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  • 1.
    Abdulle, Assyr
    et al.
    Ecole Polytech Fed Lausanne, Inst Math, ANMC, Stn 8, Lausanne, Switzerland..
    Arjmand, Doghonay
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis. Ecole Polytech Fed Lausanne, Inst Math, ANMC, Stn 8, Lausanne, Switzerland..
    Paganoni, Edoardo
    Ecole Polytech Fed Lausanne, Inst Math, ANMC, Stn 8, Lausanne, Switzerland..
    AN ELLIPTIC LOCAL PROBLEM WITH EXPONENTIAL DECAY OF THE RESONANCE ERROR FOR NUMERICAL HOMOGENIZATION2023In: Multiscale Modeling & simulation, ISSN 1540-3459, E-ISSN 1540-3467, Vol. 21, no 2, p. 513-541Article in journal (Refereed)
    Abstract [en]

    Numerical multiscale methods usually rely on some coupling between a macroscopic and a microscopic model. The macroscopic model is incomplete as effective quantities, such as the homogenized material coefficients or fluxes, are missing in the model. These effective data need to be computed by running local microscale simulations followed by a local averaging of the microscopic information. Motivated by the classical homogenization theory, it is a common practice to use local elliptic cell problems for computing the missing homogenized coefficients in the macro model. Such a consideration results in a first order error O(E/8), where E represents the wavelength of the microscale variations and 8 is the size of the microscopic simulation boxes. This error, called ``resonance error,"" originates from the boundary conditions used in the microproblem and typically dominates all other errors in a multiscale numerical method. Optimal decay of the resonance error remains an open problem, although several interesting approaches reducing the effect of the boundary have been proposed over the last two decades. In this paper, as an attempt to resolve this problem, we propose a computationally efficient, fully elliptic approach with exponential decay of the resonance error.

  • 2. Abel, John H.
    et al.
    Drawert, Brian
    Hellander, Andreas
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Petzold, Linda R.
    GillesPy: A Python package for stochastic model building and simulation2016In: IEEE Life Sciences Letters, E-ISSN 2332-7685, Vol. 2, p. 35-38Article in journal (Refereed)
  • 3.
    Abrahamsson, Andreas
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing.
    Using Function as a Service for Dynamic Application Scaling in the Cloud2018Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Function as a Service is a new addition to cloud services that allow a user to execute code in form of a function, in the cloud. All underlying complexity is handled by the cloud provider and the user only pay per use. Cloud services have been growing significantly over the past years and many companies want to take advantages of the benefits of the cloud. The cloud services deliver computing resources as a service over a network connection, often by the Internet. To use the benefit of the cloud, one can not just move an application to the cloud and think that it will solve itself. First of all, an application needs to be optimized to be able to take advantages of the cloud. Therefore, together with Tieto, a microservice architecture have been the main architectural pattern when Function as a Service has been evaluated. A major problem with applications, both application built with a monolithic and microservice architecture, is to handle great amounts of information flows. An application may have scaling issues when an information flow becomes too large.

    A person using Function as a Service does not have to buy, rent or maintain their own servers. However, Function as a Service has a certain memory and runtime restrictions, so an entire application cannot be applied to a Function as a Service. This thesis examines the possibility of using Function as a Service in different architectural environments and estimating the cost of it. Function as a Service is a new addition to cloud services, so cloud providers are also compared and evaluated in terms of the Function as a Service functionality. Function as a Service has been tested directly on various

    cloud platforms and even developed and executed locally, encapsulated in containers. The results show that Function as a Service is a good complement to an application architecture. The results also show that Function as a Service is highly flexible and cost-effective, and it is advantageous compared to physical servers and Virtual Machines. Depending on how a function is built, the developer can lower the cost even more by choosing the cloud supplier that fits best for their use. With the flexibility of Function as a Service, applications can handle greater information flow without bottlenecks in the infrastructure and therefore, becomes more efficient and cost-effective. 

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  • 4.
    Abrahamsson, Andreas
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing.
    Pettersson, Rasmus
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing.
    Smoothing of initial conditions for high order approximations in option pricing2016Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    In this article the Finite Difference method is used to solve the Black Scholes equation. A second order and fourth order accurate scheme is implemented in space and evaluated. The scheme is then tried for different initial conditions. First the discontinuous pay off function of a European Call option is used. Due to the nonsmooth charac- teristics of the chosen initial conditions both schemes show an order of two. Next, the analytical solution to the Black Scholes is used when t=T/2. In this case, with a smooth initial condition, the fourth order scheme shows an order of four. Finally, the initial nonsmooth pay off function is modified by smoothing. Also in this case, the fourth order method shows an order of convergence of four. 

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  • 5. Aceto, Lidia
    et al.
    Mazza, Mariarosa
    Serra-Capizzano, Stefano
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Fractional Laplace operator in two dimensions, approximating matrices, and related spectral analysis2020In: Calcolo, ISSN 0008-0624, E-ISSN 1126-5434, Vol. 57, article id 27Article in journal (Refereed)
  • 6.
    Adler, Jonas
    et al.
    KTH Royal Inst Technol, Dept Math, S-10044 Stockholm, Sweden.;DeepMind, 6 Pancras Sq, London N1C 4AG, England..
    Lunz, Sebastian
    Univ Cambridge, Ctr Math Sci, Cambridge CB3 0WA, England..
    Verdier, Olivier
    KTH Royal Inst Technol, Dept Math, S-10044 Stockholm, Sweden.;Western Norway Univ Appl Sci, Dept Comp Math & Phys, Bergen, Norway..
    Schonlieb, Carola-Bibiane
    Univ Cambridge, Ctr Math Sci, Cambridge CB3 0WA, England..
    Öktem, Ozan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. KTH Royal Inst Technol, Dept Math, S-10044 Stockholm, Sweden.
    Task adapted reconstruction for inverse problems2022In: Inverse Problems, ISSN 0266-5611, E-ISSN 1361-6420, Vol. 38, no 7, article id 075006Article in journal (Refereed)
    Abstract [en]

    The paper considers the problem of performing a post-processing task defined on a model parameter that is only observed indirectly through noisy data in an ill-posed inverse problem. A key aspect is to formalize the steps of reconstruction and post-processing as appropriate estimators (non-randomized decision rules) in statistical estimation problems. The implementation makes use of (deep) neural networks to provide a differentiable parametrization of the family of estimators for both steps. These networks are combined and jointly trained against suitable supervised training data in order to minimize a joint differentiable loss function, resulting in an end-to-end task adapted reconstruction method. The suggested framework is generic, yet adaptable, with a plug-and-play structure for adjusting both the inverse problem and the post-processing task at hand. More precisely, the data model (forward operator and statistical model of the noise) associated with the inverse problem is exchangeable, e.g., by using neural network architecture given by a learned iterative method. Furthermore, any post-processing that can be encoded as a trainable neural network can be used. The approach is demonstrated on joint tomographic image reconstruction, classification and joint tomographic image reconstruction segmentation.

