Viser treff 321-340 av 640

    • Scalability of Distributed Version Control Systems 

      Murphy, Mike; Bjørndalen, John Markus; Anshus, Otto (Journal article; Tidsskriftartikkel, 2017-11-26)
      <p>Distributed version control systems are popular for storing source code, but they are notoriously ill suited for storing large binary files. <p>We report on the results from a set of experiments designed to characterize the behavior of some widely used distributed version control systems with respect to scaling. The experiments measured commit times and repository sizes when storing single files ...
    • μPyCSP - Two approaches to implementing CSP-like concurrency modeling in microcontrollers. 

      Johansen, Jon Helge Langaas (Master thesis; Mastergradsoppgave, 2020-06-30)
      In this thesis, we have explored the possibility of bringing CSP-like concurrency modeling to an embedded environment. With the growth of IoT and embedded software, many of the hardships that come with concurrent coding in an inherently event-driven environment become more apparent. Convoluted and complex code is often used to handle the many fallacies of concurrency. We are solving this problem by ...
    • Information collection for smart transportation nudges 

      Johnsen, Jacob (Master thesis; Mastergradsoppgave, 2020-06-25)
      Global climate change is becoming of increasing concern. Transportation makes up a large part of carbon gasses, which affects climate change and air quality. As transportation is a big part of carbon emissions, everybody can contribute to reducing emissions through transportation. One way for people to contribute is to start choosing greener transportation. Nuding is a tool that can be used to ...
    • A Robot System for Personalized Language Education. Implementation and evaluation of a language education system built on a robot 

      Dündar, Yigit Can (Master thesis; Mastergradsoppgave, 2020-06-29)
      As modern computer hardware becomes more affordable, the application areas of Artificial Intelligence (AI) expand and become more feasible to implement efficiently. This aspect opens up opportunities where AI robots can be used to support and improve many areas of human lives. One such area is education, and this thesis project combines AI and education to evaluate whether the results from that union ...
    • Data collection and combination for smart nudges in physical activity 

      Karlsen, Lars (Master thesis; Mastergradsoppgave, 2020-06-22)
      Denne masteroppgaven innhenter data fra forskjellige relevante kilder til fysisk aktivitet, og designer et smart nudging system. Oppgaven ser på hvordan dataen fra disse relevante kildene kan brukes av systemet til å påvirke adferden og motivasjonen til folk, så folk kan bli mere fysisk aktive.
    • Storing and representing smart nudges in a user profile 

      Mæland, Marius Johan (Master thesis; Mastergradsoppgave, 2020-06-19)
      Oppgaven handler om hvordan informasjon og struktur en bruker profil trenger for og og kunne lagre smart nudges, og bruke dette til og finne brukerens preferanser. Et design på brukerprofil er laget og dette designet er brukt for og implementere en brukerprofil som inneholder smart nudger.
    • The House of Carbs: Personalized Carbohydrate Dispenser for People with Diabetes 

      Randine, Pietro; Micucci, Daniela; Hartvigsen, Gunnar; Årsand, Eirik (Journal article; Tidsskriftartikkel; Peer reviewed, 2020)
      Patients with diabetes are often worried about having low blood glucose because of the unpleasant feeling and possible dangerous situations this can lead to. This can make patients consume more carbohydrates than necessary. Ad-hoc carbohydrate estimation and dosing by the patients can be unreliable and may produce unwanted periods of high blood glucose. In this paper we present a system that ...
    • Cluster Detection Mechanisms for Syndromic Surveillance Systems: Systematic Review and Framework Development 

      Yeng, Prosper; Woldaregay, Ashenafi Zebene; Solvoll, Terje Geir; Hartvigsen, Gunnar (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-05-26)
      Background:The time lag in detecting disease outbreaks remains a threat to global health security. The advancement of technology has made health-related data and other indicator activities easily accessible for syndromic surveillance of various datasets. At the heart of disease surveillance lies the clustering algorithm, which groups data with similar characteristics (spatial, temporal, or both) to ...
    • 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 ...
    • Semi-CNN architecture for effective spatio-temporal Learning in action recognition 

      Leong, Mei Chee; Prasad, Dilip K.; Lee, Yong Tsui; Lin, Feng (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-01-12)
      This paper introduces a fusion convolutional architecture for efficient learning of spatio-temporal features in video action recognition. Unlike 2D convolutional neural networks (CNNs), 3D CNNs can be applied directly on consecutive frames to extract spatio-temporal features. The aim of this work is to fuse the convolution layers from 2D and 3D CNNs to allow temporal encoding with fewer parameters ...
    • 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 ...
    • What Do We Know About the Use of Chatbots for Public Health? 

