Ara es mostren els items 1-20 de 63

    • A 3D terrain generator: Enhancing robotics simulations with GANs 

      Arellano García, Silvia; Otero Calviño, Beatriz; Kucner, Tomasz Piotr; Canal Corretger, Ramon (Springer, 2023)
      Text en actes de congrés
      Accés restringit per política de l'editorial
      Simulation is essential in robotics to evaluate models and techniques in a controlled setting before conducting experiments on tangible agents. However, developing simulation environments can be a challenging and time-consuming ...
    • A comparative study of two compact finite difference methods: standard vs. mimetic 

      Córdova, Luis Joaquin; Rojas, Otilio; Otero Calviño, Beatriz; Castillo, José (Sociedad Venezolana de Métodos Numéricos en Ingeniería, 2014)
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      Accés restringit per política de l'editorial
      In this work, we implement two fourth-order compact finite differences (CFD) methods and use them to model wave propagation on a elastic string. The formulation of the first method employs the standard implicit CFD constructed ...
    • A cost-efficient QoS-aware analytical model of future software content delivery networks 

      Otero Calviño, Beatriz; Rodríguez Luna, Eva; Rojas, Otilio; Verdú Mulà, Javier; Costa Prats, Juan José; Pajuelo González, Manuel Alejandro; Canal Corretger, Ramon (2021-07)
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      Freelance, part-time, work-at-home, and other flexible jobs are changing the concept of workplace, and bringing information and content exchange problems to companies. Geographically spread corporations may use remote ...
    • A differential privacy protection-based federated deep learning framework to fog-embedded architectures 

      Gutiérrez Escobar, Norma; Otero Calviño, Beatriz; Rodríguez Luna, Eva; Utrera Iglesias, Gladys Miriam; Mus León, Sergi; Canal Corretger, Ramon (Elsevier, 2024-04)
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      Nowadays, companies collect massive quantities of data to enhance their operations, often at the expense of sharing user sensible information. This data is widely used to train Deep Learning (DL) neural networks to model, ...
    • A dispersion analysis of uniformly high order, interior and boundaries, mimetic finite difference solutions of wave propagation problems 

      Rojas, Otilio; Mendoza, Larry; Otero Calviño, Beatriz; Villamizar Morales, Jorge; Calderón, Giovanni; Castillo, José; Miranda, Guillermo (Springer, 2024)
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      A preliminary stability and dispersion study for wave propagation problems is developed for mimetic finite difference discretizations. The discretization framework corresponds to the fourth-order staggered-grid Castillo-Grone ...
    • A domain decomposition technique for pseudospectra computations 

      Astudillo, Reinaldo; Castillo, Zenaida; Otero Calviño, Beatriz (2013)
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      Accés restringit per política de l'editorial
      The pseudospectra, a tool to study the behavior of systems associated with nonnormal matrices has been considered extremely useful in the last decades, for that reason there is a recent interest in its efficient computation. ...
    • A mimetic wave equation discretization with absorbing boundary condition: Formulation and application 

      Solano-Feo, Freysimar; Guevara-Jordan, Juan; Rojas_Ulacio, Otilio; González-Ramirez, Carlos; Otero Calviño, Beatriz (2016)
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      The cornerstone of mimetic finite differentiation (FD) is that discrete gradients and divergences, in combination with a novel boundary flux operator satisfies an approximation to the Gauss–Divergence theorem. In this ...
    • A new mimetic scheme for the acoustic wave equation 

      Solano, Freysimar; Guevara-Jordan, Juan; Rojas, Otilio; Otero Calviño, Beatriz; Rodriguez, R. (2016-03-15)
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      A new mimetic finite difference scheme for solving the acoustic wave equation is presented. It combines a novel second order tensor mimetic discretizations in space and a leapfrog approximation in time to produce an explicit ...
    • A performance analysis of a mimetic finite difference scheme for acoustic wave propagation on GPU platforms 

      Otero Calviño, Beatriz; Frances, Jorge; Rodriguez Cruz, Robert; Rojas, Otilio; Solano, Freysimar; Guevara-Jordan, Juan (2017-02-01)
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      Accés obert
      Realistic applications of numerical modeling of acoustic wave dynamics usually demand high-performance computing because of the large size of study domains and demanding accuracy requirements on simulation results. Forward ...
    • A survey of deep learning techniques for cybersecurity in mobile networks 

      Rodríguez Luna, Eva; Otero Calviño, Beatriz; Gutiérrez Escobar, Norma; Canal Corretger, Ramon (2021-06-07)
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      The widespread use of mobile devices, as well as the increasing popularity of mobile services has raised serious cybersecurity challenges. In the last years, the number of cyberattacks has grown dramatically, as well as ...
    • A survey of machine and deep learning methods for privacy protection in the Internet of things 

