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检索条件"任意字段=Proceedings of the 3rd International Conference on Parallel and Distributed Information Systems"

共 4664 条记录，以下是161-170 订阅

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Research on text evaluation based on natural language processing and GSDMM topic model 3

Research on text evaluation based on natural language proces...

引用

3rd international conference on Electronics Technology and Artificial Intelligence, ETAI 2024

作者： Wang, Bing Department of Information Engineering Shandong Water Conservancy Vocational College Shandong Rizhao China

ISBN: (纸本)9781510683143

Driven by natural language processing technology, topic models have shown a wide range of application value in fields such as text analysis, classification and clustering. The GSDMM topic model has been widely recognized in the field of topic modeling due to its ability to automatically infer the number of clusters, fast convergence, and efficient processing of sparse and high-dimensional short texts. This paper aims to explore the text evaluation research based on natural language processing and GSDMM (Gibbs Sampling and distributed Memory Model) topic model, and carries out relevant practice in the text evaluation of project-based teaching course. © 2024 SPIE.

关键词： Teaching

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Leveraging AI for Enhanced Botnet Detection - A Review of Machine Learning Approach for Cybersecurity 3

Leveraging AI for Enhanced Botnet Detection - A Review of Ma...

引用

3rd IEEE international conference on Blockchain and distributed systems Security, ICBDS 2024

作者： Sonune, Harsha Kulkarni, Nilima Mksss's Cummins College of Engineering for Women Department of Information Technology Pune India Mitadt University Mitsoe Department of Computer Science and Engineering Maharashtra Pune India

ISBN: (纸本)9798350354348

Botnets represent a substantial threat to cybersecurity, enabling malicious actors to execute large-scale attacks that compromise network integrity and data confidentiality. Current detection methods often fall short in addressing the rapidly evolving strategies employed by botnets. This study has an aim of designing and developing a sophisticated botnet detection system leveraging artificial intelligence (AI) techniques. By integrating machine learning algorithms and advanced data analysis methods, the proposed system seeks to accurately identify and mitigate botnet activities in real-time. The study will evaluate the effectiveness of various AI models in detecting botnet traffic, provide a comparative analysis of their performance, and propose an optimal framework for implementation in cybersecurity infrastructures. © 2024 IEEE.

关键词： Bot (Internet)

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Scheme and selection of the mainboard hardware of a complete home-made distributed control system controller 3

Scheme and selection of the mainboard hardware of a complete...

引用

3rd IEEE international conference on Electronic Technology, Communication and information, ICETCI 2023

作者： Changqing, Li Wenfeng, Zhou Chengyu, Ni Kang, Wang Beijing Smartchip Microelectronics Technology Co..Ltd Beijing China

ISBN: (纸本)9798350398410

This controller of the distributed control system is an implementation scheme put forward under the background of localization substitution. The scheme is based on the microprocessor, and adopts the design principles of decentralized control function, centralized operation, and taking into account division and autonomy and comprehensive coordination. The control system is based on SCM801B468A0 and SCM621L144MJA0 chips of Smart Chip Company. It expands DDR module, EMMC module, FRAM module, SD card module and so on. It puts forward a unique design idea in communication and storage, and provides a pure home-made production scheme for distributed control system mainboard. It includes the realization architecture, the design principle of each functional module, and gives the selection ideas of related components, technical parameters, matters to be noted, as well as the functional block diagram. The distributed controller aims at the new generation of instrument control system, and is widely used in energy and electric power, rail transportation, automotive electronics, petroleum, petrochemical industries, etc. © 2023 IEEE.

关键词： distributed parameter control systems

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Data Security Protection System in Human-Machine-Object Fusion Intelligent Demand Engineering System 3

Data Security Protection System in Human-Machine-Object Fusi...

引用

3rd international conference on Integrated Circuits and Communication systems, ICICACS 2025

作者： Qi, Yongjun Li, Chenggao Tang, Hailin Shen, Junxuan Guangdong Baiyun University Faculty of Megadata and Computing Guangdong Guangzhou China School of Information and Communication Technology Mongolian University of Science and Technology Ulaanbaatar Mongolia

ISBN: (纸本)9798331508456

In the engineering system of human-machine physical intelligence requirements, the multi-source and high complexity of data pose significant security risks. Therefore, this article designs a comprehensive data security protection system. Firstly, this article chooses a dynamic encryption strategy based on role-based access control. Then, this article combines differential privacy algorithm to construct a privacy protection model to ensure the privacy of data during sharing and processing. Subsequently, this article proposes a trusted data transmission protocol. Finally, this article introduces federated learning techniques to further improve the security and robustness of data in distributed scenarios. The experimental results show that the system performs well in terms of data security, privacy protection, and processing efficiency. Especially under high-intensity attacks, the system successfully detected and prevented approximately 98% of tampering. In the above data conclusions, the research method has significant advantages in encryption performance, achieving a better balance between privacy protection and data accuracy, demonstrating strong application prospects. © 2025 IEEE.

