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: A Comprehensive Comparative Study of Toxic Language Detection in Roman Urdu Using Hybrid Machine Learning, Deep Learning, and LoRA-Optimized Transformer Models
items: Lightweight Face Anti-Spoofing with MobileNetV2: Transfer Learning, Model Compression, and Evaluation on LCC-FASD
items: Automatic design of convolutional neural network architectures using multi-objective metaheuristics for classification of medical databases
items: Type-1 and Type-2 Fuzzy Parameter Adaptation in PSO for CNN Architecture Optimization Applied to Facial Emotion Recognition
items: Systematic Literature Review of 3D Object Replacement Algorithms in Live Broadcasts
items: Unveiling Structural Dynamics in Supply Chains' Resilience: A Multi-Effect High-Frequency Panel Analysis
items: Numerically Stable and Reproducible Mittag–Leffler Evaluation for Fractional Kelvin–Voigt Creep Modelling
items: Optimal Design of PID Controller Parameters with Particle Swarm Optimization for Quadrotors
items: Method for migrating monolithic software systems and their global database to isolated microservices
items: Development of an algorithm to detect SQL vulnerabilities in PHP web pages for students of the Bachelor's Degree in Information Technology at a Mexican university
items: Design of a multilayer neural network in only two rows of an Excel spreadsheet for students without advanced programming knowledge
items: Evaluating the SEMMA Methodology with AutoML Across Phishing Detection, Pollen Classification, and Voice Identification Tasks
items: Ethical Governance of Artificial Intelligence in Higher Education: A Systematic Review and a Proposed Socio-Technical Framework for Smart Educational Environments
items: DevSecOps for Secure Software Development: A Systematic Literature Review of Practices, Benefits, and Adoption Barriers
items: Dynamic Load Balancing and Fault Tolerance for Machine Learning Deployments Using a Process Control Table
items: Fine-Tuning TrOCR for Automatic Number Plate Recognition: A YOLOv11-Based Comparison with Tesseract and EasyOCR
items: A Genetic algorithm-based optimization of CFD virtual test environments for axial cooling fan characteristic curves
items: An AI-Enabled Smart City Architecture for Monitoring and Specialised Care of People with Sarcopenic Obesity

A Comprehensive Comparative Study of Toxic Language Detection in Roman Urdu Using Hybrid Machine Learning, Deep Learning, and LoRA-Optimized Transformer Models
type: item
description: The rapid growth of social media has intensified the spread of toxic language, abusive comments, and harmful online discourse, creating serious challenges for digital safety and automated moderation. This study presents a comprehensive framework for toxic language detection in Roman Urdu using machine learning, deep learning, and transformer-based approaches. First, we do the preprocessing and normalization, then text features were extracted using TF-IDF and Count Vectorizer with unigram, bigram, trigram, and combined n-gram settings. The classification models included Naive Bayes, Logistic Regression, Random Forest, Support Vector Machine, Decision Tree, AdaBoost, XGBoost, Convolutional Neural Network, Bidirectional Long Short-Term Memory, and LLaMA 3 fine-tuned with Low-Rank Adaptation. Experimental findings show that transformer-based fine-tuning produced the strongest results, with LLaMA 3 + LoRA achieving the highest F1-score of 96.78%, outperforming all baseline machine learning and deep learning models. Among conventional methods, XGBoost and Support Vector Machine demonstrated strong and stable performance, while CNN emerged as the best-performing deep learning baseline. The results confirm that parameter-efficient transformer adaptation is highly effective for toxic language detection in Roman Urdu and provides a scalable solution for content moderation in low-resource multilingual settings. Spanish-language metadata / Metadatos en español Título en español: Un estudio comparativo exhaustivo sobre la detección de lenguaje tóxico en urdu romanizado mediante modelos híbridos de aprendizaje automático, aprendizaje profundo y transformadores optimizados con LoRA. Resumen: El rápido crecimiento de las redes sociales ha intensificado la propagación del lenguaje tóxico, los comentarios abusivos y los discursos perjudiciales en línea, lo que plantea importantes desafíos para la seguridad digital y la moderación automatizada. Este estudio presenta un marco integral …
creator: Abdul Jabbar
creator: Muhammad Jawad Nadeem
creator: Nisar Hussain
creator: Amna Qasim
creator: Momina Hafeez
creator: Grigori Sidorov
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: 2026-08-02
publication date: 2026-08-02
volume: 17
number: 4
starting page: 105
ending page: 114
doi: 10.61467/2007.1558.2026.v17i4.1528

