International Journal of Combinatorial Optimization Problems and Informatics
type: channel
description: The International Journal of Combinatorial Optimization Problems and Informatics (IJCOPI) aims to provide a forum for the dissemination and discussion of research in combinatorial optimization and informatics. The journal publishes high-quality, peer-reviewed articles with emphasis on new problems, methods, techniques, and algorithms. IJCOPI is an open access journal that supports the dissemination of scientific knowledge through electronic publication. A rigorous peer review process ensures the validity, originality, and relevance of all published contributions. The journal follows a regular publication schedule, organizing issues throughout the year. Articles may be published as part of scheduled issues to ensure timely dissemination of research results. IJCOPI publishes three regular issues per year, corresponding to the periods January–April, May–August, and September–December. Additional special issues may be published when academically justified. The journal encourages contributions that support the advancement of the United Nations Sustainable Development Goals (SDGs), particularly in areas related to industry, innovation, and infrastructure (SDG 9), as well as the application of optimization and informatics to societal and technological challenges. Type of publication The International Journal of Combinatorial Optimization Problems and Informatics (IJCOPI) is a specialised scientific research journal that publishes peer-reviewed original research articles in combinatorial optimisation, informatics, artificial intelligence, data science, operations research and related interdisciplinary fields.
publisher: Editorial Académica Dragón Azteca
language: en-US
publication name: International Journal of Combinatorial Optimization Problems and Informatics
issn: 2007-1558
items: Interval Type-3 Fuzzy-Fractal Approach for Arrhythmia Classification
items: Multilevel Detection of Symbolic Violence Against Women in Reddit's Tech Communities Using BERT
items: Does size matter? The influence of reduct size on the performance of supervised classifiers
items: Systemic Approach to Injury Phenomenology in Generation Z Padel: Biomechanical Interrelationships and Physical Armor
items: Cayley–Hamilton-Guided Krylov Regularization for Machine Learning: Theory, Computational Architecture, and Empirical Evidence
items: Comparative Benchmark of Eleven Regression Models for Software Effort Estimation on a COCOMO-Like Dataset
items: A Genetic Algorithm Framework for Efficient Electric Patient Transportation
items: Optimization of Multi-modal Relaxometry MR Acquisitions for Estimating Quantitative Brain Microstructure Parameters
items: Quantifying Perceptual Uncertainty through Non-Invasive Kinematic Tracking: A Convolutional Neural Network-Based Approach for Digital Biomarker Development
items: Fuzzy Logic and Computer Vision-Based Control Strategy for Line Following in an Omnidirectional Autonomous Mobile Robot
items: RAÍZ: A Hybrid Architecture Based on Linguistic Knowledge and Deep Learning for the Machine Translation of Low-Resource Indigenous Languages
items: Generative Artificial Intelligence: Ethical challenges and pedagogical implications in emerging educational contexts
items: Performance Analysis of Web Microservices with Technological Convergence between REST and GraphQL API Architectures

Interval Type-3 Fuzzy-Fractal Approach for Arrhythmia Classification
type: item
description: In this paper a combination of interval type-3 fuzzy logic and the fractal dimension (FD) is employed for arrhythmia classification. FD is utilized to characterize the geometrical properties in the electrocardiogram (ECG) of a patient. The fractal dimension is a good representative of an ECG signal, as is able to model its complexity. A type-3 fuzzy system is used to convey the knowledge in image classification. Type-3 helps in capturing the uncertainty in medical classification. A new technique is introduced for arrhythmia classification using the FD. Results with the MIT dataset show the effectiveness of the proposal. In addition, type-3 results were shown to be statistically better than the ones obtained by type-2 and type-1. A limitation of this study is that arrhythmia classification is performed in an offline fashion, meaning that information of patients is contained in a dataset and we process the information in the computer, which is not real-world scenario in this case. Future work could be to optimize parameters for enhancing even further the performance. Also, a hardware implementation would help in making