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    • Federated Learning for Medical Applications: A Taxonomy, Current Trends, Challenges, and Future Research Directions 

      Rauniyar, Ashish; Hagos, Desta Haileselassie; Jha, Debesh; Håkegård, Jan Erik; Bagci, Ulas; Rawat, Danda B.; Vlassov, Vladimir (Peer reviewed; Journal article, 2023)
      With the advent of the Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) algorithms, the landscape of data-driven medical applications has emerged as a promising avenue ...
    • Machine learning based assessment of preclinical health questionnaires 

      Avram, Calin; Gligor, Adrian; Roman, Dumitru; Soylu, Ahmet; Nyulas, Victoria; Avram, Laura (Peer reviewed; Journal article, 2023)
      Background: Within modern health systems, the possibility of accessing a large amount and a variety of data related to patients' health has increased significantly over the years. The source of this data could be mobile ...
    • Towards a water-smart society: Progress in linking theory and practice 

      Damman, Sigrid; Schmuck, Alexandra; Oliveira, Rosário; Koop, Steven (Stef) H.A.; Almeida, Maria do Céu; Alegre, Helena; Ugarelli, Rita Maria (Peer reviewed; Journal article, 2023)
      Few scientific publications discuss the vision of the water-smart society. Our paper addresses this gap, outlining key principles of urban water–smartness and translating them into five strategic objectives to support ...
    • eHealth policy framework in Low and Lower Middle-Income Countries; a PRISMA systematic review and analysis 

      Mengiste, Shegaw Anagaw; Antypas, Konstantinos; Johannessen, Marius Rohde; Klein, Jörn; Kazemi, Gholamhossein (Peer reviewed; Journal article, 2023)
      Background: Low and lower middle-income countries suffer lack of healthcare providers and proper workforce education programs, a greater spread of illnesses, poor surveillance, efficient management, etc., which are addressable ...
    • The DYNABIC approach to resilience of critical infrastructures 

      Rios, Erkuden; Iturbe, Eider; Rego, Angel; Ferry, Nicolas; Tigli, Jean-Yves; Lavirotte, Stephane; Rocher, Gérald; Nguyen, Phu Hong; Song, Hui; Dautov, Rustem; Mallouli, Wissam; Cavalli, Ana Rosa (Chapter, 2023)
      With increasing interdependencies and evolving threats, maintaining operational continuity in critical systems has become a significant challenge. This paper presents the DYNABIC (Dynamic business continuity of critical ...
    • Uncertainty-aware Virtual Sensors for Cyber-Physical Systems 

      Sen, Sagar; Husom, Erik Johannes; Goknil, Arda; Tverdal, Simeon; Nguyen, Phu Hong (Peer reviewed; Journal article, 2023)
      We present a data pipeline to train and deploy uncertainty-aware virtual sensors in cyber-physical systems. Our virtual sensor predicts the expected values of a physical sensor and a standard deviation indicating the degree ...
    • AutoConf: Automated Configuration of Unsupervised Learning Systems using Metamorphic Testing and Bayesian Optimization 

      Shar, Lwin Khin; Goknil, Arda; Husom, Erik Johannes; Sen, Sagar; Tun, Yan Naing; Kim, Kisub (Chapter, 2023)
      Unsupervised learning systems using clustering have gained significant attention for numerous applications due to their unique ability to discover patterns and structures in large unlabeled datasets. However, their ...
    • TRANSQLATION: TRANsformer-based SQL RecommendATION 

      Tahmasebi, Shirin; Payberah, Amir H.; Soylu, Ahmet; Roman, Dumitru; Matskin, Mihhail (Chapter, 2023)
      The exponential growth of data production emphasizes the importance of database management systems (DBMS) for managing vast amounts of data. However, the complexity of writing Structured Query Language (SQL) queries requires ...
    • ContrastNER: Contrastive-based Prompt Tuning for Few-shot NER 

      Layegh, Amirhossein; Hossein Payberah, Amir; Soylu, Ahmet; Roman, Dumitru; Matskin, Mihhail (Chapter, 2023)
      Prompt-based language models have produced encouraging results in numerous applications, including Named Entity Recognition (NER) tasks. NER aims to identify entities in a sentence and provide their types. However, the ...
    • Ergodic Performance Analysis of Reconfigurable Intelligent Surface Enabled Bidirectional NOMA 

      Rauniyar, Ashish; Østerbø, Olav Norvald; Håkegård, Jan Erik (Chapter, 2023)
      This paper proposes and investigates a reconfigurable intelligent surface (RIS) enabled bidirectional non-orthogonal multiple access (NOMA) network termed as NOMA-RIS. Here, RIS allows multiple NOMA users in one group to ...
    • A Checklist for Supply Chain Security for Critical Infrastructure Operators 