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  • 7. Adriani, Andrea
    et al.
    Bianchi, Davide
    Ferrari, Paola
    Serra-Capizzano, Stefano
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Asymptotic spectra of large (grid) graphs with a uniform local structure, Part II: Numerical applications2024In: Journal of Computational and Applied Mathematics, ISSN 0377-0427, E-ISSN 1879-1778, Vol. 437, article id 115461Article in journal (Refereed)
    Abstract [en]

    In the current work we are concerned with sequences of graphs having a grid geometry, with a uniform local structure in a bounded domain Ω ⊂ Rd , d ≥ 1. When Ω = [0, 1], such graphs include the standard Toeplitz graphs and, for Ω = [0,1]d, the considered class includes d-level Toeplitz graphs. In the general case, the underlying sequence of adjacency matrices has a canonical eigenvalue distribution, in the Weyl sense, and it has been shown in the theoretical part of this work that we can associate to it a symbol f. The knowledge of the symbol and of its basic analytical features provides key information on the eigenvalue structure in terms of localization, spectral gap, clustering, and global distribution. In the present paper, many different applications are discussed and various numerical examples are presented in order to underline the practical use of the developed theory. Tests and applications are mainly obtained from the approximation of differential operators via numerical schemes such as Finite Differences, Finite Elements, and Isogeometric Analysis. Moreover, we show that more applications can be taken into account, since the results presented here can be applied as well to study the spectral properties of adjacency matrices and Laplacian operators of general large graphs and networks, whenever the involved matrices enjoy a uniform local structure.

  • 8. Adriani, Andrea
    et al.
    Bianchi, Davide
    Serra-Capizzano, Stefano
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Asymptotic Spectra of Large (Grid) Graphs with a Uniform Local Structure (Part I): Theory2020In: Milan Journal of Mathematics, ISSN 1424-9286, E-ISSN 1424-9294, Vol. 88, no 2, p. 409-454Article in journal (Refereed)
    Abstract [en]

    We are mainly concerned with sequences of graphs having a grid geometry, with a uniform local structure in a bounded domain omega subset of Rd, d >= 1. When omega=[0,1] , such graphs include the standard Toeplitz graphs and, for omega=[0,1](d), the considered class includesd-level Toeplitz graphs. In the general case, the underlying sequence of adjacency matrices has a canonical eigenvalue distribution, in the Weyl sense, and we show that we can associate to it a symbol f. The knowledge of the symbol and of its basic analytical features provides many information on the eigenvalue structure, of localization, spectral gap, clustering, and distribution type.

    Few generalizations are also considered in connection with the notion of generalized locally Toeplitz sequences and applications are discussed, stemming e.g. from the approximation of differential operators via numerical schemes. Nevertheless, more applications can be taken into account, since the results presented here can be applied as well to study the spectral properties of adjacency matrices and Laplacian operators of general large graphs and networks

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  • 9. Adriani, Andrea
    et al.
    Semplice, Matteo
    Serra, Stefano
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Generalized Locally Toeplitz matrix-sequences and approximated PDEs on submanifolds: the flat case2023In: Linear and multilinear algebra, ISSN 0308-1087, E-ISSN 1563-5139, p. 1-23Article in journal (Refereed)
    Abstract [en]

    In the present paper, we consider a class of elliptic partial differential equations with Dirichlet boundary conditions where the operator is the Laplace-Beltrami operator Δ over   Ω¯, Ω being an open and bounded submanifold of   Rν,   ν=2,3. We will take into consideration the classical   Pk Finite Elements, in the case of Friedrichs-Keller triangulations, leading to sequences of matrices of increasing size. We are interested in carrying out a spectral analysis of the resulting matrix-sequences. The tools for our derivations are mainly taken from the Toeplitz technology and from the rather new theory of Generalized Locally Toeplitz (GLT) matrix-sequences. The current contribution is only quite an initial step, where a general programme is provided, with partial answers leading to further open questions: indeed the analysis is performed on special flat submanifolds and hence there is room for wide generalizations, with a final picture which is still unclear with respect to, e.g. the role of the submanifold curvature.

  • 10.
    Ahlkrona, Josefin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Computational Ice Sheet Dynamics: Error control and efficiency2016Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Ice sheets, such as the Greenland Ice Sheet or Antarctic Ice Sheet, have a fundamental impact on landscape formation, the global climate system, and on sea level rise. The slow, creeping flow of ice can be represented by a non-linear version of the Stokes equations, which treat ice as a non-Newtonian, viscous fluid. Large spatial domains combined with long time spans and complexities such as a non-linear rheology, make ice sheet simulations computationally challenging. The topic of this thesis is the efficiency and error control of large simulations, both in the sense of mathematical modelling and numerical algorithms. In the first part of the thesis, approximative models based on perturbation expansions are studied. Due to a thick boundary layer near the ice surface, some classical assumptions are inaccurate and the higher order model called the Second Order Shallow Ice Approximation (SOSIA) yields large errors. In the second part of the thesis, the Ice Sheet Coupled Approximation Level (ISCAL) method is developed and implemented into the finite element ice sheet model Elmer/Ice. The ISCAL method combines the Shallow Ice Approximation (SIA) and Shelfy Stream Approximation (SSA) with the full Stokes model, such that the Stokes equations are only solved in areas where both the SIA and SSA is inaccurate. Where and when the SIA and SSA is applicable is decided automatically and dynamically based on estimates of the modeling error. The ISCAL method provides a significant speed-up compared to the Stokes model. The third contribution of this thesis is the introduction of Radial Basis Function (RBF) methods in glaciology. Advantages of RBF methods in comparison to finite element methods or finite difference methods are demonstrated.

