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16th International Conference Management of Large-Scale System Development, MLSD 2023

作者： Kulba, Vladimir Medennikov, Viktor V.A. Trapeznikov Institute of Control Sciences of the Russian Academy of Sciences Laboratory of Modular Data Processing and Control Systems Moscow Russia Federal Research Center 'Computer Science and Control' of the Russian Academy of Sciences Information and Computing Systems Department Moscow Russia

ISBN: (纸本)9798350337907

The paper considers a mathematical model for managing a scientific digital ecosystem exemplified by the agriculture case;the model enables assessing the impact science exerts on the regions' socioeconomic position in order to build an adequate response to the advanced economies' regime of severe sanctions against Russia. For these purposes, a systemic analysis of the subject identification and classification of ecosystems was conducted to address the critical issue of determining the basic concepts and terms of the country's digitalization. © 2023 IEEE.

关键词： Agriculture

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An Intelligent Method for Recognizing Real and Generated Ukrainian-Language Voices

An Intelligent Method for Recognizing Real and Generated Ukr...

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Advanced Technology (KhPIWeek), IEEE KhPI Week on

作者： Khrystyna Lipianina-Honcharenko Dmytro Lendiuk Adam Ivaniush Gena Boguta Mariana Soia Khrystyna Yurkiv Department for Information-Computing Systems and Control West Ukrainian National University Ternopil Ukraine

ISBN: (数字)9798350384499

ISBN: (纸本)9798350384505

The modern development of speech synthesis technologies and convolutional neural networks (CNN) creates new opportunities and challenges in the field of voice recognition. One of the key tasks is to ensure the security and authenticity of audio information, especially in the context of information warfare and disinformation campaigns. In this context, the ability to recognize and identify generated voices becomes particularly important. This study aims to develop an intelligent method for recognizing real and generated Ukrainian-language voices using convolutional neural networks. The proposed method is based on the careful collection and preparation of data, the development and training of a CNN model, and its validation on test samples. Special attention is paid to ensuring the balance of the dataset, which is crucial for preventing model bias and improving its ability to generalize to unknown data. The model shows high performance in detecting real and generated voices, making this approach useful for local applications, particularly in Ukraine.

关键词： Training Accuracy Video on demand Speech recognition Mathematical models Data models Convolutional neural networks Web sites Speech synthesis Fake news

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System Analysis of Digital Ecosystem of Russian Agriculture 15

System Analysis of Digital Ecosystem of Russian Agriculture

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15th International Conference Management of Large-Scale System Development, MLSD 2022

作者： Medennikov, Viktor Flerov, Yuri Federal Research Center 'Computer Science and Control' of the Russian Academy of Sciences Information and Computing Systems Department Moscow Russia

ISBN: (数字)9781665497015

ISBN: (纸本)9781665497015

The paper discusses the methods that may be used to set up a science-based digital ecosystem for agriculture;these methods are based on the ideas proposed by A. Kitov and Academician V. Glushkov about a national automated information system (NAIS) for information collection and processing for accounting, planning, and management in the national economy, and substantiated by mathematical modeling. We focus on the need to ontologically integrate two basic digital ecosystem platforms: one for production and another for research and education. © 2022 IEEE.

关键词： Agriculture

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Cluster Synchronization of Kuramoto Oscillators via Pacemakers and Mean-phase Feedback control 63

Cluster Synchronization of Kuramoto Oscillators via Pacemake...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Kokubo, Ryota Matsubara, Mitsuaki Kato, Rui Ishii, Hideaki Tokyo Institute of Technology Department of Computer Science Yokohama226-8502 Japan Tokyo Institute of Technology Department of Systems and Control Engineering Yokohama226-8502 Japan Villeurbanne69622 France The University of Tokyo Department of Information Physics and Computing Tokyo113-8656 Japan

ISBN: (纸本)9798350316339

Brain networks typically exhibit characteristic synchronization patterns where several synchronized clusters coexist. On the other hand, neurological disorders are considered to be related to pathological synchronization such as excessive synchronization of large populations of neurons. Motivated by these phenomena, this paper presents two approaches to control the cluster synchronization of Kuramoto oscillators. One is based on the use of pacemakers to the clusters, and the other is based on feeding back the mean phases to the clusters. We first show conditions on the pacemaker weights and the feedback gains for the network to achieve cluster synchronization. Then, we propose a method to find optimal feedback gains through convex optimization. A numerical example demonstrates the effectiveness of the proposed methods. © 2024 IEEE.

