Viser treff 2481-2500 av 5378

    • Multiproxy paleoceanographic study from the western Barents Sea reveals dramatic Younger Dryas onset followed by oscillatory warming trend 

      Łącka, Magdalena; Michalska, Danuta; Pawłowska, Joanna; Szymańska, Natalia; Szczuciński, Witold; Forwick, Matthias; Zajączkowski, Marek (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-09-24)
      The Younger Dryas (YD) is recognized as a cool period that began and ended abruptly during a time of general warming at the end of the last glacial. New multi-proxy data from a sediment gravity core from Storfjordrenna (western Barents Sea, 253 m water depth) reveals that the onset of the YD occurred as a single short-lived dramatic environment deterioration, whereas the subsequent warming was ...
    • Bringing optical nanoscopy to life - Super-resolution microscopy of living cells 

      Opstad, Ida Sundvor (Doctoral thesis; Doktorgradsavhandling, 2021-01-29)
      Microscopy is possibly the best tool we have to peer into the microscopic world to enhance our understanding of the usually invisible, but highly complex and vital events every moment taking place inside living cells. Microscopy is brilliant, but also has its physical constraints and technical limitations. Technical advances have in the last decade pushed optical microscopy past physical limits ...
    • Learning Nanoscale Motion Patterns of Vesicles in Living Cells 

      Sekh, Arif Ahmed; Opstad, Ida Sundvor; Birgisdottir, Åsa B.; Myrmel, Truls; Ahluwalia, Balpreet Singh; Agarwal, Krishna; Prasad, Dilip K. (Conference object; Konferansebidrag, 2020-08-05)
      Detecting and analyzing nanoscale motion patterns of vesicles, smaller than the microscope resolution (~250 nm), inside living biological cells is a challenging problem. State-of-the-art CV approaches based on detection, tracking, optical flow or deep learning perform poorly for this problem. We propose an integrative approach, built upon physics based simulations, nanoscopy algorithms, and shallow ...
    • Estimation of Blood Glucose Concentration During Endurance Sports 

      Sebastiani, Giovanni; Uteng, Stig; Godtliebsen, Fred; Polàk, Jan; Brož, Jan (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-07-21)
      In this paper, we describe a new statistical approach to estimate blood glucose concentration along time during endurance sports based on measurements of glucose concentration in subcutaneous interstitial tissue. The final goal is the monitoring of glucose concentration in blood to maximize performance in endurance sports. Blood glucose concentration control during and after aerobic physical ...
    • Seeing beyond the outcrop: Integration of ground-penetrating radar with digital outcrop models of a paleokarst system 

      Janocha, Julian; Smyrak-Sikora, Aleksandra; Senger, Kim; Birchall, Thomas (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-11-25)
      Paleokarst breccias are a common feature of sedimentary rift basins. The Billefjorden Trough in the High Arctic archipelago of Svalbard is an example of such a rift. Here the Carboniferous stratigraphy exhibits intervals of paleokarst breccias formed by gypsum dissolution. In this study we integrate digital outcrop models (DOMs) with a 2D ground penetrating radar (GPR) survey to extrapolate external ...
    • Oil-Spill-Response-Oriented Information Products Derived From a Rapid-Repeat Time Series of SAR Images 

      Espeseth, Martine; Jones, Cathleen; Benjamin, Holt; Brekke, Camilla; Skrunes, Stine (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-06-19)
      New quantitative and semiautomated methods for analyzing oil slick evolution using a time series of L-band synthetic aperture radar (SAR) images with short repeat time are developed and explored. In this study, two methods that are complementary in terms of identifying temporal changes within an oil slick are presented. The two methods reflect two ways of evaluating the oil slicks. The first method ...
    • Norway-Russia disaster diplomacy for Svalbard 

      Kelman, Ilan; Sydnes, Are K.; Duda, Patrizia Isabelle; Nikitina, Elena; Webersik, Christian (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-07-03)
      The Arctic is frequently framed as a region of disaster and conflict, as well as of opportunity and cooperation. Disaster diplomacy is one approach for examining how dealing with disasters might or might not affect conflict and cooperation, yet little work on Arctic disaster diplomacy has been completed, especially regarding specific bilateral relations. This paper contributes to filling in this gap ...
    • Smart Energy and power systems modelling: an IoT and Cyber-Physical Systems perspective, in the context of Energy Informatics 

      Bordin, Chiara; Håkansson, Anne; Mishra, Sambeet (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-10-02)
      This paper aims at identifying the key role of ”Smart Energy and Power Systems Modelling”, within the context of Energy Informatics. The main objective is to describe how the specific subject of ”Smart Energy and Power Systems Modelling” can give a key contribution within the novel domain of Energy Informatics, by successfully linking and integrating the different disciplines involved. First the ...
    • Predicting the suitability of lateritic soil type for low cost sustainable housing with image recognition and machine learning techniques 

      Olukan, Tuza Adeyemi; Chiou, Yu-Cheng; Chiu, Cheng-Hsiang; Lai, Chia-Yun; Santos Hernandez, Sergio; Chiesa, Matteo (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-01-10)
      From a sustainability point of view, laterites-compressed earth bricks (LCEB) are a promising substitute for building structures in place of the conventional concrete masonry units. On the other hand, techniques for identifying and classifying laterites soil for compressed earth bricks (CEB) production are still relying on direct human expertise or ‘experts’. Human experts exploit direct visual ...
    • Hierarchical Representation Learning in Graph Neural Networks with Node Decimation Pooling 