Lightweight Face Anti-Spoofing with MobileNetV2: Transfer Learning, Model Compression, and Evaluation on LCC-FASD
type: item
description: Face recognition systems remain vulnerable to presentation attacks involving printed photographs, replayed videos, and three-dimensional masks, creating a need for accurate and computationally efficient face anti-spoofing methods. This study proposes a lightweight deep learning framework based on MobileNetV2 for detecting genuine and spoofed facial presentations. The model employs transfer learning and fine-tuning and is trained and evaluated on the Large Crowd-Collected Face Anti-Spoofing Dataset (LCC-FASD), which contains genuine and spoofed facial samples captured under varying conditions. The framework integrates image preprocessing, data augmentation, and hyperparameter optimisation to improve classification performance and generalisation. Experimental results show a precision of 95.86%, a recall of 98.45%, and an F1-score of 97.88%. Training and validation analyses, confusion-matrix evaluation, and receiver operating characteristic analysis further support the stability of the classification results. Pruning and quantisation are also applied to reduce computational complexity while preserving competitive detection performance. The resulting lightweight framework is suitable for biometric authentication systems, mobile devices, online identity-verification platforms, and edge-based security applications. The study demonstrates the potential of MobileNetV2 for efficient face anti-spoofing and provides a basis for future research on advanced presentation attacks, including deepfakes and three-dimensional masks. Spanish-language metadata / Metadatos en español Título en español: Detección ligera de ataques de suplantación facial con MobileNetV2: aprendizaje por transferencia, compresión del modelo y evaluación en LCC-FASD Resumen: Los sistemas de reconocimiento facial continúan siendo vulnerables a ataques de presentación mediante fotografías impresas, videos reproducidos y máscaras tridimensionales, lo que genera la necesidad de métodos precisos y computacionalme…
creator: Muhammad Abbas
creator: Muhammad Munib
creator: Muhammad Sajid
creator: Maryam Mazher
creator: Umme Kalsoom
creator: Liliana Chanona-Hernandez
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: 2026-08-02
publication date: 2026-08-02
volume: 17
number: 4
starting page: 115
ending page: 133
doi: 10.61467/2007.1558.2026.v17i4.1529

Automatic design of convolutional neural network architectures using multi-objective metaheuristics for classification of medical databases
type: item
description: Convolutional neural networks (CNNs) have been used for different classification tasks, achieving superior performance to machine learning techniques. However, it is necessary to modify the hyperparameters, as their performance depends on the value assigned to them, and the empirical design of CNNs requires a lot of time and effort. Therefore, in this work, we propose a generic methodology, Neural Architecture Search (NAS), to automatically find architectures that classify different medical databases from literature, generating new models that maximize efficiency through the F1 score and minimize the number of parameters. The results of a single-objective (GA) and multi-objective (NSGA-II) genetic algorithm that generated a single architecture for three different medical databases were compared, obtaining an F1 score of 2.9 and 2.831 out of a total of 3 (1 for each database) as the best performance result, respectively. Although results show that the GA got better results than the NSGA-II, the latter took a sixth of the execution time to find the solution compared to the GA. The proposed generic method, with hyperparameter encoding in predefined ranges, allows binary medical databases (e.g., pneumonia or no pneumonia) to be classified efficiently with a single architecture. Spanish-language metadata / Metadatos en español Título en español: Diseño automático de arquitecturas de redes neuronales convolucionales mediante metaheurísticas multiobjetivo para la clasificación de bases de datos médicas Resumen: Las redes neuronales convolucionales (CNN) se han utilizado en diferentes tareas de clasificación y han alcanzado un desempeño superior al de las técnicas de aprendizaje automático. Sin embargo, es necesario modificar sus hiperparámetros, ya que su desempeño depende de los valores que se les asignen, y el diseño empírico de las CNN requiere una cantidad considerable de tiempo y esfuerzo. Por lo tanto, en este trabajo se propone una metodología genérica de búsqueda d…
creator: María Susana Ávila García
creator: Erick Franco-Gaona
creator: Ivan Cruz-Aceves
creator: Arturo Hernandez-Aguirre
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: 2026-08-02
publication date: 2026-08-02
volume: 17
number: 4
starting page: 134
ending page: 151
doi: 10.61467/2007.1558.2026.v17i4.1213

Type-1 and Type-2 Fuzzy Parameter Adaptation in PSO for CNN Architecture Optimization Applied to Facial Emotion Recognition
type: item
description: It is known that through the use of Convolutional Neural Networks (CNNs) classification problems can be solved, such as facial emotion classification. Fuzzy logic has allowed to reduce the uncertainty that may exist when making a decision. In our work, a convolutional neural network model is proposed that allows, through a fuzzy Mamdani inference system, to choose the optimal hyperparameters within Particle Swarm Optimization (PSO), adjusting variables such as inertial weight and cognitive and social acceleration coefficients, in order to determine the number of convolutional layers and filters to be used within the CNN model. We evaluate Type-1 and interval Type-2 fuzzy adaptation within an identical search space and training setup, focusing on how the treatment of uncertainty shapes the quality of the resulting architectures. The experimental results allow an evaluation of the proposed hybrid system for facial emotion classification using the FER2013 dataset. Spanish-language metadata / Metadatos en español Título en español: Adaptación difusa de parámetros de tipo 1 y tipo 2 en PSO para la optimización de arquitecturas CNN aplicada al reconocimiento de emociones faciales Resumen: Es bien sabido que las redes neuronales convolucionales (CNN) permiten resolver problemas de clasificación, como la clasificación de emociones faciales. La lógica difusa ha contribuido a reducir la incertidumbre que puede existir durante la toma de decisiones. En este trabajo se propone un modelo de red neuronal convolucional que, mediante un sistema de inferencia difusa de Mamdani, permite seleccionar los hiperparámetros óptimos dentro de la optimización por enjambre de partículas (PSO). Para ello, se ajustan variables como el peso de inercia y los coeficientes de aceleración cognitiva y social, con el propósito de determinar el número de capas convolucionales y filtros que deben utilizarse en el modelo CNN. Se evalúan la adaptación difusa de tipo 1 y la adaptación difusa de tipo 2 por …
creator: Alexis Campos
creator: Patricia Melin
creator: Daniela Sanchez
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: 2026-08-02
publication date: 2026-08-02
volume: 17
number: 4
starting page: 152
ending page: 170
doi: 10.61467/2007.1558.2026.v17i4.1486

