Viser treff 215-234 av 389

    • Naturvitenskapens grunnlag og begrensning. Seminarrapport 

      Thorvaldsen, Steinar (Research report; Forskningsrapport, 1979)
      Foredrag av Arthur E. Wilder-Smith og Udo Middelmann holdt ved NTH i 1979
    • NB-FEB : an easy-to-use and scalable universal synchronization primitive for parallel programming 

      Ha, Hoai Phuong; Tsigas, Philippas; Anshus, Otto J. (Research report; Forskningsrapport, 2008-10)
      This paper addresses the problem of universal synchronization primitives that can support scalable thread synchronization for large-scale many-core architectures. The universal synchronization primitives that have been deployed widely in conventional architectures, are the compare-and-swap (CAS) and load-linked/store-conditional (LL/SC) primitives. However, such synchronization primitives are ...
    • Neural network based country wise risk prediction of COVID-19 

      Pal, Ratnabali; Sekh, Arif Ahmed; Kar, Samarjit; Prasad, Dilip K. (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-09-16)
      The recent worldwide outbreak of the novel coronavirus (COVID-19) has opened up new challenges to the research community. Artificial intelligence (AI) driven methods can be useful to predict the parameters, risks, and effects of such an epidemic. Such predictions can be helpful to control and prevent the spread of such diseases. The main challenges of applying AI is the small volume of data and the ...
    • Neural Network Based Country Wise Risk Prediction of COVID-19 

      Pal, Ratnabali; Sekh, Arif Ahmed; Kar, Samarjit; Prasad, Dilip K. (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-09-16)
      The recent worldwide outbreak of the novel coronavirus (COVID-19) has opened up new challenges to the research community. Artificial intelligence (AI) driven methods can be useful to predict the parameters, risks, and effects of such an epidemic. Such predictions can be helpful to control and prevent the spread of such diseases. The main challenges of applying AI is the small volume of data and the ...
    • Next frontiers in energy system modelling: A review on challenges and the state of the art 

      Fodstad, Marte; Crespo del Granado, Pedro; Hellemo, Lars; Knudsen, Brage Rugstad; Pisciella, Paolo; Silvast, Antti; Bordin, Chiara; Schmidt, Sarah; Straus, Julian (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-02-26)
      Energy Systems Modelling is growing in relevance on providing insights and strategies to plan a carbon-neutral future. The implementation of an effective energy transition plan faces multiple challenges, spanning from the integration of the operations of different energy carriers and sectors to the consideration of multiple spatial and temporal resolutions. In this review, we outline these challenges ...
    • NFC Prototype Bonanza 

      Holmstad, Øyvind; Kreutzer, Tor (Research report; Forskningsrapport, 2011)
      This report presents the results of the research conducted by Tor Kreutzer and Ø yvind Holmstad during the summer of 2011 at the University of Troms ø. The goal of the project was to gain practical experience with Near Field Communication (NFC) technology by exploring its properties through hands-on development of applications and services. To explore the applicability and limitations of NFC we ...
    • Njord: a fishing trawler dataset 

      Nordmo, Tor-Arne Schmidt; Ovesen, Aril Bernhard; Juliussen, Bjørn Aslak; Hicks, Steven; Thambawita, Vajira L B; Johansen, Håvard D.; Halvorsen, Pål; Riegler, Michael Alexander; Johansen, Dag (Chapter; Bokkapittel, 2022-08-05)
      Fish is one of the main sources of food worldwide. The commercial fishing industry has a lot of different aspects to consider, ranging from sustainability to reporting. The complexity of the domain also attracts a lot of research from different fields like marine biology, fishery sciences, cybernetics, and computer science. In computer science, detection of fishing vessels via for example remote ...
    • The NOOP experimental Python programming environment 

      Andersen, Anders (Journal article; Tidsskriftartikkel, 2014)
      Python is a dynamic language well suited to build a run-time providing adaptive support to distributed applications. Python has dynamic typing where variables are given a type when they are assigned a value. To introduce type safety, interfaces, and a component model in Python NOOP introduces a type language and a way to apply typing to functions (and methods). This type system is described in the ...
    • The Nornir run-time system for parallel programs using Kahn process networks on multi-core machines-a flexible alternative to MapReduce 

      Vrba, Zeljko; Halvorsen, Pål; Griwodz, Carsten; Beskow, Paul; Espeland, Håvard; Johansen, Dag (Journal article; Tidsskriftartikkel; Peer reviewed, 2013)
      Even though shared-memory concurrency is a paradigm frequently used for developing parallel applications on small- and middle-sized machines, experience has shown that it is hard to use. This is largely caused by synchronization primitives which are low-level, inherently non-deterministic, and, consequently, non-intuitive to use. In this paper, we present the Nornir run-time system. Nornir is ...
    • Northeast Arctic Cod and Prey Match-Mismatch in a High-Latitude Spring-Bloom System 