    List of papers
    1. A numerical study of scaling relations for non-Newtonian thin-film flows with applications in ice sheet modelling
    Open this publication in new window or tab >>A numerical study of scaling relations for non-Newtonian thin-film flows with applications in ice sheet modelling
    2013 (English)In: Quarterly Journal of Mechanics and Applied Mathematics, ISSN 0033-5614, E-ISSN 1464-3855, Vol. 66, p. 417-435Article in journal (Refereed) Published
    National Category
    Computational Mathematics
    Identifiers
    urn:nbn:se:uu:diva-205727 (URN)10.1093/qjmam/hbt009 (DOI)000327457200001 ()
    Projects
    eSSENCE
    Available from: 2013-08-09 Created: 2013-08-22 Last updated: 2017-12-06Bibliographically approved
    2. Accuracy of the zeroth- and second-order shallow-ice approximation: numerical and theoretical results
    Open this publication in new window or tab >>Accuracy of the zeroth- and second-order shallow-ice approximation: numerical and theoretical results
    2013 (English)In: Geoscientific Model Development, ISSN 1991-959X, E-ISSN 1991-9603, Vol. 6, p. 2135-2152Article in journal (Refereed) Published
    National Category
    Computational Mathematics
    Identifiers
    urn:nbn:se:uu:diva-213571 (URN)10.5194/gmd-6-2135-2013 (DOI)000329050500017 ()
    Projects
    eSSENCE
    Available from: 2013-12-19 Created: 2013-12-28 Last updated: 2017-12-06Bibliographically approved
    3. Dynamically coupling the non-linear Stokes equations with the shallow ice approximation in glaciology: Description and first applications of the ISCAL method
    Open this publication in new window or tab >>Dynamically coupling the non-linear Stokes equations with the shallow ice approximation in glaciology: Description and first applications of the ISCAL method
    2016 (English)In: Journal of Computational Physics, ISSN 0021-9991, E-ISSN 1090-2716, Vol. 308, p. 1-19Article in journal (Refereed) Published
    National Category
    Computational Mathematics
    Identifiers
    urn:nbn:se:uu:diva-269822 (URN)10.1016/j.jcp.2015.12.025 (DOI)000369086700001 ()
    Projects
    eSSENCE
    Available from: 2015-12-17 Created: 2015-12-18 Last updated: 2017-12-01Bibliographically approved
    4. The ISCAL method and the grounding line: Combining the Stokes equations with the Shallow Ice Approximation and Shelfy Stream Approximation
    Open this publication in new window or tab >>The ISCAL method and the grounding line: Combining the Stokes equations with the Shallow Ice Approximation and Shelfy Stream Approximation
    2016 (English)Report (Other academic)
    Series
    Technical report / Department of Information Technology, Uppsala University, ISSN 1404-3203 ; 2016-006
    National Category
    Computational Mathematics
    Identifiers
    urn:nbn:se:uu:diva-283438 (URN)
    Projects
    eSSENCE
    Available from: 2016-04-19 Created: 2016-04-13 Last updated: 2016-05-16Bibliographically approved
    5. A meshfree approach to non-Newtonian free surface ice flow: Application to the Haut Glacier d'Arolla
    Open this publication in new window or tab >>A meshfree approach to non-Newtonian free surface ice flow: Application to the Haut Glacier d'Arolla
    2016 (English)Report (Other academic)
    Series
    Technical report / Department of Information Technology, Uppsala University, ISSN 1404-3203 ; 2016-005
    National Category
    Computational Mathematics
    Identifiers
    urn:nbn:se:uu:diva-283437 (URN)
    Projects
    eSSENCE
    Available from: 2016-04-19 Created: 2016-04-13 Last updated: 2016-05-16Bibliographically approved
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  • 11.
    Ahlkrona, Josefin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    The ISCAL method and the grounding line: Combining the Stokes equations with the Shallow Ice Approximation and Shelfy Stream Approximation2016Report (Other academic)
  • 12.
    Ahlkrona, Josefin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Kirchner, Nina
    Lötstedt, Per
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    A numerical study of scaling relations for non-Newtonian thin-film flows with applications in ice sheet modelling2013In: Quarterly Journal of Mechanics and Applied Mathematics, ISSN 0033-5614, E-ISSN 1464-3855, Vol. 66, p. 417-435Article in journal (Refereed)
  • 13.
    Ahlkrona, Josefin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Kirchner, Nina
    Lötstedt, Per
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    A numerical study of the validity of Shallow Ice Approximations2012Report (Other academic)
  • 14.
    Ahlkrona, Josefin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Kirchner, Nina
    Lötstedt, Per
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Accuracy of the zeroth and second order shallow ice approximation: numerical and theoretical results2013In: Geoscientific Model Development Discussions, ISSN 1991-9611, E-ISSN 1991-962X, Vol. 6, p. 4281-4325Article in journal (Other academic)
  • 15.
    Ahlkrona, Josefin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Kirchner, Nina
    Lötstedt, Per
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Accuracy of the zeroth- and second-order shallow-ice approximation: numerical and theoretical results2013In: Geoscientific Model Development, ISSN 1991-959X, E-ISSN 1991-9603, Vol. 6, p. 2135-2152Article in journal (Refereed)
  • 16.
    Ahlkrona, Josefin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Lötstedt, Per
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Kirchner, Nina
    Zwinger, Thomas
    Dynamically coupling the non-linear Stokes equations with the shallow ice approximation in glaciology: Description and first applications of the ISCAL method2016In: Journal of Computational Physics, ISSN 0021-9991, E-ISSN 1090-2716, Vol. 308, p. 1-19Article in journal (Refereed)
    Download full text (pdf)
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  • 17.
    Ahlkrona, Josefin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Shcherbakov, Victor
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    A meshfree approach to non-Newtonian free surface ice flow: Application to the Haut Glacier d'Arolla2017In: Journal of Computational Physics, ISSN 0021-9991, E-ISSN 1090-2716, Vol. 330, p. 633-649Article in journal (Refereed)
  • 18.
    Ahlkrona, Josefin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Shcherbakov, Victor
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    A meshfree approach to non-Newtonian free surface ice flow: Application to the Haut Glacier d'Arolla2016Report (Other academic)
  • 19. Ahmad, Fayyaz
    et al.
    Al-Aidarous, Eman S.
    Alrehaili, Dina A.
    Ekström, Sven-Erik
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Furci, Isabella
    Serra-Capizzano, Stefano
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Are the eigenvalues of preconditioned banded symmetric Toeplitz matrices known in almost closed form?2018In: Numerical Algorithms, ISSN 1017-1398, E-ISSN 1572-9265, Vol. 78, p. 867-893Article in journal (Refereed)
  • 20. Ahmad, Fayyaz
    et al.
    Al-Aidarous, Eman S.
    Alrehaili, Dina A.
    Ekström, Sven-Erik
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Furci, Isabella
    Serra-Capizzano, Stefano
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Are the eigenvalues of preconditioned banded symmetric Toeplitz matrices known in almost closed form?2017Report (Other academic)
  • 21. Ahmad, Fayyaz
    et al.
    Serra-Capizzano, Stefano
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Zaka Ullah, Malik
    Al-Fhaid, A. Saleh
    A family of iterative methods for solving systems of nonlinear equations having unknown multiplicity2016In: Algorithms, E-ISSN 1999-4893, Vol. 9, p. 5:1-10, article id 5Article in journal (Refereed)
  • 22. Ahmad, Fayyaz
    et al.
    Soleymani, Fazlollah
    Khaksar Haghani, Farhad
    Serra-Capizzano, Stefano
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Higher order derivative-free iterative methods with and without memory for systems of nonlinear equations2017In: Applied Mathematics and Computation, ISSN 0096-3003, E-ISSN 1873-5649, Vol. 314, p. 199-211Article in journal (Refereed)
  • 23.
    Ahmad, Masood
    et al.
    University of Engineering and Technology, Peshawar, Pakistan.
    Islam, Siraj-ul
    University of Engineering and Technology, Peshawar, Pakistan.
    Larsson, Elisabeth
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Local meshless methods for second order elliptic interface problems with sharp corners2020In: Journal of Computational Physics, ISSN 0021-9991, E-ISSN 1090-2716, Vol. 416, article id 109500Article in journal (Refereed)
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  • 24.
    Aho, Milja
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing.
    Optimisation of Ad-hoc analysis of an OLAP cube using SparkSQL2017Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    An Online Analytical Processing (OLAP) cube is a way to represent a multidimensional database. The multidimensional database often uses a star schema and populates it with the data from a relational database. The purpose of using an OLAP cube is usually to find valuable insights in the data like trends or unexpected data and is therefore often used within Business intelligence (BI). Mondrian is a tool that handles OLAP cubes that uses the query language MultiDimensional eXpressions (MDX) and translates it to SQL queries. Apache Kylin is an engine that can be used with Apache Hadoop to create and query OLAP cubes with an SQL interface. This thesis investigates whether the engine Apache Spark running on a Hadoop cluster is suitable for analysing OLAP cubes and what performance that can be expected. The Star Schema Benchmark (SSB) has been used to provide Ad-Hoc queries and to create a large database containing over 1.2 billion rows. This database was created in a cluster in the Omicron office consisting of five worker nodes and one master node. Queries were then sent to the database using Mondrian integrated into the BI platform Pentaho. Amazon Web Services (AWS) has also been used to create clusters with 3, 6 and 15 slaves to see how the performance scales. Creating a cube in Apache Kylin on the Omicron cluster was also tried, but was not possible due to the cluster running out of memory. The results show that it took between 8.2 to 11.9 minutes to run the MDX queries on the Omicron cluster. On both the Omicron cluster and the AWS cluster, the SQL queries ran faster than the MDX queries. The AWS cluster ran the queries faster than the Omicron cluster, even though fewer nodes were used. It was also noted that the AWS cluster did not scale linearly, neither for the MDX nor the SQL queries.

