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Conocimiento generado por docentes, investigadores y estudiantes, contribuyendo al avance científico, tecnológico y social.
Marco nacional de referencia en ética y autorregulación
para la ciencia de datos, big data e inteligencia artificial
Colegio Universitario Científico de Datos
03-2026-042413111000-01
Síntesis
Producción Académica — COCID
Publicaciones recientes de nuestros docentes
Referencia APA
Cárdenas Espinoza, K. M., Penagos Corzo, J. C., & (2026). Supervivencia vial: Perspectivas transdisciplinares. Tlamalhuiliztli — Revista Forense Hispanoamericana, 8, 16–24.
Abstract
Este artículo resume las vivencias adquiridas a lo largo de 15 años formando la línea de investigación denominada "Agresividad y Violencia enfocada a la Movilidad." Se presenta la experiencia en ello, los avances encontrados, y diversas vertientes a seguir en los siguientes años. Sirve como introducción a todo el trabajo presentado en este número de la Revista Tlamalhuiliztli, y enfatiza que todo este trabajo es realizado IN MEMORIAM al Dr. Julio César Penagos Corzo, quien nos dejó el año pasado. Posiblemente éste es el último trabajo escrito que haya presentado, por lo que es un honor y un privilegio colocar nuestros nombres junto al suyo.
Referencia APA
, , Magadán-Salazar, A., Pinto-Elías, R., López-Sánchez, M., & Bensoussan, Y. (2025). Gender recognition of teen and adult voices in non-tonal and tonal languages in uncontrolled environments. Computación y Sistemas, 29(1), 353–364.
Abstract
Voice gender recognition systems is a term that refers the automatization of gender detection by an acoustic signal of voice. These systems can be trained in uncontrolled environments, whose audios present different types of noises and speaker characteristics. However, the current systems present a bias in the training language, which is usually mainly English. The present work focused on the gender recognition of adult and teen voices in a group of tonal languages and Spanish under uncontrolled environments. The features used were 7 derived from pitch, and two from the mean of the fourth formant and vocal tract length. Two scenarios were built: a training-test scenario on one dataset, and a second validation scenario using the other dataset. The metrics used were accuracy, recall, F1-score, and area under the ROC curve. The algorithms used were Multilayer Perceptron and Random Forest. Despite the bias in the datasets, the biological features and the algorithms were robust to language change.
• Enrique Díaz-Ocampo ★ RESPONSABLE • Violeta Larios-Serrato ★ RESPONSABLE
Cano-Sánchez, J., Méndez-Tenorio, A., Maldonado-Rodríguez, R., Díaz-Ocampo, E., Larios-Serrato, V. (2026). BioRemmer: un pipeline bioinformático para la identificación del perfil funcional de la biodegradación microbiana de plásticos. Journal of Bioengineering and Biomedicine Research, 10(2), 17–30.
https://doi.org/10.70632/jbbr.10.2.2026.17-30Plastic pollution has become a persistent environmental issue due to the accumulation and long-term stability of synthetic polymers in natural ecosystems. In this study, we developed BioRemmer, an automated metagenomic pipeline designed to explore the putative plastic-degrading potential of microbial communities using raw paired-end FASTQ data. The workflow integrates tools for quality control, assembly, functional annotation, binning, and phylogenomic classification, together with a targeted search for enzyme families associated with nine plastic types using HMM profiles. Validation across three metagenomes of contrasting environmental origin, including a marine plastisphere, a plastic-contaminated soil, and a human gut microbiome as a negative control, demonstrated that BioRemmer produces functionally and taxonomically coherent profiles for each context, with no high-confidence hits in the negative control.
• Enrique Díaz-Ocampo ★ RESPONSABLE • Violeta Larios-Serrato ★ RESPONSABLE
Cano-Sánchez, J., Méndez-Tenorio, A., Maldonado-Rodríguez, R., Díaz-Ocampo, E., Larios-Serrato, V. (2026). BioRemmer: un pipeline bioinformático para la identificación del perfil funcional de la biodegradación microbiana de plásticos. Journal of Bioengineering and Biomedicine Research, 10(2), 17–30.
https://doi.org/10.70632/jbbr.10.2.2026.17-30Plastic pollution has become a persistent environmental issue due to the accumulation and long-term stability of synthetic polymers in natural ecosystems. In this study, we developed BioRemmer, an automated metagenomic pipeline designed to explore the putative plastic-degrading potential of microbial communities using raw paired-end FASTQ data. The workflow integrates tools for quality control, assembly, functional annotation, binning, and phylogenomic classification, together with a targeted search for enzyme families associated with nine plastic types using HMM profiles. Validation across three metagenomes of contrasting environmental origin, including a marine plastisphere, a plastic-contaminated soil, and a human gut microbiome as a negative control, demonstrated that BioRemmer produces functionally and taxonomically coherent profiles for each context, with no high-confidence hits in the negative control.