Listar Departamento de Informática y Análisis Numérico por título

Mostrando ítems 41-60 de 253

    • Aplicación móvil para la recomendación de asignaturas en los estudios de Grado Universitarios 

      Zafra, Ángel; Gibaja, Eva; Gámez Granados, Juan Carlos; Soto, J.M.; Arauzo Azofra, Antonio; Moyano, J.M.; Ramírez, A.; Martínez, M. (UCOPress, 2018)
      Los Grados Universitarios en sus planes de estudios tienen asignados una serie de créditos optativos, en los que el estudiante tiene libertad para elegir las asignaturas que más le interesen. Esta elección suele ser bastante ...

    • Aplicando minería de datos para descubrir rutas de aprendizaje frecuentes en Moodle 

      Bogarín Vega, Alejandro; Romero Morales, C.; Cerezo Menéndez, Rebeca (Universidad de Córdoba, UCOPress, 2016)
      En este artículo, aplicamos técnicas de minería de datos para descubrir rutas de aprendizaje frecuentes. Hemos utilizado datos de 84 estudiantes universitarios, seguidos en un curso online usando Moodle 2.0. Proponemos ...

    • Area Maximizing Surfaces in Lorentzian Spaces 

      Caballero, Magdalena; Pelegrín, José A. S.; Rubio, Rafael M. (Springer, 2021)
      In this paper we provide new results for area maximizing compact spacelike surfaces with boundary embedded in Lorentz-Minkowski space, as well as establish the uniqueness of the Dirichlet problem for maximal graphs in ...

    • Artificial intelligence to automate the systematic review of scientific literature 

      De la Torre, José; Ramírez, Aurora; Romero, José Raúl (Springer, 2023)
      Artificial intelligence (AI) has acquired notorious relevance in modern computing as it effectively solves complex tasks traditionally done by humans. AI provides methods to represent and infer knowledge, efficiently ...

    • Assessing polygonal approximations: A new measurement and a comparative study 

      Fernández García, Nicolás Luis; Moral Martínez, Luis del; Carmona Poyato, Ángel; Madrid-Cuevas, F.J.; Medina-Carnicer, R. (Elsevier, 2023)
      Two proposals related to the evaluation of polygonal approximations are presented in this document. First, a new measurement, called normalized compression ratio and adjustment error (NCA), to provide a fair evaluation of ...

    • Assignments as Influential Factor to Improve the Prediction of Student Performance in Online Courses 

      Esteban, Aurora; Romero Morales, C.; Zafra Gómez, Amelia (MDPI, 2021)
      Studies on the prediction of student success in distance learning have explored mainly demographics factors and student interactions with the virtual learning environments. However, it is remarkable that a very limited ...

    • Asymmetries of the Muscle Mechanical Properties of the Pelvic Floor in Nulliparous and Multiparous Women, and Men: A Cross-Sectional Study 

      Rodrigues-de-Souza, Daiana Priscila; Sartorato Beleza, Ana Carolina; García-Luque, Lourdes; Alcaraz-Clariana, Sandra; Carmona-Pérez, Cristina; Miguel-Rubio, Amaranta de; Garzón-Alfaro, María Teresa; Cruz-Medel, Inés; Garrido Castro, Juan Luis; Alburquerque Sendín, Francisco (MDPI, 2022)
      This study aimed to identify if the muscle mechanical properties (MMPs) of both sides of pelvic floor muscles (PFMs) are symmetrical in different populations of both sexes. Between-sides comparisons of MMPs of PFMs, assessed ...

    • AttenGait: Gait recognition with attention and rich modalities 

      Castro, Francisco M.; Delgado-Escaño, Rubén; Hernández-García, Ruber; Marín-Jiménez, M.J.; Guil, Nicolás (Elsevier, 2024)
      Current gait recognition systems employ different types of manual attention mechanisms, like horizontal cropping of the input data to guide the training process and extract useful gait signatures for people identification. ...

    • Auto-adaptive Grammar-Guided Genetic Programming algorithm to build Ensembles of Multi-Label Classifiers 

      Moyano, J.M.; Ventura Soto, S. (Elsevier, 2022)
      Multi-label classification has been used to solve a wide range of problems where each example in the dataset may be related either to one class (as in traditional classification problems) or to several class labels at the ...