关键词： Requirements engineering

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distributed Fault Diagnosis System Based on Machine Learning 3

Distributed Fault Diagnosis System Based on Machine Learning

引用

3rd international conference on Intelligent Computing, Communication and Convergence, ICI3C 2023

作者： Guan, Mengru Fu, Yanyou Wang, Zhaoyue Zhang, Jiaqian Sias University Henan China

ISBN: (纸本)9798350343922

This research focuses on the development of a machine learning-based distributed fault diagnosis system that aims to improve the accuracy and real-time detection of faults in large-scale distributed systems. By deeply analysing key information such as log data, performance metrics, and network traffic of distributed systems, we design adaptable machine learning algorithms to handle distributed environments of complexity and large scale. In our research, we pay special attention to real-time fault diagnosis to detect and diagnose faults in a timely manner by monitoring and analysing the data flow of distributed systems in real time, thus minimising the potential impact on the system. The proposed machine learning algorithms are not only able to handle large-scale datasets efficiently, but also have the flexibility to adapt to different system architectures and network topologies, while exhibiting good scalability and robustness. In addition, we attempt to introduce an augmented learning approach to enable the fault diagnosis system to actively learn and optimise in order to maintain an efficient fault diagnosis capability in a dynamic and distributed environment. This innovative approach is expected to further improve the system's adaptability to emerging fault modes, thereby enhancing the system's intelligence and self-optimisation capabilities. Overall, this study introduces advanced techniques in machine learning for fault diagnosis in the field of distributed systems and lays the foundation for a more accurate, real-time and intelligent fault diagnosis system. © 2023 IEEE.

关键词： Adversarial machine learning

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Overview of Amazon Chess’ Game Playing Algorithms 3

Overview of Amazon Chess’ Game Playing Algorithms

引用

3rd international conference on Applied Mathematics, Modelling, and Intelligent Computing, CAMMIC 2023

作者： Sun, Yikai Gao, Ming Computer School Beijing Information Science and Technology University Beijing100101 China

ISBN: (数字)9781510667617

ISBN: (纸本)9781510667600

Amazon chess is a machine game with high dimension branches, in which the first step is more than 2000 actions, so it is an ideal test platform for search algorithm and Monte Carlo tree search. This paper analyses the rules and common game algorithms of Amazon chess based on its environment, and compares the advantages and disadvantages of different algorithms. Finally, the improvement direction of Monte Carlo tree search algorithm is reviewed from four aspects of evaluation function, database, search strategy and parallel computing, and the research prospect of Amazon Monte Carlo game algorithm is prospected. © 2023 SPIE.

关键词： Computer games

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Research on Digital System of Collaborative Cycle Integration information Transformation in Electric Power Enterprises 3

Research on Digital System of Collaborative Cycle Integratio...

引用

3rd international Signal Processing, Communications and Engineering Management conference, ISPCEM 2023

作者： Bin, Kong State Grid Zhejiang Electric Power Co. Ltd. Xiangshan County Power Supply Company Ningbo China

ISBN: (纸本)9798350307023

The stage model and operation mode of enterprise private cloud platform construction are developed, and the architecture of collaborative cycle integration system of power enterprises is designed. The platform implements integrated management, standardized supply and automated operation of various computing resources such as host, storage device, network, database, middleware and application software. It provides strong support for standardized construction and lean management of information construction of power grid enterprises. Practice has proved that the integrated and collaborative distributed cloud management platform across data centers can enhance the scalability, scalability and flexibility of information resources, improve the ability and efficiency of information technology operation and maintenance management, and improve the business response ability and service mode level. © 2023 IEEE.

关键词： Scalability

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Bi-level optimal configuration of energy storages in the distribution network considering distributed photovoltaic carrying capacity 3

Bi-level optimal configuration of energy storages in the dis...