this approach closer to the real persons, as arrhythmias could be classified in a quicker fashion. Spanish-language metadata / Metadatos en español Título en español: Enfoque difuso-fractal de intervalo tipo 3 para la clasificación de arritmias Resumen: En este artículo se emplea una combinación de lógica difusa de intervalo tipo 3 y dimensión fractal (FD) para la clasificación de arritmias. La FD se utiliza para caracterizar las propiedades geométricas del electrocardiograma (ECG) de un paciente. La dimensión fractal constituye una buena representación de una señal ECG, ya que permite modelar su complejidad. Se utiliza un sistema difuso tipo 3 para incorporar el conocimiento en la clasificación de imágenes. El tipo 3 contribuye a capturar la incertidumbre presente en la clasificación médica. Se introduce una nueva técnica para la clasificación de arrit…
creator: Patricia Melin
creator: Oscar Castillo
rights: Copyright (c) 2026 International Journal of Combinatorial Optimization Problems and Informatics https://creativecommons.org/licenses/by-nc-nd/4.0/
license: https://creativecommons.org/licenses/by-nc-nd/4.0/
date: 2026-09-06
publication date: 2026-09-06
volume: 17
number: 5
starting page: 1
ending page: 13
doi: 10.61467/2007.1558.2026.v17i5.1535

Multilevel Detection of Symbolic Violence Against Women in Reddit's Tech Communities Using BERT
type: item
description: This paper presents an automated system for detecting and analyzing symbolic violence directed against women in Reddit’s tech communities. Unlike explicit aggression, symbolic violence manifests itself through practices such as the dismissal of professional competence, gender stereotypes, or the normalization of hostile work environments. The system employs a four-layer architecture: (1) a lexical rule classifier serving as a baseline; (2) a fine-tuned BERT model to distinguish between direct violence, subtle violence, and neutral content; (3) a post-processing module that corrects false positives; and (4) a context classifier that differentiates between violence actively perpetrated in the text (conversational) and accounts of lived experiences (testimonial). A total of 184,572 texts from 17 Reddit communities were analyzed during the 2016–2026 period. The BERT model achieved an accuracy of 84.90% with a macro-F1 score of 0.85, detecting 23.3% of violence compared to a 9.4% obtained by the rule-based classifier. The results show that 22.3% of the corpus contains some form of symbolic violence and that 99.9% of these texts correspond to testimonial discourse, indicating that these communities function as spaces for reporting and support, not aggression. The temporal analysis reveals a statistically significant downward trend (r²=0.58, p=0.0067), with a reduction of approximately 0.36 percentage points per year. However, the prevalence remains above 20% for most of the period, suggesting that, despite the progress made by social movements such as #MeToo or the Google Walkout, symbolic violence remains a structural problem in the sector. Subtle violence predominates in technical communities, while direct violence prevails in support communities. Spanish-language metadata / Metadatos en español Título en español: Detección multinivel de violencia simbólica contra las mujeres en comunidades tecnológicas de Reddit mediante BERT Resumen: Este artículo presenta un sistema …
creator: Maricarmen Camacho-Pérez
creator: Mireya Clavel-Maqueda
creator: Eduardo Cornejo-Velazquez
rights: Copyright (c) 2026 International Journal of Combinatorial Optimization Problems and Informatics https://creativecommons.org/licenses/by-nc-nd/4.0/
license: https://creativecommons.org/licenses/by-nc-nd/4.0/
date: 2026-09-06
publication date: 2026-09-06
volume: 17
number: 5
starting page: 14
ending page: 36
doi: 10.61467/2007.1558.2026.v17i5.1404

Does size matter? The influence of reduct size on the performance of supervised classifiers
type: item
description: This study investigates the role of reduct-based attribute subsets (derived from rough set theory) with respect to supervised classification performance. Considering twenty-one datasets, two representations were assessed: minimum-length reducts containing the smallest attribute sets to retain consistency, and maximum-length reducts comprising the largest irredundant subsets. A Friedman–Nemenyi test was used to assess eleven classifiers with five quality measures. For the majority of classifiers, both types of reducts systematically degrade the predictive performance when compared with using all attributes. JRIP, Logistic Regression, and MLP are consistent and have the same performance except for