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IET Blockchain 2023年第4期3卷 182-193页

作者： Grybniak, Sergii Leonchyk, Yevhen Mazurok, Igor Nashyvan, Oleksandr Shanin, Ruslan Odessa National Polytechnic University Institute of Computer Systems Institute of Computer Systems Odesa Ukraine Odessa I.I. Mechnikov National University Faculty of Mathematics Physics and Information Technologies Odesa Ukraine

A consensus protocol is a crucial mechanism of distributed networks by which nodes can coordinate their actions and the current state of data. This article describes a BlockDAG consensus algorithm based on the Proof of Stake approach. The protocol provides network participants with cross-voting for the order of blocks, which, in the case of a fair vote, guarantees a quick consensus. Under conditions of dishonest behavior, cross-voting ensures that violations will be quickly detected. In addition, the protocol assumes the existence of a Coordinating network containing information about the approved ordering, which qualitatively increases security and also serves to improve network synchronization. © 2023 The Authors. IET Blockchain published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.

关键词： Blockchain

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Author Identification Based on Convolutional Neural Network 66

Author Identification Based on Convolutional Neural Network

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66th International Symposium ELMAR, ELMAR 2024

作者： Sebena, Marian Kacur, Juraj Zlacky, Matus Institute of Computer science and Mathematics FEI STU Bratislava81219 Slovakia Institute of Multimedia Information and Communication Technologies FEI STU Bratislava81219 Slovakia

ISBN: (纸本)9798350375411

In this study, we present an author identification model utilizing the capabilities of Convolutional Neural Networks (CNN). The primary focus of the study is on finding the optimal network structure, where the size of the extracted feature vectors by CNN is monitored in relation to the achieved accuracy. Additionally, the research examines the network structure and complexity such as the number of convolutional layers, their filters, the size and strides of pooling, etc. The proposed model demonstrates high effectiveness in identifying authors achieving an accuracy of 81.99% on test data classifying 50 authors. The model was trained and evaluated using the Reuters 50-50 dataset. These results highlight the potential of CNNs in author identification tasks. © 2024 IEEE.

关键词： Convolutional neural networks

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Organization of Storage and Processing of Experimental Results from the Continuous Process of Styrene-Butadiene Copolymerization Using Databases

Organization of Storage and Processing of Experimental Resul...

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2025 International Russian Smart Industry Conference, SmartIndustryCon 2025

作者： Mikhailova, Tatiana Mikhailov, Vladimir Mustafina, Svetlana Ufa University of Science and Technology Department of Mathematical and Computer Modeling Ufa Russia Institute of Computational Mathematics and Information Technologies Kazan Federal University Kazan Russia

ISBN: (纸本)9798331511241

The article presents an approach to storing and processing the results of industrial, laboratory, and computational experiments based on databases. The approach is presented on the example of the process of copolymerization of butadiene with styrene, which proceeds continuously in a cascade of series-connected ideal mixing reactors. A conceptual and logical database model of the industrial process under study has been created. The constructed structure can be adapted for other copolymerization processes, depending on the type of process, its formulation, and the process flow conditions. The presented physical model is implemented as a database and has been tested in the Microsoft SQL Server environment. © 2025 IEEE.

关键词： Data reduction

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Numerical Modelling of The System of Doubly Nonlinear Diffusion Equations with Convective Transfer and Damping

Numerical Modelling of The System of Doubly Nonlinear Diffus...

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2024 Cognitive Models and Artificial Intelligence Conference, AICCONF 2024

作者： Sadullaeva, Shakhlo Azimbaevna Anarova, Shahzoda Amanbayevna Khaydarov, Abdugaffor Fayzullayeva, Zarnigor Nazirova, Dilorom Mirkhodzhaeva, Nazhiba departament Intellegent systems Joint Belarusian-Uzbek Intersectoral Institute of Applied Technical Qualifications Tashkent Uzbekistan Department of Convergence of Digital Technologies Computer Engineering Faculty Tashkent University of Information Technologies Tashkent Uzbekistan Department of Applied Mathematics and Computer Analysis National University of Uzbekistan Tashkent Uzbekistan Department of Informatics Computer Engineering Faculty Tashkent University of Information Technologies Tashkent Uzbekistan Department of Applied Mathematics and Computer Analysis NUUz Tashkent Uzbekistan

ISBN: (纸本)9798400716928

Currently, studies of double nonlinear equations and systems of double nonlinear equations representing many processes found in nature are considered relevant and necessary. These equations and systems, as a rule, are nonlinear, degenerate, and have properties that are absent in linear theory and therefore make them quite difficult for both analytical and numerical analysis of the solution. For this reason, great attention is paid to the research of nonlinear mathematical models, the construction of efficient numerical solution schemes and algorithms, and the creation of software using the capabilities of computer technologies. In this article, the mathematical model of the diffusion process in a two-component nonlinear medium under the influence of time-dependent convective transfer and damping is studied. The calculation scheme, algorithm, and software for nonlinear problems were developed. Based on a study of the qualitative properties of a nonlinear mathematical model of a reaction-diffusion system, computer modeling of reaction-diffusion processes was carried out. The developed computational schemes, algorithms, and software packages for solving systems of parabolic equations with double nonlinearity provide high productivity in studying the theory and processes of numerical solutions of such problems. © 2024 ACM.

