Viser treff 241-260 av 640

    • Safe Learning for Control using Control Lyapunov Functions and Control Barrier Functions: A Review 

      Sadanandan Anand, Akhil; Seel, Katrine; Gjærum, Vilde Benoni; Håkansson, Anne; Robinson, Haakon; Saad, Aya (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-10-01)
      Real-world autonomous systems are often controlled using conventional model-based control methods. But if accurate models of a system are not available, these methods may be unsuitable. For many safety-critical systems, such as robotic systems, a model of the system and a control strategy may be learned using data. When applying learning to safety-critical systems, guaranteeing safety during learning ...
    • Emotionally charged text classification with deep learning and sentiment semantic 

      Huan, Jeow Li; Sekh, Arif Ahmed; Quek, Chai; Prasad, Dilip K. (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-09-28)
      Text classification is one of the widely used phenomena in different natural language processing tasks. State-of-the-art text classifiers use the vector space model for extracting features. Recent progress in deep models, recurrent neural networks those preserve the positional relationship among words achieve a higher accuracy. To push text classification accuracy even higher, multi-dimensional ...
    • Robust Reasoning for Autonomous Cyber-Physical Systems in Dynamic Environments 

      Håkansson, Anne; Saad, Aya; Sadanandan Anand, Akhil; Gjærum, Vilde Benoni; Robinson, Haakon; Seel, Katrine (Journal article; Tidsskriftartikkel; Peer reviewed, 2021)
      Autonomous cyber-physical systems, CPS, in dynamic environments must work impeccably. The cyber-physical systems must handle tasks consistently and trustworthily, i.e., with a robust behavior. Robust systems, in general, require making valid and solid decisions using one or a combination of robust reasoning strategies, algorithms, and robustness analysis. However, in dynamic environments, data can ...
    • Prediction of cloud fractional cover using machine learning 

      Svennevik, Hanna; Riegler, Michael A.; Hicks, Steven; Storelvmo, Trude; Hammer, Hugo L. (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-11-03)
      Climate change is stated as one of the largest issues of our time, resulting in many unwanted effects on life on earth. Cloud fractional cover (CFC), the portion of the sky covered by clouds, might affect global warming and different other aspects of human society such as agriculture and solar energy production. It is therefore important to improve the projection of future CFC, which is usually ...
    • Artificial intelligence in dry eye disease 

      Storås, Andrea Marheim; Strumke, Inga; Riegler, Michael Alexander; Grauslund, Jakob; Hammer, Hugo Lewi; Yazidi, Anis; Halvorsen, Pål; Gundersen, Kjell Gunnar; Utheim, Tor Paaske; Jackson, Catherine Joan (Journal article; Tidsskriftartikkel, 2021-11-27)
      Dry eye disease (DED) has a prevalence of between 5 and 50%, depending on the diagnostic criteria used and population under study. However, it remains one of the most underdiagnosed and undertreated conditions in ophthalmology. Many tests used in the diagnosis of DED rely on an experienced observer for image interpretation, which may be considered subjective and result in variation in diagnosis. ...
    • A comprehensive analysis of classification methods in gastrointestinal endoscopy imaging 

      Jha, Debesh; Ali, Sharib; Hicks, Steven; Thambawita, Vajira L B; Borgli, Hanna; Smedsrud, Pia H.; de Lange, Thomas; Pogorelov, Konstantin; Wang, Xiaowei; Harzig, Philipp; Tran, Minh-Triet; Meng, Wenhua; Hoang, Trung-Hieu; Dias, Danielle; Ko, Tobey H.; Agrawal, Taruna; Ostroukhova, Olga; Khan, Zeshan; Tahir, Muhammed Atif; Liu, Yang; Chang, Yuan; Kirkerød, Mathias; Johansen, Dag; Lux, Mathias; Johansen, Håvard D.; Riegler, Michael; Halvorsen, Pål (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-02-19)
      Gastrointestinal (GI) endoscopy has been an active field of research motivated by the large number of highly lethal GI cancers. Early GI cancer precursors are often missed during the endoscopic surveillance. The high missed rate of such abnormalities during endoscopy is thus a critical bottleneck. Lack of attentiveness due to tiring procedures, and requirement of training are few contributing factors. ...
    • The Mask: Masking the effects of Edge Nodes being unavailable 

      Zhakun, Ilia (Mastergradsoppgave; Master thesis, 2021-11-15)
      The arctic tundra is observed to collect data to be used for climate research. Data can be collected by cyber-physical computers with sensors. However, the arctic tundra has a limited availability of energy. Consequently, the nodes rely on batteries and sleep most of the time to increase the battery-limited operational lifetime. In addition, only a few nodes can expect to be in reach of a back-haul ...
    • 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 (Journal article; Tidsskriftartikkel; Peer reviewed, 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 state-of-the-art methods still remains an open problem. This is due to the increasing number of researched computer vision methods that can be applied to polyp datasets. Benchmarking ...
    • PyPSA meets Africa: Developing an open source electricity network model of the African continent 

      Kirli, Desen; Hampp, Johannes; van Greevenbroek, Koen; Grant, Rebecca; Mahmood, Matin; Parzen, Maximilian; Kiprakis, Aristides (Chapter; Bokkapittel, 2021-10-25)
      Electricity network modelling and grid simulations form a key enabling element for the integration of newer and cleaner technologies such as renewable energy generation and electric vehicles into the existing grid and energy system infrastructure. This paper reviews the models of the African electricity systems and highlights the gaps in the open model landscape. Using PyPSA (an open Power System ...
    • File System Support for Privacy-Preserving Analysis and Forensics in Low-Bandwidth Edge Environments 

