SINTEF Digital: Nye registreringer

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    • Defining a Remote Work Policy: Aligning Actions and Intentions 

      Smite, Darja; Moe, Nils Brede (Chapter, 2023)
      After the long period of forced work from home, many knowledge workers have not only developed a strong habit of remote work, but also consider flexibility as their personal right and no longer as a privilege. Existing ...

    • Unscheduled Meetings in Hybrid Work 

      Sporsem, Tor Thorsrud; Strand, Audun Fauchald; Hanssen, Geir Kjetil (Peer reviewed; Journal article, 2023)
      By studying four development teams in the Norwegian companies NAV and Entur, we found that unscheduled meetings are maintained by using tools like Discord and Zoom to create virtual rooms. From our findings, we provide ...

    • Organizational Debt in Large-Scale Hybrid Agile Software Development: A Case Study on Coordination Mechanisms 

      Liu, Zixuan; Stray, Viktoria; Sporsem, Tor Thorsrud (Chapter, 2023)
      Software development is a complex human-centered activity, increasingly complicated by agile organizations scaling and adopting hybrid work. While technical debt has been extensively studied, other forms of debt-organizational, ...

    • Business Development in Large-Scale Agile Software Development: Barriers and Enablers 

      Olsen, John Olav; Stray, Viktoria; Moe, Nils Brede (Chapter, 2023)
      Currently, many financial organizations must undergo a digital transformation. In this study, we investigated a transformation in a Norwegian fintech company with the aim of understanding how the tasks performed by business ...

    • Digital Transformation – A Flow Perspective 

      Ulfsnes, Rasmus; Mikalsen, Marius; Tkalich, Anastasiia; Moe, Nils Brede; Conboy, Kieran (Peer reviewed; Journal article, 2023)
      As we move along the ever-transforming world of digital technology and organizations, the perspective of how we view digital transformation (DT) also transforms. The episodic and continuous nature of changes requires an ...

    • Zero-Emission Rail in Czechia: Techno-economic analysis of lines R14, R21, R22, R25, R26, R27, SP14, U28 

      Zenith, Federico; Landmark, Andreas D.; Skeidsvoll, Line (SINTEF Rapport;2024:00230, Research report, 2024)
      This report analyses several representative regional, non-electrified rail lines in Czechia and evaluates different zero-emission technologies for their electrification: hydrogen, batteries, partial and full catenary. ...

    • Reporting of incidents in automated systems during drilling operations 

      Ottermo, Maria Vatshaug; Wille, Egil; Bjørkevoll, Knut Steinar; Bodsberg, Lars; Evjemo, Tor Erik; Fjørtoft, Kay Endre; Jaatun, Martin Gilje; Myklebust, Thor; Okstad, Eivind (SINTEF rapporter;2023:00191 A, Research report, 2023-02-06)
      This work is a preliminary study of how incidents, near misses and deviations within automated systems are currently detected, registered and, if appropriate, reported to the Petroleum Safety Authority Norway (PSA), as ...

    • Privacy-Aware IoT: State-of-the-Art and Challenges 

      Tokas, Shukun; Erdogan, Gencer; Stølen, Ketil (Chapter, 2023)
      The consumer IoT is now prevalent and creates an enormous amount of fine-grained, detailed information about consumers’ everyday actions, personalities, and preferences. Such detailed information brings new and unique ...

    • Ethical Design for Data Privacy and User Privacy Awareness in the Metaverse 

      Prillard, Ophelia; Boletsis, Costas; Tokas, Shukun (Peer reviewed; Journal article, 2024)
      The significance of the metaverse has been growing rapidly within the online realm. However, several challenges remain, including privacy, ethics, and governance. Extended reality (XR) devices used to access the metaverse ...

    • A Reference Data Model to Specify Event Logs for Big Data Pipeline Discovery 

      Benvenuti, Dario; Marrella, Andrea; Rossi, Jacopo; Nikolov, Nikolay Vladimirov; Roman, Dumitru; Soylu, Ahmet; Perales, Fernando (Peer reviewed; Journal article, 2023)
      State-of-the-art approaches for managing Big Data pipelines assume their anatomy is known by design and expressed through ad-hoc Domain-Specific Languages (DSLs), with insufficient knowledge of the dark data involved in ...