Systematic Literature Review of 3D Object Replacement Algorithms in Live Broadcasts
type: item
description: The exponential growth of live broadcasts has exacerbated the exposure of vulnerable audiences to inappropriate visual content, surpassing the capabilities of traditional reactive moderation. This systematic literature review investigates the potential of 3D object replacement algorithms as a proactive real-time solution. By analyzing research from the last five years, the study identifies key methodologies in photogrammetry, deep learning, and physically based rendering capable of dynamic substitution. Results indicate that while detection and modeling technologies are advanced, significant challenges regarding latency and visual coherence in dynamic environments remain. The paper concludes that integrating these technologies offers a promising pathway for automating content safety, particularly for protecting minors, though further research on real-time optimization is required. Spanish-language metadata / Metadatos en español Título en español: Revisión sistemática de la literatura sobre algoritmos de reemplazo de objetos 3D en transmisiones en vivo Resumen: El crecimiento exponencial de las transmisiones en vivo ha incrementado la exposición de audiencias vulnerables a contenidos visuales inapropiados, superando las capacidades de la moderación reactiva tradicional. Esta revisión sistemática de la literatura investiga el potencial de los algoritmos de reemplazo de objetos 3D como una solución proactiva en tiempo real. Mediante el análisis de investigaciones publicadas durante los últimos cinco años, el estudio identifica metodologías clave de fotogrametría, aprendizaje profundo y renderizado basado en principios físicos capaces de realizar sustituciones dinámicas. Los resultados indican que, aunque las tecnologías de detección y modelado se encuentran avanzadas, persisten desafíos importantes relacionados con la latencia y la coherencia visual en entornos dinámicos. El artículo concluye que la integración de estas tecnologías ofrece una vía prometedora para auto…
creator: Alexandra Polo Martinez
creator: Miguel Caro Alvárez
creator: Jorge Manuel Barrios Sánchez
creator: Udualdo Herrera-García
creator: Jairo Acosta-Solano
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: 2026-08-02
publication date: 2026-08-02
volume: 17
number: 4
starting page: 171
ending page: 179
doi: 10.61467/2007.1558.2026.v17i4.1330

Unveiling Structural Dynamics in Supply Chains' Resilience: A Multi-Effect High-Frequency Panel Analysis
type: item
description: This study introduces a new way to predict Supply Chain Resilience (SCR) by combining resilience stages, logistical multi-effects (like Synchronization, Spillover, Bullwhip, Ripple, and Economic effects), and strategic decision-making scenarios. A hierarchical nonlinear state-space model assesses resilience velocity in panel data by integrating structural dynamics, memory effects, and latent exogenous shocks. A Bayesian hierarchical particle filter with partial pooling is used to find the parameters. This method looks at changes at both the unit level and the global level. The framework includes nonlinear relative-change dynamics, an autoregressive memory part, and a latent exogenous variable found through principal component analysis. It also uses methods for updating strong likelihoods and resampling in a way that adapts. Transfer Entropy shows how things are connected in a dynamic way. The model is used to look at the Mexican maritime port system from 2008 to 2023, which includes the COVID-19 pandemic and the global financial crisis. The results indicate that Synchronization serves as the primary resilience driver, Bullwhip functions as an early-warning signal, persistent negative Spillovers occur, and Ripple effects are context-dependent. We use evaluation metrics and visualizations to check how well the model works. Spanish-language metadata / Metadatos en español Título en español: Revelando la dinámica estructural de la resiliencia de las cadenas de suministro: un análisis de panel de alta frecuencia con múltiples efectos Resumen: Este estudio introduce una nueva forma de predecir la resiliencia de las cadenas de suministro mediante la combinación de las etapas de resiliencia, múltiples efectos logísticos —como los efectos de sincronización, desbordamiento, látigo, propagación y económico— y escenarios estratégicos de toma de decisiones. Un modelo jerárquico no lineal de espacio de estados evalúa la velocidad de resiliencia en datos de panel mediante la integ…
creator: Fabricio Moreno-Baca
creator: Tomas Veloz
creator: Patricia Cano-Olivos
creator: Diana Sánchez-Partida
creator: José-Luis Martínez-Flores
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: 2026-08-02
publication date: 2026-08-02
volume: 17
number: 4
starting page: 180
ending page: 204
doi: 10.61467/2007.1558.2026.v17i4.1317

