Now showing items 421-440 of 1062

    • Numerical Solution of the Parametric Diffusion Equation by Deep Neural Networks 

      Geist, Moritz; Petersen, Philipp; Raslan, Mones; Schneider, Reinhold; Kutyniok, Gitta Astrid Hildegard (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-06-05)
      We perform a comprehensive numerical study of the effect of approximation-theoretical results for neural networks on practical learning problems in the context of numerical analysis. As the underlying model, we study the machine-learning-based solution of parametric partial differential equations. Here, approximation theory for fully-connected neural networks predicts that the performance of the ...
    • Quantification of the NA dependent change of shape in the image formation of a z-polarised fluorescent molecule using vectorial diffraction simulations 

      Ströhl, Florian; Bruggeman, Ezra; Rowlands, Christopher; Wolfson, Deanna; Ahluwalia, Balpreet Singh (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-01-19)
      The point spread function of a fixed fluorophore with its dipole axis colinear to the optical axis appears donut-shaped when seen through a microscope, and its light distribution in the pupil plane is radially polarized. Yet other techniques, such as photolithography, report that this same light distribution in the pupil plane appears as a solid spot. How can this same distribution lead to a spot ...
    • Estimating Radiative Forcing With a Nonconstant Feedback Parameter and Linear Response 

      Fredriksen, Hege-Beate; Rugenstein, Maria A.A.; Graversen, Rune (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-12-06)
      A new algorithm is proposed for estimating time-evolving global forcing in climate models. The method is a further development of the work of Forster et al. (2013), <a href=https://doi.org/10.1002/jgrd.50174>https://doi.org/10.1002/jgrd.50174</a>, taking into account the non-constancy of the global feedbacks. We assume that the non-constancy of this global feedback can be explained as a time-scale ...
    • Hydration dynamics and the future of small-amplitude afm imaging in air 

      Santos Hernandez, Sergio; Olukan, Tuza Adeyemi; Lai, Chia-Yun; Chiesa, Matteo (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-11-23)
      Here, we discuss the effects that the dynamics of the hydration layer and other variables, such as the tip radius, have on the availability of imaging regimes in dynamic AFM—including multifrequency AFM. Since small amplitudes are required for high-resolution imaging, we focus on these cases. It is possible to fully immerse a sharp tip under the hydration layer and image with amplitudes similar to ...
    • Unification of sparse Bayesian learning algorithms for electromagnetic brain imaging with the majorization minimization framework 

      Hashemi, Ali; Cai, Chang; Kutyniok, Gitta Astrid Hildegard; Müller, Klaus R.; Nagarajan, Srikantan S.; Haufe, Stefan (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-10-01)
      Methods for electro- or magnetoencephalography (EEG/MEG) based brain source imaging (BSI) using sparse Bayesian learning (SBL) have been demonstrated to achieve excellent performance in situations with low numbers of distinct active sources, such as event-related designs. This paper extends the theory and practice of SBL in three important ways. First, we reformulate three existing SBL algorithms ...
    • Linking sea ice deformation to ice thickness redistribution using high-resolution satellite and airborne observations 

      Von Albedyll, Luisa; Haas, Christian; Dierking, Wolfgang Fritz Otto (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-05-04)
      An unusual, large, latent-heat polynya opened and then closed by freezing and convergence north of Greenland’s coast in late winter 2018. The closing presented a natural but well-constrained full-scale ice deformation experiment. We observed the closing of and deformation within the polynya with satellite synthetic-aperture radar (SAR) imagery and measured the accumulated effects of dynamic ...
    • Joint optimization of an autoencoder for clustering and embedding 

      Boubekki, Ahcene; Kampffmeyer, Michael; Brefeld, Ulf; Jenssen, Robert (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-06-21)
      Deep embedded clustering has become a dominating approach to unsupervised categorization of objects with deep neural networks. The optimization of the most popular methods alternates between the training of a deep autoencoder and a k-means clustering of the autoencoder’s embedding. The diachronic setting, however, prevents the former to beneft from valuable information acquired by the latter. In ...
    • seMLP: Self-Evolving Multi-Layer Perceptron in Stock Trading Decision Making 

