Viser treff 1021-1040 av 5380

    • Trusted Computing on Privacy Sensitive Data with Diggi 

      Gjerdrum, Anders Tungeland; Pettersen, Robert; Johansen, Håvard D.; Van Renesse, Robbert; Johansen, Dag (Conference object; Konferansebidrag, 2017)
    • The Lower Cretaceous of Svalbard and its relevance for exploration in the northern Barents Sea 

      Grundvåg, Sten-Andreas; Jelby, Mads; Midtkandal, Ivar; Sliwinska, Kasia; Nøhr-Hansen, Henrik; Marin Restrepo, Dora Luz; Kairanov, Bereke; Escalona, Alejandro; Olaussen, Snorre (Conference object; Konferansebidrag, 2017)
      The Lower Cretaceous succession in the Barents Sea is listed as a potential play model by the Norwegian Petroleum Directorate. Reservoirs may occur in deep to shallow marine clastic wedges located in proximity to palaeo-highs and along basin margins. In addition, shelf-prism-scale clinoforms with high amplitude anomalies in their top- and bottomsets have been reported from reflection seismic but ...
    • Polarimetric Guided Nonlocal Means Covariance Matrix Estimation for Defoliation Mapping 

      Agersborg, Jørgen Andreas; Anfinsen, Stian Normann; Jepsen, Jane Uhd (Conference object; Konferansebidrag, 2020)
      In this study we investigate the potential for using synthetic aperture radar (SAR) data to provide high resolution defoliation and regrowth mapping of trees in the tundra-forest ecotone. Using aerial photographs, four areas with live forest and four areas with dead trees were identified. Quad-polarimetric SAR data from RADARSAT-2 was collected from the same area, and the complex multilook polarimetric ...
    • Generation of Lidar-Predicted Forest Biomass Maps from Radar Backscatter with Conditional Generative Adversarial Networks 

      Björk, Sara; Anfinsen, Stian Normann; Næsset, Erik; Gobakken, Terje; Zahabu, Eliakimu (Conference object; Konferansebidrag, 2020)
    • Heterogeneous Change Detection with Self-supervised Deep Canonically Correlated Autoencoders 

      Figari Tomenotti, Federico; Luppino, Luigi Tommaso; Hansen, Mads Adrian; Moser, Gabriele; Anfinsen, Stian Normann (Conference object; Konferansebidrag, 2020)
    • Change Detection with Heterogeneous Remote Sensing Data: From Semi-Parametric Regression to Deep Learning 

      Moser, Gabriele; Anfinsen, Stian Normann; Luppino, Luigi Tommaso; Serpico, Sebastian Bruno (Conference object; Konferansebidrag, 2020)
    • Polarizable Density Embedding for Large Biomolecular Systems 

      Reinholdt, Peter; Jørgensen, Frederik Kamper; Kongsted, Jacob; Olsen, Jógvan Magnus Haugaard (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-09-29)
      We present an efficient and robust fragment-based quantum–classical embedding model capable of accurately capturing effects from complex environments such as proteins and nucleic acids. This is realized by combining the molecular fractionation with conjugate caps (MFCC) procedure with the polarizable density embedding (PDE) model at the level of Fock matrix construction. The PDE contributions to the ...
    • A study of energy use and associated greenhouse gas emissions in Norwegian small-scale processing of whitefish 

      Høyli, Randulf; Aarsæther, Karl Gunnar (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-08-26)
      This study considers the energy use and associated greenhouse gas (GHG) emissions at three fish processing companies, representing a seasonal small-scale whitefish processing industry within the Norwegian coastal fisheries. The primary objective is to analyse the energy use in small-scale processing of whitefish and to provide energy requirements for primary processing, freezer and freezer storage, ...
    • Usefulness of Heat Map Explanations for Deep-Learning-Based Electrocardiogram Analysis 

      Storås, Andrea; Andersen, Ole Emil; Lockhart, Sam; Thielemann, Roman; Gnesin, Filip; Thambawita, Vajira L B; Hicks, Steven; Kanters, Jørgen K.; Strumke, Inga; Halvorsen, Pål; Riegler, Michael (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-07-11)
      Deep neural networks are complex machine learning models that have shown promising results in analyzing high-dimensional data such as those collected from medical examinations. Such models have the potential to provide fast and accurate medical diagnoses. However, the high complexity makes deep neural networks and their predictions difficult to understand. Providing model explanations can be a way ...
    • Image denoising in acoustic microscopy using block-matching and 4D filter 

      Gupta, Shubham Kumar; Pal, Rishant; Ahmad, Azeem; Melandsø, Frank; Habib, Anowarul (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-08-14)
      Scanning acoustic microscopy (SAM) is a label-free imaging technique used in biomedical imaging, non-destructive testing, and material research to visualize surface and sub-surface structures. In ultrasonic imaging, noises in images can reduce contrast, edge and texture details, and resolution, negatively impacting post-processing algorithms. To reduce the noises in the scanned image, we have employed ...
    • Better synoptic and subseasonal sea ice thickness predictions are urgently required: a lesson learned from the YOPP data validation 

