Now showing items 321-340 of 468

    • Performance of data enhancements and training optimization for neural network: A polyp detection case study 

      Henriksen, Fredrik Lund; Jensen, Rune; Stensland, Håkon Kvale; Johansen, Dag; Riegler, Michael; Halvorsen, Pål (Journal article; Tidsskriftartikkel; Peer reviewed, 2019-08-05)
      Deep learning using neural networks is becoming more and more popular. It is frequently used in areas like video analysis, image retrieval, traffic forecast and speech recognition. In this respect, the learning and training process usually requires a lot of data. However, in many areas, data is scarce which is definitely the case in our medical application scenario, i.e., polyp detection in the ...
    • 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 ...
    • Novel secure VPN architectures for LTE backhaul networks 

      Liyanage, Madhusanka; Kumar, Pradeep; Ylianttila, Mika; Gurtov, Andrei (Journal article; Tidsskriftartikkel; Peer reviewed, 2016-01-11)
      In this paper, we propose two secure virtual private network architectures for the long‐term evolution backhaul network. They are layer 3 Internet protocol (IP) security virtual private network architectures based on Internet key exchange version 2 mobility and multihoming protocol and host identity protocol. Both architectures satisfy a complete set of 3GPP backhaul security requirements such as ...
    • pVD - Personal Video Distribution 

      Su, Fei; Bjørndalen, John Markus; Ha, Hoai Phuong; Anshus, Otto (Journal article; Tidsskriftartikkel, 2013-11-25)
      A user has several personal computers, including mobile phones, tablets, and laptops, and needs to watch live camera feeds from and videos stored at any of these computers at one or more of the others. Industry solutions designed for many users, computers, and videos can be complicated and slow to apply. The user must typically rely on a third party service or at least log in. The Personal Video ...
    • MultiStage: Acting across Distance 

      Su, Fei; Tartari, Giacomo; Bjørndalen, John Markus; Ha, Hoai Phuong; Anshus, Otto (Conference object; Konferansebidrag, 2013)
      We report on a prototype system helping actors on a stage to interact and perform with actors on other stages as if they were on the same stage. At each stage four 3D cameras tiled back to back for an almost 360 degree view, continuously record actors. The system processes the recorded data on-the-fly to discover actions by actors that it should react to, and it streams data about actors and their ...
    • Masking the Effects of Delays in Human-to-Human Remote Interaction 

      Su, Fei; Bjørndalen, John Markus; Ha, Hoai Phuong; Anshus, Otto (Chapter; Bokkapittel, 2014)
      Humans can interact remotely with each other through computers. Systems supporting this include teleconferencing, games and virtual environments. There are delays from when a human does an action until it is reflected remotely. When delays are too large, they will result in inconsistencies in what the state of the interaction is as seen by each participant. The delays can be reduced, but they cannot ...
    • Wearable Sensors with Possibilities for Data Exchange: Analyzing Statusand Needs of Different Actors in Mobile Health Monitoring Systems 

      Muzny, Miroslav; Henriksen, André; Giordanengo, Alain; Mužík, Jan; Grøttland, Astrid; Blixgård, Håvard Kvalvåg; Hartvigsen, Gunnar; Årsand, Eirik (Journal article; Tidsskriftartikkel; Peer reviewed, 2019-10-31)
      <i>Background</i> - Wearable devices with an ability to collect various type of physiological data are increasingly becoming seamlessly integrated into everyday life of people. In the area of electronic health (eHealth), many of these devices provide remote transfer of health data, as a result of the increasing need for ambulatory monitoring of patients. This has a potential to reduce the cost ...
    • 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 ...
    • App Features for Type 1 Diabetes Support and Patient Empowerment: Systematic Literature Review and Benchmark Comparison 

      Martínez-Millana, Antonio; Jarones, Elena; Fernandez-Llatas, Carlos; Hartvigsen, Gunnar; Traver, Vicente (Journal article; Tidsskriftartikkel; Peer reviewed, 2018)
      <p><i>Background</i>: Research in type 1 diabetes management has increased exponentially since the irruption of mobile health apps for its remote and self-management. Despite this fact, the features affect in the disease management and patient empowerment are adopted by app makers and provided to the general population remain unexplored.</p> <p><i>Objective</i>: To study the gap between literature ...
    • 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 ...