      Bianchi, Filippo Maria; Grattarola, Daniele; Livi, Lorenzo; Alippi, Cesare (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-12-31)
      In graph neural networks (GNNs), pooling operators compute local summaries of input graphs to capture their global properties, and they are fundamental for building deep GNNs that learn hierarchical representations. In this work, we propose the Node Decimation Pooling (NDP), a pooling operator for GNNs that generates coarser graphs while preserving the overall graph topology. During training, the ...
    • A polymatroid approach to generalized weights of rank metric codes 

      Ghorpade, Sudhir R; Johnsen, Trygve (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-09-15)
      We consider the notion of a (<i>q,m)</i>-polymatroid, due to Shiromoto, and the more general notion of (<i>q,m</i>)-demi-polymatroids, and show how generalized weights can be defined for them. Further, we establish a duality for these weights analogous to Wei duality for generalized Hamming weights of linear codes. The corresponding results of Ravagnani for Delsarte rank metric codes, and Martínez-Peñas ...
    • Robustness of SAR Sea Ice Type classification across incidence angles and seasons at L-band 

      Singha, Suman; Johansson, Malin; Doulgeris, Anthony Paul (Journal article; Tidsskriftartikkel, 2020-11-16)
      In recent years, space-borne synthetic aperture radar (SAR) polarimetry has become a valuable tool for sea ice type retrieval. L-band SAR has proven to be sensitive toward deformed sea ice and is complementary compared with operationally used C-band SAR for sea ice type classification during the early and advanced melt seasons. Here, we employ an artificial neural network (ANN)-based sea ice type ...
    • Relative generalized Hamming weights of affine Cartesian codes 

      Datta, Mrinmoy (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-03-10)
      We explicitly determine all the relative generalized Hamming weights of affine Cartesian codes using the notion of footprints and results from extremal combinatorics. This generalizes the previous works on the determination of relative generalized Hamming weights of Reed–Muller codes by Geil and Martin, as well as the determination of all the generalized Hamming weights of the affine Cartesian codes ...
    • Integrability via Geometry: Dispersionless Differential Equations in Three and Four Dimensions 

      Calderbank, David M. J.; Kruglikov, Boris (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-11-25)
      We prove that the existence of a dispersionless Lax pair with spectral parameter for a nondegenerate hyperbolic second order partial differential equation (PDE) is equivalent to the canonical conformal structure defined by the symbol being Einstein–Weyl on any solution in 3D, and self-dual on any solution in 4D. The first main ingredient in the proof is a characteristic property for dispersionless ...
    • Homogeneous Levi non-degenerate hypersurfaces in C3 

      Doubrov, Boris; Medvedev, Alexandr; The, Dennis (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-06-09)
      We classify all (locally) homogeneous Levi non-degenerate real hypersurfaces in C<sup>3</sup> with symmetry algebra of dimension ≥6.
    • Blow-ups and infinitesimal automorphisms of CR-manifolds 

      Kruglikov, Boris (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-03-07)
      For a real-analytic connected CR-hypersurface M of CR-dimension n⩾1 having a point of Levi-nondegeneracy the following alternative is demonstrated for its symmetry algebra s=s(M): (i) either dims=n2+4n+3 and M is spherical everywhere; (ii) or dims⩽n2+2n+2+δ2,n and in the case of equality M is spherical and has fixed signature of the Levi form in the complement to its Levi-degeneracy locus. A version ...
    • Pre-orogenic connection of the foreland domains of the Kaoko–Dom Feliciano–Gariep orogenic system 

      Percival, Jack James; Konopásek, Jiří; Eiesland, Ragnhild; Sláma, Jiří; Campos, Roberto Sacks de; Battisti, Matheus Ariel; Bitencourt, Maria de Fatima (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-12-30)
      Neoproterozoic metasedimentary rocks in the foreland domains of the Kaoko–Dom Feliciano–Gariep orogenic system record sedimentation from the breakup of Rodinia to the amalgamation of Gondwana, and thus provide ideal subjects for investigation of the mutual pre-orogenic positions of rifted margins of the African and South American cratonic blocks. U–Pb isotopic dating of zircon in the Brusque Complex ...
    • Life in Anticipation of Wind Power Development: Three Cases from Coastal Norway 

      Staupe-Delgado, Reidar; Coombes, Philip R. (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-12-21)
      Wind power development, whilst welcomed by many as a potentially green source of energy, also gives rise to considerable local resistance. Drawing on three case studies from coastal Norway (Frøya, Haramsøy, and Egersund), the present article sets out to reflect on life in anticipation of wind power development. Reflecting on the nature of life in anticipation of undesired wind power developments, ...
    • Comparing wavelet and Fourier perspectives on the decomposition of meridional energy transport into synoptic and planetary components 

      Heiskanen, Tuomas Ilkka Henrikki; Graversen, Rune Grand; Rydsaa, Johanne Hope; Isachsen, Pål Erik (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-05-04)
      The Arctic region shows some of the world's most significant signs of climate change; for instance, a negative trend in summer sea‐ice cover of around 15% per decade and Arctic amplified surface‐air warming that is three times the global average. The atmospheric energy transport plays an important role in the Arctic climate. Recently a Fourier‐based method for studying the atmospheric energy transport ...
    • 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 ...