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Processing of Fuzzy Queries and Software Implementation to a Relational Database of Wholesale and Retail Commercial Enterprises

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Procedia Computer Science 2016年 102卷 490-494页

作者： Kenan Kilic Tarlan Abdullayev Ramiz Alakbarov Nuray Kilic Department of Computer Engineering Qafqaz University Baku AZ0101 Azerbaijan Department of ScientificbAffairs Odlar Yurdu University Baku AZ1072 Azerbaijan Information Technology and Programming Azerimed Ltd AZ1147 Azerbaijan Department of Business Administration Qafqaz University Baku AZ0101 Azerbaijan

In the article the detection of “missing” or “hidden” data during the processing of the well-defined queries to database is discussed and on terms of quality the importance is justified, the article also covers or... 详细信息

关键词： information systems relational databases fuzzy queries SQL queries fuzzy association

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Foundations of Intelligent Systems 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Troels Andreasen Henning Christiansen Juan-Carlos Cubero Zbigniew W. Raś

ISBN: (数字)9783319083261

ISBN: (纸本)9783319083254

This book constitutes the refereed proceedings of the 21st International Symposium on Methodologies for Intelligent Systems, ISMIS 2014, held in Roskilde, Denmark, in June 2014. The 61 revised full papers were carefully reviewed and selected from 111 submissions. The papers are organized in topical sections on complex networks and data stream mining; data mining methods; intelligent systems applications; knowledge representation in databases and systems; textual data analysis and mining; special session: challenges in text mining and semantic information retrieval; special session: warehousing and OLAPing complex, spatial and spatio-temporal data; ISMIS posters.

关键词： Artificial Intelligence Data Mining and Knowledge Discovery Database Management information Storage and Retrieval information Systems Applications (incl. Internet) User Interfaces and Human Computer Interaction

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Creating a Dynamic Online Learning Environment with AI Integration

Creating a Dynamic Online Learning Environment with AI Integ...

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International Computer Sciences and information Technologies (CSIT)

作者： Oleksandra Bulgakova Zarina Viniarska Viacheslav Zosimov P.M Platonov Educational and Scientific Institute of Computer Engineering Automation Robotics and Computer Programming Odesa National University of Technology Odesa Ukraine Department of Applied information systems Taras Shevchenko National University of Kyiv Kyiv Ukraine

ISBN: (数字)9798331542634

ISBN: (纸本)9798331542641

Educational, online learning has become a common practice due to rapid digitalization and recent global events. This study focuses on developing a comprehensive online learning platform that addresses users' needs by integrating advanced AI capabilities for personalized support and adaptive learning. The platform supports user registration and authentication, course and lesson management, and offers interactive features like AI-driven chat support. In this study, we show the importance of creating user-friendly online learning platforms with the implementation of modern AI trends. The development and testing of this platform is ongoing to determine the adaptation of the system to different learning styles.

关键词： Adaptive learning Electronic learning Authentication Passwords Market research Real-time systems Artificial intelligence information technology Standards Testing

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A Horizontal Federated Learning Approach to IoT Malware Traffic Detection: An Empirical Evaluation with N-BaIoT Dataset 26

A Horizontal Federated Learning Approach to IoT Malware Traf...

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26th International Conference on Advanced Communications technology, ICACT 2024

作者： Do, Phuc Hao Le, Tran Duc Vishnevsky, Vladimir Berezkin, Aleksandr Kirichek, Ruslan The Bonch-Bruevich Saint-Petersburg State University of Telecommunications Saint-Petersburg Russia Danang Architecture University Da Nang Viet Nam University of Telecommunications Department of Communication Networks and Data Transmission at Bonch-Bruevich Saint-Petersburg State Russia University of Science and Technology The University of Danang Da Nang Viet Nam The University of Danang University of Science and Technology Information Technology Faculty Danang Viet Nam V. A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences Moscow Russia Institute of Control Sciences of Russian Academy of Sciences Russia Bonch Bruevich Saint Petersburg State University of Telecommunications Department of Programming Engineering and Computer Science Russia

ISBN: (纸本)9791188428120

The increasing prevalence of botnet attacks in IoT networks has led to the development of deep learning techniques for their detection. However, conventional centralized deep learning models pose challenges in simultaneously ensuring user data privacy and detecting botnet attacks. To address this issue, this study evaluates the efficacy of Federated Learning (FL) in detecting IoT malware traffic while preserving user privacy. The study employs N-BaIoT, a dataset of real-world IoT network traffic infected by malware, and compares the effectiveness of FL models using Convolutional Neural Network, Long Short-Term Memory, and Gated Recurrent Unit models with a centralized approach. The results indicate that FL can achieve high performance in detecting abnormal traffic in IoT networks, with the CNN model yielding the best results among the three models evaluated. The study recommends the use of FL for IoT malware traffic detection due to its ability to preserve data privacy. © 2024 Global IT Research Institute - GIRI.

