Blar i Institutt for datateknologi, elektroteknologi og realfag på tittel

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    • Higher order stable schemes for stochastic convection-reaction-diffusion equations driven by additive Wiener noise 

      Tambue, Antoine; Mukam, Jean Daniel (Peer reviewed; Journal article, 2021)
      In this paper, we investigate the numerical approximation of stochastic convection–reaction–diffusion equations using two explicit exponential integrators. The stochastic partial differential equation (SPDE) is driven by ...

    • Highlights of experimental results from ALICE 

      Acharya, Shreyasi; Adam, Jaroslav; Adamová, Dagmar; Adolfsson, Jonatan; Aggarwal, Madan M.; Aglieri Rinella, G; Agnello, Michelangelo; Agrawal, Nikita; Ahammed, Zubayer; Ahn, SU; Alme, Johan; Altenkaemper, Lucas; Arsene, Ionut Christian; Bätzing, Paul Christoph; Djuvsland, Øystein; Dordic, Olja; Helstrup, Håvard; Hetland, Kristin Fanebust; Kileng, Bjarte; Langøy, Rune; Lardeux, Antoine Xavier; Lien, Jørgen André; Lindal, Svein; Lønne, Per-Ivar; Mahmood, Sohail Musa; Milosevic, Jovan; Nesbø, Simon Voigt; Nystrand, Joakim; Rehman, Attiq Ur; Richter, Matthias Rudolph; Røed, Ketil; Røhrich, Dieter; Skaali, Toralf Bernhard; Tambave, Ganesh Jagannath; Tveter, Trine Spedstad; Ullaland, Kjetil; Velure, Arild; Wagner, Boris; Wikne, Jon Christopher; Zhang, Hui; Zhao, Chengxin; Zhou, Zhuo; Zhu, Hongsheng; Aiola, Salvatore; Akindinov, Alexander; Alam, Sk Noor; Alba, José Luis Bazo; De Albuquerque, Danilo Silva; Aleksandrov, Dimitry; Allessandro, B; ALICE, Collaboration (Peer reviewed; Journal article, 2017)

    • An HL7 FHIR and GraphQL approach for interoperability between heterogeneous Electronic Health Record systems 

      Mukhiya, Suresh Kumar; Lamo, Yngve (Peer reviewed; Journal article, 2021)
      Heterogeneities in data representation and care processes create interoperability complexity among Electronic Health Record systems (EHRs). We can resolve such data and process level heterogeneities by following consistent ...

    • Homomorphic-Encrypted Volume Rendering 

      Mazza, Sebastian; Patel, Daniel; Viola, Ivan (Journal article; Peer reviewed, 2021)
      Computationally demanding tasks are typically calculated in dedicated data centers, and real-time visualizations also follow this trend. Some rendering tasks, however, require the highest level of confidentiality so that ...

    • HTML graphics for video editor 

      Hjartøy, Jørgen Ullebø; Pettersen, Marensius Bae; Aarset, Brage Sekse (Bachelor thesis, 2021)

    • Human motion estimation for human-robot cooperation 

      Venås, Gizem Ates (Doctoral thesis, 2023)
      Human Robot Cooperation (HRC) refers to the cooperation between humans and robots to achieve a common goal or perform a task together. In HRC, the robot is designed to work alongside a human operator, providing assistance ...

    • Human Motion Estimation for Physical Human-Robot Collaboration 

      Ates, Gizem (Lecture, 2019)

    • Hvordan kan ekstern strategisk designkompetanse bidra i bedrifters innovasjonsprosesser? 

      Haavik, Erlend (Master thesis, 2015-05-18)
      En studie av prosjekter gjennomført mellom designbedrifter og bedrifter i havnæringene. Oppgaven ser på hvordan ekstern strategisk designkompetanse kan bidra i bedrifters innovasjonsprosesser. Oppgaven har et dyadisk ...

    • Hybrid Density Functional Study of Au2Cs2I6, Ag2GeBaS4, Ag2ZnSnS4, and AgCuPO4 for the Intermediate Band Solar Cells 

      Rasukkannu, Murugesan; Velauthapillai, Dhayalan; Vajeeston, Ponniah (Journal article; Peer reviewed, 2018)
      We present a comprehensive investigation of the structural, electronic, mechanical, and optical properties of four promising candidates, namely Au2Cs2I6, Ag2GeBaS4, Ag2ZnSnS4, and AgCuPO4, for application in photovoltaic ...

    • Hybrid intelligent framework for automated medical learning 

      Belhadi, Asma; Djenouri, Youcef; Diaz, Vicente Garcia; Houssein, Essam H.; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2021)
      This paper investigates the automated medical learning and proposes hybrid intelligent framework, called Hybrid Automated Medical Learning (HAML). The goal is the efficient combination of several intelligent components in ...

