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Advanced Technology (KhPIWeek), IEEE KhPI Week on

作者： Mykola Zamkovyi Svitlana Gavrylenko Kyrylo Khatsko Nataliia Khatsko dept. Information Systems and Technologies National Technical University «Kharkiv Polytechnic Institute» Kharkiv Ukraine Department of Computer Engineering and Programming National Technical University “Kharkiv Polytechnic Institute” Kharkiv Ukraine

The Internet of Things (IoT) today already connects billions of different IoT devices with the Internet. With the advent of new services and services, new challenges arise: how to make a cloud service publicly available, and reliable, how and where to store data. The article considers an example of the implementation of an IoT application with cloud components, considers the implementation of connecting IoT components to a cloud provider, and presents the IoT architecture. The focus is on the architecture and implementation of data exchange protocols, the implementation of protocols? for data collection and management of remote system components Given the large amount of data transmitted by IoT devices to the cloud, data compression and interaction with cloud services is a very relevant topic. Therefore, the article also offers recommendations for managing the traffic of IoT devices. The purpose of this article is to provide a description and algorithm for connecting IoT devices to the cloud, to bring together disparate information, and make it open and understandable to beginners and academic researchers.

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Traffic and road sign recognition using deep convolutional neural network

Traffic and road sign recognition using deep convolutional n...

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2021 International Conference on Information Science and Communications Technologies, ICISCT 2021

作者： Kuchkorov, Temurbek Khamzaev, Jamshid Allamuratova, Zamira Ochilov, Temur Tashkent University of Information Technologies Nmaed after Muhammad Al-Khwarizmi Department of Computer Systems Tashkent Uzbekistan Tashkent University of Information Technologies Nmaed after Muhammad Al-Khwarizmi Joint Faculty TUIT-BSUIR Department of Information-computer Technologies and Programming Tashkent Uzbekistan

ISBN: (纸本)9781665432580

Automatic road sign recognition is one of the most important steps to help a driver prevent accidents. In this paper, the deep convolutional neural network (Deep CNN) was used for the autonomous traffic and road signs detection and recognition system. The proposed system works in real-time recognition of the image of road signs. The contribution of this article is that it consists of a newly developed datasets for 42 different road signs using combination of existing datasets and collected local road signs. The images were taken from different angles and included other parameters and conditions. More than 30K images were collected to create the dataset, which is named Uzbekistan traffic and road signs (UZ-TRS-2021). The CNN architecture was used with various parameters to achieve the best recognition speed. Experimental results show that the proposed CNN architecture achieved 98% accuracy. © 2021 IEEE.

关键词： Convolutional neural networks

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Modeling of DC Traction Motor In Ansys RMXPRT

Modeling of DC Traction Motor In Ansys RMXPRT

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Advanced Technology (KhPIWeek), IEEE KhPI Week on

作者： Vitalii Herasymenko Vladyslav Pliuhin Valentyn Noskov Oleksandr Zakovorotnyi Mykola Mezentsev Tetyana Orlova Department of Electric Transport O. M. Beketov National University of Urban Economy in Kharkiv Kharkiv Ukraine Department of the Systems of Electricity Supply and Electricity Consumption of Cities O. M. BeketovNational University of Urban Economy in Kharkiv Kharkiv Ukraine Department of Computer Engineering and Programming National Technical University «Kharkiv Polytechnic Institute» Kharkiv Ukraine Computer Engineering and Programming Department National Technical University “Kharkiv Polytechnic Institute” Kharkiv Ukraine

DC traction motors are widely used in all branches of urban economy. They began to be used in industry about a hundred years ago with the advent of the first calculation methods. When designing a DC motor, it is important to consider it comprehensively, together with the electric drive system. The article discusses the application of a more correct approach to modeling a series-excited DC motor using the ANSYS software package, in particular, the ANSYS RMxprt / Maxwell/ Simplorer bundle. The main stages of initial data input are considered and the main calculation results are shown. Using ANSYS Maxwell allows you to quickly and automatically build a typical machine geometry using RMxprt. When solving non-standard structures, it is possible to use 3D design with step-by-step elements. The analysis of the obtained graphic dependences of electric power parameters makes it possible to judge the efficiency of the electric motor and its operational properties in idling and under load. The simulation results show excellent agreement with the data obtained experimentally.

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A generative approach for user-centered, collaborative, domain-specific modeling environments

arXiv

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arXiv 2021年

作者： Zweiho, Philip Steffen, Bernhard Programming Systems Department of Computer Science Tu Dortmund University Dortmund44227 Germany

The use of low- and no-code modeling tools is today an established way in practice to give non- programmers an opportunity to master their digital challenges independently, using the means of model- driven software development. However, the existing tools are limited to a very small number of different domains such as mobile app development, which can be attributed to the enormous demands that a user has on such a tool today. These demands exceed the mere use of a modeling environment as such and require crosscutting concerns such as: easy access, direct usability and simultaneous collaboration, which result in additional effort in the realization of such tools. Our solution is based on the idea to support and simplify the creation of new domain-specific holistic tools by generating it entirely based on a declarative specification with a domain-specific meta-tool. The meta-tool Pyro demonstrated and analyzed here focuses on graph-based graphical languages to fully generate a complete, directly executable tool starting from a meta-model in order to meet all cross-cutting requirements. Copyright © 2021, The Authors. All rights reserved.

