Specialized Web Portal for Solving Problems on Multiprocessor Computing Systems

A system for remote calculations called “Specialized web portal for solving problems on multiprocessor computing systems” has been developed and installed at the Department of Ill-Posed Problems of Analysis and Applications of the Institute of Mathematics and Mechanics UrB RAS. The parallel algorithms have been incorporated into this system to solve the inverse gravity problem of lateral density reconstruction, the structural inverse gravity and magnetic problem of the contact surfaces reconstruction, and solving SLAEs with block-tridiagonal matrices in geoelectrics problems

The Problem of Scheduling for the Linear Section of a Single-Track Railway with Independent Edges Orientations

The paper is devoted to the problem of scheduling for the linear section of a single-track railway: how to organize the ow in both directions in the most efficient way. In this paper, the authors propose an algorithm for scheduling with independent edges orientations, examine the properties of this algorithm and perform the computational experiments

Algorithms for solving inverse geophysical problems on parallel computing systems

For solving inverse gravimetry problems, efficient stable parallel algorithms based on iterative gradient methods are proposed. For solving systems of linear algebraic equations with block-tridiagonal matrices arising in geoelectrics problems, a parallel matrix sweep algorithm, a square root method, and a conjugate gradient method with preconditioner are proposed. The algorithms are implemented numerically on a parallel computing system of the Institute of Mathematics and Mechanics (PCS-IMM), NVIDIA graphics processors, and an Intel multi-core CPU with some new computing technologies. The parallel algorithms are incorporated into a system of remote computations entitled "Specialized Web-Portal for Solving Geophysical Problems on Multiprocessor Computers." Some problems with "quasi-model" and real data are solved. © 2013 Pleiades Publishing, Ltd

Proton configurations in the hydrogen bonds of KH2PO4 as seen by resonant x-ray diffraction

KH2PO4 (KDP) belongs to the class of hydrogen-bonded ferroelectrics, whose paraelectric to ferroelectric phase transition is driven by the ordering of the protons in the hydrogen bonds. We demonstrate that forbidden reflections of KDP, when measured at an x-ray absorption edge, are highly sensitive to the asymmetry of proton configurations. The change of average symmetry caused by the "freezing" of the protons during the phase transition is clearly evidenced. In the paraelectric phase, we identify in the resonant spectra of the forbidden reflections a contribution related to the transient proton configurations in the hydrogen bonds, which violates the high average symmetry of the sites of the resonant atoms. The analysis of the temperature dependence reveals a change of relative probabilities of the different proton configurations. They follow the Arrhenius law, and the activation energies of polar and Slater configurations are 18.6 and 7.3 meV, respectively

Factors Influencing Nurses’ Decision to Join a Professional Association in Russia

Received 26 October 2019. Accepted 21 June 2020. Published online 9 July 2020.Many professional associations of nurses in Russia and other countries struggle to increase their membership. Even though there are obvious advantages of membership in a professional organization, many people decide against it, which makes the study of factors that affect their decision-making a pertinent task. The aim of our research is to study the factors of membership or nonmembership of nurses in professional organizations in Russia. We conducted semi-structured interviews among nurses in different Russian regions (N = 16). Their responses were analyzed by qualitative content analysis. We identified the main factors that determine nurses’ membership or non-membership in professional associations and distinguished between objective and subjective reasons as well as active or passive attitudes demonstrated by our respondents in this regard. The conclusion is made that nurses often adopt a “formal” approach to membership in professional associations, seeing it primarily as a certification requirement. This means that their interests may not coincide with the goals and mission declared by these associations in their charters. Some respondents, however, demonstrated a more active attitude, pointing out such reasons for membership as professional growth, opportunities for advanced training, socialization, exchange of ideas and so on.This research was supported by the Russian Fund of Federal Property, project No. 18-013-01154А

Memory efficient algorithm for solving the inverse gravimetry problem of finding several boundary surfaces in multilayered medium

For solving the inverse gravimetry problem of finding several boundary surfaces in a multilayered medium, the parallel algorithm was constructed and implemented for multicore CPU using OpenMP technology. The algorithm is based on the modified nonlinear conjugate gradient method with weighting factors previously proposed by authors. To reduce the memory requirements and computation time, the modification was constructed on the basis of utilizing the Toeplitz-block-Toeplitz structure of the Jacobian matrix of the integral operator. The model problem of reconstructing three surfaces using the quasi-real gravitational data was solved on a large grid. It was shown that the proposed implementation reduces the computation time by 80% in comparison with the earlier algorithm based on calculating the entire matrix. The parallel algorithm shows good scaling of 94% on 8-core processor. © 2019 Author(s).Ministry of Education and Science of the Republic of Kazakhstan: AP 05133873This work was financially supported by the Ministry of Education and Science of the Republic of Kazakhstan (project AP 05133873)

Super-resolution of satellite images: Feasibility of deep learning techniques

The work is devoted to studying the feasibility of applying the convolutional neural networks with deep learning to the problems of super-resolution of satellite images. The main aim is to enhance the image details and delete the artifacts. The algorithms for resolution enhancement were studied. The training set of satellite images was prepared. The neural network was constructed and trained using the PyTorch library for the Python language and the NVIDIA Tesla K40m graphics processors. Comparison of constructed network with the classic interpolation algorithms was carried out for the reference satellite images. It was shown that the neural network gives a better quality of the images. © 2020 American Institute of Physics Inc.. All rights reserved

An Efficient Numerical Technique for Solving the Inverse Gravity Problem of Finding a Lateral Density

The main goal of our paper is to construct a technique for the gravity inversion problem of finding a variable density in a horizontal layer on the basis of gravitational data. This technique consists of two steps: extracting the gravitational field and solving the linear integral equation of the density. After discretization and approximation of integral operator, this problem is reduced to solving large systems of linear algebraic equations. To solve these systems, we proposed a memory-efficient algorithm based on the iterative method of minimal residuals. The idea of memory optimization is based on exploiting the block-Toeplitz structure of coefficients matrix. The algorithms were parallelized and implemented using the Uran and UrFU supercomputers. A model problem with synthetic gravitational data was solved

Preface of “the second symposium on Advanced Methods and Information Technologies Applications (AMITA)”

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