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    • Selecting the Right Tool for the Task: A Hard-Soft Cake Eating Experiment with a Spoon and Fork 

      Bjarkum, Sondre; Chadoyan, Maximilian Stiegler; Medola, Fausto Orsi; Sandnes, Frode Eika (Advances in Intelligent Systems and Computing;volume 1269, Conference object, 2020-08-30)
      It is generally accepted that one need to select the correct tool for a given task. The same holds for eating utensils. A cake eating experiment was designed to determine if the visual appearance of cakes with different ...

    • Selection of Optimal EEG Electrodes for Human Emotion Recognition 

      Zhang, Jianhua; Chen, Peng (IFAC-PapersOnLine;Volume 53, Issue 2, 2020, Peer reviewed; Journal article, 2021-04-14)
      In recent years, emotion recognition has attracted increasing interest from researchers from diverse fields. Because of their intrinsic correlation with emotions, physiological signals based emotion recognition method is ...

    • Semantic Analysis of Soccer News for Automatic Game EventClassification 

      Nordskog, Aanund Jupskaas; Halvorsen, Pål; Hicks, Steven; Stensland, Haakon; Hammer, Hugo Lewi; Johansen, Dag; Riegler, Michael (International Workshop on Content-Based Multimedia Indexing, CBMI; 2019 International Conference on Content-Based Multimedia Indexing (CBMI), Conference object, 2019-10-21)
      We are today overwhelmed with information, of which an important part is news. Sports news, in particular, has become very popular, where soccer makes up a big part of this coverage. For sports fans, it can be a time ...

    • Semantic Cloud System for Scaling Data Science Solutions for Welding at Bosch 

      Zheng, Zhuoxun; Zhou, Baifan; Tan, Zhipeng; Savkovic, Ognjen; Rincon-Yanez, Diego; Nikolov, Nikolay Vladimirov; Roman, Dumitru; Soylu, Ahmet; Kharlamov, Evgeny (Peer reviewed; Journal article, 2023)
      Background and Challenges. Industry 4.0 focuses on smart factories that rely on IoT tech- nology for automation. This produces massive amounts of production data, increasing the demand for data-driven solutions and cloud ...

    • Semantic Modeling, Development and Evaluation for the Resistance Spot Welding Industry 

      Yahya, Muhammad; Zhou, Baifan; Breslin, John G.; Ali, Muhammad Intizar; Kharlamov, Evgeny (Peer reviewed; Journal article, 2023)
      The ongoing industrial revolution termed Industry 4.0 (I4.0) has borne witness to a series of profound changes towards increasing smart automation, particularly in the industrial sectors of automotive, aerospace, manufacturing, ...

    • Semirelativistic Schrödinger Equation for Relativistic Laser-Matter Interactions 

      Kjellsson Lindblom, Tor; Førre, Morten; Lindroth, Eva; Selstø, Sølve (Physical Review Letters;Vol. 121, Iss. 25 — 21 December 2018, Journal article; Peer reviewed, 2018)
      A semirelativistic formulation of light-matter interaction is derived using the so called propagation gauge and the relativistic mass shift. We show that relativistic effects induced by a superintense laser field can, to ...

    • SemML: Facilitating development of ML models for condition monitoring with semantics 

      Zhou, Baifan; Svetashova, Yulia; Silva Gusmao, Andre; Soylu, Ahmet; Cheng, Gong; Miku, Ralf; Waaler, Arild Torolv Søetorp; Kharlamov, Evgeny (Journal of Web Semantics;Volume 71, November 2021, 100664, Peer reviewed; Journal article, 2021-10-22)
      Monitoring of the state, performance, quality of operations and other parameters of equipment and production processes, which is typically referred to as condition monitoring, is an important common practice in many ...

    • Sentiment classification of online political discussions: a comparison of a word-based and dependency-based method 

      Hammer, Hugo Lewi; Solberg, Per Erik; Øvrelid, Lilja (Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis;5th, Peer reviewed; Chapter, 2014)
      Online political discussions have received a lot of attention over the past years. In this paper we compare two sentiment lexicon approaches to classify the sentiment of sentences from political discussions. The first ...

    • Sentiment classification of online political discussions: a comparison of a word-based and dependencybased method 

      Hammer, Hugo Lewi; Solberg, Per Erik; Øverlid, Lilja (5th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis;, Chapter; Peer reviewed, 2014)
      Online political discussions have received a lot of attention over the past years. In this paper we compare two sentiment lexicon approaches to classify the sentiment of sentences from political discussions. The first ...