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  • 25.
    Ait-Mlouk, Addi
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Alawadi, Sadi
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Toor, Salman
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Hellander, Andreas
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    FedQAS: Privacy-Aware Machine Reading Comprehension with Federated Learning2022In: Applied Sciences, E-ISSN 2076-3417, Vol. 12, no 6, article id 3130Article in journal (Refereed)
    Abstract [en]

    Machine reading comprehension (MRC) of text data is a challenging task in Natural Language Processing (NLP), with a lot of ongoing research fueled by the release of the Stanford Question Answering Dataset (SQuAD) and Conversational Question Answering (CoQA). It is considered to be an effort to teach computers how to "understand" a text, and then to be able to answer questions about it using deep learning. However, until now, large-scale training on private text data and knowledge sharing has been missing for this NLP task. Hence, we present FedQAS, a privacy-preserving machine reading system capable of leveraging large-scale private data without the need to pool those datasets in a central location. The proposed approach combines transformer models and federated learning technologies. The system is developed using the FEDn framework and deployed as a proof-of-concept alliance initiative. FedQAS is flexible, language-agnostic, and allows intuitive participation and execution of local model training. In addition, we present the architecture and implementation of the system, as well as provide a reference evaluation based on the SQuAD dataset, to showcase how it overcomes data privacy issues and enables knowledge sharing between alliance members in a Federated learning setting.

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  • 26. Akbari, Hesam
    et al.
    Sadiq, Muhammad Tariq
    Jafari, Nastaran
    Too, Jingwei
    Mikaeilvand, Nasser
    Cicone, Antonio
    Serra-Capizzano, Stefano
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis. Department of Science and High Technology, Division of Mathematics, University of Insubria, Como, Italy.
    Recognizing seizure using Poincaré plot of EEG signals and graphical features in DWT domain2023In: Bratislava Medical Journal, ISSN 0006-9248, E-ISSN 1336-0345, Vol. 124, no 1, p. 12-24Article in journal (Refereed)
    Abstract [en]

    Electroencephalography (EEG) signals are considered one of the oldest techniques for detecting disorders in medical signal processing. However, brain complexity and the non-stationary nature of EEG signals represent a challenge when applying this technique. The current paper proposes new geometrical features for classification of seizure (S) and seizure-free (SF) EEG signals with respect to the Poincaré pattern of discrete wavelet transform (DWT) coefficients. DWT decomposes EEG signal to four levels, and thus Poincaré plot is shown for coefficients. Due to patterns of the Poincaré plot, novel geometrical features are computed from EEG signals. The computed features are involved in standard descriptors of 2-D projection (STD), summation of triangle area using consecutive points (STA), as well as summation of shortest distance from each point relative to the 45-degree line (SSHD), and summation of distance from each point relative to the coordinate center (SDTC). The proposed procedure leads to discriminate features between S and SF EEG signals. Thereafter, a binary particle swarm optimization (BPSO) is developed as an appropriate technique for feature selection. Finally, k-nearest neighbor (KNN) and support vector machine (SVM) classifiers are used for classifying features in S and SF groups. By developing the proposed method, we have archived classification accuracy of 99.3 % with respect to the proposed geometrical features. Accordingly, S and SF EEG signals have been classified. Also, Poincaré plot of SF EEG signals has more regular geometrical shapes as compared to S group. As a final remark, we notice that the Poincaré plot of coefficients in S EEG signals has occupied more space as compared to SF EEG signals (Tab. 3, Fig. 11, Ref. 57).

  • 27.
    Al Khatib, Sultan M.
    et al.
    Al Balqa Appl Univ BAU, Prince Abdullah Bin Ghazi Fac Informat & Commun Te, Dept Software Engn, Al Salt 19117, Jordan..
    Alkharabsheh, Khalid
    Al Balqa Appl Univ BAU, Prince Abdullah Bin Ghazi Fac Informat & Commun Te, Dept Software Engn, Al Salt 19117, Jordan..
    Alawadi, Sadi
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science. Halmstad Univ, Ctr Appl Intelligent Syst Res, Sch Informat Technol, S-30118 Halmstad, Sweden.
    Selection of human evaluators for design smell detection using dragonfly optimization algorithm: An empirical study2023In: Information and Software Technology, ISSN 0950-5849, E-ISSN 1873-6025, Vol. 155, article id 107120Article in journal (Refereed)
    Abstract [en]

    Context: Design smell detection is considered an efficient activity that decreases maintainability expenses and improves software quality. Human context plays an essential role in this domain.Objective: In this paper, we propose a search-based approach to optimize the selection of human evaluators for design smell detection.Method: For this purpose, Dragonfly Algorithm (DA) is employed to identify the optimal or near-optimal human evaluator's profiles. An online survey is designed and asks the evaluators to evaluate a sample of classes for the presence of god class design smell. The Kappa-Fleiss test has been used to validate the proposed approach. Results: The results show that the dragonfly optimization algorithm can be utilized effectively to decrease the efforts (time, cost ) of design smell detection concerning the identification of the number and the optimal or near-optimal profile of human experts required for the evaluation process.Conclusions: A Search-based approach can be effectively used for improving a god-class design smell detection. Consequently, this leads to minimizing the maintenance cost.

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  • 28.
    Alawadi, Sadi
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing.
    Kebande, Victor R.
    Luleå Univ Technol, Dept Comp Sci Elect & Space Engn, Luleå, Sweden..
    Dong, Yuji
    Xian Jiaotong Liverpool Univ, Sch Internet Things, Suzhou, Peoples R China..
    Bugeja, Joseph
    Malmö Univ, Dept Comp Sci, Malmö, Sweden..
    Persson, Jan A.
    Malmö Univ, Dept Comp Sci, Malmö, Sweden..
    Olsson, Carl Magnus
    Malmö Univ, Dept Comp Sci, Malmö, Sweden..
    A Federated Interactive Learning IoT-Based Health Monitoring Platform2021In: New trends in database and information systems, ADBIS 2021 / [ed] Bellatreche, L; Dumas, M; Karras, P; Matulevicius, R; Awad, A; Weidlich, M; Ivanovic, M; Hartig, O, Springer Nature Springer Nature, 2021, Vol. 1450, p. 235-246Conference paper (Refereed)
    Abstract [en]

    Remote health monitoring is a trend for better health management which necessitates the need for secure monitoring and privacy-preservation of patient data. Moreover, accurate and continuous monitoring of personal health status may require expert validation in an active learning strategy. As a result, this paper proposes a Federated Interactive Learning IoT-based Health Monitoring Platform (FIL-IoT-HMP) which incorporates multi-expert feedback as 'Human-in-the-loop' in an active learning strategy in order to improve the clients' Machine Learning (ML) models. The authors have proposed an architecture and conducted an experiment as a proof of concept. Federated learning approach has been preferred in this context given that it strengthens privacy by allowing the global model to be trained while sensitive data is retained at the local edge nodes. Also, each model's accuracy is improved while privacy and security of data has been upheld.