关键词： Nonlinear equations

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Intelligent Solution System for Cloud Security Based on Equity Distribution:Model and Algorithms

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computers, Materials & Continua 2024年第1期78卷 1461-1479页

作者： Sarah Mustafa Eljack Mahdi Jemmali Mohsen Denden Mutasim Al Sadig Abdullah M.Algashami Sadok Turki Department of Computer Science and Information College of Science at ZulfiMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Computer Science College of Computing and InformaticsUniversity of SharjahSharjahUnited Arab Emirates Higher Institute of Computer Science and Mathematics University of MonastirMonastir5000Tunisia Mars Laboratory University of SousseSousseTunisia Department of Logistic and Maintenance UFR MIM at MetzUniversity of LorraineMetzFrance Department of Computer and Information Technologies College of Telecommunicationand Information Riyadh CTITechnical and Vocational Training Corporation TVTCRiyadh12464Saudi Arabia Department of Computer Science Higher Institute of Applied Sciences of SousseSousse UniversitySousse4000Tunisia

In the cloud environment,ensuring a high level of data security is in high *** planning storage optimization is part of the whole security process in the cloud *** enables data security by avoiding the risk of data loss and data *** development of data flow scheduling approaches in the cloud environment taking security parameters into account is *** our work,we propose a data scheduling model for the cloud *** is made up of three parts that together help dispatch user data flow to the appropriate *** first component is the Collector Agent whichmust periodically collect information on the state of the network *** second one is the monitoring agent which must then analyze,classify,and make a decision on the state of the link and finally transmit this information to the *** third one is the scheduler who must consider previous information to transfer user data,including fair distribution and reliable *** should be noted that each part of the proposedmodel requires the development of its *** this article,we are interested in the development of data transfer algorithms,including fairness distribution with the consideration of a stable link *** algorithms are based on the grouping of transmitted files and the iterative *** proposed algorithms showthe performances to obtain an approximate solution to the studied problem which is an NP-hard(Non-Polynomial solution)*** experimental results show that the best algorithm is the half-grouped minimum excluding(HME),with a percentage of 91.3%,an average deviation of 0.042,and an execution time of 0.001 s.

关键词： Cyber-security cloud computing cloud security algorithms heuristics

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Development of an Intelligent System for Recognizing Composite Materials 25

Development of an Intelligent System for Recognizing Composi...

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25th IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2024

作者： Farahov, Rustam R. Burnashev, Rustam A. Bolsunovskaya, Marina V. Institute of Computational Mathematics and Information Technologies Kazan Federal University Kazan Russia Institute of Computer Science and Technology Peter the Great St. Petersburg Polytechnic University St. Petersburg Russia

ISBN: (纸本)9798350389234

The paper presents 'Expert-Polymer', an educational intelligent system that calculates particles of powders of composite materials for 3D printing using selective laser sintering technology. The system includes a particle image analysis that uses 3D scanning to analyze the structure of particles from all sides and determine their shape, as well as spectroscopy to identify the composition of the composite material. The intelligent system is intended to be implemented in production through the use of optical instruments. Furthermore, there are plans to introduce this system for research and production purposes, with the aim of training future specialists in the field of additive manufacturing. In order to obtain images of composite material particles from optical measuring devices, Internet of Things technology will be utilized. The technology allows for the receipt of color images from remote users and the transfer of completed analysis results to them. Particle recognition is achieved through the use of a pre-trained convolutional neural network to convolve a color image. © 2024 IEEE.

关键词： Laser heating

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Designing a Medical Fuzzy Expert System Using the JFuzzyLogic Library 25

Designing a Medical Fuzzy Expert System Using the JFuzzyLogi...

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25th IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2024

作者： Burnashev, Rustam A. Bagymanov, Ruslan M. Enikeeva, Adelya I. Farahov, Rustam R. Bolsunovskaya, Marina V. Institute of Computational Mathematics and Information Technologies Kazan Federal University Kazan Russia Institute of Computer Science and Technology Peter the Great St. Petersburg Polytechnic University St. Petersburg Russia

ISBN: (纸本)9798350389234

The article presents the processes of designing a medical expert system using software tools that work with fuzzy logic. Using a simplified fuzzy inference algorithm, it was possible to achieve the fuzziness of the system by creating a knowledge base of fuzzy rules that are adjusted to take into account changes in input data (fuzzification) and output data (defuzzification). The knowledge base was formed using the open source software library JFuzzyLogic (Java programming language). The study developed a UML activity diagram and identified the steps that researchers can use to create their own intelligent systems. A unified system that combines the components of a medical information system with the created knowledge base will contribute to more efficient data processing and analysis in scientific research. Filling and processing of the knowledge base of the expert system is available to an expert of the subject area. The created knowledge base includes all the necessary functions for processing fuzzy data, setting the necessary weights for input, output and data processing. © 2024 IEEE.