PRC area, where maximum-length reducts reduce performance. For SMO, minimum-length reducts perform better than maximum-length reducts. These observations show that the efficacy of reduct-based feature selection largely depends on the characteristics of classifiers; it can provide significant dimensionality reduction without loss of accuracy for some models. Spanish-language metadata / Metadatos en español Título en español: ¿Importa el tamaño? La influencia del tamaño del reducto en el rendimiento de los clasificadores supervisados Resumen: Este estudio investiga el papel de los subconjuntos de atributos basados en reductos, derivados de la teoría de conjuntos aproximados (rough set theory), en relación con el rendimiento de la clasificación supervisada. Considerando veintiún conjuntos de datos, se evaluaron dos representaciones: reductos de longitud mínima, que contienen los conjuntos de atributos más pequeños necesarios para conservar la consistencia, y reductos de longitud máxima, que comprenden los subconjuntos irredundantes de mayor tamaño. Se utilizó una prueba de Friedman–Nemenyi para evaluar once clasificadores mediante cinco medidas de calidad. Para la mayoría de los clasificadores, ambos tipos de reductos reducen sistemáticamente el rendimiento predictivo en compar…
creator: Manuel S. Lazo-Cortés
creator: Rafael Rodríguez-Puente
creator: Adolfo Diaz-Sardinas
rights: Copyright (c) 2026 International Journal of Combinatorial Optimization Problems and Informatics https://creativecommons.org/licenses/by-nc-nd/4.0/
license: https://creativecommons.org/licenses/by-nc-nd/4.0/
date: 2026-09-06
publication date: 2026-09-06
volume: 17
number: 5
starting page: 37
ending page: 43
doi: 10.61467/2007.1558.2026.v17i5.1273

Systemic Approach to Injury Phenomenology in Generation Z Padel: Biomechanical Interrelationships and Physical Armor
type: item
description: This article examines injury patterns among Generation Z padel players through a complex systems lens. It argues that injuries are not isolated accidents but disruptions in the body's biomechanical homeostasis caused by explosive movements and rigid equipment (e.g., carbon fiber rackets). The researchers propose a "Physical Shielding" (Blindaje Físico) model, a preventive approach focused on restoring "tensegrity" and enhancing the body's resilience to mechanical stress. A key finding is the significance of prodromal states—subtle warning signs like minor inflammation that are often ignored by young athletes in favor of performance. The study reveals gender-specific patterns: men are more prone to shoulder issues, while women experience higher rates of tennis elbow (epicondylitis). Ultimately, the study advocates for a shift from traditional fitness goals to a holistic "pre-habilitation" strategy that integrates ergonomic adjustments, eccentric training, and biological self-awareness. Spanish-language metadata / Metadatos en español Título en español: Enfoque sistémico de la fenomenología de las lesiones en el pádel de la Generación Z: interrelaciones biomecánicas y blindaje físico Resumen: Este artículo examina los patrones de lesión entre jugadores de pádel de la Generación Z desde la perspectiva de los sistemas complejos. Sostiene que las lesiones no constituyen accidentes aislados, sino alteraciones de la homeostasis biomecánica del cuerpo provocadas por movimientos explosivos y equipamiento rígido, como las palas de fibra de carbono. Los investigadores proponen un modelo de «Blindaje Físico», un enfoque preventivo centrado en restaurar la «tensegridad» y aumentar la capacidad del cuerpo para resistir el estrés mecánico. Un hallazgo clave es la importancia de los estados prodrómicos, es decir, señales de advertencia sutiles, como inflamaciones leves, que los atletas jóvenes suelen ignorar en favor del rendimiento. El estudio revela patrones específicos según el …
creator: Luis Gerardo Valle Cervantes
creator: Alberto O. Ortiz-Zezzatti
rights: Copyright (c) 2026 International Journal of Combinatorial Optimization Problems and Informatics https://creativecommons.org/licenses/by-nc-nd/4.0/
license: https://creativecommons.org/licenses/by-nc-nd/4.0/
date: 2026-09-06
publication date: 2026-09-06
volume: 17
number: 5
starting page: 44
ending page: 60
doi: 10.61467/2007.1558.2026.v17i5.1408

Cayley–Hamilton-Guided Krylov Regularization for Machine Learning: Theory, Computational Architecture, and Empirical Evidence
type: item
