Recent additions

  • Data-driven blood glucose pattern classification and anomalies detection: Machine-learning applications in Type 1 diabetes 

    Woldaregay, Ashenafi Zebene; Årsand, Eirik; Botsis, Taxiarchis; Albers, David; Mamykina, Lena; Hartvigsen, Gunnar (Journal article; Tidsskriftartikkel; Peer reviewed, 2019-05-01)
    <p><i>Background - </i>Diabetes mellitus is a chronic metabolic disorder that results in abnormal blood glucose (BG) regulations. The BG level is preferably maintained close to normality through self-management practices, which involves actively tracking BG levels and taking proper actions including adjusting diet and insulin medications. BG anomalies could be defined as any undesirable reading ...
  • Reproduction study using public data of: Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs 

    Voets, Mike; Møllersen, Kajsa; Bongo, Lars Ailo (Journal article; Tidsskriftartikkel; Peer reviewed, 2019-06-06)
    We have attempted to reproduce the results in <i>Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs</i>, published in JAMA 2016; 316(22), using publicly available data sets. We re-implemented the main method in the original study since the source code is not available. The original study used non-public fundus images from EyePACS ...
  • Recommendations with a Nudge 

    Karlsen, Randi; Andersen, Anders (Journal article; Tidsskriftartikkel; Peer reviewed, 2019-06-13)
    In areas such as health, environment, and energy consumption, there is a need to do better. A common goal in society is to get people to behave in ways that are sustainable for the environment or support a healthier lifestyle. Nudging is a term known from economics and political theory, for influencing decisions and behavior using suggestions, positive reinforcement, and other non-coercive means. ...
  • Convolutional Neural Network for Breathing Phase Detection in Lung Sounds 

    Jacome, Cristina; Ravn, Johan; Holsbø, Einar; Aviles-Solis, Juan Carlos; Melbye, Hasse; Ailo Bongo, Lars (Journal article; Tidsskriftartikkel; Peer reviewed, 2019-04-15)
    We applied deep learning to create an algorithm for breathing phase detection in lung sound recordings, and we compared the breathing phases detected by the algorithm and manually annotated by two experienced lung sound researchers. Our algorithm uses a convolutional neural network with spectrograms as the features, removing the need to specify features explicitly. We trained and evaluated the ...
  • Improved maximal strength is not associated with improvements in sprint time or jump height in high-level female football players: a clusterrendomized controlled trial 

    Pedersen, Sigurd; Heitmann, Kim Arne; Sagelv, Edvard Hamnvik; Johansen, Dag; Pettersen, Svein Arne (Journal article; Tidsskriftartikkel; Peer reviewed, 2019-09-17)
    <i>Background</i> - Maximal strength increments are reported to result in improvements in sprint speed and jump height in elite male football players. Although similar effects are expected in females, this is yet to be elucidated. The aim of this study was to examine the effect of maximal strength training on sprint speed and jump height in high-level female football players.<p> <p><i>Methods</i> ...
  • Performance optimization and modeling of fine-grained irregular communication in UPC 

    Lagraviere, Jeremie Alexandre Emilien; Langguth, Johannes; Prugger, Martina; Einkemmer, Lukas; Ha, Hoai Phuong; Cai, Xing (Journal article; Tidsskriftartikkel; Peer reviewed, 2019-03-03)
    The Unified Parallel C (UPC) programming language offers parallelism via logically partitioned shared memory, which typically spans physically disjoint memory subsystems. One convenient feature of UPC is its ability to automatically execute between-thread data movement, such that the entire content of a shared data array appears to be freely accessible by all the threads. The programmer friendliness, ...
  • Interdisciplinary optimism? Sentiment analysis of Twitter data 

    Weber, Charlotte Teresa; Syed, Shaheen (Journal article; Tidsskriftartikkel; Peer reviewed, 2019-07-31)
    Interdisciplinary research has faced many challenges, including institutional, cultural and practical ones, while it has also been reported as a ‘career risk’ and even ‘career suicide’ for researchers pursuing such an education and approach. Yet, the propagation of challenges and risks can easily lead to a feeling of anxiety and disempowerment in researchers, which we think is counterproductive to ...
  • 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 ...
  • CorpOperatio: Game-inspired App for Encouraging Outdoor Physical Activity for People with Intellectual Disabilities 

    Haugland, Vebjørn (Master thesis; Mastergradsoppgave, 2019-05-31)
    This thesis presents a serious mobile exergame for people with intellectual disabilities, to help people with intellectual disability be more physically active. Exergames are games with the purpose of physically engaging the user in the gameplay, and intervenes with sedentariness and repetitive behavior. The game is based around the use of augmented reality, which is described as bringing 3D virtual ...
  • AGA: A Game-Inspired Mobile Application for Promoting Physical Activity in People With Intellectual Disabilities 

    Wiik, Marius Foshaug (Master thesis; Mastergradsoppgave, 2019-05-31)
    Obesity and other health problems have a high prevalence in people with intellectual disabilities. Many lead a sedentary lifestyle and often have low scores on fitness indicators such as muscle strength and cardiovascular fitness. The purpose of this research is to identify design techniques and features of a mobile application that can help promote physical activity in people with intellectual ...
  • Hyperprov: Blockchain-based Data Provenance using Hyperledger Fabric 

