• Déjà vu - Predicting the number of players in online games through normalization of historical data 

      Tyvand, Jon-Erik; Begnum, Kyrre; Hammer, Hugo Lewi (Chapter; Peer reviewed, 2011)
      A key factor to delivering a good online gaming experience is to have sufficient server resources relative to the number of players online. In this work, we present a simple profiling technique which allows effective ...
    • Discovering Fuzzy Association Rules from Patient's Daily Text Messages to Diagnose Melancholia 

      Huang, Yo-Ping; Chiu, Hong-Wen; Chuan, Wei-Po; Sandnes, Frode Eika (Chapter; Peer reviewed, 2010)
      With the constant stress from work load and daily life people may show symptoms of melancholia. However, most people are reluctant to describe it or may not know that they already have it. In this paper a novel system ...
    • Do Code Smells Impact the Effort of Different Maintenance Programming Activities? 

      Soh, Zepyr; Yamashita, Aiko; Khomh, Foutse (Chapter; Peer reviewed; Chapter, 2016)
      Empirical studies have shown so far that code smells have relatively low impact over maintenance effort at file level. We surmise that previous studies have found low effects of code smells because the effort considered ...
    • Drawing Abrasive Hologram Animations with Auto-Generated Scratch Patterns 

      Sandnes, Frode Eika; Eika, Evelyn (Chapter; Peer reviewed, 2017)
      Abrasive holograms allow people to experiment with impressive quasi-holography and create hologram artwork through simple means of creating reflective scratches on sheets of plastic. Most of the reported accounts of abrasive ...
    • Dynamic Ordering of Firewall Rules Using a Novel Swapping Window-based Paradigm 

      Mohan, Ratish; Yazidi, Anis; Feng, Boning; Oommen, John (Peer reviewed; Chapter, 2016)
      Designing and implementing efficient firewall strategies in the age of the Internet of Things (IoT) is far from trivial. This is because, as time proceeds, an increasing number of devices will be connected, accessed and ...
    • EEG-based affect classification with machine learning algorithms 

      Zhang, Jianhua; Yin, Zhong; Chen, Peng (Chapter, 2023)
      In this paper, we aim to study the EEG-based emotion recognition problem. First, we use clustering algorithm to determine the target class of emotions and perform binary classification of emotion along its arousal and ...
    • Effect of Added Mass Location on Manual Wheelchair Propulsion Forces 

      Alcoléa, Vitor; Medola, Fausto Orsi; Bertolaccin, Guilherme da Silva; Sandnes, Frode Eika (Advances in Intelligent Systems and Computing;1026, Chapter; Peer reviewed, 2020-08-14)
      This study investigated the influence of mass distribution on the handrim forces during manual propulsion in four different mobility tasks: straightforward motion at self-selected speed; straightforward sprint; zero radius ...
    • Effects of common keyboard layouts on physical effort : implications for kiosks and Internet banking 

      Sandnes, Frode Eika (The proceedings of Unitech2010 : International Conference on Universal Technologies;, Chapter; Peer reviewed, 2010)
      This study investigates the effect common keyboard layouts have physical effort. First, alphabetic keyboard layouts are experimentally compared to the QWERTY layout. Second, the number row often found on QWERTY keyboards ...
    • Electronic identity mass compromize: Options for recovery 

      Fritsch, Lothar (Lecture Notes in Informatics;, Chapter; Peer reviewed, 2023)
      A National Digital Identity Framework should be designed in a proactive manner, should focus on a resilience-oriented approach, and should be aimed at limiting the risks that may originate from identity data management ...
    • Enabling Smart Home with 5G Network Slicing 

      Dzogovic, Bruno; Santos, Bernardo; Noll, Josef; Do, Thuan Van; Feng, Boning; Do, van Thanh (Proceedings of the 2019 IEEE 4th International Conference on Computer and Communication Systems - ICCCS 2019;, Chapter; Peer reviewed, 2019)
      In addition to mobile phones 5G mobile networks will have to support billion IoT devices and applications. To achieve this objective 5G relies in the network slicing concept which is not yet fully understood. This paper ...
    • Enhancing creativity and play through accessible projector-based interactive PC-control touch technology 

      Begnum, Miriam Eileen Nes; Finstadsveen, Johan; Begnum, Kyrre (The proceedings of Unitech : International Conference on Universal Technologies;2010, Chapter; Peer reviewed, 2010)
      Standard computer peripherals are often challenging to use for mobility impaired, and in particular controlling computer mouse movements efficiently and without risking strain injuries. Projected touch screen technology ...
    • Equal Pay for Knowledge Workers in Academia: An Unrealistic Proposition 