description: This study develops and evaluates a Cayley–Hamilton-based framework for regularised machine learning. Its objective is to formulate a practical Krylov-subspace architecture for classification that replaces repeated dense inversion with stable operator iteration. The formulation draws on the theorem’s finite polynomial closure for square matrices. The analysis connects the characteristic-polynomial identity with regularised least-squares learning, derives full and truncated conjugate-gradient solvers, and evaluates the proposed method on four datasets. Full conjugate gradients reproduce the direct solution to machine precision, whereas truncated iteration preserves competitive predictive accuracy while reducing training cost and showing greater tolerance to perturbations in ill-conditioned data. These findings support the interpretation of the Cayley–Hamilton theorem not merely as an algebraic identity, but as a design principle for finite-dimensional learning operators, efficient computation and interpretable matrix-polynomial models. Spanish-language metadata / Metadatos en español Título en español: Regularización de Krylov guiada por Cayley–Hamilton para aprendizaje automático: Teoría, arquitectura computacional y evidencia empírica Resumen: Este estudio desarrolla y evalúa un marco basado en Cayley–Hamilton para el aprendizaje automático regularizado. Su objetivo es formular una arquitectura práctica de subespacios de Krylov para clasificación que sustituya la inversión densa repetida por una iteración estable de operadores. La formulación se fundamenta en el cierre polinómico finito del teorema para matrices cuadradas. El análisis vincula la identidad del polinomio característico con el aprendizaje regularizado mediante mínimos cuadrados, deriva solucionadores de gradiente conjugado completos y truncados, y evalúa el método propuesto en cuatro conjuntos de datos. Los gradientes conjugados completos reproducen la solución directa con precisión de máquina, mientr…
creator: Jaime Aguilar-Ortiz
rights: Copyright (c) 2026 International Journal of Combinatorial Optimization Problems and Informatics https://creativecommons.org/licenses/by-nc-nd/4.0/
license: https://creativecommons.org/licenses/by-nc-nd/4.0/
date: 2026-09-06
publication date: 2026-09-06
volume: 17
number: 5
starting page: 61
ending page: 79
doi: 10.61467/2007.1558.2026.v17i5.1420

Comparative Benchmark of Eleven Regression Models for Software Effort Estimation on a COCOMO-Like Dataset
type: item
description: This study develops a comparative benchmark for software effort estimation using the benchmark suite implemented in Python and the result package generated by that suite. Eleven regressors were compared under a leakage-safe protocol on a COCOMO-like dataset of 62 projects and 20 numeric predictors, with 49 projects reserved for model development and 13 for final hold-out testing. The evaluated methods were a three-hidden-layer deep neural network, CatBoost, XGBoost, stacked ensemble regression, random forest, support vector regression with radial basis kernel, Gaussian process regression, LightGBM, an optimized M5P model tree, gradient boosting, and AdaBoost. Model quality was judged through repeated 5×2 cross-validation on the training partition and through an independent hold-out test set, using MAE, RMSE, R², MMRE, MdMRE, and PRED(25). The repeated-CV ranking identified Gaussian process regression as the most accurate and stable model, with mean rank = 1.0000, RMSE = 0.2152, R² = 0.8998, and PRED(25) = 0.9289. The same model also dominated the hold-out evaluation, achieving MAE = 0.1444, RMSE = 0.1835, R² = 0.9084, MMRE = 0.0850, MdMRE = 0.0634, and PRED(25) = 0.9231. The overall order of precision from repeated cross-validation was: Gaussian process regression, optimized model tree (M5P), stacked ensemble regressor, gradient boosting regressor, XGBoost regressor, random forest regressor, CatBoost regressor, AdaBoost regressor, support vector regression, deep neural network, and LightGBM regressor. Permutation importance of the best model showed KDSI, ACAP, PCAP, RELY, and AAF as the most influential predictors. The evidence indicates that, for the present small-sample COCOMO-like setting, kernel-based and piecewise linear/tree-based methods outperform the deeper neural alternative. Spanish-language metadata / Metadatos en español Título en español: Benchmark comparativo de once modelos de regresión para la estimación del esfuerzo de software en un conjunto de da…
creator: Jaime Aguilar-Ortiz
creator: Víctor M. Zamudio-García
creator: Marcos Yamir Gómez-Ramos
creator: Carlos R. Domínguez-Mayorga
rights: Copyright (c) 2026 International Journal of Combinatorial Optimization Problems and Informatics https://creativecommons.org/licenses/by-nc-nd/4.0/
license: https://creativecommons.org/licenses/by-nc-nd/4.0/
