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Optimal Production Capacity Matching for Blockchain-Enabled Manufacturing Collaboration With the Iterative Double Auction Method

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IEEE/CAA Journal of Automatica Sinica 2025年第3期12卷 550-562页

作者： Ying Chen Feilong Lin Zhongyu Chen Changbing Tang Cailian Chen the Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province Zhejiang Normal University the School of Computer Science and Technology Zhejiang Normal University IEEE the College of Physics and Electronic Information Engineering Zhejiang Normal University the Department of Automation Shanghai Jiao Tong University

The increased demand for personalized customization calls for new production modes to enhance collaborations among a wide range of manufacturing practitioners who unnecessarily trust each other. In this article, a blockchain-enabled manufacturing collaboration framework is proposed, with a focus on the production capacity matching problem for blockchainbased peer-to-peer(P2P) collaboration. First, a digital model of production capacity description is built for trustworthy and transparent sharing over the blockchain. Second, an optimization problem is formulated for P2P production capacity matching with objectives to maximize both social welfare and individual benefits of all participants. Third, a feasible solution based on an iterative double auction mechanism is designed to determine the optimal price and quantity for production capacity matching with a lack of personal information. It facilitates automation of the matching process while protecting users' privacy via blockchainbased smart contracts. Finally, simulation results from the Hyperledger Fabric-based prototype show that the proposed approach increases social welfare by 1.4% compared to the Bayesian game-based approach, makes all participants profitable,and achieves 90% fairness of enterprises.

关键词： Blockchain iterative double auction manufacturing collaboration production capacity matching

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ChatGPT Based Image Steganography (CGIS): A Novel Intelligent Information Hiding Approach to Achieve Secure Covert Communication 1

ChatGPT Based Image Steganography (CGIS): A Novel Intelligen...

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1st International Conference on Advances in Electrical, Electronics and Computational Intelligence, ICAEECI 2023

作者： Mukherjee, Subhadip Mukhopadhyay, Somnath Sarkar, Sunita Assam University Department of Computer Science and Engineering Silchar788011 India Sikkim University Department of Computer Application Gangtok737102 India

ISBN: (纸本)9798350342796

Covert communication refers to the practice of exchanging information or messages in a discreet or secretive manner, with the intent of keeping the communication hidden from unintended or unauthorized recipients. Steganography is a widely used, strategy for establishing covert communication, for maintaining the privacy and security of sensitive information. Steganography ensures that the message remains concealed from surveillance or eavesdropping. Artificial Intelligence (AI) plays a crucial role in enhancing security across various domains of covert communication. ChatGPT is an AI model, specifically a natural language processing (NLP) model. It belongs to the broader category of AI models which can comprehend and produce language for humans. In this paper, a new image steganographic model named CGIS is developed for covert communication using ChatGPT. Proposed steganographic method has achieved 3.0 bpp of hiding capacity. In situations where confidentiality is critical, such as in military operations, intelligence agencies, or corporate strategies, proposed method ensures that the message cannot be detected and or extracted by any surveillance or eavesdropper. © 2023 IEEE.

关键词： Artificial Intelligence CGIS ChatGPT Covert Communication Image Steganography

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Personalized Confederation Training for Smart Iot Systems: A Cloud - Delivered Structure 3

Personalized Confederation Training for Smart Iot Systems: A...

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3rd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2023

作者： Katariya, Jitendra Kumar Nivesh Vivekananda Global University Department of Computer Science Engineering India Chandigarh School of Business Department of Master of Computer Application Jhanjeri India

ISBN: (纸本)9798350399264

The Internet of Things (IoT) has significantly impacted many facets of contemporary life, and several sophisticated IoT applications and services are already being developed. Recently, the concept of federated learning has been proposed in order to train a globally shared model on IoT devices utilising a large number of user-generated data samples while stopping data leak. Due to the widespread heterogeneities in device, statistics, and model in complex IoT contexts, traditional federated learning is not suitable for instant implementation. In this paper, we present a cloud-edge architecture for intelligent IoT applications that includes a customised federated learning framework. To address the heterogeneity worries in IoT conditions, we examine imaginative altered united learning calculations that could diminish the unfortunate results brought about by heterogeneities in various aspects. The advantages of edge registering empower smart IoT applications to meet the models for high handling pace and low inertness. At long last, we give a contextual investigation of human movement recognition in light of Web of Things to show the advantages of customisable combined learning for intelligent IoT applications. © 2023 IEEE.

