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  • Open Access

    ARTICLE

    NUMERICAL INVESTIGATION OF HEAT TRANSPORT IN A DIRECT METHANOL FUEL CELL WITH ANISOTROPIC GAS DIFFUSION LAYERS

    Zheng Miaoa, Ya-Ling Hea,*, Tian-Shou Zhaob, Wen-Quan Taoa

    Frontiers in Heat and Mass Transfer, Vol.2, No.1, pp. 1-10, 2011, DOI:10.5098/hmt.v2.1.3001

    Abstract A non-isothermal two-phase mass transport model is developed in this paper to investigate the heat generation and transport phenomena in a direct methanol fuel cell with anisotropic gas diffusion layers (GDLs). Thermal contact resistances at the GDL/CL (catalyst layer) and GDL/Rib interfaces, and the deformation of GDLs are considered together with the inherent anisotropy of the GDL. Latent heat effects due to condensation/evaporation of water and methanol between liquid and gas phases are also taken into account. Formulation of the two-phase mass transport across the membrane electrode assembly (MEA) is mainly based on the classical multiphase flow theory in the… More >

  • Open Access

    ARTICLE

    A Novel Ensemble Learning System for Cyberattack Classification

    Óscar Mogollón-Gutiérrez*, José Carlos Sancho Núñez, Mar Ávila Vegas, Andrés Caro Lindo

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1691-1709, 2023, DOI:10.32604/iasc.2023.039255

    Abstract Nowadays, IT systems rely mainly on artificial intelligence (AI) algorithms to process data. AI is generally used to extract knowledge from stored information and, depending on the nature of data, it may be necessary to apply different AI algorithms. In this article, a novel perspective on the use of AI to ensure the cybersecurity through the study of network traffic is presented. This is done through the construction of a two-stage cyberattack classification ensemble model addressing class imbalance following a one-vs-rest (OvR) approach. With the growing trend of cyberattacks, it is essential to implement techniques that ensure legitimate access to… More >

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