Nye registreringer

  • META-pipe cloud setup and execution 

    Agafonov, Aleksander; Mattila, Kimmo; Tuan, Cuong Duong; Tiede, Lars; Raknes, Inge Alexander; Bongo, Lars Ailo Aslaksen (Journal article; Tidsskriftartikkel; Peer reviewed, 2018-01-18)
    META-pipe is a complete service for the analysis of marine metagenomic data. It provides assembly of high-throughput sequence data, functional annotation of predicted genes, and taxonomic profiling. The functional annotation is computationally demanding and is therefore currently run on a high-performance computing cluster in Norway. However, additional compute resources are necessary to open the ...
  • Uni- and triaxial accelerometric signals agree during daily routine, but show differences between sports 

    Smith, Maia P; Horsch, Alexander; Standl, Marie; Heinrich, Joachim; Schulz, Holger (Journal article; Tidsskriftartikkel; Peer reviewed, 2018-10-10)
    Accelerometers objectively monitor physical activity, and ongoing research suggests they can also detect patterns of body movement. However, different types of signal (uniaxial, captured by older studies, vs. the newer triaxial) and or/device (validated Actigraph used by older studies, vs. others) may lead to incomparability of results from different time periods. Standardization is desirable. We ...
  • Norwegian e-Infrastructure for Life Sciences (NeLS) 

    Tekle, Kidane M; Gundersen, Sveinung; Klepper, Kjetil; Bongo, Lars Ailo; Raknes, Inge Alexander; Li, Xiaxi; Zhang, Wei; Andreetta, Christian; Mulugeta, Teshome Dagne; Kalaš, Matúš; Rye, Morten Beck; Hjerde, Erik; Antony Samy, Jeevan Karloss; Fornous, Ghislain; Azab, Abdulrahman; Våge, Dag Inge; Hovig, Eivind; Willassen, Nils Peder; Drabløs, Finn; Nygård, Ståle; Petersen, Kjell; Jonassen, Inge (Journal article; Tidsskriftartikkel; Peer reviewed, 2018-06-29)
    The Norwegian e-Infrastructure for Life Sciences (NeLS) has been developed by ELIXIR Norway to provide its users with a system enabling data storage, sharing, and analysis in a project-oriented fashion. The system is available through easy-to-use web interfaces, including the Galaxy workbench for data analysis and workflow execution. Users confident with a command-line interface and programming may ...
  • A systematic review of cluster detection mechanisms in syndromic surveillance: Towards developing a framework of cluster detection mechanisms for EDMON system 

    Yeng, Prosper Kandabongee; Woldaregay, Ashenafi Zebene; Solvoll, Terje; Hartvigsen, Gunnar (Journal article; Tidsskriftartikkel; Peer reviewed, 2018)
    Time lag in detecting disease outbreaks remains a threat to global health security. Currently, our research team is working towards a system called EDMON, which uses blood glucose level and other supporting parameters from people with type 1 diabetes, as indicator variables for outbreak detection. Therefore, this paper aims to pinpoint the state of the art cluster detection mechanism towards developing ...
  • Shrinkage estimation of rate statistics 

    Holsbø, Einar Jakobsen; Perduca, Vittorio (Journal article; Tidsskriftartikkel; Peer reviewed, 2018-10-08)
    This paper presents a simple shrinkage estimator of rates based on Bayesian methods. Our focus is on crime rates as a motivating example. The estimator shrinks each town’s observed crime rate toward the country-wide average crime rate according to town size. By realistic simulations we confirm that the proposed estimator outperforms the maximum likelihood estimator in terms of global risk. We also ...
  • Performance principles for trusted computing with intel SGX 

    Gjerdrum, Anders Tungeland; Pettersen, Robert; Johansen, Håvard D.; Johansen, Dag (Journal article; Tidsskriftartikkel; Peer reviewed, 2018-07-14)
    Cloud providers offering Software-as-a-Service (SaaS) are increasingly being trusted by customers to store sensitive data. Companies often monetize such personal data through curation and analysis, providing customers with personalized application experiences and targeted advertisements. Personal data is often accompanied by strict privacy and security policies, requiring data processing to be ...
  • 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 ...
  • Dissecting deep neural networks for better medical image classification and classification understanding 

