Now showing 1 - 10 of 30
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Visual Impairment Simulator Based on the Hadamard Product

2016 , Velázquez, Ramiro , Sánchez-Gómez, Claudia , Edwige E. Pissaloux

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Heidegger and the simile of the cave. The assumptions of its interpretation

2020 , Domínguez-Soberanes, Julieta , Sánchez-Gómez, Claudia , Orvañanos-Guerrero, María T.

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Liking Product Landscape: Going Deeper into Understanding Consumers’ Hedonic Evaluations

2019 , Sánchez-Gómez, Claudia , Domínguez-Soberanes, Julieta , Héctor B. Escalona-Buendía , Mario Graff , Gutiérrez, Sebastián , Gabriela Sánchez

The use of graphical mapping for understanding the comparison of products based on consumers’ perceptions is beneficial and easy to interpret. Internal preference mapping (IPM) and landscape segmentation analysis (LSA) have successfully been used for this propose. However, including all the consumers’ evaluations in one map, with products’ overall liking and attributes’ perceptions, is complicated; because data is in a high dimensional space some information can be lost. To provide as much information as possible, we propose the liking product landscape (LPL) methodology where several maps are used for representing the consumers’ distribution and evaluations. LPL shows the consumers’ distribution, like LSA, and also it superimposes the consumers’ evaluations. However, instead of superimposing the average overall liking in one map, this methodology uses different maps for each consumer’s evaluation. Two experiments were performed where LPL was used for understanding the consumers’ perceptions and compared with classic methodologies, IPM and cluster analysis, in order to validate the results. LPL can be successfully used for identifying consumers’ segments, consumers’ preferences, recognizing perception of product attributes by consumers’ segments and identifying the attributes that need to be optimized.

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Using Fully Cartesian Coordinates to Calculate the Support Reactions of Multi-Scale Mechanisms

2018 , Orvañanos-Guerrero, María T. , Sánchez-Gómez, Claudia , Dávalos Orozco, Oscar , Mariano Rivera , Velázquez, Ramiro , Acevedo, Mario

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Estimating the Maximum Power of a Concentrator Photovoltaic Module through Random Forest

2023 , Sánchez-Gómez, Claudia , Pedro M. Rodrigo

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Complete Balancing of the Six-Bar Mechanism Using Fully Cartesian Coordinates and Multiobjective Differential Evolution Optimization

2022 , Orvañanos-Guerrero, María T. , Acevedo, Mario , Daniel U. Campos-Delgado , Sánchez-Gómez, Claudia , Amir Aminzadeh Ghavifekr , Paolo Visconti , Velázquez, Ramiro

The high-speed operation of unbalanced machines may cause vibrations that lead to noise, wear, and fatigue that will eventually limit their efficiency and operating life. To restrain such vibrations, a complete balancing must be performed. This paper presents the complete balancing optimization of a six-bar mechanism with the use of counterweights. A novel method based on fully Cartesian coordinates (FCC) is proposed to represent such a balanced mechanism. A multiobjective optimization problem was solved using the Differential Evolution (DE) algorithm to minimize the shaking force (ShF) and the shaking moment (ShM) and thus balance the system. The Pareto front is used to determine the best solutions according to three optimization criteria: only the ShF, only the ShM, and both the ShF and ShM. The dimensions of the counterweights are further fine-tuned with an analysis of their partial derivatives, volumes, and area–thickness relations. Numerical results show that the ShF and ShM can be reduced by 76.82% and 77.21%, respectively, when importance is given to either of them and by 45.69% and 46.81%, respectively, when equal importance is given to both. A comparison of these results with others previously reported in the literature shows that the use of FCC in conjunction with DE is a suitable methodology for the complete balancing of mechanisms.

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A Multisensor Data Fusion Approach for Predicting Consumer Acceptance of Food Products

2020 , Álvarez-Pato, Víctor M. , Sánchez-Gómez, Claudia , Domínguez-Soberanes, Julieta , Mendoza Pérez, David Eduardo , Velázquez, Ramiro

Sensory experiences play an important role in consumer response, purchase decision, and fidelity towards food products. Consumer studies when launching new food products must incorporate physiological response assessment to be more precise and, thus, increase their chances of success in the market. This paper introduces a novel sensory analysis system that incorporates facial emotion recognition (FER), galvanic skin response (GSR), and cardiac pulse to determine consumer acceptance of food samples. Taste and smell experiments were conducted with 120 participants recording facial images, biometric signals, and reported liking when trying a set of pleasant and unpleasant flavors and odors. Data fusion and analysis by machine learning models allow predicting the acceptance elicited by the samples. Results confirm that FER alone is not sufficient to determine consumers’ acceptance. However, when combined with GSR and, to a lesser extent, with pulse signals, acceptance prediction can be improved. This research targets predicting consumer’s acceptance without the continuous use of liking scores. In addition, the findings of this work may be used to explore the relationships between facial expressions and physiological reactions for non-rational decision-making when interacting with new food products.

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Modeling of Amorphous-Carbon Cells for Molecular Dynamics Simulations

2019 , Sánchez-Gómez, Claudia , Domínguez-Soberanes, Julieta , ORTIZ-MEDINA, JOSUE

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INGEOTEC at MEX-A3T: Author profiling and aggressiveness analysis in Twitter using µTC and EvoMSA

2018 , Sánchez-Gómez, Claudia

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I3GO+ at RICATIM 2017: A semi-supervised approach to determine the relevance between images and text-annotations

2017 , Jose Ortiz-Bejar , Eric S. Tellez , Mario Graff , Sabino Miranda-Jimenez , Daniela Moctezuma , Sánchez-Gómez, Claudia