      Gabarron, Elia; Larbi, Dillys; Denecke, Kerstin; Årsand, Eirik (Journal article; Tidsskriftartikkel; Peer reviewed, 2020)
      <i>Background and objective</i>: The number of publications on the use of chatbots for health is recently increasing, however to our knowledge, there are no publications summarizing what is known about using chatbots for public health yet. The objective of this work is to provide an overview of the existing scientific literature on the use of chatbots for public health, for which purpose have chatbots ...
    • Comparison of deep learning models for multivariate prediction of time series wind power generation and temperature 

      Mishra, Sambeet; Bordin, Chiara; Taharaguchi, Kota; Palu, Ivo (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-03-02)
      Wind power experienced a substantial growth over the past decade especially because it has been seen as one of the best ways towards meeting climate change and emissions targets by many countries. Since wind power is not fully dispatchable, the accuracy of wind forecasts is a key element for the electric system operators, as it strongly affects the decision-making processes. The planning horizon can ...
    • Beneath the snow – Developing a wireless sensor node for remote locations in the Arctic 

      Tveito, Øystein (Master thesis; Mastergradsoppgave, 2020-05-15)
      In this thesis we describe how we designed, built, deployed, and improved upon a robust hardware- and software solution, tailor-made to this scientific question. During the course of this project, we created three distinct versions and we have conducted two deployments of the sensor nodes in the Arctic tundra. The node is able to measure CO2 , temperature, and humidity, in addition to monitoring an ...
    • Evaluating the performance of raw and epoch non-wear algorithms using multiple accelerometers and electrocardiogram recordings 

      Syed, Shaheen; Morseth, Bente; Hopstock, Laila Arnesdatter; Horsch, Alexander (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-04-03)
      Accurate detection of accelerometer non-wear time is crucial for calculating physical activity summary statistics. In this study, we evaluated three epoch-based non-wear algorithms (Hecht, Troiano, and Choi) and one raw-based algorithm (Hees). In addition, we performed a sensitivity analysis to provide insight into the relationship between the algorithms’ hyperparameters and classification performance, ...
    • Data-Driven and Artificial Intelligence (AI) Approach for Modelling and Analyzing Healthcare Security Practice: A Systematic Review 

      Yeng, Prosper; Nweke, Livinus Obiora; Woldaregay, Ashenafi Zebene; Yang, Bian; Snekkenes, Einar Arthur (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-03)
      Data breaches in healthcare continue to grow exponentially, calling for a rethinking into better approaches of security measures towards mitigating the menace. Traditional approaches including technological measures, have significantly contributed to mitigating data breaches but what is still lacking is the development of the “human firewall,” which is the conscious care security practices of the ...
    • Kvasir-SEG: A Segmented Polyp Dataset 

      Jha, Debesh; Pia H, Smedsrud; Riegler, Michael; Halvorsen, Pål; de Lange, Thomas; Johansen, Dag; Johansen, Håvard D. (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-01-24)
      Pixel-wise image segmentation is a highly demanding task in medical-image analysis. In practice, it is difficult to find annotated medical images with corresponding segmentation masks. In this paper, we present Kvasir-SEG: an open-access dataset of gastrointestinal polyp images and corresponding segmentation masks, manually annotated by a medical doctor and then verified by an experienced ...
    • Collision-free path finding for dynamic gaming and real time robot navigation 

      Bamal, Roopam (Peer reviewed; Book; Chapter, 2020-02-13)
      Collision-free path finding is crucial for multi-agent traversing environments like gaming systems. An efficient and accurate technique is proposed for avoiding collisions with potential obstacles in virtual and real time environments. Potential field is a coherent technique but it eventuates with various problems like static map usage and pre-calculated potential field map of the environment. It ...
    • Intelligent Offloading Distribution of High Definition Street Maps for Highly Automated Vehicles 

      Jomrich, Florian; Sharma, Aakash; Ruckelt, Tobias; Bohnstedt, Doreen; Steinmetz, Ralf (Journal article; Tidsskriftartikkel; Peer reviewed, 2018-11-24)
      Highly automated vehicles will change our personal mobility in the future. To ensure the safety and the comfort of their passengers, the cars have to rely on as many information regarding their current surrounding traffic situation, as they can obtain. In addition to classical sensors like cameras or radar sensors, automated vehicles use data from a so called High Definition Street Map. Through such ...
    • Are object detection assessment criteria ready for maritime computer vision? 

      Prasad, Dilip K.; Dong, Huixu; Rajan, Deepu; Quek, Chai (Journal article; Tidsskriftartikkel; Peer reviewed, 2019-11-25)
      Maritime vessels equipped with visible and infrared cameras can complement other conventional sensors for object detection. However, application of computer vision techniques in maritime domain received attention only recently. The maritime environment offers its own unique requirements and challenges. Assessment of the quality of detections is a fundamental need in computer vision. However, the ...