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

作者： Akram Kh. Nishanov Oybek Allamov Askar T. Rakhmanov Janar Yusupova Ortik B. Ruzibaev Department of Systematic and Practical Programming Technical Sciences Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan Department of Software Engineering Urgench Branch of Tashkent University of Information Technology named after Muhammad al Khwarizmi Urgench Uzbekistan Department of systematic and practical programming Tashkent university of information technologies named after muhammad al-Khwarizmi Tashkent Uzbekistan Faculty of Software Engineering Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan

ISBN: (数字)9798350389234

ISBN: (纸本)9798350353051

The article considers in the intellectual processing of information, moving from a large unit of measurement to a smaller, more important unit of measurement, selecting sets of informative symbols and classifying symbols, developing modern recognition systems that help specialists in the field, as well as evaluating the states of objects to be classified, developing a classification algorithm for multi-class cases of educational samples. The development of a multi-class algorithm for symbol classification serves to develop the theory of symbol recognition. It deals with the construction of a decision rule construction algorithm. Its main purpose is to determine which of the given classes the recognized object belongs to. The complexity or simplicity of the proposed algorithm depends on the number of classes participating in the study sample. If the number of classes is two, then the formulation of decision rules is simple. That is why the classification algorithms proposed by most authors are solved for cases where the number of classes is three or more, the decisive rule in the matter of classification of objects is solved by making two classes. The construction of a multi-class decision rule for classification, which takes into account all classes at the same time, is a complex and urgent issue. In the article, in the classification of objects, a multi-level complex structured decision rule was developed based on special inequalities, and two-, three- and multi-class classification algorithms were developed.

关键词： Training Productivity Measurement units Atmospheric measurements Symbols Particle measurements Classification algorithms

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Modeling of Thermoviscoelasticity Time Harmonic Variational Problem for a Thin Wall Body

Modeling of Thermoviscoelasticity Time Harmonic Variational ...

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

作者： Romanna Malets Heorgiy Shynkarenko Igor Malets Petro Vahin Department of programming Ivan Franko National University of Lviv Lviv Ukraine Department of Information System Opole University of Technology Opole Poland Lviv Ukraine Department of Project Management Information Technologies and Telecommunications Lviv State University of Life Safety Lviv Ukraine Department of Information System Ivan Franko National University of Lviv Lviv Ukraine

ISBN: (纸本)9781538628751

The paper presents the construction and analysis of vibration problem of thermoviscoelastic shells under the influence of non-stationary heat and under forced loads. The studied model was based on application of simplest finite element semidiscretization to mixed variational problem of dynamical thermoviscoelasticity. The problem in addition to the mutual influence of temperature field and stress field is also taken into account the viscoelastic properties of the material thin wall body. For assumptions quite suitable for applications we prove the well-posedness forthis model of time harmonic vibrations.

关键词： Heating systems Vibrations Harmonic analysis Mathematical model Tensile stress Load modeling Method of moments

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Analysing the Impact of COVID-19 outbreak and Economic Policy Uncertainty on Stock Markets in Major Affected Economies 6

Analysing the Impact of COVID-19 outbreak and Economic Polic...

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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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How File-access Patterns Inuence the Degree of I/O Interference between Cluster Applications

Supercomputing Frontiers and Innovations

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Supercomputing Frontiers and Innovations 2019年第2期6卷 29-55页

作者： Shah, Aamer Kuo, Chih-Song Nomura, Akihiro Matsuoka, Satoshi Wolf, Felix Laboratory for Parallel Programming Technische Universita•t Darmstadt Darmstadt Germany Taiwan Semiconductor Manufacturing Company Limited Hsinchu Taiwan Global Scientic Information and Computing Center Tokyo Institute of Technology Tokyo Japan Department of Mathematical and Computing Science Tokyo Institute of Technology Tokyo Japan

On large-scale clusters, tens to hundreds of applications can simultaneously access a parallel le system, leading to contention and, in its wake, to degraded application performance. In this article, we analyze the inuence of le-access patterns on the degree of interference. As it is by experience most intrusive, we focus our attention on write-write contention. We observe considerable dierences among the interference potentials of several typical write patterns. In particular, we found that if one parallel program writes large output les while another one writes small checkpointing les, then the latter is slowed down when the checkpointing les are small enough and the former is vice versa. Moreover, applications with a few processes writing large output les already can signicantly hinder applications with many processes from checkpointing small les. Such eects can seriously impact the runtime of real applications|up to a factor of ve in one instance. Our insights and measurement techniques oer an opportunity to automatically classify the interference potential between applications and to adjust scheduling decisions accordingly. © The Authors 2019. This paper is published with open access at ***

关键词： Benchmarking

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Design of Intelligent Decision Support System With Ensembled Machine Learning to Predict Students' Performance

Design of Intelligent Decision Support System With Ensembled...