关键词： Pacemakers

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From Digital Management Platform Development to a Computer-Aided Crop Rotation Engineering System in Agriculture

From Digital Management Platform Development to a Computer-A...

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International Conference on Management of Large-Scale System Development (MLSD)

作者： Viktor Medennikov Information and Computing Systems Department Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences Moscow Russia

ISBN: (数字)9798350375718

ISBN: (纸本)9798350375725

Thepaper deals with a formalized description of a computer-aided crop rotation engineering system based on a mathematical crop system optimization model implemented in the digital platform for industry management that would offer an ontological and functional integration of farming industry objectives from the joint science-based point of view. The paper demonstrates that when it comes to the digital economy, crop rotation should be the focal point in precision agriculture that all the farming processes are based on.

关键词： Precision agriculture Optimization models Computational modeling Crops Large-scale systems Farming

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Hierarchical Game with Cooperative Behavior of Lower Level Players

Hierarchical Game with Cooperative Behavior of Lower Level P...

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International Conference on Management of Large-Scale System Development (MLSD)

作者： Mikhail Gorelov Department of Information and Computing Systems Federal Research Center “Computer Science and Control “of the Rassian Academy of Sciences Moscow Russia

A model of a two-level hierarchical system with many participants is studied assuming that lower-level elements choose Pareto optimal outcomes. Two classes of games are studied: without feedback and with feedback. The... 详细信息

ISBN: (数字)9798350375718

ISBN: (纸本)9798350375725

关键词： Hierarchical systems Process control Games Pareto optimization Large-scale systems

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Network Intrusion Detection Based on Feature Selection and Hybrid Metaheuristic Optimization

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Computers, Materials & Continua 2023年第2期74卷 2677-2693页

作者： Reem Alkanhel El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Manal Abdullah Alohali 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 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 Information Systems Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia 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

Applications of internet-of-things(IoT)are increasingly being used in many facets of our daily life,which results in an enormous volume of *** computing and fog computing,two of the most common technologies used in IoT applications,have led to major security *** are on the rise as a result of the usage of these technologies since present security measures are *** artificial intelligence(AI)based security solutions,such as intrusion detection systems(IDS),have been proposed in recent *** technologies that require data preprocessing and machine learning algorithm-performance augmentation require the use of feature selection(FS)techniques to increase classification accuracy by minimizing the number of features *** the other hand,metaheuristic optimization algorithms have been widely used in feature selection in recent *** this paper,we proposed a hybrid optimization algorithm for feature selection in *** proposed algorithm is based on grey wolf(GW),and dipper throated optimization(DTO)algorithms and is referred to as *** proposed algorithm has a better balance between the exploration and exploitation steps of the optimization process and thus could achieve better *** the employed IoT-IDS dataset,the performance of the proposed GWDTO algorithm was assessed using a set of evaluation metrics and compared to other optimization approaches in 2678 CMC,2023,vol.74,no.2 the literature to validate its *** addition,a statistical analysis is performed to assess the stability and effectiveness of the proposed *** results confirmed the superiority of the proposed approach in boosting the classification accuracy of the intrusion in IoT-based networks.

关键词： Feature selection grey wolf optimization dipper throated optimization intrusion detection internet-of-things(IoT)

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Product Traceability Digital Tool Powered by Mathematical Model for Logistics Digital Platform 15

Product Traceability Digital Tool Powered by Mathematical Mo...

