First of all, please accept my congratulations for your article. Upon reviewing your article, I f... more First of all, please accept my congratulations for your article. Upon reviewing your article, I found the methodology and results presented to be clear and well structured. The utilization of SMOTE and the comparison of various classification algorithms demonstrates a comprehensive approach to addressing the challenge of imbalanced data and improving predictive accuracy. I would like to offer some constructive feedback to further improve. First, I recommend incorporating additional references to enrich the literature review section and provide a more complete theoretical foundation for your research. Furthermore, centralizing the presentation of results in a table format could improve the clarity and comparability of performance metrics between different algorithms. Furthermore, providing a more detailed explanation of the elements of the data set, including characteristics, preprocessing steps, and the target variable, would offer readers a better understanding of the context and characteristics of the data used in the study. Overall, I find your article promising and accept it with some suggested improvements. By addressing these suggestions, you can further strengthen the quality and impact of your research findings.
Borderline Personality Disorder (BPD) symptoms include inappropriate control of anger and severe ... more Borderline Personality Disorder (BPD) symptoms include inappropriate control of anger and severe emotional dysregulation after rejection in daily life. Nevertheless, when using the Cyberball paradigm, a tossing game to simulate social exclusion, the seven basic emotions (happiness, sadness, anger, surprise, fear, disgust, and contempt) have not been exhaustively tracked out. It was hypothesized that these patients would show anger, contempt, and disgust during the condition of exclusion versus the condition of inclusion. When facial emotions are automatically detected by Artificial Intelligence, "blending",-or a mixture of at least two emotions-and "masking",-or showing happiness while expressing negative emotions-may be most easily traced expecting higher percentages during exclusion rather than inclusion. Therefore, face videos of fourteen patients diagnosed with BPD (26 ± 6 years old), recorded while playing the tossing game, were analyzed by the FaceReader software. The comparison of conditions highlighted an interaction for anger: it increased during inclusion and decreased during exclusion. During exclusion, the masking of surprise; i.e., displaying happiness while feeling surprised, was significantly more expressed. Furthermore, disgust and contempt were inversely correlated with greater difficulties in emotion regulation and symptomatology, respectively. Therefore, the automatic detection of emotional expressions during both conditions could be useful in rendering diagnostic guidelines in clinical scenarios.
Background: Sleep disruption in elderly has been associated with an increased risk of cognitive i... more Background: Sleep disruption in elderly has been associated with an increased risk of cognitive impairment and its transition into Alzheimer’s disease (AD). High arousal indices (AIs) during sleep may serve as an early-stage biomarker of cognitive impairment non-dementia (CIND). Objective: Using full-night polysomnography (PSG), we investigated whether CIND is related to different AIs between NREM and REM sleep stages. Methods: Fourteen older adults voluntarily participated in this population-based study that included Mini-Mental State Examination, Neuropsi battery, Katz Index of Independence in Activities of Daily Living, and single-night PSG. Subjects were divided into two groups (n = 7 each) according to their results in Neuropsi memory and attention subtests: cognitively unimpaired (CU), with normal results; and CIND, with –2.5 standard deviations in memory and/or attention subtests. AIs per hour of sleep during N1, N2, N3, and REM stages were obtained and correlated with Neurop...
Artificial Neural Networks - Recent Advances, New Perspectives and Applications [Working Title]
This chapter explores the use of an artificial neural network (ANN) to obtain the elastic constan... more This chapter explores the use of an artificial neural network (ANN) to obtain the elastic constants of the components of a metal laminated composite material (MLCM). The dataset for the training and validation of the ANN was obtained by applying an analytical model developed for the study of stresses in MLCM. The information used in the dataset corresponds to MLCM configurations and data generated with variants registered in the structural presentation of the inputs and outputs. The best configuration found for the generation of the ANN models yielded an average relative error of less than 4% in relation to the results of the constants evaluated and published in a previous article. As shown in this research, it is important to have a clear definition of the problem as well as an effective selection and preparation of the characteristics of the training data during the constitutive modeling of composite materials and the correct application of the ANN.
This work presents an optimization proposal to better the computational convergence time in conve... more This work presents an optimization proposal to better the computational convergence time in convection-diffusion and driven-cavity problems by applying a simulated annealing (SA) metaheuristic, obtaining optimal values in relaxation factors (RF) that optimize the problem convergence during its numerical execution. These relaxation factors are tested in numerical models to accelerate their computational convergence in a shorter time. The experimental results show that the relaxation factors obtained by the SA algorithm improve the computational time of the problem convergence regardless of user experience in the initial low-quality RF proposal.
