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Allende-Cid, H., Canessa, E., Quezada, A., & Allende, H. (2011). An Improved Fuzzy Rule-Based Automated Trading Agent. Stud. Inform. Control, 20(2), 135–142.
Abstract: In this paper an improved Fuzzy Rule-Based Trading Agent is presented. The proposal consists in adding machine-learning-based methods to improve the overall performance of an automated agent that trades in futures markets. The modified Fuzzy Rule-Based Trading Agent has to decide whether to buy or sell goods, based on the spot and futures time series, gaining a profit from the price speculation. The proposal consists first in changing the membership functions of the fuzzy inference model (Gaussian and Sigmoidal, instead of triangular and trapezoidal). Then using the NFAR (Neuro-Fuzzy Autoregressive) model the relevant lags of the time series are detected, and finally a fuzzy inference system (Self-Organizing Neuro-Fuzzy Inference System) is implemented to aid the decision making process of the agent. Experimental results demonstrate that with the addition of these techniques, the improved agent considerably outperforms the original one.
Keywords: Automated Trading Agents; Fuzzy Rule-based Agents
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Alvarenga, T. C., De Lima, R. R., Simao, S. D., Junior, L. C. B., Bueno, J. S. D., Alvarenga, R. R., et al. (2022). Ensemble of hybrid Bayesian networks for predicting the AMEn of broiler feedstuffs. Comput. Electron. Agric., 198, 107067.
Abstract: To adequately meet the nutritional needs of broilers, it is necessary to know the values of apparent metabolizable energy corrected by the nitrogen balance (AMEn) of the feedstuffs. To determine AMEn values, biological assays, feedstuff composition tables, or prediction equations are used as a function of the chemical composition of feedstuffs, the latter using statistical methodologies such as multiple linear regression, neural networks, and Bayesian networks (BN). BN is a statistical and computational methodology that consists of graphical (graph) and probabilistic models of quantitative and/or qualitative variables. Ensembles of BN in the area of broiler nutrition are expected, as there is no research showing their AMEn prediction performance. The purpose of this article is to propose and use ensembles of hybrid Bayesian networks (EHBNs) and obtain prediction equations for the AMEn of feedstuffs used in broiler nutrition from their chemical compositions. We trained 100, 1,000, and 10,000 EHBN, and in this way, empirical distributions were found for the coefficients of the covariates (crude protein, ether extract, mineral matter, and crude fiber). Thus, the mean, median, and mode of these distributions were calculated to build prediction equations for AMEn. It is observed that the method for obtaining the coefficients of the covariates discussed in this article is an unprecedented proposal in the field of broiler nutrition. The data used to obtain the equations were obtained by meta-analysis, and the data for the validation of the equations were obtained from metabolic tests. The proposed equations were evaluated by precision measures such as the mean square error (MSE), mean absolute deviation (MAD), and mean absolute percentage error (MAPE). The best equations for predicting AMEn were derived from the mean or mode coefficients for the 10,000 EHBN results. In conclusion, the methodology used is a good tool to obtain prediction equations for AMEn as a function of the chemical composition of their feedstuffs. The coefficients were found to differ from those found by other methodologies, such as the usual neural network or multiple linear regressions. The field of broiler nutrition contributed with new equations and with a never-applied methodology and differentiated in obtaining its coefficients by empirical distributions.
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Alvarez-Miranda, E., & Pereira, J. (2017). Designing and constructing networks under uncertainty in the construction stage: Definition and exact algorithmic approach. Comput. Oper. Res., 81, 178–191.
Abstract: The present work proposes a novel Network Optimization problem whose core is to combine both network design and network construction scheduling under uncertainty into a single two-stage robust optimization model. The first-stage decisions correspond to those of a classical network design problem, while the second-stage decisions correspond to those of a network construction scheduling problem (NCS) under uncertainty. The resulting problem, which we will refer to as the Two-Stage Robust Network Design and Construction Problem (2SRNDC), aims at providing a modeling framework in which the design decision not only depends on the design costs (e.g., distances) but also on the corresponding construction plan (e.g., time to provide service to costumers). We provide motivations, mixed integer programming formulations, and an exact algorithm for the 2SRNDC. Experimental results on a large set of instances show the effectiveness of the model in providing robust solutions, and the capability of the proposed algorithm to provide good solutions in reasonable running times. (C) 2017 Elsevier Ltd. All rights reserved.
