Now showing items 361-380 of 389

    • Usefulness of Heat Map Explanations for Deep-Learning-Based Electrocardiogram Analysis 

      Storås, Andrea; Andersen, Ole Emil; Lockhart, Sam; Thielemann, Roman; Gnesin, Filip; Thambawita, Vajira L B; Hicks, Steven; Kanters, Jørgen K.; Strumke, Inga; Halvorsen, Pål; Riegler, Michael (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-07-11)
      Deep neural networks are complex machine learning models that have shown promising results in analyzing high-dimensional data such as those collected from medical examinations. Such models have the potential to provide fast and accurate medical diagnoses. However, the high complexity makes deep neural networks and their predictions difficult to understand. Providing model explanations can be a way ...
    • User Expectations and Willingness to Share Self-Collected Health Data 

      Woldaregay, Ashenafi Zebene; Henriksen, André; Issom, David-Zacharie; Pfuhl, Gerit; Sato, Keiichi; Richard, Aude; Lovis, Christian; Årsand, Eirik; Rochat, Jessica; Hartvigsen, Gunnar (Journal article; Tidsskriftartikkel; Peer reviewed, 2020)
      The rapid improvement in mobile health technologies revolutionized what and how people can self-record and manage data. This massive amount of information accumulated by these technologies has potentially many applications beyond personal need, i.e. for public health. A challenge with collecting this data is to motivate people to share this data for the benefit of all. The purpose of this study is ...
    • User Expectations and Willingness to Share Self-collected Health Data 

      Woldaregay, Ashenafi Zebene; Henriksen, André; Issom, David-Zacharie; Pfuhl, Gerit; Sato, Keiichi; Richard, Aude; Lovis, Christian; Årsand, Eirik; Rochat, Jessica; Hartvigsen, Gunnar (Journal article; Tidsskriftartikkel; Peer reviewed, 2020)
      The rapid improvement in mobile health technologies revolutionized what and how people can self-record and manage data. This massive amount of information accumulated by these technologies has potentially many applications beyond personal need, i.e. for public health. A challenge with collecting this data is to motivate people to share this data for the benefit of all. The purpose of this study is ...
    • Using 3D Convolutional Neural Networks for Real-time Detection of Soccer Events 

      Rongved, Olav Andre Nergård; Hicks, Steven; Thambawita, Vajira L B; Stensland, Håkon Kvale; Zouganeli, Evi; Johansen, Dag; Riegler, Michael Alexander; Halvorsen, Pål (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-06)
      Developing systems for the automatic detection of events in video is a task which has gained attention in many areas including sports. More specifically, event detection for soccer videos has been studied widely in the literature. However, there are still a number of shortcomings in the state-of-the-art such as high latency, making it challenging to operate at the live edge. In this paper, we present ...
    • Using a virtual event space to understand parallel application communication behavior 

      Bongo, Lars Ailo; Anshus, Otto J.; Bjørndalen, John Markus (Research report; Forskningsrapport, 2003)
      We have developed EventSpace, a configurable data collecting, management and observation system for monitoring low-level synchronization and communication events with the purpose of understanding the behavior of parallel applications on clusters and multi-clusters. Applications are instrumented by adding data collecting code in the form of event collectors to an applications communication paths. ...
    • Using a waiting protocol to separate concerns in the mutual exclusion problem 

      Fjeld, Frode V. (Research report; Forskningsrapport, 2003-11-21)
      How to implement process synchronization in a general-purpose software library while incurring a minimum of policy decisions on the system as a whole? We propose that in dealing with the problem of mutual exclusion in concurrent systems, a separation of concerns between the mechanism of detecting contention and the policy decision of what to do when such contention is detected is appropriate. We ...
    • Using Fitness Trackers and Smartwatches to Measure Physical Activity in Research: Analysis of Consumer Wrist-Worn Wearables 

