• Random sparse generators of Markovian evolution and their spectral properties 

      Nakerst, Goran; Denysov, Sergiy; Haque, Masudul (Peer reviewed; Journal article, 2023)
      The evolution of a complex multi-state system is often interpreted as a continuous-time Markovian process. To model the relaxation dynamics of such systems, we introduce an ensemble of random sparse matrices which can be ...
    • Random Testing and Evolutionary Testing for Fuzzing GraphQL APIs 

      Belhadi, Asma; Zhang, Man; Arcuri, Andrea (Peer reviewed; Journal article, 2023)
      The Graph Query Language (GraphQL) is a powerful language for APIs manipulation in web services. It has been recently introduced as an alternative solution for addressing the limitations of RESTful APIs. This paper introduces ...
    • Real-time Analysis of Physical Performance Parameters in Elite Soccer 

      Andreassen, Kim Hartvedt; Johansen, Dag; Johansen, Håvard D.; Matias Do Vale Baptista, Ivan Andre; Pettersen, Svein Arne; Riegler, Micheal; Halvorsen, Pål (International Conference on Content-Based Multimedia Indexing (CBMI);, Conference object, 2019-10-21)
      Technology is having vast impact on the sports industry, and in particular soccer. All over the world, soccer teams are adapting digital information systems to quantify performance metrics. The goal is to assess strengths ...
    • Real-Time Detection of Events in Soccer Videos using 3D Convolutional Neural Networks 

      Rognved, Olav; Hicks, Steven; Lasantha Bandara Thambawita, Vajira; Stensland, Håkon Kvale; Zouganeli, Evi; Johansen, Dag; Riegler, Michael A.; Halvorsen, Pål (IEEE International Symposium on Multimedia; 2020 IEEE International Symposium on Multimedia (ISM), Chapter; Peer reviewed, 2020-01-22)
      In this paper, we present an algorithm for automatically detecting events in soccer videos using 3D convolutional neural networks. The algorithm uses a sliding window approach to scan over a given video to detect events ...
    • Real-Time Event Detection with Random Forests and Temporal Convolutional Networks for More Sustainable Petroleum Industry 

      Qu, Yuanwei; Zhou, Baifan; Waaler, Arild Torolv Søetorp; Cameron, David B. (Journal article, 2023)
      The petroleum industry is crucial for modern society, but the production process is complex and risky. During the production, accidents or failures, resulting from undesired production events, can cause severe environmental ...
    • Real-Time Polyp Detection, Localization and Segmentation in Colonoscopy Using Deep Learning 

      Jha, Debesh; Ali, Sharib; Tomar, Nikhil Kumar; Johansen, Håvard D.; Johansen, Dag; Rittscher, Jens; Riegler, Michael A.; Halvorsen, Pal (IEEE Access;Volume: 9, Peer reviewed; Journal article, 2021-03-04)
      Computer-aided detection, localization, and segmentation methods can help improve colonoscopy procedures. Even though many methods have been built to tackle automatic detection and segmentation of polyps, benchmarking of ...
    • Real-Time Polyp Detection, Localization and Segmentation in Colonoscopy Using Deep Learning 

      Jha, Debesh; Ali, Sharib; Tomar, Nikhil Kumar; Johansen, Håvard D.; Johansen, Dag; Rittscher, Jens; Riegler, Michael; Halvorsen, Pål (IEEE Access;Volume: 9, 2021, Peer reviewed; Journal article, 2021-03-04)
      Computer-aided detection, localization, and segmentation methods can help improve colonoscopy procedures. Even though many methods have been built to tackle automatic detection and segmentation of polyps, benchmarking of ...
    • Recovering Request Patterns to a CPU Processor from Observed CPU Consumption Data 

      Hammer, Hugo Lewi; Yazidi, Anis; Bratterud, Alfred; Haugerud, Hårek; Feng, Boning (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering;188(1), Journal article; Peer reviewed, 2016)
      Statistical queuing models are popular to analyze a computer systems ability to process different types requests. A common strategy is to run stress tests by sending artificial requests to the system. The rate ...
    • Recurrent Neural Network-Based Prediction of TCP Transmission States from Passive Measurements 

