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Erratum to: The Software system LingvoDoc and the Possibilities It Offers for Documentation and Analysis of Ob-Ugric Languages

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Doklady Mathematics 2023年第3期106卷 487-487页

作者： Normanskaja, Yu. V. Borisenko, O. D. Beloborodov, I. B. Avetisyan, A. I. Ivannikov Institute for System Programming of the Russian Academy of Sciences Russia Russia Institute of Linguistics of the Russian Academy of Sciences Russia Russia

An Erratum to this paper has been published: https://***/10.1134/S1064562422340038

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Using Machine Learning Techniques for Assessing Media Text Readability

Using Machine Learning Techniques for Assessing Media Text R...

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Annual Siberian Russian Workshop on Electron Devices and Materials (EDM)

作者： Andrey Laputenko Tatiana Evtushenko Elena Klochkova Nina Yevtushenko Department of Information Technologies National Research Tomsk State University Tomsk Russian Federation Graduate School of Applied Linguistics and Translation Studies Peter the Great St. Petersburg Polytechnic University Saint Petersburg Russian Federation Department of Software Engineering Ivannikov Institute for System Programming of the Russian Academy of Sciences Moscow Russian Federation

The paper addresses the problem of assessing media text readability depending on the correlation of objective and subjective text complexity. Objective text complexity refers to a set of measurable characteristics such as baseline, morphological, syntactic and lexical characteristics of a media text (a piece of news published on university websites), which is calculated automatically for each text. In total, 34 parameters are considered. Subjective text complexity score is assigned to each text by human experts who assess the clarity, structure, cohesion and coherence of the text. The correlation between subjective and objective text complexity is studied using machine learning models. The readability level is measured using machine learning methods and regression-correlation analysis. Namely, an artificial neural network and regression models are used. It is demonstrated that the use of polynomial features and lasso regularization allows to get a compact regression model of a high quality. The use of the chosen machine learning techniques made it possible to estimate the impact of distinct linguistic features on the readability level.

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Simulation and optimization of injector parameters with OpenFOAM and globalizer tools

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AIP Conference Proceedings 2023年第1期2849卷

作者： Konstantin Barkalov Ilya Lebedev Daniil Ryazanov Sergey Strijak Lobachevsky State University of Nizhny Novgorod Nizhny Novgorod Russia Ivannikov Institute for System Programming of the RAS Moscow Russia

The paper presents results of simulation and optimization of the processes taking place in a fuel system injector. Simula-tion has been carried using tools of the OpenFOAM system. The problem of differential pressure minimization at the injector inlet and outlet was set and solved. This problem was considered as a Lipschitz optimization problem with a black-box type objective function. To solve it, we used an efficient global search algorithm implemented in the Globalizer system.

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Dipper Throated Optimization for Detecting Black-Hole Attacks inMANETs

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Computers, Materials & Continua 2023年第1期74卷 1905-1921页

作者： Reem Alkanhel El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Mostafa Abotaleb Doaa Sami Khafaga Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of System Programming South Ural State UniversityChelyabinsk454080Russia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

In terms of security and privacy,mobile ad-hoc network(MANET)continues to be in demand for additional debate and *** more MANET applications become data-oriented,implementing a secure and reliable data transfer protocol becomes a major concern in the ***,MANET’s lack of infrastructure,unpredictable topology,and restricted resources,as well as the lack of a previously permitted trust relationship among connected nodes,contribute to the attack detection burden.A novel detection approach is presented in this paper to classify passive and active black-hole *** proposed approach is based on the dipper throated optimization(DTO)algorithm,which presents a plausible path out of multiple paths for statistics transmission to boost MANETs’quality of service.A group of selected packet features will then be weighed by the DTO-based multi-layer perceptron(DTO-MLP),and these features are collected from nodes using the Low Energy Adaptive Clustering Hierarchical(LEACH)clustering *** is a powerful classifier and the DTO weight optimization method has a significant impact on improving the classification process by strengthening the weights of key features while suppressing the weights ofminor *** hybridmethod is primarily designed to combat active black-hole *** the LEACH clustering phase,however,can also detect passive black-hole *** effect of mobility variation on detection error and routing overhead is explored and evaluated using the suggested *** diverse mobility situations,the results demonstrate up to 97%detection accuracy and faster execution ***,the suggested approach uses an adjustable threshold value to make a correct conclusion regarding whether a node is malicious or benign.