Numerically Stable and Reproducible Mittag–Leffler Evaluation for Fractional Kelvin–Voigt Creep Modelling
type: item
description: Fractional Kelvin–Voigt models capture long-memory behaviour in viscoelastic creep, but their numerical implementation depends on the Mittag–Leffler function. Naive evaluation of this function can cause overflow, loss of numerical significance, and nonphysical creep responses, thereby compromising constitutive interpretation and parameter calibration. This study develops and validates a numerically stable and reproducible Mittag–Leffler evaluator for time-domain creep simulations under constant stress. Reliability is assessed through four operational criteria: bounded special-function values on the negative real axis, preservation of monotonic decay, low benchmark error relative to a trusted reference, and improved creep fidelity compared with the best classical Kelvin–Voigt baseline. The proposed implementation combines regime-aware series and asymptotic evaluation, a calibrated branch-switching policy, overflow-safe safeguards, and reproducibility controls. Supplementary ablation and synthetic-noise experiments show that the evaluator remains suitable for calibration-oriented fractional creep studies without introducing spurious numerical artefacts into the constitutive response. The resulting methodology provides a reliable computational basis for fractional viscoelastic modelling, numerical benchmarking, and parameter-estimation studies involving Mittag–Leffler functions. Spanish-language metadata / Metadatos en español Título en español: Evaluación numéricamente estable y reproducible de la función de Mittag–Leffler para el modelado de fluencia mediante el modelo fraccionario de Kelvin–Voigt Resumen: Los modelos fraccionarios de Kelvin–Voigt permiten representar el comportamiento de memoria de largo alcance en la fluencia viscoelástica, pero su implementación numérica depende de la función de Mittag–Leffler. Una evaluación directa de esta función puede provocar desbordamientos, pérdida de significancia numérica y respuestas de fluencia físicamente inconsistente…
creator: Jaime Aguilar-Ortiz
creator: Carlos R. Domínguez-Mayorga
creator: Ocotlán Diaz-Parra
creator: Jorge A. Ruiz-Vanoye
creator: Francisco R. Trejo-Macotela
creator: Marco A. Vera-Jiménez
creator: Víctor M. Zamudio-García
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: 2026-08-02
publication date: 2026-08-02
volume: 17
number: 4
starting page: 205
ending page: 220
doi: 10.61467/2007.1558.2026.v17i4.1389

Optimal Design of PID Controller Parameters with Particle Swarm Optimization for Quadrotors
type: item
description: This study presents a comprehensive comparative analysis of multiple Particle Swarm Optimization configurations for optimizing Proportional-Integral-Derivative controllers in quadrotor unmanned aerial vehicles. Traditional PID tuning methods such as Ziegler-Nichols often produce suboptimal performance for complex multi-variable systems. We investigate four distinct PSO configurations—Fast, Balanced, Quality, and Aggressive—evaluating their performance across five diverse flight scenarios including basic takeoff, attitude control, and transitional flight maneuvers. The optimization process focuses on twelve PID parameters controlling altitude, roll, pitch, and yaw dynamics. Experimental results demonstrate that PSO-based optimization significantly outperforms conventional Ziegler-Nichol’s tuning, with Root Mean Square Error improvements ranging from 45.2% to 51.7% across different configurations. Statistical analysis confirms the robustness and consistency of PSO-based approaches across varying operational conditions. Spanish-language metadata / Metadatos en español Título en español: Diseño óptimo de los parámetros de controladores PID mediante optimización por enjambre de partículas para cuadricópteros Resumen: Este estudio presenta un análisis comparativo exhaustivo de múltiples configuraciones de optimización por enjambre de partículas (PSO) para optimizar controladores proporcional-integral-derivativo (PID) en vehículos aéreos no tripulados de tipo cuadricóptero. Los métodos tradicionales de ajuste PID, como el de Ziegler–Nichols, suelen producir un desempeño subóptimo en sistemas multivariables complejos. Se investigan cuatro configuraciones distintas de PSO —Fast, Balanced, Quality y Aggressive— y se evalúa su desempeño en cinco escenarios de vuelo diferentes, entre ellos el despegue básico, el control de actitud y las maniobras de vuelo transicional. El proceso de optimización se centra en doce parámetros PID que controlan la dinámica de altitud, alabeo, cabe…
creator: Fevrier Valdez
creator: Prometeo Cortes-Antonio
creator: Luis Adrian Silva
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: 2026-08-02
publication date: 2026-08-02
volume: 17
number: 4
starting page: 221
ending page: 232
doi: 10.61467/2007.1558.2026.v17i4.1347