关键词： Malware

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Recursive Neyman Algorithm for Optimum Sample Allocation under Box Constraints on Sample Sizes in Strata

arXiv

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arXiv 2023年

作者： Wesolowski, Jacek Wieczorkowski, Robert Wójciak, Wojciech Programming Coordination of Statistical Surveys and Registers Department Statistics Poland Aleja Niepodleglości 208 Warsaw00-925 Poland Faculty of Mathematics and Information Science Warsaw University of Technology ul. Koszykowa 75 Warsaw00-662 Poland

The optimum sample allocation in stratified sampling is one of the basic issues of survey methodology. It is a procedure of dividing the overall sample size into strata sample sizes in such a way that for given sampling designs in strata the variance of the stratified π estimator of the population total (or mean) for a given study variable assumes its minimum. In this work, we consider the optimum allocation of a sample, under lower and upper bounds imposed jointly on sample sizes in strata. We are concerned with the variance function of some generic form that, in particular, covers the case of the simple random sampling without replacement in strata. The goal of this paper is twofold. First, we establish (using the Karush-Kuhn-Tucker conditions) a generic form of the optimal solution, the so-called optimality conditions. Second, based on the established optimality conditions, we derive an efficient recursive algorithm, named RNABOX, which solves the allocation problem under study. The RNABOX can be viewed as a generalization of the classical recursive Neyman allocation algorithm, a popular tool for optimum allocation when only upper bounds are imposed on sample strata-sizes. We implement RNABOX in R as a part of our package stratallo which is available from the Comprehensive R Archive Network (CRAN) repository. Copyright © 2023, The Authors. All rights reserved.

关键词： Sampling

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Data poisoning: issues, challenges, and needs

Data poisoning: issues, challenges, and needs

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7th IET Smart Cities Symposium (SCS 2023)

作者： Mohammad Aljanabi Alaa Hamza Omran Maad M Mijwil Mostafa Abotaleb El-Sayed M. El-kenawy Sahar Yousif Mohammed Abdelhameed Ibrahim Department of computer College of Education Aliarqai university Baghdad Iraq University of information technology and communications Baghdad Iraq Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt Computer Science Department Computer Science & Information Technology College Anbar University Anbar Iraq Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

Data poisoning attacks, where adversaries manipulate training data to degrade model performance, are an emerging threat as machine learning becomes widely deployed in sensitive applications. This paper provides a comprehensive overview of data poisoning including attack techniques, adversary incentives, impacts on security and reliability, detection methods, defenses, and key research gaps. We examine label flipping, instance injection, backdoors, and other attack categories that enable malicious outcomes ranging from IP theft to accidents in autonomous systems. Promising detection approaches include statistical tests, robust learning, and forensics. However, significant challenges remain in translating academic defenses like adversarial training and sanitization into practical tools ready for operational use. With safety and trustworthiness at stake, more research on benchmarking evaluations, adaptive attacks, fundamental tradeoffs, and real-world deployment of defenses is urgently needed. Understanding vulnerabilities and developing resilient machine learning pipelines will only grow in importance as data integrity is fundamental to developing safe artificial intelligence.

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Algebraic models of application of computer systems and information technologies

Algebraic models of application of computer systems and info...

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IEEE International Scientific Conference on Informatics

作者： Volodymyr Ovsyak Oleksandr Ovsyak Dmytro Bui Julia Petruszka Dept. Application of Informatics Kielce University of Technology Kielce Poland Dept. Kino and Arts National University of Culture and Arts L'viv Ukraine Department of Theory and Technology of Programming Taras Shevchenko National University of Kyiv Kyiv Ukraine Dept. Automatic and Information Technology Ukrainian University of Printing L'viv Ukraine

The mathematical models of diagrams of using cases of computer systems and information technologies (for Microsoft Visual *** platform) are built in the forms of Glushkov's algorithmic algebra systems, Zeitlin-Pogorilyi's modified algorithmic algebra systems, modified algorithmic algebras and primitive program algebras (PPA), which is an example of programing algebra class of composite type. Property of monotonicity and continuity is established for the branching operation of PPA as the corollary of the representation of branching operation in terms of set-theoretic constructions of function restriction over set using the properties of monotonicity and distributivity of function restriction and whole image of set with respect to binary relation.

关键词： Algebra Unified modeling language Computational modeling Computers information technology Mathematical model Visualization

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Methodology of Teaching programming Science Through Online Platforms

Methodology of Teaching Programming Science Through Online P...

