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6th Smart Cities Symposium, SCS 2022

作者： Matuka, Adelajda Asafo, Shuffield Seyram Eweke, Gamaliel O. Mishra, Pradeep Ray, Soumik Abotaleb, Mostafa Makarovskikh, Tatiana Alhussan, Amel Ali Abdelhamid, Abdelaziz A. El-Kenawy, El-Sayed M. Dutta, P.K. Chowdhury, Subrata University of Macerata Department of Economics and Law Italy Niger Delta University Department of Banking & Finance Nigeria J.N.K.V.V. College of Agriculture M.P. Powarkheda India Centurion University of Technology and Management Odisha Paralakhemundi India Department of System Programming South Ural State University Chelyabinsk454080 Russia Department of Computer Sciences College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University Saudi Arabia Department of Computer Science Faculty of Computer and Information Sciences Ain Shams University Egypt Department of Communications and Electronics Delta Higher Institute of Engineering and Technolog Egypt School of Engineering and Technology Amity University West Bengal Kolkata India AP Chittoor India

ISBN: (纸本)9781839538544

The covid-19 pandemic and Economic Policy Uncertainty resulting from the shutdown of production, withdrawal of investments, enforcement of lockdowns and quarantines globally, have been directly affecting stock markets worldwide. This study is thus an attempt to analyse the impact of the COVID-19 pandemic on stock market behaviour in major affected economies. Moreover, the time frame was extended by using current data which investigate the impact of the virus during the boom and the blast phase in the country's most hit by the pandemic crisis such as China, Italy, UK and US. The frequency of the data is daily, and it dates from 3 January 2020 up to 10 February 2021. The considered time framework will give a deep insight into how stock markets behave in the case of an exogenous shock. The Dickey-Fuller Augmented Unit Root Test indicates that all the variables are stationary at first difference, which is one of the main conditions to have robust result, and the ARCH-LM test for the heteroskedasticity of the residuals, which show that all the probability values are significant, rejecting the null hypothesis of no ARCH effect. Based on the results of GARCH (1,1), we conclude that the change in stock markets volatility is positive and significant in China, Italy, UK and USA. This suggests that the impacts of COVID-19 outbreak and economic policy uncertainty on Stock Markets are a significant and Homogeneous across the studied countries, and the shock on FTSE Italia All Share has the longest time to vanish which makes it the riskiest to invest during this period, while the shock on SP500 USA has the shortest time to disappear meaning that it is safest Stock Market in this study. These findings have significant implications for policymakers, institutional and individual investors and Financial Markets analysts. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Investments

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Monitoring and accounting for the distributed computing system of the ATLAS experiment 27

Monitoring and accounting for the distributed computing syst...

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27th Symposium on Nuclear Electronics and Computing, NEC 2019

作者： Barberis, D. Aimar, A. Alekseev, A. de Sousa Andrade, P.M. Rodrigues Beermann, T.A. Gardner, R.W. Bear, B. Garrido Korchuganova, T. Magnoni, L. Padolski, S. Schanet, E. Tsvetkov, N. Vukotić, I. Wenaus, T. Dipartimento di Fisica dell’Università di Genova e INFN Sezione di Genova Via Dodecaneso 33 GenovaI - 16146 Italy CERN Genève 23CH - 1211 Switzerland Institute of System Programming Russian Academy of Science Moscow Russia Universidad Andrés Bello Santiago Chile Plekhanov Russian University of Economics Stremyanny Lane 36 MoscowRU – 117997 Russia Bergische Universitaet Wuppertal Gaußstr. 20 WuppertalDE - 42119 Germany University of Chicago Enrico Fermi Institute 5640 S Ellis Ave ChicagoIL60637 United States Brookhaven National Laboratory UptonNY United States Fakultät für Physik Ludwig-Maximilians-Universität München Am Coulombwall 1 Garching bei MünchenDE - 85748 Germany

Over the years, ATLAS has developed a large number of monitoring and accounting tools for distributed computing applications. In advance of the increased experiment data rates and monitoring data volumes foreseen for LHC Run 3, starting in 2012, a new infrastructure has been provided by the CERN-IT Monit group, based on InfluxDB as the data store and Grafana as the display environment. ATLAS is adapting and further developing its monitoring tools to use this infrastructure for data and workflow management monitoring and accounting dashboards, expanding the range of previous possibilities with the aim of achieving a single, simpler, environment for all monitoring applications. This contribution describes the tools used, the data flows for monitoring and accounting, the problems encountered and the solutions found. Copyright © 2019 for this paper by its authors.