Method for migrating monolithic software systems and their global database to isolated microservices
type: item
description: Migrating monolithic applications to microservice architectures offers benefits such as scalability, resilience, and continuous deployment. However, decomposing shared monolithic databases remains a major challenge due to strong structural and functional dependencies among application components and shared relational schemas. This paper proposes a semi-automatic decomposition method that identifies candidate microservices and service-specific databases through static analysis of use-case interaction sequences, source code dependencies, and database access relationships aligned with business capabilities. The proposed approach evaluates structural coupling using the Shared Table Coupling Index (IATC) indicator before and after migration. The method was validated through a case study and an empirical evaluation involving 17 monolithic systems from public repositories. The results show a statistically significant reduction in shared-data coupling, with an average reduction of approximately 91%, indicating the effectiveness of the proposed approach for reducing structural dependencies during monolith-to-microservices migration. Spanish-language metadata / Metadatos en español Título en español: Método para migrar sistemas de software monolíticos y su base de datos global hacia microservicios aislados Resumen: La migración de aplicaciones monolíticas hacia arquitecturas de microservicios ofrece beneficios como escalabilidad, resiliencia y despliegue continuo. Sin embargo, la descomposición de bases de datos monolíticas compartidas continúa siendo un desafío importante debido a las fuertes dependencias estructurales y funcionales entre los componentes de la aplicación y los esquemas relacionales compartidos. Este artículo propone un método semiautomático de descomposición que identifica microservicios candidatos y bases de datos específicas para cada servicio mediante el análisis estático de las secuencias de interacción de los casos de uso, las dependencias del código fu…
creator: Omar Hernández López
creator: René Santaolaya Salgado
creator: Blanca Dina Valenzuela Robles
creator: Noé Alejandro Castro Sánchez
creator: Juan Carlos Rojas Pérez
creator: Sergio Fabían Ruiz Paz
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: 2026-08-02
publication date: 2026-08-02
volume: 17
number: 4
starting page: 233
ending page: 251
doi: 10.61467/2007.1558.2026.v17i4.1434

Development of an algorithm to detect SQL vulnerabilities in PHP web pages for students of the Bachelor's Degree in Information Technology at a Mexican university
type: item
description: This project develops an educational web platform that integrates an algorithm capable of detecting SQL vulnerabilities in PHP-based web page code. The project aims to strengthen the computer security knowledge of sixth-semester students in the Bachelor's Degree in Information Technology at the Tizayuca Higher School (UAEH) through the use of a practical tool that analyzes code, offering automated feedback in simplified, non-technical language. The research takes a mixed approach using an agile methodology based on DevOps (Development Operations), allowing iterative cycles of development, testing, and continuous improvement. The algorithm was validated with real code fragments, enabling correct detection of vulnerabilities in code in more than 75% of cases, reducing false positives by 10%. The results show a positive educational impact, significantly improving students' understanding of SQL injection prevention, thereby promoting the adoption of good security practices on websites. Spanish-language metadata / Metadatos en español Título en español: Desarrollo de un algoritmo para detectar vulnerabilidades SQL en páginas web PHP dirigido a estudiantes de la Licenciatura en Tecnologías de la Información de una universidad mexicana Resumen: Este proyecto desarrolla una plataforma web educativa que integra un algoritmo capaz de detectar vulnerabilidades SQL en el código de páginas web desarrolladas en PHP. Su objetivo es fortalecer los conocimientos sobre seguridad informática de los estudiantes de sexto semestre de la Licenciatura en Tecnologías de la Información de la Escuela Superior de Tizayuca de la Universidad Autónoma del Estado de Hidalgo (UAEH), mediante una herramienta práctica que analiza código y proporciona retroalimentación automatizada en un lenguaje simplificado y no técnico. La investigación adopta un enfoque mixto y utiliza una metodología ágil basada en DevOps —operaciones de desarrollo—, lo que permite realizar ciclos iterativos de desarrollo, prueba…
creator: Braulio J. Sánchez Urbina
creator: Evangelina Lezama-León
creator: Israel Acuña-Galván
creator: Alonso Ernesto Solís-Galindo
creator: Sandra Luz Hernandez-Mendoza
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: 2026-08-02
publication date: 2026-08-02
volume: 17
number: 4
starting page: 252
ending page: 268
doi: 10.61467/2007.1558.2026.v17i4.1318

Design of a multilayer neural network in only two rows of an Excel spreadsheet for students without advanced programming knowledge
type: item
description: Artificial neural networks (ANNs) are intelligent techniques used as classification, prediction, or pattern recognition elements. It is necessary to have advanced programming knowledge to develop an artificial neural network using the Backpropagation (BP) learning algorithm. This research proposes the development of a multilayer neural network using the BP algorithm in only two rows of an Excel spreadsheet for students without advanced programming knowledge. The first row: the forward propagation of the network and the calculation of gradients in a simple manner. Each calculation is made in a specific cell. In the second row, the error is propagated backwards using the Backpropagation algorithm, adjusting the weights and biases of the output and hidden layers by subtracting the product of the two gradients. Once the correct filling of the two rows is complete, the data from the first and second rows is selected and dragged to the desired number of iterations in an easy, clear, and simple way, so that anyone without programming knowledge can develop a multilayer neural network. The tool does not require installation and offers a portable solution for designing neural networks for engineering students or students in any degree program without advanced programming knowledge. This methodology has been taught to 10 bachelor's and master´s groups in business management at the University of Guanajuato, resulting in 11 articles published in peer-reviewed journals, 3 bachelor’s theses, and 4 master’s theses. Spanish-language metadata / Metadatos en español Título en español: Diseño de una red neuronal multicapa en solo dos filas de una hoja de cálculo de Excel para estudiantes sin conocimientos avanzados de programación Resumen: Las redes neuronales artificiales (RNA) son técnicas inteligentes utilizadas para tareas de clasificación, predicción y reconocimiento de patrones. Por lo general, el desarrollo de una red neuronal artificial mediante el algoritmo de aprendizaje por …
creator: Roberto Baeza-Serrato
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: 2026-08-02
publication date: 2026-08-02
volume: 17
number: 4
starting page: 269
ending page: 286
doi: 10.61467/2007.1558.2026.v17i4.1386

