Telemática: Envíos recentes

Mostrando ítems 41-45 de 45

    • Network Anomaly Detection Using Machine Learning Techniques 

      Estévez Pereira, Julio Jairo; Fernández, Diego; Nóvoa, Francisco (MDPI AG, 2020-08-19)
      [Abstract] While traditional network security methods have been proven useful until now, the flexibility of machine learning techniques makes them a solid candidate in the current scene of our networks. In this paper, we ...

    • Annotated Dataset for Anomaly Detection in a Data Center with IoT Sensors 

      Vigoya, Laura; Fernández, Diego; Carneiro, Víctor; Cacheda, Fidel (MDPI AG, 2020-07-04)
      [Abstract] The relative simplicity of IoT networks extends service vulnerabilities and possibilities to different network failures exhibiting system weaknesses. Therefore, having a dataset with a sufficient number of ...

    • High Order Profile Expansion to tackle the new user problem on recommender systems 

      Fernández, Diego; Formoso, Vreixo; Cacheda, Fidel; Carneiro, Víctor (Public Library of Science, 2019-11-07)
      [Abstract] Collaborative Filtering algorithms provide users with recommendations based on their opinions, that is, on the ratings given by the user for some items. They are the most popular and widely implemented algorithms ...

    • Time-Aware Detection Systems 

      López-Vizcaíno, Manuel F.; Vigoya, Laura; Cacheda, Fidel; Nóvoa, Francisco (MDPI AG, 2019-08-05)
      [Abstract] Communication network data has been growing in the last decades and with the generalisation of the Internet of Things (IoT) its growth has increased. The number of attacks to this kind of infrastructures have ...

    • Early Detection of Depression: Social Network Analysis and Random Forest Techniques 

      Cacheda, Fidel; Fernández, Diego; Nóvoa, Francisco; Carneiro, Víctor (J M I R Publications, Inc., 2019-06-10)
      [Abstract] Background: Major depressive disorder (MDD) or depression is among the most prevalent psychiatric disorders, affecting more than 300 million people globally. Early detection is critical for rapid intervention, ...