    • Measuring Community Response to Noise—Factors Affecting the Results of Annoyance Surveys 

      Gjestland, Truls Tormodsønn (Peer reviewed; Journal article, 2024)
      Social surveys are conducted to determine how annoyed people are in a certain noise situation. The results are typically presented as exposure–response curves showing the percentage of the area population that are highly ...

    • On the Evolution of Stress and Microstructure in Radio Frequency-Sputtered Lead-Free (Ba,Ca)(Zr,Ti)O3 Thin Films 

      Dahl-Hansen, Runar Plunnecke; Stange, Marit Synnøve Sæverud; Sunde, Tor Olav Løveng; Ræder, Johan Henrik; Rørvik, Per Martin Ljønes (Peer reviewed; Journal article, 2024)
      Thin-film piezoelectrics are widely investigated for actuators and energy harvesters, but there are few alternatives to toxic lead zirconate titanate. Biocompatible Ca- and Zr-modified BaTiO3 (BCZT) is one of the most ...

    • Pseudo-Hamiltonian system identification 

      Holmsen, Sigurd; Eidnes, Sølve; Riemer-Sørensen, Signe (Peer reviewed; Journal article, 2024)
      Identifying the underlying dynamics of physical systems can be challenging when only provided with observational data. In this work, we consider systems that can be modelled as first-order ordinary differential equations. ...

    • Pseudo-Hamiltonian neural networks for learning partial differential equations 

      Eidnes, Sølve; Lye, Kjetil Olsen (Peer reviewed; Journal article, 2024)
      Pseudo-Hamiltonian neural networks (PHNN) were recently introduced for learning dynamical systems that can be modelled by ordinary differential equations. In this paper, we extend the method to partial differential equations. ...

    • I Just Want to Help: SMEs Engaging with Cybersecurity Technology 

      Pickering, Brian; Phillips, Stephen C.; Erdogan, Gencer (Chapter, 2023)
      The cybersecurity landscape is particularly challenging for SMEs. On the one hand, they must comply with regulation or face legal sanction. But on the other, they may not have the resource or expertise to ensure regulatory ...

    • Towards Community-Driven Generative AI 

      Dautov, Rustem; Husom, Erik Johannes; Sen, Sagar; Song, Hui (Chapter, 2023)
      While the emerging market of Generative Artificial Intelligence (AI) is increasingly dominated and controlled by the Tech Giants, there is also a growing interest in open-source AI code and models from smaller companies, ...

    • A Need for Privacy-Assistive Technology in Notice and Consent Paradigm in IoT 

      Tokas, Shukun; Erdogan, Gencer (Chapter, 2023)
      A privacy notice is a document/notification that is addressed to consumers, describing how their personal information will be handled. While browsing the Internet, installing an app on smartphone, setting up a smart sensor ...

    • A Framework Addressing Challenges in Cybersecurity Testing of IoT Ecosystems and Components 

      Taylor, Steve; Jaatun, Martin Gilje; McGibney, Alan; Seidl, Robert; Hrynchenko, Pavlo; Prosvirin, Dmytro; Mancilla, Rosella (Chapter, 2024)
      This paper describes challenges within IoT ecosystems from the perspective of cybersecurity testing along with a proposed approach to address them that will be investigated in a recently started Horizon Europe project named ...

    • Customer journeys and process mining – challenges and opportunities 

      Halvorsrud, Ragnhild; Mannhardt, Felix; Prillard, Ophelia; Boletsis, Costas (Peer reviewed; Journal article, 2024)
      Recently, there has been increased awareness about the importance of data derived from actual customer journeys, including the subjective customer experience, in the analysis and evaluation of service quality. In this ...

    • Replay-Driven Continual Learning for the Industrial Internet of Things 

      Sen, Sagar; Nielsen, Simon; Husom, Erik Johannes; Goknil, Arda; Tverdal, Simeon; Pinilla, Leonardo (Chapter, 2023)
      The Industrial Internet of Things (IIoT) leverages thousands of interconnected sensors and computing devices to monitor and control large and complex industrial processes. Machine learning (ML) applications in IIoT use ...