• 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 ...
    • Data Analysis and Nudging for Green Transportation 

      Jemea, Lady Limunga (Master thesis; Mastergradsoppgave, 2019-05-14)
      The topic of a more sustainable environment has been a core factor to governments and the public for many years. Sustainability in land transportation brings about less emission of greenhouse gases, less pollution, less traffic, a healthier and more active society. Ignorance to sustainability has brought about several environmental and human concerns including global warming. Global warming is the ...
    • Data Analysis Techniques for Smart Nudging 

      Dhanasekaran, Seshathiri; Andersen, Anders; Karlsen, Randi; Håkansson, Anne (Conference object; Konferansebidrag, 2021)
      <p>Nudge principles and techniques are significant in communications, marketing, and groups’ motivation to improve personal health, wealth, and well-being. We make numerous decisions in online situations. People’s health and well-being have garnered widespread interest and concern in this wearable’s age. Smart nudging is defined as “digital nudging, where the guidance of user behavior is tailored ...
    • Data collection and analysis methods for smart nudging to promote physical activity: Protocol for a mixed methods study 

      Dhanasekaran, Seshathiri; Andersen, Anders; Karlsen, Randi; Håkansson, Anne; Henriksen, André (Journal article; Tidsskriftartikkel; Peer reviewed, 2023)
      New digital technologies like activity trackers, nudge concepts, and approaches can inspire and improve personal health. There is increasing interest in employing such devices to monitor people’s health and well-being. These devices can continually gather and examine health-related information from people and groups in their familiar surroundings. Context-aware nudges can assist people in self-managing ...
    • 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.
    • Data collection and smart nudging to promote physical activity and a healthy lifestyle using wearable devices 

      Dhanasekaran, Seshathiri; Andersen, Anders; Karlsen, Randi; Håkansson, Anne; Henriksen, André (Chapter; Bokkapittel, 2022-08-22)
      Nudge principles and techniques can motivate and improve personal health through emerging digital devices, such as activity trackers. Tracking people's health and well-being using such devices have earned widespread interest. These devices can continuously capture and analyze health-related data from individuals and communities in their everyday environment. Providing context-aware nudges can help ...
    • Data Management for Nudged Green Transportation 

      Crăciun, Cosmin Radu (Master thesis; Mastergradsoppgave, 2019-05-14)
      Climate change is one of the most talked about topics in the world at the moment. In the context of man induced Global Warming, there are many proposed ideas on how to combat its effects and many more are still needed. We propose employing nudge theory to persuade people into using environmentally friendly modes of transport through a software application. This thesis focuses on the data management ...
    • Data management platform for citizen science education projects 

      Angelvik, Nina (Master thesis; Mastergradsoppgave, 2018-05-15)
      The air:bit project is a computer science education project that we developed in 2016 for use in North-Norwegian upper secondary (videregående) schools. Students build and code their own air quality sensor kits (air:bits), before collecting air quality data in their local areas. They create their own air quality related research questions, which they answer by analyzing the collected air:bit data ...
    • 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 ...
    • 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 ...
    • Data-driven modeling and prediction of blood glucose dynamics: Machine learning applications in type 1 diabetes 

      Woldaregay, Ashenafi Zebene; Årsand, Eirik; Walderhaug, Ståle; Albers, David; Mamykina, Lena; Botsis, Taxiarchis; Hartvigsen, Gunnar (Journal article; Tidsskriftartikkel; Peer reviewed, 2019-07-26)
      <i>Background</i>: Diabetes mellitus (DM) is a metabolic disorder that causes abnormal blood glucose (BG) regulation that might result in short and long-term health complications and even death if not properly managed. Currently, there is no cure for diabetes. However, self-management of the disease, especially keeping BG in the recommended range, is central to the treatment. This includes actively ...
    • Data-intensive computing infrastructure systems for unmodified biological data analysis pipelines 

      Bongo, Lars Ailo; Pedersen, Edvard; Ernstsen, Martin (Journal article; Tidsskriftartikkel; Peer reviewed, 2015-11-18)
      Biological data analysis is typically implemented using a deep pipeline that combines a wide array of tools and databases. These pipelines must scale to very large datasets, and consequently require parallel and distributed computing. It is therefore important to choose a hardware platform and underlying data management and processing systems well suited for processing large datasets. There are many ...
    • Dataset of Consumer-Based Activity Trackers as a Tool for Physical Activity Monitoring in Epidemiological Studies During the COVID-19 Pandemic 

