Recent Submissions

  • Virtual Actuator and Sensor Fault Tolerant Consensus for Homogeneous Linear Multi-Agent Systems 

    Rotondo, Damiano; Theilliol, Didier; Ponsart, Jean-Christophe (Peer reviewed; Journal article, 2023)
    This paper presents a fault tolerant consensus protocol for homogeneous linear multi-agent systems using virtual actuators and virtual sensors. By means of the virtual actuators/sensors, the faulty system is reconfigured ...
  • From Baseline to Top Performer: A Reproducibility Study of Approaches at the TREC 2021 Conversational Assistance Track 

    Lajewska, Weronika; Balog, Krisztian (Chapter, 2023)
    This paper reports on an effort of reproducing the organizers’ baseline as well as the top performing participant submission at the 2021 edition of the TREC Conversational Assistance track. TREC systems are commonly regarded ...
  • Modeling and identification of the Quanser Aero using a detailed description of friction and centripetal forces 

    Dyvik, Mathias; Fjereide, Didrik Efjestad; Rotondo, Damiano (Chapter, 2023)
    This paper deals with the modeling and identification of the Quanser Aero. The Quanser Aero is an aerospace laboratory setup designed for teaching aerospace concepts. Two propellers generate thrust and allow the user to ...
  • Distributed Ledger Technology Based Integrated Healthcare Solution for Bangladesh 

    ISLAM, MD. ARIFUL; ISLAM, MD. ANTONIN; JACKY, MD. AMZAD HOSSAIN; AL-AMIN, MD.; MIAH, MD. SAEF ULLAH; Khan, Md Muhidul Islam; HOSSAIN, MD. IQBAL (Peer reviewed; Journal article, 2023)
    Healthcare data is highly sensitive and must be safeguarded. Personal and sensitive data, such as names and addresses, is stored in Encrypted Electronic Health Records (EHRs). This paper proposes a Blockchain-based distributed ...
  • Generating Usage-related Questions for Preference Elicitation in Conversational Recommender Systems 

    Kostric, Ivica; Balog, Krisztian; Radlinski, Filip (Journal article, 2023)
    A key distinguishing feature of conversational recommender systems over traditional recommender systems is theirability to elicit user preferences using natural language. Currently, the predominant approach to preference ...
  • A Systematic Review of Fairness, Accountability, Transparency and Ethics in Information Retrieval 

    Bernard, Nolwenn; Balog, Krisztian (Peer reviewed; Journal article, 2023)
    We live in an information society that strongly relies on information retrieval systems, such as search engines and conversational assistants. Consequently, the trustworthiness of these systems is of critical importance, ...
  • Optimizing Document Classification: Unleashing the Power of Genetic Algorithms 

    Mustafa, Ghulam; Rauf, Abid; Al-Shamayleh, Ahmad Sami; Sulaiman, Muhammad; Afzal, Muhammad Tanvir; Akhunzada, Adnan (Peer reviewed; Journal article, 2023)
    Many individuals, including researchers, professors, and students, encounter difficulties when searching for scholarly documents, papers, and journals within a specific domain. Consequently, scholars have begun to focus ...
  • Exploring the need for a CERT for the Norwegian Construction Sector 

    Skytterholm, Andrea Neverdal; Jaatun, Martin Gilje (Chapter, 2023)
    This paper presents an empirical study on the need for sector-specific CERT capacity in the Norwegian construction sector. Findings from the interviews demonstrate a need for developing competence in ICT security in this ...
  • The Control Zendo: A Game of Inductive Logic for Teaching Automatic Control 

    Rotondo, Damiano; Jimarkon, Pattamawan; Fjereide, Didrik Efjestad (Peer reviewed; Journal article, 2023)
    Board games and card games have been used with some degree of success in the implementation of active strategies for education, since they stimulate problem solving and increase the learning and engagement of the students. ...
  • Are you sure it’s an artifact? Artifact detection and uncertainty quantification in histological images 

    Kanwal, Neel; Lopez-Perez, Miguel; Kiraz, Umay; Zuiverloon, Tahlita C M; Molina, Rafael (Peer reviewed; Journal article, 2023)
    Modern cancer diagnostics involves extracting tissue specimens from suspicious areas and conducting histotechnical procedures to prepare a digitized glass slide, called whole slide image (WSI), for further examination. ...
  • Design of switching state-feedback controllers for linear systems subject to asymmetric saturations 