    • Automatic learning of gait signatures for people identification 

      Castro, F.M.; Marín-Jiménez, M.J.; Guil, N.; Pérez de la Blanca, N. (2017-12-05)
      This work targets people identification in video based on the way they walk (i.e. gait). While classical methods typically derive gait signatures from sequences of binary silhouettes, in this work we explore the use of ...

    • Automatic melanoma diagnosis via modern machine learning techniques 

      Pérez Perdomo, Eduardo (Universidad de Córdoba, UCOPress, 2022)
      The incidence and mortality rates of skin cancer remain a huge concern in many countries. According to the latest statistics about melanoma skin cancer, only in the Unites States, 7,650 deaths are expected in 2022, which ...

    • Autómatas celulares y aplicaciones 

      Cano, Alberto; Rojas, Ángela (FISEM, 2016)
      Un autómata celular es un modelo matemático para un sistema dinámico que evoluciona en pasos discretos. Este trabajo presenta una aplicación de los autómatas celulares para el cifrado de información y el reparto de secretos. ...

    • BiViCyT: Biblioteca Virtual de Documentos Científicos y Técnicos 

      Cerruela García, Gonzalo; Fuentes Alventosa, Javier; Luque Ruiz, Irene; Gómez-Nieto, Miguel Ángel (Universidad de Córdoba, Vicerrectorado de Innovación y Calidad Docente, 2003)
      In this paper a Web information system devoted to the administration of scientific and technicians documents that are produced by the university community is presented. BiViCyT allows the management of tha administrative ...

    • Borderline kernel based over-sampling 

      Pérez-Ortiz, María; Gutiérrez, Pedro A.; Hervás-Martínez, César (2017-03-30)
      Nowadays, the imbalanced nature of some real-world data is receiving a lot of attention from the pattern recognition and machine learning communities in both theoretical and practical aspects, giving rise to di erent ...

    • Building Suitable Datasets for Soft Computing and Machine Learning Techniques from Meteorological Data Integration: A Case Study for Predicting Significant Wave Height and Energy Flux 

      Gómez-Orellana, Antonio Manuel; Fernández, Juan Carlos; Dorado Moreno, Manuel; Gutiérrez, Pedro A.; Hervás-Martínez, César (MDPI, 2021)
      Meteorological data are extensively used to perform environmental learning. Soft Computing (SC) and Machine Learning (ML) techniques represent a valuable support in many research areas, but require datasets containing ...

    • Cifrado de imágenes y Matemáticas 

      Rojas, Ángela; Cano, Alberto (Universidad Nacional de La Plata, 2011)
      Un tema que debe interesar al profesorado de Matemáticas de todos los niveles educativos es cómo hacer comprender a nuestros alumnos la utilidad de los conceptos matemáticos que están estudiando en nuestras asignaturas. ...

    • Una clase de aritmética modular, matrices y cifrado para Ingeniería 

      Rojas, Ángela; Cano, Alberto (Federación Iberoamericana de Educación Matemática (FISEM), 2011)
      El Álgebra Lineal tiene una gran cantidad de aplicaciones sin embargo se suele abordar casi siempre de una forma bastante abstracta a nivel universitario. Así que para motivar a nuestro alumnado planificamos realizar ...

    • A Classification Module for Genetic Programming Algorithms in JCLEC 

      Cano, Alberto; Luna, J.M.; Zafra, Amelia; Ventura Soto, S. (MIT Press, 2014)
      JCLEC-Classi cation is a usable and extensible open source library for genetic program- ming classi cation algorithms. It houses implementations of rule-based methods for clas- si cation based on genetic programming, ...

    • Classification Rule Mining with Iterated Greedy 

      Pedraza, Juan A.; García-Martínez, Carlos; Cano, Alberto; Ventura Soto, S. (2017-03-30)
      In the context of data mining, classi cation rule discovering is the task of designing accurate rule based systems that model the useful knowledge that di erentiate some data classes from others, and is present in large ...

    • Comparing Evolutionary Algorithms and Particle Filters for Markerless Human Motion Capture 

      Yeguas-Bolívar, Enrique; Muñoz-Salinas, Rafael; Medina-Carnicer, R.; Carmona Poyato, Ángel (Elsevier, 2014)
      Markerless Human Motion Capture is the problem of determining the joints’ angles of a three-dimensional articulated body model that best matches current and past observations acquired by video cameras. The problem of ...