date: 2026-09-06
publication date: 2026-09-06
volume: 17
number: 5
starting page: 80
ending page: 105
doi: 10.61467/2007.1558.2026.v17i5.1441

A Genetic Algorithm Framework for Efficient Electric Patient Transportation
type: item
description: The transportation of individuals with limited mobility, such as the elderly, persons with disabilities, and pregnant women, to various healthcare facilities for medical appointments poses a significant logistical challenge, particularly in urban areas where mobility is can be complicated by diverse factors. This study proposes the design and implementation of an efficient route planning system that incorporates time window constraints for pick-up, drop-off and travel times for each service requestor, utilizing a fleet of low-capacity electric vehicles. The project merges an insertion heuristic in its first phase to obtain initial solutions with a genetic algorithm in its second phase to refine these solutions, generating feasible and more effective routes. The primary objectives are to minimize the total service time and carbon dioxide emissions while ensuring the satisfaction of patients' specific demands. Several experiments were conducted, varying key system parameters across different scenarios. The results are significant, demonstrating the shortest travel times for each generated route. Furthermore, the findings provide a sustainable alternative that can be replicated in various urban settings. Spanish-language metadata / Metadatos en español Título en español: Marco basado en algoritmos genéticos para el transporte eléctrico eficiente de pacientes Resumen: El transporte de personas con movilidad limitada, como adultos mayores, personas con discapacidad y mujeres embarazadas, hacia distintos centros sanitarios para acudir a citas médicas plantea un importante desafío logístico, especialmente en áreas urbanas donde la movilidad puede verse dificultada por diversos factores. Este estudio propone el diseño y la implementación de un sistema eficiente de planificación de rutas que incorpora restricciones de ventanas de tiempo para la recogida, el traslado, la llegada al destino y los tiempos de viaje correspondientes a cada solicitante del servicio, utilizando una…
creator: Rodolfo Eleazar Pérez Loaiza
creator: Edmundo Bonilla Huerta
creator: Aaron Guerrero Campanur
creator: Ricardo Pérez Cabrera
rights: Copyright (c) 2026 International Journal of Combinatorial Optimization Problems and Informatics https://creativecommons.org/licenses/by-nc-nd/4.0/
license: https://creativecommons.org/licenses/by-nc-nd/4.0/
date: 2026-09-06
publication date: 2026-09-06
volume: 17
number: 5
starting page: 106
ending page: 120
doi: 10.61467/2007.1558.2026.v17i5.1328

Optimization of Multi-modal Relaxometry MR Acquisitions for Estimating Quantitative Brain Microstructure Parameters
type: item
description: This study addresses the optimization of MRI acquisition protocols to improve the estimation of brain microstructure descriptors, with a focus on the myelin fraction. The problem is formulated as a binary optimization task with constraints, where each decision variable encodes whether a specific repetition time is included in the protocol. Each candidate protocol is evaluated through an objective function that quantifies the relative error in the estimation of the myelin fraction. Different approximated optimization strategies were analyzed, including local search and memetic algorithms with and without explicit diversity control. Under realistic acquisition conditions, population-based strategies outperformed both local search and fixed reference protocols, reducing the relative estimation error by over 30%. These findings highlight the potential of systematic optimization in MRI acquisition protocol design. Spanish-language metadata / Metadatos en español Título en español: Optimización de adquisiciones de relaxometría multimodal por RM para estimar parámetros cuantitativos de la microestructura cerebral Resumen: Este estudio aborda la optimización de protocolos de adquisición de resonancia magnética (RM) con el objetivo de mejorar la estimación de descriptores de la microestructura cerebral, con especial atención a la fracción de mielina. El problema se formula como una tarea de optimización binaria con restricciones, en la que cada variable de decisión codifica si un tiempo de repetición específico se incluye o no en el protocolo. Cada protocolo candidato se evalúa mediante una función objetivo que cuantifica el error relativo en la estimación de la fracción de mielina. Se analizaron distintas estrategias aproximadas de optimización, entre ellas la búsqueda local y algoritmos meméticos con y sin control explícito de la diversidad. Bajo condiciones realistas de adquisición, las estrategias basadas en poblaciones superaron tanto a la búsqueda local como a los prot…