  • 29.
    Alkhabbas, Fahed
    et al.
    Malmö Univ, Internet Things & People Res Ctr, S-21119 Malmö, Sweden.;Malmö Univ, Dept Comp Sci & Media Technol, S-21119 Malmö, Sweden..
    Alsadi, Mohammed
    Norwegian Univ Sci & Technol, Dept Comp Sci, N-7491 Trondheim, Norway..
    Alawadi, Sadi
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Halmstad Univ, Ctr Appl Intelligent Syst Res, Sch Informat Technol, S-30118 Halmstad, Sweden..
    Awaysheh, Feras M.
    Univ Tartu, Delta Res Ctr, Inst Comp Sci, EE-51009 Tartu, Estonia..
    Kebande, Victor R.
    Blekinge Inst Technol, Dept Comp Sci DIDA, S-37179 Karlskrona, Sweden..
    Moghaddam, Mahyar T.
    Univ Southern Denmark, Maersk Mc Kinney Moller Inst MMMI, DK-5230 Odense, Denmark..
    ASSERT: A Blockchain-Based Architectural Approach for Engineering Secure Self-Adaptive IoT Systems2022In: Sensors, E-ISSN 1424-8220, Vol. 22, no 18, article id 6842Article in journal (Refereed)
    Abstract [en]

    Internet of Things (IoT) systems are complex systems that can manage mission-critical, costly operations or the collection, storage, and processing of sensitive data. Therefore, security represents a primary concern that should be considered when engineering IoT systems. Additionally, several challenges need to be addressed, including the following ones. IoT systems' environments are dynamic and uncertain. For instance, IoT devices can be mobile or might run out of batteries, so they can become suddenly unavailable. To cope with such environments, IoT systems can be engineered as goal-driven and self-adaptive systems. A goal-driven IoT system is composed of a dynamic set of IoT devices and services that temporarily connect and cooperate to achieve a specific goal. Several approaches have been proposed to engineer goal-driven and self-adaptive IoT systems. However, none of the existing approaches enable goal-driven IoT systems to automatically detect security threats and autonomously adapt to mitigate them. Toward bridging these gaps, this paper proposes a distributed architectural Approach for engineering goal-driven IoT Systems that can autonomously SElf-adapt to secuRity Threats in their environments (ASSERT). ASSERT exploits techniques and adopts notions, such as agents, federated learning, feedback loops, and blockchain, for maintaining the systems' security and enhancing the trustworthiness of the adaptations they perform. The results of the experiments that we conducted to validate the approach's feasibility show that it performs and scales well when detecting security threats, performing autonomous security adaptations to mitigate the threats and enabling systems' constituents to learn about security threats in their environments collaboratively.

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  • 30.
    Alkharabsheh, Khalid
    et al.
    Al Balqa Appl Univ BAU, Prince Abdullah Bin Ghazi Fac Informat & Commun T, Dept Software Engn, As Salt 197111, Jordan..
    Alawadi, Sadi
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing.
    Crespo, Yania
    Univ Valladolid, Escuela Ingn Informat, Dept Informat, Campus Miguel Delibes, Valladolid 47011, Spain..
    Manso, M. Esperanza
    Univ Valladolid, Escuela Ingn Informat, Dept Informat, Campus Miguel Delibes, Valladolid 47011, Spain..
    Gonzalez, Jose A. Taboada
    Univ Santiago de Compostela, Ctr Singular Invest Tecnoloxias Informac, CiTIUS, Santiago De Compostela 15782, Spain..
    Analysing Agreement Among Different Evaluators in God Class and Feature Envy Detection2021In: IEEE Access, E-ISSN 2169-3536, Vol. 9, p. 145191-145211Article in journal (Refereed)
    Abstract [en]

    The automatic detection of Design Smells has evolved in parallel to the evolution of automatic refactoring tools. There was a huge rise in research activity regarding Design Smell detection from 2010 to the present. However, it should be noted that the adoption of Design Smell detection in real software development practice is not comparable to the adoption of automatic refactoring tools. On the basis of the assumption that it is the objectiveness of a refactoring operation as opposed to the subjectivity in definition and identification of Design Smells that makes the difference, in this paper, the lack of agreement between different evaluators when detecting Design Smells is empirically studied. To do so, a series of experiments and studies were designed and conducted to analyse the concordance in Design Smell detection of different persons and tools, including a comparison between them. This work focuses on two well known Design Smells: God Class and Feature Envy. Concordance analysis is based on the Kappa statistic for inter-rater agreement (particularly Kappa-Fleiss). The results obtained show that there is no agreement in detection in general, and, in those cases where a certain agreement appears, it is considered to be a fair or poor degree of agreement, according to a Kappa-Fleiss interpretation scale. This seems to confirm that there is a subjective component which makes the raters evaluate the presence of Design Smells differently. The study also raises the question of a lack of training and experience regarding Design Smells.

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  • 31.
    Alkharabsheh, Khalid
    et al.
    Al Balqa Appl Univ BAU, Prince Abdullah bin Ghazi Fac Informat & Commun T, Dept Software Engn, Salt, Jordan.
    Alawadi, Sadi
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science. Halmstad Univ, Sch Informat Technol, Ctr Appl Intelligent Syst Res, S-30118 Halmstad, Sweden.
    Ignaim, Karam
    Al Balqa Appl Univ BAU, Prince Abdullah bin Ghazi Fac Informat & Commun T, Dept Software Engn, Salt, Jordan.
    Zanoon, Nabeel
    Al Balqa Appl Univ BAU, Appl Sci Dept, Aqaba Coll, Salt, Jordan.
    Crespo, Yania
    Univ Valladolid, Escuela Ingn Informat, Dept Informat, Campus Miguel Delibes,Paseo Belen 15, Valladolid 47011, Spain.
    Manso, Esperanza
    Al Balqa Appl Univ BAU, Prince Abdullah bin Ghazi Fac Informat & Commun T, Dept Software Engn, Salt, Jordan.;Univ Valladolid, Escuela Ingn Informat, Dept Informat, Campus Miguel Delibes,Paseo Belen 15, Valladolid 47011, Spain.
    Taboada, Jose A.
    Univ Santiago Compostela, Ctr Singular Invest Tecnol Intelixent, CiTIUS, Santiago De Compostela 15782, Spain.
    Prioritization of god class design smell: A multi-criteria based approach2022In: JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES, ISSN 1319-1578, Vol. 34, no 10, p. 9332-9342Article in journal (Refereed)
    Abstract [en]

    Context: Design smell Prioritization is a significant activity that tunes the process of software quality enhancement and raises its life cycle.