      Jun, S.W; Sekh, Arif Ahmed; Quek, Chai; Prasad, Dilip K. (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-02-24)
      There is a growing interest in automatic crafting of neural network architectures as opposed to expert tuning to fnd the best architecture. On the other hand, the problem of stock trading is considered one of the most dynamic systems that heavily depends on complex trends of the individual company. This paper proposes a novel self-evolving neural network system called self-evolving Multi-Layer ...
    • Revealing the Quasi-Periodic Crystallographic Structure of Self-Assembled SnTiS3 Misfit Compound 

      Rajput, Nitul S.; Baik, Hionsuck; Lu, Jin-You; Tamalampudi, Srinivasa Reddy; Sankar, Raman; Al Ghaferi, Amal; Chiesa, Matteo (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-04-28)
      Chemical vapor transport synthesis of SnTiS3 yields a self-assembled heterostructure of two distinct constituent materials, the semiconductor SnS and the semimetal TiS2. The misfit layer compound, although thermodynamically stable, is structurally complex, and precise understanding of the structure is necessary for designing nanoengineered heterojunction compound devices or for theoretical studies. ...
    • Determination of the Azimuthal Extent of Coherent E-Region Scatter Using the ICEBEAR Linear Receiver Array 

      Huyghebaert, Devin Ray; McWilliams, Kathryn A.; Hussey, Glenn; Galeschuk, Draven; Chau, Jorge L.; Vierinen, Juha (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-03-07)
      The Ionospheric Continuous-wave E-region Bistatic Experimental Auroral Radar (ICEBEAR) is a VHF coherent scatter radar that operates with a field-of-view centered on 58°N, 106°W and measures characteristics of ionospheric E-region plasma density irregularities. The initial operations of ICEBEAR utilized a wavelength-spaced linear receiving array to determine the angle of arrival of the ionospheric ...
    • Investigating the Ubiquitous Presence of Nanometric Water Films on Surfaces 

      Santos Hernandez, Sergio; Amadei, Carlo Alberto; Lai, Chia-Yun; Olukan, Tuza Adeyemi; Lu, Jin-You; Font, Josep; Barcons, Victor; Verdaguer, Albert; Chiesa, Matteo (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-06-25)
      When we speak of nanometric water films on surfaces we are speaking about a truly ubiquitous phenomenon in nature. All surfaces exposed to ambient conditions are covered by a thin film of water that affects or mediates surface chemistry, general physical-chemical processes on surfaces, and even solid–solid interactions. We have investigated this phenomenon for over a decade by exploiting dynamic ...
    • Improved Arctic Sea Ice Freeboard Retrieval From Satellite Altimetry Using Optimized Sea Surface Decorrelation Scales 

      Landy, Jack Christopher; Bouffard, Jerome; Wilson, Chris; Rynders, Stefanie; Aksenov, Yevgeny; Tsamados, Michel (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-11-18)
      A growing number of studies are concluding that the resilience of the Arctic sea ice cover in a warming climate is essentially controlled by its thickness. Satellite radar and laser altimeters have allowed us to routinely monitor sea ice thickness across most of the Arctic Ocean for several decades. However, a key uncertainty remaining in the sea ice thickness retrieval is the error on the sea surface ...
    • The computational complexity of understanding binary classifier decisions 

      Wäldchen, Stephan; Macdonald, Jan; Hauch, Sascha; Kutyniok, Gitta Astrid Hildegard (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-01-21)
      For a d-ary Boolean function Φ: {0, 1}<sup>d</sup> → {0, 1} and an assignment to its variables x = (x<sub>1</sub>, x<sub>2</sub>, . . . , x<sub>d</sub>) we consider the problem of finding those subsets of the variables that are sufficient to determine the function value with a given probability δ. This is motivated by the task of interpreting predictions of binary classifiers described as Boolean ...
    • Multimodal on-chip nanoscopy and quantitative phase imaging reveals the nanoscale morphology of liver sinusoidal endothelial cells 