creator: Ashley Dafne Aguilar-Salinas
creator: Alonso Ramírez-Manzanares
creator: Ramon Orlando Ruiz-Olais
creator: Carlos Segura
rights: Copyright (c) 2026 International Journal of Combinatorial Optimization Problems and Informatics https://creativecommons.org/licenses/by-nc-nd/4.0/
license: https://creativecommons.org/licenses/by-nc-nd/4.0/
date: 2026-09-06
publication date: 2026-09-06
volume: 17
number: 5
starting page: 121
ending page: 137
doi: 10.61467/2007.1558.2026.v17i5.1191

Quantifying Perceptual Uncertainty through Non-Invasive Kinematic Tracking: A Convolutional Neural Network-Based Approach for Digital Biomarker Development
type: item
description: The analysis of human motor function is considered fundamental in the biomedical and clinical fields, as it allows us to understand how sensory information is transformed into motor responses. In this study, we proposed an analytical design that combined a visual discrimination task with non-invasive tracking of hand trajectories, using convolutional neural networks (CNNs) applied to video analysis. Five young adults (aged 24 to 34) participated in a perceptual task in which they had to decide whether a pattern of static black bars was regular or irregular. The difficulty of the task was controlled by spatial variation, defined as controlled variations in the spacing between the bars. Behavioral variables, such as accuracy and reaction time, were recorded, along with kinematic parameters such as path length, linearity index, maximum velocity, and variability. The results showed that irregular stimuli were associated with lower accuracy, longer reaction times, and greater variability in motor performance compared to regular stimuli. These findings indicate that perceptual difficulty is reflected not only in behavioral performance but also in the fine structure of motor execution. This work highlights the potential of non-invasive tracking and computer vision for the development of kinematic biomarkers of confidence in decision-making, with applications in the early detection and monitoring of motor and chronic-degenerative disorders. Spanish-language metadata / Metadatos en español Título en español: Cuantificación de la incertidumbre perceptiva mediante seguimiento cinemático no invasivo: un enfoque basado en redes neuronales convolucionales para el desarrollo de biomarcadores digitales Resumen: El análisis de la función motora humana se considera fundamental en los ámbitos biomédico y clínico, ya que permite comprender cómo la información sensorial se transforma en respuestas motoras. En este estudio se propuso un diseño analítico que combinó una tarea de discrimin…
creator: Alberto Nicolas López Moreno
creator: Geovanni Hernández Gomez
creator: José Manuel López-Villagómez
creator: Juan Manuel López-Hernández
rights: Copyright (c) 2026 International Journal of Combinatorial Optimization Problems and Informatics https://creativecommons.org/licenses/by-nc-nd/4.0/
license: https://creativecommons.org/licenses/by-nc-nd/4.0/
date: 2026-09-06
publication date: 2026-09-06
volume: 17
number: 5
starting page: 138
ending page: 152
doi: 10.61467/2007.1558.2026.v17i5.1306

Fuzzy Logic and Computer Vision-Based Control Strategy for Line Following in an Omnidirectional Autonomous Mobile Robot
type: item
description: This article presents the design of a vision-based line-following control strategy for an omnidirectional mobile robot operating on surfaces marked by lines. The proposed approach combines computer vision techniques with a Mamdani-type fuzzy controller to generate motion commands directly from visual feedback. Image acquisition is performed using an onboard webcam with a resolution of 320 × 240 pixels, enabling continuous real-time capture. The Prewitt filter is applied to detect edges and extract the position of the line from a defined region of interest. Based on the processed images, the lateral deviation of the robot with respect to the image centre is computed and used as input to the fuzzy controller. The controller generates forward linear and angular velocity commands following a feedforward control structure. Simulation results obtained using an omnidirectional mobile robot model demonstrate stable and smooth line-following behaviour, showing that the proposed system is capable of tracking the trajectory without losing the reference line under the tested conditions. Spanish-language metadata / Metadatos en español Título en