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15th International Conference Management of Large-Scale System Development, MLSD 2022

ISBN: (数字)9781665497015

ISBN: (纸本)9781665497015

This paper discusses a mathematical model for establishing a single digital logistics platform as a link between all participants in the added-value creation chain, including producers, resource and services suppliers, consumers, and logistics companies. This demonstrates that the platform in question is an opportunity to create digital tools for products and goods traceability throughout the entire production and logistics chain from the field to the end consumer's kitchen. © 2022 IEEE.

关键词： Digital devices

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Teeth Segmentation from Bite-Wing X-Ray Images by Integrating Nested Dual UNet with Swin Transformers

Teeth Segmentation from Bite-Wing X-Ray Images by Integratin...

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2024 IEEE International Conference on systems, Man, and Cybernetics, SMC 2024

作者： Li, Yubo Tian, Yibin Zhang, Zhiyuan Zhang, Xueyang Du, Bingran Zeng, Zhi School of Computer and Information Science Chongqing Normal University Chongqing401331 China College of Mechatronics and Control Engineering Shenzhen University Shenzhen518060 China Litemaze Technology Shenzhen518000 China School of Computing and Information Systems Singapore Management University Singapore487372 Singapore Shunde Hospital Department of Stomatology Foshan528000 China

ISBN: (纸本)9781665410205

In medical practice, the precision of image segmentation is crucial for diagnosis and treatment evaluations. Specifically, in dentistry, accurate teeth segmentation from bite-wing images is important for automatic and objective evaluations of root canal treatments. This study introduces Swin-U2 Net, a model merging the nested dual UNet with residual U-block and Swin Transformers. It combines the local feature extraction capability of the former and the global attention and context understanding of the latter. It has been evaluated for tooth root segmentation using 500 bite-wing dental x-ray images obtained from a root canal treatment clinic. It achieved the best segmentation outcome in terms of Intersection over Union (IOU) and the third best result in terms of Dice Similarity Coefficient (DSC) with the second least amount of network parameters among six UNet-like models, thus it is effective and efficient. © 2024 IEEE.

关键词： Image segmentation

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Voting Classifier and Metaheuristic Optimization for Network Intrusion Detection

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Computers, Materials & Continua 2023年第2期74卷 3183-3198页

作者： Doaa Sami Khafaga Faten Khalid Karim Abdelaziz A.Abdelhamid El-Sayed M.El-kenawy Hend K.Alkahtani Nima Khodadadi Mohammed Hadwan Abdelhameed Ibrahim Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt The Department of Civil and Environmental Engineering Florida International UniversityMiamiFLUSA Department of Information Technology College of ComputerQassim UniversityBuraydah51452Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt

Managing physical objects in the network’s periphery is made possible by the Internet of Things(IoT),revolutionizing human *** attacks and unauthorized access are possible with these IoT devices,which exchange data to enable remote *** attacks are often detected using intrusion detection methodologies,although these systems’effectiveness and accuracy are *** paper proposes a new voting classifier composed of an ensemble of machine learning models trained and optimized using metaheuristic *** employed metaheuristic optimizer is a new version of the whale optimization algorithm(WOA),which is guided by the dipper throated optimizer(DTO)to improve the exploration process of the traditionalWOA *** proposed voting classifier categorizes the network intrusions robustly and *** assess the proposed approach,a dataset created from IoT devices is employed to record the efficiency of the proposed algorithm for binary attack *** dataset records are balanced using the locality-sensitive hashing(LSH)and Synthetic Minority Oversampling Technique(SMOTE).The evaluation of the achieved results is performed in terms of statistical analysis and visual plots to prove the proposed approach’s effectiveness,stability,and *** achieved results confirmed the superiority of the proposed algorithm for the task of network intrusion detection.

关键词： Voting classifier whale optimization algorithm dipper throated optimization intrusion detection internet-of-things

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