The study of the mechanical behavior of composite materials has acquired great importance due to ... more The study of the mechanical behavior of composite materials has acquired great importance due to the innumerable number of applications in new technological developments. As a result, many theories and analytical models have been developed with which its mechanical behavior is predicted; these models require knowledge of elastic properties. This work describes a basic theoretical framework, based on linear elasticity theory and classical lamination theory, to generate constitutive models of laminated materials made up of orthotropic layers. Thus, the models of three orthotropic laminated composite materials made up of layers of epoxy resin reinforced with fiberglass were also obtained. Finally, by means of experimental axial load tests, the constants of the orthotropic layers were determined.
In this paper, a hybrid genetic algorithm implemented in a grid environment to solve hard instanc... more In this paper, a hybrid genetic algorithm implemented in a grid environment to solve hard instances of the flexible flow shop scheduling problem with sequence-dependent setup times is introduced. The genetic algorithm takes advantage of the distributed computing power on the grid to apply a hybrid local search to each individual in the population and reach a near optimal solution in a reduced number of generations. Ant colony systems and simulated annealing are used to apply a combination of iterative and cooperative local searches, respectively. This algorithm is implemented using a master–slave scheme, where the master process distributes the population on the slave process and coordinates the communication on the computational grid elements. The experimental results point out that the proposed scheme obtains the upper bound in a broad set of test instances. Also, an efficiency analysis of the proposed algorithm indicates its competitive use of the computational resources of the g...
Journal of Mechanical Science and Technology, 2021
In this study, a novel method for determining stresses in the torsion problems of laminated compo... more In this study, a novel method for determining stresses in the torsion problems of laminated composite trimetallic and bimetallic bars was developed and evaluated via experimental and numerical analyses. The objective of this method is to transform a real transversal section of a model for a laminated composite bar into a hypothetical virtual section that is homogenous and isotropic. An analogy with the transformed-section method for solving composite beams under flexion was conducted. The shear stresses (maximum on external surfaces and interfaces) in laminated composite bars were undergoing torsion. Isotropic symmetric and asymmetric laminated composite bars were examined analytically, and the results of their respective experimental and numerical tests were analyzed. The proposed method exhibits differences between 2 % and 12 % compared with the experimental results and between 2 % and 10 % compared with the results obtained using the finite element method.
This paper presents a methodological scheme to obtain the maximum benefit in occupational health ... more This paper presents a methodological scheme to obtain the maximum benefit in occupational health by attending to psychosocial risk factors in a company. This scheme is based on selecting an optimal subset of psychosocial risk factors, considering the departments’ budget in a company as problem constraints. This methodology can be summarized in three steps: First, psychosocial risk factors in the company are identified and weighted, applying several instruments recommended by business regulations. Next, a mathematical model is built using the identified psychosocial risk factors information and the company budget for risk factors attention. This model represents the psychosocial risk optimization problem as a Multidimensional Knapsack Problem (MKP). Finally, since Multidimensional Knapsack Problem is NP-hard, one simulated annealing algorithm is applied to find a near-optimal subset of factors maximizing the psychosocial risk care level. This subset is according to the budgets assign...
Paper waste in the mockups design with regular, irregular, and amorphous patterns is a critical p... more Paper waste in the mockups design with regular, irregular, and amorphous patterns is a critical problem in digital printing presses. Paper waste reduction directly impacts production costs, generating business and environmental benefits. This problem can be mapped to the two-dimensional irregular bin-packing problem. In this paper, an iterated local search algorithm using a novel neighborhood structure to detect overlaps between amorphous shapes is introduced. This algorithm is used to solve the paper waste problem, modeled as one 2D irregular bin-packing problem. The experimental results show that this approach works efficiently and effectively to detect and correct the overlaps between regular, irregular, and amorphous figures.
In this paper, a computational methodology combining the simulated annealing algorithm with two m... more In this paper, a computational methodology combining the simulated annealing algorithm with two machine learning techniques to select a near-optimal safeguard set for business risk response is presented. First, a mathematical model with four types of risk factor responses (avoid, mitigate, transfer, and accept) is constructed. Then, the simulated annealing algorithm is applied to find a set of near-optimal solutions to the model. Next, these solutions are processed by the k-means clustering algorithm for identifying three categories, and with a decision tree classifier, the most relevant elements of each one are obtained. Finally, the categorized solutions are shown to the decision-makers through a user interface. These stages are designed with the aim of the users can take an appropriate safeguard set and develop one specific and optimal program to respond to business risk factors. The results generated by the proposed approach are reached in a reasonable time using less computational resources than those used by other procedures. Furthermore, the best results obtained by the simulated annealing algorithm use a lower business budget, and they have a relative-error less than 0.0013% of the optimal solution given by a deterministic method. INDEX TERMS Risk factor to bankruptcy, metaheuristic, machine learning, k-means, decision trees.