español: Estrategia de control basada en lógica difusa y visión por computador para el seguimiento de líneas en un robot móvil autónomo omnidireccional Resumen: Este artículo presenta el diseño de una estrategia de control para el seguimiento de líneas basada en visión, destinada a un robot móvil omnidireccional que opera sobre superficies marcadas con líneas. El enfoque propuesto combina técnicas de visión por computador con un controlador difuso de tipo Mamdani para generar comandos de movimiento directamente a partir de la retroalimentación visual. La adquisición de imágenes se realiza mediante una cámara web integrada con una resolución de 320 × 240 píxeles, lo que permite una captura continua en tiempo real. Se aplica el filtro de Prewitt para detectar bordes y extraer la posición de la línea dentro de una región de interés definida…
creator: Jacinto González-Aguilar
creator: Oscar Castillo
creator: Prometeo Cortés-Antonio
rights: Copyright (c) 2026 International Journal of Combinatorial Optimization Problems and Informatics https://creativecommons.org/licenses/by-nc-nd/4.0/
license: https://creativecommons.org/licenses/by-nc-nd/4.0/
date: 2026-09-06
publication date: 2026-09-06
volume: 17
number: 5
starting page: 153
ending page: 167
doi: 10.61467/2007.1558.2026.v17i5.1531

RAÍZ: A Hybrid Architecture Based on Linguistic Knowledge and Deep Learning for the Machine Translation of Low-Resource Indigenous Languages
type: item
description: Indigenous languages continue to experience significant technological marginalisation due to limited digital corpora, orthographic inconsistency, dialectal variation, morphological complexity, and insufficient representation in contemporary natural language processing systems. This study introduces RAÍZ, a hybrid machine translation architecture designed for low-resource Indigenous languages. The proposed framework combines Transformer-based multilingual modelling with linguistically informed components, including phonetic normalisation, morphological segmentation, semantic contextualisation, lexical retrieval mechanisms, and community-centred validation procedures involving native speakers. The architecture was evaluated using Spanish–Nahuatl and Spanish–Mazahua translation tasks through a mixed evaluation strategy integrating BLEU, chrF, and COMET metrics alongside qualitative assessment focused on clarity, naturalness, semantic fidelity, and cultural appropriateness. Experimental results indicate that RAÍZ achieved 28.6 BLEU, 56.8 chrF, and 74% COMET in the Spanish–Nahuatl task, while obtaining 27.4 BLEU, 54.9 chrF, and 71% COMET for Spanish–Mazahua translation. The findings suggest that hybrid and linguistically grounded approaches can improve translation robustness in low-resource settings while supporting culturally sensitive language technologies. The study further highlights the importance of combining neural architectures with community participation and explicit linguistic knowledge in the development of more inclusive machine translation systems for Indigenous languages. Spanish-language metadata / Metadatos en español Título en español: RAÍZ: Una arquitectura híbrida basada en conocimiento lingüístico y aprendizaje profundo para la traducción automática de lenguas indígenas con pocos recursos Resumen: Las lenguas indígenas continúan experimentando una importante marginación tecnológica debido a la disponibilidad limitada de corpus digitales, la inconsist…
creator: Gabriela Salas-Cabrera
creator: Aníbal Alejandro Gallegos-Macías
creator: Francisco R. Trejo-Macotela
rights: Copyright (c) 2026 International Journal of Combinatorial Optimization Problems and Informatics https://creativecommons.org/licenses/by-nc-nd/4.0/
license: https://creativecommons.org/licenses/by-nc-nd/4.0/
date: 2026-09-06
publication date: 2026-09-06
volume: 17
number: 5
starting page: 168
ending page: 182
doi: 10.61467/2007.1558.2026.v17i5.1451

Generative Artificial Intelligence: Ethical challenges and pedagogical implications in emerging educational contexts
type: item
