dramatically reducing current and future fraud losses for the company. Keywords: Fraud prediction; Unsupervised learning; Interpretable machine learning; EXplainable AI (XAI); Telecommunications

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On the effect of product demand correlation on the storage space allocation problem in a fast-pick area of a warehouse

F. Gré; A. Ossa; R. González-Ramírez; M. Vélez | Lecture Notes of Computer Science | 2021

The storage location assignment problem (SLAP), also known as the slotting problem involves the decisions of how much and where should be stored each stock keeping unit (SKU) in the fast-pick area with the aim to minimize total order-picking and replenishment costs associated to the distance traveled by the picking operators. Motivated by this, we propose to analyze the impact of SKUs demand correlation on the slotting decisions. Based on an experimental design, the effects of SKUs with correlated demand are analyzed. Results show that the most significant factor with respect to the total distance traveled is the number of orders, followed by the capacity of the bins and the number of bins in each location. Results of an instance solved to optimality by a commercial solver and a greedy heuristic in which the latter does not consider the demand correlation illustrate the impact that demand correlation has on the solution obtained.

Keywords: Warehousing; Slotting problem; Order-picking; Demand Correlation; Fast-pick area

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A Production Planning MILP Optimization Model for a Manufacturing Company

Cedillo-Robles, J.A., Smith, N.R., González-Ramirez, R.G., Alonso-Stocker, J., Alonso-Stocker, J., Askin, R.G | Communications in Computer and Information Science | 2021

This paper proposes a mixed-integer linear programming (MILP) model that is implemented based on a rolling horizon scheme to solve an aggregate production planning decision problem of a manufacturing company that produces snacks in Monterrey, Mexico. The demand of the company is characterized by trends and seasonality. The proposed solution is evaluated by means of computational experiments to determine the relation between demand uncertainty and flexibility of a production system. A 2k factorial experimental design and a multivariate regression were performed. Results show forecast bias and length of frozen period in the rolling horizon have a strong effect on total profit. The safety stock level was also found to be a significant factor, depending on the level of bias.

Keywords: Production planning; Rolling horizon; Forecast error; Flexibility factors

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An Operational Planning Model to Support First Mile Logistics for Small Fresh-Produce Growers

Majluf-Manzur, Á.M., González-Ramirez, R.G., Velasco-Paredes, R.A., Villalobos, J.R. | Communications in Computer and Information Science | 2021

In this work, we propose a hierarchical optimization model to support harvest and local routing decisions of fresh agricultural products. The proposed model has been motivated by the fact that small growers of fresh produce very often face difficulties in terms of availability of local (or first-mile) logistics at reasonable prices which results in lower profit margins and more food waste. So, in order to reduce the cost of first-mile logistics they can co-ordinate the consolidation of the harvests from different growers to send their products to the packing facility. Hence, we integrate harvesting and routing operations for a set of small growers with the aim to reduce their operational costs. The proposed framework has been implemented and preliminary evaluated with some instances considering as case study farmers of fresh produce in the central region of Chile.

Keywords: First mile logistics; Small fresh-produce growers; Harvesting and distribution planning

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Desafíos de transformación institucional y digital en autoridades portuarias sudamericanas. Caso del Puerto de Buenos Aires Argentina

Luis M. Ascencio, Sergio Gorgone, Rosa G. González-Ramírez | Editions EMS Management & Society. SEFACIL Foundation | 2021

Este capítulo aborda los desafíos de la transformación digital que comienzan a

enfrentar la inmensa mayoría de las autoridades portuarias creadas en Sudamérica

con las reformas de los 90’s y 2000. Los estados nacionales consolidaron

empresas, consorcios y autoridades portuarias locales de derecho privado y

titularidad estatal, con énfasis en la descentralización y fomento a las inversiones

privadas. La irrupción de las tecnologías de información en la industria marítimoportuaria surge con el advenimiento en los 90 de los estándares EDIFACT y

posteriormente los protocolos basados en Internet y donde los principales

puertos globales adoptaron rápidamente soluciones tecnológicas, por ejemplo,

un Port Community System (PCS), que requiere el trabajo colaborativo de toda

la comunidad portuaria. La colaboración técnica entre la Autoridad Portuaria de

Barcelona y AGP-Puerto Buenos Aires permitió a este último iniciar el camino a

la modernización digital desarrollando actividades de planificación y transición

entre los años 2000 y 2020, para crear un plan estratégico integral en 2020 que

recoge todas las lecciones aprendidas y que le permitirá escalar sus actuales

soluciones para convertirse al final de esta década en un smart port o puerto

inteligente.

Palabras clave: Digitalización en puertos, Port Community Systems, Intercambio

Electrónico de Datos, Smart port

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A cooperative game model for the Port of Valparaiso and San Antonio in Chile

Ana María Vallina, Rosa G González-Ramírez, Ariel Gutiérrez-Ortiz | Editions EMS Management & Society. SEFACIL Foundation | 2021

This chapter proposes an econometric model considering a cooperativecompetitive game between the main terminals of the Port of Valparaiso and the

Port of San Antonio in Chile. Two cases are analysed: a Cooperative game and

a Non-Cooperative game in order to determine the benefits achieved by the two

terminals. The analysis presented is based on the implementation of two games:

cooperative and non-cooperative, in order to analyse the potential benefits that

cooperation may have between these two ports, that are located very closed

to each other geographically, sharing the same hinterland. Results show the

advantages of cooperation among these two ports by achieving higher profits

than just competing to capture market against each other.

Keywords: Competition; cooperation; seaport; game theory.

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An option contract model for leasing containers in the shipping industry

We propose an option contract model for the leasing of containers. In an option contract, the shipping company commits to order a quantity of containers from the leasing company and has the right to modify its order at a later stage, according to its actual requirement. Under this scheme, the shipping company is allowed to request a smaller or larger number of containers than the agreed initial order. This is done by buying an option premium in advance from the container leasing company. We present numerical results for different scenarios based on information provided by experts in the industry. For the purposes of comparison, a nonoption contract scheme is also evaluated. According to our numerical results, an option contract is better under a scenario where demand is normally distributed with a large standard deviation. This scenario is commonly observed in practice due to the dynamism and volatility of the shipping industry. We conclude that, under an option contract scheme, the shipping company has more flexibility to adjust its demand for containers and to be requested from the leasing company, and this adjustment is compensated by an option price determined according to variations in demand. Keywords: Container leasing; Option contracts; Cox–Ross–Rubinstein pricing model; Maritime shipping; Shipping line

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Best practices in manufacturing processes: Experiences from Latin America

García Alcaraz, J.L., Rivera Cadavid, L., González-Ramírez, R.G., Leal Jamil, G., Chong, M. | Springer | 2021

This book reports the best practices that companies established in Latin America are implementing in their manufacturing processes in order to generate high quality products and stay in the market. It lists the technologies, production and administrative philosophies that are being implemented, presenting a collection of successful cases of studies from Latin America. The book describes how the tools and techniques are being integrated, modified and combined to create new technical resources for assisting the decision making process for better economic performance in manufacturing companies. The efforts deployed for assisting the transformation of raw materials into products and services are described. The authors explain the main key success factors or drivers for success of each tool, technique or hybrid combination approach applied to solve manufacturing problems.

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Spectrum assignment for connected vehicles: Local licensing versus coopetition.

Basaure, A., Finley, B., & Hämmäinen, H. | Computer Communications, 179, 157-165. | 2021

The deployment of 5G urban networks is often described as a disruptive phenomenon since it enables new emerging Internet of Things (IoT) applications such as connected vehicles. Such applications demand new spectrum regulations to decrease network investment requirements by incentivizing operator cooperation. However, currently, no clear consensus exists on the appropriate regulatory regime for such an urban deployment. This work explores two main alternative regulatory scenarios for a connected vehicle use case. Both alternatives lower implementation costs while promoting competition. The first alternative is to maintain the current scheme of spectrum assignment while facilitating additional flexibility for infrastructure sharing (ex-post competition). The second alternative is to define local areas for monopoly 5G provisioning and define the conditions for competition ex-ante. Through agent-based simulations, this work shows that a local licensing of spectrum scenario may achieve better performance than alternative scenarios with traditional spectrum assignment. Additional sensitivity checks also help detail the practical trade-offs.

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Design of a location and transportation optimization model including quality of service using constrained multinomial logit.

Héctor López-Ospina, Ángela Agudelo-Bernal, Lina Reyes-Muñoz, Gabriel Zambrano-Rey, Juan Pérez. | Applied Mathematical Modelling 89 (2021) 428-453. | 2021

The design of an integrated network with decisions about tactical transportation and strategic locations is complicated and challenging. In addition to the need to consider cost issues, the consumers’ preferences will also have a significant impact on the resulting network. We propose an integrated transportation and location optimization model for designing logistic networks. Our model uses a hybrid iterative heuristic based on a genetic algorithm and a constrained multinomial logit, which includes consumers’ preferences and quality of service variables. Our results show relevant differences when considering, along with network costs, parameters related to the consumers: travel distance, congestion, waiting time, and service time.

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Does Education Mitigate the Effect of Population Aging on Health Expenditure? A Panel Data Study of Latin American Countries.

Borrescio, F.; Valenzuela P. | Journal of Aging and Health, 585-595. | 2021

Objective: To examine whether the effect of population aging on healthcare expenditures as a share of Gross Domestic Product (GDP) is attenuated in more educated countries. Method: The analysis is based on a dataset of 22 Latin American countries between 1995 and 2013. We estimate panel data models with country and time fixed effects, and control for potential nonlinear effects of population aging on health expenditure. Results: We find population aging increases health expenditure as a share of GDP in economies characterized by low levels of education, but this effect is mitigated in economies with higher levels of education. Results are driven by private health expenditures. Discussion: Results suggest population aging and education have a stronger influence on healthcare expenditures in less developed countries. This finding is important in a context in which the rapid growth of the aging population is likely to lead to significant costs in terms of health expenditures, but less so in more educated societies.

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Gender Inequality and Mental Health during the COVID-19 Pandemic.

Borrescio, F.; Valenzuela P. | Interntional Journal of Public Health. | 2021

Objective: We explore gender differences in mental health deterioration and psychological well-being due to the COVID-19 pandemic, as well as the mechanisms through which these differences may operate.

Methods: Using data from the Life during Pandemic survey in Chile, which covers 2,545 adult respondents, we estimate econometric models to explore gender differences in psychological well-being and mental health as well as economic fragility and household workload during the COVID-19 pandemic.

Results: We find women are more likely to report overall bad mental health and deterioration of well-being. They are also more likely to have a new diagnosis of a mental health problem, to be pursuing treatment and taking prescription medication. Moreover, women report an increase in household chores and in childcare, and are more likely to have lost their employment or experienced a loss of income due to the pandemic.

Conclusion: Our results offer a general picture of gender differences in the psychological impact of COVID-19. We argue that policies that mitigate economic stress and address the needs of women specifically may ease mental health deterioration due to the pandemic.

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The strategic design of port services based on a total landed cost approach

González-Ramírez, R.G.; Villalobos, R.; Meneses, C. | International Journal of Logistics Management, 32 (1), 96-120. | 2021

Purpose

This paper explores the effect of port’s service time, particularly the mean and variability, on shippers’ total landed costs to determine the competitive position of the port and derive recommendations for the strategic design of port services.

Design/methodology/approach

The competitive position of a port is estimated considering the service level offered to the end-users of the port such as port service time, its variability and its effect on the total landed costs observed by the port users. The proposed methodology is meant to help ports to determine the required service time levels to maintain or gain a competitive advantage against other ports, in terms of attracting common hinterland’s customers.

Findings

Results show the advantages of considering service levels factors to determine the competitive position of a port, and what are the minimum characteristics required to capture more traffic volumes, that can help port managers to take strategic design decisions to better position the port in the current fierce market.

Research limitations/implications

The proposed methodology is illustrated by considering a case study, which is the Port of Guaymas in Mexico. Data was not directly collected by the port, but based on interviews with shippers and public information, a representative case is presented. Due to a confidentiality agreement with the Port, specific references for most of the data used to estimate the model’s parameters are not provided. The analysis is intended to show the potential value of this mechanism and can be used for evaluating the competitive position, from a high-level perspective, of any port to determine potential hinterland by improving the service level of the port.

Originality/value

The existing literature on port choice and port competition has not previously considered the effect of port service levels under the perspective of total landed costs of the users, being this paper a contribution to fulfill this gap.

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A two stage cap-and-trade model with allowance re-trading and capacity investment: The case of the Chilean NDC targets.

Amigo, P.; Feijoo, F.; Cea-Echenique, S. | Energy 224. | 2021

In this work, we study an alternative approach for capping and pricing carbon emissions in electric markets: the cap-and-trade paradigm with re-trade of allowances. We model the electric market (generators and allowances’ auctioneer) as a two stage stochastic capacity expansion equilibrium problem, where we allow future investment and re-trading of emission permits among generators. The model studies generation and future investments in the electric sector in two regimes of demand: deterministic and stochastic. The configuration enforces the reduction of carbon emissions by setting a carbon budget, which allows to assess the impact of green policies and pledges concerning an electric system. We use the proposed model to analyze the Chilean electric sector under a cap-and-trade paradigm as an alternative to the existing carbon tax. We show that the Chilean pledge regarding emissions reductions does not encourage a shift to greener technologies. Moreover, we characterize two strategies to comply with the renewable targets by mid-century. On the one hand, a stringent carbon budget that induces high price of carbon permits and phases out coal-based generators. On the other hand, a less stringent target which significantly encourages investment in renewable technologies, but with low remaining shares of coal-based electric generation towards 2050. Keywords: Cap-and-trade; Emissions trading; Mixed complementarity problem; Incomplete markets; Stochastic capacity investment; NDC

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Independent Sets and Hitting Sets of Bicolored Rectangular Families.

Soto, J.A, Telha C. | Algorithmica 82, 1918-1952. | 2021

A bicolored rectangular family BRF is the collection of all axis-parallel rectangles formed by selecting a bottom-left corner from a finite set of points A and an upper-right corner from a finite set of points B. We devise a combinatorial algorithm to compute the maximum independent set and the minimum hitting set of a BRF that runs in O(n2.5logn−−−−√)-time, where n=|A|+|B|. This result significantly reduces the gap between the Ω(n7)-time algorithm by Benczúr (Discrete Appl Math 129 (2–3):233–262, 2003) for the more general problem of finding directed covers of pairs of sets, and the O(n2)-time algorithms of Franzblau and Kleitman (Inf Control 63(3):164–189, 1984) and Knuth (ACM J Exp Algorithm 1:1, 1996) for BRFs where the points of A lie on an anti-diagonal line. Furthermore, when the bicolored rectangular family is weighted, we show that the problem of finding the maximum weight of an independent set is NP-hard, and provide efficient algorithms to solve it on important subclasses. Keywords: Independent set; Hitting set; Axis-parallel rectangles; Jump number

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The strategic design of port services based on a total landed cost approach.

González-Ramírez, R. G., Villalobos, J. R., Meneses, C. | International Journal of Logistics Management. In press | 2020

Purpose

This paper explores the effect of port’s service time, particularly the mean and variability, on shippers’ total landed costs to determine the competitive position of the port and derive recommendations for the strategic design of port services.

Design/methodology/approach

The competitive position of a port is estimated considering the service level offered to the end-users of the port such as port service time, its variability and its effect on the total landed costs observed by the port users. The proposed methodology is meant to help ports to determine the required service time levels to maintain or gain a competitive advantage against other ports, in terms of attracting common hinterland’s customers.

Findings

Results show the advantages of considering service levels factors to determine the competitive position of a port, and what are the minimum characteristics required to capture more traffic volumes, that can help port managers to take strategic design decisions to better position the port in the current fierce market.

Research limitations/implications

The proposed methodology is illustrated by considering a case study, which is the Port of Guaymas in Mexico. Data was not directly collected by the port, but based on interviews with shippers and public information, a representative case is presented. Due to a confidentiality agreement with the Port, specific references for most of the data used to estimate the model’s parameters are not provided. The analysis is intended to show the potential value of this mechanism and can be used for evaluating the competitive position, from a high-level perspective, of any port to determine potential hinterland by improving the service level of the port.

Originality/value

The existing literature on port choice and port competition has not previously considered the effect of port service levels under the perspective of total landed costs of the users, being this paper a contribution to fulfill this gap.

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The Effects of Increasing Penalties in Drunk Driving Laws-Evidence from Chile

García-Echalar, A.; Rau, T. | International Journal of Environmental Research and Public Health | 2020

This paper analyzes Chile’s drunk driving laws and their effects on car crashes, injuries, and deaths. There were two policy changes. While the 2012 law increased license suspension penalties and decreased the legal blood alcohol limits for drivers, the 2014 law only increased sanctions, including at least one year of actual imprisonment for drunk driving implicated in car crashes with severe injury or death. We use a rich data set of countrywide administrative records that permit us to identify direct measures of alcohol-related accidents, including fatalities and injuries. We also have access to blood alcohol tests to assess whether the laws affected drivers’ alcohol consumption. Using count data models and a rich set of covariates, including police stops and gasoline sales, we find a short-run decrease in accidents and injuries for the 2012 law and a sustained decline in these outcomes for the 2014 law. Neither intervention has an effect on deaths. There is a marginal decline in alcohol consumption after the enactment of both legal changes. However, while the 2012 law only affects male drivers, the 2014 law affects both males and females. No reductions in alcohol intake are found for heavy drinkers.

Keywords: drunk driving law; increasing penalties; car accidents; injuries and deaths

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MODELO ESTRATÉGICO RECONFIGURÁVEL PARA A LOGÍSTICA DA INTERFACE TERRESTRE PORTUÁRIA NO CHILE

Rosa G González-Ramírez, Luis M Ascencio, Carla Vairetti, María Dolores Gracia, Julio Mar-Orti | Revista Eletrônica de Estratégia & Negócios | 2020

Este artículo propone el diseño de una plataforma para apoyar el diseño de políticas públicas del transporte de carga. Como foco de atención se tiene lo que se denomina la “última milla portuaria” o interfaz terrestre de los puertos en la zona interportuaria que se conoce también como transporte drayage. A modo de caso de estudio, se considera el Puerto de San Antonio. Los resultados de las pruebas y experimentación servirán como recomendaciones de reglamentos y normativas para el diseño y desarrollo de servicios de economía circular en una comunidad logística portuaria, así como políticas públicas para el sector. Palabras clave: Transporte drayage de carga, Puertos marítimos, Políticas públicas para la facilitación del transporte, modelos de apoyo a decisiones.

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Internet of things (IoT) platform competition: Consumer switching versus provider multihoming

Basaure, A.; Vesselkov, A.; Töyli, J. | Technovation, 90, 102101 | 2020

Internet of things (IoT) brings new opportunities and represents a new source of welfare and efficiency. However, the emerging consumer IoT platform competition creates the risk of monopoly power due to network effects. Overall, it is likely that both competition (incentivized through lowering consumer switching costs) and cooperation (achieved through interoperability, which enables data portability and service provider multihoming) are needed to maximize social welfare. This article aims to address how consumer switching costs and provider multihoming affect competition of emerging consumer IoT data platforms under different market conditions and regulatory schemes. It utilizes agent-based modelling that is especially suitable when decision making is distributed at a micro level while some rules are applied in a centralized fashion. The obtained findings emphasize the role of the regulator in guiding the market. It seems that when switching costs diminish at all sides of the platforms, consumers and service providers will favour the platform with a higher number of users. Further, service provider multihoming mitigates market concentration on both sides of a platform when switching costs are low. Thus, there seems to be a minimum level of interoperability needed to promote market competition. Further, although data portability gives more freedom to consumers in choosing a platform provider, it may result in a winner-takes-all situation due to strong indirect network effects.

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Design of a location and transportation optimization model including quality of service using constrained multinomial logit

López H., Águdelo A., Reyes L., Zambrano G.; Pérez, Juan. | Applied Mathematical Modelling. 89:428-453 | 2020

The design of an integrated network with decisions about tactical transportation and strategic locations is complicated and challenging. In addition to the need to consider cost issues, the consumers’ preferences will also have a significant impact on the resulting network. We propose an integrated transportation and location optimization model for designing logistic networks. Our model uses a hybrid iterative heuristic based on a genetic algorithm and a constrained multinomial logit, which includes consumers’ preferences and quality of service variables. Our results show relevant differences when considering, along with network costs, parameters related to the consumers: travel distance, congestion, waiting time, and service time.

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Desafíos de transformación institucional y digital en Autoridades portuarias sudamericanas. Caso del Puerto de Buenos Aires Argentina

Luis M. Ascencio, Sergio Gorgone, Rosa G. González-Ramírez | Dinámica portuaria en el Caribe y América Latina. Ports in transition to face global challenges. Editions EMS Management & Society. SEFACIL Foundation. | 2020

This chapter addresses the challenges of the digital transformation that the vast

majority of port authorities created in South America are facing with the reforms

of the 90’s and 2000. The national states consolidated companies, consortia

and local port authorities of private law and state ownership, with emphasis

on decentralization and promotion of private investment. The emergence of

information technologies in the maritime-port industry arises with the advent of the

EDIFACT standards in the 90s and later the internet-based protocols where the

main ports rapidly adopt technological solutions, for example, a Port Community

System, that requires the collaborative work of the entire port community. The

technical collaboration between the Barcelona Port Authority and AGP-Puerto

Buenos Aires lead the latter to initiate the path to digital modernization by

developing planning and transition activities between 2000 and 2020, to create

a comprehensive strategic plan in 2020 that includes all the lessons learned and

that allowed it to scale its current solutions to become a smart port at the end of

this decade.

Keywords: Port Digitalization, Port Community System, Electronic Data

Interchange, smart port

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Special issue: Data-driven decision making in Latin American supply chains (Ed.)

Cedillo-Campos, G., González-Ramírez R.G., Mejía-Argueta, C., González-Felliu, J. | Computers & Industrial Engineering. Volume 139, 1-4. | 2020

No Abstract Avialable

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An option contract model for leasing containers in the shipping industry.

Gómez-Padilla, A., González-Ramírez, R. G., Alarcón, F., Voß, S. | Maritime Economics & Logistics. | 2020

We propose an option contract model for the leasing of containers. In an option contract, the shipping company commits to order a quantity of containers from the leasing company and has the right to modify its order at a later stage, according to its actual requirement. Under this scheme, the shipping company is allowed to request a smaller or larger number of containers than the agreed initial order. This is done by buying an option premium in advance from the container leasing company. We present numerical results for different scenarios based on information provided by experts in the industry. For the purposes of comparison, a nonoption contract scheme is also evaluated. According to our numerical results, an option contract is better under a scenario where demand is normally distributed with a large standard deviation. This scenario is commonly observed in practice due to the dynamism and volatility of the shipping industry. We conclude that, under an option contract scheme, the shipping company has more flexibility to adjust its demand for containers and to be requested from the leasing company, and this adjustment is compensated by an option price determined according to variations in demand. Keywords: Container leasing; Option contracts; Cox–Ross–Rubinstein pricing model; Maritime shipping; Shipping line

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A cooperative game model for the Port of Valparaiso and San Antonio in Chile

Ana María Vallina, Rosa G González-Ramírez, Ariel Gutiérrez-Ortiz | Dinámica portuaria en el Caribe y América Latina. Ports in transition to face global challenges. Editions EMS Management & Society. SEFACIL Foundation. | 2020

This chapter proposes an econometric model considering a cooperativecompetitive game between the main terminals of the Port of Valparaiso and the

Port of San Antonio in Chile. Two cases are analysed: a Cooperative game and

a Non-Cooperative game in order to determine the benefits achieved by the two

terminals. The analysis presented is based on the implementation of two games:

cooperative and non-cooperative, in order to analyse the potential benefits that

cooperation may have between these two ports, that are located very closed

to each other geographically, sharing the same hinterland. Results show the

advantages of cooperation among these two ports by achieving higher profits

than just competing to capture market against each other.

Keywords: Competition; cooperation; seaport; game theory.

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Enhancing the classification of Social Media Opinions by Optimizing the Structural Information

Carla Vairetti, Eugenio Martinez Cámara, Sebastián Maldonado, M. Victoria Luzon and Francisco Herrera

Future Generation Computer Systems / ELSEVIER, 2020

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Profit-based Churn Prediction based on Minimax Probability Machines

Sebastián Maldonado, Julio López and Carla Vairetti

European Journal of Operational Research / ELSEVIER, 2020

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Efficient n-gram construction for text categorization using feature selection techniques

Maximiliano García, Sebastián Maldonado, and Carla Vairetti

Intelligent Data Analysis IOS Press, 2020


The impact of operational strategies on vessel handling times: a simulation approach.

Gracia, M.; Mar-Ortiz, J.; González-Ramírez, R. | International Journal of Shipping and Transport Logistics. 11(4):287-315 | 2019

Abstract: This paper reports a study of the ship loading and discharging

process at a container terminal. Our objective was to analyse the impact of

different operational strategies on vessel handling times in order to derive

managerial insights that can be used by terminal operators to manage this key

performance indicator. As a basis for our study, a simulation model was

implemented, validated, and verified to gain insight into the containers loading

and discharging process. Four scenarios were constructed to resemble possible

instances under which a vessel would operate at a Mexican container terminal,

with the different operational strategies that were designed and evaluated for

each scenario. An experimental framework was proposed, based on

comparisons of scenarios and search experimentation, and employing a

fractional factorial design to evaluate the impact of several factors on the vessel

handling times. Our results emphasise that with an adequate design of the

operation parameters, combined with the implementation of efficient stacking

policies; it is possible to keep VHT under control. Conclusions and

recommendations for further research are also discussed.

Keywords: container terminals; simulation analysis; vessel handling times;

VHT; operational strategies; port logistics.

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Robust nonparallel support vector machines via second-order cone programming.

López, J.; Maldonado, S.; Carrasco, M. | Neurocomputing. 364:227-238 | 2019

A novel binary classification approach is proposed in this paper, extending the ideas behind nonparallel support vector machine (NPSVM) to robust machine learning. NPSVM constructs two twin hyperplanes by solving two independent quadratic programming problems and generalizes the well-known twin support vector machine (TWSVM) method. Robustness is conferred on the NPSVM approach by using a probabilistic framework for maximizing model fit, which is cast into two second-order cone programming (SOCP) problems by assuming a worst-case setting for the data distribution of the training patterns. Experiments on benchmark datasets confirmed the theoretical virtues of our approach, showing superior average performance compared with various SVM formulations. Keywords: Support vector machines; Twin support vector machines; Nonparallel support vector machines; Second-order cone programming; Robustness

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Retail store location and pricing within a competitive environment using constrained multinomial logit.

Zambrano-Rey, G.; López-Ospina, H.; Pérez, J. | Applied Mathematical Modelling. 75:521-534 | 2019

The purpose of this paper is to report a pricing and retail location model using the constrained multinomial logit (CMNL), which takes into account customers’ utility and maximum willingness to pay via cut-off soft-constraints. The proposed model is probabilistic and non-linear, therefore a PSO metaheuristic approach was designed to determine the most suitable price, store locations and demand segmentation. The results obtained in test-cases showed a close relationship between price and location decisions. In addition, the results suggest that not only price, but also location decisions are affected when the consumers’ maximum willingness to pay is considered.

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Research Directions in Technology Development to Support Real-Time Decisions of Fresh Produce Logistics

Villalobos, J.R., Soto-Silva, W.E., González-Araya, M., González-Ramírez, R.G. | Computers and Electronics in Agriculture, 167, 105092. | 2019

Recent developments in consumption patterns, lowering of trade barriers, the emergence of low cost/miniature sensors and information technologies, and advanced business analytics tools are changing the playing field on which most of the agri-food supply chains operate. The intelligent use of sensing and information technologies has the potential to start a new food revolution in which limited resources such as water, capital, transportation capacity and labor could be optimally exploited so that fresh food, in particular fruits and vegetables, get to the consumer with minimal or no food waste. One of the keys for making this vision a reality is transforming the data collected as these products traverse the supply chain into effective and efficient supply chain decisions. This transformation relies on that the underlying decision systems that take advantage of this data exist or can be developed. The aim of this paper is to provide an overview of the state of the art and challenges and opportunities emerging from the integration of sensing data and information into decision support systems for supply chain of fresh fruits and vegetables. Keywords: Fresh produce supply chain; Information systems and technology; Decision making

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Regularized minimax probability machine.