关键词： Black-hole attack mobile ad-hoc network optimization dipper throated optimization

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Hybrid Grey Wolf and Dipper Throated Optimization in Network Intrusion Detection systems

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Computers, Materials & Continua 2023年第2期74卷 2695-2709页

作者： Reem Alkanhel Doaa Sami Khafaga El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Rashid Amin Mostafa Abotaleb B.M.El-den Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science University of Engineering and TechnologyTaxilaPakistan Department of System Programming South Ural State UniversityChelyabinsk454080Russia

The Internet of Things(IoT)is a modern approach that enables connection with a wide variety of devices *** to the resource constraints and open nature of IoT nodes,the routing protocol for low power and lossy(RPL)networks may be vulnerable to several routing ***’s why a network intrusion detection system(NIDS)is needed to guard against routing assaults on RPL-based IoT *** imbalance between the false and valid attacks in the training set degrades the performance of machine learning employed to detect network ***,we propose in this paper a novel approach to balance the dataset classes based on metaheuristic optimization applied to locality-sensitive hashing and synthetic minority oversampling technique(LSH-SMOTE).The proposed optimization approach is based on a new hybrid between the grey wolf and dipper throated optimization *** prove the effectiveness of the proposed approach,a set of experiments were conducted to evaluate the performance of NIDS for three cases,namely,detection without dataset balancing,detection with SMOTE balancing,and detection with the proposed optimized LSHSOMTE *** results showed that the proposed approach outperforms the other approaches and could boost the detection *** addition,a statistical analysis is performed to study the significance and stability of the proposed *** conducted experiments include seven different types of attack cases in the RPL-NIDS17 *** on the 2696 CMC,2023,vol.74,no.2 proposed approach,the achieved accuracy is(98.1%),sensitivity is(97.8%),and specificity is(98.8%).

关键词： Metaheuristics grey wolf optimization dipper throated optimization dataset balancing locality sensitive hashing SMOTE

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Towards Russian national data lake prototype 27

Towards Russian national data lake prototype

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27th Symposium on Nuclear Electronics and Computing, NEC 2019

作者： Alekseev, A. Campana, S. Espinal, X. Jezequel, S. Kiryanov, A. Klimentov, A. Mitsyn, V. Zarochentsev, A. Plekhanov Russian University of Economics 36 Stremyanny lane Moscow Russia CERN. 1 Espl. des Particules Geneva Switzerland Petersburg Nuclear Physics Institute of NRC "KI". 1 Orlova roshcha Gatchina Russia JINR 6 Joliot-Curie st. Dubna Russia St. Petersburg State University 13B Universitetskaya emb Saint Petersburg Russia Brookhaven National Laboratory UptonNY United States Institute of System Programming Russian Academy of Science Moscow Russia Universidad Andrés Bello Santiago Chile L.a.p.p. Laboratoire d'Annecy De Physique Des Particules Annecy-le-Veus France

The evolution of the computing facilities and the way storage will be organized and consolidated will play a key role in how this possible shortage of resources will be addressed by the LHC experiments. The need for an effective distributed data storage has been identified as fundamental from the beginning of LHC, and this topic has become particularly vital in the light of the preparation for the HL-LHC run. WLCG has started an R&D within DOMA project and in this contribution we will report the recent results related to the Russian federated data storage systems configuration and testing. We will describe different system configurations and various approaches to test data storage federation. We are considering EOS and dCache storage systems as a backbone software for data federation and xCache for data caching. We'll also report about synthetic tests and experiments specific tests developed by ATLAS and ALICE for federated storage prototype in Russia. Data Lake project has been launched in Russian Federation in 2019 to set up a National Data Lake prototype for HENP and to consolidate geographically distributed data storage systems connected by fast network with low latency, we will report the project objectives and status. Copyright © 2019 for this paper by its authors.

关键词： Lakes

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On the high-accuracy approach to flow simulation aroundthe airfoils by using vortex method

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IOP Conference Series: Materials Science and Engineering 2018年第1期468卷

作者： K S Kuzmina I K Marchevsky V S Moreva Bauman Moscow State Technical University Moscow Russia Ivannikov Institute for System Programming of the Russian Academy of Sciences Moscow Russia

Some problems connected to vortex methods development for 2D incompressible flow simulation around airfoils are discussed. In the numerical schemes and algorithms which are normally used in the vortex methods, the airfoil is approximated by a polygon consists of rectilinear panels, and the the vortex sheet intensity, which is placed on the airfoil surface line and simulates the airfoil's influence the flow, is assumed to be piecewise-constant or piecewise-linear function. The most accurate mathematical models and numerical algorithms, based on such approaches, provide the estimation for the order of the error between O(h) and O(h 2) for the average vortex sheet intensity over the panels (h is the maximal panel length). In the present research a new approach is developed, where the vortex sheet intensity is assumed to be discontinuous piecewise-linear or piecewise-quadratic function and the curvature of the panels is taken into account. In order to compute the coefficients of the main system of the algebraic equations, the least squares method is used instead of commonly used no-through or no-slip conditions at separate control points or over the panels in the average. It is shown, that the developed approach is much more accurate in comparison with previously known ones: for some test problems (flows around a circular airfoil, an elliptical airfoil and Zhukovsky airfoil) it permits to obtain numerical solution which has error of order O(h 4).

