Recent Submissions

  • Deep reinforcement learning meets graph neural networks: Exploring a routing optimization use case 

    Almasan Puscas, Felician Paul; Suárez-Varela Maciá, José Rafael; Rusek, Krzysztof; Barlet Ros, Pere; Cabellos Aparicio, Alberto (Elsevier, 2022-12-01)
    Article
    Restricted access - publisher's policy
    Deep Reinforcement Learning (DRL) has shown a dramatic improvement in decision-making and automated control problems. Consequently, DRL represents a promising technique to efficiently solve many relevant optimization ...
  • Countering a drone in a 3D space: Analyzing deep reinforcement learning methods 

    Cetin, Ender; Barrado Muxí, Cristina; Pastor Llorens, Enric (Multidisciplinary Digital Publishing Institute (MDPI), 2022-11-16)
    Article
    Open Access
    Unmanned aerial vehicles (UAV), also known as drones have been used for a variety of reasons and the commercial drone market growth is expected to reach remarkable levels in the near future. However, some drone users can ...
  • Graph signal reconstruction techniques for IoT air pollution monitoring platforms 

    Ferrer Cid, Pau; Barceló Ordinas, José María; García Vidal, Jorge (Institute of Electrical and Electronics Engineers (IEEE), 2022-08-03)
    Article
    Open Access
    Air pollution monitoring platforms play a very important role in preventing and mitigating the effects of pollution. Recent advances in the field of graph signal processing have made it possible to describe and analyze air ...
  • Acceleration with long vector architectures: Implementation and evaluation of the FFT kernel on NEC SX-Aurora and RISC-V vector extension 

    Vizcaino Serrano, Pablo; Mantovani, Filippo; Ferrer Ibañez, Roger; Labarta Mancho, Jesús José (Wiley (John Wiley & Sons), 2022-11-02)
    Article
    Restricted access - publisher's policy
    Novel architectures leveraging long and variable vector lengths like the NEC SX-Aurora or the vector extension of RISCV are appearing as promising solutions on the supercomputing market. These architectures often require ...
  • A low-power IoT device for measuring water table levels and soil moisture to ease increased crop yields 

    López, Emiliano; Vionnet, Carlos; Ferrer Cid, Pau; Barceló Ordinas, José María; García Vidal, Jorge; Contini, Guillermo; Prodolliet, Jorge; Maiztegui, José (2022-09-09)
    Article
    Open Access
    The simultaneous measurement of soil water content and water table levels is of great agronomic and hydrological interest. Not only does soil moisture represent the water available for plant growth but also water table ...
  • Building a Digital Twin for network optimization using graph neural networks 

    Ferriol Galmés, Miquel; Suárez-Varela Maciá, José Rafael; Paillissé Vilanova, Jordi; Shi, Xiang; Xiao, Shihan; Cheng, Xiangle; Barlet Ros, Pere; Cabellos Aparicio, Alberto (2022-11-09)
    Article
    Open Access
    Network modeling is a critical component of Quality of Service (QoS) optimization. Current networks implement Service Level Agreements (SLA) by careful configuration of both routing and queue scheduling policies. However, ...
  • Wireless energy harvesting for autonomous reconfigurable intelligent surfaces 

    Ntontin, Konstantinos; Boulogeorgos, Alexandros Apostolos A.; Björnson, Emil; Martins, Wallace Alves; Kisseleff, Steven; Abadal Cavallé, Sergi; Alarcón Cot, Eduardo José; Papazafeiropoulos, Anastasios; Lazarakis, Fotis; Chatzinotas, Symeon (Institute of Electrical and Electronics Engineers (IEEE), 2022-08-24)
    Article
    Open Access
    In the current contribution, we examine the feasibility of fully-energy-autonomous operation of reconfigurable intelligent surfaces (RIS) through wireless energy harvesting (EH) from incident information signals. Towards ...
  • Transfer-learning-based intrusion detection framework in IoT networks 

    Rodríguez Luna, Eva; Valls, Pol; Otero Calviño, Beatriz; Costa Prats, Juan José; Verdú Mulà, Javier; Pajuelo González, Manuel Alejandro; Canal Corretger, Ramon (Multidisciplinary Digital Publishing Institute (MDPI), 2022-07-27)
    Article
    Open Access
    Cyberattacks in the Internet of Things (IoT) are growing exponentially, especially zero-day attacks mostly driven by security weaknesses on IoT networks. Traditional intrusion detection systems (IDSs) adopted machine ...
  • Challenges, difficulties and barriers for engineering higher education 

    Valero García, Miguel (OmniaScience, 2022-10-19)
    Article
    Open Access
    Higher education in general, and engineering higher education in particular, is constantly under pressure to introduce reforms that improve the employability of graduates. Among the most common claims is the development ...
  • Small-layered feed-forward and convolutional neural networks for efficient P wave earthquake detection 

    Mus León, Sergi; Otero Calviño, Beatriz; Alvarado Vivas, Leonardo; Canal Corretger, Ramon; Rojas Ulacio, Otilio (2022-11-15)
    Article
    Restricted access - publisher's policy
    The number and efficiency of seismic networks have steadily increase over time delivering large datasets to be analyzed for earthquake occurrence. Automatic tools for accurate earthquake detection are under emerging and ...
  • Image-based multi-agent reinforcement learning for demand–capacity balancing 

    Mas Pujol, Sergi; Salamí San Juan, Esther; Pastor Llorens, Enric (Multidisciplinary Digital Publishing Institute (MDPI), 2022-10-14)
    Article
    Open Access
    Air traffic flow management (ATFM) is of crucial importance to the European Air Traffic Control System due to two factors: first, the impact of ATFM, including safety implications on ATC operations; second, the possible ...
  • Automated metadata annotation: What is and is not possible with machine learning 

    Wu, Mingfang; Brandhorst, Hans; Marinescu, Maria Cristina; More López, Joaquim; Hlava, Margorie; Busch, Joseph (The MIT Press. Massachusetts Institute of Technology, 2022-10-07)
    Article
    Open Access
    Automated metadata annotation is only as good as training dataset, or rules that are available for the domain. It's important to learn what type of data content a pre-trained machine learning algorithm has been trained on ...

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