Evaluating the SEMMA Methodology with AutoML Across Phishing Detection, Pollen Classification, and Voice Identification Tasks
type: item
description: The exponential growth of data has led to an increasing demand for effective methodologies in the field of machine learning. SEMMA (Sample, Explore, Modify, Model, and Assess) stands out among these methodologies due to its clear and efficient structure for pattern extraction. The contribution of this study lies in the application of the SEMMA methodology to a variety of case studies involving historical data, images, and audio. Specific datasets were used to address phishing detection, pollen image analysis, and voice classification in audio recordings. The results obtained highlight the effectiveness of SEMMA in solving data analysis problems across various domains and disciplines. Furthermore, potential future research directions in this field are identified. Spanish-language metadata / Metadatos en español Título en español: Evaluación de la metodología SEMMA con AutoML en tareas de detección de phishing, clasificación de polen e identificación de voz Resumen: El crecimiento exponencial de los datos ha generado una demanda cada vez mayor de metodologías eficaces en el campo del aprendizaje automático. SEMMA (Muestrear, Explorar, Modificar, Modelar y Evaluar) destaca entre estas metodologías debido a su estructura clara y eficiente para la extracción de patrones. La contribución de este estudio radica en la aplicación de la metodología SEMMA a diversos estudios de caso que involucran datos históricos, imágenes y audio. Se utilizaron conjuntos de datos específicos para abordar la detección de phishing, el análisis de imágenes de polen y la clasificación de voz en grabaciones de audio. Los resultados obtenidos destacan la eficacia de SEMMA para resolver problemas de análisis de datos en diversos ámbitos y disciplinas. Además, se identifican posibles líneas futuras de investigación en este campo. Palabras Claves: metodología SEMMA; aprendizaje automático automatizado; selección de modelos; detección de phishing; clasificación de polen; identificación de voz; bosque …
creator: Cecilia-Irene Loeza-Mejía
creator: Eddy Sánchez-DelaCruz
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: 2026-08-02
publication date: 2026-08-02
volume: 17
number: 4
starting page: 1
ending page: 9
doi: 10.61467/2007.1558.2026.v17i4.1290

Ethical Governance of Artificial Intelligence in Higher Education: A Systematic Review and a Proposed Socio-Technical Framework for Smart Educational Environments
type: item
description: The increasing use of artificial intelligence (AI) in higher education has intensified debates on academic ethics, authorship, and institutional governance, particularly in intelligent education environments. Although international guidelines for the responsible use of AI exist, they tend to adopt general normative approaches and show limitations when applied to specific institutional contexts. This study proposes a socio-technical framework for the ethical governance of AI in higher education. Through a systematic review, following PRISMA guidelines, of studies indexed in Scopus and Web of Science (2022–2025), normative gaps are identified and five interdependent dimensions are structured. In addition, an operationalization based on indicative variables and indicators is proposed to support institutional diagnosis. The study concludes that the ethical adoption of AI requires dynamic and context-sensitive models that balance technological innovation, academic integrity, and human oversight. Spanish-language metadata / Metadatos en español Título en español: Gobernanza ética de la inteligencia artificial en la educación superior: una revisión sistemática y una propuesta de marco sociotécnico para entornos educativos inteligentes Resumen: El uso creciente de la inteligencia artificial (IA) en la educación superior ha intensificado los debates sobre la ética académica, la autoría y la gobernanza institucional, particularmente en los entornos educativos inteligentes. Aunque existen directrices internacionales para el uso responsable de la IA, estas suelen adoptar enfoques normativos generales y presentan limitaciones cuando se aplican a contextos institucionales específicos. Este estudio propone un marco sociotécnico para la gobernanza ética de la IA en la educación superior. Mediante una revisión sistemática, realizada conforme a las directrices PRISMA, de estudios indexados en Scopus y Web of Science entre 2022 y 2025, se identifican brechas normativas y se estructura…
creator: Gerardo Antonio Hernández Torres
creator: Ariel Gutiérrez Valencia
creator: Armando Morales Murillo
creator: Antonio Becerra 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: 2026-08-02
publication date: 2026-08-02
volume: 17
number: 4
starting page: 10
ending page: 24
doi: 10.61467/2007.1558.2026.v17i4.1298