关键词： Monitoring

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Intelligent system for Classifying of Acoustic Endoscopic Images of the Pancreas Based the Analysis of Walsh Spectra of Local Windows

Intelligent System for Classifying of Acoustic Endoscopic Im...

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Information Technology (ACIT)

作者： Riad Taha Al-Kasasbeh Sergey Filist Olga Shatalova Dmitry Sergeevich Kondrashov Ashraf Shaqadan Nikolay A. Korenevskiy Osama M. Al-Habahbeh Emad Saleh Tarawneh Evgeny Starkov Mechatronics Engineering Department The University of Jordan Amman Jordan Department of SMART Technologies Moscow Polytechnic University Moscow Russian Federation Department of Biomedical Engineering Southwest State University Kursk Russian Federation Civil Engineering Department Zarqa University Zarqa Jordan University of Business and Technology Jeddah Saudi Arabia South-West State University Russian Federation The University of Jordan Jordan Institute of System Programming of the Russian Academy of Sciences Russian Federation

ISBN: (数字)9798331540012

ISBN: (纸本)9798331540029

The purpose of the work is to develop and study methods and algorithms for intelligent classification systems for digital medical images. A method for automatic classification of medical images was developed using neural networks and transparency masks obtained by preliminary image segmentation. This allows you to generate descriptors only for those pixels that are selected by the transparency mask. Also algorithmic and software for classifying medical images has been developed. Experimental testing was carried out on ultrasound images of the pancreas. Differential diagnostics was carried out on control samples. The classes "oncology" and "pancreatitis" were divided. The diagnostic sensitivity by class turned out to be at least 0.8, while the diagnostic specificity is at least 0.85.

关键词： Image segmentation Ultrasonic imaging Sensitivity Neural networks Software algorithms Oncology Software Pancreas Intelligent systems Medical diagnostic imaging

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Numerical simulation of compressible gas flows using regularized gas dynamic equations solver QGDFoam

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AIP Conference Proceedings 2018年第1期2027卷

作者： M. V. Kraposhin T. G. Elizarova M. A. Istomina D. A. Ryazanov K. A. Vatutin 1Ivannikov Institute for System Programming of RAS Moscow Russia 2Keldysh Institute of Applied Mathematics of RAS Moscow Russia 3Lomonosov Moscow State University Moscow Russia

The work presents results of the application of a new OpenFOAM® solver QGDFoam for the numerical simulation of viscous compressible flows in a wide range of Mach numbers. The new solver is based on the explicit approximation of regularized, or quasi-gas dynamic (QGD) equations. The mixed finite-volume and finite-difference approximation is constructed on unstructured spatial grids with co-located variables storage. The solver has been tested for a number of 1D Riemann problems (Sod’s problem, Noh test and others) and 2D cases (Mach 3 forward step, Ladenburg supersonic jet flow with Mach reflection, NASA Langley supersonic overexpanded jet flow and subsonic laminar flow over a backward-facing step). Results of numerical simulations were compared with analytic solutions and OpenFOAM® implementation of the Kurganov-Tadmor scheme, known as rhoCentralFoam. The testing procedure has shown that whereas QGD algorithm is more diffusive than Godunov-type methods with 2nd order TVD schemes with limiters, it is far less diffusive compared with pure upwind schemes as HLL. It was shown that OpenFOAM implementation of the QGD algorithm allows to compute successfully subsonic, sonic and supersonic flows, while other OpenFOAM® solvers have a very limited operational Mach number range. Preliminary results of QGDFoam application for large-scale 3D problems are presented. Scaling tests for up to 768 cores showed good scalability of QGDFoam solver.

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Optimizing machine learning algorithms to enhance blood donation for liver patients: a case study

Optimizing machine learning algorithms to enhance blood dona...

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7th IET Smart Cities Symposium (SCS 2023)

作者： Maad M. Mijwil El-Sayed M. El-kenawy Indu Bala Mohammad Aljanabi Mostafa Abotaleb Abdelhameed Ibrahim Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt School of Electrical and Electronics Engineering Lovely Professional University Punjab India Department of Computer Aliraqia University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

Blood is vital for transporting oxygen, nutrients, and hormones to all body parts as it circulates through arteries and veins. It removes carbon dioxide, regulates body temperature, and maintains the body's immune system. Individuals constantly need blood and its derivatives to save their lives and improve their health through medical treatments and surgical operations. Liver diseases are one of the diseases that affects the health of individuals and requires blood to continue living. These diseases cause significant damage to people's health, and early diagnosis plays a crucial role in saving lives. In this paper, machine learning algorithms (support vector machine and random forest) are involved in detecting liver diseases and determining whether donors are suitable to donate blood from blood values. This paper is applied research that found that the performance measures of the random forest algorithm achieved excellent performance in identifying suitable people to donate blood.

