Envíos recientes

  • How do preschoolers interact with peers? Characterising child and group behaviour in games with tangible interfaces in school 

    Barros-Blanco, Beatriz; Triviño-Rodriguez, Jose Luis; Trella López, Mónica; Marco Rubio, Javier (Elsevier, 2022-09)
    Learning social skills is an important part of the socialisation process of children, which should occur at school, at home and in any place where children live. There are very few studies on social interaction and ...
  • Classifying resilience approaches for protecting smart grids against cyber threats 

    Syrmakesis, Andrew D.; Alcaraz Tello, María Cristina; Hatziargyriou, Nikos D. (Springer, 2022-05-06)
    Smart grids (SG) draw the attention of cyber attackers due to their vulnerabilities, which are caused by the usage of heterogeneous communication technologies and their distributed nature. While preventing or detecting ...
  • Estimación del estado de salud de la batería de iones de litio basada en características con redes neuronales artificiales 

    Driscoll, Lewis; De la Torre, Sebastián; Gomez-Ruiz, Jose Antonio (Elsevier, 2022-06)
    Precise online lithium-ion battery state of health estimation is critical for the correct operation and management of battery-based energy storage systems such as microgrids and electric vehicles. However, in such applications ...
  • Combining multiple granularity variability in a software product line approach for web engineering 

    Horcas Aguilera, José Miguel; Cortiñas, Alejandro; Fuentes-Fernández, Lidia; Luaces, Miguel-R (Elsevier, 2022-08)
    Context: Web engineering involves managing a high diversity of artifacts implemented in different languages and with different levels of granularity. Technological companies usually implement variable artifacts of Software ...
  • Ensemble methods for meningitis aetiology diagnosis 

    Guzman-de-los-Riscos, Eduardo Francisco; Belmonte, María-Victoria; Lelis, Viviane M. (Wiley, 2022-03-18)
    In this work, we explore data-driven techniques for the fast and early diagnosis concerning the etiological origin of meningitis, more specifically with regard to differentiating between viral and bacterial meningitis. We ...
  • Dynamic and adaptive fault-tolerant asynchronous federated learning using volunteer edge devices 

    Morell Martínez, José Ángel; Alba, Enrique (Elsevier, 2022)
    The number of devices, from smartphones to IoT hardware, interconnected via the Internet is growing all the time. These devices produce a large amount of data that cannot be analyzed in any data center or stored in the ...
  • Using machine learning techniques for architectural design tracking: An experimental study of the design of a shelter 

    Millan-Valldeperas, Eva; Belmonte-Martinez, Maria Victoria; Boned Purkiss, Javier; Gavilanes-Velaz-de-Medrano, Juan; Perez-de-la-Cruz, Jose-Luis; [et al.] (Elsevier, 2022-07-22)
    In this paper, we present a study aimed at tracking and analysing the design process. More concretely, we intend to explore whether some elements of the conceptual design stage in architecture might have an influence on ...
  • Walk-IT: An Open-Source Modular Low-Cost Smart Rollator 

    Fernandez-Carmona, Manuel; Ballesteros Gómez, Joaquín; Díaz-Boladeras, María; Parra-Llanas, Xavier; Urdiales, Cristina; [et al.] (IOAP-MPDI, 2022-03-08)
    Rollators are widely used in clinical rehabilitation for gait assessment, but gait analysis usually requires a great deal of expertise and focus from medical staff. Smart rollators can capture gait parameters autonomously ...
  • Multi-objective dynamic programming with limited precision 

    Mandow-Andaluz, Lorenzo; Perez-de-la-Cruz-Molina, Jose Luis; Pozas García, Nicolás (Springer, 2021-11-02)
    This paper addresses the problem of approximating the set of all solutions for Multi-objective Markov Decision Processes. We show that in the vast majority of interesting cases, the number of solutions is exponential or ...
  • Capping methods for the automatic configuration of optimization algorithms 

    de Souza, Marcelo; Ritt, Marcus; Lopez Ibañez Infante, Manuel (Elsevier, 2022-03)
    Automatic configuration techniques are widely and successfully used to find good parameter settings for optimization algorithms. Configuration is costly, because it is necessary to evaluate many configurations on different ...
  • FIMED: Flexible management of biomedical data 