    Tunstad, Petter (Master thesis; Mastergradsoppgave, 2019-05-31)
    With data intensive computing helping advance state-of-the-art in varied fields, data provenance and lineage continue to remain formidable challenges in assisting with integrity and reproducibility in research and applications. This is particularly challenging for distributed scenarios, where data may be originating from decentralized sources without any centralized control by a single trusted entity. ...
  • Scalable exploration of population-scale drug consumption data 

    Skar, Tengel Ekrem (Master thesis; Mastergradsoppgave, 2019-06-01)
    The potential for knowledge discovery is currently underutilized on pharmacoepidemiologic data sets. A big dataset enables finding and assessing rare drug consumption patterns that are associated with adverse drug reactions causing hospitalization, or death. To enable such exploration of big pharmacoepidemiology data, four key issues need so be addressed. First, to ingest, transform, preprocess ...
  • Latency Optimized Microservice Architecture for Privacy Preserving Computing 

    Magnussen, Nikolai Åsen (Master thesis; Mastergradsoppgave, 2019-06-01)
    Recent developments in microservices architecture and building have lead to the advent of unikernels, a specialized operating system kernel coupled with, and executing only, a single application. This thesis presents PPCE a distributed system utilising a microservices architecture based on unikernels, created to enable privacy-preserving computing for users, classes of users, and more importantly; ...
  • EDMON - A backend server for an infection detection system monitoring individuals with type 1 diabetes 

    Coucheron, Sverre (Master thesis; Mastergradsoppgave, 2019-05-31)
    There are a growing number of adults with diabetes worldwide. Within 2045 it is expected to become over 600 million individuals. Since there are no known cures for diabetes, self-monitoring and self-recording are often used to manage the condition. Having tools such as mobile applications allow individuals to do this. The world and society face a significant health threat from communicable diseases, ...
  • RoadAhead - Removing Uncertainty in Travel. Creating a Data Warehouse for Green Transportation Nudging 

    Wallann, Håkon (Master thesis; Mastergradsoppgave, 2019-06-22)
    This paper describes a data warehouse approach to environmentally friendly transportation nudging. Transportation makes up a significant part of global carbon emissions. These emissions impacts both the climate and the health of individuals. As such, efforts should be done to address transportation patterns and habits. In addition to the reduction of air pollution, making people more active ...
  • Limelight: Real-Time Detection of Pump-and-Dump Events on Cryptocurrency Exchanges Using Deep Learning 

    Nilsen, Andreas Isnes (Master thesis; Mastergradsoppgave, 2019-06-01)
    Following the birth of cryptocurrencies back in 2008, internet investment platforms called exchanges were created to constellate these cryptocurrencies. Allowing investors to sell and buy assets equitable and agile over a single interface. Exchanges now have become popular and carry out over 99% of all daily transactions, totaling hundreds of millions of dollars. Despite that exchanges handling ...
  • DaoCron. Job Scheduler for Autonomous Observation Units in the Arctic Tundra 

    Moe Carstens, Martin Sommerseth (Master thesis; Mastergradsoppgave, 2019-05-31)
    DaoCron is a service which enables users to schedule tasks periodically. The Distributed Arctic Observatory (DAO) aims to improve the data collection from the arctic tundra using Observation Units (OUs). These OUs are given a set of tasks which they are expected to schedule at certain intervals. In order to schedule these tasks at certain time-intervals one can make use of Cron, which is a tool for ...
  • Verification of the Chord protocol in TLA+ 

    Lund, Jørgen Aarmo (Master thesis; Mastergradsoppgave, 2019-05-15)
    In traditional software engineering methodologies, software correctness is established through testing and progressive fault mitigation. Safety properties are established by demonstrating that a sufficiently large number of test cases fail to violate them. In contrast, formal verification methods permit a systems design process where desired safety properties are stated outright in the system ...
  • DiDiMap. Diet Diary and Consumption Control for Monitoring Bowel Dysfunctions and low-FODMAP Diet App 

    Olsen, Tobias Robin Borgen (Master thesis; Mastergradsoppgave, 2019-05-31)
    The purpose of this project was to design and implement a mobile application for people with bowel dysfunctions, intolerances, and food allergies. The application was expected to provide all needed functionality for the target groups day to day challenges. Irritable bowel syndrome, intolerances, and food allergies affect a significant portion of the population. On a world basis, 15\% of the ...
  • VisualBox. A Generic Data Integration and Visualization Tool 

    Aurdal, Pontus Edvard (Master thesis; Mastergradsoppgave, 2019-05-30)
    The number of cellular Internet of Things (IoT) connections is expected to grow at a rate of 30% each year and is reaching into the billions by 2019. The world of IoT can be fragmented since data sources span a wide variety of protocols, API's, authentication methods and file formats. Data collection and processing can be complex and producing visualizations for value extraction can be a tedious ...

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