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Distributed Nash Equilibrium Seeking Strategies Under Quantized Communication

IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 103-112页

作者： Maojiao Ye Qing-Long Han Lei Ding Shengyuan Xu Guobiao Jia IEEE the School of Automation Nanjing University of Science and TechnologyNanjing 210094China the School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourne VIC 3122Australia the Institute of Advanced Technology Nanjing University of Posts and TelecommunicationsNanjing 210023China

This paper is concerned with distributed Nash equi librium seeking strategies under quantized communication. In the proposed seeking strategy, a projection operator is synthesized with a gradient search method to achieve the optimization o players' objective functions while restricting their actions within required non-empty, convex and compact domains. In addition, a leader-following consensus protocol, in which quantized informa tion flows are utilized, is employed for information sharing among players. More specifically, logarithmic quantizers and uniform quantizers are investigated under both undirected and connected communication graphs and strongly connected digraphs, respec tively. Through Lyapunov stability analysis, it is shown that play ers' actions can be steered to a neighborhood of the Nash equilib rium with logarithmic and uniform quantizers, and the quanti fied convergence error depends on the parameter of the quan tizer for both undirected and directed cases. A numerical exam ple is given to verify the theoretical results.

关键词： Consensus distributed Nash equilibrium seeking projected gradient play quantized communication

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Accelerate Data Loading in Distributed Training with Fast Reconfigurable Optical Network

Accelerate Data Loading in Distributed Training with Fast Re...

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2024 Asia Communications and Photonics Conference, ACP 2024 and International Conference on Information Photonics and Optical Communications, IPOC 2024

作者： Li, Wenzhe Zhang, Xinhang Jia, Wenxuan Chen, Zhuohan Yuan, Guojun Wang, Zhan Zhang, Peiheng High Performance Computing Center Institute of Computing Technology CAS Beijing China Department of Intelligent Science and Technology Hangzhou Institute of Advanced Study UCAS Hangzhou China Institute of Intelligent Computing Technology Chinese Academy of Sciences Suzhou China

We enhance our prior all-optical reconfigurable network to accelerate the data loading with minimized communication distance between compute and storage nodes. A novel corresponding data loading scheme is proposed to ... 详细信息

ISBN: (纸本)9798350379266

关键词： Data Loading Distributed Deep Learning Reconfigurable optical network

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CR-DIS: An Efficient Heuristic Algorithm for Minimum Weighted Vertex Cover Problem

CR-DIS: An Efficient Heuristic Algorithm for Minimum Weighte...

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2024 International Conference on New Trends in Computational Intelligence, NTCI 2024

作者： Hao, Chenkai Zhu, Enqiang Cyberspace Institute of Advanced Technology Guangzhou University Guangzhou China Institute of Computing Science and Technology Guangzhou University Guangzhou China

ISBN: (纸本)9798331517021

The minimum weighted vertex cover (MWVC) problem is a well-known NP-hard combinatorial optimization problem. In this problem, each vertex of the graph is assigned a positive weight, and the objective is to identify a set of vertices such that every edge is covered by at least one vertex from the set, while minimizing the sum of all vertices' weights in the set. It has greater generality and broader applications than the minimum vertex cover (MVC) problem. Due to its NP-hard nature, efficiently solving the MWVC problem is a significant challenge. This paper introduces a highly efficient heuristic algorithm named CR-DIS for MWVC, which consists of two components: a construction with reductions and a dynamic improvement search framework. We compare CR-DIS with three state-of-the-art algorithms on a large number of graphs. Experimental results indicate that CR-DIS performs at a superior level, especially on large sparse graphs, yielding more best solutions and, in many instances, achieving smaller solutions with similar running times. © 2024 IEEE.

关键词： Heuristic algorithms

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Evolution Analysis of Network Attack and Defense Situation Based on Game Theory

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Computers, Materials & Continua 2025年第4期83卷 1475-1494页

作者： Haiyan Sun Chenglong Shao Jianwei Zhang Kun Wang Wanwei Huang College of Software Engineering Zhengzhou University of Light IndustryZhengzhou450007China Intelligent Computing Power Research Department Zhengzhou Xinda Advanced Technology Research InstituteZhengzhou450007China

To address the problem that existing studies lack analysis of the relationship between attack-defense game behaviors and situation evolution from the game perspective after constructing an attack-defense model,this paper proposes a network attack-defense game model(ADGM).Firstly,based on the assumption of incomplete information between the two sides of the game,the ADGM model is established,and methods of payoff quantification,equilibrium solution,and determination of strategy confrontation results are ***,drawing on infectious disease dynamics,the network attack-defense situation is defined based on the density of nodes in various security states,and the transition paths of network node security states are ***,the network zero-day virus attack-defense behaviors are analyzed,and comparative experiments on the attack-defense evolution trends under the scenarios of different strategy combinations,interference methods,and initial numbers are conducted using the NetLogo simulation *** experimental results indicate that this model can effectively analyze the evolution of the macro-level network attack-defense situation from the micro-level attack-defense *** instance,in the strategy selection experiment,when the attack success rate decreases from 0.49 to 0.29,the network destruction rate drops by 11.3%,in the active defense experiment,when the interference coefficient is reduced from 1 to 0.7,the network destruction rate decreases by 7%,and in the initial node number experiment,when the number of initially infected nodes increases from 10 to 30,the network destruction rate rises by 3%.

