Viser treff 1-20 av 757

    • User Interface for Nudges: Development of Nudge Patterns Library and Nudge Components Library 

      Vasylieva, Tetiana (Master thesis, 2025)
      This thesis explores how digital nudging can be systematically represented and implemented in user interfaces through design and development resources. Nudging refers to practice of subtly guiding individuals toward desired actions without restricting their freedom of choice. In digital contexts, it relies on user interface (UI) elements to influence behavior. Despite increasing interest, the practical ...
    • Joavku: Real-Time Team Assignment using Visual Data 

      Sørvik, Aslak Vik (Master thesis, 2025)
      This thesis presents Joavku, a lightweight and interpretable system for performing automated team assignment of football players using only visual data. Unlike many existing systems that rely on custom-trained machine learning models or external tracking technologies, Joavku utilizes a novel color-based classification method that identifies the dominant team color in a player’s kit. By isolating key ...
    • Monitovra 

      Livastøl, Håvard (Master thesis, 2025)
      This thesis investigates the co-optimization of state-of-the-art computer vision models and camera configurations to enable accurate, real-time soccer analysis. This work is part of the broader development of the Cyber Security Group's real-time soccer analysis system at UiT The Arctic University of Norway, a low-cost, modular solution for real-time performance analysis. By combining practical system ...
    • Attempting to reduce the number of same-day elective-surgery cancelations using consumer-grade wearable devices and kernel density estimation 

      Jernsletten, Johan-Niillas Ludviksen (Master thesis, 2025)
      As people live longer and have increasingly sedentary and unhealthy lifestyles the pressure on the healthcare sector will be increasing in the future. To cope with this increased demand, technological solutions are being tested and implemented with the aim of offsetting some of the added workload. One of these new technological solutions is the use of consumer-grade wearable devices and machine ...
    • Fuse: Space-Efficient Token-Based Key Exchange using Elliptic Curves 

      Bjordal, Aslak Røstad (Master thesis, 2025)
      This thesis presents a novel implementation of a Non-Interactive Key Exchange (NIKE) protocol using features from Attribute-Based Encryption (ABE) to achieve a highly space-efficient key distribution scheme. Our Token-Based Key Exchange (TBKE) implementation enables scalable symmetric key generation through compact, capability-based tokens, making it particularly suited for resource-constrained ...
    • LLMs and Online Privacy: Toward Automated Relevance Assessment 

      Johansen, Sofie (Master thesis, 2025)
      As digital footprints grow, individuals face increasing challenges in understanding and managing the personal information available about them online. The OPP tool addresses this by retrieving public URLs related to a user's identity. This thesis enhances OPP by integrating a Large Language Model to automatically assess the relevance of these search results. The project explores how prompt engineering ...
    • Chronolock: Causal Time-Ordering with Blockchain Smart Contracts 

      Møller-Hansen, Marius (Master thesis, 2025)
      Distributed systems struggle with synchronization, especially when components must agree on the order of events across application or trust boundaries. Without clear causal ordering, systems can become vulnerable to inconsistencies, coordination failures, and auditability issues. This thesis presents \textbf{Chronolock}, a blockchain-hybrid system that enforces causal-time ordering across distributed ...
    • Artificial Intelligence to Improve Clinical Coding Practice in Scandinavia: Crossover Randomized Controlled Trial 

      Chomutare, Taridzo; Svenning, Therese Olsen; Hernández, Miguel; Ngo, Phuong Dinh; Budrionis, Andrius; Markljung, kaisa; Hind, Lill Irene; Torsvik, Torbjørn; Mikalsen, Karl Øyvind; Babic, Aleksandar; Dalianis, Hercules (Journal article; Tidsskriftartikkel; Peer reviewed, 2025-07-03)
      Background: Clinical coding is critical for hospital reimbursement, quality assessment, and health care planning. In Scandinavia, however, coding is often done by junior doctors or medical secretaries, leading to high rates of coding errors. Artificial intelligence (AI) tools, particularly semiautomatic computer-assisted coding tools, have the potential to reduce the excessive burden of administrative ...
    • Design and Evaluation of Interference Handling Mechanisms in Flow-Level Simulators 

      Solli, Stian Alexander (Master thesis, 2025)
      Wireless distributed systems face significant challenges when multiple devices share limited spectrum resources, leading to signal interference that corrupts data and impacts system performance. Flow-level network simulators, while computationally efficient, typically struggle to accurately model wireless interference scenarios, requiring users to implement complex collision handling mechanisms ...
    • BenderGPT: LLM Assisted Query Optimizing 

      Aarekol, Asbjørn Gisleson (Master thesis, 2025)
      Large language models have recently shown the ability to perform complex reasoning and planning tasks far beyond their original training objectives, yet they rarely serve as autonomous building blocks in production systems. Meanwhile, database query optimizers remain rigid, handcrafted systems that struggle with large complex queries. To bridge this gap, we introduce BenderGPT, a pluggable LLM‐powered ...
    • A Simulated UAV System for Greenhouse Gas Emission Source Localization Using Dispersion Modeling 

      Nonskar, Eirik Flønes (Master thesis, 2025)
      Accurate and efficient localization of greenhouse gas (GHG) emission sources is an important challenge in environmental monitoring. Unmanned aerial vehicles (UAVs) offer a flexible platform for this task, but efficient sampling and localization remain challenging, particularly under resource constraints such as limited flight time and onboard processing capabilities. This thesis presents a simulated ...
    • Automating the TinyML Pipeline: From Model Compression to Edge Deployment 