Maldonado, S.; Carrasco, M.; López, J. | Knowledge-Based Systems. 177: 127-135. | 2019

In this paper, we propose novel second-order cone programming formulations for binary classification, by extending the Minimax Probability Machine (MPM) approach. Inspired by Support Vector Machines, a regularization term is included in the MPM and Minimum Error Minimax Probability Machine (MEMPM) methods. This inclusion reduces the risk of obtaining ill-posed estimators, stabilizing the problem, and, therefore, improving the generalization performance. Our approaches are first derived as linear methods, and subsequently extended as kernel-based strategies for nonlinear classification. Experiments on well-known binary classification datasets demonstrate the virtues of the regularized formulations in terms of predictive performance. Keywords: Minimax probability machine; Regularization; Second-order cone programming; Support vector machines

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Prospective study using archetypes and system dynamics

Nikulin, C., López-Campos, M., González-Ramírez R.G. | Academia Revista Latinoamericana de Administración, 32(2), 181-202. | 2019

Purpose

The purpose of this paper is to propose a combination of forecasting methods that enables a holistic understanding of a future situation, given certain influencing variables by a combination of real data and expert knowledge.

Design/methodology/approach

The proposal combines two well-known methods: first, system archetypes that correspond to generic structures, allowing us to handle model management issues, and second, system dynamics that offers technical support on a computational level to assess different scenarios or problem solutions.

Findings

The case study considers the situation of the mining industry in Chile and its related variables, including four different scenarios. Based on the proposed methodology, the results indicate that: first, the price of copper is paramount for the industry and its effects are not limited to company profits; second, a long period of downfall in copper prices could halt exploration and development projects.

Research limitations/implications

Systemic archetypes are still a subject of research and their application in different fields of knowledge continues to increase to improve this simulation approach.

Practical implications

The case study illustrates the combination of a Vester matrix and initial system archetype models that are enriched using the system dynamics approach. Indeed, the case study aims to understand the consequences of different scenarios based on the problem-driven approach provided by Vester.

Social implications

The goal of prospective studies of large-scale and complex situations is to model the real situation to obtain solutions that may enhance social welfare.

Originality/value

The proposed methodology contributes to the existing literature by integrating techniques such as the Vester matrix, system archetype modelling and system dynamics simulation, all of which were proposed previously in the literature as independent techniques.

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Modeling and Analysis of the Port Logistical Business Processes and Categorization of Main Logistics Costs.

Vairetti, C.; González, Ramírez,R.; Spaggiari,L.; Gómez, A. | Chapter 20. Editors: Alice E. Smith. In: Women in Industrial and Systems Engineering: Key Advances and Perpectives on Emerging topics. Springer. 457-485. (2019). ISBN: 978-3-030-11865-5. | 2019

Foreign trade in Chile accounts for approximately 30% of the GDP (gross domestic product). In 2015, from the total volume, 92% of the imports and 96% of the exports were transferred by maritime ports. Hence, maritime ports are key nodes of the global transport chain with a strategic role on the country’s economic development. The export and import processes imply a physical flow of the cargo and transportation vehicles, as well as an information flow that is exchanged among the different stakeholders involved. Information transmission can be paper-based or electronic and following international standards and protocols. In the particular case of Chile, data has been traditionally interchanged in paper, lacking a harmonization and standardization of the different documents and information. This generates inefficient operations as well as a lack of coordination and visibility of cargo in the different processes and echelons of the port supply chain. In this chapter, we propose a framework for the modeling and analysis of port-logistics business processes, as well as the corresponding documents and costs. As a case study, we consider the logistics business processes with the participation of a bonded warehouse of the Port of Valparaiso in Chile. These are referred as the “direct and manifested import” business processes and the “Stacking and consolidation export” business process. For comparison purposes, we analyze the logistics costs for the case of the Port of Valparaiso in Chile, the Port of Buenaventura in Colombia, and the Port of Buenos Aires in Argentina. Recommendations to support the standardization of the related processes are presented for port authorities and related stakeholders.

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Facilitating conditions for successful adoption of inter-organizational information systems in seaports.

Vairetti, C.; González, R.; Maldonado, S.; Álvarez, C.; Voβ, S. | Transportation Research Part A. 130:333.350. | 2019

Inter-Organizational Information Systems (IOISs) for seaport logistics facilitate monitoring operations, the exchange of information with stakeholders, and meeting regulations of foreign trade. However, seaport contexts entail complexities in terms of stakeholder involvement and business processes that must be considered thoroughly toward the successful adoption of IOISs. This research seeks to identify factors influencing the successful adoption of IOISs in seaports. It follows a grounded theory approach relying on semi-structured interviews and expert opinions to identify facilitating conditions for the adoption of IOISs. Survey research was conducted in order to investigate the appraisal of different ports in Latin America and the Caribbean region regarding the diverse conditions. The results obtained were analyzed descriptively and through a Principal Components Analysis. The latter was conducted in order to discern relevant dimensions influencing the adoption of IOISs in seaports. The results of the study allow deriving managerial insights and practical recommendations to support technological plans at ports and guide the decision-making regarding the digitalization process. Keywords: Inter-organizational information systems; Seaports; Principal component analysis; Policy recommendations; Grounded theory

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Automatic time series analysis for electric load forecasting via support vector regression.

Maldonado, S.; González, A.; Crone, S. | Applied Soft Computing Journal. 83: 105616. | 2019

In this work, a strategy for automatic lag selection in time series analysis is proposed. The method extends the ideas of feature selection with support vector regression, a powerful machine learning tool that can identify nonlinear patterns effectively thanks to the introduction of a kernel function. The proposed approach follows a backward variable elimination procedure based on gradient descent optimisation, iteratively adjusting the widths of an anisotropic Gaussian kernel. Experiments on four electricity demand forecasting datasets demonstrate the virtues of the proposed approach in terms of predictive performance and correct identification of relevant lags and seasonal patterns, compared to well-known strategies for time series analysis designed for energy load forecasting and state-of-the-art strategies for automatic model selection. Keywords: Analytics; Feature selection; Support vector regression; Time series analysis; Electric load forecasting

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Profit-based credit scoring based on robust optimization and feature selection.

López, J.; Maldonado, S. | Information Sciences. 500: 190-202. | 2019

A novel framework for profit-based credit scoring is proposed in this work. The approach is based on robust optimization, which is designed for dealing with uncertainty in the data, and therefore is effective at classifying new samples that follow a slightly different distribution in relation to the original dataset used to create the model. Instead of minimizing a loss function based on statistical measures, the proposed method maximizes the profit of the credit scoring model, balancing the benefits and losses of granting credit with the variable acquisition costs. The reduction of these is performed using feature selection techniques embedded in the learning process. The robust approach results in four second order cone programming formulations, which can be solved efficiently using interior point algorithms. Experiments on two credit scoring datasets demonstrate the virtues of our approach in terms of its predictive performance, and the managerial insights that can be gained from it.

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Hierarchical time series forecasting via Support Vector Regression in the European Travel Retail Industry.

Karmy, J.; Maldonado, S. | Expert Systems With Applications. 137:59-73. | 2019

Times series often offers a natural disaggregation in a hierarchical structure. For example, product sales can come from different cities, districts, or states; or be grouped by categories and subcategories. This hierarchical structure can be useful for improving the forecast, and this strategy is known as hierarchical time series (HTS) analysis. In this work, a novel strategy for sales forecasting is proposed using Support Vector Regression (SVR) and hierarchical time series. We formalize three different hierarchical time series approaches: bottom-up SVR, top-down SVR, and middle-out SVR, and use them in a sales forecasting project for the Travel Retail Industry. Various hierarchical structures are proposed for the retail industry in order to achieve accurate product-level predictions. Experiments on these datasets demonstrate the virtues of SVR-based hierarchical time series in terms of predictive performance when compared with the traditional ARIMA and Holt-Winters approaches for this task. Keywords: Hierarchical time series; Support Vector Regression; Time series analysis; Sales forecasting

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Analytics meets port logistics: A decision support system for container stacking operations.

Maldonado, S.; Gonzále, R.; Quijada, F.; Ramírez, A. | Decision Support Systems. 121:84-93. | 2019

A Decision Support System (DSS) is proposed in this paper for improving container stacking operations. This DSS addresses the stacking problem for import containers via a two-step strategy. First, dwell times are predicted for each container using analytics techniques. This prediction is used as an input for a mathematical programming model that minimizes container rehandles heuristically. Numerical examples are presented using data from the Port of Arica in Chile as a case study. The results confirm the virtues of the proposed DSS to effectively support planning decisions at the container yard. Furthermore, results also show good performance of the operations at the yard in terms of rehandles in comparison with the current practices of this port terminal and well-known stacking strategies. Keywords: Port logistics; Model-driven decision support systems; Analytics; Dwell time prediction; Container stacking

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An optimization framework for the distribution process of a manufacturing company balancing deliverymen workload and customer’s waiting times.

Camacho, J.; Nucamendi, S.; González, R. | Computers & Industrial Engineering. 137: 106080. | 2019

In this paper, we consider the distribution process of a manufacturing company that supplies products to the customers located in a service region. The company distributes its products partitioning the service region into delivery zones or districts that are served by a single deliveryman. Two objectives are considered when designing the delivery zones: balance the workload associated with each zone, and the minimization of the customers’ waiting times (latency). The former objective concerns a districting decision, and the latter objective is related to a routing decision. To support these planning decisions, an optimization framework based on a novel bi-objective optimization model is proposed. To approximate the frontier of non-dominated solutions of the bi-objective problem, an efficient heuristic algorithm inspired in the -constraint method is developed. The proposed algorithm exploits the characteristics of the problem, and it is used to solve a real case study. Obtained results are compared with the current solution employed by the company. Both objective function values are improved by any of the solutions in the approximated Pareto front. To show the efficiency and robustness of the proposed algorithm, an additional set of instances derived from the case study is tested. The results indicate that the algorithm is able to approximate the Pareto fronts despite their shape. Hence, interesting managerial insights to improve the current decisions of the company are provided derived from the computational experiments. Keywords: Distribution planning; Delivery zones; Bi-objective optimization; Latency; Routing

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Facilitating Conditions for Successful Adoption of Inter-Organizational Information Systems in Seaports

Carla Vairetti, Rosa G. González-Ramírez, Sebastián Maldonado and Claudio Álvarez

Transportation Research Part A: Policy and Practice / ELSEVIER, 2019

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An Alternative SMOTE Oversampling Strategy for High-dimensional Datasets

Sebastián Maldonado, Julio López and Carla Vairetti

Applied Soft Computing / ELSEVIER, 2019

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An Alternative SMOTE Oversampling Strategy for High-dimensional Datasets

Sebastián Maldonado, Julio López and Carla Vairetti

Applied Soft Computing / ELSEVIER, 2019

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Modeling and Analysis of the Port Logistical Business Processes and Categorization of Main Logistics Costs

Carla Vairetti, Rosa González-Ramirez, Luisa Fernanda Spaggiari and Alejandra Gómez Padilla

Women in Industrial and Systems Engineering: Key Advances and Perspectives on Emerging Topics / Springer Book, 2019

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Understanding time use via data mining: a clustering-based framework.

Rosales, J.; Maldonado, S.; Seret, A. | Intelligent Data Analysis 22(3), 597-616. | 2018

Abstract: In this work, a data mining framework is proposed to improve the understanding of how people allocate their time. Using a multivariate approach, we performed a clustering procedure, and subsequently a regression analysis to detect which variables influence individual time use for each cluster found. Results suggest that the impact of various sociodemographic variables on sleep and work depends significantly on the characteristics of the individuals analyzed. This suggests that inquiries into time allocation and individual behavior should no longer be limited to discussions focused only on single variables. Based on our results, we recommend that researchers advance their methodological analysis towards a multifactorial approach and include clustering as a fundamental step. Proper identification of the most significant variables involved in time allocation decisions would allow researchers to better analyze and interpret their data and results.

Keywords: Time use, sleep, work, clustering, data mining

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Robust twin support vector regression via second-order cone programming.

López, J.; Maldonado, S. | Knowledge-based Systems 152. 83-93. | 2018

Twin Support Vector Regression is an effective machine learning strategy, which splits the predictive task into two small problems, gaining in both efficiency and predictive performance. In this paper, a novel extension for twin Support Vector Regression is presented. The proposal is based on robust optimization, conferring robustness to the predictive task by dealing effectively with uncertainty. The method is first developed as a linear one, and then, subsequently extended to a kernel-based formulation. Our approach accomplishes the best performance on benchmark datasets compared to alternative methods, such as linear regression, support vector regression, and twin support vector regression. This gain in performance demonstrates the virtues of robust optimization on reducing the risk of overfitting, and generalizing the training patterns well with reduced complexity. Keywords: Support vector regression; Twin support vector machines; Second-order cone programming; Robust optimization

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Reserve System to improve Logistics of Empty containers: case study of a container store in Peru.

Chong, M., González, R., Talavera, Á., Purisaga, E., Poquioma, A. | Revista Electrónica de Estrategia E Negocios- REEN, 11 (2), 222-245. (Emerging Citation Report). | 2018

La necesidad de optimizar el proceso operativo de un almacén para el despacho de contenedores de exportación motivó el presente estudio. El alcance tiene tres objetivos en el despacho de contenedores vacíos tipo reefer: primero, minimizar el tiempo de despacho que, actualmente, dura un promedio de tres horas, desde que el transporte del cliente ingresa al almacén, recibe el contenedor y se retira; segundo, mejorar en calidad el estado de entrega de los contenedores; y, tercero, lograr una reducción en los costos operativos del proceso de despacho. Palabras clave: Contenedores de exportación; Despacho de contenedores; Logística portuaria

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Redefining Support Vector Machines with the Ordered Weighted Average.

Maldonado, S.; Merigó, J.; Miranda, J. | Knowledge-based Systems 148,41-46. | 2018

In this work, the classical soft-margin Support Vector Machine (SVM) formulation is redefined with the inclusion of an Ordered Weighted Averaging (OWA) operator. In particular, the hinge loss function is rewritten as a weighted sum of the slack variables to guarantee adequate model fit. The proposed two-step approach trains a soft-margin SVM first to obtain the slack variables, which are then used to induce the order for the OWA operator in a second SVM training. Originally developed as a linear method, our proposal extends it to nonlinear classification thanks to the use of Kernel functions. Experimental results show that the proposed method achieved the best overall performance compared with standard SVM and other well-known data mining methods in terms of predictive performance. Keywords: OWA operators; OWA quantifiers; Support vector machines; Hinge loss

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Redefining nearest neighbor classification in high-dimensional settings.

López, J.; Maldonado, S. | Pattern Recognition Letters 110, 36-43. | 2018

In this work, a novel nearest neighbor approach is presented. The main idea is to redefine the distance metric in order to include only a subset of relevant variables, assuming that they are of equal importance for the classification model. Three different distance measures are redefined: the traditional squared Euclidean, the Manhattan, and the Chebyshev. These modifications are designed to improve classification performance in high-dimensional applications, in which the concept of distance becomes blurry, i.e., all training points become uniformly distant from each other. Additionally, the inclusion of noisy variables leads to a loss of predictive performance if the main patterns are contained in just a few variables, since they are equally weighted. Experimental results on low- and high-dimensional datasets demonstrate the importance of these modifications, leading to superior average performance in terms of Area Under the Curve (AUC) compared with the traditional k nearest neighbor approach.

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Optimizing a bi-objective production-distribution planning problem using a GRASP.

Casas, M.S.; Camacho,J.; González, R.; Marmolejo, J.; Velarde, J. | Complexity. (2018), Article ID 3418580, 13 pg. | 2018

This paper addresses a biobjective production-distribution planning problem. The problem is formulated as a mixed integer programming problem with two objectives. The objectives are to minimize the total costs and to balance the total workload of the supply chain, which consist of plants and depots, considering that it represents a company vertically integrated. In order to solve the model, we propose an adapted biobjective GRASP to obtain an approximation of the Pareto front. To evaluate the performance of the proposed algorithm, numerical experimentations are conducted over a set of instances used for similar problems. Results indicate that the proposed GRASP obtains a relatively small number of nondominated solutions for each tested instance in very short computational time. The approximated Pareto fronts are discontinuous and nonconvex. Moreover, the solutions clearly show the compromise between both objective functions.

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On the on-line maintenance scheduling problem

Shamsaei, F. ; Telha, C.; Van Vyve, M. | Optimization Letters, vol. 12, no 2, pp. 387-397 | 2018

A machine instantly serves requests but needs to undergo maintenance after serving a maximum of L requests. We want to maximize the number of requests served. In the on-line version, we prove that serving L requests before placing a maintenance is 0.5-competitive and is best possible for deterministic algorithms. We describe a 0.585-competitive randomized algorithm and show an upper bound of 2L/(3L−1). We also analyze the empirical performance of various on-line algorithms on specific arrival distributions. Keywords: Maintenance scheduling; Competitive analysis; Randomized algorithms

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Modeling and Analysis of the apples export supply chain business processes: experiences from Chile. “Best practices in manufacturing processes: Experiences from Latin America”.

López,M.; González, R.; Bearzotti,L; Canella,S. | Springer. Guest editors: Jorge Luis García, Mario Chong, Rosa G. González-Ramírez, Leonardo Riviera. | 2018

In this chapter, we present an analysis of the fresh apple export supply chain in Chile. Fresh fruits are one of the main exports in Chile, after the mining products. This supply chain is particularly complex due to its perishable nature and the fact that the fruit export season occurs during the summer period, overlapping with the arrival of cruises. For this reason, maritime ports present high levels of utilization and congestion. We follow the Business Process Analysis (BPA) methodology proposed by United Nations to model the current situation of the shipment business processes, from the warehouse or packing facility of the shipper to the port of departure where it will be loaded to the corresponding vessel. With this analysis, we identify the main challenges and opportunities and propose a redesign of the current processes. The proposed redesigned business processes consider the implementation of electronic data interchange procedures instead of the paper-based ones currently employed.

Keywords: Business process management; Trade facilitation; Supply chain management

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Mining EEG with SVM for understanding cognitive underpinnings of math problem solving strategies.

Bosch, P.; Herrera, M.; López, J.; Maldonado, S. | Behavioural Neurology 2018. Article ID 4638903. 15 pages. | 2018

We have developed a new methodology for examining and extracting patterns from brain electric activity by using data mining and machine learning techniques. Data was collected from experiments focused on the study of cognitive processes that might evoke different specific strategies in the resolution of math problems. A binary classification problem was constructed using correlations and phase synchronization between different electroencephalographic channels as characteristics and, as labels or classes, the math performances of individuals participating in specially designed experiments. The proposed methodology is based on using well-established procedures of feature selection, which were used to determine a suitable brain functional network size related to math problem solving strategies and also to discover the most relevant links in this network without including noisy connections or excluding significant connections.

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Ellipsoidal Support Vector Regression based on Second-order Cone Programming.

Maldonado, S.; López, J. | Neurocomputing 305, 59-69. | 2018

In this paper, we propose a novel method for Support Vector Regression (SVR) based on second-order cones. The proposed approach defines a robust worst-case framework for the conditional densities of the input data. Linear and kernel-based second-order cone programming formulations for SVR are proposed, while the duality theory allows us to derive interesting geometrical properties for this strategy: the method maximizes the margin between two ellipsoids obtained by shifting the response variable up and down by a fixed parameter. Experiments for regression on twelve well-known datasets confirm the superior performance of our proposal compared to alternative methods such as standard SVR and linear regression. Keywords: Support vector regression; Robust optimization; Second-order cone programming; Kernel methods

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Double regularization methods for robust features election and SVM classification via DC programming

López, J.; Maldonado, S.; Carrasco, M. | Information Sciences. | 2018

In this work, two novel formulations for embedded feature selection are presented. A second-order cone programming approach for Support Vector Machines is extended by

adding a second regularizer to encourage feature elimination. The one- and the zeronorm penalties are used in combination with the Tikhonov regularization under a robust setting designed to correctly classify instances, up to a predefined error rate, even for the worst data distribution. The use of the zero norm leads to a nonconvex formulation, which is solved by using Difference of Convex (DC) functions, extending DC programming to second-order cones. Experiments on high-dimensional microarray datasets were performed, and the best performance was obtained with our approaches compared with well-known feature selection methods for Support Vector Machines. Keywords: Zero norm; Support vector machines; Second-order cone programming; Dc algorithm

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Decision support for fleet allocation and contract renegotiation in contracted open-pit mine blasting operations.

Pérez, J.; Maldonado, S.; González, R. | International Journal of Production Economics 204. 59-69. | 2018

In the current copper mining scenario, where prices are decreasing and pits are larger, there is a pressing need for increasing operational productivity. This is particularly important for mining contractors, who are constantly facing the additional pressure of obsolescence if they are not able to provide cost-savings for mine owners. In this paper, we deal with operational efficiency for blasting operations in open-pit mine sites, and propose a framework for minimizing truck allocation costs with hazardous materials based on mathematical programming. Apart from reducing operational costs, the proposed research allows contractors to re-negotiate contracts with mine owners. An integrated model for blasting operation is proposed, taking into account multiple owners with various open pits, each one of them having multiple blasting grids. The main methodological contribution is the inclusion of specially tailored constraints for modelling the blending requirements for the on-delivery production of the explosives, an important aspect given the hazardous nature of the chemical compounds that are transported. The proposed framework was implemented by a Chilean contractor, leading to savings up to 15% of the total operational costs and allowing better tactical decisions, as contract renegotiation or fleet design. Keywords: Fleet allocation; Open-pit mining; Hazardous material; Explosives transportation

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Dealing with high-dimensional class-imbalanced datasets: embedded feature selection for SVM classification.

Maldonado, S.; López, J. | Applied Soft Computing 67, 94-105. | 2018

In this work, we propose a novel feature selection approach designed to deal with two major issues in machine learning, namely class-imbalance and high dimensionality. The proposed embedded strategy penalizes the cardinality of the feature set via the scaling factors technique, and is used with two support vector machine (SVM) formulations designed to deal with the class-imbalanced problem, namely Cost Sensitive SVM, and Support Vector Data Description. The proposed concave formulations are solved via a Quasi-Newton update and Armijo line search. We performed experiments on 12 highly imbalanced microarray datasets using linear and Gaussian kernel, achieving the highest average predictive performance with our approach compared with the most well-known feature selection strategies. Keywords: Feature selection; Support Vector Data Description; Cost-sensitive learning; Embedded approaches; Imbalanced data classification

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Competitive uncapacitated lot-sizing game.

Carvalho, M.; Pedroso, J.P.; Telha, C. Van Vyve, M. | International Journal of Production Economics, vol. 204, pp. 148-159. | 2018

We study the strategical behaviour of firms facing a lot-sizing problem with Cournot competition. Each player is a firm with her own production facility, modeled as an uncapacitated lot-sizing problem (i.e., production incurs set-up and variable costs and inventories are allowed). A Cournot competition is played in each time period (market) with each player deciding the quantity of product to place on it. The market price of that product in each time period depends on the total quantity placed in the market.

We show that this is a potential game with possibly multiple pure Nash equilibria. We then investigate the plausibility of these equilibria to predict the game outcome by evaluating the difficulty of computing them. If the game has a single period, we prove that an equilibrium can be found in polynomial time, but it is weakly NP-hard to find an optimal pure Nash equilibrium (with respect to a given equilibrium refinement). If the game has no variable production and inventory costs, we prove that a pure Nash equilibrium can be computed in polynomial time. Keywords: Cournot competition; Lot-sizing problem; Nash equilibria; Potential game

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A Novel Storage Space Allocation Policy for Import Containers

Gaete, M.; González M.; González, R. ; Astudillo, C. | Operations Research and Enterprise Systems (pp. 293-316). CCIS, Volume 884. Springer. | 2018

In developing countries, such as those in Latin America, inland flows of container terminals present high levels of uncertainty and variability. This situation occurs mainly due to lack of automation procedures, affecting coordination with the hinterlands. In this article, a methodology based on a dwell time segregated container storage policy is proposed. This methodology considers only import containers, due to the difficulty to determine a segregation criterion, which motivated us to use container dwell time information. Dwell times are discretized to determine classes, so that containers of the same class are assigned to close locations at the yard. The architecture of a decision support system to aid the stacking decisions based on this storage policy is proposed. The port of Arica in Chile is considered as a case study, and a discrete-event simulation model is also proposed to estimate potential benefits of this approach. Numerical results for the case study show a good performance, with potential reduction of the rehandles incurred when containers are retrieved from the yard.

Keywords: Container storage policies; Dwell times of containers; Segregation of containers; Classification algorithms

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A discrete bilevel brain storm algorithm for solving a sales territory design problem -a case study

Nucamendi, S.; Davila, D.; Camacho-Vallejo, F.; González-Ramírez R. | Memetic Computing. Volume 10, Issue 4, pp 441-458. https://doi.org/10.1007/s12293-018-0266-5. | 2018

A sales territory design problem faced by a manufacturing company that supplies products to a group of customers located in a service region is addressed in this paper. The planning process of designing the territories has the objective to minimizing the total dispersion of the customers without exceeding a limited budget assigned to each territory. Once territories have been determined, a salesperson has to define the day-by-day routes to satisfy the demand of customers. Currently, the company has established a service level policy that aims to minimize total waiting times during the distribution process. Also, each territory is served by a single salesperson. A novel discrete bilevel optimization model for the sales territory design problem is proposed. This problem can be seen as a bilevel problem with a single leader and multiple independent followers, in which the leader’s problem corresponds to the design of territories (manager of the company), and the routing decision for each territory corresponds to each follower. The hierarchical nature of the current company’s decision-making process triggers some particular characteristics of the bilevel model. A brain storm algorithm that exploits these characteristics is proposed to solve the discrete bilevel problem. The main features of the proposed algorithm are that the workload is used to verify the feasibility and to cluster the leader’s solutions. In addition, four discrete mechanisms are used to generate new solutions, and an elite set of solutions is considered to reduce computational cost. This algorithm is used to solve a real case study, and the results are compared against the current solution given by the company. Results show a reduction of more than 20% in the current costs with the solution obtained by the proposed algorithm. Furthermore, a sensitivity analysis is performed, providing interesting managerial insights to improve the current operations of the company. Keywords: Brain storm algorithm; Bilevel optimization; Sales territory design; Latency

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A heuristic procedure for the outbound container space assignment problem for small and midsize maritime terminals

Guerra, R.; Smith, N.R.; González, R.G.; Cardenas, L. | International Journal of Machine Learning and Cybernetics, 9(10), 1719-1732. | 2018

The space allocation problem for outbound containers involves assigning containers to specific locations in the yard as they are delivered to the port. The problem is challenging because the arrival sequence is not known in advance, which makes it difficult to minimize container rehandling during the ship loading operation. This paper provides a heuristic procedure for the container space allocation problem employing reach stacker vehicles as container handling equipment. Procedures reported in the existing literature apply to rubber-tired gantry (RTG) cranes. Therefore, we are extending current research to the cases of port terminals that employ reach stacker vehicles, commonly used by small or medium size ports in emerging countries such as in Latin America. In addition, we adapted a procedure recently published in the literature. Empirical results show that the proposed heuristic yields better performance than the adapted heuristic. Another contribution of this paper is the formulation of a perfect information mathematical model which computes a lower bound on the number of rehandles required to load a group of containers given their arrival sequence to the port. The gap between the number of rehandle movements achieved by the proposed heuristic and the perfect information model is reported. Keywords: Container space allocation problem; Reach stacker vehicle; Maritime terminal; Rehandle movements

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SAW-Q: A dynamic composition approach of REST services based on queue

Jesús Bellido, Rosa Alarcón, Cesare Pautasso and Carla Vairetti

IEEE Transactions on Services Computing, 2018

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The impact of lanes segmentation and booking levels on container terminal gate congestion.

Gracia, M.D., González-Ramírez R.G., Mar-Ortiz, J. | Flexible Services and Manufacturing, 29 (3-4), 403-432. | 2017

Recent trends in port performance improvement include the coordination of intermodal transport logistics to reduce congestion and inefficiencies generated at the gates of the terminals. Congestion at the gate of a terminal generates several problems such as pollution and long waiting times for truck carriers. As part of the strategies and best practices to reduce congestion, some ports worldwide have implemented advanced booking systems in order to coordinate truck arrivals and deliveries at the gate of their container terminals. We will refer to these systems as truck appointment systems. In general terms, a truck appointment system provides a mechanism where truck carriers coordinate their time of arrival at the container terminal based on an advanced booking. In this way, gate managers are able to better plan their port operations and equipment allocation, to reduce the waiting times of trucks and improve the turnaround time for container deliveries. In order to account for the real benefits of such systems, the particular conditions of each container terminal need to be considered. In this paper, a case study of a Chilean port terminal is analyzed. The aim is to provide recommendations that may reduce congestion and improve the container terminal´s gate control of truck arrivals, turnaround times and container deliveries by means of efficient lane segmentation policies. Several scenarios were examined under which different booking levels are considered for an environment in which the arrival of containers can vary significantly from day to day and on a seasonal basis. As a basis for our study a fractional factorial design is performed in order to analyze the impact of controllable factors on two service levels measures, which reduce the number of scenarios needed to obtain robust conclusions. Keywords: Intermodal coordination; Truck appointment system; Simulation analysis; Ports optimization; Port terminal congestion

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Synchronized feature selection for Support Vector Machines with twin hyperplanes.