First of all, please accept my congratulations for your article. Upon reviewing your article, I f... more First of all, please accept my congratulations for your article. Upon reviewing your article, I found the methodology and results presented to be clear and well structured. The utilization of SMOTE and the comparison of various classification algorithms demonstrates a comprehensive approach to addressing the challenge of imbalanced data and improving predictive accuracy. I would like to offer some constructive feedback to further improve. First, I recommend incorporating additional references to enrich the literature review section and provide a more complete theoretical foundation for your research. Furthermore, centralizing the presentation of results in a table format could improve the clarity and comparability of performance metrics between different algorithms. Furthermore, providing a more detailed explanation of the elements of the data set, including characteristics, preprocessing steps, and the target variable, would offer readers a better understanding of the context and characteristics of the data used in the study. Overall, I find your article promising and accept it with some suggested improvements. By addressing these suggestions, you can further strengthen the quality and impact of your research findings.
Borderline Personality Disorder (BPD) symptoms include inappropriate control of anger and severe ... more Borderline Personality Disorder (BPD) symptoms include inappropriate control of anger and severe emotional dysregulation after rejection in daily life. Nevertheless, when using the Cyberball paradigm, a tossing game to simulate social exclusion, the seven basic emotions (happiness, sadness, anger, surprise, fear, disgust, and contempt) have not been exhaustively tracked out. It was hypothesized that these patients would show anger, contempt, and disgust during the condition of exclusion versus the condition of inclusion. When facial emotions are automatically detected by Artificial Intelligence, "blending",-or a mixture of at least two emotions-and "masking",-or showing happiness while expressing negative emotions-may be most easily traced expecting higher percentages during exclusion rather than inclusion. Therefore, face videos of fourteen patients diagnosed with BPD (26 ± 6 years old), recorded while playing the tossing game, were analyzed by the FaceReader software. The comparison of conditions highlighted an interaction for anger: it increased during inclusion and decreased during exclusion. During exclusion, the masking of surprise; i.e., displaying happiness while feeling surprised, was significantly more expressed. Furthermore, disgust and contempt were inversely correlated with greater difficulties in emotion regulation and symptomatology, respectively. Therefore, the automatic detection of emotional expressions during both conditions could be useful in rendering diagnostic guidelines in clinical scenarios.
Background: Sleep disruption in elderly has been associated with an increased risk of cognitive i... more Background: Sleep disruption in elderly has been associated with an increased risk of cognitive impairment and its transition into Alzheimer’s disease (AD). High arousal indices (AIs) during sleep may serve as an early-stage biomarker of cognitive impairment non-dementia (CIND). Objective: Using full-night polysomnography (PSG), we investigated whether CIND is related to different AIs between NREM and REM sleep stages. Methods: Fourteen older adults voluntarily participated in this population-based study that included Mini-Mental State Examination, Neuropsi battery, Katz Index of Independence in Activities of Daily Living, and single-night PSG. Subjects were divided into two groups (n = 7 each) according to their results in Neuropsi memory and attention subtests: cognitively unimpaired (CU), with normal results; and CIND, with –2.5 standard deviations in memory and/or attention subtests. AIs per hour of sleep during N1, N2, N3, and REM stages were obtained and correlated with Neurop...
Artificial Neural Networks - Recent Advances, New Perspectives and Applications [Working Title]
This chapter explores the use of an artificial neural network (ANN) to obtain the elastic constan... more This chapter explores the use of an artificial neural network (ANN) to obtain the elastic constants of the components of a metal laminated composite material (MLCM). The dataset for the training and validation of the ANN was obtained by applying an analytical model developed for the study of stresses in MLCM. The information used in the dataset corresponds to MLCM configurations and data generated with variants registered in the structural presentation of the inputs and outputs. The best configuration found for the generation of the ANN models yielded an average relative error of less than 4% in relation to the results of the constants evaluated and published in a previous article. As shown in this research, it is important to have a clear definition of the problem as well as an effective selection and preparation of the characteristics of the training data during the constitutive modeling of composite materials and the correct application of the ANN.
This work presents an optimization proposal to better the computational convergence time in conve... more This work presents an optimization proposal to better the computational convergence time in convection-diffusion and driven-cavity problems by applying a simulated annealing (SA) metaheuristic, obtaining optimal values in relaxation factors (RF) that optimize the problem convergence during its numerical execution. These relaxation factors are tested in numerical models to accelerate their computational convergence in a shorter time. The experimental results show that the relaxation factors obtained by the SA algorithm improve the computational time of the problem convergence regardless of user experience in the initial low-quality RF proposal.