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Alzate-Grisales, J. A., Mora-Rubio, A., García-García, F., Tabares-Soto, R., & de la Iglesia-Vaya, M. (2023). SAM-UNETR: Clinically Significant Prostate CanceSegmentation Using Transfer Learning From Large Model. IEEE Access, 11, 118217–118228.
Abstract: Prostate cancer (PCa) is one of the leading causes of cancer-related mortality among men worldwide. Accurate and efficient segmentation of clinically significant prostate cancer (csPCa) regions from magnetic resonance imaging (MRI) plays a crucial role in diagnosis, treatment planning, and monitoring of the disease, however, this is a challenging task even for the specialized clinicians. This study presents SAM-UNETR, a novel model for segmenting csPCa regions from MRI images. SAM-UNETR combines a transformer-encoder from the Segment Anything Model (SAM), a versatile segmentation model trained on 11 million images, with a residual-convolution decoder inspired by UNETR. The model uses multiple image modalities and applies prostate zone segmentation, normalization, and data augmentation as preprocessing steps. The performance of SAM-UNETR is compared with three other models using the same strategy and preprocessing. The results show that SAM-UNETR achieves superior reliability and accuracy in csPCa segmentation, especially when using transfer learning for the image encoder. This demonstrates the adaptability of large-scale models for different tasks. SAM-UNETR attains a Dice Score of 0.467 and an AUROC of 0.77 for csPCa prediction.
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Antico, F. C., De la Varga, I., Esmaeeli, H. S., Nantung, T. E., Zavattieri, P. D., & Weiss, W. J. (2015). Using accelerated pavement testing to examine traffic opening criteria for concrete pavements. Constr. Build. Mater., 96, 86–95.
Abstract: The risk of cracking in a concrete pavement that is opened to traffic at early ages is related to the maximum tensile stress sigma(I), that develops in the pavement and its relationship to the measured, age dependent, flexural strength of a beam,f(r). The stress that develops in the pavement is due to several factors including traffic loading and restrained volume change caused by thermal or hygral variations. The stress that develops is also dependent on the time-dependent mechanical properties, pavement thickness, and subgrade stiffness. There is a strong incentive to open many pavements to traffic as early as possible to allow construction traffic or traffic from the traveling public to use the pavement. However, if the pavement is opened to traffic too early, cracking may occur that may compromise the service life of the pavement. The purpose of this paper is two-fold: (1) to examine the current opening strength requirements for concrete pavements (typically a flexural strength from beams, f(r)) and (2) to propose a criterion based on the time-dependent changes of sigma(I)/f(r), which accounts for pavement thickness and subgrade stiffness without adding unnecessary risk for premature cracking. An accelerated pavement testing (APT) facility was used to test concrete pavements that are opened to traffic at an early age to provide data that can be compared with an analytical model to determine the effective sigma(I)/f(r), based on the relevant features of the concrete pavement, the subgrade, and the traffic load. It is anticipated that this type of opening criteria can help the decision makers in two ways: (1) it can open pavement sections earlier thereby reducing construction time and (2) it may help to minimize the use of materials with overly accelerated strength gain that are suspected to be more susceptible to develop damage at early ages than materials that gain strength more slowly. (C) 2015 Elsevier Ltd. All rights reserved.
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Araya-Letelier, G., Antico, F. C., Burbano-Garcia, C., Concha-Riedeld, J., Norambuena-Contreras, J., Concha, J., et al. (2021). Experimental evaluation of adobe mixtures reinforced with jute fibers. Constr. Build. Mater., 276(2021), 122127.