Maldonado, S.; López, J. | Knowledge-based Systems 132C, 119-128. | 2017

In this work, a novel feature selection method for twin Support Vector Machine (SVM) is presented. The main idea is to combine two regularizers, namely the Euclidean and infinite norm to perform twin classification and variable selection simultaneously. This latter task is performed in a coordinated fashion, enabling that the same attributes are selected in each twin classifiers. A single optimization problem is used to solve both subproblems, leading to a sparse final classification rule. Experiments on low- and high-dimensional datasets indicate that our approaches present the best average performance compared to well-known feature selection strategies, also achieving a synchronized feature elimination in the two twin classifiers. Our approaches are also able to improve the performance of the twin classifier, demonstrating the importance of feature selection in high-dimensional tasks. Keywords: Support vector machine; Embedded methods; Feature selection; L-infinity norm

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Simultaneous Preference Estimation and Heterogeneity Control for Choice-based Conjoint via Support Vector Machines.

López, J.; Maldonado, S.; Montoya, R. | Journal of the Operational Research Society 68(11), 1323-1334. | 2017

Support vector machines (SVMs) have been successfully used to identify individuals’ preferences in conjoint analysis. One of the challenges of using SVMs in this context is to properly control for preference heterogeneity among individuals to construct robust partworths. In this work, we present a new technique that obtains all individual utility functions simultaneously in a single optimization problem based on three objectives: complexity reduction, model fit, and heterogeneity control. While complexity reduction and model fit are dealt using SVMs, heterogeneity is controlled by shrinking the individual-level partworths toward a population mean. The proposed approach is further extended to kernel-based machines, conferring flexibility to the model by allowing nonlinear utility functions. Experiments on simulated and real-world datasets show that the proposed approach in its linear form outperforms existing methods for choice-based conjoint analysis.

Keywords: conjoint analysis; heterogeneity control; support vector machines; OR in marketing; artificial intelligence

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Robust Kernel-based Multiclass Support Vector Machines via Second-Order Cone Programming.

Maldonado, S.; López, J. | Applied Intelligence 46(4). 983-992. | 2017

Kernel methods are very important in pattern analysis due to their ability to capture nonlinear relationships in datasets. The best known kernel-based technique is Support Vector Machine (SVM), which can be used for several pattern recognition tasks, including multiclass classification. In this paper, we focus on maximum margin classifiers for nonlinear multiclass learning, based on second-order cone programming (SOCP), proposing three novel formulations that extend the most common strategies for this task: One-vs.-The-Rest, One-vs.-One, and All-Together optimization. The proposed SOCP formulations achieved superior performance compared to their traditional SVM counterparts on benchmark datasets, demonstrating the virtues of robust optimization. Keywords: Multiclass classification; Second-order cone programming; Kernel methods; Support vector machines

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Review of fuzzy techniques in maritime shipping operations.

Ries, J., González-Ramírez, R.G., Voss, S. | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10572 LNAI, pp. 253-269. | 2017

Fuzzy Logic has found significant interest in the context of global shipping networks due to its applicability to uncertain decision making environments. Its use has been particularly important when solving location and equipment selection problems. While being applicable as a stand-alone technique, Fuzzy Logic has become increasingly interesting as an added feature within classic Operational Research techniques. This paper gives an outline of the methodological relevance of Fuzzy Logic at a strategic, tactical and operational level for maritime operations. In addition, a general classification of decision problems in maritime logistics is presented, extending previous classifications in the literature to the wider context of multiple port networks.

Keywords: Fuzzy Logic; Hybrid techniques; Maritime shipping; Container terminals

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Reducing Port-Related Empty Trip Truck Emissions: A Mathematical Approach for Truck Appointments with Collaboration.

Schulte, F.; Lalla-Ruíz, E.; González-Ramírez, R.G.; Voβ, S. | Transport Research Part E, 105, 195-212. | 2017

Port-related emissions are a growing problem for urban areas often located directly next to maritime container terminals highly frequented by container trucks. Empty truck trips, caused by a lack of coordination among truckers, are responsible for a significant share of these emissions, and collaboration among truckers is seen as the major opportunity to address this issue. Truck appointment systems (TASs) schedule truck activities and enable collaboration for transportation between terminals and client locations. The aim of this work is to introduce a collaborative planning model to be operated within a TAS and to investigate its impact on emission and cost objectives. Starting with a review of requirements for a TAS with collaboration, an optimization model based on the multiple traveling salesman problem with time windows is developed, leveraging collaboration to reduce costs and emissions. The results for a real-world case demonstrate that the developed approach provides appropriately coordinated truck schedules and effectively reduces truck emissions and costs.

Keywords: Port emissions; Truck appointment system; Collaboration; Empty trips; Optimization model

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Integrated framework for profit-based feature selection and SVM classification in credit scoring.

Maldonado, S.; Bravo, C.; Pérez, J.; López, J. | Decision Support Systems 104, 113-121. | 2017

In this paper, we propose a profit-driven approach for classifier construction and simultaneous variable selection based on linear Support Vector Machines. The main goal is to incorporate business-related information such as the variable acquisition costs, the Types I and II error costs, and the profit generated by correctly classified instances, into the modeling process. Our proposal incorporates a group penalty function in the SVM formulation in order to penalize the variables simultaneously that belong to the same group, assuming that companies often acquire groups of related variables for a given cost rather than acquiring them individually. The proposed framework was studied in a credit scoring problem for a Chilean bank, and led to superior performance with respect to business-related goals. Keywords: Profit measure; Group penalty; Credit scoring; Support Vector Machines; Analytics

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Impact on Yard Efficiency of a Truck Appointment System for a Port Terminal.

Nafarrete-Ramírez, A., Guerra-Olivares, R., Smith, N.R., González-Ramírez, R.G, Voβ, S | Annals of Operations Research. | 2017

Port terminals consist of two interfaces for transferring cargo among transport modes: (1) the seaside or quayside interface and (2) the landside interface. At the seaside interface, cargo is loaded and unloaded from the vessels and stored temporarily at the yard. Landside operations consist of receiving and dispatching cargo from external trucks and rail. The increasing volumes of international trade are demanding more efficient cargo handling throughout the port logistic chain and coordination with the hinterland, hence attracting more attention from both practitioners and researchers on the landside interface of ports. Due to the high variability of truck arrivals with a significant concentration at peak hours, congestion at the access gates of ports and an unbalanced utilization of the resources occur. Truck appointment systems (TAS) have already been implemented in some ports as a coordination mechanism to reduce congestion at ports, balance demand and capacity, and reduce truck turnaround times. Based on the current situation faced by the Port of Arica, Chile, this paper aims to analyze potential configurations of a TAS and evaluate its impacts on yard operations, specifically in the reduction of container rehandles, as well as truck turnaround times. For this, a discrete-event simulation model and a heuristic procedure are proposed and experimentation is performed using historical data from the port terminal. Results indicate that implementing a TAS may significantly benefit yard operations in terms of reducing container rehandles as well as truck waiting times. Keywords: Port terminal operations; Truck appointment system; Discrete-event simulation; Landside coordination

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Group-Penalized Feature Selection and Robust Twin SVM Classification via Second-order Cone Programming.

López, J.; Maldonado, S. | Neurocomputing 235. 112-121. | 2017

Selecting the relevant factors in a particular domain is of utmost interest in the machine learning community. This paper concerns the feature selection process for twin support vector machine (TWSVM), a powerful classification method that constructs two nonparallel hyperplanes in order to define a classification rule. Besides the Euclidean norm, our proposal includes a second regularizer that aims at eliminating variables in both twin hyperplanes in a synchronized fashion. The baseline classifier is a twin SVM implementation based on second-order cone programming, which confers robustness to the approach and leads to potentially better predictive performance compared to the standard TWSVM formulation. The proposal is studied empirically and compared with well-known feature selection methods using microarray datasets, on which it succeeds at finding low-dimensional solutions with highest average performance among all the other methods studied in this work. Keywords: Support vector machines; Feature selection; Twin SVM; Second-order cone programming; Group penalty

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Empty container stacking operations: case study of an empty container depot in Valparaiso Chile.

Pascual J., Aranda, D., Hidalgo, F., Smith, A., Karakaya, E., González-Ramírez, R.G. | Proceedings- Winter Simulation Conference, 7822419, pp. 3724-3725. | 2017

This study analyzes the handling operations performance at an Empty Container Depot that serves different shipping lines operating with the port of Valparaíso, Chile. With the aid of a discrete event simulation model built in Simio that interacts with an SQL Server database, we seek to improve container stacking policies and to redesign the depot’s layout such that truck turn-around times decrease.

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Embedded Heterogeneous Feature Selection for Conjoint Analysis: a SVM approach using L1 penalty.

Maldonado, S.; Montoya, R.; López, J. | Applied Intelligence 46(4).775-787. | 2017

This paper presents a novel embedded feature selection approach for Support Vector Machines (SVM) in a choice-based conjoint context. We extend the L1-SVM formulation and adapt the RFE-SVM algorithm to conjoint analysis to encourage sparsity in consumer preferences. This sparsity can be attributed to consumers being selective about the attributes they consider when evaluating alternatives in choice tasks. Given limited individual data in choice-based conjoint, we control for heterogeneity by pooling information across consumers and shrinking the individual weights of the relevant attributes towards a population mean. We tested our approach through an extensive simulation study that shows that the proposed approach can capture the sparseness implied by irrelevant attributes. We also illustrate the characteristics and use of our approach on two real-world choice-based conjoint data sets. The results show that the proposed method has better predictive accuracy than competitive approaches, and that it provides additional information at an individual level. Implications for product design decisions are discussed. Keywords: Feature selection; Support vector machines; Conjoint analysis; L1 norm

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Dynamic Rough-Fuzzy Support Vector Clustering.

Saltos, R.; Maldonado, S.; Weber, R. | IEEE Transactions on Fuzzy Systems. 25(6) 1508-1521.9. | 2017

Clustering is one of the main data mining tasks with many proven techniques and successful real-world applications. However, in changing environments, the existing systems need to be regularly updated in order to describe in the best possible way an observed phenomenon at each point in time. Since changes lead to uncertainty, the respective systems also require an adequate modeling of the involved kinds of uncertainty. This paper presents a novel method for dynamic clustering called dynamic rough-fuzzy support vector clustering (D-RFSVC). Its main idea is to take advantage of the knowledge acquired in previous cycles to speed up model updating while tracking the structural changes that clusters can experience over time. The core method of the proposed approach is the well-known support vector clustering algorithm, which can be used for large datasets employing powerful optimization techniques. The computational experiments, together with a conceptual and numerical comparative study, highlight the potential D-RFSVC has in dynamic environments.

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Cost-based feature selection for Support Vector Machines – An application in credit scoring.

Maldonado, S.; Pérez, J.; Bravo, C. | European Journal of Operational Research 261 (2), 656-665. | 2017

In this work we propose two formulations based on Support Vector Machines for simultaneous classification and feature selection that explicitly incorporate attribute acquisition costs. This is a challenging task for two main reasons: the estimation of the acquisition costs is not straightforward and may depend on multivariate factors, and the inter-dependence between variables must be taken into account for the modelling process since companies usually acquire groups of related variables rather than acquiring them individually. Mixed-integer linear programming models are proposed for constructing classifiers that constrain acquisition costs while classifying adequately. Experimental results using credit scoring datasets demonstrate the effectiveness of our methods in terms of predictive performance at a low cost compared to well-known feature selection approaches.

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Benefits of Mobile End User Network Switching and Multihoming.

Finley, B.; Basaure, A. | Computer Communications. 117: 24-35. | 2017

Mobile users have not been able to exploit spatio-temporal differences between individual mobile networks operators for a variety of reasons. End user network switching and multihoming are two promising mechanisms that could allow such exploitation. However these mechanisms have not been thoroughly explored at a general system level with QoE metrics. Therefore, in this work we analyze these mechanisms in a variety of diverse scenarios through a system level model based on an agent based modeling framework.

In terms of results, we find that in all scenarios end user network switching provides significant benefits in terms of both throughput and mean opinion score as the number of available networks increases. However, contrastingly, end user multihoming in most scenarios does not provide significant benefits over network switching given the same number of available networks. The major reason is inefficient radio resource allocation resulting from individual networks not taking the multihoming nature of end users into account. Though, in low user density situations this inefficiency is not a problem and multihoming does provide increased throughput though not increased mean opinion scores. Finally, scenarios that vary the fraction of users adopting multihoming suggests that both early and late adopters will have similar gains over users not adopting multihoming. Thus the adoption dynamics of multihoming appear favorable. Overall, the results support the applicability of end user network switching for improving mobile user experience and the applicability of end user multihoming in more limited situations.

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Assessing University Enrollment and Admission Efforts via Hierarchical Classification and Feature Selection.

Maldonado, S.; Armelini, G.; Guevara, C.A. | Intelligent Data Analysis 21(4) 945-962. | 2017

Recruiting prospective students efficiently and effectively is a very important challenge for universities, mainly because of the increasing competition and the relevance of enrollment-generated revenues. This work provides an intelligent system for modeling the student enrollment decisions problem. A nested logit classifier was constructed to predict which prospective students will eventually enroll in different Bachelor degree programs of a small-sized, private Chilean university. Feature selection is performed to identify the key features that influence the student decisions, such as socio-demographic variables (gender, age, school type, among others), admission efforts, and admission test results. Our results suggest that on-campus activities are far more productive than career fairs and other efforts performed off campus, demonstrating the importance of bringing prospective students to the university. Furthermore, variables such as gender, school type, and declared university and Bachelor degree program preferences are shown to be relevant in successfully modeling the student’s choice of university.

Keywords: Hierarchical classification, university enrollment, feature selection, analytics, nested logit

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A robust formulation for twin multiclass support vector machine.

López, J.; Maldonado, S.; Carrasco, M. | Applied Intelligence 47(4), 1031-1043. | 2017

Multiclass classification is an important task in pattern analysis since numerous algorithms have been devised to predict nominal variables with multiple levels accurately. In this paper, a novel support vector machine method for twin multiclass classification is presented. The main contribution is the use of second-order cone programming as a robust setting for twin multiclass classification, in which the training patterns are represented by ellipsoids instead of reduced convex hulls. A linear formulation is derived first, while the kernel-based method is also constructed for nonlinear classification. Experiments on benchmark multiclass datasets demonstrate the virtues in terms of predictive performance of our approach. Keywords: Support vector classification; Multiclass classification; Twin support vector machines; Second-order cone programming

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A GRASP-Tabu heuristic approach to territory design for pickup and delivery operations for large scale instances.

González, R.; Smith, N.; Askin, R., Camacho, J;, J González, J. | Mathematical Problems in Engineering. (2017), ID 4708135, 13 pages. | 2017

We address a logistics districting problem faced by a parcel company whose operations consist of picking up and delivering packages over a service region. The districting process aims to find a partition of the service region into delivery and collection zones that may be served by a single vehicle that departs from a central depot. Criteria to be optimized are to balance workload content among the districts and to create districts of compact shape. A solution approach based on a hybrid procedure that combines elements of GRASP and Tabu Search (TS) is proposed to solve large-scale instances. Numerical experimentation is performed considering different instance sizes and types. Results show that the proposed solution approach is able to solve large-scale instances in reasonable computational times with good quality of the solutions obtained. To determine the quality of the solutions, results are compared with CPLEX solutions and with the current real solution to highlight the benefits of the proposed approach. Conclusions and recommendations for further research are provided.

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Robust Kernel-based Multiclass Support Vector Machines via Second-Order Cone Programming.

Maldonado, S., López, J. | Applied Intelligence 46 (4) 983-992 | 2017


Group-Penalized Feature Selection and Robust Twin SVM Classification via Second-order Cone Programming

López, J., Maldonado, S. | Neurocomputing 235. 112-121. | 2017


Embedded Heterogeneous Feature Selection for Conjoint Analysis: a SVM approach using L1 penalty

Maldonado, S., Montoya, R., López, J. | Applied Intelligence 46(4). 775-787 | 2017


Assessing University Enrollment and Admission Efforts via Hierarchical Classification and Feature Selection

Maldonado, S., Armelini, G., Guevara, C.A. | Intelligent Data Analysis 21(4). 945-962. | 2017


Simultaneous Preference Estimation and Heterogeneity Control for Choice-based Conjoint via Support Vector Machines

López, J., Maldonado, S., Montoya, R. | Journal of the Operational Research Society 68(11). 1323-1334. | 2017


Impact on Yard Efficiency of a Truck Appointment System for a Port Terminal

Nafarrete-Ramírez, A., Guerra-Olivares, R., Smith, N.R., González-Ramírez, R.G, Voβ, S. | Annals of Operations Research, 258(2), 196-216 | 2017


Cost-based feature selection for Support Vector Machines – An application in credit scoring

Maldonado, S., Pérez, J., Bravo, C. | European Journal of Operational Research 261 (2), 656–665. | 2017


A robust formulation for twin multiclass support vector machine

López, J., Maldonado, S., Carrasco, M. | Applied Intelligence 47(4), 1031-1043. | 2017


Synchronized feature selection for Support Vector Machines with twin hyperplanes

Maldonado, S., López, J. | Knowledge-based Systems 132C, 119-128. | 2017


Integrated framework for profit-based feature selection and SVM classification in credit scoring

Maldonado, S., Bravo, C., Pérez, J., López, J. | Decision Support Systems 104, 113-121. | 2017


Dynamic Rough-Fuzzy Support Vector Clustering.

Saltos, R., Maldonado, S., Weber, R. | IEEE Transactions on Fuzzy Systems 25(6) 1508-1521. | 2017


A GRASP-Tabu heuristic approach to territory design for pickup and delivery operations for large scale instances

Ramírez, R.G. Neale R. Smith, Ronald G. Askin, José-Fernando Camacho-Vallejod, Jose Luis González-Velarde. | ”. Mathematicals Problems in Engineering. Volume 2017 (2017), Article ID 4708135, 13 pages. | 2017


Reducing Port-Related Empty Trip Truck Emissions: A Mathematical Approach for Truck Appointments with Collaboration

Schulte, F., Lalla-Ruíz, E., González-Ramírez, R.G., Voβ, S. | Transport Research Part E, 105, 195-212. | 2017


Integrated framework for profit-based feature selection and SVM classification in credit scoring

S. Maldonado, C. Bravo, J. López, J. Pérez | Decision Support Systems, Vol. 104, pp. 113-121. | 2017


Cost-base feature selection for Support Vector Machines: An application in credit scoring

S. Maldonado, J. Pérez, C. Bravo | European Journal of Operational Research, Vol. 261, Issue2, pp. 656-665 | 2017


Transaction vs. switching costs-Comparison of three core mechanisms for mobile markets.

Basaure; SuomI; Hämmäinen. | Telecommunications Policy. 40(6), 545-566. | 2016

The fast growth in demand of mobile Internet urges mobile network operators (MNOs) to rapidly increase the wireless network capacity. For this purpose, governments are allocating large parts of the valuable low frequency spectrum to MNOs. This expansion also adds pressure to better optimize the intra-MNO and inter-MNO spectrum usage. Regulators are concerned about problems such as network blackouts, coverage disparities and congestion. Latest technology developments provide new mechanisms to address these problems through two alternative evolution paths, operator-driven and user-driven. The operator-driven path permits operators to trade network capacity and spectrum through, for instance, national roaming and dynamic spectrum access mechanisms, respectively. On the other hand, the user-driven path enables users (and traffic) to rapidly switch between networks through an end-user multihoming mechanism which intensifies retail competition. MNOs are reluctant to adopt these mechanisms if they involve risks. However, regulators can facilitate the deployment of these mechanisms by guiding the level of inter-MNO transaction costs and end-user switching costs. This paper analyzes the market dynamics of these three core mechanisms by employing agent-based modeling. Initial results indicate that each mechanism improves allocative efficiency on a dynamic basis and that such mechanisms become necessary if the current static market model based on vertically integrated MNOs is not able to meet the requirements of service quality, capacity and coverage. One promising use case of the proposed mechanisms is the indoor femto-cellular deployment which suffers from coverage disparity due to static single-MNO base stations. Moreover, either end-user multihoming or national roaming may provide MNOs a feasible business case for building indoor infrastructure by solving coverage disparity problems, by means of competition or cooperation, respectively. Dynamic spectrum access may work as an extension of the previous mechanisms for solving congestion; however, it requires higher technical and business coordination.

Keywords: Inter-MNO transaction costs; End-user switching costs; Dynamic spectrum access; National roaming; End-user multihoming; Cooperation; Competition; Wholesale and retail trading

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Tramp ship scheduling problem with berth allocation considerations and time-dependent constraints.

López-Ramos, F., Guarnaschelli, A., Camacho-Vallejo, J.F., Hervert-Escobar, L., González-Ramírez, R.G. | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10061 LNAI, pp. 346-361. | 2016

This work presents a model for the Tramp Ship Scheduling problem including berth allocation considerations, motivated by a real case of a shipping company. The aim is to determine the travel schedule for each vessel considering multiple docking and multiple time windows at the berths. This work is innovative due to the consideration of both spatial and temporal attributes during the scheduling process. The resulting model is formulated as a mixed-integer linear programming problem, and a heuristic method to deal with multiple vessel schedules is also presented. Numerical experimentation is performed to highlight the benefits of the proposed approach and the applicability of the heuristic. Conclusions and recommendations for further research are provided.

Keywords: Tramp ship scheduling; Berth allocation; Multiple docking; Time-dependent constraints

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Supply Chains under Security Threat: The First National Exploratory Study in Mexico.

Cedillo-Campos, M.G., Bueno-Solano, A., González-Ramírez, R. G., Jiménez-Sánchez, E. Pérez-Salas, G. | Handbook of Research on Military, Aeronautical, and Maritime Logistics and Operations. Alberto Ochoa-Zezzatti, Jöns Sánchez, Miguel Gastón Cedillo-Campos and Margain de Lourdes (Eds.). IGI Global. | 2016

Contemporary prosperity depends on effective and secure supply chain networks that support economic competitiveness. Disruptions in global supply chains would have critical consequences on economies. The lack of technical studies and quantitative data concerning security that affects supply chain operations in Latin America, motivated to develop an exploratory study. Considering the complexity of the question studied, this paper details a set of case studies that explore, from a qualitative research approach, to what extent fulfilling security international standards now necessary to access mature markets such as the U.S and Canada allows export companies located in emerging countries as Mexico to face effectively the different types and levels of local risk. These results should help both academics and practitioners to more readily understand, first, the key logistics components now taken into account when improving security in export-oriented supply chains is required, and second, decision-makers’ perspectives regarding supply chain security standards (SCSS) available on the market. A discussion of results is exposed and finally, discussion and future research are presented.

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Special issue: Supply chain network design in emerging markets- Editorial.

González-Ramírez, R.G., Litvinchev, I. | Netnomics, 17(1), pp. 1-2. | 2016

No Abstract Avialable

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Pricing and composition of bundles with constrained multinomial logit.

Pérez, J.; López-Ospina, H.; Cataldo,A.; Ferrer, J. | Int. Journal of Production Research. 54(13). 3994-4007. | 2016

In this paper, we propose an extension of the problem of bundling with multinomial logit, making an explicit inclusion of the consumers’ maximum willingness to pay (MWTP) by means of the constrained multinomial logit (CMNL). In the bundling problem, we determine the price and the composition of bundles offered for a single segment of consumers by a firm, which is competing with others in the market, and we compare this result to a base case in which the consumers’ MWTP is not considered. We assume these consumers as rational since they choose the bundle that maximise their utility and the bundle price is within their MWTP. The resulting model is a non-linear mixed integer programme which is solved in two steps: (i) pricing is the first step; the prices are numerically determined in a fixed point equations system and (ii) in the second step the composition of the bundle is determined by explicit enumeration. The results show that the price obtained is less than the one got in the case without CMNL (and bigger than the costs), and the composition of the offered bundle is different as well. It is possible to conclude that not considering the consumers’ MWTP in the context of the problem of bundling will imply an overestimation of the firm’s profit. We have analysed as well the results for a Chilean telecommunications company. These results show the importance of including the MWTP in the pricing and composition process.

Keywords: pricing; constrained multinomial logit; bundle composition; consumer choice models

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Multi-class Second-Order Cone Programming Support Vector Machines.

López, J.; Maldonado, S. | Information Sciences, 328-341. | 2016

This paper presents novel second-order cone programming (SOCP) formulations that determine a linear multi-class predictor using support vector machines (SVMs). We first extend the ideas of OvO (One-versus-One) and OvA (One-versus-All) SVM formulations to SOCP-SVM, providing two interesting alternatives to the standard SVM formulations. Additionally, we propose a novel approach (MC-SOCP) that simultaneously constructs all required hyperplanes for multi-class classification, based on the multi-class SVM formulation (MC-SVM). The use of conic constraints for each pair of training patterns in a single optimization problem provides an adequate framework for a balanced and effective prediction.

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Improving Logistics Operations at Container Terminals by Simulation Optimization Approaches

Mar-Ortiz, J., Gracia, M.D., González-Ramírez, R.G. | Handbook of Research on Managerial Strategies for Achieving Optimal Performance in Industrial Processes” Edited by: Giner Alor Hernández, Cuauhtémoc Sánchez-Ramírez and Jorge Luis García-Alcaraz. IGI Global. | 2016

Container terminals as strategic nodes in global supply chains require improving logistics operations in order to compete. This chapter addresses the problem of how to improve logistics operations to increase the container terminal’s throughput and capacity by lean logistics principles and simulation optimization methods. Current research in container terminals is focused on solving specific decision problems at container terminals, e.g., determining the optimal number of equipment to increase productivity. However, there is little evidence of studies related to designing operations to increase performance indicators, such as truck turnaround times or crane productivity, through simulation-optimization models and lean logistics principles. Consequently, the aim of this chapter is to describe a methodological framework for improving logistics operations at container terminals using lean logistics principles and simulation-optimization techniques. A research agenda to explore the applicability and usefulness of the proposed approach on a set of integrated problems is finally proposed.

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Efficient approximation algorithms for the Economic Lot-Sizing in continuous time.

Telha C.;Van Vyve M. | Discrete Optimization, vol. 20, pp. 23-39. | 2016

We consider a continuous-time variant of the classical Economic Lot-Sizing (ELS) problem. In this variant, the setup cost is a continuous function with lower bound Kmin > 0, the demand and holding costs are integrable functions of time and arbitrary replenishment policies are allowed. Starting from the assumption that certain operations involving the setup and holding cost functions can be carried out efficiently, we show that this variant admits a simple approximation scheme based on dynamic programming: if the optimal cost of an instance is OPT, we can find a solution with cost at most (1 + ε)OPT using no more than O (1 /ε^2*OPT/Kmin*log OPT /Kmin) of these operations. We argue, however, that this algorithm could be improved on instances where the setup costs are generally “very large” compared with Kmin. This leads us to introduce a notion of input-size parameter σ that is significantly smaller than OPT/Kmin on instances of this type, and then to define an approximation scheme that executes O (1/ε^2*σ^2*log^2(OPT/ Kmin)) operations. Besides dynamic programming, this second approximation scheme builds on a novel algorithmic approach for Economic Lot Sizing problems. Keywords: Lot-sizing; Approximation scheme; Sub-linear complexity; Continuous time; Economic Order Quantity

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Directions for Sustainable Ports in Latin America and the Caribbean.

Schulte, F.; González, R.; Ascencio, L.; Voss, S. | International Journal of Transport Economics. XLII(3). 215-337.. | 2016

The sustainable design of port processes and the use of respective tools and frameworks for ports in Asia and Europe have received significant attention, while similar challenges and methods for the Latin American ports have not been examined to the same extent. This empirical study of the Latin American ports aims to establish the foundation of an agenda for researchers and practitioners dealing with challenges of sustainable port development in Latin America and the Caribbean (LAC). We present a structural comparison of the examined ports and current results from workshop-based focus group studies conducted in order to elaborate current sustainability challenges and practices in seven major LAC ports. In this way, we obtain insights into specific challenges of LAC ports on the way to more sustainable processes. We structure these insights with respect to the dimensions of sustainability in a staged conceptual reference model for sustainable ports in LAC. The developed model considers the development process of LAC ports and can function as a guideline for researchers and practitioners working in the field of sustainable port logistics and development in the region.

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Correcting for endogeneity due to omitted attributes in discrete-choice models: the multiple indicator solution.