      Henriksen, André; Mikalsen, Martin Haugen; Woldaregay, Ashenafi Zebene; Muzny, Miroslav; Hartvigsen, Gunnar; Hopstock, Laila Arnesdatter; Grimsgaard, Sameline (Journal article; Tidsskriftartikkel; Peer reviewed, 2018-03-22)
      Background: New fitness trackers and smartwatches are released to the consumer market every year. These devices are equipped with different sensors, algorithms, and accompanying mobile apps. With recent advances in mobile sensor technology, privately collected physical activity data can be used as an addition to existing methods for health data collection in research. Furthermore, data collected ...
    • Using machine learning to provide automatic image annotation for wildlife camera traps in the Arctic 

      Thom, Håvard; Bjørndalen, John Markus; Kleiven, Eivind Flittie; Soininen, Eeva M; Killengreen, Siw Turid; Ehrich, Dorothee; Ims, Rolf Anker; Anshus, Otto; Horsch, Alexander (Chapter; Bokkapittel, 2017)
      The arctic tundra is considered the terrestrial biome expected to be most impacted by climate change, with temperatures projected to increase as much as 10 °C by the turn of the century. The Climate-ecological Observatory for Arctic Tundra (COAT) project monitors the climate and ecosystems using several sensor types. We report on results from projects that automate image annotations from two of the ...
    • Using satellite execution to reduce latency for mobile/cloud applications 

      Pettersen, Robert; Valvåg, Steffen; Kvalnes, Åge Andre; Johansen, Dag (Peer reviewed; Journal article; Tidsskriftsartikkel, 2016-02-03)
      We demonstrate a practical way to reduce latency for mobile .NET applications that interact with cloud services, without disrupting application architectures. We provide a programming abstraction for location-independent code, which has the potential to execute either locally or at a satellite execution environment in the cloud, where other cloud services can be accessed with low latency. This ...
    • Utilizing Alike Neighbor Influenced Similarity Metric for Efficient Prediction in Collaborative Filter-Approach-Based Recommendation System 

      Singh, Raushan Kumar; Singh, Pradeep Kumar; Singh, Juginder Pal; Singh, Akhilesh Kumar; Dhanasekaran, Seshathiri (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-11-17)
      The most popular method collaborative filter approach is primarily used to handle the information overloading problem in E-Commerce. Traditionally, collaborative filtering uses ratings of similar users for predicting the target item. Similarity calculation in the sparse dataset greatly influences the predicted rating, as less count of co-rated items may degrade the performance of the collaborative ...
    • UX-based personalization of timed media experiences 

      Arntzen, Ingar M; Borch, Njål Trygve (Conference object; Konferansebidrag, 2021)
      A client-side approach brings great opportunities for flexible personalization of timed media experiences. This, turns it into a challenge of UX development. However, UX development does not support time-driven rendering or shared interactivity, which are required by media related scenarios. Moreover, UX development is already quite complicated, so adding support for timed rendering and shared ...
    • Validation of ESDS Using Epidemic-Based Data Dissemination Algorithms 

      Guegan, Loic; Rais, Issam; Anshus, Otto Johan (Journal article; Tidsskriftartikkel, 2023-09-27)
      The study of Distributed Systems (DS) is important as novel solutions in this area impact many sub-fields of Computer Science. Although, studying DS is not an easy task. A common approach is to deploy a test-bed to perform a precise evaluation of the system. This can be costly and time consuming for large scale platforms. Another solution is to perform network simulations, allowing for more flexibility ...
    • Validity of the Polar M430 Activity Monitor in Free-Living Conditions: Validation Study 

      Henriksen, André; Grimsgaard, Sameline; Horsch, Alexander; Hartvigsen, Gunnar; Hopstock, Laila Arnesdatter (Journal article; Tidsskriftartikkel; Peer reviewed, 2019-08-16)
      <i>Background</i>: Accelerometers, often in conjunction with heart rate sensors, are extensively used to track physical activity (PA) in research. Research-grade instruments are often expensive and have limited battery capacity, limited storage, and high participant burden. Consumer-based activity trackers are equipped with similar technology and designed for long-term wear, and can therefore ...
    • The variability of physical match demands in elite women's football 