关键词： fuzzy expert systems fuzzy logic intelligent search JFuzzyLogic knowledge base medical data

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Verification of Genuineness of Educational Internet Resources Using Machine Learning Methods 4

Verification of Genuineness of Educational Internet Resource...

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4th International Conference on Technology Enhanced Learning in Higher Education, TELE 2024

作者： Privalov, Aleksandr N. Smirnov, Vadim A. Institute of Advanced Information Technologies Tula State Lev Tolstoy Pedagogical University Tula Russia Ivanovo State University Department of Mathematics Computer Science and Teaching Methods Shuya Russia

ISBN: (纸本)9798350353532

The analysis of various sources has been carried out, confirming the demand for protective solutions against information threats from fake websites of organizations. The relevance of the research topic is confirmed by the presence of addresses similar in spelling to popular educational Internet resources in the list of domain names of the RU zone registered over the past year. When developing security solutions, it is proposed to use a site verifying the genuineness method based on the use of machine learning algorithms. A review of research by various authors has been conducted in order to determine the most frequently used features for verifying the genuineness of Internet resources in the machine learning models. The authors propose their own verifying the genuineness features that can be used in a situation where data about an Internet resource is extracted from the domain name registry. The proposed features differ from the known ones in that they contain signs of micro-markup on the site and storage of site settings files for search engines on servers. The developed features were tested using a naive Bayesian classifier as a machine learning algorithm. The proposed features can be used in the implementation of a software tool to counteraction threats from fake educational sites. © 2024 IEEE.

关键词： Adversarial machine learning

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Prediction of Solar Energy from Sky Images and Meteorological Data Using Neural Networks 65

Prediction of Solar Energy from Sky Images and Meteorologica...

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65th International Symposium ELMAR, ELMAR 2023

作者： Sebena, Marian Kacur, Juraj Institute of Computer Science and Mathematics FEI STU Bratislava812 19 Slovakia Institute of Multimedia Information and Communication Technologies FEI STU Bratislava812 19 Slovakia

ISBN: (纸本)9798350325126

Many of the renewable energy generation methods suffer from the variable power output they produce. This is because they depend on elements with a substantial stochastic nature. To mitigate the variability different controlling mechanisms must be deployed. For thorough and optimal control, it is a necessity to predict the generated power in the near or more distant future. In this article, we explore the possibility of predicting electricity production by photovoltaic panels based on sky images. In addition, we also tested selected meteorological data that are relevant and available. For this purpose, we used SkyCam dataset that contains required information. We have proposed 3 scenarios combining block-based and sequential processing of sky images and selected meteorological data using CNN and LSTM networks. The best results were obtained by a combination of sky images and meteorological data processed as sequence of frames by LSTM. The achieved mean absolute error was 44.3 W/m2 for 15-minute intervals. © 2023 IEEE.

关键词： Forecasting

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Development of a Method and System for Recycling Polystyrene Production Waste 25

Development of a Method and System for Recycling Polystyrene...

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25th IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2024

作者： Farahov, Rustam R. Burnashev, Rustam A. Enikeeva, Adelya I. Bolsunovskaya, Marina V. Institute of Computational Mathematics and Information Technologies Kazan Federal University Kazan Russia Institute of Information Technology and Intelligent Systems Kazan Federal University Kazan Russia Institute of Computer Science and Technology Peter the Great St. Petersburg Polytechnic University St. Petersburg Russia

ISBN: (纸本)9798350389234

Currently, the consumption of natural resources is important for humanity. Therefore, reducing the production of production waste not only saves natural resources, but also increases the profit of the manufacturer. When producing polystyrene powder, the waste produced is a coarse powder with a wide range of particle sizes and irregular geometry. It is possible to obtain low-grade products from waste, such as disposable tableware, industrial containers, Petri dishes, etc. Manufacturers are interested in developing new processing methods to use waste materials to produce high-quality products. The purpose of the work is to study the possibility of using polystyrene production waste in selective laser sintering processes. The method we are developing for processing polystyrene-based polymer powder allows us to avoid the use of additional chemical exposure, and to select the optimal operating mode for a selective laser sintering installation with the resulting processed material. It is planned to introduce this method into the field of materials processing for additive manufacturing. © 2024 IEEE.

关键词： Laser heating

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