Guevara, A.; Polanco, D. | Transportmetrica A: Transport Science. 12(5): 458-478. | 2016

Various transportation discrete-choice models suffer from endogeneity due to the omission of attributes that are relevant for the decision maker, but cannot be measured by the researcher. The control function (CF) method can be used to address this model flaw in discrete-choice models in which the problem occurs at the level of each alternative. However, the CF requires instrumental variables, which are difficult to obtain in various practical cases. In comparison, the multiple indicator solution (MIS) method does not require instruments, but indicators, which may be easier to gather in various circumstances. The MIS method has only been described so far for linear models. In this article, we show that MIS can be extended to discrete-choice modelling under mild assumptions. We also discuss the conditions under which it could be applied in practical transportation models estimated with revealed preference (RP) and stated preferences (SP) data where the source of endogeneity can be identified explicitly. We then use Monte Carlo experiments to illustrate the finite sample properties of MIS and CF. Results seem to suggest that MIS is robust to mild violations of modelling assumptions. We finally illustrate the application of the MIS method to an SP experiment of dwelling choice, showing that the MIS seems to have addressed successfully the omission of quality inferred from a picture. KEYWORDS: Instrumental variables; indicators; control function; Monte Carlo; stated preferences

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An online algorithm for the container stacking problema.

Guerra, R.; Smith, N.; González R. | DYNA. 83 (198). 195-204. | 2016

Efficient cargo handling is a key element for a maritime port to compete and provide good service levels to its users. The performance of a port is related to ship-turnaround, which is conditioned by the ships loading and unloading operational efficiency. At the yard, containers are temporarily stacked in order to later either load them onto a ship or dispatch them to external users. Stacking has a strong impact on ships’ service times. This paper proposes a container stacking policy, considering the particular characteristics of a container terminal in Chile. In order to measure the performance of the procedure, an upper bound for the number of re-handles of containers is estimated as a function of the block’s capacity. Numerical results are provided in comparison to an upper bound, and a good performance by the proposed procedure is demonstrated.

Keywords: Container Terminal, Yard Management, Container stacking problem.

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A second-order cone programming formulation for Twin Support Vector Machines.

Maldonado, S.; López, J.; Carrasco, M. | Applied Intelligence. 45: 265. DOI 10.1007/s10489-016-0764-4. | 2016

Second-order cone programming (SOCP) formulations have received increasing attention as robust optimization schemes for Support Vector Machine (SVM) classification. These formulations study the worst-case setting for class-conditional densities, leading to potentially more effective classifiers in terms of performance compared to the standard SVM formulation. In this work we propose an SOCP extension for Twin SVM, a recently developed classification approach that constructs two nonparallel classifiers. The linear and kernel-based SOCP formulations for Twin SVM are derived, while the duality analysis provides interesting geometrical properties of the proposed method. Experiments on benchmark datasets demonstrate the virtues of our approach in terms of classification performance compared to alternative SVM methods. Keywords: Support vector classification; Twin support vector machines; Second-order cone programming

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A second-order cone programming formulation for nonparallel hyperplane support vector machine.

Carrasco, M.; López, J.; Maldonado, S. | Expert Systems With Applications. 54: 95-104. | 2016

Expert systems often rely heavily on the performance of binary classification methods. The need for accurate predictions in artificial intelligence has led to a plethora of novel approaches that aim at correctly predicting new instances based on nonlinear classifiers. In this context, Support Vector Machine (SVM) formulations via two nonparallel hyperplanes have received increasing attention due to their superior performance. In this work, we propose a novel formulation for the method, Nonparallel Hyperplane SVM. Its main contribution is the use of robust optimization techniques in order to construct nonlinear models with superior performance and appealing geometrical properties. Experiments on benchmark datasets demonstrate the virtues in terms of predictive performance compared with various other SVM formulations. Managerial insights and the relevance for intelligent systems are discussed based on the experimental outcomes. Keywords: Support vector classification; Nonparallel hyperplane SVM; Second-order cone programming

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A Second-Order Cone Programming Formulation for Nonparallel Hyperplane Support Vector Machine

Carrasco, M.; López, J.; Maldonado, S. | Expert Systems with Applications. 54: 95-104. | 2016

Expert systems often rely heavily on the performance of binary classification methods. The need for accurate predictions in artificial intelligence has led to a plethora of novel approaches that aim at correctly predicting new instances based on nonlinear classifiers. In this context, Support Vector Machine (SVM) formulations via two nonparallel hyperplanes have received increasing attention due to their superior performance. In this work, we propose a novel formulation for the method, Nonparallel Hyperplane SVM. Its main contribution is the use of robust optimization techniques in order to construct nonlinear models with superior performance and appealing geometrical properties. Experiments on benchmark datasets demonstrate the virtues in terms of predictive performance compared with various other SVM formulations. Managerial insights and the relevance for intelligent systems are discussed based on the experimental outcomes.

Keywords: Support vector classification; Nonparallel hyperplane SVM; Second-order cone programming

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A Novel Multi-class SVM Model Using Second-Order Cone Constraints.

López, J.; Maldonado, S.; Carrasco, M. | Applied Intelligence. 44:457-469 DOI 10.1007/s10489-015-0712-8 | 2016

In this work we present a novel maximum-margin approach for multi-class Support Vector Machines based on second-order cone programming. The proposed method consists of a single optimization model to construct all classification functions, in which the number of second-order cone constraints corresponds to the number of classes. This is a key difference from traditional SVM, where the number of constraints is usually related to the number of training instances. This formulation is extended further to kernel-based classification, while the duality theory provides an interesting geometric interpretation: the method finds an equidistant point between a set of ellipsoids. Experiments on benchmark datasets demonstrate the virtues of our method in terms of predictive performance compared with various other multicategory SVM approaches. Keywords: Multi-class classification; Support vector machines; Second-order cone programming.

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A fleet management model for the Santiago Fire Department..

Pérez, J.; Maldonado, S.; López-Ospina, H. | Fire Safety Journal. 82: 1-11. | 2016

The Santiago Fire Department (from here referred to as SFD) lacks a fleet management strategy since their vehicles remain allocated in fixed fire stations, while the presence of seasonal patterns suggests that the frequency of events changes according to their geographical distribution. This fact has led to inequitable service in terms of response times among the nine zones of the SFD. In this empirical study we propose a fleet assignment model for the Santiago Fire Department to maximize the number of incidents successfully attended (standard responses). Results suggest that the implementation of the fleet management proposal will lead to an increase in the number of standard responses of between 6% and 20% with respect to the current situation. This increase in performance is especially important since it does not require new vehicles; it just optimizes the existing siting via dynamic reallocation. Keywords: Fleet management; Fleet allocation; Emergency response

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Transaction vs. Switching Costs – Comparison of Three Core Mechanisms for Mobile Markets

Basaure, A., Suomi, H., & Hämmäinen, H | Telecommunications Policy | 2016


A Reconfiguration of Fire Station and Fleet Locations for the Santiago Fire Department

J. Pérez, S. Maldonado, V. Marianov | Iinternational Journal of Production Research 54(11), 3170-3186. | 2016


A fleet management model for the Santiago Fire Department

Juan Pérez, Sebastián Maldonado, Héctor López-Ospina | FIRE SAFETY JOURNAL | 2016


Pricing and composition of bundles with Constrained Multinomial Logit

Juan Pérez, Héctor López-Ospina, Alejandro Cataldo and Juan-Carlos Ferrer | INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH | 2016


A time allocation model considering external providers

Rosales-Salas, J., and Jara-Díaz, S. | Transportation Research Part B: Methodological | 2016


Beyond Transport time: A review of Time Use Modelling

Jara-Díaz, S., and Rosales-Salas, J. | Transportation Research Part A: Policy and Practice | 2016


A Reconfiguration of Fire Station and Fleet Locations for the Santiago Fire Department

Pérez, J., Maldonado, S., Marianov, V. | International Journal of Production Research 54 (11), 3170-3186 | 2016


A Novel Multi-class SVM Model Using Second-Order Cone Constraints

López, J., Maldonado, S., Carrasco, M. | Applied Intelligence 44(2), 457-469 | 2016


Multi-class Second-Order Cone Programming Support Vector Machines

López, J., Maldonado, S. | Information Sciences 330, 328-341 | 2016


A second-order cone programming formulation for Twin Support Vector Machines

Maldonado, S., López, J., Carrasco, M. | Applied Intelligence 45(2), 265-276. | 2016


A Second-Order Cone Programming Formulation for Nonparallel Hyperplane Support Vector Machine

Carrasco, M., López, J., Maldonado, S. | Expert Systems with Applications 54, 95-104 | 2016


A Fleet Management Model for the Santiago Fire Department

Pérez, J., Maldonado, S., López, H | Fire Safety Journal 82, 1-11. | 2016


The impact of lanes segmentation and booking levels on container terminal gate congestion

Gracia, M.D., González-Ramírez R.G., Mar-Ortiz, J. | Flexible Services and Manufacturing, 29 (3-4), 403-432. | 2016


Directions for sustainable port in Latin America and the Caribbean

Schulte F., González-Ramírez, R.G., Ascencio, L.M., Voß, S. | International Journal of Transport Economics, 43(3), 315-337. | 2016


An online algorithm for the container stacking problem

Guerra-Olivares, R., Smith N.R., González-Ramírez R.G. | DYNA, 83 (198), pp. 196-205. | 2016


Spectrum and license flexibility for 5G networks

Kliks, A.; Holland, O.; Basaure, A.; Matinmikko, M | IEEE Communications Magazine | 2015

Spectrum sharing is a key solution facilitating availability of the necessary spectrum for 5G wireless networks. This article addresses the problem of flexible spectrum sharing by the application of adaptive licensing among interested stakeholders. In particular, it acts as a proponent of “pluralistic licensing” and verifies it in three simulation scenarios that are of strong interest from the perspective of 5G networks. The concluding analysis offers discussion of the potential benefits offered to spectrum holders and other interested players through the application of the pluralistic licensing concept.

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Robust feature selection for multiclass Support Vector Machines using second-order cone programming.

López, J.; Maldonado, S. | INTELLIGENT DATA ANALYSIS. 19(1): S117-S133. | 2015

This work addresses the issue of high dimensionality for linear multiclass Support Vector Machines (SVMs) using second-order cone programming (SOCP) formulations. These formulations provide a robust and efficient framework for classification, while an adequate feature selection process may improve predictive performance. We extend the ideas of SOCP-SVM from binary to multiclass classification, while a sequential backward elimination algorithm is proposed for variable selection, defining a contribution measure to determine the feature relevance. Experimental results with multiclass microarray datasets demonstrate the effectiveness of a low-dimensional data representation in terms of performance.

Keywords: Feature selection, multiclass classification, second-order cone programming, Support Vector Machines

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Reducing port-related truck emissions: Coordinated truck appointments to reduce empty truck trips.

Schulte, F., González-Ramírez, R.G., Voβ, S. | Corman et al. (Eds.): ICCL 2015, LNCS 9335, pp. 495-509. | 2015

Port-related emissions are a growing problem for urban areas often located directly next to maritime container terminals highly frequented by container trucks. Empty truck trips, caused by a lack of coordination among truckers, are responsible for a significant share of these emissions, and collaboration among truckers is seen as the major opportunity to address this issue. Truck appointment systems (TASs) schedule truck activities and enable collaboration for transportation between terminals and client locations. The aim of this work is to introduce a collaborative planning model to be operated within a TAS and to investigate its impact on emission and cost objectives. Starting with a review of requirements for a TAS with collaboration, an optimization model based on the multiple traveling salesman problem with time windows is developed, leveraging collaboration to reduce costs and emissions. The results for a real-world case demonstrate that the developed approach provides appropriately coordinated truck schedules and effectively reduces truck emissions and costs. Keywords: Port emissions; Truck appointment system; Collaboration; Empty trips; Optimization model

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Profit-based feature selection using support vector machines – General framework and an application for customer retention.

Maldonado, S.; Flores, A.; Verbraken, T.; Baesens, B.; Weber,R. | APPLIED SOFT COMPUTING. 35: 740-748. | 2015

Churn prediction is an important application of classification models that identify those customers most likely to attrite based on their respective characteristics described by e.g. socio-demographic and behavioral variables. Since nowadays more and more of such features are captured and stored in the respective computational systems, an appropriate handling of the resulting information overload becomes a highly relevant issue when it comes to build customer retention systems based on churn prediction models. As a consequence, feature selection is an important step of the classifier construction process. Most feature selection techniques; however, are based on statistically inspired validation criteria, which not necessarily lead to models that optimize goals specified by the respective organization. In this paper we propose a profit-driven approach for classifier construction and simultaneous variable selection based on support vector machines. Experimental results show that our models outperform conventional techniques for feature selection achieving superior performance with respect to business-related goals. Keywords: Data mining; Feature selection; Support vector machines; Churn prediction; Customer retention; Maximum profit

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Novel Licensing Schemes

Holland, O.; Basaure, A.; Yamada, W. | Opportunistic Spectrum Sharing and White Space Access: The Practical Reality, 369-389. | 2015

Regulation is often a key challenge that must be overcome in realizing opportunistic spectrum sharing and white spaces access. The associated nature of spectrum licenses issued to spectrum owners can often constrain the possibility of sharing spectrum in an opportunistic manner, especially if there is no agreement from the “owner” of the spectrum that is being opportunistically used or shared. This chapter investigates approaches that are being taken to facilitate opportunistic spectrum sharing and white spaces access through enhancing the nature of the licenses that are issued to spectrum users. Moreover, it presents the proposed novel licensing scheme Pluralistic Licensing and argues/demonstrates its beneficial nature particularly from a financial point of view.

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Kernel Penalized K-means: A feature selection method based on Kernel K-means.

Maldonado, S.; Carrizosa.; Weber, R. | INFORMATION SCIENCES. 322: 150-160. | 2015

We present an unsupervised method that selects the most relevant features using an embedded strategy while maintaining the cluster structure found with the initial feature set. It is based on the idea of simultaneously minimizing the violation of the initial cluster structure and penalizing the use of features via scaling factors. As the base method we use Kernel K-means which works similarly to K-means, one of the most popular clustering algorithms, but it provides more flexibility due to the use of kernel functions for distance calculation, thus allowing the detection of more complex cluster structures. We present an algorithm to solve the respective minimization problem iteratively, and perform experiments with several data sets demonstrating the superior performance of the proposed method compared to alternative approaches.

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Identifying next relevant variables for segmentation by using feature selection approaches.

Seret, A.; Maldonado, S.; Baesens, B. | EXPERT SYSTEMS WITH APPLICATIONS. 42(15-16): 6255-6266. | 2015

Data mining techniques are widely used by researchers and companies in order to solve problems in a myriad of domains. While these techniques are being adopted and used in daily activities, new operational challenges are encountered concerning the steps following this adoption. In this paper, the problem of updating and improving an existing clustering model by adding relevant new variables is studied. A relevant variable is here defined as a feature which is highly correlated with the current structure of the data, since our main goal is to improve the model by adding new information to the current segmentation, but without modifying it significantly. For this purpose, a general framework is proposed, and subsequently applied in a real business context involving an event organizer facing this problem. Based on extensive experiments based on real data, the performance of the proposed approach is compared to existing methods using different evaluation metrics, leading to the conclusion that the proposed technique is performing better for this specific problem. Keywords: Clustering; Feature selection; Filter methods; Customer segmentation; Business analytics

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How Do Surficial Lithic Assemblages Weather in Arid Environments? A Case Study from the Atacama Desert, Northern Chile.

Ugalde, P.; Santoro, C.; Gayo, E.; Latorre, C.; Maldonado, S.; De Pol-Holz, R.; Jackson, D. | GEOARCHAEOLOGY-AN INTERNATIONAL JOURNAL. 30(4): 352-368. | 2015

Archaeological sites composed only of surficial lithics are widespread in arid environments. Numerical dating of such sites is challenging, however, and even establishing a relative chronology can be daunting. One potentially helpful method for assigning relative chronologies is to use lithic weathering, on the assumption that the most weathered artifacts are also the oldest. Yet, few studies have systematically assessed how local environmental processes affect weathering of surficial lithics. Using macroscopic analyses, we compared the weathering of surficial lithic assemblages from seven mid-to-late Holocene archaeological sites sampled from four different microenvironments in the Atacama Desert of northern Chile. Changes in polish, texture, shine, and color were used to establish significant differences in weathering between two kinds of locations: interfluves and canyon sites. Lithics from interfluve sites were moderately to highly weathered by wind and possessed a dark coating, whereas canyon lithics were mildly weathered despite greater exposure to moisture, often lacked indications of eolian abrasion, and lacked dark coatings. Our results show that lithic weathering can be used as a proxy for relative age, but only after considering local environmental factors. The power of such chronologies can be improved by combining archaeological, paleoenvironmental, geomorphological, and taphonomic data.

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Fieller Stability Measure: a novel model-dependent backtesting approach.

Bravo, C.; Maldonado, S. | JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY. 66(11): 1895-1905. | 2015

Dataset shift is present in almost all real-world applications, since most of them are constantly dealing with changing environments. Detecting fractures in datasets on time allows recalibrating the models before a significant decrease in the model’s performance is observed. Since small changes are normal in most applications and do not justify the efforts that a model recalibration requires, we are only interested in identifying those changes that are critical for the correct functioning of the model. In this work we propose a model-dependent backtesting strategy designed to identify significant changes in the covariates, relating a confidence zone of the change to a maximal deviance measure obtained from the coefficients of the model. Using logistic regression as a predictive approach, we performed experiments on simulated data, and on a real-world credit scoring dataset. The results show that the proposed method has better performance than traditional approaches, consistently identifying major changes in variables while taking into account important characteristics of the problem, such as sample sizes and variances, and uncertainty in the coefficients. Keywords: concept drift; dataset shift; backtesting; credit scoring; statistics; logistic regression

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Churn prediction via support vector classification: An empirical comparison.

Maldonado, S. | INTELLIGENT DATA ANALYSIS. 19(1): S135-S17. | 2015

An empirical framework for customer churn prediction modeling is presented in this work. This task represents a very interesting business analytics challenge, given its highly class imbalanced nature, and the presence of noisy variables that adversely affect the prediction capabilities of classification models. In this work, two SVM-based techniques are compared: Support Vector Data Description (SVDD), and standard two-class SVMs. The proposed methodology involves the comparison of these two methods under different conditions of class imbalance and using different subsets of variables. Feature ranking is performed via the Fisher Score Criterion, while the class imbalance problem is dealt with through resampling techniques, namely random undersampling and SMOTE oversampling. Experiments on four customer churn prediction datasets show the advantages of SVDD: it outperforms standard SVM in terms of predictive performance, demonstrating the importance of techniques that take the class imbalance problem into account.

Keywords: Support vector machines, support vector data description, feature selection, class imbalance problem, data mining

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An embedded feature selection approach for support vector classification via second-order cone programming.

Maldonado, S.; López, J. | Intelligent Data Analysis -1. 1-15. | 2015

Feature selection is an important machine learning topic, especially in high dimensional applications, such as cancer prediction with microarray data. This work addresses the issue of high dimensionality of feature selection for linear and kernel-based Support Vector Machines (SVMs) considering second-order cone programming formulations. These formulations provide a robust and efficient framework for classification, while an adequate feature selection process avoids errors in the estimation of means and covariances. Our approach is based on a sequential backward elimination which uses different linear and kernel-based contribution measures to determine the feature relevance. Experimental results with microarray datasets demonstrate the effectiveness in terms of predictive performance and construction of a low-dimensional data representation.

Keywords: Second-order cone programming, Support Vector Machines, feature selection, kernel methods, data mining

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Advanced conjoint analysis using feature selection via support vector machines.

Maldonado, S.; Montoya, R.; Weber, R. | EUROPEAN JOURNAL OF OPERATIONAL RESEARCH. 241(2): 564-574. | 2015

One of the main tasks of conjoint analysis is to identify consumer preferences about potential products or services. Accordingly, different estimation methods have been proposed to determine the corresponding relevant attributes. Most of these approaches rely on the post-processing of the estimated preferences to establish the importance of such variables. This paper presents new techniques that simultaneously identify consumer preferences and the most relevant attributes. The proposed approaches have two appealing characteristics. Firstly, they are grounded on a support vector machine formulation that has proved important predictive ability in operations management and marketing contexts and secondly they obtain a more parsimonious representation of consumer preferences than traditional models. We report the results of an extensive simulation study that shows that unlike existing methods, our approach can accurately recover the model parameters as well as the relevant attributes. Additionally, we use two conjoint choice experiments whose results show that the proposed techniques have better fit and predictive accuracy than traditional methods and that they additionally provide an improved understanding of customer preferences.

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Adoption of Dynamic Spectrum Access technologies: A System Dynamics approach.

Basaure, A; Sridhar, V; Hämmäinen, H. | Telecommunication Systems, 63(2), 169-19. | 2015

The introduction of dynamic spectrum access (DSA) technologies in mobile markets faces technical, economic and regulatory challenges. This paper defines industry openness and spectrum centralization as the two key factors that affect the adoption of DSA technologies. The adoption process is analyzed employing a comprehensive System Dynamics model that considers the network and substitution effects. Two possible scenarios, namely operator-centric and user-centric adoption of DSA technologies are explored in the model. The analysis indicates that operator-centric DSA technologies may be adopted in most countries where spectrum is centralized, while end-user centric DSA technologies may be adopted in countries with decentralized spectrum regime and in niche emerging services. The study highlights the role of standards-based design and concludes by citing case studies that show the practicality of this analysis and associated policy prescriptions. Keywords: Dynamic spectrum access; Industry openness; Spectrum centralization; System dynamics; User-centric and operator-centric adoption scenarios

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A Reconfiguration of Fire Station and Fleet Locations for the Santiago Fire Department.

Pérez, J.; Maldonado, S.; Marianov, V. | International Journal of Production Research. 54 (11). 3170-3186. | 2015

The geographical distribution of the population of the city of Santiago, Chile, has changed significantly in recent years. In spite of this fact, the location of the fire stations has remained unchanged. We propose a model for the optimal location of the fire stations and a fleet assignment for the Santiago Fire Department (SFD), aimed at maximising the number of events attended to with a predefined standard response. The results of the model are compared with respect to the current location of fire stations and fleet assignment in the SFD. There are different types of resources (stations and vehicles), and different types of events in which the same types of vehicles are used. We analyse various possible current and future scenarios, using a forecast based on historical data. Our results show that by optimally reallocating the resources a 10–30% increase can be achieved in the number of emergency calls that are attended to with an adequate response in time and number of vehicles, without the need for additional fire stations or vehicles. Thus our contribution is empirical and relies on the real world application which is being considered by Chilean government.

Keywords: fire stations; fleet allocation; probabilistic models

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A multi-class SVM approach based on the l(1)-norm minimization of the distances between the reduced convex hulls.

Carrasco, M.; Lopez, J.; Maldonado, S. | PATTERN RECOGNITION. 48(5): 1598-1607. | 2015

Multi-class classification is an important pattern recognition task that can be addressed accurately and efficiently by Support Vector Machine (SVM). In this work we present a novel SVM-based multi-class classification approach based on the center of the configuration, a point which is equidistant to all classes. The center of the configuration is obtained from the dual formulation by minimizing the distances between the reduced convex hulls using the l1-norm, while the decision functions are subsequently constructed from this point. This work also extends the ideas of Zhou et al. (2002) [37] to multi-class classification. The use of l1-norm provides a single linear programming formulation, which reduces the complexity and confers scalability compared with other multi-class SVM methods based on quadratic programming formulations. Experiments on benchmark datasets demonstrate the virtues of our approach in terms of classification performance and running times compared with various other multi-class SVM methods. Keywords: Multi-class classification; Support vector machines; Linear programming

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A heuristic procedure for the outbound container relocation problem during export loading operations.

Guerra-Olivares, R., González-Ramírez, R.G., Smith, N. | Mathematical Problems in Engineering. Volume 2015, Article ID 201749, 13 pages. | 2015

During export ship loading operations, it is often necessary to perform relocation movements with containers that interfere with access to the desired container in the ship loading sequence. This paper presents a real-time heuristic procedure for the container relocation problem employing reachstacker vehicles as container handling equipment. The proposed heuristic searches for good relocation coordinates within a set of nearby bays. The heuristic has a parameter that determines how far from the original bay a container may be relocated. The tradeoff between reducing relocation movements and limiting vehicle travel distances is examined and the performance of the heuristic is compared with a common practice in the smaller container terminals in Chile and Mexico. Finally, a mathematical model for the container relocation problem is presented.

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A framework to evaluate over-costs in natural resources logistics chains.

Pérez-Salas, G., González-Ramírez, R.G., Cedillo-Campos, M.G. | DYNA-Colombia, 82 (191), 85-92. | 2015

Foreign trade barriers and duties have been significantly reduced by multilateral agreements and integration mechanisms among nations. Logistics costs represent a significant proportion of the final price of the items, especially of the commodities. For this reason, minimizing logistics costs is an important challenge for nations in order to enhance competiveness of foreign trade and in particular to take advantage of natural resources rents. In this article, we propose a holistic framework for estimating logistics costs, focused on determining over costs that result from inefficient procedures and a lack of adequate public policies and regulations of the public entities. These issues have not been considered in the literature, and this article fills this gap. As a case study, we present the application of the framework to estimate over costs in some natural resources logistics chains of Bolivia. A discussion of the results found is presented together with recommendations for further research.

Keywords : Natural Resources; Logistics chains; International trade.

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A Bi-level Optimization Model for Aid Distribution after the Occurrence of a Disaster.

Camacho-Vallejo, J.F., González-Rodríguez, E., Almaguer F.J., González-Ramírez, R.G. | Journal of Cleaner Production, 105, 134-145. | 2015

In this paper the authors propose a bi-level mathematical programming model for humanitarian logistics to optimize decisions related to the distribution of international aid after a catastrophic disaster. In this situation, non-profit international organizations and foreign countries will offer to help by shipping certain necessary products, such as bottled water, food and medicine, but will want to minimize the shipping costs. At the same time, the affected country seeks to distribute the received aid to the affected areas as efficiently and quickly as possible. To deal with the considered problem, we reformulate the bi-level model and reduce it into a nonlinear single-level mathematical model; then we linearize it to obtain a mixed integer programming problem. To validate the proposed mathematical model, we consider as a case study the earthquake in Chile in 2010. We solve the reformulated model by using real data simulating the aid distribution scenario, and we interpret the obtained numerical results, giving some recommendations for aid distribution following future disasters.

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How Do Surficial Lithic Assemblages Weather in Arid Environments? A Case Study from the Atacama Desert, Northern Chile

Ugalde, Paula C., Calogero M. Santoro, Eugenia M. Gayo, Claudio Latorre, Sebastián Maldonado, Ricardo Pol‐Holz, and Donald Jackson | Geoarchaeology | 2015

Archaeological sites composed only of surficial lithics are widespread in arid environments. Numerical dating of such sites is challenging, however, and even establishing a relative chronology can be daunting. One potentially helpful method for assigning relative chronologies is to use lithic weathering, on the assumption that the most weathered artifacts are also the oldest. Yet, few studies have systematically assessed how local environmental processes affect weathering of surficial lithics. Using macroscopic analyses, we compared the weathering of surficial lithic assemblages from seven mid-to-late Holocene archaeological sites sampled from four different microenvironments in the Atacama Desert of northern Chile. Changes in polish, texture, shine, and color were used to establish significant differences in weathering between two kinds of locations: interfluves and canyon sites. Lithics from interfluve sites were moderately to highly weathered by wind and possessed a dark coating, whereas canyon lithics were mildly weathered despite greater exposure to moisture, often lacked indications of eolian abrasion, and lacked dark coatings. Our results show that lithic weathering can be used as a proxy for relative age, but only after considering local environmental factors. The power of such chronologies can be improved by combining archaeological, paleoenvironmental, geomorphological, and taphonomic data.

Ver enlace externo


New insights on random regret minimization models

van Cranenburgh, Sander; Guevara, Cristian Angelo; Chorus, Caspar G | Transportation Research Part A: Policy and Practice | 2015

This paper develops new methodological insights on Random Regret Minimization (RRM) models. It starts by showing that the classical RRM model is not scale-invariant, and that – as a result – the degree of regret minimization behavior imposed by the classical RRM model depends crucially on the sizes of the estimated taste parameters in combination with the distribution of attribute-values in the data. Motivated by this insight, this paper makes three methodological contributions: (1) it clarifies how the estimated taste parameters and the decision rule are related to one another; (2) it introduces the notion of “profundity of regret”, and presents a formal measure of this concept; and (3) it proposes two new family members of random regret minimization models: the μRRM model, and the Pure-RRM model. These new methodological insights are illustrated by re-analyzing 10 datasets which have been used to compare linear-additive RUM and classical RRM models in recently published papers. Our re-analyses reveal that the degree of regret minimizing behavior imposed by the classical RRM model is generally very limited. This insight explains the small differences in model fit that have previously been reported in the literature between the classical RRM model and the linear-additive RUM model. Furthermore, we find that on 4 out of 10 datasets the μRRM model improves model fit very substantially as compared to the RUM and the classical RRM model.