    Objective: A multi-criteria merge strategy for Design Smell prioritization is described. The strategy is exemplified with the case of God Class Design Smell.

    Method: An empirical adjustment of the strategy is performed using a dataset of 24 open source projects. Empirical evaluation was conducted in order to check how is the top ranked God Classes obtained by the proposed technique compared against the top ranked God class according to the opinion of developers involved in each of the projects in the dataset.

    Results: Results of the evaluation show the strategy should be improved. Analysis of the differences between projects where respondents answer correlates with the strategy and those projects where there is no correlation should be done.

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  • 32.
    Alkharabsheh, Khalid
    et al.
    Al Balqa Appl Univ BAU, Prince Abdullah Bin Ghazi Fac Informat & Commun T, Dept Software Engn, Salt, Jordan..
    Alawadi, Sadi
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing.
    Kebande, Victor R.
    Blekinge Inst Technol, Dept Comp Sci DIDA, S-37179 Karlskrona, Sweden..
    Crespo, Yania
    Univ Valladolid, Dept Informat, Escuela Ingn Informat, Campus Miguel Delibes, Paseo Belen 15, Valladolid 47011, Spain..
    Fernández-Delgado, Manuel
    Univ Santiago de Compostela, Ctr Singular Invest Tecnoloxias Intelixentes, CiTIUS, Santiago De Compostela 15782, Spain..
    Taboada, José Á.
    Univ Santiago de Compostela, Ctr Singular Invest Tecnoloxias Intelixentes, CiTIUS, Santiago De Compostela 15782, Spain..
    A comparison of machine learning algorithms on design smell detection using balanced and imbalanced dataset: A study of God class2022In: Information and Software Technology, ISSN 0950-5849, E-ISSN 1873-6025, Vol. 143, article id 106736Article in journal (Refereed)
    Abstract [en]

    Context: Design smell detection has proven to be a significant activity that has an aim of not only enhancing the software quality but also increasing its life cycle.

    Objective: This work investigates whether machine learning approaches can effectively be leveraged for software design smell detection. Additionally, this paper provides a comparatively study, focused on using balanced datasets, where it checks if avoiding dataset balancing can be of any influence on the accuracy and behavior during design smell detection.

    Method: A set of experiments have been conducted-using 28 Machine Learning classifiers aimed at detecting God classes. This experiment was conducted using a dataset formed from 12,587 classes of 24 software systems, in which 1,958 classes were manually validated.

    Results: Ultimately, most classifiers obtained high performances,-with Cat Boost showing a higher performance. Also, it is evident from the experiments conducted that data balancing does not have any significant influence on the accuracy of detection. This reinforces the application of machine learning in real scenarios where the data is usually imbalanced by the inherent nature of design smells.

    Conclusions: Machine learning approaches can effectively be used as a leverage for God class detection. While in this paper we have employed SMOTE technique for data balancing, it is worth noting that there exist other methods of data balancing and with other design smells. Furthermore, it is also important to note that application of those other methods may improve the results, in our experiments SMOTE did not improve God class detection.

    The results are not fully generalizable because only one design smell is studied with projects developed in a single programming language, and only one balancing technique is used to compare with the imbalanced case. But these results are promising for the application in real design smells detection scenarios as mentioned above and the focus on other measures, such as Kappa, ROC, and MCC, have been used in the assessment of the classifier behavior.

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  • 33.
    Allmann-Rahn, F.
    et al.
    Ruhr Univ Bochum, Universitatsstr 150, D-44801 Bochum, Germany..
    Grauer, R.
    Ruhr Univ Bochum, Universitatsstr 150, D-44801 Bochum, Germany..
    Kormann, Katharina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Ruhr Univ Bochum, Universitatsstr 150, D-44801 Bochum, Germany..
    A parallel low-rank solver for the six-dimensional Vlasov-Maxwell equations2022In: Journal of Computational Physics, ISSN 0021-9991, E-ISSN 1090-2716, Vol. 469, article id 111562Article in journal (Refereed)
    Abstract [en]

    Continuum Vlasov simulations can be utilized for highly accurate modelling of fully kinetic plasmas. Great progress has been made recently regarding the applicability of the method in realistic plasma configurations. However, a reduction of the high computational cost that is inherent to fully kinetic simulations would be desirable, especially at high velocity space resolutions. For this purpose, low-rank approximations can be employed. The so far available low-rank solvers are restricted to either electrostatic systems or low dimensionality and can therefore not be applied to most space, astrophysical and fusion plasmas. In this paper we present a new parallel low-rank solver for the full six-dimensional electromagnetic Vlasov-Maxwell equations that can utilize distributed memory architectures. Special care is taken to ensure the conservation of mass and a good representation of Gauss's law. The low-rank Vlasov solver is applied to standard benchmark problems of plasma turbulence and magnetic reconnection and compared to the full grid method. It yields accurate results at significantly reduced computational cost.

  • 34.
    Almquist, Martin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Efficient Simulation of Wave Phenomena2017Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Wave phenomena appear in many fields of science such as acoustics, geophysics, and quantum mechanics. They can often be described by partial differential equations (PDEs). As PDEs typically are too difficult to solve by hand, the only option is to compute approximate solutions by implementing numerical methods on computers. Ideally, the numerical methods should produce accurate solutions at low computational cost. For wave propagation problems, high-order finite difference methods are known to be computationally cheap, but historically it has been difficult to construct stable methods. Thus, they have not been guaranteed to produce reasonable results.

    In this thesis we consider finite difference methods on summation-by-parts (SBP) form. To impose boundary and interface conditions we use the simultaneous approximation term (SAT) method. The SBP-SAT technique is designed such that the numerical solution mimics the energy estimates satisfied by the true solution. Hence, SBP-SAT schemes are energy-stable by construction and guaranteed to converge to the true solution of well-posed linear PDE. The SBP-SAT framework provides a means to derive high-order methods without jeopardizing stability. Thus, they overcome most of the drawbacks historically associated with finite difference methods.

    This thesis consists of three parts. The first part is devoted to improving existing SBP-SAT methods. In Papers I and II, we derive schemes with improved accuracy compared to standard schemes. In Paper III, we present an embedded boundary method that makes it easier to cope with complex geometries. The second part of the thesis shows how to apply the SBP-SAT method to wave propagation problems in acoustics (Paper IV) and quantum mechanics (Papers V and VI). The third part of the thesis, consisting of Paper VII, presents an efficient, fully explicit time-integration scheme well suited for locally refined meshes.