      Onderwater, Jurian Jasper (Master thesis, 2025)
      Deploying machine learning on resource-constrained devices such as microcontrollers, especially in harsh environments (e.g., the arctic) presents significant challenges. This thesis explores solving these challenges in the framework of TinyMLOps, focusing on enabling live model updates and predicting inference latency on STM micro controllers. A method for seamless runtime weight updates via direct ...
    • Little to lose: The case for a robust European green hydrogen strategy 

      van Greevenbroek, Koen; Schmidt, Johannes; Zeyringer, Marianne; Horsch, Alexander (Journal article; Tidsskriftartikkel; Peer reviewed, 2025-06-11)
      Europe is bound by the Paris Agreement to transition to net-zero greenhouse gas emissions by 2050; the EU has further proposed a 90% emissions reduction target already for 2040. Green hydrogen (that is, hydrogen produced from clean electricity) is often framed as a key component in the transition to net-zero emissions, being a viable emissions-free alternative to fossil fuels in some contexts. ...
    • Automatic time in bed detection from hip-worn accelerometers for large epidemiological studies: The Tromsø Study 

      Weitz, Marc; Syed, Shaheen; Hopstock, Laila Arnesdatter; Morseth, Bente; Henriksen, André; Horsch, Alexander (Journal article; Tidsskriftartikkel, 2025-05-06)
      Accelerometers are frequently used to assess physical activity in large epidemiological studies. They can monitor movement patterns and cycles over several days under free-living conditions and are usually either worn on the wrist or the hip. While wrist-worn accelerometers have been frequently used to additionally assess sleep and time in bed behavior, hip-worn accelerometers have been widely ...
    • Automated Guided Vehicle Collision Avoidance with Reinforcement Learning 

      Mundt, Thomas (Master thesis; Mastergradsoppgave, 2022-05-23)
      Industry 4.0 introduces a new approach to manufacturing, focusing on connecting and automating machines. Automated vehicles that can operate in a dynamic environment, will enable the move towards Industry 4.0 to require less manual effort. The approach will be to create a simulation of an environment, with several Automated Guided Vehicles, that use a reinforcement learning system to avoid ...
    • Towards Migraine-Event Prediction Using Continuous Long-Term Biometric Sensor Data 

      Henriksen, André; Ursin, Daniel; Norbye, Anja Margrete Davis; Hartvigsen, Gunnar; Farbu, Erlend Hoftun (Journal article; Tidsskriftartikkel; Peer reviewed, 2025)
      Migraine is a common chronic headache disorder characterizsed by episodes of moderate to severe headaches, resulting in a large personal- and societal burden. To address this, we implemented a mobile app solution aimed at enhancing continuous data collection and increasing data coverage for the Empatica E4 biometric sensor device. Our ultimate goal is to use this system in a future migraine event ...
    • Piloting an Augmented Reality Exergame for Persons with Intellectual Disabilities 

      Henriksen, André; Millana, Antonio Martinez; Gomez-Noe, Alejandro; Hartvigsen, Gunnar; Anke, Audny Gabriele Wagner; Stellander, Magnus; Dybwad, Dorthe; Luzi, Thomas; Michalsen, Henriette (Journal article; Tidsskriftartikkel; Peer reviewed, 2025)
      In this paper we propose a new approach for increasing physical activity (PA) in individuals with intellectual disabilities (IDs), using augmented reality exergames to increase adherence and motivation. The game encourages PA by showing virtual elements through a mobile phone camera. The elements only appeared if the player moved in the real world. The game was specifically designed for people with ...
    • Secondary use of health records for prediction, detection, and treatment planning in the clinical decision support system: a systematic review 

      Pant, Dipendra; Nytrø, Øystein; Leventhal, Bennett L.; Clausen, Carolyn Elizabeth; Koochakpour, Kaban; Stien, Line; Westbye, Odd Sverre; Koposov, Roman A; Røst, Thomas Brox; Frodl, Thomas; Skokauskas, Norbert (Journal article; Tidsskriftartikkel; Peer reviewed, 2025-05-16)
      Background - This study aims to understand how secondary use of health records can be done for prediction, detection, treatment recommendations, and related tasks in clinical decision support systems.<p> <p>Methods - Articles mentioning the secondary use of EHRs for clinical utility, specifically in prediction, detection, treatment recommendations, and related tasks in decision support were ...
    • eU2U: Energy-efficient Wireless Charging and Trajectory Design for IoT Data Collection 

      Zhang, Qixia; Taherkordi, Amirhosein; Ha, Hoai Phuong (Journal article; Tidsskriftartikkel; Peer reviewed, 2025-05-05)
      Thanks to their high maneuverability, high flexibility, and low cost, unmanned aerial vehicles (UAVs) have been widely used for data collection in the Internet of Things (IoT). To deal with UAV's onboard battery limitation, UAV-to-UAV (U2U) wireless charging mechanism emerges as a promising solution for extending flight distance and reducing mission completion time. However, U2U charging mechanisms ...
    • Cost-Efficient Vehicular Edge Computing Deployment for Mobile Air Pollution Monitoring 

      Zhang, Qixia; Taherkordi, Amirhosein; Ha, Hoai Phuong (Chapter; Bokkapittel, 2024-07-03)
      Vehicular Edge Computing (VEC) emerges as a rem-edy to achieve flexible and fine-grained air pollution monitoring, where vehicles equipped with onboard sensors can sense, process, calibrate and store air pollutants on the drive, and roadside units (RSUs) can be deployed for vehicles to offload data via low-cost vehicle-to-RSU (V2R) communication. However, existing VEC-based air pollution monitoring ...