关键词： Internet of things

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Structured Approach for Relation Extraction in Legal Documents 4

Structured Approach for Relation Extraction in Legal Documen...

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4th IEEE Global Conference for Advancement in Technology, GCAT 2023

作者： Sasidharan, Anjali K. Rahulnath, R. Department of Computer Science and Application Amrita School of Engineering Amrita Vishwa Vidyapeetham Amritapuri India

ISBN: (纸本)9798350305258

Legal documents contain a wealth of valuable information, making them crucial for knowledge extraction and analysis. Extracting structured relationships between entities in legal texts can significantly enhance our understanding of legal concepts and facilitate the creation of knowledge graphs. In this paper, we propose a structured approach combining relation extraction, graph reasoning, and clustering methods to effectively extract and represent legal relationships. Firstly, we employ state-of-the-art relation extraction techniques to identify relevant entities and their relationships from unstructured legal documents. These techniques leverage natural language processing (NLP) and machine learning algorithms to recognize entity pairs and assign appropriate relationship labels. Next, we leverage graph reasoning to enhance the extracted relationships by incorporating additional contextual information. By representing the legal entities and their relationships as nodes and edges in a knowledge graph, we can apply reasoning algorithms to infer implicit relationships, resolve conflicts, and expand the graph based on the legal domain's rules and regulations. Furthermore, we integrate clustering methods to organize related legal entities and relationships into meaningful clusters within the knowledge graph. By grouping semantically similar entities and relationships, we can uncover patterns, identify common themes, and enable more effective retrieval and analysis of legal information. Our experiments demonstrate that the structured approach, combining relation extraction, graph reasoning, and clustering methods, effectively extracts and represents legal relationships in a knowledge graph. The resulting graph provides a comprehensive and organized representation of legal concepts, facilitating legal research, decision-making, and knowledge discovery in the legal domain. © 2023 IEEE.

关键词： Clustering methods Graph reasoning Knowledge graph creation Legal documents Machine learning Natural language processing Relation extraction

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MemoChat App: An Advancement in Existing WhatsApp 1

MemoChat App: An Advancement in Existing WhatsApp

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1st IEEE International Conference on Advances in Computing, Communication and Networking, ICAC2N 2024

作者： Takkar, Hardik Sharma, Krishna Karun Kumar, Nagadamudi Vijay Jha, Manish Kumar Saraswat, Bal Krishna Tyagi, Himani Sharda University Computer Science and Engineering Department Uttar Pradesh Greater Noida India Sharda University Computer Science and Application Department Uttar Pradesh Greater Noida India

ISBN: (纸本)9798350356816

With over 1 billion users in 180 countries, it's no surprise that WhatsApp is one of the most popular instant messaging apps available today. Whether you're looking to make voice or video calls, or simply share messages, photos, and videos with friends and family, this app is an excellent choice. Not only is it free of charge, but it's also incredibly reliable and easy to use. With its user-friendly interface and convenient features, WhatsApp is the perfect way to stay connected with loved ones, no matter where they are in the world. With regular updates, WhatsApp is becoming even more user-friendly and interactive. Though there may be some issues, solutions are always available. By addressing these problems head-on, WhatsApp can provide a unique and unparalleled messaging experience, setting itself apart from the competition. The future of WhatsApp is bright, and no one can't wait to see what's in store! Have you ever encountered the problem of not being able to send messages to specific members of a group? Unfortunately, with the current system, messages sent to a group are received by everyone in the group. However, there are ways to work around this issue. To access the Include and Exclude options while sending a message, simply click on the Arrow symbol located next to the attachment icon. This will open up a new section where you can choose which members to include or exclude from the message. It's a simple and effective way to ensure that your messages are only sent to the intended recipients. © 2024 IEEE.