    Hicks, Steven Alexander; Riegler, Michael; Pogorelov, Konstantin; Ånonsen, Kim Vidar; de Lange, Thomas; Johansen, Dag; Jeppsson, Mattis; Randel, Kristin Ranheim; Eskeland, Sigrun Losada; Halvorsen, Pål (Journal article; Tidsskriftartikkel; Peer reviewed, 2018-07-23)
    Neural networks, in the context of deep learning, show much promise in becoming an important tool with the purpose assisting medical doctors in disease detection during patient examinations. However, the current state of deep learning is something of a "black box", making it very difficult to understand what internal processes lead to a given result. This is not only true for non-technical users but ...
  • Design and development of a context-aware knowledge-based module for identifying relevant information and information gaps in patients with type 1 diabetes self-collected health data 

    Giordanengo, Alain; Øzturk, Pinar; Hansen, Anne Helen; Årsand, Eirik; Grøttland, Astrid; Hartvigsen, Gunnar (Journal article; Tidsskriftartikkel; Peer reviewed, 2018-07-11)
    <p><i>Background</i>: Patients with diabetes use an increasing number of self-management tools in their daily life. However, health institutions rarely use the data generated by these services mainly due to (1) the lack of data reliability, and (2) medical workers spending too much time extracting relevant information from the vast amount of data produced. This work is part of the FullFlow project, ...
  • Quantified Soccer Using Positional Data: A Case Study 

    Pettersen, Svein Arne; Johansen, Håvard D.; Baptista, Ivan A. M.; Halvorsen, Pål; Johansen, Dag (Journal article; Tidsskriftartikkel; Peer reviewed, 2018-07-06)
    Performance development in international soccer is undergoing a silent revolution fueled by the rapidly increasing availability of athlete quantification data and advanced analytics. Objective performance data from teams and individual players are increasingly being collected automatically during practices and more recently also in matches after FIFA's 2015 approval of wearables in electronic ...
  • Flexible Devices for Arctic Ecosystems Observations 

    Michalik, Lukasz Sergiusz; Anshus, Otto; Bjørndalen, John Markus (Journal article; Tidsskriftartikkel; Peer reviewed, 2017-11-26)
    <p>Devices for observing the environment range from basic sensor systems, like step-counters, through wild-life cameras, with limited processing capabilities, to more capable devices with significant processing, memory and storage resources. Individual usage domains can benefit from a range of functionalities in these devices including flexibility in prototyping, on- device analytics, network roaming, ...
  • Using Fitness Trackers and Smartwatches to Measure Physical Activity in Research: Analysis of Consumer Wrist-Worn Wearables 

    Henriksen, André; Mikalsen, Martin Haugen; Woldaregay, Ashenafi Zebene; Muzny, Miroslav; Hartvigsen, Gunnar; Hopstock, Laila Arnesdatter; Grimsgaard, Sameline (Journal article; Tidsskriftartikkel; Peer reviewed, 2018-03-22)
    Background: New fitness trackers and smartwatches are released to the consumer market every year. These devices are equipped with different sensors, algorithms, and accompanying mobile apps. With recent advances in mobile sensor technology, privately collected physical activity data can be used as an addition to existing methods for health data collection in research. Furthermore, data collected ...
  • Design and evaluation of a computer-based 24-Hour physical activity recall (cpar24) instrument 

    Kohler, Simone; Behrens, Gundula; Olden, Matthias; Baumeister, Sebastian E.; Horsch, Alexander; Fischer, Beate; Leitzmann, Michael F. (Journal article; Tidsskriftartikkel; Peer reviewed, 2017-05-30)
    <p><i>Background</i>: Widespread access to the Internet and an increasing number of Internet users offers the opportunity of using Web-based recalls to collect detailed physical activity data in epidemiologic studies.</p> <p><i>Objective</i>: The aim of this investigation was to evaluate the validity and reliability of a computer-based 24-hour physical activity recall (cpar24) instrument with ...
  • Efficient disease detection in gastrointestinal videos – global features versus neural networks 

