• Learning Bayesian Networks for Student Modeling 

      Millán, Eva; Belmonte-Martinez, Maria Victoria; Jiménez, Guiomar; Pérez-de-la-Cruz, José-Luis (2015-07-03)
      In the last decade, there has been a growing interest in using Bayesian Networks (BN) in the student modelling problem. This increased interest is probably due to the fact that BNs provide a sound methodology for this ...
    • LinTraP: Primitive Operators for the Execution of Model Transformations with LinTra 

      Burgueño, Loli; Syriani, Eugene; Wimmer, Manuel; Gray, Jeff; Moreno Vallecillo, Antonio (2014-07-31)
      The problems addressed by Model-Driven Engineering (MDE) approaches are increasingly complex, hence performance and scalability of model transformations are gaining importance. In previous work, we introduced LinTra, which ...
    • Local Optima Network Analysis for MAX-SAT 

      Ochoa, Gabriela; Chicano, Francisco (2019-07-22)
      Local Optima Networks (LONs) are a valuable tool to understand fitness landscapes of optimization problems observed from the perspective of a search algorithm. Local optima of the optimization problem are linked by an edge ...
    • Local Optima Networks, Landscape Autocorrelation and Heuristic Search Performance 

      Chicano, Francisco; Daolio, Fabio; Ochoa, Gabriela; Vérel, Sébastien; Tomassini, Marco; [et al.] (2014-10-06)
      Recent developments in fitness landscape analysis include the study of Local Optima Networks (LON) and applications of the Elementary Landscapes theory. This paper represents a first step at combining these two tools to ...
    • LTMaker: a tool for semiautomatic reconstruction of the embryonic lineage tree from 4D-microscopy 

      Vico-Vela, Francisco Jose; Lobo Fernández, Daniel; Gómez, Antonio; Burrezo García, Salvador; Fernández Rodríguez, Jose David; [et al.] (2013-12-03)
      Studies of animal development using a 4Dmicroscopy system generate an immense amount of image data. In order to properly analyze the recorded embryogenesis, a computer-aided systematic process of categorization of ...
    • Machine and Human Observable Differences in Groups’ Collaborative Problem-Solving Behaviours 

      Cukurova, Mutlu; Luckin, Rose; Mavrikis, Manolis; Millan-Valldeperas, Eva (2019-10-18)
      This paper contributes to our understanding of how to design learning analytics to capture and analyse collaborative problem-solving (CPS) in practice-based learning activities. Most research in learning analytics focuses ...
    • Machine learning models to search relevant genetic signatures in clinical context 

      Urda, Daniel; Luque-Baena, Rafael; Franco, Leonardo; Sánchez-Maroño, Noelia; Jerez-Aragonés, José Manuel (2017-06-26)
      Clinicians are interested in the estimation of robust and relevant genetic signatures from gene sequencing data. Many machine learning approaches have been proposed trying to address well-known issues of this complex ...
    • Managing Uncertain Complex Events in Web of Things Applications 

      Moreno, Nathalie; Fernández-Bertoa, Manuel; Barquero, Gala; Burgueño, Loli; Troya, Javier; [et al.] (2018-05-31)
      A critical issue in the Web of Things (WoT) is the need to process and analyze the interactions of Web-interconnected real-world objects. Complex Event Processing (CEP) is a powerful technology for analyzing streams of ...
    • Máster INFTEL: Transición de la universidad a la empresa en el campo de las comunicaciones móviles 

      Morales-Bueno, Rafael; Cantalejo-Garcia, Francisco; Morales-Becerra, Carlos R.; Araujo-Yaselli, Marian (2014-07-22)
      Las actividades de los estudiantes en la universidad tienen características claramente diferentes a las actividades en una empresa. Al pasar el estudiante de un lugar al otro necesita un periodo de adaptación. Reducir ese ...
    • Math Oracles: A New Way of Designing Efficient Self-Adaptive Algorithms 

      Luque-Polo, Gabriel Jesús; Alba-Torres, Enrique (ACM Press, 2013)
      In this paper we present a new general methodology to develop self-adaptive methods at a low computational cost. Instead of going purely ad-hoc we de ne several simple steps to include theoretical models as additional ...
    • Measuring Procedural Knowledge in Problem Solving Environments with Item Response Theory 