      Vikebø, Frode Bendiksen; Broch, Ole Jacob; Kajiya Endo, Clarissa Akemi; Frøysa, Håvard G; Carroll, JoLynn; Juselius, Jonas; Langangen, Øystein Ole Gahr (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-12-20)
      By combining an ocean model, a nutrient-phytoplankton-zooplankton-detritus-model and an individual-based model for early life stages of Northeast Arctic cod we systematically investigate food limitations and growth performance for individual cod larvae drifting along the Norwegian coast from spawning grounds toward nursery areas in the Barents Sea. We hypothesize that there is food shortage for ...
    • 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 novel algorithm to detect non-wear time from raw accelerometer data using deep convolutional neural networks 

      Syed, Shaheen; Morseth, Bente; Hopstock, Laila Arnesdatter; Horsch, Alexander (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-04-23)
      To date, non-wear detection algorithms commonly employ a 30, 60, or even 90 mins interval or window in which acceleration values need to be below a threshold value. A major drawback of such intervals is that they need to be long enough to prevent false positives (type I errors), while short enough to prevent false negatives (type II errors), which limits detecting both short and longer episodes of ...
    • A Novel Approach for Continuous Health Status Monitoring and Automatic Detection of Infection Incidences in People With Type 1 Diabetes Using Machine Learning Algorithms (Part 2): A Personalized Digital Infectious Disease Detection Mechanism 

      Woldaregay, Ashenafi Zebene; Launonen, Ilkka Kalervo; Albers, David; Igual, Jorge; Årsand, Eirik; Hartvigsen, Gunnar (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-08-12)
      <i>Background</i>: Semisupervised and unsupervised anomaly detection methods have been widely used in various applications to detect anomalous objects from a given data set. Specifically, these methods are popular in the medical domain because of their suitability for applications where there is a lack of a sufficient data set for the other classes. Infection incidence often brings prolonged ...
    • 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 ...
    • Numerical Investigation of Radiative Hybrid Nanofluid Flows over a Plumb Cone/Plate 

      Peter, Francis; Sambath, Paulsamy; Dhanasekaran, Seshathiri (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-10-18)
      Non-Newtonian fluids play a crucial role in applications involving heat transfer and mass transfer. The inclusion of nanoparticles in these fluids improves the efficiency of heat and mass transfer processes. This study employs a numerical solution approach to examine the flow of non-Newtonian hybrid nanofluids over a plumb cone/plate surface, considering the effects of magnetohydrodynamics (MHD) and ...
    • Omni-Kernel: An Operating System Architecture for Pervasive Monitoring and Scheduling 

      Kvalnes, Åge; Johansen, Dag; Renesse, Robbert van; Schneider, Fred B.; Valvåg, Steffen (Research report; Forskningsrapport, 2013)
      Clouds commonly employ virtual machine technology to leverage and efficiently utilize computational resources in data centers. The workloads encapsulated by virtual machines contend for the resources of their hosting machines, and interference from resource sharing can cause unpredictable performance. Despite the use of virtual machine technology, the role of the operating system as an arbiter of ...
    • On Edge Cloud Service Provision with Distributed Home Servers 

      Khan, Muhammed Amin; Freitag, Felix (Conference object; Konferansebidrag, 2017-12-28)
      Edge computing has been proposed for new types of cloud services, which need computing infrastructure at the network edge. Driven by important use cases from the Internet of Things (IoT) domain, edge cloud computing has also a huge business potential. Edge computing devices are already operational in many industrial and consumer-oriented scenarios. A typical characteristic of these solutions is, ...
    • On evaluation metrics for medical applications of artificial intelligence 

      Hicks, Steven A.; Strumke, Inga; Thambawita, Vajira L B; Hammou, Malek; Riegler, Michael Alexander; Halvorsen, Pål (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-04-08)
      Clinicians and software developers need to understand how proposed machine learning (ML) models could improve patient care. No single metric captures all the desirable properties of a model, which is why several metrics are typically reported to summarize a model’s performance. Unfortunately, these measures are not easily understandable by many clinicians. Moreover, comparison of models across studies ...
    • On Optimizing Transaction Fees in Bitcoin using AI: Investigation on Miners Inclusion Pattern 

      Tedeschi, Enrico; Nordmo, Tor-Arne Schmidt; Johansen, Dag; Johansen, Håvard D. (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-04-09)
      The transaction-rate bottleneck built into popular proof-of-work-based cryptocurrencies, like Bitcoin and Ethereum, leads to fee markets where transactions are included according to a first-price auction for block space. Many attempts have been made to adjust and predict the fee volatility, but even well-formed transactions sometimes experience unexpected delays and evictions unless a substantial ...
    • On the design and performance of the PARFUM Parallel Fault Tolerant Volume Renderer 

      Asplin, Jo; Mehus, Sindre (Research report; Forskningsrapport, 1997-01)
      Volume rendering is an important and CPU-intensive technique for visualizing large scalar fields. In essence, a volume renderer performs two activites on behalf of the user: loading a new data set, and rendering the current one. At one level, the performance of an individual activity is important. At another level, the erformance of the session as a whole, in particular switching from one activity ...