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Informatics, Electronics, and Radio Engineering (PIERE), International Conference Problems of

作者： Akram Nishanov Oybek Allamov Janar Yusupova Marks Matyakubov Baxtiyor Qalandarov Reyimberganov Bahrom Department of Systematic and Practical Programming 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 Master of Urgench branch of TATU named after Muhammad al-Khwarizmi Urgench Branch of Tashkent University of Information Technology named after Muhammad al-Khwarizmi Urgench Uzbekistan Student of Urgench branch of TATU named after Muhammad al-Khwarizmi Urgench Branch of Tashkent University of Information Technology named after Muhammad al-Khwarizmi Urgench Uzbekistan

ISBN: (数字)9798331516321

ISBN: (纸本)9798331516338

This article presents an experiment conducted among students of the Faculty of “Software Engineering” of the Urgench branch of TATU named after Muhammad al-Khwarizmi. Teaching programming using online platforms in education has shown promising results in improving student outcomes. This article discusses the methodology used, the comparative results, and the impact of the platform on software education. The rapid adoption of online platforms in education has changed the way programming is taught, providing students with an interactive, hands-on learning environment. This shift is especially relevant in teaching programming, where real-time feedback and practice are essential to mastering algorithms and coding concepts. The study compared two groups: one was trained using the https://***/platform and the assignments were checked using this system, and the second group was trained using traditional methods. The results showed that students who used the online platform had a high level of mastery, which highlighted the effectiveness of integrating https://***/into programming education.

关键词： Education Software algorithms Real-time systems Software Encoding Computer science education Problem-solving Informatics programming profession

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Speaker's Emotions Recognition Module Based on the GoogleLeNet Neural Network

Speaker's Emotions Recognition Module Based on the GoogleLeN...

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2022 International Conference on Smart information Systems and Technologies, SIST 2022

作者： Tereikovskyi, Ihor Tereikovska, Liudmyla Kryvoruchko, Olena Tereikovskyi, Oleh Tyshchenko, Dmytro Franchuk, Tamara National Technical University Of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Dept. Of System Programming And Specialized Computer Systems Kyiv Ukraine Kyiv National University Of Construction And Architecture Dept. Of Information Technology For Design And Applied Mathematics Kyiv Ukraine Kyiv National University Of Trade And Economics Dept. Of Software Engineering And Cyber Security Kyiv Ukraine National Technical University Of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Dept. Of Department Of Computer Engineering Kyiv Ukraine

ISBN: (数字)9781665467902

ISBN: (纸本)9781665467902

The article is devoted to the development of means for recognition of the emotions of the speaker, based on the neural network analysis of fixed fragments of the voice signal. The possibility of improving recognition tools through the use of a convolutional neural network of the GoogLeNet type is shown. The expediency of training the network on the examples of the TESS database is determined. A procedure for representing a voice signal in the form of a square grayscale image has been developed. Based on the use of the specified database, the modification of the GoogLeNet network was carried out. The architecture and software implementation of the recognition module have been developed. With the help of computer experiments, it has been established that after 150 epochs of training on a fairly limited training sample, the modified GoogLeNet makes it possible to achieve an accuracy of recognition of the speaker's emotions of approximately 0.97 on test examples. The obtained accuracy is comparable to the accuracy of the best modern systems of this purpose and confirms the promise of using neural network models like GoogLeNet for emotion recognition based on voice signal analysis. The need for further research aimed at reducing the resource intensity of the neural network model is shown. © 2022 IEEE.

关键词： Emotion Recognition

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The Studying of Hydrogen Diffusion Non-Stationary Processes Near a Crack in the Field of Heterogeneous Mechanical Tensions for the Encapsulated MEMS Devices

The Studying of Hydrogen Diffusion Non-Stationary Processes ...

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International Conference on Perspective Technologies and Methods in MEMS Design (MEMSTECH)

作者： Winfried Auzinger Roksolyana Stolyarchuk Yaroslav Pelekh Oksana Kozar Serhii Mentynskyi Mykola Ihnatyshyn Institute for Analysis and Scientific Computing Vienna University of Technology (TU Wien) Wien Austria Department of Computational Mathematics and Programming Lviv Polytechnic National University Lviv Ukraine Department of Mechanical Engineering Natural Sciences and Information Technologies Mukachevo State University Mukachevo Ukraine Department of Light Industry and Professional Education Mukachevo State University Mukachevo Ukraine

ISBN: (数字)9781728171807

ISBN: (纸本)9781728171814

In this paper we study an elastic-plastic isotropic body weakened by a rectilinear crack, directed along the abscissa axis, under the action of stresses symmetrical about its plane. An approximate (analytical and numerical) solution of this problem is constructed under the condition that the hydrostatic deformation of the split expansion is approximated by a parabola. The concentration of hydrogen near the top of the crack is calculated. Note that when using the above calculation formulas, at each node we get several approximations to the exact solution. In the proposed methods, only three appeals to the right-hand side of the differential equation are necessary to obtain both the third order accuracy method and the two approximations (upper and lower) of the second order of accuracy.

关键词： mathematical model elastic-plastic isotropic body hydrogen diffusion internal crack continued fractions two-sided approximations nonlinear methods diffusion of hydrogen internal cracks MEMS devices cracks Cocaine Fissure Mathematical Model Continued fraction Fields

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