      Jaatun, Martin Gilje; Sæle, Hanne (Chapter, 2024)
      Critical infrastructure applications do not emerge fully formed, but generally rely on components and services from third-party vendors. This paper presents a brief survey on good practice for security requirements to be ...
    • A method for threat modelling of industrial control systems 

      Flå, Lars; Jaatun, Martin Gilje (Chapter, 2024)
      In this paper, we propose a new method for threat modelling of industrial control systems (ICS). The method is designed to be flexible and easy to use. Model elements inspired by IEC 62443 and Data Flow Diagrams (DFD) are ...
    • An inclusive Lifecycle Approach for IoT Devices Trust and Identity Management 

      Loupos, Konstantinos; Niavis, Harris; Michalopoulos, Fotis; Misiakoulis, George; Skarmeta, Antonio F.; García, Jesús; Palomares, Angel; Song, Hui; Dautov, Rustem; Giampaolo, Francesca; Mancilla, Rosella; Costantino, Francesca; Van Landuyt, Dimitri; Michiels, Sam; More, Stefan; Xenakis, Christos; Bampatsikos, Michail; Politis, Ilias; Krilakis, Konstantinos; Syvridis, Dimitris (Chapter, 2023)
      ERATOSTHENES is an EC, co-funded, research project strongly considering modern security challenges in the domain of Internet of Things in mind of their huge penetration into our day to day lives. There are a series of ...
    • Real-Time Performance of Industrial IoT Communication Technologies: A Review 

      Behnke, Ilja; Austad, Henrik (Peer reviewed; Journal article, 2023)
      With the growing need for automation and the ongoing merge of OT and IT, industrial networks have to transport a high amount of heterogeneous data with mixed criticality such as control traffic, sensor data, and configuration ...
    • Global report on assistive technology 

      Antypas, Konstantinos; Austin, Victoria; Banes, David; Blakstad, Mats; Boot, Fleur Heleen; Botelho, Fernando; Burton, Angela; Calvo, Irene; Cook, Albert M.; Dasgupta, Rajib; Desideri, Lorenzo; Ebuenyi, Ikenna; Encarnação, Pedro; France, Tim; Gupta, Shivani; Holloway, Catherine; Johnson, Ceridwen; MacLachlan, Malcolm; Mannan, Hasheem; Marella, Manjula; McKinnon, Iain; Polgar, Jan; Muller, Sébastien; Layton, Natasha; Loeb, Micthell; Øderud, Tone; Patrick, Mikaela; Pryor, Wesley; Aniyamuzaala, James Rwampigi; Shae, Kylie; Sharma, Shweta; Singh, Ravinder; Smith, Emma; Tardiff, Claude (Research report, 2022)
      There is a large, unmet need for assistive technology worldwide. The Global report on assistive technology was developed in response to the World Health Assembly resolution (WHA71.8) on improving access to assistive ...
    • Jammertest 2022: Jamming and Spoofing Lessons Learned 

      Morrison, Aiden J; Sokolova, Nadezda; Solberg, Anders Martin; Gerrard, Nicolai; Rødningsby, Anders; Hauglin, Harald; Rødningen, Thomas; Dahlø, Tor Ole (Peer reviewed; Journal article, 2023)
      Jammertest 2022 was a week-long series of satellite navigation and timing signal jamming and spoofing exercises carried out on the Norwegian island of Andøya in September of 2022. Organized via a collaboration between the ...
    • Kunnskapsoversikt cyberkriminalitet 

      Meland, Per Håkon; Bjørge, Nina Møllerstuen; Høiby, Marte; Kilskar, Stine Skaufel (SINTEF Rapport;2023:01331, Research report, 2024)
      På oppdrag fra Justis- og beredskapsdepartementet har SINTEF gjennomført en systematisk litteraturstudie for å adressere forskningsspørsmål knyttet til begreps-definisjoner og hvordan man kan måle omfang av fenomenet ...
    • Balancing the Norwegian regulated power market anno 2016 to 2022 

      Austnes, Pål Forr; Riemer-Sørensen, Signe; Bordvik, David Andreas; Andresen, Christian Andre (Peer reviewed; Journal article, 2024)
      The balancing market for power is designed to account for the difference between predicted supply/demand of electricity and the realised supply/demand. However, increased electrification of society changes the consumption ...
    • Enhancing elasticity models with deep learning: A novel corrective source term approach for accurate predictions 

      Sørbø, Sondre; Blakseth, Sindre Stenen; Rasheed, Adil; Kvamsdal, Trond; San, Omer (Peer reviewed; Journal article, 2024)
    • Verdiskapingsutviklingen for produksjonsbedrifter i Arena Skog. TFoU-rapport 2019:10. 

      Sand, Roald; Sollid, Torgunn (Research report, 2019)
      Formålet med rapporten er å belyse verdiskapingsutviklingen de siste årene for produksjonsbedriftene som er medlem av Arena Skog. Disse produksjonsbedriftene driver i hovedsak innen skognæringen, dvs. skogbruk og tilhørende ...