      Hagos, Desta Haileselassie; Engelstad, Paal E.; Yazidi, Anis; Kure, Øivind (2018 IEEE 17th International Symposium on Network Computing and Applications (NCA);, Chapter; Chapter; Peer reviewed, 2018-11-29)
      Long Short-Term Memory (LSTM) neural networks are a state-of-the-art techniques when it comes to sequence learning and time series prediction models. In this paper, we have used LSTM-based Recurrent Neural Networks (RNN) ...
    • Reducing False Detection during Inspection of HDD using Super Resolution Image Processing and Deep Learning 

      Ieamsaard, Jirarat; Sandnes, Frode Eika; Muneesawang, Paisarn (Journal article; Peer reviewed, 2017)
      High false detection rates are a key reliability challenge in the Hard Disk Drive (HDD) industry. Therefore, automatic visual inspection is increasingly employed for HDD inspection. In order ...
    • Reducing Scanning Keyboard Input Errors with Extended Start Dwell-Time 

      Sandnes, Frode Eika; Eika, Evelyn; Medola, Fausto Orsi (Journal article; Peer reviewed, 2018)
      Some individuals with reduced motor function rely on scanning keyboards to operate computers. A problem observed with scanning keyboards is that errors typically occur during the first group or first cell of a group. This ...
    • 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 (Lecture Notes in Business Information Processing;, Chapter; Peer reviewed; Conference object; Journal article, 2023)
      State-of-the-art approaches for managing Big Data pipelines assume their anatomy is known by design and expressed through adhoc Domain-Specific Languages (DSLs), with insufficient knowledge of the dark data involved in the ...
    • Reference deployment models for eliminating user concerns on cloud security 

      Zhao, Gansen; Rong, Chunming; Jaatun, Martin Gilje; Sandnes, Frode Eika (Journal article; Peer reviewed, 2010-06-17)
      Cloud computing has become a hot topic both in research and in industry, and when making decisions on deploying/adopting cloud computing related solutions, security has always been a major concern. This article summarizes ...
    • Reflective Text Entry: A Simple Low Effort Predictive Input Method Based on Flexible Abbreviations 

      Sandnes, Frode Eika (Procedia Computer Science;67, Journal article; Peer reviewed, 2015-11-06)
      Users with reduced physical functioning such as ALS patients need more time and effort to operate computers. Most of the previous assistive technologies use prefix based predictive text input algorithms. Prefix based ...
    • Regularity of twisted spectral triples and pseudodifferential calculi 

      Matassa, Marco; Yuncken, Robert (Journal of Noncommutative Geometry;, Journal article; Peer reviewed, 2019-03-13)
      We investigate the regularity condition for twisted spectral triples. This condition is equivalent to the existence of an appropriate pseudodifferential calculus compatible with the spectral triple. A natural approach to ...
    • Regulatory Intermediaries: The Role of Interest Organizations in Supporting Web Accessibility Policy Implementation. 

      Giannoumis, G. Anthony (Studies in Health Technology and Informatics;Volume 256: Transforming our World Through Design, Diversity and Education, Journal article; Peer reviewed, 2018)
      This article explores how interest organizations, including non-profit and commercial service providers, act as intermediaries to support the implementation of regulations for web accessibility. Web accessibility policies ...
    • Rehabilitation and Product Design: Towards the Inclusion of People with Disabilities Through Interdisciplinary Collaboration 

      Medola, Fausto Orsi; Sandnes, Frode Eika; Rodrigues, A. C. T.; Paschoarelli, L. C.; Silva, L. M. (Journal article; Peer reviewed, 2018)
      In low-GDP countries, such as Brazil, many older people and people with disabilities rely on the public health system for access to assistive devices, which are important to support them to live healthy and dignified lives. ...
    • A reinforcement learning based game theoretic approach for distributed power control in downlink NOMA 

      Rauniyar, Ashish; Yazidi, Anis; Engelstad, Paal E.; Østerbø, Olav Norvald (IEEE International Symposium on Network Computing and Applications; 2020 IEEE 19th International Symposium on Network Computing and Applications (NCA), Chapter; Peer reviewed, 2021-01-05)
      Optimal power allocation problem in wireless networks is known to be usually a complex optimization problem. In this paper, we present a simple and energy-efficient distributed power control in downlink Non-Orthogonal ...
    • Relativistic dynamics for hydrogenlike systems 

      Kjellsson, Tor; Selstø, Sølve; Bræck, Simen; Lindroth, Eva (Peer reviewed; Journal article, 2015)
      The interaction between super intense laser pulses and hydrogenlike systems is investigated. We aim to study cases where the field drives the electron up to velocities of v~0.5c, where relativistic effects are believed to ...