Ponències/Comunicacions de congressos: Enviaments recents

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    • Do DL models and training environments have an impact on energy consumption? 

      Rey Juárez, Santiago del; Martínez Fernández, Silverio Juan; Cruz, Luís; Franch Gutiérrez, Javier (Institute of Electrical and Electronics Engineers (IEEE), 2023)
      Text en actes de congrés
      Accés obert
      Current research in the computer vision field mainly focuses on improving Deep Learning (DL) correctness and inference time performance. However, there is still little work on the huge carbon footprint that has training ...

    • Adaptive task-oriented chatbots using feature-based knowledge bases 

      Campàs Gené, Carla; Motger de la Encarnación, Joaquim; Franch Gutiérrez, Javier; Marco Gómez, Jordi (Springer, 2023)
      Comunicació de congrés
      Accés restringit per política de l'editorial
      Task-oriented chatbots relying on a knowledge base for domain-specific content exploitation have been largely addressed in research and industry applications. Despite this, multiple challenges remain to be fully conquered, ...

    • Comparision of models built using AutoML and data fusion 

      Haq, Anam; Wilk, Szymon; Abelló Gamazo, Alberto (Springer, 2022)
      Text en actes de congrés
      Accés obert
      Automated machine learning (AutoML) has made life easier for data analysts or scientists by providing quick insights into data by building machine learning (ML) models. AutoML techniques are applied to vast areas from image ...

    • Towards green AI-based software systems: an architecture-centric approach (GAISSA) 

      Martínez Fernández, Silverio Juan; Franch Gutiérrez, Javier; Durán López, Francisco Javier (Institute of Electrical and Electronics Engineers (IEEE), 2023)
      Text en actes de congrés
      Accés obert
      Nowadays, AI-based systems have achieved out-standing results and have outperformed humans in different domains. However, the processes of training AI models and inferring from them require high computational resources, ...

    • Metrics for code smells of ML pipelines 

      Costal Costa, Dolors; Gómez Seoane, Cristina; Martínez Fernández, Silverio Juan (Springer, 2023)
      Comunicació de congrés
      Accés restringit per política de l'editorial
      ML pipelines, as key components of ML systems, shall be developed following quality assurance techniques. Unfortunately, it is often the case in which they present maintainability issues, due to the experimentatal nature ...

    • Insights from using goal models for teaching data structures 

      Ruiz, Marcela; Franch Gutiérrez, Javier (CEUR-WS.org, 2023)
      Text en actes de congrés
      Accés obert
      Previous research has shown the feasibility of using goal models as a notation to describe data structures. Such results motivated further empirical research to elucidate the extent to which teaching data structures using ...

    • Learning analytics’ privacy in the fog and edge computing: a systematic mapping review 

      Amo Filvà, Daniel; Fonseca Escudero, David; García Peñalvo, Francisco José; Alier Forment, Marc; Casany Guerrero, María José (Springer Nature, 2022)
      Comunicació de congrés
      Accés restringit per política de l'editorial
      The educational context that integrates Learning Analytics processes presents a high fragility in the data processing. In addition, using analytical technologies in cloud computing adds new drawbacks that increase such ...

    • The maker movement in engineering education: A partial literature review of the research opportunities on competency development 

      Saavedra Munar, Leonardo; Alier Forment, Marc (Springer Nature, 2022)
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      This paper presents a partial review of the literature related to the maker movement, its inclusion in engineering education and the way in which this insertion contributes on the development of skills. Initially, it is ...

    • Roleplay ethical debates, an activity to learn to apply ethical theories to dilemmas and improve critical thinking 

      Casany Guerrero, María José; Alier Forment, Marc (Springer Nature, 2022)
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      Accés restringit per política de l'editorial
      The teaching of ethics in engineering curriculums is gaining impor- tance and relevance, especially in disciplines related to computer science, software engineering, data science and artificial intelligence. This paper ...

    • Exploring the carbon footprint of Hugging Face's ML models: a repository mining study 

      Castaño Fernández, Joel; Martínez Fernández, Silverio Juan; Franch Gutiérrez, Javier; Bogner, Justus (Institute of Electrical and Electronics Engineers (IEEE), 2023)
      Text en actes de congrés
      Accés obert
      Background: The rise of machine learning (ML) systems has exacerbated their carbon footprint due to increased capabilities and model sizes. However, there is scarce knowledge on how the carbon footprint of ML models is ...

    • Towards a modern quality framework 

      Glinz, Martin; Seyff, Norbert; Bühne, Stan; Franch Gutiérrez, Javier; Lauenroth, Kim (Institute of Electrical and Electronics Engineers (IEEE), 2023)
      Text en actes de congrés
      Accés obert
      Quality frameworks have been used in requirements engineering (RE) for a long time to help elicit and document quality requirements. However, existing quality frameworks have major issues that hamper their applicability, ...

    • Mobile feature-oriented knowledge base generation using knowledge graphs 

      Motger de la Encarnación, Joaquim; Franch Gutiérrez, Javier; Marco Gómez, Jordi (Springer, 2023)
      Comunicació de congrés
      Accés restringit per política de l'editorial
      Knowledge bases are centralized repositories used for developing knowledge-oriented information systems. They are essential for adaptive, specialized knowledge in dialogue systems, supporting up-to-date domain-specific ...