Abstract: Due to their sustainability as well as physical and mechanical performance, different natural fibers, both vegetal and animal fibers, have been successfully used in adobe mixtures (AMs) to enhance properties such as cracking control, flexural toughness and water erosion resistance, among others. However, the use of jute fibers (JFs), one of the most largely produced vegetal fiber worldwide, has not been extensively studied on AMs. Consequently, this study evaluates the effects of the incorporation of varying dosages (0.5 and 2.0 wt%) and lengths (7, 15, and 30 mm) of JFs on the physical/thermal/mechanical/fracture and durability performance of AMs, a specific type of earth-based construction material widely used globally. Experimental results showed that the incorporation of 2.0 wt% dosages of JFs increased the capillary water absorption of AMs, which might affect AM durability. The latter result could be explained by the additional porosity generated by the spaces left between the JFs and the matrix of adobe, as well as the inherent water absorption of the JFs. The incorporation of JFs significantly improved the behavior of AMs in terms of thermal conductivity, drying shrinkage cracking control, flexural toughness and water erosion performance, without affecting their compressive and flexural strength. For example, flexural toughness indices were increased by 297% and crack density ratio as well as water erosion depth values were reduced by 93% and 62%, respectively, when 2.0 wt%-15 mm length JFs were incorporated into AM. Since the latter combination of JF dosage and length provided the overall best results among AMs, it is recommended by this study as JF-reinforcement scheme for AMs for construction applications such as adobe masonry and earth plasters.
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Araya-Letelier, G., Antico, F. C., Carrasco, M., Rojas, P., & Garcia-Herrera, C. M. (2017). Effectiveness of new natural fibers on damage-mechanical performance of mortar. Constr. Build. Mater., 152, 672–682.
Abstract: Addition of fibers to cement-based materials improve tensile and flexural strength, fracture toughness, abrasion resistance, delay cracking, and reduce crack widths. Natural fibers have recently become more popular in the construction materials community. This investigation addresses the characterization of a new animal fiber (pig hair), a massive food-industry waste worldwide, and its use in mortars. Morphological, physical and mechanical properties of pig hair are determined in order to be used as reinforcement in mortars. A sensitivity analysis on the volumes of fiber in mortars is developed. The results from this investigation showed that reinforced mortars significantly improve impact strength, abrasion resistance, plastic shrinkage cracking, age at cracking, and crack widths as fiber volume increases. Other properties such as compressive and flexural strength, density, porosity and modulus of elasticity of reinforced mortars are not significantly affected by the addition of pig hair. (C) 2017 Elsevier Ltd. All rights reserved.
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Araya-Letelier, G., Concha-Riedel, J., Antico, F. C., & Sandoval, C. (2019). Experimental mechanical-damage assessment of earthen mixes reinforced with micro polypropylene fibers. Constr. Build. Mater., 198, 762–776.
Abstract: The addition of engineered polypropylene fibers to earthen materials offers new opportunities to control their damage evolution and mechanical properties that altogether provides more reliability and extends the life span of these materials. The latter is of special interest considering that earthen materials are still widely used in the form of adobe blocks for earthen masonry, cob, rammed earth or even earthen mortars for new construction and conservation of historic buildings. In this work, the effect of dosage of micro polypropylene fibers (MPPF) in the damage-mechanical performance of earthen mixes is studied experimentally. Part of the experiments includes two different tests to assess distributed and localized cracking of reinforced earth subject to restrained drying shrinkage. In addition, the experimental results showed that the incorporation of MPPF increases up to 83 times the impact strength and 11 times the flexural toughness of earthen mixes. Other mechanical properties such as compressive and flexural strength are not statistically affected by the incorporation of MPPF. (C) 2018 Elsevier Ltd. All rights reserved.
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Araya-Letelier, G., Concha-Riedel, J., Antico, F. C., Valdes, C., & Caceres, G. (2018). Influence of natural fiber dosage and length on adobe mixes damage-mechanical behavior. Constr. Build. Mater., 174, 645–655.
Abstract: This study addresses the use of a natural fiber (pig hair), a massive food-industry waste, as reinforcement in adobe mixes (a specific type of earthen material). The relevance of this work resides in the fact that earthen materials are still widely used worldwide because of their low cost, availability, and low environmental impact. Results show that adobe mixes' mechanical-damage behavior is sensitive to both (i) fiber dosage and (ii) fiber length. Impact strength and flexural toughness are increased, whereas shrinkage distributed crack width is reduced. Average values of compressive and flexural strengths are reduced as fiber dosage and length increase, as a result of porosity generated by fiber clustering. Based on the results of this work a dosage of 0.5% by weight of dry soil using 7 mm fibers is optimal to improve crack control, flexural toughness and impact strength without statistically affecting flexural and compressive strengths. (C) 2018 Elsevier Ltd. All rights reserved.