关键词： Network attack-defense situation evolution zero-day virus NetLogo

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A Review of Intelligent Configuration and Its Security for Complex Networks

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Chinese Journal of Electronics 2024年第4期33卷 920-947页

作者： Yue ZHAO Bin YANG Fei TENG Xianhua NIU Ning HU Bo TIAN Science and Technology on Communication Security Laboratory School of Computer and Information Engineering Chuzhou University School of Computing and Artificial Intelligence Southwest Jiaotong University School of Computer and Software Engineering Xihua University Cyberspace Institute of Advanced Technology Guangzhou University

Complex networks are becoming more complex because of the use of many components with diverse technologies. In fact, manual configuration that makes each component interoperable has breed latent danger to system security. There is still no comprehensive review of these studies and prospects for further research. According to the complexity of component configuration and difficulty of security assurance in typical complex networks, this paper systematically reviews the abstract models and formal analysis methods required for intelligent configuration of complex networks, specifically analyzes, and compares the current key technologies such as configuration semantic awareness, automatic generation of security configuration, dynamic deployment, and verification evaluation. These technologies can effectively improve the security of complex networks intelligent configuration and reduce the complexity of operation and maintenance. This paper also summarizes the mainstream construction methods of complex networks configuration and its security test environment and detection index system, which lays a theoretical foundation for the formation of the comprehensive effectiveness verification capability of configuration security. The whole lifecycle management system of configuration security process proposed in this paper provides an important technical reference for reducing the complexity of network operation and maintenance and improving network security.

关键词： Complex networks Intelligent configuration Configuration security Software defined network Lifecycle management

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An Ensemble Machine Learning Model for Osteoporosis Risk Prediction from Medical Data 2

An Ensemble Machine Learning Model for Osteoporosis Risk Pre...

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2nd International Conference on Machine Learning and Autonomous Systems, ICMLAS 2025

作者： Thulasi, M. Thailambal, G. Vels Institute of Science Technology & Advanced Studies Department of Advanced Computing and Analytics Tamil Nadu Chennai India

ISBN: (纸本)9798331505745

The metabolic condition osteoporosis afflicted a large number of people worldwide. Osteoporosis causes major health and its financial implications worldwide. However, the advancement of osteoporosis-related methods for forecasting is inadequate. Machine Learning (ML), a subfield of Artificial Intelligence (AI)I allows computers to 'learn' using programs. In comparison to classic statistical methods, ML places a greater focus on prediction accuracy and can find patterns in multidimensional data sets. This study propose an ensemble model employing Random Forest(RF), XGBoost(XGB) and Light Gradient Boosting(LGBM) techniques for the prediction of osteoporosis from the medical data of an individual. The accuracy, precision, recall, and f1-score were computed to compare the model with four alternative machine learning models: Logistic Regression (LR), Decision Tree (DT), Support Vector Machine (SVM), and K-Nearest Neighbor (KNN). The findings show that the ensemble model outperforms with an accuracy, precision, recall and F1-score of 93.5%, 92.8%, 94.2% and 93.5% respectively. © 2025 IEEE.

关键词： Support vector machines

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Deterministic Hash and Linear Congruential BlowFish Extreme Learning for User Authentication in Cloud computing

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SN Computer Science 2023年第6期4卷 796页

作者： Radha, S. Jeyalaksshmi, S. School of Computing Sciences Vels Institute of Science Technology and Advanced Studies Chennai India

advanced technology of Cloud computing (CC) is to provide the services without straight executive of users and demand for resources. It is very scalable and vigorous as well as offers data access anywhere at any time over a cloud environment. Due to many users using the same shared computing resource, security is the more significant of cloud data privacy. User authentication is mainly perceptive defense issue in CC from unauthorized user accessed in cloud services. Various methods are improved in authentication security. However, it failed to improve the complexity of user authentication. Therefore, a novel technique called Deterministic Hash and Linear Congruential BlowFish Authenticated Extreme Learning (DHLCBAEL) method is redeveloped for improving accuracy and reducing the time consumption of accurate authentication. A different layer of isolated nodes is utilized by feed-forward neural network with extreme learning machine technique. The DHLCBAEL method includes four different layers, namely, input, two hidden layers, and an output layer carried for efficient user authentication. Initially, the number of users is specified to input layer by DHLCBAEL method. After that, DHLCBAEL method comprises two steps, namely User Registration and User Authentication at the hidden layer 1 and hidden layer 2, respectively. In the user registration step, the user registers their details and stores them on the cloud server using the Deterministic Davies–Meyer Snefru hash function. After that authentication process is carried out during data transmission. To encrypt the data, the symmetric key of cloud user uses the Lehmer congruential BlowFish cryptography algorithm. Next, it sends the ciphertext to cloud server. When the employer needs to enter the information using cloud server, then validate the authentication server their employer identity. During the authentication process, the DHLCBAEL method authenticates the user with help of a simple matching coefficient. When a user