      Ovesen, Aril Bernhard; Nordmo, Tor-Arne Schmidt; Johansen, Håvard D.; Riegler, Michael Alexander; Halvorsen, Pål; Johansen, Dag (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-10-18)
      In this paper, we present initial results from our distributed edge systems research in the domain of sustainable harvesting of common good resources in the Arctic Ocean. Specifically, we are developing a digital platform for real-time privacy-preserving sustainability management in the domain of commercial fishery surveillance operations. This is in response to potentially privacy-infringing mandates ...
    • Unraveling the Impact of Land Cover Changes on Climate Using Machine Learning and Explainable Artificial Intelligence 

      Kolevatova, Anastasiia; Riegler, Michael; Cherubini, Francesco; Hu, Xiangping; Hammer, Hugo Lewi (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-10-15)
      A general issue in climate science is the handling of big data and running complex and computationally heavy simulations. In this paper, we explore the potential of using machine learning (ML) to spare computational time and optimize data usage. The paper analyzes the effects of changes in land cover (LC), such as deforestation or urbanization, on local climate. Along with green house gas emission, ...
    • Integration of HelseID with Third-Party Role Assignments Data 

      Fagermyr, Thomas L. (Master thesis; Mastergradsoppgave, 2021-08-31)
      The Norwegian healthcare sector is vast, with a substantial number of organizations employing plenty of people, and thereof, 7,300 are customers of Norsk Helsenett. Maintaining and keeping up-to-date information about access rights for these customers is a difficult, time-consuming, and manual task, especially since organizations often change personnel without notifying the system administrators. ...
    • How to use an app to Nudge people to choose more green transportation? 

      Myrvang, Ingvild Kristiane (Mastergradsoppgave; Master thesis, 2021-10-02)
      Making green transport choices are more important than ever to save the environment. To accomplish this there must be a reduction in emissions of greenhouse gases and other pollutants. How to make people choose green transportation, when it is inconvenient, is an interesting challenge. Most would rather take the easy way out to avoid the extra planning and estimation of how to reach their destination. ...
    • Slicer 

      Knutsen, Øystein (Mastergradsoppgave; Master thesis, 2021-09-15)
      Explorative data visualization is a widespread tool for gaining insights from datasets. Investigating data in linked visualizations lets users explore potential relationships in their data at will. Furthermore, this type of analysis does not require any technical knowledge, widening the userbase from developers to anyone. Implementing explorative data visualizations in web browsers makes data analysis ...
    • Combination of satellite imagery and wind data in deep learning approach to detect oil spills 

      Borhaug, Hans Berg (Mastergradsoppgave; Master thesis, 2021-09-15)
      The ocean is vulnerable to oil related activities such as oil production and transport that can harm the environment. Environmental damages from oil spills can be large if not dealt with. Satellite images from radar are useful to detect oil spills because they cover both day and night and penetrates clouds. However, detecting oil spills in ocean areas from satellite images are not a trivial task due ...
    • Smart contract formation enabling energy-as-a-service in a virtual power plant 

      Mishra, Sambeet; Crasta, Cletus John; Bordin, Chiara; Mateo-Fornés, Jordi (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-10-22)
      Energy as a service (EaaS) is an emerging business model that enables the otherwise passive energy consumers to play an active role and participate in the energy utility services. This platform is formed through smart contracts registering peer-to-peer (P2P) transactions of energy through price and quantity. Many industries, including finance, have already leveraged smart contracts to introduce ...
    • IRON-MAN: An Approach to Perform Temporal Motionless Analysis of Video Using CNN in MPSoC 

      Dey, Somdip; Singh, Amit Kumar; Prasad, Dilip K.; McDonald-Maier, Klaus Dieter (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-07-20)
      This paper proposes a novel human-inspired methodology called IRON-MAN (Integrated RatiONal prediction and Motionless ANalysis) for mobile multi-processor systems-on-chips (MPSoCs). The methodology integrates analysis of the previous image frames of the video to represent the analysis of the current frame in order to perform Temporal Motionless Analysis of the Video (TMAV). This is the first work ...
    • Experiences Building and Deploying Wireless Sensor Nodes for the Arctic Tundra 

      Murphy, Michael J.; Tveito, Øystein; Kleiven, Eivind Flittie; Rais, Issam; Soininen, Eeva M; Bjørndalen, John Markus; Anshus, Otto (Journal article; Tidsskriftartikkel, 2021-08-02)
      The arctic tundra is most sensitive to climate change. The change can be quantified from observations of the fauna, flora and weather conditions. To do observations at sufficient spatial and temporal resolution, ground-based observation nodes with sensors are needed. However, the arctic tundra is resource-limited with regards to energy, data networks, and humans. There are also regulatory and practical ...
    • Authentication and Authorization in Blind Data Miners 

      Myrland, Morten (Master thesis; Mastergradsoppgave, 2021-06-15)
      Chronic pain is defined as pain that lasts for at least 12 weeks. People with chronic pain conditions can have difficulties getting through daily tasks because the pain can limit their mobility, strength, and endurance. As of 2021, there is no universal treatment that works for all cases of chronic pain. A tool that can give personalized treatment alternatives for each patient can benefit this ...
    • Can a code snippet portal contribute to greater learning outcomes in other fields of science and technology? 

      Taha, Sidra (Master thesis; Mastergradsoppgave, 2021-06-08)
      In this project we developed a web portal for students and by students in order to be able to help each other understanding coding in the different subjects across fields of study. The web portal is implemented using HTML programming language and its templates, and running the front-end with flask web application framework. A database has been made for collecting and storing code snippets.