Now showing items 64-83 of 627

    • 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 ...
    • ColdNotify: A Notification Service For A Distributed Arctic Observatory 

      Kraabøl, Petter (Master thesis; Mastergradsoppgave, 2019-05-15)
      One of the key challenges in the Distributed Arctic Observatory (DAO) project is designing infrastructure to reliably interact with remote, configurable observation units that capture and provide observation data from challenging environments. DAO’s infrastructure is a work in progress and researching alternative strategies for interacting with observation units is necessary to gain experience ...
    • Collecting and distributing sensor data using the Argos middleware platform 

      Mortensen, Mats (Master thesis; Mastergradsoppgave, 2007-06-15)
      Applications that adapt to environmental and situational changes are difficult to build because computers cannot capture, represent or process context information as easily as human beings. Nevertheless, context information is very valuable because it allows applications to be made more user-friendly, flexible, and adaptable. This realization has spawned a multitude of research efforts to simplify ...
    • Collecting health-related research data using consumer-based wireless smart scales 

      Johannessen, Erlend; Johansson, Jonas; Hartvigsen, Gunnar; Horsch, Alexander; Årsand, Eirik; Henriksen, André (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-03-14)
      Background: Serious public-health concerns such as overweight and obesity are in many cases caused by excess intake of food combined with decreases in physical activity. Smart scales with wireless data transfer can, together with smart watches and trackers, observe changes in the population’s health. They can present us with a picture of our metabolism, body health, and disease risks. Combining ...
    • Collecting relevant images context information 

      Jakobsen, Børge (Master thesis; Mastergradsoppgave, 2010-01-08)
      Digital photographing has become more and more popular as cameras and mobile phones get more advanced and have newer technology embedded. Manually searching in these growing image collections is problematic because of missing context information related to the image itself. If related context information could be added as an automated process, it could help the user view and locate images and ...
    • 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 ...
    • 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 ...
    • COMBUSTI/O. Abstractions facilitating parallel execution of programs implementing common I/O patterns in a pipelined fashion as workflows in Spark 

      Fagerli, Jarl (Master thesis; Mastergradsoppgave, 2016-05-31)
      In light of recent years’ exploding data generation in life sciences, increasing downstream analysis capabilities is paramount to address the asymmetry of innovation in data creation contra processing capacities. Many contemporaneously used tools are sequential programs, ofttimes including convoluted dependencies leading to workflows crashing due to misconfiguration, detrimental to both development ...
    • Comparative validation of multi-instance instrument segmentation in endoscopy: Results of the ROBUST-MIS 2019 challenge 

      Ross, Tobias; Reinke, Annika; M. Full, Peter; Wagner, Martin; Kenngott, Hannes; Apitz, Martin; Hempe, Hellena; Mindroc Filimon, Diana; Scholz, Patrick; Tran, Thuy Nuong; Bruno, Pierangela; Arbeláez, Pablo; Bian, Gui-Bin; Bodenstedt, Sebastian; Lindström Bolmgren, Jon; Bravo-Sánchez, Laura; Chen, Hua-Bin; González, Cristina; Guo, Dong; Halvorsen, Pål; Heng, Pheng-Ann; Hosgor, Enes; Hou, Zeng-Guang; Isensee, Fabian; Jha, Debesh; Jiang, Tingting; Jin, Yueming; Kirtac, Kadir; Kletz, Sabrina; Leger, Stefan; Li, Zhixuan; H. Maier-Hein, Klaus; Ni, Zhen-Liang; Riegler, Michael; Schoeffmann, Klaus; Shi, Ruohua; Speidel, Stefanie; Stenzel, Michael; Twick, Isabell; Wang, Gutai; Wang, Jiacheng; Wang, Liansheng; Wang, Lu; Zhang, Yujie; Zhou, Yan-Jie; Zhu, Lei; Wiesenfarth, Manuel; Kopp-Schneider, Annette; P. Müller-Stich, Beat; Maier-Hein, Lena (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-11-28)
      Intraoperative tracking of laparoscopic instruments is often a prerequisite for computer and roboticassisted interventions. While numerous methods for detecting, segmenting and tracking of medical instruments based on endoscopic video images have been proposed in the literature, key limitations remain to be addressed: Firstly, robustness, that is, the reliable performance of state-of-the-art methods ...
    • 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 ...
    • Compliant Sharing of Sensitive Data with Dataverse and Lohpi 

