• Automated estimation of mitral annular plane systolic excursion by artificial intelligence from 3D ultrasound recordings 

      Tasken, Anders Austlid; Berg, Erik Andreas Rye; Grenne, Bjørnar Leangen; Holte, Espen; Dalen, Håvard; Stølen, Stian Bergseng; Lindseth, Frank; Aakhus, Svend; Kiss, Gabriel Hanssen (Peer reviewed; Journal article, 2023)
      Perioperative monitoring of cardiac function is beneficial for early detection of cardiovascular complications. The standard of care for cardiac monitoring performed by trained cardiologists and anesthesiologists involves ...
    • Characterizing Multi-Chip GPU Data Sharing 

      Zhang, Shiqing; Naderan-Tahan, Mahmood; Jahre, Magnus; Eeckhout, Lieven (Journal article; Peer reviewed, 2023)
      Multi-chip Graphics Processing Unit (GPU) systems are critical to scale performance beyond a single GPU chip for a wide variety of important emerging applications. A key challenge for multi-chip GPUs, though, is how to ...
    • Conceptualization and scalable execution of big data workflows using domain-specific languages and software containers 

      Nikolov, Nikolay; Dessalk, Yared Dejene; Khan, Akif Quddus; Soylu, Ahmet; Matskin, Mihhail; Payberah, Amir; Roman, Dumitru (Journal article; Peer reviewed, 2021)
      Big Data processing, especially with the increasing proliferation of Internet of Things (IoT) technologies and convergence of IoT, edge and cloud computing technologies, involves handling massive and complex data sets on ...
    • Creating Dynamic Checklists via Bayesian Case-Based Reasoning: Towards Decent Working Conditions for All 

      Flogard, Eirik Lund; Mengshoel, Ole Jakob; Bach, Kerstin (Peer reviewed; Journal article, 2022)
      Every year there are 1.9 million deaths world-wide attributed to occupational health and safety risk factors. To address poor working conditions and fulfill UN's SDG 8, "protect labour rights and promote safe working ...
    • Data driven case base construction for prediction of success of marine operations 

      Mathisen, Bjørn Magnus; Aamodt, Agnar; Langseth, Helge (Journal article; Peer reviewed, 2017)
      It is a common situation to have lots of recorded data that you want to use for improving a process in your organization or make use of this data to provide new services or products. Starting with one primary data set we ...
    • Delegated Replies: Alleviating Network Clogging in Heterogeneous Architectures 

      Zhao, Xia; Eeckhout, Lieven; Jahre, Magnus (Peer reviewed; Journal article, 2022)
      Heterogeneous architectures with latency-sensitive CPU cores and bandwidth-intensive accelerators are attractive as they deliver high performance at favorable cost. These architectures typically have significantly more ...
    • Electronic Health Record improvement using incident reports 

      Teame, Tesfay; Stålhane, Tor; Nytrø, Øystein (Journal article; Peer reviewed, 2017)
      This paper discusses reactive improvement of clinical software using methods for incident analysis. We used the “Five Whys” method because we had only descriptive data and depended on a domain expert for the analysis. The ...
    • Evaluating the effectiveness of game-based learning for teaching refugee children Arabic using the integrated LEAGUÊ-GQM approach 

      Tahir, Rabail; Wang, Alf Inge (Peer reviewed; Journal article, 2022)
      Game-based learning (GBL) is widely utilised in various domains and continues to receive interest and attention from researchers and practitioners alike. However, there is still a lack of empirical evidence concerning its ...
    • EVICARE Sluttrapport: Fra forskning til praksis – fra praksis til kunnskap 

      Nytrø, Øystein; Eiring, Øystein; Hovland, Kristin Hildegard (Research report, 2015)
      EviCare var det første, offentlige innovasjonsprosjektet innen IKT i Norge som fikk støtte fra Norges Forskningsråd. Hovedmålet med prosjektet var å utvikle metoder og teknologi som leverer forskningsbasert kunnskap der ...
    • Extracting news events from microblogs 