      Rodríguez Luna, Eva; Otero Calviño, Beatriz; Canal Corretger, Ramon (Multidisciplinary Digital Publishing Institute (MDPI), 2023-01-21)
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      Recent advances in hardware and information technology have accelerated the proliferation of smart and interconnected devices facilitating the rapid development of the Internet of Things (IoT). IoT applications and services ...
    • All-terminal reliability evaluation through a Monte Carlo simulation based on an MPI implementation 

      Pascual Martinez, Silvia; Otero Calviño, Beatriz; Rocco Sanseverino, Claudio M. (2012)
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      All-terminal reliability (ATR), defined as the probability that every node in a network can communicate with every other node, is an important problem in research areas such as mobile ad-hoc wireless networks, grid computing ...
    • Alternating direction implicit time integrations for finite difference acoustic wave propagation: parallelization and convergence 

      Otero Calviño, Beatriz; Rojas, Otilio; Moya, Ferrán; Castillo, José (Elsevier, 2020-06-15)
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      Accés obert
      This work studies the parallelization and empirical convergence of two finite difference acoustic wave propagation methods on 2-D rectangular grids, that use the same alternating direction implicit (ADI) time integration. ...
    • Ambiences: on-the-fly usage of available resources through personal devices 

      Otero Calviño, Beatriz; Gil, Marisa (2013-10)
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      Accés obert
      In smart spaces such as smart homes, computation is embedded everywhere: in toys, appliances, or the home’s infrastructure. Most of these devices provide a pool of available resources which the user can take advantage, ...
    • Artificial neural networks as emerging tools for earthquake detection 

      Rojas, Otilio; Otero Calviño, Beatriz; Alvarado, Leonardo; Mus, Sergi; Tous Liesa, Rubén (2019)
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      As seismic networks continue to spread and monitoring sensors become more ef¿cient, the abundance of data highly surpasses the processing capabilities of earthquake interpretation analysts. Earthquake catalogs are fundamental ...
    • Compact finite difference modeling of 2-D acoustic wave propagation 

      Córdova, Luis; Rojas, Otilio; Otero Calviño, Beatriz; Castillo, Jose (2016-03-15)
      Article
      Accés obert
      We present two fourth-order compact finite difference (CFD) discretizations of the velocity–pressure formulation of the acoustic wave equation in 2-D rectangular grids. The first method uses standard implicit CFD on nodal ...
    • Conceptos básicos necesarios en la asignatura de Fundamentos de Ordenadores (ETSETB) 

      Jiménez Castells, Marta; Otero Calviño, Beatriz (Universitat Politècnica de Catalunya, 2013-05)
      Apunts
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      Este documento está dirigido a los estudiantes de nuevo ingreso que cursarán estudios de Ingeniería en la ETSETB. Concretamente el documento resultará útil para los estudiantes matriculados en la asignatura de Fundamentos ...
    • Deep learning detection of GPS spoofing 

      Jullian Parra, Olivia; Otero Calviño, Beatriz; Stojilovic, Mirjana; Costa Prats, Juan José; Verdú Mulà, Javier; Pajuelo González, Manuel Alejandro (Springer Nature, 2022)
      Text en actes de congrés
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      Unmanned aerial vehicles (UAVs) are widely deployed in air navigation, where numerous applications use them for safety-of-life and positioning, navigation, and timing tasks. Consequently, GPS spoofing attacks are more and ...
    • Deep neural networks for earthquake detection and source region estimation in north-central Venezuela 

      Tous Liesa, Rubén; Alvarado Bermúdez, Leonardo; Otero Calviño, Beatriz; Cruz de la Cruz, Stalin Leonel; Rojas Ulacio, Otilio (2020-10-01)
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      Accés obert
      Reliable earthquake detection algorithms are necessary to properly analyze and catalog the continuously growing seismic records. We report the results of applying a deep convolutional neural network, called UPC‐UCV ...
    • Deep-learning based detection for cyber-attacks in IoT networks: A distributed attack detection framework 

      Jullian Parra, Olivia; Otero Calviño, Beatriz; Rodríguez Luna, Eva; Gutiérrez Escobar, Norma; Antona Pizà, Héctor; Canal Corretger, Ramon (Springer Nature, 2023-02-04)
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      Accés obert
      The widespread use of smart devices and the numerous security weaknesses of networks has dramatically increased the number of cyber-attacks in the internet of things (IoT). Detecting and classifying malicious traffic is ...