      Matias Do Vale Baptista, Ivan Andre; Winther, Andreas Kjæreng; Johansen, Dag; Bredsgaard Randers Thomsen, Morten; Pedersen, Sigurd; Pettersen, Svein Arne (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-01-21)
      Peak locomotor demands are considered as key metrics for conditioning drills prescription and training monitoring. However, research in female football has focused on absolute values when reporting match demands, leading to sparse information being provided regarding the degrees of variability of such metrics. Thus, the aims of this study were to investigate the sources of variability of match ...
    • Video Analytics in Elite Soccer: A Distributed Computing Perspective 

      Jha, Debesh; Rauniyar, Ashish; Johansen, Håvard D.; Johansen, Dag; Riegler, Michael Alexander; Halvorsen, Pål; Bagci, Ulas (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-07-22)
      Ubiquitous sensors and Internet of Things (IoT)technologies have revolutionized the sports industry, providing new methodologies for planning, effective coordination of training, and match analysis post-game. New methods, including machine learning, image, and video processing, have been developed for performance evaluation, allowing the analyst to track the performance of a player in real-time. ...
    • Virtual labeling of mitochondria in living cells using correlative imaging and physics-guided deep learning 

      Somani, Ayush; Sekh, Arif Ahmed; Opstad, Ida Sundvor; Birgisdottir, Åsa birna; Myrmel, Truls; Ahluwalia, Balpreet Singh; Horsch, Alexander; Agarwal, Krishna; Prasad, Dilip K. (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-09-28)
      Mitochondria play a crucial role in cellular metabolism. This paper presents a novel method to visualize mitochondria in living cells without the use of fluorescent markers. We propose a physics-guided deep learning approach for obtaining virtually labeled micrographs of mitochondria from bright-field images. We integrate a microscope’s point spread function in the learning of an adversarial neural ...
    • Virtual Power Plants and Integrated Energy System: Current Status and Future Prospects 

      Mishra, Sambeet; Bordin, Chiara; Leinakse, Madis; Wen, Fushuan; J. Howlett, Robert; Palu, Ivo (Chapter; Bokkapittel, 2022)
      The power system is undergoing a digitalization, decarbonization, and decentralization. Economic incentives along with resiliency and reliability concerns are partly driving the transition. In the process of decentralization, local energy markets are forming at various places. A virtual power plant (VPP) is a by-product of this digitalization capitalizing on the opportunity to further promote renewable ...
    • Visual Sentiment Analysis from Disaster Images in Social Media 

      Zohaib Hassan, Syed; Ahmad, Kashif; Hicks, Steven; Halvorsen, Pål; Al-Fuqaha, Ala; Conci, Nicola; Riegler, Michael Alexander (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-05-10)
      The increasing popularity of social networks and users’ tendency towards sharing their feelings, expressions, and opinions in text, visual, and audio content have opened new opportunities and challenges in sentiment analysis. While sentiment analysis of text streams has been widely explored in the literature, sentiment analysis from images and videos is relatively new. This article focuses on ...
    • Vitamin D in relation to incident sarcopenia and changes in muscle parameters among older adults: The KORA-Age Study 

      Conzade, Romy; Grill, Eva; Bischoff-Ferrari, Heike A.; Ferrari, Uta; Horsch, Alexander; Peters, Annette; Thorand, Barbara (Journal article; Tidsskriftartikkel; Peer reviewed, 2019-05-08)
      Summary We report low baseline 25-hydroxyvitamin D (25OHD) levels being associated with unfavorable changes in muscle mass and physical performance over three years, but not with incident sarcopenia. Future prospective studies are needed to assess causality and to address the issue of competing risks such as mortality in older cohorts. Introduction Effects of low serum 25-hydroxyvitamin D (25OHD) ...
    • Vortex. An event-driven multiprocessor operating system supporting performance isolation 

      Renesse, Robbert van; Kvalnes, Aage; Johansen, Dag; Arnesen, Audun (Research report; Forskningsrapport, 2003-06-13)
      Vortex is a new multiprocessor operating system that is entirely event-driven. The Vortex kernel, as well as its applications, are structured as stagesthat communicate through event passing. Each stage is a small finite state machine. The event architecture is efficient and allows Vortex to balance load across the processors automatically. Vortex uses an Event Scheduling Tree (EST) on each CPU. ...