    Ruiz, Adrián; Rotondo, Damiano; Morcego, Bernardo (Peer reviewed; Journal article, 2023)
    This paper considers the problem of controlling a linear system affected by asymmetrical input saturation. The proposed solution is based on using a linear matrix inequality (LMI)-based methodology to find the gains of a ...
  • Event-triggered fault-tolerant leader-following control for homogeneous multi-agent systems 

    Vazquez Trejo, Juan Antonio; Chadli, Mohammed; Rotondo, Damiano; Adam Medina, Manuel; Theilliol, Didier (Peer reviewed; Journal article, 2022)
    In this paper, the design of an event-triggered fault-tolerant control for leader-following consensus in multi-agent systems subject to actuator faults is presented. The problem under consideration is to reduce the control ...
  • The Weighted Kalman Filter 

    Rotondo, Damiano (Peer reviewed; Journal article, 2023)
    This paper proposes a new version of the Kalman filter, referred to as weighted Kalman filter (WKF). In the WKF some recent results on the weighted linearization of nonlinear systems are exploited to incorporate modifications ...
  • Impact of extent of resection on outcome from glioblastoma using the RANO resect group classification system: a retrospective, population-based cohort study 

    Bjorland, Line; Mahesparan, Rupavathana; Fluge, Øystein; Gilje, Bjørnar; Kurz, Kathinka Dæhli; Farbu, Elisabeth (Peer reviewed; Journal article, 2023)
    Background Extent of resection (EOR) is associated with survival in glioblastoma. A standardized classification for EOR was lacking until a system was recently proposed by the response assessment in neuro-oncology (RANO) ...
  • Automatic analysis of X (Twitter) data for supporting depression diagnosis 

    Królak, Aleksandra; Wiktorski, Tomasz; Żmudzińska, Aleksandra (Peer reviewed; Journal article, 2023-12)
    Depression is an increasingly common problem that often goes undiagnosed. The aim of this paper was to determine whether an analysis of tweets can serve as a proxy for assessing depression levels in the society. The work ...
  • Learning Parameterized ODEs From Data 

    Li, Qing; Evje, Steinar; Geng, Jiahui (Peer reviewed; Journal article, 2023)
    In contemporary research, neural networks are being used to derive Ordinary Differential Equations (ODEs) from observations. However, parameterized ODEs pose a more significant challenge than non-parameterized ODEs since ...
  • ARTICONF decentralized social media platform for democratic crowd journalism 

    Rito Lima, Inês; Filipe, Vasco; Marinho, Claudia; Ulisses, Alexandre; Chakravorty, Antorweep; Hristov, Atanas; Saurabh, Nishant; Zhao, Zhiming; Xin, Ruyue; Prodan, Radu (Peer reviewed; Journal article, 2023)
    Media production and consumption behaviors are changing in response to new technologies and demands, giving birth to a new generation of social applications. Among them, crowd journalism represents a novel way of constructing ...
  • Vision transformers for small histological datasets learned through knowledge distillation 

    Kanwal, Neel; Eftestøl, Trygve Christian; Khoraminia, Farbod; Zuiverloon, Tahlita C M; Engan, Kjersti (Chapter, 2023)
    Computational Pathology (CPATH) systems have the potential to automate diagnostic tasks. However, the artifacts on the digitized histological glass slides, known as Whole Slide Images (WSIs), may hamper the overall performance ...
  • Availability model of a 5G-MEC system 

    Pathirana, Thilina Dhanushka Kalahe; Nencioni, Gianfranco (Chapter, 2023)
    Multi-access Edge Computing (MEC) is one of the enabling technologies of the fifth generation (5G) of mobile networks. MEC enables services with strict latency requirements by bringing computing capabilities close to the ...
  • Analysis of Machine Learning Based Imputation of Missing Data 

    Rizvi, Syed Tahir Hussain; Latif, Muhammad Yasir; Amin, Muhammad Saad; Telmoudi, Achraf Jabeur; Shah, Nasir Ali (Peer reviewed; Journal article, 2023)
    Data analysis and classification can be affected by the availability of missing data in datasets. To deal with missing data, either deletion- or imputation-based methods are used that result in the reduction of data records ...

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