DevSecOps for Secure Software Development: A Systematic Literature Review of Practices, Benefits, and Adoption Barriers
type: item
description: The implementation of DevSecOps has emerged as an essential strategy for incorporating security from the early stages of software development. Its adoption allows for reducing vulnerabilities, streamlining threat detection, and complying with security regulations. Using a Systematic Literature Review, the study retrieved thirty research articles that met the requirements for inclusion in the review. The objective is to provide an overview of the current state of existing empirical studies on DevSecOps practices, which can help define strengths and areas of opportunity, and allow for planning future studies. Finally, studies reveal several advantages to adopting the DevSecOps approach, such as creating more secure and resilient software, improving cybersecurity defenses, and fostering a safe and open culture through communication and collaboration among development teams. However, the literature highlighted specific challenges or barriers to adopting this approach, such as organizational resistance, cultural transformations, and the complexity of implementing new security tools and procedures. Spanish-language metadata / Metadatos en español Título en español: DevSecOps para el desarrollo seguro de software: una revisión sistemática de la literatura sobre prácticas, beneficios y barreras de adopción Resumen: La implementación de DevSecOps se ha consolidado como una estrategia esencial para incorporar la seguridad desde las primeras etapas del desarrollo de software. Su adopción permite reducir vulnerabilidades, agilizar la detección de amenazas y cumplir con las normativas de seguridad. Mediante una revisión sistemática de la literatura, el estudio recuperó treinta artículos de investigación que cumplieron los criterios de inclusión establecidos. El objetivo es ofrecer una visión general del estado actual de los estudios empíricos existentes sobre las prácticas de DevSecOps, con el fin de identificar sus fortalezas y áreas de oportunidad, así como facilitar la planif…
creator: Patricia Martínez-Moreno
creator: José Antonio Vergara-Camacho
creator: Víctor Adrián Lueváno-Mondragon
creator: Karla Alejandra Jiménez-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: 2026-08-02
publication date: 2026-08-02
volume: 17
number: 4
starting page: 25
ending page: 40
doi: 10.61467/2007.1558.2026.v17i4.1299

Dynamic Load Balancing and Fault Tolerance for Machine Learning Deployments Using a Process Control Table
type: item
description: Deploying machine learning models in production environments presents significant challenges when systems must process high request volumes while maintaining stable real-time performance. Existing solutions often address request distribution, performance monitoring, and fault management separately, which may contribute to bottlenecks, increased latency, and service saturation. This study presents the design of a Process Control Table that acts as a central coordinator for orchestrating the real-time execution of machine learning models. The proposed mechanism dynamically routes incoming tasks to the least occupied worker available at the time of assignment. Prototype testing indicates that the Process Control Table reduces latency and maintains more stable response times under high demand than the traditional schemes evaluated in the study, which tended to become saturated. The mechanism also promotes equitable workload distribution and incorporates automatic failover capabilities to improve deployment reliability. These findings indicate that centralised process coordination can support dynamic load balancing, request optimisation, and fault tolerance in machine learning deployments. Spanish-language metadata / Metadatos en español Título en español: Balanceo dinámico de carga y tolerancia a fallos en despliegues de aprendizaje automático mediante una tabla de control de procesos Resumen: El despliegue de modelos de aprendizaje automático en entornos de producción presenta desafíos significativos cuando los sistemas deben procesar un gran volumen de solicitudes y, al mismo tiempo, mantener un rendimiento estable en tiempo real. Las soluciones existentes suelen abordar por separado la distribución de solicitudes, la monitorización del rendimiento y la gestión de fallos, lo que puede contribuir a la aparición de cuellos de botella, al aumento de la latencia y a la saturación del servicio. Este estudio presenta el diseño de una tabla de control de procesos que actúa c…
creator: Cesar Primero-Huerta
creator: Luis-Armando Guadarrama-Osorio
creator: Mariana-Carolyn Cruz-Mendoza
creator: Eddy Sánchez-DeLaCruz
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: 2026-08-02
publication date: 2026-08-02
volume: 17
number: 4
starting page: 41
ending page: 56
doi: 10.61467/2007.1558.2026.v17i4.1296

Fine-Tuning TrOCR for Automatic Number Plate Recognition: A YOLOv11-Based Comparison with Tesseract and EasyOCR
type: item
description: TrOCR, a recently proposed object character recognition engine, is implemented along with the YOLOv11 object detector into an Automatic Number Plate Recognition (ANPR) pipeline to identify plates at an entrance of one of the Universidad Juárez Autónoma de Tabasco campus. First tests show moderate results of TrOCR, obtaining a performance of 0.4605 using the Character Error Rate (CER) metric. To improve this result, we perform a fine-tune of the base TrOCR engine retraining the model using a dataset of 651 custom license plate images. The retrained TrOCR reduced CER to 0.2576, demonstrating the effectiveness of retraining for improving recognition accuracy in challenging conditions. The approach shows that combining YOLOv11 with a fine-tuned OCR engine allows accurate recognition under varied conditions, highlighting its potential for robust, real-world deployment. Spanish-language metadata / Metadatos en español Título en español: Ajuste fino de TrOCR para el reconocimiento automático de matrículas: una comparación basada en YOLOv11 con Tesseract y EasyOCR Resumen: Los sistemas de reconocimiento automático de matrículas (ANPR, por sus siglas en inglés) suelen constar de dos etapas: la localización de la matrícula en una imagen y el reconocimiento de sus caracteres mediante reconocimiento óptico de caracteres (OCR). Aunque el aprendizaje profundo ha mejorado significativamente la precisión de la detección —con modelos como YOLOv11, que ofrecen un rendimiento robusto y en tiempo real—, la etapa de OCR continúa siendo un problema abierto, especialmente en condiciones adversas como desenfoque por movimiento, baja iluminación u oclusión parcial. Este artículo evalúa y compara tres motores de OCR —Tesseract, EasyOCR y TrOCR— dentro de una arquitectura ANPR que utiliza YOLOv11 para la detección en un entorno real de un campus universitario. Una contribución principal es el ajuste fino de TrOCR mediante un conjunto de datos personalizado de 651 imágenes de matrículas, diseñ…
creator: Manuel Antonio García-Herrera
creator: Betania Hernández-Ocaña
creator: José Hernández-Torruco
creator: Oscar Chávez-Bosquez
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: 2026-08-02
publication date: 2026-08-02
volume: 17
number: 4
starting page: 57
ending page: 73
doi: 10.61467/2007.1558.2026.v17i4.1294