    List of papers
    1. A solution to the stability issues with block norm summation by parts operators
    Open this publication in new window or tab >>A solution to the stability issues with block norm summation by parts operators
    2013 (English)In: Journal of Computational Physics, ISSN 0021-9991, E-ISSN 1090-2716, Vol. 253, p. 418-442Article in journal (Refereed) Published
    National Category
    Computational Mathematics
    Identifiers
    urn:nbn:se:uu:diva-205418 (URN)10.1016/j.jcp.2013.07.013 (DOI)000323610500022 ()
    Available from: 2013-07-24 Created: 2013-08-16 Last updated: 2017-12-06Bibliographically approved
    2. Optimal diagonal-norm SBP operators
    Open this publication in new window or tab >>Optimal diagonal-norm SBP operators
    2014 (English)In: Journal of Computational Physics, ISSN 0021-9991, E-ISSN 1090-2716, Vol. 264, p. 91-111Article in journal (Refereed) Published
    National Category
    Computational Mathematics
    Identifiers
    urn:nbn:se:uu:diva-215785 (URN)10.1016/j.jcp.2013.12.041 (DOI)000331717100005 ()
    Available from: 2014-01-15 Created: 2014-01-16 Last updated: 2017-12-06Bibliographically approved
    3. A high-order accurate embedded boundary method for first order hyperbolic equations
    Open this publication in new window or tab >>A high-order accurate embedded boundary method for first order hyperbolic equations
    2017 (English)In: Journal of Computational Physics, ISSN 0021-9991, E-ISSN 1090-2716, Vol. 334, p. 255-279Article in journal (Refereed) Published
    National Category
    Computational Mathematics
    Identifiers
    urn:nbn:se:uu:diva-310122 (URN)10.1016/j.jcp.2016.12.034 (DOI)000395210500015 ()
    Available from: 2016-12-28 Created: 2016-12-11 Last updated: 2017-06-30Bibliographically approved
    4. Atmospheric sound propagation over large-scale irregular terrain
    Open this publication in new window or tab >>Atmospheric sound propagation over large-scale irregular terrain
    2014 (English)In: Journal of Scientific Computing, ISSN 0885-7474, E-ISSN 1573-7691, Vol. 61, p. 369-397Article in journal (Refereed) Published
    National Category
    Computational Mathematics
    Identifiers
    urn:nbn:se:uu:diva-218680 (URN)10.1007/s10915-014-9830-4 (DOI)000343215600007 ()
    Available from: 2014-02-14 Created: 2014-02-14 Last updated: 2017-12-06Bibliographically approved
    5. High-fidelity numerical solution of the time-dependent Dirac equation
    Open this publication in new window or tab >>High-fidelity numerical solution of the time-dependent Dirac equation
    2014 (English)In: Journal of Computational Physics, ISSN 0021-9991, E-ISSN 1090-2716, Vol. 262, p. 86-103Article in journal (Refereed) Published
    National Category
    Computational Mathematics Theoretical Chemistry
    Identifiers
    urn:nbn:se:uu:diva-215119 (URN)10.1016/j.jcp.2013.12.038 (DOI)000330955200006 ()
    Available from: 2014-01-09 Created: 2014-01-10 Last updated: 2017-12-06Bibliographically approved
    6. Realization of adiabatic Aharonov–Bohm scattering with neutrons
    Open this publication in new window or tab >>Realization of adiabatic Aharonov–Bohm scattering with neutrons
    Show others...
    2015 (English)In: Physical Review A. Atomic, Molecular, and Optical Physics, ISSN 1050-2947, E-ISSN 1094-1622, Vol. 92, no 5, p. 052108:1-5, article id 052108Article in journal (Refereed) Published
    National Category
    Atom and Molecular Physics and Optics Computational Mathematics
    Identifiers
    urn:nbn:se:uu:diva-246721 (URN)10.1103/PhysRevA.92.052108 (DOI)000364468300002 ()
    Funder
    Swedish Research Council, D0413201
    Available from: 2015-11-12 Created: 2015-03-09 Last updated: 2017-12-04Bibliographically approved
    7. Multilevel local time-stepping methods of Runge–Kutta-type for wave equations
    Open this publication in new window or tab >>Multilevel local time-stepping methods of Runge–Kutta-type for wave equations
    2017 (English)In: SIAM Journal on Scientific Computing, ISSN 1064-8275, E-ISSN 1095-7197, Vol. 39, p. A2020-A2048Article in journal (Refereed) Published
    National Category
    Computational Mathematics
    Identifiers
    urn:nbn:se:uu:diva-310123 (URN)10.1137/16M1084407 (DOI)000415797300064 ()
    Available from: 2017-09-14 Created: 2016-12-11 Last updated: 2018-03-02Bibliographically approved
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  • 35.
    Almquist, Martin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing.
    Numerical wave propagation in large-scale 3-D environments2012Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    High-order accurate finite difference methods have been applied to the acoustic wave equation in discontinuous media and curvilinear geometries, using the SBP-SAT method. Strict stability is shown for the 2-D wave equation with general boundary conditions. The fourth-order accurate method for the 3-D wave equation has been implemented in C and parallelized using MPI. The implementation has been verified against an analytical solution and runs efficiently on a large number of processors.

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    Numerical wave propagation in large-scale 3-D environments
  • 36.
    Almquist, Martin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Dunham, Eric M.
    Elastic wave propagation in anisotropic solids using energy-stable finite differences with weakly enforced boundary and interface conditions2021In: Journal of Computational Physics, ISSN 0021-9991, E-ISSN 1090-2716, Vol. 424Article in journal (Refereed)
    Abstract [en]

    Summation-by-parts (SBP) finite difference methods have several desirable properties for second-order wave equations. They combine the computational efficiency of narrow-stencil finite difference operators with provable stability on curvilinear multiblock grids. While several techniques for boundary and interface conditions exist, weak imposition via simultaneous approximation terms (SATs) is perhaps the most flexible one. Although SBP methods have been applied to elastic wave equations many times, an SBP-SAT method for general anisotropic elastic wave equations has not yet been presented in the literature. We fill this gap by deriving energy-stable self-adjoint SBP-SAT methods for general anisotropic materials on curvilinear multiblock grids. The methods are based on fully compatible SBP operators. Although this paper focuses on classical SBP finite difference operators, the presented boundary and interface treatments are general and apply to a range of methods that satisfy an SBP property. We demonstrate the stability and accuracy properties of a particular set of fully compatible SBP-SAT schemes using the method of manufactured solutions. We also demonstrate the utility of the new method in elastodynamic cloaking and seismic imaging in mountainous regions.

  • 37.
    Almquist, Martin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Dunham, Eric M.
    Non-stiff boundary and interface penalties for narrow-stencil finite difference approximations of the Laplacian on curvilinear multiblock grids2020In: Journal of Computational Physics, ISSN 0021-9991, E-ISSN 1090-2716, Vol. 408Article in journal (Refereed)
    Abstract [en]

    The Laplacian appears in several partial differential equations used to model wave propagation. Summation-by-parts simultaneous approximation term (SBP-SAT) finite difference methods are often used for such equations, as they combine computational efficiency with provable stability on curvilinear multiblock grids. However, the existing SBP-SAT discretization of the Laplacian quickly becomes prohibitively stiff as grid skewness increases. The stiffness stems from the SATs that impose inter-block couplings and Dirichlet boundary conditions. We resolve this issue by deriving stable SATs whose stiffness is almost insensitive to grid skewness. The new discretization thus allows for large time steps in explicit time integrators, even on very skewed grids. It also applies to the variable-coefficient generalization of the Laplacian. We demonstrate the efficacy and versatility of the new SATs by applying them to acoustic wave propagation problems inspired by marine seismic exploration and infrasound monitoring of volcanoes.