      Sharma, Aakash; Nilsen, Thomas Bye; Johansen, Håvard D. (Conference object; Konferansebidrag, 2021-06)
    • 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. ...
    • Comprehensive Analysis of Solar Panel Performance and Correlations with Meteorological Parameters 

      Sarmah, Pranjal; Das, Dipankar; Saikia, Madhurjya; Kumar, Virendra; Yadav, Surendra Kumar; Paramasivam, Prabhu; Dhanasekaran, Seshathiri (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-12-08)
      To mitigate the adverse effects of fossil fuel-based energy, mankind is in constant search of clean and cost-effective sources of energy, such as solar energy. The economic viability of a power plant to harness solar energy mostly depends on the efficiency of solar panels. Investigations over the years show that the solar panel efficiency significantly depends on the different meteorological parameters. ...
    • A configuration tool for process oriented UAV programming. 

      Pettersen, Ørjan (Master thesis; Mastergradsoppgave, 2010-06-25)
      This thesis covers the design, implementation and evaluation of a configuration tool for process oriented Unmanned Aerial Vehicle (UAV) programming. In addition it will examine if and how a process network can be used to control sensors and communication channels on an UAV in flight. NORUT-IT is currently developing a sensor platform based on UAVs. The mission computer software they have at the ...
    • Consumer-Based Activity Trackers as a Tool for Physical Activity Monitoring in Epidemiological Studies During the COVID-19 Pandemic: Development and Usability Study 

      Henriksen, André; Johannessen, Erlend; Hartvigsen, Gunnar; Grimsgaard, Sameline; Hopstock, Laila Arnesdatter (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-04-23)
      Background: Consumer-based physical activity trackers have increased in popularity. The widespread use of these devices and the long-term nature of the recorded data provides a valuable source of physical activity data for epidemiological research. The challenges include the large heterogeneity between activity tracker models in terms of available data types, the accuracy of recorded data, and how ...
    • A context-aware mobile bus application 

      Hansen, Christer Andre (Master thesis; Mastergradsoppgave, 2010-05-18)
      Accessing route information should be easy. Today, most collective transport companies distribute timeta- bles online as electronic documents and in paper format. These solutions are outdated and cumbersome to use. However, systems have been built to make the task of finding route information easy, and to replace these formats. Most of these systems, still, have limitations. They rely on users knowing ...
    • Context-based image retrieval in Fronter learning environment 

      Larsen, Jelena N (Master thesis; Mastergradsoppgave, 2011-02)
      The Internet has become a natural medium for finding information and resources, and has probably become the most important tool in education and e-learning as well. Many educational institutions use on-line systems for uploading, creating and publishing educational content to students and pupils. Extended use of multimedia files, video, audio and image, as a part of the content is a growing trend ...
    • Continious Synchronization of Conflict-Free Replicated Relations 

      Iversen, Gustav Heide (Master thesis; Mastergradsoppgave, 2022-05-12)
      Local-first software is an attempt to use the benefits of cloud service while reducing its drawbacks. Local-first software gives the clients ownership and control of their data and makes the service always available. It is achieved by having the primary copy of the service at the client. The most common way to implement local-first software is by utilizing Conflict-free Replicated Datatypes or CRDTs, ...
    • Continuation-passing enactment of distributed recoverable workflows 

      Weihei, Yu; Yang, Jie (Research report; Forskningsrapport, 2006)
      Scalability, reliability and adaptability are among the key requirements for the enactment of distributed workflows. In addition, system resources should be efficiently utilized. Central workflow engines and static analysis of workflow specifications are some of the important obstacles to meeting these requirements. We propose a fully decentralized approach to workflow enactment that is not subject ...
    • Continuous and automated data collection in migraine research - Extending the data collection capabilities of the Empatica E4 

      Ursin, Daniel (Mastergradsoppgave; Master thesis, 2023-06-01)
      Migraine is a recurrent headache disorder that afflicts significant portions of the global population. There is no current cure and migraines are mainly managed through symptomatic medical treatments and manual biofeedback routines. Automated data collection and prediction of migraine attacks through machine learning could be viable approaches for helping migraineurs and for reducing the impact of ...