description: Generative Artificial Intelligence (GAI) has rapidly transformed higher education by introducing new possibilities for personalized learning and pedagogical innovation. It has emerged as a powerful support system capable of information processing and decision-making tasks in higher education. Unlike traditional educational technologies, models such as ChatGPT enable dynamic interaction with learners. Students engage with knowledge, complete academic tasks, and regulate their performance. Building upon previous studies, this article incorporates an expanded theorical framework, and a deeper ethical analysis of student perceptions and emotions, emphasizing its role as a support tool in their learning processes. The results suggest that while ChatGPT enhances efficiency, accessibility, and learner autonomy, it also introduces significant risks related to overreliance, academic integrity, and the loss of critical thinking skills. The study concludes that should be integrated as an academic mediator, emphasizing the need for ethical guidelines and pedagogical institutional redesign. Spanish-language metadata / Metadatos en español Título en español: Inteligencia Artificial Generativa: desafíos éticos e implicaciones pedagógicas en contextos educativos emergentes Resumen: La Inteligencia Artificial Generativa (IAG) ha transformado rápidamente la educación superior al introducir nuevas posibilidades para el aprendizaje personalizado y la innovación pedagógica. Se ha consolidado como un potente sistema de apoyo capaz de realizar tareas de procesamiento de información y toma de decisiones en el ámbito de la educación superior. A diferencia de las tecnologías educativas tradicionales, modelos como ChatGPT permiten una interacción dinámica con los estudiantes. Estos interactúan con el conocimiento, realizan tareas académicas y regulan su propio desempeño. A partir de estudios previos, este artículo incorpora un marco teórico ampliado y un análisis ético más profundo de las per…
creator: Ana Paulina Alfaro Rodríguez
creator: Mónica del Carmen Olivarría González
creator: Héctor Luis López López
creator: Rosa Leticia Ibarra Martínez
rights: Copyright (c) 2026 International Journal of Combinatorial Optimization Problems and Informatics https://creativecommons.org/licenses/by-nc-nd/4.0/
license: https://creativecommons.org/licenses/by-nc-nd/4.0/
date: 2026-09-06
publication date: 2026-09-06
volume: 17
number: 5
starting page: 183
ending page: 194
doi: 10.61467/2007.1558.2026.v17i5.1300

Performance Analysis of Web Microservices with Technological Convergence between REST and GraphQL API Architectures
type: item
description: Efficient data exchange between heterogeneous systems is a critical need in modern software development. REST API and GraphQL API are the dominant paradigms for web microservices implementation; however, the scientific community has not reached a consensus on which offers better performance. Both technologies offer complementary strengths worth of studying, while REST has better response time and throughput, GraphQL improves on resource consumption. This paper presents a controlled and reproducible experiment that evaluates server response time when combining both technologies in different proportions within the development of a system. Microservices were designed by combining REST and GraphQL technologies on a basic generic user management case study; a set of 32 microservices web designs, each composed by five CRUD operations and operating with server request volumes ranging from 1 to 10, accumulating up to 76,800 requests. Findings show that a web service design involving the management of 4 CRUD operations by REST and 1 by GraphQL achieves comparable or superior median response times in contrast with a design that implements all operations using REST. Particularly, when one of the read or create CRUD operations is implemented using GraphQL and the remaining with REST the response time is minimized. In the other hand, implementing one of the update or delete CRUD operations with GraphQL causes a significative worst performance. These results provide empirical evidence of the requirements that a web microservices must meet to improve its design from the combination of REST and GraphQL technologies. Hence, strategic integration of GraphQL and REST in web microservice design might result in overall performance improvements, opposing the common sense that dictates using REST will always results in the best response times. Spanish-language metadata / Metadatos en español Título en español: Análisis del rendimiento de microservicios web con convergencia tecnológica ent…
creator: Carlos Arturo Aguilar-Díaz
creator: Nelson Rangel-Valdez
creator: María Lucila Morales-Rodríguez
creator: Guadalupe Castilla-Valdez
creator: Claudia Guadalupe Gómez-Santillán
creator: Ana Lidia Martínez-Salazar
creator: Pedro Martín García-Vite
rights: Copyright (c) 2026 International Journal of Combinatorial Optimization Problems and Informatics https://creativecommons.org/licenses/by-nc-nd/4.0/
license: https://creativecommons.org/licenses/by-nc-nd/4.0/
date: 2026-09-06
publication date: 2026-09-06
volume: 17
number: 5
starting page: 195
ending page: 211
doi: 10.61467/2007.1558.2026.v17i5.1412