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2024 International Conference on Communication, Computer Sciences and Engineering, IC3SE 2024

作者： Deepan, S. Rajendran, Dineshkumar Dhaliwal, Navdeep Praveena, K. Lourens, Melanie Anandhi, R.J. School Of Cs & Ai Sr University Telangana Warangal India School Of Computing And Innovative Technologies British University Computer Games Design And Programming Viet Nam Lovely Professional University Phagwara India Institute Of Aeronautical Engineering Dundigal Hyderabad India Durban University Of Technology Faculty Of Management Sciences South Africa New Horizon College Of Engineering Department Of Information Science Engineering Bangalore India

ISBN: (纸本)9798350366846

Evaluating student performance is important for universities and institutions in the current student education landscape because it helps them create models that work better for students. The automation of various features related to fundamental student traits and behaviours that manage massive amounts of data efficiently processes these. To handle student records that included information about students' behaviour and how it related to their academic performance, the companies employed models of classification with mining concepts. Additionally, the quality of result classification can be substantially improved by using learning analytics and Educational Data Mining (EDM). The educational establishments are making an effort to lower the low student performance. To address this issue, numerous methods for assessing student performance have been devised, allowing the relevant faculties to intervene and enhance the final product. Three classes - Low Performance Student, Average Student, and Smart Student - were created using the K-Mean Clustering methodology for classifying student records. Features including grade point, number of deficits, student attendance, medium of education, and board of education are taken into account when classifying the data. In this case, the WEKA tool is also utilized for implementing the model and outcome assessments. © 2024 IEEE.

关键词： Decision support systems

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Word-Based Turkish Lip Reading System with Two Stream 3dcnn and Bilstm

SSRN

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SSRN 2023年

作者： Erbey, Ali Barışçı, Necaattin Department of Computer Programming Distance Education Vocational School Usak University Usak64200 Turkey Department of Information Systems Informatics Institute Gazi University Ankara Turkey Department of Computer Engineering Faculty of Technology Gazi University Ankara06500 Turkey

Lip reading is a technique that aims to understand spoken words by analyzing people's lip movements. Deep learning algorithms are used as a powerful tool for detecting and recognizing lip movements more accurately. In this study, we present a lip-reading architecture for the Turkish language. The architecture is trained to recognize Turkish words using 3DCNN (3D Convolutional Neural Network) architecture and two-stream deep learning methods. The model was trained on video data representing lip movements and learned to classify words accurately. The Turkish lip reading system has been trained and tested on a large Turkish lip reading dataset. In the experiments, an accuracy of 87.12% was achieved with the proposed model, indicating successful results in the Turkish language. The proposed model demonstrates high accuracy rates in recognizing Turkish words, showcasing its effectiveness. This paper introduces a novel architecture, a lip-reading system that employs deep learning techniques, providing a robust tool for successful Turkish lipreading applications. © 2023, The Authors. All rights reserved.

关键词： Convolutional neural networks

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Social Engineering Attacks Detection Approach

Social Engineering Attacks Detection Approach

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IEEE International Conference on Dependable Systems, Services and Technologies (DESSERT)

作者： Sergii Lysenko Volodymyr Vorobiov Oleksandr Bokhonko Piotr Gaj Oleg Savenko Jacek Wołoszyn Department of Computer Engineering and Information Systems Khmelnitsky National University Khmelnitsky Ukraine Silesian University of Technology Gliwice Poland Department of Computer Engineering and System Programming Khmelnitsky National University Khmelnitsky Ukraine Department of Informatics and Teleinformatics Kazimierz Pulaski University of Technology and Humanities in Radom Radom Poland

