This paper tackles the problem of forecasting real-life crime. However, the recollected data only produced thirty-five short-sized crime time series for three urban areas. We present a comparative analysis of four simple and four machine-learning-based ensemble forecasting methods. Additionally, we propose five forecasting techniques that manage the seasonal component of the time series. Furthermore, we used the symmetric mean average percentage error and a Friedman test to compare the performance of the forecasting methods and proposed techniques. The results showed that simple moving average with seasonal removal techniques produce the best performance for these series. It is important to highlight that a high percentage of the time series has no auto-correlation and a high level of symmetry, which is deemed as white noise and, therefore, difficult to forecast.

A substantial number of students with hearing impairments are enrolled in higher education, motivating the development of inclusive assistive technologies that reduce communication barriers. This study developed and evaluated a prototype electronic glove that translates Mexican Sign Language (LSM) signs into Spanish text using machine learning. Eight participants (four deaf and four hearing with LSM proficiency) completed four sessions involving 12 signs; three sessions (S1–S3) were used for model development and one session (T) was held out for evaluation. Models were trained on S1–S3 and tested on T using a session-level split without window mixing across sessions; therefore, results represent a speaker-dependent, inter-session pilot assessment rather than a speaker-independent generalization test. The glove integrates flex sensors and an inertial measurement unit IMU MPU6050 connected to an ESP32-C3 SuperMini microcontroller. These components were selected due to their low cost, availability, and ease of integration, making them suitable for the development of accessible wearable assistive technologies. Under this protocol, the system achieved a window-level overall test accuracy of 97.0% (95% CI computed at the window level: 96.00–97.00), with higher performance for the dynamic subset (98.0%) than for the static subset (95.0%), and an algorithmic decision delay of 1.2 s. Usability and acceptance were evaluated using the System Usability Scale (SUS) and a Technology Acceptance Model (TAM)-based questionnaire. The mean SUS score was 50.6 ± 1.8 (marginal usability), while participants reported positive perceptions across TAM constructs. Overall, findings demonstrate technical feasibility under controlled inter-session conditions and provide a foundation for iterative user-centered refinement, followed by strict speaker-independent validation and classroom deployment studies in future work.

Los gases de efecto invernadero atrapan el calor irradiado del sol en la atmósfera, provocando un aumento en la temperatura del planeta que puede traer consecuencias devastadoras para el ser humano. Diversos países han acordado estrategias que contribuyan a reducir las emisiones de este tipo de gases para el año 2030. Entre las soluciones propuestas destaca la reducción de emisiones de CO2 derivadas del transporte. Razón por la cual, los vehículos eléctricos (EV) alimentados con celdas de hidrógeno o baterías resultan una opción viable y sostenible. Este artículo proporciona una descripción y clasificación de los vehículos eléctricos alimentados por baterías. Sus ventajas, desventajas, los principios de operación y la posible incorporación de supercapacitores. Los cuales son dispositivos de almacenamiento de energía que al ser incorporados permiten entregar energía en cortos periodos de tiempo. Su integración reduce los ciclos de carga descarga del sistema de baterías contribuyendo a prolongar su vida útil y con el tiempo, disminuir costos.

This document is focused on guiding Decision Makers (DM) regarding the Information and Communications Technology (ICT) infrastructure that should be selected for proper administrative and academic operation within Higher Education Institutions (HEI). These technologies include the Internet, hardware infrastructure, institutional email, and educational platforms. This selection problem arises due to the diversity of providers offering ICT services in terms of speed, storage, number of users, and costs for each of the technologies. This decision involves a thorough evaluation of the different selection alternatives that converge in a real life scenario increasingly influenced by the use and application of technologies. The TOPSIS method is applied due to its ease of use in evaluating the various characteristics of each of the technologies and because it offers an ordering based on the values of proximity to an ideal solution, thus offering a ranking as a guide to support the decision of the DM according to his preferences. Smart citations: https://scite.ai/reports/10.61467/2007.1558.2026.v17i2.1164Dimensions.Open Alex.

The inventory control and design of a warehouse in the metal-mechanical company in southern Tamaulipas aims to optimize the inventory control and planning process in a metal-mechanical industrial maintenance services company, applying a non-experimental, transversal, quantitative, and qualitative descriptive approach and purposeful, with the ABC inventory classification method, which is obtained by carrying out a diagnosis of the company's inventory control, categorization of materials based on their rotation of use through a Pareto analysis, analysis of the rotation of type A, B, and C materials, respectively and establishing safety stocks, finally making the proposal of new policies for inventory control as well as physical distribution in the warehouse according to the ABC classification.

La contaminación atmosférica constituye uno de los principales riesgos ambientales para la salud pública y afecta con mayor intensidad a la población infantil, las personas adultas mayores y quienes presentan enfermedades preexistentes. Este artículo analiza los retos del monitoreo de la calidad del aire en contextos urbanos, con énfasis en zonas caracterizadas por crecimiento acelerado, actividad industrial y cobertura limitada de estaciones de referencia. Mediante una revisión narrativa de literatura científica y documentos oficiales, se examinan los efectos del material particulado, la contribución de la ecologización urbana, la situación del monitoreo en México y el potencial de sensores de bajo costo, internet de las cosas, plataformas web, imágenes satelitales e inteligencia artificial. Los estudios revisados muestran que estas tecnologías permiten ampliar la cobertura espacial y temporal, generar información cercana a las comunidades y apoyar el análisis predictivo; sin embargo, sus datos requieren calibración, control de calidad y comparación con equipos de referencia. En el contexto de Altamira, Tamaulipas, se plantea el monitor de calidad del aire MB01-ICA como una propuesta tecnológica local de carácter indicativo y educativo, orientada a fortalecer la información ambiental y la participación social. Se concluye que la combinación de infraestructura verde, monitoreo accesible y gobernanza de datos puede contribuir a una vigilancia ambiental más equitativa, siempre que se evite sustituir las estaciones regulatorias por dispositivos no validados.