      Yang, Qinghua; Xiu, Yongwu; Luo, Hao; Wang, Jinfei; Landy, Jack Christopher; Bushuk, Mitchell; Wang, Yiguo; Liu, Jiping; Chen, Dake (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-06-20)
      In the context of global warming, Arctic sea ice has declined substantially during the satellite era (Kwok 2018). The retreating and thinning of Arctic sea ice provide opportunities for human activities in the Arctic, such as tourism, fisheries, shipping, natural resource exploitation, and wildlife management; however, new risks emerge. To ensure the safety and emergency management of human activities ...
    • Computational design of the temperature optimum of an enzyme reaction 

      van der Ent, Florian; Skagseth, Susann; Lund, Bjarte Aarmo; Sočan, Jaka; Griese, Julia J.; Brandsdal, Bjørn Olav; Åqvist, Johan Lennart Gösta (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-06-28)
      Cold-adapted enzymes are characterized both by a higher catalytic activity at low temperatures and by having their temperature optimum down-shifted, compared to mesophilic orthologs. In several cases, the optimum does not coincide with the onset of protein melting but reflects some other type of inactivation. In the psychrophilic α-amylase from an Antarctic bacterium, the inactivation is thought to ...
    • Wind redistribution of snow impacts the Ka- and Ku-band radar signatures of Arctic sea ice 

      Nandan, Vishnu; Willatt, Rosemary; Mallett, Robbie; Stroeve, Julienne; Geldsetzer, Torsten; Scharien, Randall; Tonboe, Rasmus; Yackel, John; Landy, Jack Christopher; Clemens-Sewall, David; Jutila, Arttu; Wagner, David N.; Krampe, Daniela; Huntemann, Marcus; Mahmud, Mallik; Jensen, David; Newman, Thomas; Hendricks, Stefan; Spreen, Gunnar; Macfarlane, Amy; Schneebeli, Martin; Mead, James; Ricker, Robert; Gallagher, Michael; Duguay, Claude; Raphael, Ian; Polashenski, Chris; Tsamados, Michel; Matero, Ilkka; Hoppmann, Mario (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-06-02)
      Wind-driven redistribution of snow on sea ice alters its topography and microstructure, yet the impact of these processes on radar signatures is poorly understood. Here, we examine the effects of snow redistribution over Arctic sea ice on radar waveforms and backscatter signatures obtained from a surface-based, fully polarimetric Ka- and Ku-band radar at incidence angles between 0∘ (nadir) and 50∘. ...
    • Attention-guided Temporal Convolutional Network for Non-intrusive Load Monitoring 

      Ren, Huamin; Su, Xiaomeng; Jenssen, Robert; Li, Jingyue; Anfinsen, Stian Normann (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-12-01)
      With the prevalence of smart meter infrastructure, data analysis on consumer side becomes more and more important in smart grid systems. One of the fundamental tasks is to disaggregate users' total consumption into appliance-wise values. It has been well noted that encoding of temporal dependency is a key issue for successful modelling of the relations between the total consumption and its decomposed ...
    • Evidence of hyperpycnally fed turbidites in a basin floor setting, Eocene of Spitsbergen, Arctic Norway 

      Grundvåg, Sten-Andreas; Helland-Hansen, William (Conference object; Konferansebidrag, 2018)
      The Eocene of Spitsbergen, Svalbard, has received considerable attention in the literature because of its spectacular seismic-scale clinoforms exposed along many fiords and valleys. Previous investigations particularly focused on the slope segment of the clinoforms and demonstrated how sustained-type, hyperpycnal flows deriving from shelf-edge deltas played a major role in bringing sand onto the ...
    • Universality of intermittent fluctuations in the Alcator C-Mod scrape-off layer 

      Kube, Ralph; Garcia, Odd Erik; Theodorsen, Audun; Brunner, Dan; Kuang, Adam; LaBombard, Brian; Terry, Jim L. (Conference object; Konferansebidrag, 2017)
    • Blob shapes in the scrape-off layer: Comparison of measurements to simulations 

      Kube, Ralph; Garcia, Odd Erik; Theodorsen, Audun; Brunner, Dan; Kuang, Adam; LaBombard, Brian; Terry, Jim L. (Conference object; Konferansebidrag, 2017)
    • Adhesive free PVDF copolymer focused transducers for high frequency acoustic imaging 

      Habib, Anowarul; Wagle, Sanat; Melandsø, Frank (Conference object; Konferansebidrag, 2019)
      The present study has demonstrated to produce a reliable PVDF copolymer focused transducers from a layer-by-layer deposition method by engraving milled spherical cavies in a PEI polymer substrate. The proposed method which process P(VDF-TrFE) from the fluid phase, is adhesive-free in the sense that it does not require any additional adhesive layers for material binding. The transducer was acoustically ...
    • Dust Trajectory Calculations in the Inner Heliosphere and Circumstellar Debris Disks 

      Mann, Ingrid; Stamm, Johann Immanuel; Czechowski, Andrzej; Baumann, Carsten; Myrvang, Margaretha; Li, Aigen (Conference object; Konferansebidrag, 2018)
    • Subseasonal Predictions of Polar Low Activity Using a Hybrid Statistical-Dynamical Approach 

      Boyd, Kevin; Wang, Zhuo; Walsh, John; Stoll, Johannes Patrick (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-06-21)
      The subseasonal prediction of polar low (PL) activity is explored using a hybrid statistical-dynamical approach. A previously developed PL genesis potential index is paired with ECMWF reforecasts and forecasts to predict regional statistics of PL activity across the sub-Arctic. Regional PL activity is skillfully predicted in all regions at forecast ranges of up to a month. Additionally, the ...