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Araya-Letelier, G., Maturana, P., Carrasco, M., Antico, F. C., & Gomez, M. S. (2019). Mechanical-Damage Behavior of Mortars Reinforced with Recycled Polypropylene Fibers. Sustainability, 11(8), 17 pp.
Abstract: Commercial polypropylene fibers are incorporated as reinforcement of cement-based materials to improve their mechanical and damage performances related to properties such as tensile and flexural strength, toughness, spalling and impact resistance, delay formation of cracks and reducing crack widths. Yet, the production of these polypropylene fibers generates economic costs and environmental impacts and, therefore, the use of alternative and more sustainable fibers has become more popular in the research materials community. This paper addresses the characterization of recycled polypropylene fibers (RPFs) obtained from discarded domestic plastic sweeps, whose morphological, physical and mechanical properties are provided in order to assess their implementation as fiber-reinforcement in cement-based mortars. An experimental program addressing the incorporation of RPFs on the mechanical-damage performance of mortars, including a sensitivity analysis on the volumes and lengths of fiber, is developed. Using analysis of variance, this paper shows that RPFs statistically enhance flexural toughness and impact strength for high dosages and long fiber lengths. On the contrary, the latter properties are not statistically modified by the incorporation of low dosages and short lengths of RPFs, but still in these cases the incorporation of RPFs in mortars have the positive environmental impact of waste encapsulation. In the case of average compressive and flexural strength of mortars, these properties are not statistically modified when adding RPFs.
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Armstrong, M., Valencia, J., Lagos, G., & Emery, X. (2022). Constructing Branching Trees of Geostatistical Simulations. Math. Geosci., 54, 711–743.
Abstract: This paper proposes the use of multi-stage stochastic programming with recourse for optimised strategic open-pit mine planning. The key innovations are, firstly, that a branching tree of geostatistical simulations is developed to take account of uncertainty in ore grades, and secondly, scenario reduction techniques are applied to keep the trees to a manageable size. Our example shows that different mine plans would be optimal for the downside case when the deposit turns out to be of lower grade than expected compared to when it is of higher grade than expected. Our approach further provides th
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Atkinson, J., & Escudero, A. (2022). Evolutionary natural-language coreference resolution for sentiment analysis. Int. J. Inf. Manage. Data Insights, 2(2), 100115.
Abstract: Communicating messages on social media usually conveys much implicit linguistic knowledge, which makes it difficult to process texts for further analysis. One of the major problems, the linguistic coreference resolution task involves detecting coreference chains of entities and pronouns that coreference them. It has mostly been addressed for formal and full-sized text in which a relatively clear discourse structure can be discovered, using Natural-Language Processing techniques. However, texts in social media are short, informal and lack a lot of underlying linguistic information to make decisions so traditional methods can not be applied. Furthermore, this may significantly impact the performance of several tasks on social media applications such as opinion mining, network analysis, sentiment analysis, text categorization. In order to deal with these issues, this research address the task of linguistic co-referencing using an evolutionary computation approach. It combines discourse coreference analysis techniques, domain-based heuristics (i.e., syntactic, semantic and world knowledge), graph representation methods, and evolutionary computation algorithms to resolving implicit co-referencing within informal opinion texts. Experiments were conducted to assess the ability of the model to find implicit referents on informal messages, showing the promise of our approach when compared to related methods.
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Babonneau, F., Barrera, J., & Toledo, J. (2021). Decarbonizing the Chilean Electric Power System: A Prospective Analysis of Alternative Carbon Emissions Policies. Energies, 14(16), 4768.
Abstract: In this paper, we investigate potential pathways for achieving deep reductions in CO2 emissions by 2050 in the Chilean electric power system. We simulate the evolution of the power system using a long-term planning model for policy analysis that identifies investments and operation strategies to meet demand and CO2 emissions reductions at the lowest possible cost. The model considers a simplified representation of the main transmission network and representative days to simulate operations considering the variability of demand and renewable resources at different geographical locations. We perform a scenario analysis assuming different ambitious renewable energy and emission reduction targets by 2050. As observed in other studies, we show that the incremental cost of reducing CO2 emissions without carbon capture or offset alternatives increases significantly as the system approaches zero emissions. Indeed, the carbon tax is multiplied by a factor of 4 to eliminate the last Mt of CO2 emissions, i.e., from 2000 to almost 8500 USD/tCO(2) in 2050. This result highlights the importance of implementing technology-neutral mechanisms that help investors identify the most cost-efficient actions to reduce CO2 emissions. Our analysis shows that Carbon Capture and Storage could permit to divide by more than two the total system cost of a 100% renewable scenario. Furthermore, it also illustrates the importance of implementing economy-wide carbon emissions policies that ensure that the incremental costs to reduce CO2 emissions are roughly similar across different sectors of the economy.