  • 38.
    Almquist, Martin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Karasalo, Ilkka
    Mattsson, Ken
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Atmospheric sound propagation over large-scale irregular terrain2013Report (Other academic)
  • 39.
    Almquist, Martin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Karasalo, Ilkka
    Mattsson, Ken
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Atmospheric sound propagation over large-scale irregular terrain2014In: Journal of Scientific Computing, ISSN 0885-7474, E-ISSN 1573-7691, Vol. 61, p. 369-397Article in journal (Refereed)
  • 40.
    Almquist, Martin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Mattsson, Ken
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Edvinsson, Tomas
    Uppsala University, Disciplinary Domain of Science and Technology, Chemistry, Department of Chemistry - Ångström, Inorganic Chemistry.
    High-fidelity numerical solution of the time-dependent Dirac equation2014In: Journal of Computational Physics, ISSN 0021-9991, E-ISSN 1090-2716, Vol. 262, p. 86-103Article in journal (Refereed)
  • 41.
    Almquist, Martin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Mattsson, Ken
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Edvinsson, Tomas
    Uppsala University, Disciplinary Domain of Science and Technology, Chemistry, Department of Chemistry - Ångström, Inorganic Chemistry.
    Stable and accurate simulation of phenomena in relativistic quantum mechanics2013In: Proc. 11th International Conference on Mathematical and Numerical Aspects of Waves, Tunisia: ENIT , 2013, p. 213-214Conference paper (Other academic)
  • 42.
    Almquist, Martin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Mehlin, Michaela
    Multilevel local time-stepping methods of Runge–Kutta-type for wave equations2017In: SIAM Journal on Scientific Computing, ISSN 1064-8275, E-ISSN 1095-7197, Vol. 39, p. A2020-A2048Article in journal (Refereed)
  • 43. Almquist, Martin
    et al.
    Wang, Siyang
    Werpers, Jonatan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Order-preserving interpolation for summation-by-parts operators at nonconforming grid interfaces2019In: SIAM Journal on Scientific Computing, ISSN 1064-8275, E-ISSN 1095-7197, Vol. 41, p. A1201-A1227Article in journal (Refereed)
  • 44. AL-Naday, Mays
    et al.
    Reed, Martin
    Dobre, Vlad
    Toor, Salman
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Volckaert, Bruno
    De Turck, Filip
    Service-based Federated Deep Reinforcement Learning for Anomaly Detection in Fog Ecosystems2023In: 2023 26th Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN), Institute of Electrical and Electronics Engineers (IEEE), 2023, p. 121-128Conference paper (Refereed)
    Abstract [en]

    With Digital transformation, the diversity of services and infrastructure in backhaul fog network(s) is rising to unprecedented levels. This is causing a rising threat of a wider range of cyber attacks coupled with a growing integration of constrained range of infrastructure, particularly seen at the network edge. Deep reinforcement-based learning is an attractive approach to detecting attacks, as it allows less dependency on labeled data with better ability to classify different attacks. However, current approaches to learning are known to be computationally expensive (cost) and the learning experience can be negatively impacted by the presence of outliers and noise (quality). This work tackles both the cost and quality challenges with a novel service-based federated deep reinforcement learning solution, enabling anomaly detection and attack classification at a reduced data cost and with better quality. The federated settings in the proposed approach enable multiple edge units to create clusters that follow a bottom-up learning approach. The proposed solution adapts deep Q-learning Network (DQN) for service-tunable flow classification, and introduces a novel federated DQN (FDQN) for federated learning. Through such targeted training and validation, variation in data patterns and noise is reduced. This leads to improved performance per service with lower training cost. Performance and cost of the solution, along with sensitivity to exploration parameters are evaluated using an example publicly available dataset (UNSW-NB15). Evaluation results show the proposed solution to maintain detection accuracy with lower data supply, while improving the classification rate by a factor of ≈ 2.

  • 45. Amani Rad, Jamal
    et al.
    Höök, Josef
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Larsson, Elisabeth
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    von Sydow, Lina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Forward deterministic pricing of options using Gaussian radial basis functions2018In: Journal of Computational Science, ISSN 1877-7503, E-ISSN 1877-7511, Vol. 24, p. 209-217Article in journal (Refereed)
    Download full text (pdf)
    fulltext
  • 46.
    Andrade-Loarca, Hector
    et al.
    Ludwig Maximilians Univ Munchen, Dept Math, D-80333 Munich, Germany..
    Kutyniok, Gitta
    Ludwig Maximilians Univ Munchen, Dept Math, D-80333 Munich, Germany.;Univ Tromso, Dept Phys & Technol, N-9019 Tromso, Norway..
    Öktem, Ozan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. KTH Royal Inst Technol, Dept Math, SE-10044 Stockholm, Sweden.
    Petersen, Philipp
    Univ Vienna, Fac Math, A-1090 Vienna, Austria.;Univ Vienna, Res Network Data Sci, A-1090 Vienna, Austria..
    Deep microlocal reconstruction for limited-angle tomography2022In: Applied and Computational Harmonic Analysis, ISSN 1063-5203, E-ISSN 1096-603X, Vol. 59, p. 155-197Article in journal (Refereed)
    Abstract [en]

    We present a deep-learning-based algorithm to jointly solve a reconstruction problem and a wavefront set extraction problem in tomographic imaging. The algorithm is based on a recently developed digital wavefront set extractor as well as the well-known microlocal canonical relation for the Radon transform. We use the wavefront set information about x-ray data to improve the reconstruction by requiring that the underlying neural networks simultaneously extract the correct ground truth wavefront set and ground truth image. As a necessary theoretical step, we identify the digital microlocal canonical relations for deep convolutional residual neural networks. We find strong numerical evidence for the effectiveness of this approach.

    Download full text (pdf)
    fulltext
  • 47.
    Andrejev, Andrej
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Toor, Salman
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Hellander, Andreas
    Holmgren, Sverker
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Risch, Tore
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Scientific analysis by queries in extended SPARQL over a scalable e-Science data store2013In: Proc. 9th International Conference on e-Science, Los Alamitos, CA: IEEE Computer Society, 2013, p. 98-106Conference paper (Refereed)
  • 48. Antolín, Roberto
    et al.
    Nettelblad, Carl
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Gorjanc, Gregor
    Money, Daniel
    Hickey, John M.
    A hybrid method for the imputation of genomic data in livestock populations2017In: Genetics Selection Evolution, ISSN 0999-193X, E-ISSN 1297-9686, Vol. 49, article id 30Article in journal (Refereed)
  • 49. Anzt, Hartwig
    et al.
    Lukarski, Dimitar
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Tomov, Stanimire
    Dongarra, Jack
    Self-adaptive multiprecision preconditioners on multicore and manycore architectures2015In: High Performance Computing for Computational Science – VECPAR 2014, Springer, 2015, p. 115-123Conference paper (Refereed)
  • 50. Appelö, Daniel
    et al.
    Kreiss, Gunilla
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Wang, Siyang
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    An explicit Hermite–Taylor method for the Schrödinger equation2017In: Communications in Computational Physics, ISSN 1815-2406, E-ISSN 1991-7120, Vol. 21, p. 1207-1230Article in journal (Refereed)
1234567 1 - 50 of 1040
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