      Sandnes, Frode Eika (Palgrave Debates in Business and Management;, Chapter; Peer reviewed, 2021-12-10)
      This chapter argues for unequal pay in the cultural context of Norwegian academia. Academia is an interesting case to study, as knowledge workers are often idealistically driven rather than through pay. Contrary to the ...
    • Ergodic Capacity Performance of D2D IoT Relay NOMA-SWIPT Systems with Direct Links 

      Rauniyar, Ashish; Engelstad, Paal E.; Østerbø, Olav Norvald (International Conference on Telecommunications and Signal Processing (TSP); 2020 43rd International Conference on Telecommunications and Signal Processing (TSP), Chapter; Peer reviewed, 2020-08-11)
      We investigate the Ergodic capacity (EC) performance of device-to-device (D2D) Internet of Things (IoT) relay non-orthogonal multiple access (NOMA)- simultaneous wireless information and power transfer (SWIPT) systems where ...
    • Evading a Machine Learning-based Intrusion Detection System through Adversarial Perturbations 

      Fladby, Torgeir; Haugerud, Hårek; Nichele, Stefano; Begnum, Kyrre; Yazidi, Anis (RACS: Research in Applied Computation Symposium; RACS '20: International Conference on Research in Adaptive and Convergent Systems, Chapter; Peer reviewed; Conference proceeding, 2020-10)
      Machine-learning based Intrusion Detection and Prevention Systems provide significant value to organizations because they can efficiently detect previously unseen variations of known threats, new threats related to known ...
    • Evaluating Accessibility and Usability of an Experimental Situational Awareness Room 

      Gjøsæter, Terje; Radianti, Jaziar (Advances in Intelligent Systems and Computing;Vol 776, Chapter; Peer reviewed, 2018-06-24)
      New advanced emergency management facilities such as a control room which is equipped with advanced ICT technologies should consider universal design principles and ensure the accessibility and usability of some important ...
    • Evaluation of orthosis rapid prototyping during the design process: Analysis of verification models 

      Ferrari, Ana Lya Moya; Piculo dos Santos, Aline Darc; Bertolaccini, Guilherme da Silva; Medola, Fausto Orsi; Sandnes, Frode Eika (Advances in Intelligent Systems and Computing;975, Chapter; Peer reviewed, 2020)
      hysical prototypes allow the testing of ideas quickly with models that look similar to the final product. Rapid Prototyping (RP) based on additive or subtractive technologies allow trial usability tests to avoid errors and ...
    • Executable Knowledge Graph for Transparent Machine Learning in Welding Monitoring at Bosch 

      Zheng, Zhuoxun; Zhou, Baifan; Zhou, Dongzhuoran; Soylu, Ahmet; Kharlamov, Evgeny (Chapter; Peer reviewed; Conference object, 2022)
      With the development of Industry 4.0 technology, modern industries such as Bosch’s welding monitoring witnessed the rapid widespread of machine learning (ML) based data analytical applications, which in the case of welding ...
    • ExeKG: Executable Knowledge Graph System for User-friendly Data Analytics 

      Zhuoxun, Zheng; Zhou, Baifan; Zhou, Dongzhuoran; Soylu, Ahmet; Kharlamov, Evgeny (CIKM: Conference on Information and Knowledge Management;, Chapter; Peer reviewed; Conference object, 2022)
      Data analytics including machine learning (ML) is essential to extract insights from production data in modern industries. However, industrial ML is affected by: the low transparency of ML towards non-ML experts; poor and ...
    • Exploring Circular Hough Transforms for Detecting Hand Feature Points in Noisy Images from Ghost-Circle Patterns 

      Sandnes, Frode Eika (Chapter, 2021-03-15)
      Several applications involve the automatic analysis of hand images such as biometry, digit-ratio measurements, and gesture recognition. A key problem common to these applications is the separation of hands from the background. ...
    • Exploring Multilingual Word Embedding Alignments in BERT Models: A Case Study of English and Norwegian 

      Aaby, Pernille; Biermann, Daniel; Yazidi, Anis; Borges Moreno e Mello, Gustavo; Palumbo, Fabrizio (Lecture Notes in Computer Science;, Chapter; Peer reviewed; Conference object; Journal article, 2023)
      Contextual language models, such as transformers, can solve a wide range of language tasks ranging from text classification to question answering and machine translation. Like many deep learning models, the performance ...