• Enhancing smart road safety with federated learning for Near Crash Detection to advance the development of the Internet of Vehicles 

      Djenouri, Youcef; Belbachir, Nabil; Michalak, Tomasz; Belhadi, Asma; Srivastava, Gautam (Peer reviewed; Journal article, 2024)
      We introduce an innovative methodology for the identification of vehicular collisions within Internet of Vehicles (IoV) applications. This approach combines a knowledge base system with deep learning for model selection ...
    • Evolutionary-based automated testing for GraphQL APIs 

      Belhadi, Asma; Zhang, Man; Arcuri, Andrea (GECCO: Genetic and Evolutionary Computation Conference;GECCO '22: Proceedings of the Genetic and Evolutionary Computation Conference Companion, Conference object, 2022)
      The Graph Query Language (GraphQL) is a powerful language for APIs manipulation in web services. It has been recently introduced as an alternative solution for addressing the limitations of RESTful APIs. This paper introduces ...
    • Federated Constrastive Learning and Visual Transformers for Personal Recommendation 

      Belhadi, Asma; Djenouri, Youcef; Andrade, Fabio Augusto de Alcantara; Srivastava, Gautam (Peer reviewed; Journal article, 2024)
      This paper introduces a novel solution for personal recommendation in consumer electronic applications. It addresses, on the one hand, the data confidentiality during the training, by exploring federated learning and trusted ...
    • An intelligent collaborative image-sensing system for disease detection 

      Djenouri, Youcef; Belhadi, Asma; Yazidi, Anis; Srivastava, Gautam; Chatterjee, Pushpita; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2023)
      In this paper we introduce a novel framework for disease detection. The framework is based on intelligent agents where each agent studies the interaction among the different medical data observations using reinforcement ...
    • Intelligent digital tools for screening of brain connectivity and dementia risk estimation in people affected by mild cognitive impairment: the AI-Mind clinical study protocol 

      Haraldsen, Ira Hebold; Hatlestad-Hall, Christoffer; Marra, Camillo; Renvall, Hanna; Maestú, Fernando; Acosta-Hernández, Jorge; Alfonsin, Soraya; Andersson, Vebjørn; Anand, Abhilash; Ayllón, Victor; Babic, Aleksandar; Belhadi, Asma; Birck, Cindy; Bruña, Ricardo; Caraglia, Naike; Carrarini, Claudia; Christensen, Erik; Cicchetti, Americo; Daugbjerg, Signe; Di Bidino, Rossella; Diaz-Ponce, Ana; Drews, Ainar; Giuffrè, Guido Maria; Georges, Jean; Gil-Gregorio, Pedro; Gove, Dianne; Govers, Tim M.; Hallock, Harry; Hietanen, Marja; Holmen, Lone; Hotta, Jaakko; Kaski, Samuel; Khadka, Rabindra; Kinnunen, Antti S.; Koivisto, Anne M.; Kulashekhar, Shrikanth; Larsen, Denis; Liljeström, Mia; Lind, Pedro; Marcos Dolado, Alberto; Marshall, Serena; Merz, Susanne; Miraglia, Francesca; Montonen, Juha; Mäntynen, Ville; Øksengård, Anne Rita; Olazarán, Javier; Paajanen, Teemu; Peña, José M.; Peña, Luis; Peniche, Daniel lrabien; Sanz Perez, Ana; Radwan, Mohamed; Ramírez-Toraño, Federico; Rodríguez-Pedrero, Andrea; Saarinen, Timo; Salas-Carrillo, Mario; Salmelin, Riitta; Sousa, Sonia; Suyuthi, Abdillah; Toft, Mathias; Toharia, Pablo; Tveitstøl, Thomas; Tveter, Mats; Upreti, Ramesh; Vermeulen, Robin J.; Vecchio, Fabrizio; Yazidi, Anis; Rossini, Paolo Maria (Peer reviewed; Journal article, 2023)
      More than 10 million Europeans show signs of mild cognitive impairment (MCI), a transitional stage between normal brain aging and dementia stage memory disorder. The path MCI takes can be divergent; while some maintain ...
    • Interpretable intrusion detection for next generation of Internet of Things 

      Djenouri, Youcef; Belhadi, Asma; Srivastava, Gautam; Lin, Jerry Chun-Wei; Yazidi, Anis (Peer reviewed; Journal article, 2023)
      This paper presents a new framework for intrusion detection in the next-generation Internet of Things. MinMax normalization strategy is used to collect and preprocess data. The Marine Predator algorithm is then used to ...
    • JavaScript SBST Heuristics to Enable Effective Fuzzing of NodeJS Web APIs 

      Zhang, Man; Belhadi, Asma; Arcuri, Andrea (Peer reviewed; Journal article, 2023)
      JavaScript is one of the most popular programming languages. However, its dynamic nature poses several challenges to automated testing techniques. In this paper, we propose an approach and open-source tool support to enable ...
    • Random Testing and Evolutionary Testing for Fuzzing GraphQL APIs 

      Belhadi, Asma; Zhang, Man; Arcuri, Andrea (Peer reviewed; Journal article, 2023)
      The Graph Query Language (GraphQL) is a powerful language for APIs manipulation in web services. It has been recently introduced as an alternative solution for addressing the limitations of RESTful APIs. This paper introduces ...
    • Shapley visual transformers for image-to-text generation 

      Belhadi, Asma; Djenouri, Youcef; Belbachir, Nabil; Michalak, Tomasz; Srivastava, Gautam (Peer reviewed; Journal article, 2024)
      In the contemporary landscape of the web, text-to-image generation stands out as a crucial information service. Recently, deep learning has emerged as the cutting-edge methodology for advancing text-to-image generation ...
    • Social Web in IoT: Can Evolutionary Computation and Clustering Improve Ontology Matching for Social Web of Things? 

      Belhadi, Asma; Djenouri, Djamel; Djenouri, Youcef; Belbachir, Nabil; Srivastava, Gautam (IEEE Transactions on Computational Social Systems;, Peer reviewed; Journal article, 2023)
      Many Internet of Things (IoT) applications can benefit from Social Web of Things (S-WoT) methods that enable knowledge discovery and help solving interoperability problems. The semantic modeling of S-WoT is the main emphasis ...
    • Spatio-temporal visual learning for home-based monitoring 

      Djenouri, Youcef; Belbachir, Nabil; Cano, Alberto; Belhadi, Asma (Peer reviewed; Journal article, 2024)
      This paper introduces a novel concept for Home-based Monitoring (HM) that enables robust analysis and understanding of activities towards improved caring and safety. Spatio-Temporal Visual Learning for HM (STVL-HM) is a ...