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Developing quasi-steady model for studying hemostatic response using supercomputer technologies

Supercomputing Frontiers and Innovations

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Supercomputing Frontiers and Innovations 2018年第4期5卷 67-72页

作者： Trifanov, Petr V. Kaneva, Valeriia N. Strijhak, Sergei V. Panteleev, Mikhail A. Ataullakhanov, Fazoil I. Dunster, Joanne Voevodin, Vadim V. Nechipurenko, Dmitry Y. Department of Physics Lomonosov Moscow State University Moscow Russia Dmitry Rogachev National Research Center of Pediatric Hematology Oncology and Immunology Moscow Russia Center for Theoretical Problems of Physicochemical Pharmacology Moscow Russia Ivannikov Institute for System Programming of the RAS Moscow Russia Faculty of Biological and Medical Physics Moscow Institute of Physics and Technology Dolgoprudny Russia Institute for Cardiovascular and Metabolic Research School of Biological Sciences University of Reading Berkshire United Kingdom Research Computing Center of Lomonosov Moscow State University Moscow Russia

Formation of the platelet plug represents a primary response to the vessel wall injury, but may also result in vessel occlusion. The decrease of the local blood flow due to platelet thrombus formation may lead to serious complications, such as ischemic stroke and myocardial infarction. However, mechanisms responsible for regulation of thrombus dynamics are not clear. In order to get a deeper insight into the role of blood flow and platelet interactions in the formation of the primary platelet plug we developed a particle-based model of microvascular thrombosis using quasisteady flow approximation. In order to simulate thrombus dynamics at physiologically relevant timescales of several minutes, we took advantage of the supercomputer technologies. Our in silico analysis revealed the importance of platelet size heterogeneity for describing experimental data on microvascular thrombus formation. Thus, our model represents a useful tool for the supercomputeraided computational analysis of thrombus dynamics in the microvessels on physiologically relevant timescales. © The Author 2018.

关键词： Platelets

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Forecasting Nonlinear Nonstationary Processes in Machine Learning Task

Forecasting Nonlinear Nonstationary Processes in Machine Lea...

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IEEE International Conference on Data Stream Mining & Processing (DSMP)

作者： Peter Bidyuk Aleksandr Gozhyj Irina Kalinina Victoria Vysotska Mikhail Vasilev Romanna Malets Department of Mathematical Methods of System Analysis National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" Kyiv Ukraine Department of Intelligent Information Systems Petro Mohyla Black Sea National University Nikolaev Ukraine Department of Information Systems And Networks National University "Lvivska politechnika" Lviv Ukraine Programming Department Ivan Franko Lviv National University Lviv Ukraine

ISBN: (数字)9781728132143

ISBN: (纸本)9781728132150

The article discusses the features of the solving the forecasting problems using machine learning techniques. The issues of accounting and correctly processing non-linear non-stationary processes in the problems of modeling and forecasting time series in various areas are considered. The analysis of stages and methods for solving machine learning problems. As an example, consider the problem of predicting currency pairs based on historical data. A comparative analysis of the normalization methods in data clustering is given. For the six currency pairs a short-term forecast is proposed.

关键词： Forecasting Time series analysis Machine learning Load modeling Currencies Predictive models Classification algorithms

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Numerical simulation in 2D strongly coupled FSI problems for incompressible flows by using vortex method

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AIP Conference Proceedings 2018年第1期2027卷

作者： Kseniia Kuzmina Ilia Marchevsky Evgeniya Ryatina 1Bauman Moscow State Technical University Russia 2Ivannikov Institute for System Programming of the Russian Academy of Sciences Russia

Two coupling strategies for numerical simulation in Fluid-Structure Interaction problems using vortex methods are considered and implemented in new open-source code VM2D developed by the authors for 2D incompressible flows simulations around airfoils using vortex methods. The first strategy called “partitioned approach” implies that hydrodynamical subproblem and mechanical one are solved separately, step-by-step. However, this method has limited range of applicability. In the second strategy called “monolithic approach” these two subproblems are solved together. Both approaches are implemented in the VM2D code and their comparison is carried out for the model problem of a circular cylinder wind resonance (transversal oscillations) simultation.

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