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A multi-class SVM approach based on the l1-norm minimization of the distances between the reduced convex hulls

Carrasco, M., López, J., Maldonado, S. | Pattern Recognition | 2015

Multi-class classification is an important pattern recognition task that can be addressed accurately and efficiently by Support Vector Machine (SVM). In this work we present a novel SVM-based multi-class classification approach based on the center of the configuration, a point which is equidistant to all classes. The center of the configuration is obtained from the dual formulation by minimizing the distances between the reduced convex hulls using the l1-norm, while the decision functions are subsequently constructed from this point. This work also extends the ideas of Zhou et al. (2002) [37] to multi-class classification. The use of l1-norm provides a single linear programming formulation, which reduces the complexity and confers scalability compared with other multi-class SVM methods based on quadratic programming formulations. Experiments on benchmark datasets demonstrate the virtues of our approach in terms of classification performance and running times compared with various other multi-class SVM methods.

Ver enlace externo


Kernel Penalized K-means: A feature selection method based on Kernel K-means

Maldonado, Sebastian; Carrizosa, Emilio; Weber, Richard | Information Sciences | 2015

We present an unsupervised method that selects the most relevant features using an embedded strategy while maintaining the cluster structure found with the initial feature set. It is based on the idea of simultaneously minimizing the violation of the initial cluster structure and penalizing the use of features via scaling factors. As the base method we use Kernel K-means which works similarly to K-means, one of the most popular clustering algorithms, but it provides more flexibility due to the use of kernel functions for distance calculation, thus allowing the detection of more complex cluster structures. We present an algorithm to solve the respective minimization problem iteratively, and perform experiments with several data sets demonstrating the superior performance of the proposed method compared to alternative approaches.

Ver enlace externo


Fieller Stability Measure: a novel model-dependent backtesting approach

Bravo, Cristian; Maldonado, Sebastian | Journal of the Operational Research Society | 2015

Dataset shift is present in almost all real-world applications, since most of them are constantly dealing with changing environments. Detecting fractures in datasets on time allows recalibrating the models before a significant decrease in the model’s performance is observed. Since small changes are normal in most applications and do not justify the efforts that a model recalibration requires, we are only interested in identifying those changes that are critical for the correct functioning of the model. In this work we propose a model-dependent backtesting strategy designed to identify significant changes in the covariates, relating a confidence zone of the change to a maximal deviance measure obtained from the coefficients of the model. Using logistic regression as a predictive approach, we performed experiments on simulated data, and on a real-world credit scoring dataset. The results show that the proposed method has better performance than traditional approaches, consistently identifying major changes in variables while taking into account important characteristics of the problem, such as sample sizes and variances, and uncertainty in the coefficients.

Ver enlace externo


Profit-based feature selection using support vector machines – General framework and an application for customer retention

Maldonado, Sebastian; Flores, Alvaro; Verbraken, Thomas; Bart Baesens, Richard Weber | Applied Soft Computing | 2015

Churn prediction is an important application of classification models that identify those customers most likely to attrite based on their respective characteristics described by e.g. socio-demographic and behavioral variables. Since nowadays more and more of such features are captured and stored in the respective computational systems, an appropriate handling of the resulting information overload becomes a highly relevant issue when it comes to build customer retention systems based on churn prediction models. As a consequence, feature selection is an important step of the classifier construction process. Most feature selection techniques; however, are based on statistically inspired validation criteria, which not necessarily lead to models that optimize goals specified by the respective organization. In this paper we propose a profit-driven approach for classifier construction and simultaneous variable selection based on support vector machines. Experimental results show that our models outperform conventional techniques for feature selection achieving superior performance with respect to business-related goals.

Ver enlace externo


Identifying next relevant variables for segmentation by using feature selection approaches

Seret, Alex; Maldonado, Sebastian; Baesens, Bart | Expert Systems with Applications | 2015

Data mining techniques are widely used by researchers and companies in order to solve problems in a myriad of domains. While these techniques are being adopted and used in daily activities, new operational challenges are encountered concerning the steps following this adoption. In this paper, the problem of updating and improving an existing clustering model by adding relevant new variables is studied. A relevant variable is here defined as a feature which is highly correlated with the current structure of the data, since our main goal is to improve the model by adding new information to the current segmentation, but without modifying it significantly. For this purpose, a general framework is proposed, and subsequently applied in a real business context involving an event organizer facing this problem. Based on extensive experiments based on real data, the performance of the proposed approach is compared to existing methods using different evaluation metrics, leading to the conclusion that the proposed technique is performing better for this specific problem.

Ver enlace externo


Advanced conjoint analysis using feature selection via support vector machines

Maldonado, Sebastian; Montoya, Ricardo; Weber, Richard | European Journal of Operational Research | 2015

One of the main tasks of conjoint analysis is to identify consumer preferences about potential products or services. Accordingly, different estimation methods have been proposed to determine the corresponding relevant attributes. Most of these approaches rely on the post-processing of the estimated preferences to establish the importance of such variables. This paper presents new techniques that simultaneously identify consumer preferences and the most relevant attributes. The proposed approaches have two appealing characteristics. Firstly, they are grounded on a support vector machine formulation that has proved important predictive ability in operations management and marketing contexts and secondly they obtain a more parsimonious representation of consumer preferences than traditional models. We report the results of an extensive simulation study that shows that unlike existing methods, our approach can accurately recover the model parameters as well as the relevant attributes. Additionally, we use two conjoint choice experiments whose results show that the proposed techniques have better fit and predictive accuracy than traditional methods and that they additionally provide an improved understanding of customer preferences.

Ver enlace externo


Robust feature selection for multiclass Support Vector Machines using second-order cone programming

Lopez, Julio; Maldonado, Sebastian | Intelligent Data Analysis | 2015

This work addresses the issue of high dimensionality for linear multiclass Support Vector Machines (SVMs) using second-order cone programming (SOCP) formulations. These formulations provide a robust and efficient framework for classification, while an adequate feature selection process may improve predictive performance. We extend the ideas of SOCP-SVM from binary to multiclass classification, while a sequential backward elimination algorithm is proposed for variable selection, defining a contribution measure to determine the feature relevance. Experimental results with multiclass microarray datasets demonstrate the effectiveness of a low-dimensional data representation in terms of performance.


Churn prediction via support vector classification: An empirical comparison

Maldonado, Sebastian | Intelligent Data Analysis | 2015

An empirical framework for customer churn prediction modeling is presented in this work. This task represents a very interesting business analytics challenge, given its highly class imbalanced nature, and the presence of noisy variables that adversely affect the prediction capabilities of classification models. In this work, two SVM-based techniques are compared: Support Vector Data Description (SVDD), and standard two-class SVMs. The proposed methodology involves the comparison of these two methods under different conditions of class imbalance and using different subsets of variables. Feature ranking is performed via the Fisher Score Criterion, while the class imbalance problem is dealt with through resampling techniques, namely random undersampling and SMOTE oversampling. Experiments on four customer churn prediction datasets show the advantages of SVDD: it outperforms standard SVM in terms of predictive performance, demonstrating the importance of techniques that take the class imbalance problem into account.


Spectrum and license flexibility for 5G networks

Basaure, A., & Matinmikko, M., Kliks, A., Holland, O. | IEEE Communications Magazine, 53(7), 42-49 | 2015

Spectrum sharing is a key solution facilitating availability of the necessary spectrum for 5G wireless networks. This article addresses the problem of flexible spectrum sharing by the application of adaptive licensing among interested stakeholders. In particular, it acts as a proponent of “pluralistic licensing” and verifies it in three simulation scenarios that are of strong interest from the perspective of 5G networks. The concluding analysis offers discussion of the potential benefits offered to spectrum holders and other interested players through the application of the pluralistic licensing concept.

Ver enlace externo


Adoption of Dynamic Spectrum Access technologies: A System Dynamics approach

Basaure, A; Sridhar, V; Hämmäinen, H. | Telecommunication systems | 2015

The introduction of dynamic spectrum access (DSA) technologies in mobile markets faces technical, economic and regulatory challenges. This paper defines industry openness and spectrum centralization as the two key factors that affect the adoption of DSA technologies. The adoption process is analyzed employing a comprehensive System Dynamics model that considers the network and substitution effects. Two possible scenarios, namely operator-centric and user-centric adoption of DSA technologies are explored in the model. The analysis indicates that operator-centric DSA technologies may be adopted in most countries where spectrum is centralized, while end-user centric DSA technologies may be adopted in countries with decentralized spectrum regime and in niche emerging services. The study highlights the role of standards-based design and concludes by citing case studies that show the practicality of this analysis and associated policy prescriptions.

Ver enlace externo


A time-hierarchical microeconomic model of activities

López-Ospina H., Martínez, F. J., Cortés, C. E. | Transportation | 2015

The microeconomic approach to explain consumers’ behavior regarding the choice of activities, consumption of goods and use of time is extended in this paper by explicitly including the temporal dimension in the choice-making process. Recognizing that some activities, such as a job and education, involve a long-term commitment and that other activities, such as leisure and shopping, are conducted and modified in the short term, we make these differences explicit in a microeconomic framework. Thus, a hierarchical temporal structure defines the time window or frequency of adjusting the variables of activities (duration, location and consumption of goods) and the magnitude of the resources (time and money) spent. We specify and analyze a stylized microeconomic model with two time scales, the macro and micro level, concluding that preference observations at the micro level, such as transport mode choice, are strongly conditioned by the prevailing choices at the macro scale. This result has strong implications for the current theory of the value and allocation of time, as well as on the location of activities, as illustrated by numerical example.

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Understanding time use: Daily or weekly data?

Jara-Díaz, S., and Rosales-Salas, J. | Transportation Research Part A: Policy and Practice, Vol. 76, pp. 38-57. | 2015


Feature Selection for Multiclass Support Vector Machines Using Second-Order Cone Programming

López, J., Maldonado, S. | Intelligent Data Analysis 19 (S1), Special Issue in Business Analytics, 117-133 | 2015


Editorial. Intelligent Data Analysis 19 (S1)

Bravo, C., Davison, M., Maldonado, S., Weber, R. | Special Issue in Business Analytics, 1-2. | 2015


An Embedded Feature Selection Approach for Support Vector Classification via Second-order Cone Programming

Maldonado, S., López, J. | Intelligent Data Analysis 19 (6), 1233-1257 | 2015


A Bi-level Optimization Model for Aid Distribution after the Occurrence of a Disaster

Camacho-Vallejo, J.F., González-Rodríguez, E., Almaguer F.J., González-Ramírez, R.G. | Journal of Cleaner Production, 105, 134-145. | 2015


Solving the Bilevel Facility Location Problem under Preferences by a Stackelberg-Evolutionary algorithm.

Camacho, F., Cordero E., González-Ramírez, R.G. | Mathematical Problems in Engineering, Volume 2014, (2014) Article ID 430243, 14 pages. ISSN: 1563-5147. | 2014

This research highlights the use of game theory to solve the classical problem of the uncapacitated facility location optimization model with customer order preferences through a bilevel approach. The bilevel model provided herein consists of the classical facility location problem and an optimization of the customer preferences, which are the upper and lower level problems, respectively. Also, two reformulations of the bilevel model are presented, reducing it into a mixed-integer single-level problem. An evolutionary algorithm based on the equilibrium in a Stackelberg’s game is proposed to solve the bilevel model. Numerical experimentation is performed in this study and the results are compared to benchmarks from the existing literature on the subject in order to emphasize the benefits of the proposed approach in terms of solution quality and estimation time.

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Robust Classification of Imbalanced Data using Ensembles of One-Class and Two-Class SVMs. Special Issue on Business Analytics and Intelligent Optimization.

Maldonado, S.; Montecinos, C. | Intelligent Data Analysis 18(1), 95-112. (ISI-Q4) (99/121)(IF: 0.548). | 2014

200 words for Intelligent Data Systems The class imbalance problem is a relatively new challenge that has attracted growing attention from both industry and academia, since it strongly affects classification performance. Research also established that class imbalance is not an issue by itself, but its relationship with class overlapping and noise has an important impact on the prediction performance and stability. This fact has motivated the development of several approaches for classification of imbalanced data see e.g. [29,39]. In this paper, we present credit card customer churn prediction, an important topic in business analytics, using an ensemble of classifiers. Since this problem is considered as highly imbalanced, we employ different techniques for classification, such as Support Vector Data Description SVDD and two-class SVMs. The main idea is to address both class imbalance and class overlapping by stacking different classification approaches, while evaluating the diversity of the individual classifiers considering meta-learning measures. We performed experiments on artificial data sets and one real customer churn prediction problem from a Chilean financial entity, comparing our approach with well-known classification techniques for imbalanced data. The proposed strategy achieves an improvement of 6.1% over the best individual classifier in terms of predictive performance, providing accurate and robust classification models for different levels of balance and noise. Keywords: Classification, imbalanced data, ensemble learning, support vector data description, churn prediction, support vector machines, meta learning

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Proceedings of the Computational Logistics: 5th International Conference, ICCL .

RG González-Ramírez, F Schulte, S Voß, JAC Díaz. | Proceedings, Lecture Notes in Computer Science, LNCS 8760. | 2014

This book constitutes the refereed proceedings of the 5th International Conference on Computational Logistics, ICCL 2014, held in Valparaiso, Chile, in September 2014. The 11 papers presented in this volume were carefully reviewed and selected for inclusion in the book. They are organized in topical sections entitled: optimization of transport problems; container terminal applications; simulation and environmental sustainability applications.

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Implications of dynamic spectrum management for regulation.

Basaure, A.; Marianov, V.; Paredes, R. | Telecommunications Policy. Vol 39 (7), 563-579. | 2014

The Coase theorem suggests that a regulatory scheme, which clearly defines spectrum property rights and allows transactions between participants, induces an optimal spectrum assignment. This paper argues that the conditions required by Coase are gradually achieved by the introduction of Dynamic Spectrum Management (DSM), which enables a dynamic reassignment of spectrum bands at different times and places. DSM reduces the costs associated with spectrum transactions and thus provides an opportunity to enhance efficiency through voluntary transactions. This study analyzes the factors affecting the benefits of a regulatory scheme allowing transactions, compares and quantifies the potential gains associated with different spectrum regimes by employing agent-based simulations and suggests policy implications for spectrum regulation. Keywords: Dynamic spectrum management (DSM); Value of the spectrum; Coase theorem; Agent-based modeling (ABM); Spectrum regimes; Spectrum transactions; Interference and property rights.

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Imbalanced data classification using second-order cone programming Support Vector Machines.

Maldonado, S.; López, J. | Pattern Recognition 47(5), 2070-2079. (ISI-Q1) (22/121)(IF: 3.153). | 2014

Learning from imbalanced data sets is an important machine learning challenge, especially in Support Vector Machines (SVM), where the assumption of equal cost of errors is made and each object is treated independently. Second-order cone programming SVM (SOCP-SVM) studies each class separately instead, providing quite an interesting formulation for the imbalanced classification task. This work presents a novel second-order cone programming (SOCP) formulation, based on the LP-SVM formulation principle: the bound of the VC dimension is loosened properly using the -norm, and the margin is directly maximized using two margin variables associated with each class. A regularization parameter C is considered in order to control the trade-off between the maximization of these two margin variables. The proposed method has the following advantages: it provides better results, since it is specially designed for imbalanced classification, and it reduces computational complexity, since one conic restriction is eliminated. Experiments on benchmark imbalanced data sets demonstrate that our approach accomplishes the best classification performance, compared with the traditional SOCP-SVM formulation and with cost-sensitive formulations for linear SVM. Keywords: Class-imbalanced data; Support Vector Machines; LP-SVM; SOCP-SVM

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Feature Selection for Support Vector Machines via Mixed Integer Linear Programming.

Maldonado, S.; Pérez, J.; Labbé, M.; Weber, R. | Information Sciences 279, 163-175. (ISI-Q1)(8/135) (IF: 3.069). | 2014

The performance of classification methods, such as Support Vector Machines, depends heavily on the proper choice of the feature set used to construct the classifier. Feature selection is an NP-hard problem that has been studied extensively in the literature. Most strategies propose the elimination of features independently of classifier construction by exploiting statistical properties of each of the variables, or via greedy search. All such strategies are heuristic by nature. In this work we propose two different Mixed Integer Linear Programming formulations based on extensions of Support Vector Machines to overcome these shortcomings. The proposed approaches perform variable selection simultaneously with classifier construction using optimization models. We ran experiments on real-world benchmark datasets, comparing our approaches with well-known feature selection techniques and obtained better predictions with consistently fewer relevant features.

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Supply chain disruptions propagation caused by criminal acts.

Cedillo, Pérez-Salas, G., G., Bueno, A., González-Ramírez R.G., Jiménez E. | Journal of Applied Research Technology, 12(4), 684-694. | 2014

To understand disruptions and their propagation along the supply chains is becoming critical for designing competitive global supply chains operating in emerging economies. It leads to economic damages to every organization involved in a supply chain, but it also decreases national logistics competitiveness. This research provides numerical elements in terms of significance of the security issue in Latin America, and at the same time, proposes a system dynamics assessment model based on real-life information, able to establish analysis scenarios in order to measure the impacts derived of supply chain disruptions propagation caused by criminal acts. Finally, useful conclusions for designing more resilient supply chains and future research are exposed. Keywords: supply chain; disruption propagation; system dynamics; risk management; emerging markets

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A heuristic procedure for a ship routing and scheduling problem with variable speed and discretized time windows.

Castillo, K. González-Ramírez, R.G., Miranda, P. Smith, N. | Mathematical Problems in Engineering. Volume 2014 (2014), Article ID 750232, 13 pages. | 2014

This paper develops a heuristic algorithm for solving a routing and scheduling problem for tramp shipping with discretized time windows. The problem consists of determining the set of cargoes that should be served by each ship, the arrival, departure, and waiting times at each port, while minimizing total costs. The heuristic proposed is based on a variable neighborhood search, considering a number of neighborhood structures to find a solution to the problem. We present computational results, and, for comparison purposes, we consider instances that can be solved directly by CPLEX to test the performance of the proposed heuristic. The heuristics achieves good solution quality with reasonable computational times. Our computational results are encouraging and establish that our heuristic can be utilized to solve large real-size instances.

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A fuzzy logic model for the container stacking problem at the Container Terminal

Ries, J., González-Ramírez, R.G., Miranda, P. | R.G. González-Ramírez et al. (Eds.): ICCL 2014, LNCS 8760, pp. 93-111, 2014. | 2014

We address the problem of storage space allocation in a sea port terminal. The problem consists of assigning a block space in the yard of a container terminal to every incoming container while ensuring operational efficiency. The proposed framework uses a 2-stage framework in combination with a fuzzy logic rule-based strategy. The concept is motivated by the problem faced by container terminals in Chile and the aim is to provide real-time decision support to deal with a high degree of uncertainty in the arrival of containers at the yard. In addition, the framework provides a more flexible design to include a set of different criteria as well as different infrastructures and layouts of container ports. Numerical results are presented, comparing the results of the fuzzy framework with respect to algorithms proposed in the literature, considering different scenarios.

Keywords: Storage space allocation; container terminal operations; fuzzy logic; online decision support

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A Collaborative Supply Chain Management System for a Maritime Port Logistics Chain

Ascencio, L., González-Ramírez R.G., Smith, N., Bearzotti, L., Camacho, F. | Journal of Applied Research Technology, 12(3), 444-458. | 2014

In this article we propose a collaborative logistics framework for a Port Logistics Chain (PLC) based on the principles of Supply Chain Management (SCM) that rely on stakeholders integration and collaboration, providing a reference model for the inland coordination of the PLC. A comprehensive literature review was conducted, analyzing several cases in which SCM practices have been implemented as well as studies related to port development, governance, coordination and best practices associated. This background information was used to identify current gaps in logistics management practices and potential scopes of intervention within the PLC to suggest a redesign process and configure new structures under a collaborative scheme, following the guidelines of SCM. Keywords: Port Logistics Chain; Supply Chain Management; Demand Management; Orders Management; Vehicle Management

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Feature selection for high-dimensional class-imbalanced data sets using support vector machines

Maldonado, S., Weber, R., Famili, F. | Information Sciences | 2014

Feature selection and classification of imbalanced data sets are two of the most interesting machine learning challenges, attracting a growing attention from both, industry and academia. Feature selection addresses the dimensionality reduction problem by determining a subset of available features to build a good model for classification or prediction, while the class-imbalance problem arises when the class distribution is too skewed. Both issues have been independently studied in the literature, and a plethora of methods to address high dimensionality as well as class-imbalance has been proposed. The aim of this work is to simultaneously explore both issues, proposing a family of methods that select those attributes that are relevant for the identification of the target class in binary classification. We propose a backward elimination approach based on successive holdout steps, whose contribution measure is based on a balanced loss function obtained on an independent subset. Our experiments are based on six highly imbalanced microarray data sets, comparing our methods with well-known feature selection techniques, and obtaining a better prediction with consistently fewer relevant features.

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Alternative Second-Order Cone Programming Formulations for Support Vector Classification

Maldonado, S., López, J. | Information Sciences | 2014

This paper presents two novel second-order cone programming (SOCP) formulations that determine a linear predictor using Support Vector Machines (SVMs). Inspired by the soft-margin SVM formulation, our first approach (ξ-SOCP-SVM) proposes a relaxation of the conic constraints via a slack variable, penalizing it in the objective function. The second formulation (r -SOCP-SVM) is based on the LP-SVM formulation principle: the bound of the VC dimension is loosened properly using the l∞-norm, and the margin is directly maximized. The proposed methods have several advantages: The first approach constructs a flexible classifier, extending the benefits of the soft-margin SVM formulation to second-order cones. The second method obtains comparable results to the SOCP-SVM formulation with less computational effort, since one conic restriction is eliminated. Experiments on well-known benchmark datasets from the UCI Repository demonstrate that our approach accomplishes the best classification performance compared to the traditional SOCP-SVM formulation, LP-SVM, and to standard linear SVM.

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Imbalanced data classification using second-order cone programming Support Vector Machines

Maldonado, S., López, J. | Pattern Recognition | 2014

Learning from imbalanced data sets is an important machine learning challenge, especially in Support Vector Machines (SVM), where the assumption of equal cost of errors is made and each object is treated independently. Second-order cone programming SVM (SOCP-SVM) studies each class separately instead, providing quite an interesting formulation for the imbalanced classification task. This work presents a novel second-order cone programming (SOCP) formulation, based on the LP-SVM formulation principle: the bound of the VC dimension is loosened properly using the l∞-norm, and the margin is directly maximized using two margin variables associated with each class. A regularization parameter C is considered in order to control the trade-off between the maximization of these two margin variables. The proposed method has the following advantages: it provides better results, since it is specially designed for imbalanced classification, and it reduces computational complexity, since one conic restriction is eliminated. Experiments on benchmark imbalanced data sets demonstrate that our approach accomplishes the best classification performance, compared with the traditional SOCP-SVM formulation and with cost-sensitive formulations for linear SVM.

Ver enlace externo


Feature Selection for Support Vector Machines via Mixed Integer Linear Programming

Maldonado, S., Pérez, J., Labbé, M., Weber, R. | Information Sciences | 2014

The performance of classification methods, such as Support Vector Machines, depends heavily on the proper choice of the feature set used to construct the classifier. Feature selection is an NP-hard problem that has been studied extensively in the literature. Most strategies propose the elimination of features independently of classifier construction by exploiting statistical properties of each of the variables, or via greedy search. All such strategies are heuristic by nature. In this work we propose two different Mixed Integer Linear Programming formulations based on extensions of Support Vector Machines to overcome these shortcomings. The proposed approaches perform variable selection simultaneously with classifier construction using optimization models. We ran experiments on real-world benchmark datasets, comparing our approaches with well-known feature selection techniques and obtained better predictions with consistently fewer relevant features.

Ver enlace externo


Robust Classification of Imbalanced Data using Ensembles of One-Class and Two-Class SVMs

Maldonado, S., Montecinos, C. | Intelligent Data Analysis | 2014

200 words for Intelligent Data Systems The class imbalance problem is a relatively new challenge that has attracted growing attention from both industry and academia, since it strongly affects classification performance. Research also established that class imbalance is not an issue by itself, but its relationship with class overlapping and noise has an important impact on the prediction performance and stability. This fact has motivated the development of several approaches for classification of imbalanced data see e.g. [29,39]. In this paper, we present credit card customer churn prediction, an important topic in business analytics, using an ensemble of classifiers. Since this problem is considered as highly imbalanced, we employ different techniques for classification, such as Support Vector Data Description SVDD and two-class SVMs. The main idea is to address both class imbalance and class overlapping by stacking different classification approaches, while evaluating the diversity of the individual classifiers considering meta-learning measures. We performed experiments on artificial data sets and one real customer churn prediction problem from a Chilean financial entity, comparing our approach with well-known classification techniques for imbalanced data. The proposed strategy achieves an improvement of 6.1% over the best individual classifier in terms of predictive performance, providing accurate and robust classification models for different levels of balance and noise.


Implications of dynamic spectrum management for regulation

Basaure, A., Marianov, V., & Paredes, R. | Telecommunications Policy. Vol 39 (7), 563–579 | 2014

The Coase theorem suggests that a regulatory scheme, which clearly defines spectrum property rights and allows transactions between participants, induces an optimal spectrum assignment. This paper argues that the conditions required by Coase are gradually achieved by the introduction of Dynamic Spectrum Management (DSM), which enables a dynamic reassignment of spectrum bands at different times and places. DSM reduces the costs associated with spectrum transactions and thus provides an opportunity to enhance efficiency through voluntary transactions. This study analyzes the factors affecting the benefits of a regulatory scheme allowing transactions, compares and quantifies the potential gains associated with different spectrum regimes by employing agent-based simulations and suggests policy implications for spectrum regulation.

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A method for designing a strategy map using AHP and linear programming

Quezada, L.E., López-Ospina, H. | International Journal of Production Economics | 2014

This paper presents a method to support the identification of the cause-effect relationships of strategic objectives of a strategy map of a balanced scorecard. A strategy map contains the strategic objectives of an organization, grouped into four perspectives (a) finances, (b) clients, (c) internal processes and (d) growth and learning, all of them linked through cause-effect relationships. The issue addressed in this paper is the identification of those relationships, topic in which the existing literature is scarce. A previous work was revisited, which uses the Analytic Hierarchy Process (AHP) to establish the “importance” of the arcs (relationships) of a strategy map. That work then deletes those arcs with an importance lower than a given threshold level defined by the authors. This paper goes beyond by selecting the arcs using a multi-objective linear programming model (LP). The model has two objectives (a) to minimize the number of selected relationships and (b) to maximize the total importance of the selected relationships. It is interested to see that a trade-off between both objectives is produced, so a control variable is used to incorporate the importance given to both objectives by managers. The paper also shows some applications of the method and their analysis.

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A Review of Primary Mine Ventilation System Optimization

Acuña, Enrique I., Lowndes, Ian S. | Interfaces | 2014

Within the mining industry, a safe and economical mine ventilation system is an essential component of all underground mines. In recent years, research scientists and engineers have explored operations research methods to assist in the design and safe operation of primary mine ventilation systems. The main objective of these studies is to develop algorithms to identify the primary mine ventilation systems that minimize the fan power costs, including their working performance. The principal task is to identify the number, location, and duty of fans and regulators for installation within a defined ventilation network to distribute the required fresh airflow at minimum cost. The successful implementation of these methods may produce a computational design tool to aid mine planning and ventilation engineers. This paper presents a review of the results of a series of recent research studies that have explored the use of mathematical methods to determine the optimum design of primary mine ventilation systems relative to fan power costs.

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Feature selection for support vector machines via mixed integer linear programming

Maldonado, S.; Pérez, J.; Labbé, M.; Weber, R. | INFORMATION SCIENCES | 2014


A Collaborative Framework for a Port Logistics Chain

Ascencio, L., González-Ramírez R.G., Smith, N., Bearzotti, L., Camacho, F. | Journal of Applied Research Technology, Volume 12, Issue 3, 2014, 444-458. | 2014


The event management problem in a container terminal.

Bearzotti, L., González-Ramírez R.G., Miranda P. | Journal of Applied Research Technology, JART, Volume 11, Number 1, pp. 95-102. ISSN: 1665-6423. | 2013

The container terminal is a convergence point in the cargo flow, being a focal point for multiple supply chains. Theoperations performed in a container terminal involve one of the most complex environments within the transportindustry. A container terminal plays a critical role in international shipping and is under pressure to cope withincreasing container traffic.This paper presents a multiagent model to solve the event management problem; this problem has a number offeatures which makes the agent a suitable technology to consider applying. The model presented is the basis fordeveloping a tool for the event management process in order to contribute to the reduction of logistics cost and toenhance the competitiveness of the container terminal.