A Genetic algorithm-based optimization of CFD virtual test environments for axial cooling fan characteristic curves
type: item
description: This paper presents an evolutionary optimization approach aimed at improving the numerical characterization of axial fan performance in computer cooling applications. The proposed framework integrates Computational Fluid Dynamics (CFD) simulations with Genetic Algorithms to refine the geometric configuration of a virtual test environment. A digital wind tunnel was developed in SolidWorks Flow Simulation, employing the Lam-Bremhorst k–ε turbulence model to reproduce operating conditions. The optimization process focused on adjusting key geometric variables, including tunnel diameter, overall length, and measurement point distribution, with the objective of reducing deviations from reference performance data provided by manufacturers. A case study conducted on a ROG STRIX XF120 axial fan showed that the optimized configuration yielded a closer approximation of both static pressure and airflow rates, achieving root mean square errors of 1.7% and 9.2%, respectively. The results indicate that the proposed methodology is adaptable to different fan models and underscore the relevance of blade aerodynamic design in enhancing the reliability of numerically derived characteristic curves. Spanish-language metadata / Metadatos en español Título en español: Optimización basada en algoritmos genéticos de entornos virtuales de prueba CFD para las curvas características de ventiladores axiales de refrigeración Resumen: Este artículo presenta un enfoque de optimización evolutiva destinado a mejorar la caracterización numérica del desempeño de ventiladores axiales en aplicaciones de refrigeración de sistemas informáticos. El marco propuesto integra simulaciones de dinámica de fluidos computacional (CFD) con algoritmos genéticos para perfeccionar la configuración geométrica de un entorno virtual de pruebas. Se desarrolló un túnel de viento digital en SolidWorks Flow Simulation, utilizando el modelo de turbulencia k–ε de Lam-Bremhorst para reproducir las condiciones de operación. El pr…
creator: José Gustavo Leyva Retureta
creator: Angel Ehécatl García Martínez
creator: Fernando Aldana Franco
creator: Alam Josué Reyes López
creator: Virginia Lagunes Barradas
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: 2026-08-02
publication date: 2026-08-02
volume: 17
number: 4
starting page: 74
ending page: 93
doi: 10.61467/2007.1558.2026.v17i4.1295

An AI-Enabled Smart City Architecture for Monitoring and Specialised Care of People with Sarcopenic Obesity
type: item
description: Smart cities can contribute to public health through digital monitoring systems, telemedicine services, efficient emergency management, and data-driven decision-making. Sarcopenic obesity, characterised by the coexistence of obesity and loss of muscle mass, represents an emerging public health challenge that requires continuous monitoring and specialised care. This study proposes a conceptual smart city architecture for monitoring and supporting people with sarcopenic obesity. The proposed architecture integrates hardware-based monitoring technologies with artificial intelligence software to facilitate access to healthcare services, support remote care, and enable data-informed decision-making. By combining technological infrastructure and artificial intelligence within a smart city framework, the conceptual model seeks to improve the coordination and accessibility of specialised healthcare and contribute to the quality of life of people living with sarcopenic obesity. The main contribution of this study is an integrated conceptual architecture that connects digital monitoring, telemedicine, artificial intelligence, and specialised care within a smart city environment. Future research should evaluate its technical feasibility, clinical applicability, privacy requirements, usability, and effectiveness in real-world healthcare contexts. Spanish-language metadata / Metadatos en español Título en español: Una arquitectura de ciudad inteligente basada en inteligencia artificial para el monitoreo y la atención especializada de personas con obesidad sarcopénica. Resumen: Las ciudades inteligentes pueden contribuir a la salud pública mediante sistemas de monitoreo digital, servicios de telemedicina, una gestión eficiente de emergencias y la toma de decisiones basada en datos. La obesidad sarcopénica, caracterizada por la coexistencia de obesidad y pérdida de masa muscular, representa un desafío emergente de salud pública que requiere monitoreo continuo y atención especializ…
creator: Mirta Fuentes-Ramos
creator: Irahan-Otoniel José-Guzmán
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: 2026-08-02
publication date: 2026-08-02
volume: 17
number: 4
starting page: 94
ending page: 104
doi: 10.61467/2007.1558.2026.v17i4.1297