Listar GI-Telemática-Artigos por autor "Fernández, Diego"

Mostrando ítems 1-6 de 6

    • 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 ...

    • Application of machine learning algorithms for the validation of a new CoAP-IoT anomaly detection dataset 

      Vigoya, Laura; Pardal Noya, Alberto; Fernández, Diego; Carneiro, Víctor (MDPI, 2023-04)
      [Abstract]: With the rise in smart devices, the Internet of Things (IoT) has been established as one of the preferred emerging platforms to fulfil their need for simple interconnections. The use of specific protocols such ...

    • 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, ...

    • 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 ...

    • IoT Dataset Validation Using Machine Learning Techniques for Traffic Anomaly Detection 

      Vigoya, Laura; Fernández, Diego; Carneiro, Víctor; Nóvoa, Francisco (MDPI, 2021)
      [Abstract] With advancements in engineering and science, the application of smart systems is increasing, generating a faster growth of the IoT network traffic. The limitations due to IoT restricted power and computing ...

    • Measuring Early Detection of Anomalies 

      López-Vizcaíno, Manuel F.; Novoa, Francisco; Fernández, Diego; Cacheda, Fidel (IEEE, 2022)
      [Abstract] Early detection is a matter of growing importance in multiple domains as network security, health conditions over social network services or weather forecasts related disasters. It is not enough to make a good ...