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Barrera, J., Cancela, H., & Moreno, E. (2015). Topological optimization of reliable networks under dependent failures. Oper. Res. Lett., 43(2), 132–136.
Abstract: We address the design problem of a reliable network. Previous work assumes that link failures are independent. We discuss the impact of dropping this assumption. We show that under a common-cause failure model, dependencies between failures can affect the optimal design. We also provide an integer-programming formulation to solve this problem. Furthermore, we discuss how the dependence between the links that participate in the solution and those that do not can be handled. Other dependency models are discussed as well. (C) 2014 Elsevier B.V. All rights reserved.
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Barrera, J., Carrasco, R. A., & Moreno, E. (2020). Real-time fleet management decision support system with security constraints. TOP, 28(3), 728–748.
Abstract: Intelligent transportation, and in particular, fleet management, has been a forefront concern for a plethora of industries. This statement is especially true for the production of commodities, where transportation represents a central element for operational continuity. Additionally, in many industries, and in particular those with hazardous environments, fleet control must satisfy a wide range of security restrictions to ensure that risks are kept at bay and accidents are minimum. Furthermore, in these environments, any decision support tool must cope with noisy and incomplete data and give recommendations every few minutes. In this work, a fast and efficient decision support tool is presented to help fleet managers oversee and control ore trucks, in a mining setting. The main objective of this system is to help managers avoid interactions between ore trucks and personnel buses, one of the most critical security constraints in our case study, keeping a minimum security distance between the two at all times. Furthermore, additional algorithms are developed and implemented, so that this approach can work with real-life noisy GPS data. Through the use of historical data, the performance of this decision support system is studied, validating that it works under the real-life conditions presented by the company. The experimental results show that the proposed approach improved truck and road utilization significantly while allowing the fleet manager to control the security distance required by their procedures.
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Barrera, J., Homem-De-Mello, T., Moreno, E., Pagnoncelli, B. K., & Canessa, G. (2016). Chance-constrained problems and rare events: an importance sampling approach. Math. Program., 157(1), 153–189.
Abstract: We study chance-constrained problems in which the constraints involve the probability of a rare event. We discuss the relevance of such problems and show that the existing sampling-based algorithms cannot be applied directly in this case, since they require an impractical number of samples to yield reasonable solutions. We argue that importance sampling (IS) techniques, combined with a Sample Average Approximation (SAA) approach, can be effectively used in such situations, provided that variance can be reduced uniformly with respect to the decision variables. We give sufficient conditions to obtain such uniform variance reduction, and prove asymptotic convergence of the combined SAA-IS approach. As it often happens with IS techniques, the practical performance of the proposed approach relies on exploiting the structure of the problem under study; in our case, we work with a telecommunications problem with Bernoulli input distributions, and show how variance can be reduced uniformly over a suitable approximation of the feasibility set by choosing proper parameters for the IS distributions. Although some of the results are specific to this problem, we are able to draw general insights that can be useful for other classes of problems. We present numerical results to illustrate our findings.
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Baselli, G., Contreras, F., Lillo, M., Marin, M., & Carrasco, R. A. (2020). Optimal decisions for salvage logging after wildfires. Omega-Int. J. Manage. Sci., 96, 9 pp.