    Hurtado Requena, Sandro; García-Nieto, José; Navas-Delgado, Ismael; Aldana-Montes, Jose Francisco (Elsevier, 2021-11)
    Background and objectives: In the last decade, clinical trial management systems have become an essential support tool for data management and analysis in clinical research. However, these clinical tools have design ...
  • Metaheuristics on quantum computers: Inspiration, simulation and real execution 

    Dahi, Abdelmoiz Zakaria; Alba-Torres, Enrique (ELSEVIER, 22-05)
    Quantum-inspired metaheuristics are solvers that incorporate principles inspired from quantum mechanics into classical-approximate algorithms using non-quantum machines. Due to the uniqueness of quantum principles, the ...
  • Road pollution estimation from vehicle tracking in surveillance videos by deep convolutional neural networks 

    García-González, Jorge; Molina Cabello, Miguel Ángel; Luque-Baena, Rafael; Ortiz-de-lazcano-Lobato, Juan Miguel; López-Rubio, Ezequiel (ELSEVIER, 2021-12)
    Air quality and reduction of emissions in the transport sector are determinant factors in achieving a sustainable global climate. The monitoring of emissions in traffic routes can help to improve route planning and to ...
  • Semantic modelling of Earth Observation remote sensing 

    Aldana Martín, José Francisco; Garcia Nieto, Jose Manuel; Roldan-Garcia, Maria del Mar; Aldana-Montes, Jose Francisco (ELSEVIER, 2022-01)
    Earth Observation (EO) based on Remote Sensing (RS) is gaining importance nowadays, since it offers a well-grounded technological framework for the development of advanced applications in multiple domains, such as climate ...
  • TITAN: A knowledge-based platform for Big Data workflow management 

    Benítez-Hidalgo, Antonio; Barba-González, Cristóbal; Gutiérrez-Moncayo, Pedro; Paneque, Manuel; Nebro-Urbaneja, Antonio Jesus; [et al.] (ELSEVIER, 2021-11-28)
    Modern applications of Big Data are transcending from being scalable solutions of data processing and analysis, to now provide advanced functionalities with the ability to exploit and understand the underpinning knowledge. ...
  • A takeover time-driven adaptive evolutionary algorithm for mobile user tracking in pre-5G cellular networks 

    Zakaria Abdelmoiz, Dahi; Alba-Torres, Enrique (ELSEVIER, 2022-02)
    Cellular networks are one of today’s most popular means of communication. This fact has made the mobile phone industry subject to a huge scientific and economic competition, where the quality of service is key. Such a ...
  • Using machine learning techniques for architectural design tracking: an experimental study of the design of a shelter 

    Millan-Valldeperas, Eva; Belmonte-Martinez, Maria Victoria; Boned-Purkiss, Francisco Javier; Gavilanes-Velaz-de-Medrano, Juan; Perez-de-la-Cruz-Molina, Jose Luis; [et al.] (Elsevier, 2022)
    In this paper, we present a study aimed at tracking and analysing the design process. More concretely, we intend to explore whether some elements of the conceptual design stage in architecture might have an influence on ...
  • Improved detection of small objects in road network sequences using CNN and super resolution 

    García Aguilar, Iván; Luque Baena, Rafael Marcos; López-Rubio, Ezequiel (2021)
    The detection of small objects is one of the problems present in deep learning due to the context of the scene or the low number of pixels of the objects to be detected. According to these problems, current pre-trained ...
  • Skin lesion classification by ensembles of deep convolutional networks and regularly spaced shifting 

    Thurnhofer Hemsi, Karl; López-Rubio, Ezequiel; Domínguez, Enrique; Elizondo, David A. (2021)
    Skin lesions are caused due to multiple factors, like allergies, infections, exposition to the sun, etc. These skin diseases have become a challenge in medical diagnosis due to visual similarities, where image classification ...
  • Ensemble ellipse fitting by spatial median consensus 

    Thurnhofer Hemsi, Karl; López-Rubio, Ezequiel; Blazquez-Parra, Elidia Beatriz; Ladrón de Guevara Muñoz, Carmen; De Cózar Macías, Óscar David (2021)
    Ellipses are among the most frequently used geometric models in visual pattern recognition and digital image analysis. This work aims to combine the outputs of an ensemble of ellipse fitting methods, so that the deleterious ...

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