      Øystein, Repp; Ramampiaro, Heri (Journal article; Peer reviewed, 2018)
      Twitter stream has become a large source of information, but the magnitude of tweets posted and the noisy nature of its content makes harvesting of knowledge from Twitter has challenged researchers for long time. Aiming ...
    • Gender Equality in Tech Entrepreneurship: A Systematic Mapping Study 

      Wilson, Alis Wiken; Patón-Romero, Jose David (Chapter, 2022)
      The largest gender gaps within entrepreneurship today are in the Information Technology (IT) sector, where male entrepreneurs are more than twice as likely as women to operate. The current gender gap in tech society needs ...
    • Health and Social Impacts of Playing Pokémon Go on Various Player Groups 

      Wang, Alf Inge; Skjervold, Audun (Peer reviewed; Journal article, 2021)
      Pokémon Go might be considered to be one of the most successful exergames ever released. When the game was released in the summer of 2016, Pokémon Go players spent more time exercising, being outdoors, and socializing with ...
    • High Utility Drift Detection in Quantitative Data Streams 

      Duong, Quang-Huy; Ramampiaro, Heri; Nørvåg, Kjetil; Fournier-Viger, Philippe; Dam, Thu-Lan (Journal article; Peer reviewed, 2018)
      This paper presents an efficient algorithm for detecting changes (drifts) in the utility distributions of patterns, named High Utility Drift Detection in Transactional Data Stream (HUDD-TDS). The algorithm is specifically ...
    • hUGe2: An Interdisciplinary Research Program for Sustainability 

      Patón-Romero, Jose David; Jaccheri, Maria Letizia (Chapter, 2021)
      The continuous adoption and evolution of technology in all aspects and areas of our lives and our environment entails new and complex challenges and asks for interdisciplinary perspective to avoid biases that affect ...
    • Imaging framework: An interoperable and extendable connector for image-related Java frameworks 

      Christoph, Praschl; Andreas, Pointner; Baumgartner, David; Gerald Adam, Zwettler (Peer reviewed; Journal article, 2021)
      The number of computer vision and image processing tasks has increased during the last years. Although Python is most of the time the first choice in this area, there are situations, where the utilization of another ...
    • Learning similarity measures from data 

      Mathisen, Bjørn Magnus; Aamodt, Agnar; Langseth, Helge; Bach, Kerstin (Journal article; Peer reviewed, 2019)
      Defining similarity measures is a requirement for some machine learning methods. One such method is case-based reasoning (CBR) where the similarity measure is used to retrieve the stored case or a set of cases most similar ...
    • LMT: Accurate and Resource-Scalable Slowdown Prediction 

      Salvesen, Peter; Jahre, Magnus (Peer reviewed; Journal article, 2022)
      Multi-core processors suffer from inter-application interference which makes the performance of an application depend on the behavior of the applications it happens to be co-scheduled with. This results in performance ...
    • Near-optimal multi-accelerator architectures for predictive maintenance at the edge 

      Koraei, Mostafa; Cebrian, Juan Manuel; Jahre, Magnus (Peer reviewed; Journal article, 2023)
    • Pedagogical agents: Influences of artificially generated instructor personas on taking chances 

      Jost, Patrick (Peer reviewed; Journal article, 2020)
      Educational institutes are currently facing the new normality that an ongoing pandemic situation has brought to teaching and learning. Distributed learning with content that blends over several platforms and locations needs ...
    • Quantifying quality: Towards a Post-Humanist Perspective on Sensemaking 

      Monteiro, Eric; Østerlie, Thomas; Parmiggiani, Elena; Mikalsen, Marius (Chapter, 2018)
      Processes of quantifying the qualitative have deep historical roots that demonstrate their contested nature. The ongoing push for Big Data/data science presupposes the quantification of qualitative phenomena. We analyse ...