      Henriksen, André; Johannessen, Erlend; Hartvigsen, Gunnar; Grimsgaard, Sameline; Hopstock, Laila Arnesdatter (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-03-01)
      Physical activity (PA) data were downloaded from 113 participants who owned a Garmin or Fitbit activity tracker in 2019 and 2020. Upon participant authorization, data were automatically downloaded from the Garmin and Fitbit cloud storages. The mSpider tool, a solution for automatic and continuous data extraction from activity tracker providers, were used to download participant data. Available ...
    • Dataset of fitness trackers and smartwatches to measuring physical activity in research 

      Henriksen, André; Woldaregay, Ashenafi Zebene; Muzny, Miroslav; Hartvigsen, Gunnar; Hopstock, Laila Arnesdatter; Grimsgaard, Sameline (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-07-16)
      Objectives: Accelerometer-based wrist-worn ftness trackers and smartwatches (wearables) appeared on the consumer market in 2011. Many wearable devices have been released since. The objective of this data paper is to describe a dataset of 423 wearables released before July 2017.<p> <p>Data description: We identifed wearables and extracted information from six online and ofine databases. We ...
    • Dataset of motivational factors for using mobile health applications and systems 

      Henriksen, André; Issom, David-Zacharie; Woldaregay, Ashenafi Zebene; Pfuhl, Gerit; Årsand, Eirik; Sato, Keiichi; Hartvigsen, Gunnar (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-09-16)
      We created and carried out a cross-sectional anonymous structured questionnaire on what motivates users of mobile health applications and wearables to share their collected health related data. The questionnaire was distributed online in English, French, and Norwegian. In addition, a flyer with information of where to locate the online questionnaire was distributed during a Swiss health conference. ...
    • Dárkon 

      Johansen, Sebastian Lyng (Mastergradsoppgave; Master thesis, 2023-05-22)
      Sports today are more competitive than ever, with an eye for extreme details. Small margins can differentiate between succeeding or failing. That is why it is essential for a team to pay attention to all these margins and use them to their advantage. Technology today plays a huge part in sports. With video cameras and sensors following the players’ every move, it is vital to use this technology ...
    • De-identifying Norwegian Clinical Text using Resources from Swedish and Danish 

      Lamproudis, Anastasios; Mora, Sara; Olsen Svenning, Therese; Torsvik, Torbjørn; Chomutare, Taridzo Fred; Ngo, Phuong Dinh; Dalianis, Hercules (Journal article; Tidsskriftartikkel, 2023)
      The lack of relevant annotated datasets represents one key limitation in the application of Natural Language Processing techniques in a broad number of tasks, among them Protected Health Information (PHI) identification in Norwegian clinical text. In this work, the possibility of exploiting resources from Swedish, a very closely related language, to Norwegian is explored. The Swedish dataset is ...
    • A Declarative Profile Model for Qos negotiation 

      Hanssen, Øyvind (Research report; Forskningsrapport, 2005-12)
      In this report we define the semantics of a language for dynamic QoS expressions which can be evaluated at run-time for conformance. We define how expressions can be constructed from atomic expressions termed ’basic profiles’ using composition operators. Two such operators are defined: The sum ( ’+’ ) which corresponds to simple conjunction and component-sum (’Å’) which assume that the operands ...
    • A Deep Diagnostic Framework Using Explainable Artificial Intelligence and Clustering 

      Thunold, Håvard Horgen; Riegler, Michael; Yazidi, Anis; Hammer, Hugo Lewi (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-11-09)
      An important part of diagnostics is to gain insight into properties that characterize a disease. Machine learning has been used for this purpose, for instance, to identify biomarkers in genomics. However, when patient data are presented as images, identifying properties that characterize a disease becomes far more challenging. A common strategy involves extracting features from the images and ...
    • Deep learning and hand-crafted feature based approaches for polyp detection in medical videos 

      Pogorelov, Konstantin; Ostroukhova, Olga; Jeppsson, Mattis; Espeland, Håvard; Griwodz, Carsten; de Lange, Thomas; Riegler, Michael; Halvorsen, Pål (Journal article; Tidsskriftartikkel; Peer reviewed, 2018-07-23)
      Video analysis including classification, segmentation or tagging is one of the most challenging but also interesting topics multimedia research currently try to tackle. This is often related to videos from surveillance cameras or social media. In the last years, also medical institutions produce more and more video and image content. Some areas of medical image analysis, like radiology or brain ...