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Territorios como plataformas logísticas: Lecciones Aprendidas y recomendaciones para el Caso de la Región de Valparaíso.

Ascencio, L., González-Ramírez R.G. | Revista Márgenes, No. 13, Vol. 10. ISSN: 0719-4463. | 2013

Los territorios con vocación internacional como las ciudades puerto, deben emprender ajustes a su gobernanza local, regional y global con miras a solucionar problemas que se relacionan con la ciudadanía, la creciente demanda privada por suelo industrial y la anexión de nuevos Hinterland de influencia. La experiencia internacional, no exenta de dificultades, más la experiencia local de diálogo, proveen una base de conocimiento desde donde poder cimentar un nuevo trato en materias de complejidad territorial.

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SVM-based feature selection and classification for email filtering. Pattern recognition- Applications and methods.

Maldonado, S.; L’Huillier, G. | Advances in Intelligent Systems and Computing, 204 (1): 135-148, 2013. | 2013

The email inbox is indeed a dangerous place, but using pattern recognition tools it is possible to filter most wasteful elements that may cause damage to end users. Furthermore, as phishing and spam strategies have shown an adversarial and dynamic behavior, the number of variables to be considered for a proper email classification has increased substantially over time. For many years these elements have driven pattern recognition and machine learning communities to keep improving email filtering techniques. This work presents an embedded feature selection approach that determines a non-linear decision boundary with minimal error and a reduced number of features by penalizing their use in the dual formulation of binary Support Vector Machines (SVMs). The proposed method optimizes the width of an anisotropic RBF Kernel via successive gradient descent steps, eliminating those features that have low relevance for the model. Experiments with two real-world spam and phishing data sets demonstrate that our approach has a better performance than well-known feature selection algorithms while consistently using a smaller number of variables.

Keywords: Spam and phishing filtering; Support vector machines; Feature selection; Embedded methods

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Methodologies for granting and managing loans for micro-entrepreneurs: New developments and practical experiences.

Bravo, C. ; Maldonado, S.; Weber, R. | European Journal of Operational Research, 227 (2): 358-366, 2013. | 2013

We present a methodology to grant and follow-up credits for micro-entrepreneurs. This segment of grantees is very relevant for many economies, especially in developing countries, but shows a behavior different to that of classical consumers where established credit scoring systems exist. Parts of our methodology follow a proven procedure we have applied successfully in several credit scoring projects. Other parts, such as cut-off point construction and model follow-up, however, had to be developed and constitute original contributions of the present paper. The results from two credit scoring projects we developed in Chile, one for a private bank and one for a governmental credit granting institution, provide interesting insights into micro-entrepreneurs’ repayment behavior which could also be interesting for the respective segment in countries with similar characteristics.

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Hybrid extragradient proximal algorithm coupled with parametric approximation and penalty/barrier methods.

Carrasco, M. | Optimization: A Journal of Mathematical Programming and Operations Research, 62 (3): 397-414, 2013. | 2013

In this article we study the hybrid extragradient method coupled with approximation and penalty schemes for convex minimization problems. Under certain hypotheses, which include, for example, the case of Tikhonov regularization, we prove asymptotic convergence of the method to the solution set of our minimization problem. When we use schemes of penalization or barrier, we can show asymptotic convergence using the well-known fast/slow parameterization techniques and exploiting the existence and finite length of an optimal path.

Keywords: parametric approximation; proximal pointhybrid method; convex optimization; global convergence

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Methodologies for Granting and Managing Loans for Micro-Entrepreneurs: New Developments and Practical Experiences

Bravo, C., Maldonado, S., Weber, R. | European Journal of Operational Research 227(2), 358-366 | 2013


Identification of Non-Technical Competency Gaps of Engineering Graduates in Chile

Le Boeuf, R., Pizarro, M., Espinoza R. | International Journal of Engineering Education | 2013

A study was performed to identify the non-technical competencies needed by engineering graduates in Chile. A list of abilities and knowledge attributes were derived from similar studies and the expectations expressed by professional organizations. Input was received from managers of 75 different companies across a broad range of industries and sizes and 116 engineering graduates regarding the importance and preparation for 57 abilities and knowledge attributes in 10 categories. Each competency was given a priority based on one of three criteria: 50% or more of managers reporting it to be of the highest level of importance, an average rating greater than a cutoff, and a weighted measure of priority incorporating the importance and gap between graduate preparation and needs. The results suggest that, to managers in Chile, the most important non-technical competencies are in the areas of project control, ethics, communications, teamwork, innovation and budgeting. The competencies identified as important were similar to those seen in studies in other countries, but with a greater emphasis on ethics and innovation and less emphasis on quality and customer focus. Amethod for prioritizing the important competencies was also presented. Many initiatives were proposed to improve specific non-technical competencies that graduates need for competing in the Chilean job market. This paper presents the methodology, the findings, the comparisons with results from similar studies in other countries, and the strategies developed as a result of the findings.


Insider Trading en Chile: Uso de Información Privilegiada en la bolsa de valores chilena entre 2006 y 2008

Rosales, Jorge | Editorial Académica Española. Saarbrücken, Alemania. ISBN 978-3-8473-6036-0. | 2012


Rentabilidad Educacional: Medición Econométrica de la influencia de la Educación sobre el nivel de los Ingresos en Chile

Rosales, J., Prado, J., Canales, K. | Editorial Académica Española. Saarbrücken, Alemania. ISBN 978-3-659-04742-8 | 2012


A branch-and-cluster coordination scheme for selecting prison facility sites under uncertainty

Hernández P, Alonso-Ayuso A., Bravo F., Escudero L., Grignard M., Marianov V., Weintraub A. | Computers & Operations Research, Volume 39 | 2012

A multi-period stochastic model and an algorithmic approach to location of prison facilities under uncertainty are presented and applied to the Chilean prison system. The problem consists of finding locations and sizes of a preset number of new jails and determining where and when to increase the capacity of both new and existing facilities over a time horizon, while minimizing the expected costs of the prison system. Constraints include maximum inmate transfer distances, upper and lower bounds for facility capacities, and scheduling of facility openings and expansion, among others. The uncertainty lies in the future demand for capacity, because of the long time horizon under study and because of the changes in criminal laws, which could strongly modify the historical tendencies of penal population growth. Uncertainty comes from the effects of penal reform in the capacity demand. It is represented in the model through probabilistic scenarios, and the large-scale model is solved via a heuristic mixture of branch-and-fix coordination and branch-and-bound schemes to satisfy the constraints in all scenarios, the so-called branch-and-cluster coordination scheme. We discuss computational experience and compare the results obtained for the minimum expected cost and average scenario strategies. Our results demonstrate that the minimum expected cost solution leads to better solutions than does the average scenario approach. Additionally, the results show that the stochastic algorithmic approach that we propose outperforms the plain use of a state-of-the-art optimization engine, at least for the three versions of the real-life case that have been tested by us.

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Future trends in business analytics and optimization.

Brown, D.E.; Paas, G.; Smith-Miles, K.; Thomas, L.C.; Weber, R.; Baeza-Yates, R.; Bravo, C.; L’Huillier, G.; Maldonado, S. | Intelligent Data Analysis, 15 (6): 1001-1017, 2011. | 2011

During the last decades, the disciplines of Data Mining and Operations Research have been working mostly independent of each other. However, the increasing complexity of today’s applications in areas such as business, medicine, and science requires more and more interaction between both disciplines. On the one hand, several data mining algorithms are based on optimization methods. On the other hand, in several applications the pure Knowledge Discovery in Databases (KDD) process is not sufficient since it does not take explicitly into account the entire decision process. This report presents future trends in Business Analytics and Optimization discussed at the panel sessions during the workshop on Business Analytics and Optimization (BAO’2010).

Keywords: Future trends, Business Analytics and Optimization, Data Mining, Methodological Research, Real-life Applications

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Districting and Customer Clustering within Supply Chain Planning: A Review of Modeling and Solution Approaches.

Miranda, P.A., R.G. Gonzalez-Ramirez, N. Smith | Supply Chain Management – New Perspectives. Intech Publisher. Edited by Sanda Renko, ISBN: 978-953-307-633-1, pp: 737-770. | 2011

No Abstract Avialable

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Complexity of the multi-product capacitated lot sizing problem (CLSP) with pricing.

Smith, N.R., Gatica, R., González-Ramírez, R.G. | International Journal of Biomedical Soft Computing and Human Sciences, Vol. 17, No. 2, pp. 93-97. ISSN: 1345-1529. | 2011

We study the computational complexity of the multi product capacitated lot-sizing problem with pricing. It has been observed that the introduction of prices in the CLSP seems to make the problem computationally easier. The purpose of this paper is to show that even with the introduction of prices the problem is still NP-Hard. Keywords: complexity theory, inventory, lot-sizing, pricing

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On–line Approximate String Matching with Bounded Errors

Kiwi, M.; Navarro, G.;Telha, C. | Theoretical Computer Science,vol. 412, no 45, pp. 6359-6370, 2011. | 2011

We introduce a new dimension to the widely studied on-line approximate string matching problem, by introducing an error threshold parameter ε so that the algorithm is allowed to miss occurrences with probability ε. This is particularly appropriate for this problem, as approximate searching is used to model many cases where exact answers are not mandatory. We show that the relaxed version of the problem allows us breaking the average-case optimal lower bound of the classical problem, achieving average case O(nlog σ m/m) time with any ϵ=poly(k/m), where n is the text size, m the pattern length, k the number of errors for edit distance, and σ the alphabet size. Our experimental results show the practicality of this novel and promising research direction.

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A hybrid metaheuristic approach to optimize the districting design of a parcel company

González-Ramírez, R.G., Smith, N.R., Askin, R.G., Miranda, P.A., Sánchez, J.M | Journal of Applied Research Technology, JART, 9(1), 19-35. ISSN: 1665-6423. | 2011

In this article we address a districting problem faced by a pickup and delivery parcel company over a determined service region. The service region is divided into districts, each served by a single vehicle that departs from a central depot. Two objectives are optimized: compactness and balance of the workload content among the districts. We present a mathematical formulation of the problem and a heuristic algorithm to solve the problem. Numerical results are presented in comparison to CPLEX 11.1 solutions for the smaller size instances. The results show that the heuristic performs well. The algorithm is able to solve moderate size instances in reasonable computational time, given the strategic nature of the problem.

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A heuristic approach for a multi-product capacitated lot-sizing problem with pricing

González-Ramírez R.G., Smith N.R., Askin R.G | International Journal of Production Research, IJPR. 49(4), 1173-1196. ISSN: 1366-588X. | 2011

We address a multi-product capacitated lot-sizing problem with pricing. The objective is to maximise profit. The problem extends the multi-product capacitated lot-sizing problem (CLSP) found in the literature to include price as a decision variable, demand as a function of price, setup time, and more general holding costs. We present a heuristic procedure that can be used to solve large problem instances quickly with good solution quality. The results of computational testing are presented.

Keywords: decomposition; economic lot-sizing; profit maximisation; pricing

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A Dantzig-Wolfe decomposition approach for a multi-product capacitated lot sizing problem with pricing

González-Ramírez R.G., Smith N.R., Askin R.G. | International Journal of Production Research, IJPR. Volume 49, Number 4, 2011, pp. 1173-1196. | 2011


A note on the convergence of an inertial version of a diagonal hybrid projection-point algorithm.

Carrasco, M.; Pichard, K. | Optimization, Volume 59, Issue 4 May 2010 , pages 561 – 574. | 2010

In this note, an inertial and relaxed version of a diagonal hybrid projection-proximal point algorithm is considered, in order to find the minimum of a function f approximated by a sequence of functions (in general, smoother than f or taking into account some constraints of the problem). Two convergence theorems are proved under different kind of assumptions, which allows to apply the method in various cases.

Keywords: parametric approximation; diagonal iteration; proximal point; hybrid method; inertial term; relaxation; global convergence

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A heuristic approach for a logistics districting problem.

González-Ramírez R.G., Smith N.R., Askin R.G, Kalashnikov, V., | International Journal of Innovative Computing, Information & Control, IJICIC, 6(8), 3551-3562. ISSN: 1349-4198. | 2010

This article addresses a logistics districting problem for a company whoseoperations consist of the pickup and delivery of packages within a region. The serviceregion is to be divided into districts, each served by a single vehicle that departs from acentral depot. The district design aims to optimize two criteria: compact district shapeand balance of workload content among districts. We present a mathematical formulationof the problem as well as a multi-start heuristic procedure to solve the problem. Theprocedure combines some elements of metaheuristics such as Tabu Search and GRASP.Experimental results in comparison with CPLEX solutions are presented. Keywords: Districting, Compactness, Workload balance, Tabu search, GRASP

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Shipment consolidation by terminals and vehicles.

González-Ramírez R.G., Askin R.G, Smith N.R., Villalobos R. | Revista de Matemática: Teoría y Aplicaciones, Volume 16, Number 1, pp. 178-187. ISSN: 1409-2433. | 2009

Este proyecto diseña e implementa un nuevo módulo como parte de una herramienta para el análisis de actividades logísticas llamada ”Logistika”, que fue desarrollada por algunos alumnos de posgrado en la Universidad del Estado de Arizona (ASU). Inicialmente, Logistika solo teńıa disponible el “Módulo para la localización de plantas”, pero nosotros realizamos una extensión para incluir un nuevo módulo llamado “Módulo para la consolidación de envíos”. El objetivo es determinar la mejor estrategia de distribución para productos manufacturados en Mexico hacia clientes ubicados en Estados Unidos. La herramienta explora dos estrategias de consolidación: por vehículos y por terminales para minimizar los costos de transportación e inventario en tránsito incurridos. También se considera que se desea localizar un centro de consolidación en México para el cual la mejor ubicación debe ser encontrada.

Palabras clave: Consolidación, Localización Minimización de Costos, Ruteo

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A heuristic approach to a lot sizing and pricing multiproduct, multiperiod and discrete time model.

González-Ramírez R.G., Smith N.R., Askin R.G. | ICIC Express Letters 3 (A), pp. 489-494. ISSN: 1881-803X. | 2009

This work presents an optimization method to solve a multi productcapacitated lot sizing problem with pricing. In this way, prices and inventorydecisions are coordinated. A heuristic methodology based on a modified versionof a Dantzig-Wolfe decomposition approach is proposed. Experimental results incomparison to CPLEX 11.1 are reported.

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OPF with SVC and UPFC modeling for longitudinal systems

R. Palma, L. Vargas, J. Pérez, R. Torres | IEEE TRANSACTIONS ON POWER SYSTEMS | 2004


Engineering and Technology Management: Education

D. F. Kocaoglu, F. E. Rivera | Directions, INFORMS XXXIII – SINGAPORE, Singapore, June 25-28 | 1995


Engineering and Technology Management

D. F. Kocaoglu, F. E. Rivera | TIMS/ORSA Joint National Meeting, Detroit, October 23-26 | 1994

Matemática


A feasible direction algorithm for nonlinear second-order cone programs

Canelas, A.; Carrasco, M.; López, J. | Optimization Methods & Software. 34(6):1322-1341. | 2019

In this work, we present a new feasible direction algorithm for solving smooth nonlinear second-order cone programs. These consist of minimizing a nonlinear smooth objective function subject to some nonlinear second-order cone constraints. Given an interior point to the feasible set defined by the conic constraints, the algorithm generates a feasible sequence with monotone decreasing values of the objective function. Under mild assumptions, we prove the global convergence of the algorithm to KKT points. Finally, we present some computational results applied to several instances of randomly generated benchmark problems and robust support vector machine classification.

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A new method for reliability analysis and reliability-based design optimization

Canelas, A.; Carrasco, M.; Lopez, J. | Structural and Multidisciplinary Optimization. 59(5): 1655-1671. | 2019

We present a novel method for reliability-based design optimization, which is based on the approximation of the safe region in the random space by a polytope-like region. This polytope is in its turn transformed into quite a simple region by using generalized spherical coordinates. The failure probability can then be easily estimated by considering simple quadrature rules. One of the advantages of the proposed approach is that by increasing the number of vertices, we can improve arbitrarily the accuracy of the failure probability estimation. The sensitivity analysis of the failure probability is also provided. We show that the proposed approach leads to an optimization problem, where the set of optimization variables includes all the original design variables and all the parameters that control the shape of the polytope. In addition, this problem can be solved by a single iteration scheme of optimization. We illustrate the performance of the new approach by solving several examples of truss topology optimization.

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Application of the sequential parametric convex approximation method to the design of robust trusses

Canelas, A.; Carrasco, M; López, J. | J. Glob. Optim. 68: 169-187. | 2017

We study an algorithm recently proposed, which is called sequential parametric approximation method, that finds the solution of a differentiable nonconvex optimization problem by solving a sequence of differentiable convex approximations from the original one. We show as well the global convergence of this method under weaker assumptions than those made in the literature. The optimization method is applied to the design of robust truss structures. The optimal structure of the model considered minimizes the total amount of material under mechanical equilibrium, displacements and stress constraints. Finally, Robust designs are found by considering load perturbations.

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Stochastic topology design optimization for continuous elastic materials

Carrasco, M.; Ivorra, B.; Manuel Ramos, A. | COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING. 289: 131-154. | 2015

In this paper, we develop a stochastic model for topology optimization. We find robust structures that minimize the compliance for a given main load having a stochastic behavior. We propose a model that takes into account the expected value of the compliance and its variance. We show that, similarly to the case of truss structures, these values can be computed with an equivalent deterministic approach and the stochastic model can be transformed into a nonlinear programming problem, reducing the complexity of this kind of problems. First, we obtain an explicit expression (at the continuous level) of the expected compliance and its variance, then we consider a numerical discretization (by using a finite element method) of this expression and finally we use an optimization algorithm. This approach allows to solve design problems which include point, surface or volume loads with dependent or independent perturbations. We check the capacity of our formulation to generate structures that are robust to main loads and their perturbations by considering several 2D and 3D numerical examples. To this end, we analyze the behavior of our model by studying the impact on the optimized solutions of the expected-compliance and variance weight coefficients, the laws used to describe the random loads, the variance of the perturbations and the dependence/independence of the perturbations. Then, the results are compared with similar ones found in the literature for a different modeling approach.

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Stochastic topology design optimization for continuous elastic materials

Carrasco, M., Ivorra, B., Ramos, A.M. | Computer Methods in Applied Mechanics and Engineering | 2015

In this paper, we develop a stochastic model for topology optimization. We find robust structures that minimize the compliance for a given main load having a stochastic behavior. We propose a model that takes into account the expected value of the compliance and its variance. We show that, similarly to the case of truss structures, these values can be computed with an equivalent deterministic approach and the stochastic model can be transformed into a nonlinear programming problem, reducing the complexity of this kind of problems. First, we obtain an explicit expression (at the continuous level) of the expected compliance and its variance, then we consider a numerical discretization (by using a finite element method) of this expression and finally we use an optimization algorithm. This approach allows to solve design problems which include point, surface or volume loads with dependent or independent perturbations. We check the capacity of our formulation to generate structures that are robust to main loads and their perturbations by considering several 2D and 3D numerical examples. To this end, we analyze the behavior of our model by studying the impact on the optimized solutions of the expected-compliance and variance weight coefficients, the laws used to describe the random loads, the variance of the perturbations and the dependence/independence of the perturbations. Then, the results are compared with similar ones found in the literature for a different modeling approach.

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A multi-class SVM approach based on the l1-norm minimization of the distances between the reduced convex hulls

Carrasco, M., López, J., Maldonado, S. | Pattern Recognition | 2015

Multi-class classification is an important pattern recognition task that can be addressed accurately and efficiently by Support Vector Machine (SVM). In this work we present a novel SVM-based multi-class classification approach based on the center of the configuration, a point which is equidistant to all classes. The center of the configuration is obtained from the dual formulation by minimizing the distances between the reduced convex hulls using the l1-norm, while the decision functions are subsequently constructed from this point. This work also extends the ideas of Zhou et al. (2002) [37] to multi-class classification. The use of l1-norm provides a single linear programming formulation, which reduces the complexity and confers scalability compared with other multi-class SVM methods based on quadratic programming formulations. Experiments on benchmark datasets demonstrate the virtues of our approach in terms of classification performance and running times compared with various other multi-class SVM methods.

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Dual convergence for penalty algorithms in convex programming

Álvarez, F.; Carrasco, M.; Champion, T. | Journal of Optimization Theory and Applications, 153 (2): 388-407, 2012. | 2012

Algorithms for convex programming, based on penalty methods, can be designed to have good primal convergence properties even without uniqueness of optimal solutions. Taking primal convergence for granted, in this paper we investigate the asymptotic behavior of an appropriate dual sequence obtained directly from primal iterates. First, under mild hypotheses, which include the standard Slater condition but neither strict complementarity nor second-order conditions, we show that this dual sequence is bounded and also, each cluster point belongs to the set of Karush–Kuhn–Tucker multipliers. Then we identify a general condition on the behavior of the generated primal objective values that ensures the full convergence of the dual sequence to a specific multiplier. This dual limit depends only on the particular penalty scheme used by the algorithm. Finally, we apply this approach to prove the first general dual convergence result of this kind for penalty-proximal algorithms in a nonlinear setting.

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An expected compliance model for topology optimization, Differ

Carrasco, M.; Ivorra, B.; Ramos, A.M.; Lecaros, R. | Equ. Appl., 4(1): 111-120, 2012. | 2012

In this paper, we focus in developing a stochastic model for topology optimization. The principal objective of such a model is to find robust structures for a given main load having a stochastic behavior. In the first part, we present the expected compliance formulation and some results in topology optimization. Then, in order to illustrate the interest of our approach, we consider a preliminary 3D cantilever benchmark experiment and compare the obtained results with the one given by a single load approach.

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A variance-expected compliance model for structural optimization

Carrasco, M.; Ivorra, B.; Ramos, A.M. | Journal of Optimization Theory and Applications, 1 (152): 136-151, 2012. | 2012

The goal of this paper is to find robust structures for a given main load and its perturbations. In the first part, we show the mathematical formulation of an original variance-expected compliance model used for structural optimization. In the second part, we study the interest of this model on two 3D benchmark test cases and compare the obtained results with those given by an expected compliance model.

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Minimization of the expected compliance as an alternative approach to multiload model. Structural and multidisciplinary optimization

F. Álvarez, M. Carrasco. | Structural and Multidisciplinary Optimization, 29 (2005), no. 6, 470 – 476. | 2005

We show that a problem of finding the truss of minimum expected compliance under stochastic loading conditions is equivalent to the dual of a special convex minimax problem, and therefore may be efficiently solved. This equivalence makes it possible to provide classic multiload compliance minimization problems with interpretations in a probabilistic setting. In fact, we prove that minimizing the expected compliance amounts to solving a multiload-like problem associated with a particular finite set of loading scenarios, which depend on the mean and the variance of the perturbations.

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Convergence of a diagonal hybrid projection-proximal point algorithm for approximation methods in optimization

F. Álvarez, M. Carrasco, Pichard, K. | Mathematics of Operations Research, 30 (2005), no. 4, 966 -984. | 2005

In order to minimize a closed convex function that is approximated by a sequence of better behaved functions, we investigate the global convergence of a general hybrid iterative algorithm, which consists of an inexact relaxed proximal point step followed by a suitable orthogonal projection onto a hyperplane. The latter permits to consider a fixed relative error criterion for the proximal step. We provide various sets of conditions ensuring the global convergence of this algorithm. The analysis is valid for nonsmooth data in infinite-dimensional Hilbert spaces. Some examples are presented, focusing on penalty/barrier methods in convex programming. We also show that some results can be adapted to the zero-finding problem for a maximal monotone operator.

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Movilidad Urbana

Exploring the effect of boarding and alighting ratio on passengers’ behaviour at metro stations by laboratory experiments

Seriani, S., Fernandez, R., Luangboriboon, N., Fujiyama, T. | Journal of Advanced Transportation Article ID 6530897 / 2019 / DOI: 10.1155/2019/6530897. | 2019

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Experimental study for estimating the passenger space at metro stations with platform edge doors

Seriani, S, Fujiyama, T | Transportation Research Record: Journal of the Transportation Research Board | 2019

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Obras Civiles

Probabilistic characterization of a high-cycle accumulation model for sands

[J45] Birrell, M., Pasten, C., Abell, J., and Astroza, R. | Computers and Geotechnics | 2022

In this paper, we employ a Bayesian approach to estimate the parameters of a high cycle accumulation model for sands using experimental data. Global sensitivity analysis and Markov-Chain Monte Carlo simulation are conducted for each of the twenty-four available experimental drained triaxial test results, considering the effect of estimating soil parameters at each strain-cycle under several loading conditions. Probability distributions inferred from each data source are then combined to obtain a single distribution for model parameters. Model calibration is then validated against new observations. The accumulated strain model is calibrated through explicit computation of strain at each cycle and the strain dependence of model parameters is included through the cyclic variation of the model constants. Keywords: High cycle accumulation model; Ratcheting; Bayesian estimation; Sensitivity analysis

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ShakerMaker: A framework that simplifies the simulation of seismic ground-motions

Jose A. Abell., Jorge G.F. Crempien, Matías Recabarren

SoftwareX, 2022

ShakerMaker is an open-source python framework which simplifies the generation of synthetic broad-band seismograms, produced by finite-fault kinematic representations of earthquake ruptures, using a 1-D layered model of the crust and the frequency–wavenumber (f–k) method. It is designed to bring closer the engineering seismology and earthquake engineering communities, by catering to the earthquake simulation needs of both disciplines. One particular goal of this framework is to provide a simple way to produce high-fidelity earthquake motions for use with the domain-reduction method, simplifying the setup of physically accurate finite-element simulations of multi-scale seismological and earthquake engineering problems through the use of a new specialized file format. ShakerMaker’s core is composed of a high-performance Fortran implementation of the f–k method, that is exposed to the user as a python framework. Its software architecture emphasizes simplicity, extensibility, and performance, allowing users to specify complex simulation scenarios with short scripts. The message passing interface is used to achieve scalability from simple single-processor machines to HPC clusters.

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Statistical analysis of the modal properties of a seismically-damaged five-story RC building identified using ambient vibration data

Astroza, R., Conte, J.P., Restrepo, J.I., Ebrahimian, H., and Hutchinson, T.C.

Journal of Building Engineering, 2022

Damage detection (DD) is one of the primary goals of health monitoring of civil structures. Vibration-based techniques aim to identify the modal properties (or vibration characteristics) of structures and are one of the most popular approaches for structural damage detection. The use of vibration characteristics (natural frequencies, damping ratios, and mode shapes) for DD purposes is based on the premise that these characteristics change when the structure suffers damage, since the modal properties depend on the physical properties (mass, stiffness, and damping) of the structure. The use of output-only measurements (e.g., ambient vibration or AV) is the most popular approach for damage detection of civil structures. AV data recorded before and after the structure has potentially suffered damage can be used for DD. However, application of vibration-based DD using AV requires an accurate and reliable estimation of the modal properties and their variability (or uncertainty) in order to genuinely determine the existence of damage. This study presents a comprehensive statistical analysis of the identified modal properties of a full-scale five-story reinforced concrete building using AV data. The building specimen was tested on the [email protected] shake table in base-isolated and fixed-base configurations. On April 6, 2012, about two weeks before the start of the seismic tests in the base-isolated configuration, a dense array of twenty accelerometers was deployed on the structure and AV data were recorded continuously until May 18, 2012, three days after completion of the seismic tests in the fixed-base configuration. In its fixed-base configuration, the building was subjected to a sequence of six earthquake motions that progressively damaged the structure. Two popular methods of operational modal analysis are used to automatically identify the modal properties of the fixed-base building at different damage states using the recorded AV data. A statistical analysis of the identified modal parameters is performed to investigate the statistical variability and accuracy of the system identification results. The variability of the identified modal parameters due to environmental conditions is also investigated.

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A Bayesian approach for fatigue damage diagnosis and prognosis of wind turbine blades

Jaramillo, F., Gutiérrez, J.M., Orchard, M., Guarini, M., and Astroza, R.

Mechanical Systems and Signal Processing, 2022

This paper proposes a Bayesian framework based on particle filters for online fatigue damage diagnosis and prognosis for wind turbine blades (WTBs). The framework integrates theoretical and practical aspects with the purpose of developing a robust monitoring tool. Besides, a damage indicator based on identified modal frequencies of the WTB is defined to quantify the degree of damage to the monitored blade. Furthermore, feature extraction techniques on vibration signals are considered to obtain the online observations and inputs needed by the Bayesian framework. Experimental data collected from a fatigue test performed on a WTB was used to validate the proposed methodology. The results obtained by the damage diagnosis algorithm show the great potential of the Bayesian processor for damage estimation of the monitored WTB and uncertainty quantification related to the estimated variable. According to the damage prognosis results, the proposed algorithm could generate suitable long-term predictions of the damage indicator so as to estimate the time-of-failure (ToF) probability mass function (PMF) for the monitored WTB. Consequently, the computed ToF-PMF was able to include the experimental ToF within its 95% confidence interval, demonstrating the accuracy of the Bayesian approach.