引用

3rd international conference on Electrical, Electronics, and information Engineering, EEIE 2024

作者： Men, Maochen Zhang, Qing Zhai, Wenqi Zhang, Jinshuai Zhao, Rui Zhengzhou University Comprehensive Design and Research Institute Co. Ltd. Henan Zhengzhou450001 China Zhengzhou University School of Electrical and Information Engineering Henan Zhengzhou450001 China State Grid Corporation of Henan Province Electric Power Research Institute of Electric Power Henan Zhengzhou450052 China State Grid Corporation of Shandong Province Electric Power Linyi Power Supply Company Shandong Linyi276000 China

ISBN: (纸本)9781510688179

Large-scale distributed PV access to the low-voltage distribution network is prone to cause serious power back-feeding, resulting in PV distribution transformers in the distribution network reversing heavy overload and node voltage rise over the limit, exceeding the distributed PV carrying capacity in the distribution network. In response to the issue, based on the full consideration of the distribution network, the economic and safe operation of the energy storage system. We construct a two-layer optimization model of the distributed PV storage, considering the PV carrying capacity in the distribution network, the power grid's security, and the economy of the energy storage system. The simulation and analysis of selected actual PV heavy overload areas prove the effectiveness of the configuration method for managing the problem of PV heavy overload areas exceeding the carrying capacity and reducing the comprehensive cost. © The Authors.

关键词： Power distribution networks

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Secure Data Sharing and Mining in distributed Environments 3

Secure Data Sharing and Mining in Distributed Environments

引用

3rd international conference on Technological Advancements in Computational Sciences, ICTACS 2023

作者： Dari, Sukhvinder Singh Alawadi, Ahmed Hussein Verma, Ankit Sheela, M. Sahaya Jebaseeli, S. Kanmani Symbiosis Law School Nagpur Symbiosis International Pune India College of Technical Engineering The Islamic University Najaf Iraq Ies College of Technology Department of Electronics & Communication Engineering Bhopal India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Ece Chennai India New Prince Shri Bhavani College of Engineering and Technology India

ISBN: (纸本)9798350342338

In today's interconnected world, distributed systems have emerged as the backbone for facilitating global collaborations and real-time data exchanges. As more organizations migrate to distributed architectures, the ability to share and mine data securely across disparate networks becomes paramount. Secure data sharing ensures that information is accessible to only authorized entities, while secure data mining aims to extract meaningful patterns from vast datasets without compromising privacy or integrity. This paper delves into the intricacies of implementing robust security protocols in distributed environments, emphasizing the Role-Based Access Control (RBAC) and transaction processing mechanisms. Through a comprehensive exploration, we aim to highlight the importance of marrying security with functionality to harness the full potential of distributed systems without sacrificing confidentiality and trust. © 2023 IEEE.

关键词： data mining distributed systems Role-Based Access Control (RBAC) secure data sharing transaction processing

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An Adaptive Load Balancing Strategy for distributed Machine Learning 3

An Adaptive Load Balancing Strategy for Distributed Machine ...

引用

3rd international conference on Frontiers of Electronics, information and Computation Technologies, ICFEICT 2023

作者： Min, Haozhe Xue, Meiting Zhu, Weibo Zeng, Yan Zhao, Nailiang Zhang, Jilin Hangzhou Dianzi University College of Cyberspace HangZhou China Hangzhou Dianzi University School of Computer Seience and Techrology HangZhou China

ISBN: (纸本)9798350302356

Within a distributed deep learning training system, variances in performance among computing nodes, as well as the influence of external environmental factors, can result in training interruptions or reduced convergence speed. As such, this paper presents an approach to address this issue by proposing a dynamic task allocation strategy among nodes, aimed at mitigating the impact of performance discrepancies on the training efficiency of distributed deep learning systems. This proposed approach is referred to as the 'Auto weight-based load balancing strategy' (Auto-WLBS) and involves dynamically adjusting the task allocation among computing nodes based on their performance characteristics. In order to maximize computing power while minimizing the lag effect on the training of the entire system, Auto-WLBS partitions and alters the errands by introductory division and halfway alteration. Combined with LSP model, AW-LSP model is proposed. Finally, a comparative experiment was conducted on the cifar10 and cifar100 datasets, and Auto-WLBS was experimentally verified from the perspective of model training loss function changes, model accuracy, and training time. The experimental findings demonstrate that compared to the BSP model, SSP model, and LSP model, the AW-LSP model has a smaller communication overhead, and the communication overhead can be reduced by up to 23.70%. Compared with the SSP model and the LSP model, the model accuracy can be improved by up to 14.5% and 8.6%, respectively. © 2023 IEEE.

关键词： Computing power

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