关键词： Authentication Cloud computing Deterministic Davies–Meyer Snefru hash function Extreme learning Lehmer congruential BlowFish cryptography

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Domain Transformation for PMMA-Inserted Vertebral Body Segmentation

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Journal of computing Science and Engineering 2022年第1期16卷 43-51页

作者： Park, Minyoung Park, Jinah School of Computing Korea Advanced Institute of Science and Technology Daejeon Korea Republic of

Learning-based medical image segmentation has been advanced with the collection of datasets and various training methodologies. In this work, we target bone cement (polymethylmethacrylate [PMMA]) inserted vertebral body segmentation, where the target dataset was relatively scarce, compared to a large-scale dataset for the regular vertebra segmentation task. We presented a novel domain transformation framework, where a large-scale training set for our target task was generated from the existing dataset of a different domain. We proposed two main components: label translation and image translation. Label translation was proposed to filter out unnecessary regions in a segmentation map for our target task. In addition to label translation, image translation was proposed to virtually generate PMMA-inserted images from the original data. The synthesized training set by our method successfully simulated the data distribution of the target task;therefore a clear performance improvement was observed by the dataset. By extensive experiments, we showed that our method outperformed baseline methods in terms of segmentation performance. In addition, a more accurate shape and volume of a bone were measured by our method, which satisfied the medical purpose of segmentation. © 2022. The Korean institute of Information Scientistsand Engineers. All Rights Reserved.

关键词： Computer vision

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Analyzing Brain Damages in Children with Image Processing Using KNN and FCM Algorithms

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SN Computer Science 2024年第1期5卷 62页

作者： Kayathri, B. Prasanna, S. School of Computing Sciences Vels Institute of Science Technology and Advanced Studies Tamil Nadu Chennai India Department of Computer Applications Vels Institute of Science Technology and Advanced Studies Tamil Nadu Chennai India

In current scenario, children are addicted towards mobile communication devices such as mobile phone, tablet and various wireless devices. Exploring more radio frequencies with these devices causes brain damage in children aged 5–10 years. This paper uses an original calculation for the examination of the cerebral image. Typically, an MRI scan or CT scan will show the Cerebrum’s living structures. The brain of children is scanned in MRI and analyzed through image processing to know whether the children put their lives in danger or not, parents should be aware of their kids’ true health. The analysis of training data selected from MRI scan pictures yields 96.3% accuracy in determining the outcomes through examination of the children’s brains. Hence, the findings of brain analyses on various children are examined. Thus, the existing methods to analysis on finding brain damage which is not enough to sort out the problem still, so proposed method is needed to find Brain Damage Findings (BDF) which has to work prominently compared with the existing methods of FCM and KNN with unique test and trained data of brain. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Communication devices CT (Computerized Tomography) Damage FCM (Fuzzy C-Means) KNN (K-Nearest Neighbour) MRI (Magnetic Resonance Imaging)

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Emotion-Aware Talking Face Generation Based on 3DMM 4

Emotion-Aware Talking Face Generation Based on 3DMM

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4th International Conference on Neural Networks, Information and Communication Engineering, NNICE 2024

作者： Chen, Xinyu Tang, Sheng Zhengzhou University Henan Institute of Advanced Technology Henan Zhengzhou China Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798350394375

Current methods for generating videos of talking face based on deep learning mainly focus on the correlation between lip movements and audio content. Although these methods have high generation quality and good audio-visual synchronization, they ignore facial expressions in talking face videos. To solve this problem, Audio to Expression Network (A2ENet), an emotional talking face video generation framework based on 3DMM, is proposed in this paper to generate talking face videos with facial expressions in an audio-driven way. Firstly, A2ENet uses two Transformer based encoders to extract audio features, and uses a cross-reconstruction emotion disentanglement method to decompose audio into potential space of content information and potential space of emotion information, and then uses a Transformer Decoder to integrate these two feature spaces. After that, the Proposed method predict the 3D expression coefficient that matches the emotion of the audio, and finally uses the renderer to generate the talking face video. By using the eye control parameters, A2ENet can realize the eye movements control of talking face. A2ENet associating the initial 3D expression coefficients with specific individuals to retain the identity information of the reference face. Experimental results show that our method can generate talking face videos with appropriate facial expressions, and achieve more accurate lip movements and better video quality. © 2024 IEEE.

关键词： Deep learning

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