Abstract: Strategic, tactical, and operational harvesting plans for the forestry and logging industry have been widely studied for more than 60 years. Many different settings and specific constraints due to legal, environmental, and operational requirements have been modeled, improving the performance of the harvesting process significantly. During the summer of 2017, Chile suffered from the most massive wildfires in its history, affecting almost half a million hectares, of which nearly half were forests owned by medium and small forestry companies. Some of the stands were burned by intense crown fires, which always spread fast, that burned the foliage and outer layer of the bark but left standing dead trees that could be salvage harvested before insect and decay processes rendered them unusable for commercial purposes. Unlike the typical operational programming models studied in the past, in this setting, companies can make insurance claims on part or all of the burnt forest, whereas the rest of the forest needs to be harvested before it loses its value. This problem is known as the salvage logging problem. The issue also has an important social component when considering medium and small forestry and logging companies: most of their personnel come from local communities, which have already been affected by the fires. Harvesting part of the remaining forest can allow them to keep their jobs longer and, hopefully, leave the company in a better financial situation if the harvesting areas are correctly selected. In this work, we present a novel mixed-integer optimization-based approach to support salvage logging decisions, which helps in the configuration of an operational-level harvesting and workforce assignment plan. Our model takes into account the payment from an insurance claim as well as future income from harvesting the remaining trees. The model also computes an optimal assignment of personnel to the different activities required. The objective is to improve the cash position of the company by the end of the harvest and ensure that the company is paying all its liabilities and maintaining personnel. We show how our model performs compared to the current decisions made by medium and small-sized forestry companies, and we study the specific case of a small forestry company located in Cauquenes, Chile, which used our model to decide its course of action. (C) 2019 Elsevier Ltd. All rights reserved.
Keywords: Salvage logging; Forest harvesting; Wildfires; Workforce allocation
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Becker, F., Montealegre, P., Rapaport, I., & Todinca, I. (2021). The role of randomness in the broadcast congested clique model. Inf. Comput., 281, 104669.
Abstract: We study the role of randomness in the broadcast congested clique model. This is a message-passing model of distributed computation where the nodes of a network know their local neighborhoods and they broadcast, in synchronous rounds, messages that are visible to every other node.
This works aims to separate three different settings: deterministic protocols, randomized protocols with private coins, and randomized protocols with public coins. We obtain the following results: If more than one round is allowed, public randomness is as powerful as private ran-domness. One-round public-coin algorithms can be exponentially more powerful than determin-istic algorithms running in several rounds. One-round public-coin algorithms can be exponentially more powerful than one-round private-coin algorithms. One-round private-coin algorithms can be exponentially more powerful than one-round deterministic algorithms. |
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Beltran, J. F., Nunez, E., Nunez, F., Silva, I., Bravo, T., & Moffat, R. (2018). Static response of asymmetrically damaged metallic strands: Experimental and numerical approach. Constr. Build. Mater., 192, 538–554.
Abstract: In this study, the effect of the presence of broken wires (damage) asymmetrically distributed on metallic strands surfaces on their static response is assessed. To this end, a general mechanical model for multi layered strands is presented, in which damaged strands are treated as a 1D nonlinear beam under uncoupled biaxial bending and axial load (NLBM). The NLBM is validated by comparisons with the results obtained from an experimental program especially designed for studying the effect of surface damage distribution on strands response and 3D nonlinear finite element simulations. Analyses are carried out on two strand constructions: 1 x 7 and 1 x 19, in which the damage levels and strand diameters vary from 5% to 40% and from 3.5 mm to 22.2 mm, respectively. Results indicate that the NLBM accurate predicts the static response (residual strength, stiffness, axial strain field, and deformed configuration) of the asymmetrically damaged strands, achieving good computational efficiency and numerical robustness. (C) 2018 Elsevier Ltd. All rights reserved.
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Bitran, E., Rivera, P., & Villena, M. J. (2014). Water management problems in the Copiapo Basin, Chile: markets, severe scarcity and the regulator. Water Policy, 16(5), 844–863.
Abstract: This research focuses on the determination of the factors that led to the failure of water management in the Copiapo Basin in Chile. Interestingly, the existence of full private ownership and free tradability of water rights has not prevented the overexploitation of groundwater resources. In the paper, firstly, water regulation and the role of the regulator in Chile are briefly discussed. Secondly, the evolution of water resources in the Copiapo region is characterized and analyzed, and the granting of water use rights in the basin in the last 30 years is concisely described. Thirdly, we examine and analyze prices and quantities traded in the water market of the Copiapo region. We will argue that this crisis is a consequence first of failure in regulatory implementation and second of an extremely rigid regulatory framework that leaves limited room for adjustment to changing conditions, especially regarding the emergence of new information concerning water availability. We believe this investigation is not only relevant for this case in particular, but also for other regions and countries where water markets are in place.
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