      Hernando, Manuel; Guzmán, Eduardo; Conejo, Ricardo (Springer, 2013)
      In this paper, a new data-driven model to measure procedural knowledge is described. The model is based on Item Response Theory. The main idea behind this new model is to establish an analogy between the testing and the ...
    • Measuring the Quality of Machine Learning and Optimization Frameworks 

      Villalobos, Ignacio; Ferrer, Javier; Alba, Enrique (2018-11-26)
      Software frameworks are daily and extensively used in research, both for fundamental studies and applications. Researchers usually trust in the quality of these frameworks without any evidence that they are correctly build, ...
    • Mecanismos de reconfiguración eco-eficiente de código en aplicaciones móviles Android 

      Canete, Angel; Horcas, José M.; Fuentes-Fernández, Lidia (2018-10-03)
      Los dispositivos móviles ofrecen cada vez mayores prestaciones a costa de un mayor consumo energético. La energía consumida por un móvil no sólo depende de las aplicaciones en sí, sino también de las interacciones del ...
    • Mejora de la Empatía y de Competencias Transversales a través de la Revisión por Pares 

      Pastrana Brincones, José Luis (2016-06-10)
      Este trabajo presenta un caso de estudio que muestra cómo la revisión por pares entre iguales puede ser usada para el desarrollo de la empatía. La experiencia ha sido llevada a cabo durante los 2 últimos años con una ...
    • Melanoma expression analysis with Big Data technologies 

      Fernandez-Rovira, Alicia; Lavado-Valenzuela, Rocio; Berciano-Guerrero, Miguel Angel; Navas-Delgado, Ismael; Aldana-Montes, Jose Francisco (PeerJ, 2017-09-26)
      Melanoma is a highly immunogenic tumor. Therefore, in recent years physicians have incorporated drugs that alter the immune system into their therapeutic arsenal against this disease, revolutionizing in the treatment of ...
    • MELOMICS: Contributions of computer science and biology to receptive music therapy 

      Vico-Vela, Francisco Jose; Sánchez-Quintana, Carlos Alberto; Albarracín-Molina, David (2014-01-07)
      It is surprising the fact that while the personalized medicine model is more and more accepted, receptive music therapy is still applied collectively. Although, in some hospitals the subject (patient or health-medical ...
    • Metaheurísticas híbridas para el problema del apagado de celdas en redes 5G 

      Zapata Cano, Pablo Helio; Mora García, Antonio; Luna-Valero, Francisco; Padilla-de-la-Torre, Pablo; Valenzuela-Valdés, Juan Francisco (2018-10-30)
      La densificación masiva de estaciones base (BS) es una de las tecnologías facilitadoras bien reconocidas por la literatura para el desarrollo de la quinta generación de redes de telecomunicaciones (5G). Su implementación, ...
    • Metaheurísticas para Smart Mobility: Reducción de Emisiones y Consumo de Carburantes en el Tráfico Urbano 

      García-Nieto, José; Alba-Torres, Enrique (2013-07-17)
      Hoy en día, la mejora del tráfico vehicular supone una labor ineludible en nuestras ciudades a la hora de mitigar problemas como la excesiva emisión de gases contaminantes y el consumo no sostenible de carburantes. El ...
    • Migrants Selection and Replacement in Distributed Evolutionary Algorithms for Dynamic Optimization 

      Bravo, Yesnier; Luque-Polo, Gabriel Jesús; Alba-Torres, Enrique (Springer, 2013)
      Many distributed systems (task scheduling, moving priorities, changing mobile environments, ...) can be linked as Dynamic Optimization Problems (DOPs), since they require to pursue an optimal value that changes over time. ...
    • Minería de datos educativos para la predicción personalizada del rendimiento académico 

      Del Campo-Ávila, José; Ramos-Jimenez, Gonzalo Pascual; Morales-Bueno, Rafael; Baena-García, Manuel (2018-03-22)
      La Minería de Datos Educativos (Educational Data Mining - EDM) está adquiriendo gran importancia como un nuevo campo de investigación interdisciplinario relacionado con algunas otras áreas. Está directamente relacionado ...