    • Sequence effects in the estimation of software development effort 

      Jørgensen, Magne; Halkjelsvik, Torleif (Journal of Systems and Software;Volume 159, January 2020, 110448, Journal article; Peer reviewed, 2019-10-18)
      Currently, little is known about how much the sequence in which software development tasks or projects are estimated affects judgment-based effort estimates. To gain more knowledge, we examined estimation sequence effects ...

    • Short-Term Forecasting of Monkeypox Cases Using a Novel Filtering and Combining Technique 

      Iftikhar, Hasnain; Khan, Murad; Khan, Mohammed Saad; Khan, Mehak (Peer reviewed; Journal article, 2023)
      : In the modern world, new technologies such as artificial intelligence, machine learning, and big data are essential to support healthcare surveillance systems, especially for monitoring confirmed cases of monkeypox. The ...

    • SIM-PIPE DryRunner: An approach for testing container-based big data pipelines and generating simulation data 

      Thomas, Aleena; Nikolov, Nikolay; Pultier, Antoine; Roman, Dumitru; Elvesæter, Brian; Soylu, Ahmet (IEEE Annual International Computer Software and Applications Conference (COMPSAC);2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC), Conference object, 2022-08-10)
      Big data pipelines are becoming increasingly vital in a wide range of data intensive application domains such as digital healthcare, telecommunication, and manufacturing for efficiently processing data. Data pipelines in ...

    • Simple and practical skin detection with static RGB-color lookup tables: A visualization-based study 

      Sandnes, Frode Eika; Neyse, Levent; Huang, Yo-Ping (Chapter; Peer reviewed; Chapter, 2016)
      Many skin detection approaches have been proposed in the image analysis literature. Some are simple and static; the others are dynamic and rely on complex machine learning algorithms and training data. Generally the simple ...

    • A simple back-of-the-envelope test for self-citations using Google Scholar author profiles 

      Sandnes, Frode Eika (Scientometrics;124 (2020), Journal article; Peer reviewed, 2020-05-18)
      The issue of self-citation has received much attention in academia. Widely used and accessible tools such as Google Scholar do not provide information about self-citations. Therefore, a simple and practical back-of-the-envelope ...

    • A Simple Content-based Strategy for Estimating the Geographical Location of a Webcam 

      Sandnes, Frode Eika (Lecture Notes in Computer Science = Lecture notes in artificial intelligence;6297, Journal article; Peer reviewed, 2010)
      This study proposes a strategy for determining the approximate geographical location of a webcam based on a sequence of images taken at regular intervals. For a time-stamped image sequence spanning 24 hours the approximate ...

    • Simplified cloud-oriented virtual machine management with MLN 

      Begnum, Kyrre (Journal of Supercomputing;, Journal article; Peer reviewed, 2010-03-25)
      System administrators are faced with the challenge of making their existing systems power-efficient and scalable. Although Cloud Computing is offered as a solution to this challenge by many, we argue that having multiple ...

    • Simulating the Euler equations on multiple GPUs using Python 

      Brodtkorb, Andre; Sætra, Martin Lilleeng (Frontiers in Physics;, Peer reviewed; Journal article, 2022)
      GPUs have become a household name in High Performance Computing (HPC) systems over the last 15 years. However, programming GPUs is still largely a manual and arduous task, which requires expert knowledge of the physics, ...

    • SinGAN-Seg: Synthetic training data generation for medical image segmentation 

      Thambawita, Vajira L B; Salehi, Pegah; Sheshkal, Sajad Amouei; Hicks, Steven; Hammer, Hugo Lewi; Parasa, Sravanthi; de Lange, Thomas; Halvorsen, Pål; Riegler, Michael (PLOS ONE;17(5): e0267976, Peer reviewed; Journal article, 2022-05-02)
      Analyzing medical data to find abnormalities is a time-consuming and costly task, particularly for rare abnormalities, requiring tremendous efforts from medical experts. Therefore, artificial intelligence has become a ...

    • A single neural cellular automaton for body-brain co-evolution 

      Pontes Filho, Sidney; Walker, Kathryn; Najarro, Elias; Nichele, Stefano; Risi, Sebastian (Chapter; Peer reviewed; Conference object, 2022)
      The discovery of complex multicellular organism development took millions of years of evolution. The genome of such a multicellular organism guides the development of its body from a single cell, including its control ...

    • Single-leg stance on a challenging surface can enhance cortical activation in the right hemisphere – A case study 

      Khan, Haroon; Qureshi, Nauman Khalid; Yazidi, Anis; Engell, Håvard; Mirtaheri, Peyman (Peer reviewed; Journal article, 2023)
      Maintaining body balance, whether static or dynamic, is critical in performing everyday activities and developing and optimizing basic motor skills. This study investigates how a professional alpine skier’s brain activates ...