The study of the mechanical behavior of composite materials has acquired great importance due to ... more The study of the mechanical behavior of composite materials has acquired great importance due to the innumerable number of applications in new technological developments. As a result, many theories and analytical models have been developed with which its mechanical behavior is predicted; these models require knowledge of elastic properties. This work describes a basic theoretical framework, based on linear elasticity theory and classical lamination theory, to generate constitutive models of laminated materials made up of orthotropic layers. Thus, the models of three orthotropic laminated composite materials made up of layers of epoxy resin reinforced with fiberglass were also obtained. Finally, by means of experimental axial load tests, the constants of the orthotropic layers were determined.
In this paper, a hybrid genetic algorithm implemented in a grid environment to solve hard instanc... more In this paper, a hybrid genetic algorithm implemented in a grid environment to solve hard instances of the flexible flow shop scheduling problem with sequence-dependent setup times is introduced. The genetic algorithm takes advantage of the distributed computing power on the grid to apply a hybrid local search to each individual in the population and reach a near optimal solution in a reduced number of generations. Ant colony systems and simulated annealing are used to apply a combination of iterative and cooperative local searches, respectively. This algorithm is implemented using a master–slave scheme, where the master process distributes the population on the slave process and coordinates the communication on the computational grid elements. The experimental results point out that the proposed scheme obtains the upper bound in a broad set of test instances. Also, an efficiency analysis of the proposed algorithm indicates its competitive use of the computational resources of the g...
Journal of Mechanical Science and Technology, 2021
In this study, a novel method for determining stresses in the torsion problems of laminated compo... more In this study, a novel method for determining stresses in the torsion problems of laminated composite trimetallic and bimetallic bars was developed and evaluated via experimental and numerical analyses. The objective of this method is to transform a real transversal section of a model for a laminated composite bar into a hypothetical virtual section that is homogenous and isotropic. An analogy with the transformed-section method for solving composite beams under flexion was conducted. The shear stresses (maximum on external surfaces and interfaces) in laminated composite bars were undergoing torsion. Isotropic symmetric and asymmetric laminated composite bars were examined analytically, and the results of their respective experimental and numerical tests were analyzed. The proposed method exhibits differences between 2 % and 12 % compared with the experimental results and between 2 % and 10 % compared with the results obtained using the finite element method.
This paper presents a methodological scheme to obtain the maximum benefit in occupational health ... more This paper presents a methodological scheme to obtain the maximum benefit in occupational health by attending to psychosocial risk factors in a company. This scheme is based on selecting an optimal subset of psychosocial risk factors, considering the departments’ budget in a company as problem constraints. This methodology can be summarized in three steps: First, psychosocial risk factors in the company are identified and weighted, applying several instruments recommended by business regulations. Next, a mathematical model is built using the identified psychosocial risk factors information and the company budget for risk factors attention. This model represents the psychosocial risk optimization problem as a Multidimensional Knapsack Problem (MKP). Finally, since Multidimensional Knapsack Problem is NP-hard, one simulated annealing algorithm is applied to find a near-optimal subset of factors maximizing the psychosocial risk care level. This subset is according to the budgets assign...
Paper waste in the mockups design with regular, irregular, and amorphous patterns is a critical p... more Paper waste in the mockups design with regular, irregular, and amorphous patterns is a critical problem in digital printing presses. Paper waste reduction directly impacts production costs, generating business and environmental benefits. This problem can be mapped to the two-dimensional irregular bin-packing problem. In this paper, an iterated local search algorithm using a novel neighborhood structure to detect overlaps between amorphous shapes is introduced. This algorithm is used to solve the paper waste problem, modeled as one 2D irregular bin-packing problem. The experimental results show that this approach works efficiently and effectively to detect and correct the overlaps between regular, irregular, and amorphous figures.
In this paper, a computational methodology combining the simulated annealing algorithm with two m... more In this paper, a computational methodology combining the simulated annealing algorithm with two machine learning techniques to select a near-optimal safeguard set for business risk response is presented. First, a mathematical model with four types of risk factor responses (avoid, mitigate, transfer, and accept) is constructed. Then, the simulated annealing algorithm is applied to find a set of near-optimal solutions to the model. Next, these solutions are processed by the k-means clustering algorithm for identifying three categories, and with a decision tree classifier, the most relevant elements of each one are obtained. Finally, the categorized solutions are shown to the decision-makers through a user interface. These stages are designed with the aim of the users can take an appropriate safeguard set and develop one specific and optimal program to respond to business risk factors. The results generated by the proposed approach are reached in a reasonable time using less computational resources than those used by other procedures. Furthermore, the best results obtained by the simulated annealing algorithm use a lower business budget, and they have a relative-error less than 0.0013% of the optimal solution given by a deterministic method. INDEX TERMS Risk factor to bankruptcy, metaheuristic, machine learning, k-means, decision trees.
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Papers by Marta Eraña