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A experimental study of a cable-pulleys spring-damper energy dissipation system for buildings

Hernández, F., Astroza, R., Beltrán, J.F., Zhang, X., and Mercado, V.

Journal of Building Engineering, 2022

An energy dissipation mechanism made of a cable-pulleys system placed in series with a spring-damper device (fluid viscous) is experimentally studied. The system aims to provide high damping ratios for all the structural modes by using a unique spring-damper device to dissipate the seismic energy of the entire structure (and all its structural modes). Shake table tests and pull-back tests are carried out on a scaled five-story structure to compare the dissipation capabilities provided by the proposed system. Therefore, the same structure is tested under different configurations that included: i) the structure itself without any energy mitigation device, ii) the structure with viscous dampers installed on each story, iii) the structure with the proposed cable-pulleys and the spring-damper system, and iv) the structure with the cable-pulleys system but without any dissipation device. The experimental results showed that the structure with the proposed system exhibits a highly nonlinear response (mainly explained by the cable-pulleys interaction) evidenced by the significant change of the structure’s dynamic properties during the time. The Short-Time Transfer Function plots show that the structure’s natural frequencies change significantly when the cable-pulleys system is included. Complementarily, a novel time-variant system identification approach, termed Mod-ζ(var), is proposed, which allows estimating the time-variant evolution of the structure’s dynamic properties during seismic tests (natural frequencies, damping ratios, and mode shapes). Moreover, the Mod-ζ(var) approach also enables computing relevant engineering quantities such as the empirical response spectrum from experimental data. It is found that the analyzed energy dissipation system provides high damping ratios (>10%) for all the structural modes, allowing reducing the seismic demands in terms of the empirical response spectrum, inter-story drifts, inter-story shear forces, peak accelerations, and Housner Intensities at each floor.

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Bayesian updating and identifiability assessment of nonlinear finite element models

Ramancha, M.K., Astroza, R., Madarshahian, R., and Conte, J.P.

Mechanical Systems and Signal Processing, 2022

A promising and attractive way of performing structural health monitoring (SHM) and damage prognosis (DP) of engineering systems is through utilizing a nonlinear finite element (FE) model. Often, FE models contain parameters that are unknown or known with significant level of uncertainty. Such parameters need to be estimated/updated/calibrated using data measured from the physical system. The Bayesian paradigm to model updating/calibration is attractive as it accounts, using a rigorous probabilistic framework, for numerous sources of uncertainties existing in the real-world. However, applying Bayesian methods to nonlinear FE models of large-scale civil structural systems is computationally very prohibitive. Additionally, non-identifiability of FE model parameters poses challenges in the model updating process. This paper presents Bayesian model updating and identifiability analysis of nonlinear FE models with a specific testbed civil structure, Pine Flat concrete gravity dam, as illustration example. Model updating is performed in the recursive mode using the unscented Kalman filter (UKF) and in the batch mode using the transitional Markov chain Monte Carlo (TMCMC) method. Limitations in terms of applicability and computational challenges of each method for model updating of large-scale nonlinear FE models are addressed and discussed. Identifiability and sensitivity analyses of the model are then performed using local and global methods. Local practical identifiability analysis using local sensitivity in conjunction with the Fisher information matrix is used to assess the parameter identifiability in a certain local region in the parameter space. Due to the nonexistence of a method to assess global practical identifiability, variance-based global sensitivity analysis (Sobol’s method) is used herein. Identifiability and sensitivity analysis results are used to choose the parameters to be included in the model updating phase.

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A Lifecyle assessment of a low-energy mass-timber building and mainstream concrete alternative in Central Chile

Felmer, G., Morales-Vera, R., Astroza, R., González, I., Puettmann, M., and Wishnie, M.

Sustainability, 2022

While high-rise mass-timber construction is booming worldwide as a more sustainable alternative to mainstream cement and steel, in South America, there are still many gaps to overcome regarding sourcing, design, and environmental performance. The aim of this study was to assess the carbon emission footprint of using mass-timber products to build a mid-rise low-energy residential building in central Chile (CCL). The design presented at a solar decathlon contest in Santiago was assessed through lifecycle analysis (LCA) and compared to an equivalent mainstream concrete building. Greenhouse gas emissions, expressed as global warming potential (GWP), from cradle-to-usage over a 50-year life span, were lower for the timber design, with 131 kg CO2 eq/m2 of floor area (compared to 353 kg CO2 eq/m2) and a biogenic carbon storage of 447 tons of CO2 eq/m2 based on sustainable forestry practices. From cradle-to-construction, the embodied emissions of the mass-timber building were 42% lower (101 kg CO2 eq/m2) than those of the equivalent concrete building (167 kg CO2 eq/m2). The embodied energy of the mass-timber building was 37% higher than that of its equivalent concrete building and its envelope design helped reduce space-conditioning emissions by as much as 83%, from 187 kg CO2 eq/m2 as estimated for the equivalent concrete building to 31 kg CO2 eq/m2 50-yr. Overall, provided that further efforts are made to address residual energy end-uses and end-of-life waste management options, the use of mass-timber products offers a promising potential in CCL for delivering zero carbon residential multistory buildings.

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Flue Gas Desulfurization (FGD) Fly Ash as a Sustainable, Safe Alternative for Cement-Based Materials

I. Navarrete; F. Vargas; P. Martinez; A. Paul; M. López | Journal of Cleaner Production | 2021

The reduction in fly ash production in coal-fired power plants has created an opportunity to explore alternative types of fly ashes previously deemed unfit for use in concrete. In plants using flue gas desulfurization (FGD) processes, fly ash could contain high amounts of sulfur oxides, making its use in concrete inadvisable. However, the type of sulfur compound present in a fly ash strongly impacts its performance in concrete. In this study, two types of fly ash were used to evaluate the effect of sulfur oxides on mortar mixtures incorporating fly ash as supplementary cementitious material (SCM); one from an FGD unit, with high sulfur oxide content (in the form of hannebachite), and the other generated in a system without FGD, with negligible sulfur oxide. Calorimetry results show that hannebachite can effectively control C3A hydration similar to gypsum; however, its presence in FGD fly ash does not induce deleterious expansion associated with internal sulfate attack in mortars. TGA and XRD analyses suggest that hannebachite has lower reactivity than sulfate. Hannebachite not only maintains the pozzolanic reactivity of the fly ash, but its fineness may promote OPC hydration, increasing compressive strength. The results of this study indicate that FGD fly ash can be used as an SCM, allowing more sustainable concrete production.

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Extending the particle finite element method for sediment transport simulation

N. Galano; P. Moreno-Casas; J.A. Abell | Computer Methods in Applied Mechanics and Engineering | 2021

The present work extends the capabilities of the Particle Finite Element Method (PFEM), which allows modeling of soil–fluid–structure interaction problems, to allow the modeling of sediment transport and scouring effects. This is accomplished by implementing scouring rules on an evolving scourable-interface, i.e. the interface surface between fluid and soil. The proposed method improves upon previous proposals by jointly capturing both the temporal and spatial scales of scouring evolution, as shown in the presented validation exercise, and also because its parametrization is conforms with commonplace engineering procedures for scouring prediction. The extension preserves desirable PFEM properties such as conservation of mass, mesh-size independence, and stability of the numerical solution of the PFEM equations and adds a negligible computational overhead to the PFEM implementation.

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On the performance of unscented Kalman filter in parameter estimation of nonlinear finite element models

Astroza, R. and Barrientos, N. | Chapter 39 in Experimental Vibration Analysis for Civil Structures (ISBN 978-0-367-54746-2) | 2021

This paper describes a framework to update nonlinear finite element (FE) models. The method combines advanced mechanics-based nonlinear FE models and the Unscented Kalman filter (UKF) to estimate unknown time-invariant model parameters of FE models of civil structures subjected to earthquake excitation. The performance and computational cost of different unscented transformations (UTs) are examined in this paper, and the standard and square-root formulations of the filter are also investigated. A two-dimensional, 3-story, 3-bay steel moment frame with eight unknown parameters is used as application example. The steel frame is modeled using fiber-section beam-column elements with distributed plasticity and is subjected to a ground motion recorded during the 1989 Loma Prieta earthquake. The results indicate that most of the UKFs provide accurate estimates of the model parameters but significant differences in the computational cost are observed.

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Experimental system and damage identification of small-scale wind turbine blades

Gutiérrez, J.M., Astroza, R., Abell, J., Soto, C., Jaramillo, F., Guarini, M., and Orchard, M. | Chapter 23 in Experimental Vibration Analysis for Civil Structures (ISBN 978-0-367-54746-2) |2021

Blades are one of the main and more costly components of wind turbines and, besides, are difficult to inspect and maintain. Due to operational conditions, wind turbine blades (WTBs) are prone to suffer structural damage, chiefly because of fatigue or extreme loading. Therefore, it is crucial to monitor the state of health (SoH) of these components by implementing robust damage diagnosis and prognosis methods, for identifying the damage and estimating the remaining useful life (RUL), respectively. To study the degradation effects due to fatigue and extreme loads on WTBs, a testing system for small-scale blades was designed and built. The testing machine is able to induce sinusoidal loading with varying amplitude and frequency, then generating damage caused by repetitive loads. Test protocols consisting of extreme (close to resonance) and fatigue-type loading were designed to progressively damage the WTBs, and impact and pull-back tests were conducted at different stages of damage. The free vibration response data measured by an accelerometer array during impact tests is used to identify the modal properties of the blades using an output-only system identification algorithm. The variations of the identified modal properties are then correlated to the physical damage using modal-based damage indices.

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Time variant system identification of superstructures of base-isolated buildings

Hernández, F., Díaz, P., and Astroza, R., Ochoa-Cornejo, F., and Zhang, X. | Engineering Structures | 2021

The time-variant dynamic properties related to the superstructure of base-isolated (BI) buildings are identified using a simple substructure approach. Based on the acceleration data recorded in BI buildings during earthquake events, the short-time deterministic-stochastic subspace identification (STDSI) method and a novel short-time transfer function (STTF) method are used to identify the temporal evolution of the modal properties of the superstructure, which can be consequently employed to study the evolution of its potential damage. The proposed substructure approach is applied to experimental data from three BI structures: a building numerically simulated using the commercial software SAP2000, a full-scale five-story reinforced concrete BI building tested at different intensity levels on a large-scale shake table, and an instrumented four-story reinforced masonry building located in Chile. The results indicate that the identified modal properties obtained for the superstructure by using the proposed approach are comparable to those obtained from the corresponding fixed-base (FB) buildings, allowing to study in detail the dynamic behavior of BI buildings’ superstructures disaggregating the highly inelastic response associated with the seismic isolation system. Keywords: Substructure approach; STTF; STDSI; Base-isolated buildings; System identification

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Bayesian inference for calibration and validation of uniaxial reinforcing steel models

Birrell, M., Astroza, R., Restrepo, J.I., Loftizadeh, K., Carreño, R., Bazaez, R., and Hernandez, F. | Engineering Structures | 2021

With ever-advancing structural design and evaluation techniques becoming available for structural engineers, the required level of knowledge about nonlinear material behavior in civil structures has increased accordingly over recent years. In the context of finite element (FE) modeling, constitutive material models play a crucial role in the computation of the structural response. Although significant research has focused on characterizing the stress–strain relationship in reinforcing steel, most of these efforts have considered experimental response data from monotonic tests. In this paper, results from experimental cyclic tests conducted on 36 reinforcing steel coupons obtained from three major manufacturers encompassing two widely used steel grades are employed to gain a deep understanding of the relationship between model formulation and response, for three well-known hysteretic reinforcing steel one-dimensional constitutive stress–strain relationships. Initially, the three models are briefly described. Then, a local sensitivity analysis (LSA) is performed to provide an insight on the influence of each model parameter in model response, followed by a global sensitivity analysis (GSA) performed to further understand the composition of response variability due to parameter uncertainty. Model calibration is then carried out in a probabilistic manner, using the Bayesian estimation (BE) framework through the use of Markov Chain Monte Carlo (MCMC), and informed by LSA and GSA results. Parameter estimation results for each model are discussed, with an emphasis on the level of accuracy of predictions achieved with estimated sets of parameters in each case. The amount of information extracted about each parameter during calibration is assessed, leading to a performance comparison between the three constitutive laws under study. Keywords: Reinforcing steel; Constitutive models; Bayesian estimation; Sensitivity analysis

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Seismic response analysis and modal identification of a full-scale five-story base-isolated building tested on the [email protected] shake table

Astroza, R., Conte, J.P., Restrepo, J.I., Ebrahimian, H., and Hutchinson, T.C. | Engineering Structures | 2021

This paper presents the analysis of the seismic response and the identification of the dynamic properties of an equivalent linear time-invariant model of a full-scale five-story base-isolated reinforced concrete building tested on the unidirectional [email protected] shake table. A sequence of seven scaled historic earthquake records was applied by the shake table to the building, progressively increasing the seismic demand on the structure and its nonstructural components and systems. The effects of the isolation system on elongating the predominant period of the building, concentrating the displacement in the isolation layer, and augmenting the energy dissipation capacity of the building system are investigated. Low-amplitude white noise (WN) base excitation tests were conducted before and after each seismic test and ambient vibration (AV) data were recorded continuously for a period of approximately sixteen days containing the sequence of seven seismic tests performed. Because of the low intensity of the white noise base and ambient excitations, a quasi-linear response of the base-isolated building is assumed, allowing the modal parameters of an equivalent linear viscously damped time-invariant model to be estimated from vibration data recorded during the WN and AV tests. Different state-of-the-art system identification methods, including output-only and input-output methods, are used to estimate the modal properties of the base-isolated building. Results show that the identified modal parameters obtained from different methods are in good agreement and that the assumption of quasi-linear response for each low-amplitude test is appropriate. The effects of the amplitude of the excitation, earthquake input motions, and environmental conditions are clearly evidenced by the changes induced in the estimated modal parameters of the building. Keywords: System identification; Shake table test; Seismic test; Base isolation

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Bayesian parameter and joint probability distribution estimation for a hysteretic constitutive model of reinforcing steel

Birrell, M., Astroza, R., Carreño, R., Restrepo, J.I., and Araya-Letelier, G. | Structural Safety |2021

With the structural design paradigm shift since the early 2000′s from the traditional approach to performance-based design (PBD), there has been a growing need for reliable nonlinear finite element (FE) models that can accurately predict the response of structures when subjected to extreme loads, such as earthquakes. In the case of reinforced concrete (RC) structures, a proper representation of the hysteretic nonlinear behavior of reinforcing steel becomes crucial in order to carry out nonlinear time history analyses. The Giuffrè-Menegotto-Pinto (GMP) uniaxial steel constitutive law has been widely used by researchers and practitioners to model reinforcing steel bars. Despite the widespread in its implementation, a limited number of studies have proposed well-calibrated parameter values for this model. In addition, low identifiability of its governing parameters and the high cost of generating reliable experimental data have prevented a thorough probabilistic characterization of the GMP model parameters. Usually, only default parameter values from the early development of the model tend to be used. This paper uses experimental data from cyclic tests conducted on 36 reinforcing steel coupons manufactured in accordance to ASTM A615 and A706 Grade 60 reinforcing steel and proposes a joint probability density function (PDF) for the most influential parameters of the GMP material model. First, a local sensitivity analysis (LSA) is conducted to provide insight into the influence of each parameter in the model response. Also, global sensitivity analysis (GSA) is used to have a deep understanding of the composition of the variability in the model response due to parameter uncertainty and the level of interactions among parameters. The Bayesian approach is combined with the information obtained from GSA and LSA as input, to estimate model parameters and quantify the estimation uncertainties and propagate them to the material stress response. Uncertainty in model predictions obtained with the proposed PDF is assessed, and the impact of considering parameter correlations on the material response is investigated. Keywords: Bayesian estimation; Constitutive material model; Reinforcing steel; Sensitivity analysis

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Real-time thermal dynamic analysis of a house using RC models and joint state-parameter estimation

Li, Y., Castiglione, J., Astroza, R., and Chen, Y. | Building and Environment | 2021

To enable optimal building energy management in response to the ever-changing building and boundary conditions, it is critical to have numerical models that can provide accurate online prediction based on economically measurable inputs and feedback. The present study explores the capabilities of using the unscented Kalman filter (UKF) in combination with resistance-capacitance (RC) models for online estimation of the thermal dynamics of single detached houses. A joint state-parameter UKF estimation approach is applied to estimate unknown state and model parameters by using fictitious process equations to augment the state vector to include model parameters. The performance of this approach is evaluated by comparing the estimated state values to the monitored data. In addition, the prediction capability of the updated model is also investigated. The estimation procedure, mathematical operations, and result analysis are presented in detail. The remarkable model performance achieved shows that the UKF can efficiently improve RC models’ predictability and enable timely online model updating and response prediction. Keywords: Building thermal dynamics; RC models; State-parameter estimation; Unscented kalman filter; Real-time online prediction

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Bayesian parameter estimation of resistor-capacitor models for building thermal dynamics

Chen, Y., Castiglione, J., Astroza, R., and Li, Y. | Journal of Building Engineering | 2021

Accurate and computationally efficient building energy models are critical to the development of online or pseudo-online control strategies and other building management activities. However, such models need to overcome the large uncertainty involved with continuously changing occupant activities and building status. The present study uses unscented Kalman filtering (UKF) in the model parameter estimation for simple yet accurate resistor-capacitor (RC) models to develop reliable building energy models. The estimation procedure, mathematical operations, and other estimation enhancing techniques are presented in detail. Synthetic and measured data were used to validate and evaluate the methodology. The obtained model shows better performance when compared with a model that was calibrated using genetic algorithms in a previous study. This remarkable model performance shows that UKF can enable timely online model update and improve the model predictability.

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The role of moisture transport mechanisms on the performance of lightweight aggregates in internal curing

Paul A., Murgadas S., Delpiano J., Moreno-Casas P.M., Walczak M., Lopez M. | Construction and Building Materials | 2021

Internal curing (IC) of concrete by pre-wetted lightweight aggregate (LWA) is an established technology to assist cement hydration and reduce shrinkage and cracking in concrete. However, the current understanding in what makes a certain LWA effective for IC gives opportunities to improve the technique. The aim of this article is to identify the moisture transport mechanisms within an LWA that govern IC performance. Results on LWA of different internal structures (natural, manufactured), and different size distributions (fine, coarse), pre-soaked with either pure water or water containing shrinkage reducing admixtures (SRA), indicate that there are different mechanisms involved in water uptake and release: one controlled by capillary action, and one controlled by air diffusion into the pore water. It is concluded that it is the internal structure, geometry, and particle size distribution of the LWA that determine the effect of SRA and the overall LWA impact on the IC performance. By using 3D micro-CT images LWAs are studied in order to determine which characteristics (pore size, pore connectivity, pore distribution) are better suited for improving IC. This contribution to understanding water transport in LWAs may help to engineer the characteristics of LWA optimized for IC applications. Keywords: Porosity; Diffusion; Absorption; Desorption; CT scan; Internal curing; Lightweight aggregate

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The impact of gap dimensions on passengers boarding and alighting using different mobility aids at railway stations by laboratory experiments

Seriani, S.; Fernández, R.; Oyanedel, C. | International Journal of Rail Transportation | 2021

The main objective of the research is to study the impact generated by the dimensions of the horizontal (distance between the train and the platform) and vertical (height between the train and the platform) gap on passengers who use different mobility aids. The aim is to find standard dimensions in the design of the platform train interface, allowing an accessible boarding and alighting process for users with disabilities or reduced mobility. The method is based on experiments performed in a controlled environment at the Human Dynamics Laboratory (LDH) in Universidad de los Andes (Chile), through a mock-up configured with representative characteristics of a train and its adjacent platform. Using cameras arranged on the ceiling, the boarding and alighting process was registered according to a new accessibility level. The results allow obtaining scenarios with a ‘desirable gap’, as well as scenarios with inaccessible gaps. KEYWORDS: Passenger; mobility aid; platform train interface; design; vertical gap; horizontal gap; experiment; railway station

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Seismic Fragility Assessment of Chilean Skewed Highway Bridges.

Aldea, S., Bazáez, R., Astroza, R., Hernández, F. | Engineering Structures. 201: 109742 | 2021

The 2010 Maule, Chile earthquake demonstrated that many bridges were highly vulnerable to seismic demands. Among these bridges, skewed multi-span prestressed concrete girder bridges supported on non-anchored elastomeric bearings were the most vulnerable ones. After the 2010 Maule earthquake, several damaged skewed bridges were repaired and retrofitted using an updated seismic design criterion. Therefore, this study aims to compare the seismic performance of typical Chilean skewed highway bridges in their original design (prior to 2010) and in their repaired condition (post 2010). With this aim, three-dimensional (3D) nonlinear finite element models of four skewed bridges, which were damaged during the 2010 Maule earthquake, are developed and analyzed. Nonlinear static and incremental dynamic analyses (IDAs) are conducted, and fragility curves are obtained to evaluate the short-term evolution of the Chilean design practices. Additionally, the influence of the skew angle, vertical seismic bars, modelling assumptions and anchorage of elastomeric bearings, on the seismic performance of Chilean skewed highway bridges is analyzed through IDAs and fragility curves. The results of this study show that repair measures considered after the 2010 Maule earthquake improve the seismic performance of skewed bridges and effectively prevent span unseating. However, the adopted measures do not significantly improve the performance at slight to moderate damage states. It is also demonstrated that the skew angle and deck-abutment pounding have significant influence on the seismic performance. Finally, the results show that an adequate modelling of vertical elements, such as elastomeric bearings, must be considered to avoid underestimating displacement demands. Keyword: Skewed highway bridges; Seismic performance; Incremental dynamic analysis; Fragility curves

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Understanding the lateral dimension of traffic: Measuring and modeling lane discipline

Delpiano, R. | Transportation Research Record, 2675(12), 1030-1042. | 2021

There is growing interest in understanding the lateral dimension of traffic. This trend has been motivated by the detection of phenomena unexplained by traditional models and the emergence of new technologies. Previous attempts to address this dimension have focused on lane-changing and non-lane-based traffic. The literature on vehicles keeping their lanes has generally been limited to simple statistics on vehicle position while models assume vehicles stay perfectly centered. Previously the author developed a two-dimensional traffic model aiming to capture such behavior qualitatively. Still pending is a deeper, more accurate comprehension and modeling of the relationships between variables in both axes. The present paper is based on the Next Generation SIMulation (NGSIM) datasets. It was found that lateral position is highly dependent on the longitudinal position, a phenomenon consistent with data capture from multiple cameras. A methodology is proposed to alleviate this problem. It was also discovered that the standard deviation of lateral velocity grows with longitudinal velocity and that the average lateral position varies with longitudinal velocity by up to 8 cm, possibly reflecting greater caution in overtaking. Random walk models were proposed and calibrated to reproduce some of the characteristics measured. It was determined that drivers’ response is much more sensitive to the lateral velocity than to position. These results provide a basis for further advances in understanding the lateral dimension. It is hoped that such comprehension will facilitate the design of autonomous vehicle algorithms that are friendlier to both passengers and the occupants of surrounding vehicles.

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The influence of the density inside a train carriage on passenger boarding rate.

Luangboriboon, N.; Seriani, S.; Fujiyama, T. | International Journal of Rail Transportation, 9, 5. | 2021

Passenger alighting and boarding time is an important factor for crowded metros with high-frequency operations. Some operators leave the train doors open until the last passenger boards or passengers voluntarily stop boarding, while others regulate the boarding process. To evaluate whether it is effective to regulate the passenger while boarding or not, this research explores how the density inside the train would influence the passenger boarding rate by conducting a laboratory experiment. The results showed that the passenger boarding rate increased as the density increased, up to approximately 2.5–3.0 passengers/m2. Beyond that point, our results suggested that the boarding rate may have decreased, but the evidence was not conclusive. It is deduced that, under the experimented density (up to around 5 passengers/m2), the density does not have any apparent negative effects on the boarding rate, which implies that there is no strong evidence to recommend passenger boarding regulation. KEYWORDS: Train passenger; density; boarding rate; experiment

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Study of the Space Occupied by a Wheelchair User at Metro de Santiago Platforms by Laboratory Experiments.

Valdivieso, J.; Seriani, S. | Journal of Advanced Transportation. | 2021

The objective is to study the space a wheelchair passenger would use in the preferential waiting areas of an urban railway platform. For this purpose, an analysis of the variables that interfere in the space occupied by a wheelchair user was carried out at Metro de Santiago platforms, to design a preferential prototype waiting area at the Human Dynamics Laboratory of the Universidad de los Andes (Chile). The prototype has a 3.0 m long and 2.5 m wide carriage, together with a preferential waiting area on the platform of the same length as the carriage, and 2.0 m wide. With this prototype defined, a detection method was developed using PeTrack software, to accurately identify the limits of the space occupied by a wheelchair user under two scenarios of different density levels in the preferential waiting area: medium-density (1.5 passengers/m2) and high-density (4.0 passengers/m2). It was observed that the space occupied by a wheelchair user decreased by 33% as the density increased from medium to high. On the other hand, for a high-density level, the space occupied by a wheelchair user was found to be 61% higher than that occupied by a passenger without reduced mobility. This variation occurred mainly because passengers increased their distance from the wheelchair user, which widened their area of influence. Further experiments are proposed as future research to extend this analysis using other density situations.

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Biopolymer-waste fiber reinforcement for earthen materials: capillarity, mechanical, impact and abrasion performance

Gonzalez-Calderon, H., Araya-Letelier, G., Kunze, S., Burbano-Garcia, C., Reidel, U., Sandoval, C., Astroza, R., and Bas, F. | Polymers, 12(8), 1819 | 2020

The poultry industry, highly prevalent worldwide, generates approximately 7.7 × 106 metric tons of chicken feathers (CFs), which become a major environmental challenge due to their disposal when considered waste or due to their energy transformation consumption when considered by-products. CFs are mainly composed of keratin (approximately 90%), which is one of the most important biopolymers whose inherent characteristics make CFs suitable as biopolymer fibers (BPFs). This paper first assesses the morphological and chemical characteristics of these BPFs, through scanning electron microscopy and energy dispersive X-ray spectroscopy, and then evaluates the waste valorization of these BPFs as a sustainable alternative for fiber-reinforcement of earthen mixes intended for earthen construction, such as adobe masonry, rammed earth, and earthen plasters. In particular, four earthen mixes with increasing doses of BPFs (i.e., 0%, 0.25%, 0.5%, and 1% of BPFs by weight of soil) were developed to evaluate the impact of BPF-reinforcement on the capillary, mechanical, impact, and abrasion performance of these earthen mixes. The addition of BPFs did not significantly affect the mechanical performance of earthen mixes, and their incorporation had a statistically significant positive effect on the impact performance and abrasion resistance of earthen mixes as the BPF dose increased. On the other hand, the addition of BPFs increased the capillary water absorption rate, possibly due to a detected increment in porosity, which might reduce the durability of water-exposed BPF-reinforced earthen mixes, but a statistically significant increment only occurred when the highest BPF dose was used (1%). Keywords: biopolymer fiber; waste chicken feathers; fiber-reinforced earthen mixes; capillarity; impact strength; abrasion resistance

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Auto-regressive model based input and parameter estimation for nonlinear finite element models

Castiglione, J.; Astroza, R.; Eftekhar Azam, S.; Linzell, D. | Mechanical Systems and Signal Processing, Mechanical Systems and Signal Processing, 143, 106779 | 2020

A novel framework to accurately estimate nonlinear structural model parameters and unknown external inputs (i.e., loads) using sparse sensor networks is proposed and validated. The framework assumes a time-varying auto-regressive (TAR) model for unknown loads and develops a strategy to simultaneously estimate those loads and parameters of the nonlinear model using an unscented Kalman filter (UKF). First, it is confirmed that a Kalman filter (KF) allows to estimate TAR parameters for a measured, earthquake, acceleration time-history. The KF-based framework is then coupled to an UKF to jointly identify unmeasured inputs and nonlinear finite element (FE) model parameters. The proposed approach systematically assimilates different structural response quantities to estimate TAR and FE model parameters and, as a result, updates the FE model and unknown external excitation estimates. The framework is validated using simulated experiments on a realistic three-dimensional nonlinear steel frame subjected to unknown seismic ground motion. It is demonstrated that assuming relatively low order TAR model for the unknown input leads to precise reconstruction and unbiased estimation of nonlinear model parameters that are most sensitive to measured system response. Keywords

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Adaptive Kalman filters for nonlinear finite element model updating

Song, M.; Astroza, R.; Ebrahimian, H.; Papadimitriou, C.; Moaveni, B | Mechanical Systems and Signal Processing, 143, 106837 | 2020

This paper presents two adaptive Kalman filters (KFs) for nonlinear model updating where, in addition to nonlinear model parameters, the covariance matrix of measurement noise is estimated recursively in a near online manner. Two adaptive KF approaches are formulated based on the forgetting factor and the moving window covariance-matching techniques using residuals. Although the proposed adaptive methods are integrated with the unscented KF (UKF) for nonlinear model updating in this paper, they can be alternatively combined with other types of nonlinear KFs such as the extended KF (EKF) or the ensemble KF (EnKF). The performance of the proposed methods is investigated through two numerical applications and compared to that of a non-adaptive UKF and an existing dual adaptive filter. The first application considers a nonlinear steel pier where nonlinear material properties are selected as updating parameters. Significant improvements in parameter estimation results are observed when using adaptive filters compared to the non-adaptive approach. Furthermore, the covariance matrix of simulated measurement noise is estimated from the adaptive approaches with acceptable accuracy. Effects of different types of modeling errors are studied in the second numerical application of a nonlinear 3-story 3-bay steel frame structure. Similarly, more accurate and robust parameter estimations and response predictions are obtained from the adaptive approaches compared to the non-adaptive approach. The results verify the effectiveness and robustness of the proposed adaptive filters. The forgetting factor and moving window methods are shown to have a simpler tuning process compared to the dual adaptive method while providing similar performance.Keywords: Adaptive Kalman filter; Nonlinear model updating; System identification; Unscented Kalman filter; Modeling errors; Covariance-matching technique

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Memory-enhanced plasticity modelling of sand behaviour under undrained cyclic loading

Haoyuan Liu, Andrea Diambra, José Antonio Abell, Federico Pisanò. | Journal of Geotech. and Geoenvironmental Eng. | 2020

This work presents a critical state plasticity model for predicting the response of sands to cyclic loading. The well-known bounding surface SANISAND framework by Dafalias and Manzari is enhanced with a memory surface to capture micromechanical, fabric-related processes directly affecting cyclic sand behavior. The resulting model, SANISAND-MS, was recently proposed by Liu et al. and successfully applied to the simulation of drained sand ratcheting under thousands of loading cycles. Herein, novel ingredients are embedded into Liu et al.’s formulation to better capture the effects of fabric evolution history on sand stiffness and dilatancy. The new features enable remarkable accuracy in simulating undrained pore pressure buildup and cyclic mobility behavior in medium-dense to dense sand. The performance of the upgraded SANISAND-MS is validated against experimental test results from the literature—including undrained cyclic triaxial tests at varying cyclic loading conditions and precyclic consolidation histories. The proposed modeling platform will positively impact the study of relevant cyclic and dynamic problems, for instance, in the fields of earthquake and offshore geotechnics.