关键词： Specifications

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Analysis of Hardware and Software Tools for Implementation of Cognitive Radio Networks

Analysis of Hardware and Software Tools for Implementation o...

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2022 International Conference on Information Science and Communications Technologies, ICISCT 2022

作者： Reypnazarov, Ernazar Khujamatov, Halimjon Khasanov, Doston Allamuratova, Zamira Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi Tashkent Uzbekistan Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi The Computer Enjineering Faculty Tashkent Uzbekistan Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi Department of Data Communication Networks and Systems Tashkent Uzbekistan Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi Department of Information-Computer Technologies and Programming Tashkent Uzbekistan

ISBN: (纸本)9781665472296

This paper analyzes of the hardware and software tools for implementing a cognitive radio network. In particular, software-configurable radio modules, which are considered the main element of the cognitive network, were studied according to their main characteristics, among which the widely used ones were comparatively analyzed. As a result of the analysis, the HackRF One device was selected as the most preferred option for cognitive network research, and its working principles, structure, and characteristics were revealed in detail. It also provides information about the GNU Radio software environment and its capabilities, which are used to operate the HackRF One device. © 2022 IEEE.

关键词： Digital signal processing

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A recommender system for WordPress themes using item-based collaborative filtering technique 29

A recommender system for WordPress themes using item-based c...

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29th International Scientific Conference Electronics, ET 2020

作者： Ujkani, Berat Minkovska, Daniela Stoyanova, Lyudmila Technical University of Sofia Faculty of Computer Systems and Technologies Department of Programming and Computer Technologies 8 Kliment Ohridski blvd Sofia1000 Bulgaria

ISBN: (纸本)9781728174266

Recommender systems allow making personalized recommendations for items or products while browsing online, using numerous algorithms and techniques to predict and recommend potentially useful items to a specific user. This paper presents a system built for the purpose of filtering out WordPress themes trough the ratings or reviews of other similar users using item-based collaborative filtering technique and provide user-specific recommendations for the largest online marketplace of web templates called Themeforest, part of Envato marketplaces. © 2020 IEEE.

关键词： Collaborative filtering

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Storage of key Features of Images of Sulfur Imprints in the Mathematical Structure Form

Storage of key Features of Images of Sulfur Imprints in the ...

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2020 International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2020

作者： Bagaev, I.I. Logunova, O.S. Institute of Energy and Automated Systems Nosov Magnitogorsk State Technical University Department of Computer Engineering and Programming Magnitogorsk Russia

ISBN: (纸本)9781728169514

The aim of the study is to develop a method for storing images of sulfur imprints. In the framework of the study, a more effective method of representing images of sulfur imprints by using knowledge of the specificity of these images was developed compared to universal methods. In particular, a method for storing images of sulfur imprints has been developed, which stores information about objects that are significant for technological analysis in the image. The developed method was tested for images of sulfur imprints of continuously cast billets for the conditions of a large metallurgical enterprise in Russia. To conduct a computational experiment, a software product was designed and developed that allows you to convert the image of a sulfur imprint into a mathematical representation, as well as the process of restoring the main image. Using the array of retrospective information of 2011-2018 and the developed software product, the calculation of the effectiveness of the presentation of graphic information in the form of a structural unit of information without directly saving the image was performed. The average share of stored information from the original volume is 0.53 percent © 2020 IEEE.

关键词： Sulfur

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Research of Energy Detection Method in Spectrum Sensing in Cognitive Radio Networks

Research of Energy Detection Method in Spectrum Sensing in C...

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2022 International Conference on Information Science and Communications Technologies, ICISCT 2022

作者： Reypnazarov, Ernazar Khujamatov, Halimjon Khasanov, Doston Allamuratova, Zamira Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi Tashkent Uzbekistan Computer Enjineering Faculty Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi Tashkent Uzbekistan Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi Department of Data Communication Networks and Systems Tashkent Uzbekistan Department of Information-Computer Technologies and Programming Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi Tashkent Uzbekistan

ISBN: (纸本)9781665472296

This paper presents the threshold value determination model, its implementation algorithm, and the characteristics of the threshold value depending on the probability of false signal detection, developed for the purpose of researching the method of energy determination in spectrum sensing in cognitive radio networks. Also, the main methods of single-band spectrum sensing in cognitive radio networks were initially studied in the article, and the main spectrum detection algorithms were comparatively analyzed. © 2022 IEEE.

关键词： Cognitive radio

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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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Lookback Period, Epochs and Hidden States Effect on Time Series Prediction Using a LSTM based Neural Network 28

Lookback Period, Epochs and Hidden States Effect on Time Ser...

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28th National Conference with International Participation, TELECOM 2020

作者： Koparanov, Kiril Andreev Georgiev, Krasin Krasimirov Shterev, Vasil Aleksandrov Technical University of Sofia Faculty of Computer Systems and Technologies Department of Programming and Computer Technologies 8 Kliment Ohridski blvd. Sofia1000 Bulgaria

ISBN: (纸本)9781728187174

Forecasting time series problem occurs in various subject areas. Recently neural network techniques have been used for solving such tasks. However, they have not been sufficiently studied. The article explores the influence of the lookback period, the training epochs, and hidden state dimensionality in forecasting time series using long short-term memory. Numerical experiments with example financial data show that using more lags does not improve the results. Such a study of model parameters is important for their proper selection. © 2020 IEEE.

关键词： Time series

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