    Pogorelov, Konstantin; Riegler, Michael; Eskeland, Sigrun Losada; de Lange, Thomas; Johansen, Dag; Griwodz, Carsten; Schmidt, Peter Thelin; Halvorsen, Pål (Journal article; Tidsskriftartikkel; Peer reviewed, 2017-07-19)
    Analysis of medical videos from the human gastrointestinal (GI) tract for detection and localization of abnormalities like lesions and diseases requires both high precision and recall. Additionally, it is important to support efficient, real-time processing for live feedback during (i) standard colonoscopies and (ii) scalability for massive population-based screening, which we conjecture can be done ...
  • Peer Observations of Observation Units 

    Stormoen, Camilla (Master thesis; Mastergradsoppgave, 2018-06-01)
    The Arctic Tundra in the far northern hemisphere is one of ecosystems that are most affected by the climate changes in the world today. Five Fram Center institutions developed a long-term research project called Climate-ecological Observatory for Arctic Tundra (COAT). Their goal is to create robust observation systems which enable documentation and understanding of climate change impacts on the ...
  • The metagenomic data life-cycle: standards and best practices 

    Ten Hoopen, Petra; Finn, Robert D.; Bongo, Lars Ailo; Corre, Erwan; Fosso, Bruno; Meyer, Folker; Mitchell, Alex; Pelletier, Eric; Pesole, Graziano; Santamaria, Monica; Willassen, Nils Peder; Cochrane, Guy (Journal article; Tidsskriftartikkel; Peer reviewed, 2017-08-01)
    Metagenomics data analyses from independent studies can only be compared if the analysis workflows are described in a harmonized way. In this overview, we have mapped the landscape of data standards available for the description of essential steps in metagenomics: (i) material sampling, (ii) material sequencing, (iii) data analysis, and (iv) data archiving and publishing. Taking examples from marine ...
  • Internet of Things Mini Display-based Motivation, Notification and Warning System for Groups of People with Diabetes Type 1 

    Mikalsen, Martin Haugen (Master thesis; Mastergradsoppgave, 2018-06-01)
    Diabetes is a complex and time-consuming affair for the people that are afflicted by the disease. A strict self-management regime needs to be followed to avoid short- and long-term complications, which requires a great deal of motivation and support from others. Low- or high-blood glucose levels can cause short- and long-term consequences, ranging from headaches and thirst to coma. In the last few ...
  • Making your devices speak. Integration between Amazon Alexa and the Managed IoT Cloud 

    Holden, Thomas (Master thesis; Mastergradsoppgave, 2018-06-01)
    Speech recognition and communication between humans and machines are increasingly popular today. Several companies already have products in this market segment. The Managed IoT Cloud (MIC) platform is a complete ecosystem for management of Internet of Things (IOT) devices, data storage and analysis of data. However, the platform lacks an integration with a personal assistant to introduces ...
  • Arctic HARE. A Machine Learning-based System for Performance Analysis of Cross-country Skiers 

    Nordmo, Tor-Arne Schmidt (Master thesis; Mastergradsoppgave, 2018-06-01)
    The advances in sensor technology and big-data processing enable performance analysis of sport athletes. With the increase in data, both from on-body sensors and cameras, it is possible to quantify what makes a good athlete. However, typical approaches in sports performance analysis are not adequately equipped for automatically handling big data. This thesis presents Arctic Human Activity ...
  • Swiftmend: Data Synchronization in Open mHealth Applications with Restricted Connectivity 

    Hansen, Christoffer Hellerud (Master thesis; Mastergradsoppgave, 2018-06-01)
    Open mHealth applications often include mobile devices and cloud services with replicated data between components. These replicas need periodical synchronization to remain consistent. However, there are no guarantee of connectivity to networks which do not bill users on the quantity of data usage. This thesis propose Swiftmend, a system with synchronization that minimize the quantity of I/O used on ...

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