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Bayesian parameter estimation of resistor-capacitor models for building thermal dynamics

Chen, Y., Castiglione, J., Astroza, R., and Li, Y. | Journal of Building Engineering | 2020

Accurate and computationally efficient building energy models are critical to the development of online or pseudo-online control strategies and other building management activities. However, such models need to overcome the large uncertainty involved with continuously changing occupant activities and building status. The present study uses unscented Kalman filtering (UKF) in the model parameter estimation for simple yet accurate resistor-capacitor (RC) models to develop reliable building energy models. The estimation procedure, mathematical operations, and other estimation enhancing techniques are presented in detail. Synthetic and measured data were used to validate and evaluate the methodology. The obtained model shows better performance when compared with a model that was calibrated using genetic algorithms in a previous study. This remarkable model performance shows that UKF can enable timely online model update and improve the model predictability.

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Flue Gas Desulfurization (FGD) Fly Ash as a Sustainable, Safe Alternative for Cement-Based Materials

Navarrete, I.; Vargas, F.; Martinez, P.; Paul, A.; Lopez, M. | Journal of Cleaner Production | 2020

The reduction in fly ash production in coal-fired power plants has created an opportunity to explore alternative types of fly ashes previously deemed unfit for use in concrete. In plants using flue gas desulfurization (FGD) processes, fly ash could contain high amounts of sulfur oxides, making its use in concrete inadvisable. However, the type of sulfur compound present in a fly ash strongly impacts its performance in concrete. In this study, two types of fly ash were used to evaluate the effect of sulfur oxides on mortar mixtures incorporating fly ash as supplementary cementitious material (SCM); one from an FGD unit, with high sulfur oxide content (in the form of hannebachite), and the other generated in a system without FGD, with negligible sulfur oxide. Calorimetry results show that hannebachite can effectively control C3A hydration similar to gypsum; however, its presence in FGD fly ash does not induce deleterious expansion associated with internal sulfate attack in mortars. TGA and XRD analyses suggest that hannebachite has lower reactivity than sulfate. Hannebachite not only maintains the pozzolanic reactivity of the fly ash, but its fineness may promote OPC hydration, increasing compressive strength. The results of this study indicate that FGD fly ash can be used as an SCM, allowing more sustainable concrete production.

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Detecting, Tracking and Counting People Getting On/Off a Metropolitan Train Using a Standard Video Camera

Velastin, S.A.; Fernández, R.; Espinosa, J.E.; Bay. A. | Sensors | 2020

The main source of delays in public transport systems (buses, trams, metros, railways) takes place in their stations. For example, a public transport vehicle can travel at 60 km per hour between stations, but its commercial speed (average en-route speed, including any intermediate delay) does not reach more than half of that value. Therefore, the problem that public transport operators must solve is how to reduce the delay in stations. From the perspective of transport engineering, there are several ways to approach this issue, from the design of infrastructure and vehicles to passenger traffic management. The tools normally available to traffic engineers are analytical models, microscopic traffic simulation, and, ultimately, real-scale laboratory experiments. In any case, the data that are required are number of passengers that get on and off from the vehicles, as well as the number of passengers waiting on platforms. Traditionally, such data has been collected manually by field counts or through videos that are then processed by hand. On the other hand, public transport networks, specially metropolitan railways, have an extensive monitoring infrastructure based on standard video cameras. Traditionally, these are observed manually or with very basic signal processing support, so there is significant scope for improving data capture and for automating the analysis of site usage, safety, and surveillance. This article shows a way of collecting and analyzing the data needed to feed both traffic models and analyze laboratory experimentation, exploiting recent intelligent sensing approaches. The paper presents a new public video dataset gathered using real-scale laboratory recordings. Part of this dataset has been annotated by hand, marking up head locations to provide a ground-truth on which to train and evaluate deep learning detection and tracking algorithms. Tracking outputs are then used to count people getting on and off, achieving a mean accuracy of 92% with less than 0.15% standard deviation on 322 mostly unseen dataset video sequences.

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Output-only nonlinear finite element model updating using autoregressive process

Castiglione, J., Astroza, R., Eftekhar Azam, S., and Linzell, D. | Chapter 9 in Model Validation and Uncertainty Quantification, Vol. 3, Springer | 2020

A novel approach to deal with nonlinear system identification of civil structures subjected to unmeasured excitations is presented. Using only sparse global dynamic structural response, mechanics-based nonlinear finite element (FE) model parameters and unmeasured inputs are estimated. Unmeasured inputs are represented by a time-varying autoregressive (TAR) model. Unknown FE model parameters and TAR model parameters are jointly estimated using an unscented Kalman filter. The proposed method is validated using numerically simulated data from a 3D steel frame subjected to seismic base excitation. Six material parameters and one component of the base excitation are considered as unknowns. Excellent input and model parameter estimations are obtained, even for low order TAR models. Keywords: Model updating; Input estimation; Finite element model; Kalman filter; Auto-regressive model

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Bayesian nonlinear finite element model updating of a full-scale bridge-column using sequential Monte Carlo

Ramancha, M.K., Astroza, R., Conte, J.P., Restrepo, J.I., and Todd, M.D. | Chapter 43 in Model Validation and Uncertainty Quantification, Vol. 3, Springer | 2020

Digital twin-based approaches for structural health monitoring (SHM) and damage prognosis (DP) are emerging as a powerful framework for intelligent maintenance of civil structures and infrastructure systems. Model updating of nonlinear mechanics-based Finite Element (FE) models using input and output measurement data with advanced Bayesian inference methods is an effective way of constructing a digital twin. In this regard, the nonlinear FE model updating of a full-scale reinforced-concrete bridge column subjected to seismic excitations applied by a large shake table is considered in this paper. This bridge column, designed according to US seismic design provisions, was tested on the [email protected] Large High-Performance Outdoor Shake Table (LHPOST). The column was subjected to a sequence of ten recorded earthquake ground motions and was densely instrumented with an array of 278 sensors consisting of strain gauges, linear and string potentiometers, accelerometers and Global Positioning System (GPS) based displacement sensors to measure local and global responses during testing. This heterogeneous dataset is used to estimate/update the material and damping parameters of the developed mechanics-based distributed plasticity FE model of the bridge column. The sequential Monte Carlo (SMC) method (set of advanced simulation-based Bayesian inference methods) is used herein for the model updating process. The inherent architecture of SMC methods allows for parallel model evaluations, which is ideal for updating computationally expensive models.

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On the performance of unscented Kalman filter in parameter estimation of nonlinear finite element models

Astroza, R. and Barrientos, N. | Chapter 39 in Experimental Vibration Analysis for Civil Structures, CRC Press | 2020

This paper describes a framework to update nonlinear finite element (FE) models. The method combines advanced mechanics-based nonlinear FE models and the Unscented Kalman filter (UKF) to estimate unknown time-invariant model parameters of FE models of civil structures subjected to earthquake excitation. The performance and computational cost of different unscented transformations (UTs) are examined in this paper, and the standard and square-root formulations of the filter are also investigated. A two-dimensional, 3-story, 3-bay steel moment frame with eight unknown parameters is used as application example. The steel frame is modeled using fiber-section beam-column elements with distributed plasticity and is subjected to a ground motion recorded during the 1989 Loma Prieta earthquake. The results indicate that most of the UKFs provide accurate estimates of the model parameters but significant differences in the computational cost are observed.

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Nonlinear model updating using recursive and batch bayesian methods

Song, M., Astroza, R., Ebrahimian, H., Moaveni, B., and Papadimitriou, C. | Chapter 31 in Model Validation and Uncertainty Quantification, Vol. 3, Springer | 2020

This paper studies the performance of recursive and batch Bayesian methods for nonlinear model updating. Unscented Kalman filter (UKF) is selected to represent the recursive Bayesian method, and two UKF approaches are investigated and compared, i.e., non-adaptive UKF and adaptive UKF. The proposed new adaptive filter, forgetting factor adaptive UKF, estimates the model parameters and measurement noise covariance in an online manner. The forgetting factor adaptive UKF is based on the principle of matching the covariance of residuals to its theoretical values by updating the measurement noise covariance. The performance of non-adaptive UKF, adaptive UKF and batch Bayesian method are investigated when applied to a numerical nonlinear 3-story 3-bay steel frame structure for parameter estimation of material properties. Different types of modeling errors are considered in the 21 updating models to study the effects of modeling errors on model updating. It is found that adaptive UKF approach provides the most accurate parameter estimations, while batch Bayesian approach gives the smallest errors on response predictions.

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Non-unique estimates in material parameter identification of nonlinear FE models governed by multiaxial material models using unscented Kalman filtering

Ramancha, M.K.; Madarshahian, R.; Astroza, R.; Conte, J.P | Chapter 29 in Model Validation and Uncertainty Quantification, Vol. 3, Springer (ISBN 978-3-030-12075-7) | 2020

Bayesian nonlinear finite element (FE) model updating using input and output measurements have emerged as a powerful technique for structural health monitoring (SHM), and damage diagnosis and prognosis of complex civil engineering systems. The Bayesian approach to model updating is attractive because it provides a rigorous framework to account for and quantify modeling and parameter uncertainty. This paper employs the unscented Kalman filter (UKF), an advanced nonlinear Bayesian filtering method, to update, using noisy input and output measurement data, a nonlinear FE model governed by a multiaxial material constitutive law. Compared to uniaxial material constitutive models, multiaxial models are typically characterized by a larger number of material parameters, thus requiring parameter estimation to be performed in a higher dimensional space. In this work, the UKF is applied to a plane strain FE model of Pine Flat dam (a concrete gravity dam on King’s River near Fresno, California) to update the time-invariant material parameters of the cap plasticity model, a three-dimensional non-smooth multi-surface plasticity concrete model, used to represent plain concrete behavior. This study considers seismic input excitation and utilizes numerically simulated measurement response data. Estimates of the multi-axial material model parameters (for the single material model used in this study) are non-unique. All sets of parameter estimates yield very similar and accurate seismic response predictions of both measured and unmeasured response quantities. Keywords: Non-unique estimates; Bayesian parameter estimation; Unscented Kalman filter; Nonlinear FE model; Cap plasticity model; Concrete gravity dams

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Finite element model updating accounting for modeling uncertainty

Astroza, R.; Alessandri, A.; Conte, J.P. | Chapter 24 in Model Validation and Uncertainty Quantification, Vol. 3, Springer (ISBN 978-3-030-12075-7) | 2020

A novel approach to deal with modeling uncertainty when updating mechanics-based finite element (FE) models is presented. In this method, a dual adaptive filtering approach is adopted, where the Unscented Kalman filter (UKF) is used to estimate the unknown parameters of the nonlinear FE model and a linear Kalman filter (KF) is employed to estimate the diagonal terms of the covariance matrix of the simulation error vector based on a covariance-matching technique. Numerically simulated response data of a two-dimensional three-story three-bay steel frame structure with eight unknown material model parameters subjected to seismic base excitation is employed to illustrate and validate the proposed methodology. The results of the validation studies show that the proposed approach significantly outperforms the parameter-only estimation approach widely investigated and used in the literature.

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System identification of a five-story building using seismic strong-motion data

Astroza, R.; Hernández, F.; Díaz, P.; Gutiérrez, G. | Chapter 24 in Dynamics of Civil Structures, Vol. 2, Springer (ISBN 978-3-030-12115-0) | 2020

A full scale five-story reinforced concrete building was built and tested on the Large High Performance Outdoor Shake Table (LHPOST) at the University of California, San Diego in 2012. The main objective of the test program was to study the seismic response of the structure and the nonstructural components (NSCs) and their dynamic interaction at different levels of seismic excitation. The building specimen was first tested base-isolated and then fixed at its base. In the fixed-base configuration, a suite of six earthquake motions of various intensities was applied to the building to progressively increase the seismic demand. In this paper, the modal parameters of the fixed-base building are identified using the input-output dynamic data recorded during the seismic tests. The deterministic-stochastic subspace identification method (DSI) is employed to estimate the variations of the modal properties of the building during the seismic tests by employing a short-time windowing approach. The changes of the modal parameters during the seismic motions are tracked, analyzed, and compared to those previously obtained from ambient vibrations and low-amplitude white noise base excitation tests. The variation of the identified natural frequencies and equivalent damping ratios of the building changed with the intensity of the input motions and damage in the structure, while the mode shapes are found to be insensitive to them.

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Experimental system and damage identification of small-scale wind turbine blades

Gutiérrez, J.M., Astroza, R., Abell, J., Soto, C., Jaramillo, F., Guarini, M., and Orchard, M. | Chapter 23 in Experimental Vibration Analysis for Civil Structures, CRC Press | 2020

Blades are one of the main and more costly components of wind turbines and, besides, are difficult to inspect and maintain. Due to operational conditions, wind turbine blades (WTBs) are prone to suffer structural damage, chiefly because of fatigue or extreme loading. Therefore, it is crucial to monitor the state of health (SoH) of these components by implementing robust damage diagnosis and prognosis methods, for identifying the damage and estimating the remaining useful life (RUL), respectively. To study the degradation effects due to fatigue and extreme loads on WTBs, a testing system for small-scale blades was designed and built. The testing machine is able to induce sinusoidal loading with varying amplitude and frequency, then generating damage caused by repetitive loads. Test protocols consisting of extreme (close to resonance) and fatigue-type loading were designed to progressively damage the WTBs, and impact and pull-back tests were conducted at different stages of damage. The free vibration response data measured by an accelerometer array during impact tests is used to identify the modal properties of the blades using an output-only system identification algorithm. The variations of the identified modal properties are then correlated to the physical damage using modal-based damage indices.

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Calibration of a large nonlinear finite element model of a highway bridge with many uncertain parameters

Astroza, R.; Barrientos, N.; Li, Y.; Saavedra Flores, E. | Chapter 20 in Model Validation and Uncertainty Quantification, Vol. 3, Springer (ISBN 978-3-030-12075-7). | 2020

Finite element (FE) model updating has emerged as a powerful technique for structural health monitoring (SHM) and damage identification (DID) of civil structures. Updating mechanics-based nonlinear FE models allows for a complete and comprehensive damage diagnosis of large and complex structures. Recursive Bayesian estimation methods, such as the Unscented Kalman filter (UKF), have been used to update nonlinear FE models of civil structures; however, their use have been limited to models with a relatively low number of degrees of freedom and with a limited number of unknown model parameters, because it is otherwise impractical for computationally demanding models with many uncertain parameters. In this paper, a FE model of the Marga-Marga bridge, an eight-span seismically-isolated bridge located in Viña del Mar-Chile, is updated based on numerically simulated response data. Initially, 95 model parameters are considered unknown, and then, based on a simplified sensitivity analysis, a total of 27 model parameters are considered in the estimation. Different measurement sets, including absolute accelerations, relative displacements, strains, and shear deformations of the isolators, are analyzed to investigate the effects of considering heterogeneous responses on the estimation results. In addition, a non-recursive estimation procedure is presented and its effectiveness in reducing the computational cost, while maintaining accuracy and robustness in the estimation, is demonstrated. Keywords: Model updating; Nonlinear finite element model; Parameter estimation; High-dimensional parameter space

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Real-time thermal dynamic analysis of a house using RC models and joint state-parameter estimation

Li, Y., Castiglione, J., Astroza, R., and Chen, Y. | Building and Environment | 2020

To enable optimal building energy management in response to the ever-changing building and boundary conditions, it is critical to have numerical models that can provide accurate online prediction based on economically measurable inputs and feedback. The present study explores the capabilities of using the unscented Kalman filter (UKF) in combination with resistance-capacitance (RC) models for online estimation of the thermal dynamics of single detached houses. A joint state-parameter UKF estimation approach is applied to estimate unknown state and model parameters by using fictitious process equations to augment the state vector to include model parameters. The performance of this approach is evaluated by comparing the estimated state values to the monitored data. In addition, the prediction capability of the updated model is also investigated. The estimation procedure, mathematical operations, and result analysis are presented in detail. The remarkable model performance achieved shows that the UKF can efficiently improve RC models’ predictability and enable timely online model updating and response prediction. Keywords: Building thermal dynamics; RC models; State-parameter estimation; Unscented kalman filter; Real-time online prediction

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A two-dimensional traffic model for two-dimensional traffic flow problems

Delpiano, R.; Herrera, J.C.; Laval, J.; Coeymans, J.E. | Transportation Research Part C: Emerging Technologies 53, 76-92. | 2020

This paper proposes a two-dimensional car-following model to tackle traffic flow problems where considering continuum lateral distances enables a simpler or more natural mathematical formulation compared to traditional car-following models. These problems include (i) the effects of lateral friction often observed in HOV lanes and diverge bottlenecks, (ii) the relaxation phenomenon at merge bottlenecks, (iii) the occurrence of accidents due to lane changing, and (iv) traffic models for autonomous vehicles (AVs). We conjecture that traditional car-following models, where the lateral dimension is discretized into lanes, struggle with these problems and one has to resort to ad-hoc rules conceived to directly achieve the desired effect, and that are difficult to validate.


Uncertainty quantification and propagation in the modeling of liquefiable sands

Mercado, V.; Ochoa, F.; Astroza, R.; El-Sekelly, W.; Abdoun, T.; Pastén, C.; Hernández, F. | Soil Dynamics and Earthquake Engineering, 123, 217-229. | 2019

We argue that the distance maintained by drivers in order to avoid collisions in all directions plays a fundamental role in all these problems. To test this hypothesis, we propose a simple two-dimensional microscopic car-following model based on the social force paradigm, and build simulation experiments that reproduce these phenomena. These phenomena are reproduced as an indirect consequence of the model’s formulation, as opposed to ad-hoc rules, thus shedding light on their causes. A better understanding of the behavior of human drivers in the lateral dimension can be translated to improving autonomous driving algorithms so that they are human-friendly. In addition, since AV technology is proprietary, we argue that the proposed model should provide a good starting point for building AV traffic flow models when real data becomes available, as these data come from sensors that cover two-dimensional regions. Keywords: Traffic flow theory; Microscopic traffic models; Car following; Social forces; Two-dimensional traffic; Relaxation phenomenon

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The role of composition in the structure and water-binding in alkali-silica reaction sol and gel.

Rashidi, M.; Paul, A.; Do, C.; Kurtis, M. | Cement and Concrete Research. 124: 1058145 | 2019

The discrepancy between alkali cation (Na+) used in accelerated assessments of potential alkali-silica reactivity (ASR) and those predominant in portland cements (larger amounts of K+ than Na+) leads to questions regarding the reliability of standardized test methods to predict concrete field performance. To better understand the role of alkali cation type in ASR, this study investigates the influence of alkali cation type on the structure and water-binding ability of ASR sols and gels of varying composition. Results obtained by small-angle neutron scattering, 1H NMR relaxometry, and rheological measurements indicate the formation of densified agglomerate structures with increasing silica-to-alkali molar mass ratios (S/A). However, Na-based sols exhibit a greater tendency to agglomerate and a higher dynamic viscosity than K-based ones. Furthermore, at high S/A, 1H NMR relaxometry shows the greater ability of K-based gels to bind water, suggesting the better dispersion of siliceous structures and the development of finer porosities. Keywords: Characterization (B); Amorphous material (B); Alkali-aggregate reaction (C); Rheology (A); Small-angle neutron scattering

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Shear bond behaviour of elemental composite beams with different configurations.

Sheeta, I.;Ahmed, S.; Avudaiappan, S.; ESaavedra, E.; Chandra, Y.; Astroza, R. | Engineering Structures. 201: 109742 | 2019

In this study, an experimental program for testing steel concrete composite slabs subjected to symmetrical double line loads has been carried out to investigate the longitudinal shear bond behaviour. Different configurations of steel concrete composite slabs with and without embossments were studied. The flexural characteristics, ultimate strength and bond strength (end slip test) of composite slabs were determined. Partial connection (PC) approach was used to predict the longitudinal shear bond. The embossments in the profile decks slightly enhanced the longitudinal shear resistance and load carrying capacity (especially, at the end of the plastic stage), and also delayed debonding. Two failure modes, brittle and ductile phases, were observed during the tests. The experimental results demonstrated that the embossments do not have promising contributions to longitudinal shear strength and ductility of the composite slab elements, especially to elastic and plastic behaviour stages prior to the ultimate load carrying capacity. This study proposes a semi empirical formula (SEF) to evaluate the shear stress using simplification of the m-k method. The proposed SEF method was validated with data obtained from literature, showing an acceptable level of reliability and therefore, it could represent a good alternative for m-k and PC methods. Keywords: Composite profile deck; Embossments; Shear-bond; Semi empirical method

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Predicting Wave‐Induced Sediment Resuspension at the Perimeter of Lakes Using a Steady‐State Spectral Wave Model.

Roberts, D. C. ; Moreno‐Casas, P.; Bombardelli, F. A.; Hook, S. J.; Hargreaves, B. R.; Schladow, S. G. | Water Resources Research. 55(2): 1279-1295. | 2019

A steady-state spectral wave model, STWAVE, is evaluated as a tool for predicting wave-induced sediment resuspension in lake littoral zones. Steady-state wave height and bed-shear stress estimates are tested against 2 years of high-frequency wave height and turbidity data from six littoral measurement stations in Lake Tahoe. Average wave and sediment resuspension response to a broad range of wind conditions are well captured by the model. Despite steady-state assumptions, the model reproduces patterns in wave height and sediment resuspension under time-varying wind conditions at sites with different wave exposure. Model results are insensitive to the measurement location of wind data input among six offshore meteorological buoys. Uniform and variable wind field assumptions yield similar resuspension predictions. Results representing the steady-state response to spatially uniform wind speed-direction combinations enable output from a single set of model runs to serve as a reasonable static reference for hindcasting and predicting wave resuspension patterns. This obviates the need for repeated model runs, making STWAVE output an efficient tool for exploring long-term spatio-temporal patterns in nearshore wave forcing. Application of this tool is limited by wave height overprediction for short fetches and presumably by the validity of uniform wind field assumptions over very long fetches. Applied successfully at Lake Tahoe, we find that the north and east shores, exposed to the prevailing southwesterly winds, see resuspension conditions upward of 3,000 hr/year, while the south and west shores typically see less than 500. Location-specific resuspension hours can vary by upward of ±200 hr/year due to shifting interannual wind patterns.

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Performance comparison of Kalman-based filters for nonlinear structural finite element model updating.

Astroza, R.; Ebrahimian, H.; Conte, J. | Journal of Sound and Vibration. 438: 520- 542. | 2019

Finite element (FE) model updating has emerged as a powerful technique for structural health monitoring and damage identification of civil structures. Updating mechanics-based nonlinear FE models allows for a complete and comprehensive damage diagnosis of large and complex structures, but it is computationally demanding. This paper first introduces an Iterated Extended Kalman filter (IEKF) to update mechanics-based nonlinear FE models of civil structures. Different model updating techniques using the Extended Kalman filter (EKF), Unscented Kalman Filter (UKF) and IEKF, are then compared for their performance in terms of convergence, accuracy, robustness, and computational demand. Finally, a non-recursive estimation procedure is presented and its effectiveness in reducing the computational cost, while maintaining accuracy and robustness, is demonstrated. An application example is presented based on numerically simulated response data for a three-dimensional 5-story 2-by-1 bay reinforced concrete (RC) frame building subjected to bi-directional earthquake excitation. Excellent estimation results are obtained with the EKF, UKF, and IEKF used in conjunction with the proposed non-recursive estimation approach. Because of the analytical linearization used in the EKF and IEKF, abrupt and large jumps in the estimates of the model parameters are observed with these filters, which may lead to divergence of the nonlinear FE model solution procedure. The UKF slightly outperforms the EKF and IEKF, but at a higher computational cost. Keywords: Nonlinear finite element model; Parameter estimation; Kalman-based filter; Damage identification

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Modelling the cyclic ratcheting of sands through memory-enhanced bounding surface plasticity.

Liu, H.Y.; Abell, J.A. ; Diambra F., A.; Pisano, F. | Géotechnique. 69(9):783-800. (2019). | 2019

The modelling and simulation of cyclic sand ratcheting is tackled via a plasticity model formulated withinthe well-known critical state, bounding surface SANISAND framework. For this purpose, a third locus –termed ‘memory surface’ – is cast into the constitutive formulation, so as to phenomenologically capturemicro-mechanical, fabric-related processes directly relevant to the cyclic response. The predictive capabilityof the model under numerous loading cycles (‘high-cyclic’ loading) is explored with focus on drainedloading conditions, and validated against experimental test results from the literature – including triaxial,simple shear and oedometer cyclic loading. The model proves capable of reproducing the transition fromratcheting to shakedown response, in combination with a single set of soil parameters for different initial,boundary and loading conditions. This work contributes to the analysis of soil-structure interaction underhigh-cyclic loading events, such as those induced by environmental and/or traffic loads. KEYWORDS: sands, stiffness, constitutive relations, plasticity, numerical modelling, offshore engineering

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Modelling the distribution of passengers waiting to board the train at metro stations

Seriani, S.; Fujiyama, T. | Journal of Rail Transport Planning & Management | 2019

No Posee Abstract

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Generalized algorithms for particle motion and collision with streambeds.

Moreno-Casas, P.; Bombardelli, F.; Toro, J. | International Journal of Sediment Research. 34: 295-306. | 2019

Recent theoretical and numerical models for the motion of saltating particles close to stream beds are constituted of three sub-models: a) a set of equations describing the particle “free flight”, b) a sub-model to calculate the post-collision particle velocity, and c) a mathematical representation of the bed roughness. In this paper, a comprehensive three-dimensional (3-D), theoretical/numerical model for bed-load motion at large Reynolds numbers is presented. By using geometric considerations and stochastic parameters to characterize collisions with the wall, five new sub-models for representation of bed roughness are, for the first time to the best of our knowledge, proposed and implemented. The emphasis of this paper is on the particle model, for which Basset, Magnus, drag, submerged weight, virtual mass, and lift forces are included. For the range of particle sizes (sands) analyzed herein, it is found that the stream-wise contribution of the Basset force, compared to other forces, may be as large as 60%. Whereas in the wall-normal direction, the Basset force is equ