    • A hybrid multi-particle approach to range assessment-based treatment verification in particle therapy 

      Meric, Ilker; Alagoz, Enver; Hysing, Liv Bolstad; Kögler, Toni; Lathouwers, Danny; Lionheart, William R. B.; Mattingly, John; Obhodas, Jasmina; Pausch, Guntram; Pettersen, Helge Egil Seime; Ratliff, Hunter Nathaniel; Rovituso, Marta; Schellhammer, Sonja M.; Setterdahl, Lena Marie; Skjerdal, Kyrre; Sterpin, Edmond; Sudac, Davorin; Turko, Joseph A.; Ytre-Hauge, Kristian Smeland (Peer reviewed; Journal article, 2023)
      Particle therapy (PT) used for cancer treatment can spare healthy tissue and reduce treatment toxicity. However, full exploitation of the dosimetric advantages of PT is not yet possible due to range uncertainties, warranting ...

    • Hybrid treatment verification based on prompt gamma rays and fast neutrons: Multivariate modelling for proton range determination 

      Schellhammer, Sonja M.; Meric, Ilker; Löck, Steffen; Kögler, Toni (Peer reviewed; Journal article, 2023)
      Robust and fast in vivo treatment verification is expected to increase the clinical efficacy of proton therapy. The combined detection of prompt gamma rays and neutrons has recently been proposed for this purpose and shown ...

    • Hyper-graph-based attention curriculum learning using a lexical algorithm for mental health 

      Ahmed, Usman; Lin, Jerry Chun-Wei; Srivastava, Gautam (Peer reviewed; Journal article, 2022)
      In this paper, we propose a structure hypergraph and an emotional lexicon for word representation. Our method can solve problems related to vocabulary size, grammatical representation of words, and the lack of an emotional ...

    • Hypercube - multiplayer spill med Unreal Engine og dedikert server (Amazon Web Services Gamelift) 

      Irgens, Marius (Bachelor thesis, 2021)

    • I Can See Clearly Now: Clairvoyant Assertions for Deadlock Checking 

      Abusdal, Ole Jørgen; Din, Crystal Chang; Pun, Violet Ka I; Stolz, Volker (Peer reviewed; Journal article, 2022)
      Static analysers are traditionally used to check various correctness properties of software. In the face of refactorings that can have adverse effects on correctness, developers need to analyse the code after refactoring ...

    • Identification and authorization with single accelerometer data - implications from "Wearables in Arthritis" project 

      Mielnik, Pawel; Hjelle, Anja Myhre; Pollen, Bjarte; Tokarz, Krzysztof; Fojcik, Marcin Andrzej (Peer reviewed; Journal article, 2023)
      Introduction: Miniaturisation and development of mobile devices led to accelerometers being literally everywhere. The way we are moving seems intuitively very personal, resulting in increased interest in the possibility ...

    • IDS-INT: Intrusion detection system using transformer-based transfer learning for imbalanced network traffic 

      Ullah, Farhan; Ullah, Shamsher; Srivastava, Gautam; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2023)
      A network intrusion detection system is critical for cyber security against illegitimate attacks. In terms of feature perspectives, network traffic may include a variety of elements such as attack reference, attack type, ...

    • Image quality of list-mode proton imaging without front trackers 

      Sølie, Jarle Rambo; Volz, Lennart; Pettersen, Helge Egil Seime; Piersimoni, Pierluigi; Odland, Odd Harald; Røhrich, Dieter; Helstrup, Håvard; Peitzmann, Thomas; Ullaland, Kjetil; Varga-Kofarago, Monika; Mehendale, Shruti Vineet; Grøttvik, Ola Slettevoll; Eikeland, Viljar Nilsen; Meric, Ilker; Seco, Joao (Peer reviewed; Journal article, 2020)
      List mode proton imaging relies on accurate reconstruction of the proton most likely path (MLP) through the patient. This typically requires two sets of position sensitive detector systems, one upstream (front) and one ...

    • Impact of Deep Learning Libraries on Online Adaptive Lightweight Time Series Anomaly Detection 

      Lee, Ming-Chang; Lin, Jia-Chun (Chapter; Peer reviewed, 2023)
      Providing online adaptive lightweight time series anomaly detection without human intervention and domain knowledge is highly valuable. Several such anomaly detection approaches have been introduced in the past years, but ...

    • The impact of requirements on systems development speed: a multiple-case study in automotive 

      Ågren, Magnus S.; Knauss, Eric; Heldal, Rogardt; Pelliccione, Patrizio; Malmqvist, Gösta; Bodén, Jonas (Peer reviewed; Journal article, 2019)
      Automotive manufacturers have historically adopted rigid requirements engineering processes. This allowed them to meet safety-critical requirements when producing a highly complex and differentiated product out of the ...