The paper focuses on the problem of technical social engineering attacks that encompass the manipulation of individuals to reveal sensitive information, execute actions, or breach security systems. These exploits frequently capitalize on human psychology, trust, and a lack of vigilance to attain unauthorized entry to networks, systems, or data. In contrast to traditional social engineering tactics that center on psychological manipulation, technical social engineering attacks employ technological means and strategies to manipulate and beguile individuals. The paper presents an attempt to detect social engineering attacks. The approach utilized four machine learning algorithms (decision tree, random forest, K-nearest neighbor, and extreme gradient boosting). The analysis is centered on data collected from network hosts, which may serve as indicators of a potential social engineering attack. The empirical results demonstrated high detection accuracy.

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Seven more myths of formal methods: Dispelling industrial prejudices 2nd

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2nd International Symposium of Formal Methods Europe, FME 1994

作者： Bowen, Jonathan P. Hinchey, Michael G. Oxford University Computing Laboratory Programming Research Group Wolfson Building Parks Road OxfordOX1 3QD United Kingdom University of Cambridge Computer Laboratory New Museums Site Pembroke Street CambridgeCB2 3QG United Kingdom Department of Computer and Information Science New Jersey Institute of Technology United States

ISBN: (纸本)9783540585558

For whatever reason, formal methods remain one of the more contentious techniques in industrial software engineering. Despite some improvement in the uptake of formal methods, it is still the case that the vast majority of potential users of formal methods fail to become actual users. A paper by Hall in 1990 [31] exaznined a number of ‘myths’ concerning formal methods, assumed by some to be valid. This paper considers a few more beliefs held by many and presents some counter examples. © 1994, Springer Verlag. All rights reserved.

关键词： Formal methods

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The prediction of students' academic performances with a classification model built using data mining techniques

The prediction of students' academic performances with a cla...

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6th Smart Cities Symposium (SCS 2022)

作者： H. Alkattan M. Abotaleb A. Ali Subhi O. A. Adelaja A. Kadi H. K. Ibrahim Al-Mahdawi Department of System Programming South Ural State University Chelyabinsk Russia University of Diyala Diyala Iraq Information Communication and Technology Department Lagos State University Lagos Nigeria Department of Food and Biotechnology South Ural State University Chelyabinsk Russia

In the purview of most educational sectors today, numerous reviews regarding data mining have been the primary focus, with goals of discovering vast knowledge patterns for students' data. This paper focuses on building model that predicted the performance of computer science students in some courses they were examined through classification technique. The model built for the purpose of classification via decision tree classifier which was adopted in WEKA and KNIME analytics platform. The workflow model basically connected nodes to generate the decision trees while J4.8 Decision Tree Classifier programmable outputs were generated for the courses to obtain the confusion matrix and other instances. Bar Charts were plotted to display the students' performance in the courses. The mean absolute errors, RMS error and relative absolute error all read 0% while the kappa value obtained from the analysis ranged between 0.991 – 1.00 which perfectly agrees for most statistical values.

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How file access patterns influence interference among cluster applications

How file access patterns influence interference among cluste...

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IEEE International Conference on Cluster Computing

作者： Chih-Song Kuo Aamer Shah Akihiro Nomura Satoshi Matsuoka Felix Wolf Department of Computer Science RWTH Aachen University Aachen Germany German Research School for Simulation Sciences Laboratory for Parallel Programming Aachen Germany Tokyo Institute of Technology Global Scientific Information and Computing Center Tokyo Japan

On large-scale clusters, tens to hundreds of applications can simultaneously access a parallel file system, leading to contention and in its wake to degraded application performance. However, the degree of interference depends on the specific file access pattern. On the basis of synchronized time-slice profiles, we compare the interference potential of different file access patterns. We consider both micro-benchmarks, to study the effects of certain patterns in isolation, and realistic applications to gauge the severity of such interference under production conditions. In particular, we found that writing large files simultaneously with small files can slow down the latter at small chunk sizes but the former at larger chunk sizes. We further show that such effects can seriously affect the runtime of real applications-up to a factor of five in one instance. In the future, both our insights and profiling techniques can be used to automatically classify the interference potential between applications and to adjust scheduling decisions accordingly.

关键词： Interference Servers Throughput Benchmark testing Market research Degradation Aggregates

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