      Butola, Ankit; Coucheron, David Andre; Szafranska, Karolina; Ahmad, Azeem; Mao, Hong; Tinguely, Jean-Claude; McCourt, Peter Anthony; Paramasivam, Senthilkumaran; Mehta, Dalip Singh; Agarwal, Krishna; Ahluwalia, Balpreet Singh (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-11-23)
      Visualization of three-dimensional (3D) morphological changes in the subcellular structures of a biological specimen is a major challenge in life science. Here, we present an integrated chip-based optical nanoscopy combined with quantitative phase microscopy (QPM) to obtain 3D morphology of liver sinusoidal endothelial cells (LSEC). LSEC have unique morphology with small nanopores (50-300 nm in ...
    • First Studies of Mesosphere and Lower Thermosphere Dynamics Using a Multistatic Specular Meteor Radar Network Over Southern Patagonia 

      Conte, J. F.; Chau, Jorge L.; Urco, Juan M.; Latteck, Ralph; Vierinen, Juha; Salvador, Jacobo (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-01-18)
      This paper presents for the first time results on winds, tides, gradients of horizontal winds, and momentum fluxes at mesosphere and lower thermosphere altitudes over southern Patagonia, one of the most dynamically active regions in the world. For this purpose, measurements provided by SIMONe Argentina are investigated. SIMONe Argentina is a novel multistatic specular meteor radar system ...
    • Physics-based machine learning for subcellular segmentation in living cells 

      Sekh, Arif Ahmed; Opstad, Ida Sundvor; Godtliebsen, Gustav; Birgisdottir, Åsa Birna; Ahluwalia, Balpreet Singh; Agarwal, Krishna; Prasad, Dilip K. (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-12-15)
      Segmenting subcellular structures in living cells from fluorescence microscope images is a ground truth (GT)-deficient problem. The microscopes’ three-dimensional blurring function, finite optical resolution due to light diffraction, finite pixel resolution and the complex morphological manifestations of the structures all contribute to GT-hardness. Unsupervised segmentation approaches are quite ...
    • Multiobjective optimization of a hybrid wind/solar battery energy system in the Arctic 

      Nguyen, Tuan Thanh; Boström, Tobias Kristoffer (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-04-30)
      This paper presents an optimal design of a hybrid wind turbine/PV/battery energy system for a household application using a multiobjective optimization approach, namely, particle swarm optimization (PSO). The ultimately optimal component selection of the hybrid renewable energy system (HRES) is suggested by comprehensively investigating the effects of various factors on the cost-reliability relation, ...
    • Multiresolution Dynamic Mode Decomposition (mrDMD) of Elastic Waves for Damage Localisation in Piezoelectric Ceramic 

      Kalimullah, Nur MM; Shelke, Amit; Habib, Anowarul (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-08-27)
      The performance of piezoelectric sensors deteriorated due to the presence of defect, delamination, and corrosion that needed to be diagnosed for the effective implementation of the structural health monitoring (SHM) framework. A novel experimental approach based on Coulomb coupling is devised to visualise the interaction of ultrasonic waves with microscale defects in the Lead Zirconate Titanate ...
    • Detecting and Interpreting Faults in Vulnerable Power Grids With Machine Learning 

      Chiesa, Matteo; Bianchi, Filippo Maria; Eikeland, Odin Foldvik; Holmstrand, Inga Setså; Bakkejord, Sigurd (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-11-10)
      Unscheduled power disturbances cause severe consequences both for customers and grid operators. To defend against such events, it is necessary to identify the causes of interruptions in the power distribution network. In this work, we focus on the power grid of a Norwegian community in the Arctic that experiences several faults whose sources are unknown. First, we construct a data set consisting ...
    • Electron Density Depletion Region Observed in the Polar Cap Ionosphere 

      Bjoland, Lindis Merete; Ogawa, Y.; Løvhaug, Unni Pia; Lorentzen, Dag Arne; Hatch, Spencer Mark; Oksavik, Kjellmar (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-12-16)
      This paper presents and discusses electron density depletion regions observed with the incoherent scatter EISCAT Svalbard Radar (ESR) located at 75.43°N geomagnetic latitude. The data include several decades of measurements, which make them suitable for studying statistical features and characteristics of the ionospheric parameters. Here we focus on the electron density depletions and their dependence ...