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Correction: Enhancing SNV identification in whole-genome sequencing data through the incorporation of known genetic variants into the minimap2 index

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BMC bioinformatics 2024年第1期25卷 268页

作者： Egor Guguchkin Artem Kasianov Maksim Belenikin Gaukhar Zobkova Ekaterina Kosova Vsevolod Makeev Evgeny Karpulevich Ivannikov Institute for System Programming Moscow Russia. guguchkin@ispras.ru. Institute for Information Transmission Problems Moscow Russia. Evogen LLC Moscow Russia. Vavilov Institute of General Genetics Moscow Russia. Institute of Biochemistry and Genetics of Ufa Scientific Centre Ufa Russia. Cancer Research UK National Biomarker Centre University of Manchester Manchester Manchester M20 4BX UK. Ivannikov Institute for System Programming Moscow Russia.

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Towards Optimizing Cloud Computing Using Residue Number system

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Journal of Physics: Conference Series 2021年第1期1715卷

作者： N Kucherov E Kuchukova A Tchernykh V Kuchukov M Babenko North-Caucasus Federal University Stavropol Russia CICESE Research Center Ensenada BC México South Ural State University Chelyabinsk Russia Ivannikov Institute for System Programming Moscow Russia

In the work methods for building systems of distributed data storage based on the system of residual classes are considered. The use of direct conversion of data from the positional system of calculation to the residue number system will have a large computational complexity, the use of modules of a particular type allows you to solve this problem. The operation of scaling and expansion of the base system, which is necessary to restore the number of stored parts in case of failure of one or more cloud servers, is considered.

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Preface

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2004年 2981卷 V-VI页

作者： Müller-Schloer, Christian Ungerer, Theo Bauer, Bernhard University of Hannover Institute of Systems Engineering System and Computer Architecture - SRA Appelstr. 4 Hannover Germany University of Augsburg Institute of Informatics Augsburg Germany University of Augsburg Department of Software Engineering and Programming Languages Augsburg Germany

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Study of aerophysical processes in the wind farm of the Republic of Adygey

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AIP Conference Proceedings 2021年第1期2351卷

作者： A. V. Ivanov S. V. Strijhak 1)Ivannikov Institute for System Programming of the Russian Academy of Sciences (ISP RAS) 109004 Moscow Russia 2)M. V. Keldysh Institute of Applied Mathematic of the Russian Academy of Sciences (KIAM RAS) 125047 Moscow Russia

The article presents numerical modeling of meteorological processes in the wind farm of the Republic of Adygea. The wind farm has 60 wind turbines, the capacity of each wind turbine is 2.5 MW. A test configuration with 4 nested domains was developed to study the wind farm. The computations were carried out using the WRF-ARW computational code with the wind turbine parameterization module. The calculation was performed for the period 01.04.2020 00:00 – 01.05.2020 00:00 UTC. As a result, the dimensions of the wake formed by the wind farm were obtained, and the influence of the parameterization of wind turbines on the wind distribution calculation was shown. The potential vortex wake can reach sizes up to 15 km. The losses of generated power can reach 1 MW inside the vortex wake. The computations were run on high performance cluster UNIHUB of ISP RAS.

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Exact solutions of boundary integral equation arising in vortex methods for incompressible flow simulation around elliptical and Zhukovsky airfoils

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Journal of Physics: Conference Series 2019年第1期1348卷

作者： Kseniia Kuzmina Ilia Marchevsky Evgeniya Ryatina Ivannikov Institute for System Programming of the RAS Alexander Solzhenitsyn st. 25 Moscow 109004 Russia Bauman Moscow State Technical University 2-nd Baumanskaya st. 5 Moscow 105005 Russia

The problem of 2D incompressible flow simulation around airfoils using vortex methods is considered. An exact solution for the boundary integral equation with respect to a free vortex sheet intensity at the airfoil surface line that arises in such problems is obtained. The exact solution is constructed for flows around elliptical and Zhukovsky airfoils using the theory of complex potentials and conformal mappings technique. It is possible to take into account the influence of singularities in the flow domain — point vortices which simulate vortex wake. The obtained exact solutions can be used to verify and estimate the accuracy of numerical schemes for the boundary integral equation solution: such procedure is also described in details.

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