关键词： Instant messaging applications

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Blockchain and Machine Learning for Data-Driven Insights in Consumer Behavior Analytics 13

Blockchain and Machine Learning for Data-Driven Insights in ...

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13th IEEE International Conference on Communication Systems and Network Technologies, CSNT 2024

作者： Rawat, Bhupender Singh Thapliyal, Nitin Pal, Sunil Kumar Mishra, Nikhil Verma, Rohan College of Smart Computing Coer University Roorkee India Graphic Era Hill University Department of Computer Science & Engineering Dehradun India Axis Colleges Department of Computer Science & Application Kanpur India Department of Computer Science & Engineering Dehradun India

ISBN: (纸本)9798350305463

Comparing with neural network method to more known methods, this article assesses their simplicity and effectiveness. Our approach uses new network pruning, interpretability-based regularization, and gradient-based sensitivity analysis. Numerous dataset trials show that the suggested method is more accurate, faster, and more durable than others. Also easier to understand. It turns out that small neural networks may simplify models without compromising accuracy. This comparative study shows how neural networks can handle complex data and make good predictions. These networks will be increasingly accessible in daily life. © 2024 IEEE.

关键词： Sensitivity analysis

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Multiprocessor Task Scheduling Optimization for Cyber-Physical System Using an Improved Salp Swarm Optimization Algorithm

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SN computer Science 2024年第1期5卷 184页

作者： Acharya, Biswaranjan Panda, Sucheta Ray, Niranjan K. Department of Computer Application Veer Surendra Sai University of Technology Burla Odisha Sambalpur 768018 India School of Computer Engineering KIIT Deemed to be University Odisha Bhubaneswar 751024 India

Salp Swarm Algorithm (SSA) is a bio-inspired optimization algorithm used in this paper to optimize the multiprocessor scheduling process in the current cyber-physical system. Although SSA is mainly utilized in terms of local search, in our case, an improved version has been introduced with the use of a Local Search Algorithm (LSA) and binary SSA, namely Improved SSA (ISSA). More to the point, eight optimization algorithms are compared with this proposed ISSA namely SSA, Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Grey Wolf Optimizer (GWO), Jaya Algorithm (JAYA), Chaotic Squirrel Search Algorithm (CSSA), Quantum-inspired Binary Chaotic Salp Swarm Algorithm (QBCSSA) and Space Transformation Search (STS) with SSA is termed as STS-SSA. The performance of ISSA along with the other 6 meta-heuristic and 2 improved versions of SSA algorithms are compared with 12 traditional benchmark functions and evaluated for 100 and 300 dimensions. Convergent curves have also been demonstrated and the proposed ISSA has been shown to find a global optimum within the very initial phase of iterations. For calculating the efficiency of the proposed algorithm, the gear train design problem has been employed. The proposed algorithm has demonstrated higher accuracy rates and better convergent values than the other applied algorithms. © 2024, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Benchmark function Cyber-physical system Gear train strategy Global optima Grid computing Local search algorithm (LSA) Multiprocessor task scheduling Salp swarm algorithm

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SSHTDNS: A Blockchain-Based Secure, Scalable, and High-Throughput Domain Name System 3

SSHTDNS: A Blockchain-Based Secure, Scalable, and High-Throu...

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3rd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2023

作者： Singh, Baldev Kavita Vivekananda Global University Department of Computer Science Engineering Jaipur India Chandigarh School of Business Department of Master of Computer Application India

ISBN: (纸本)9798350399264

The Internet's crucial domain name system is in charge of translating domain names into IP addresses. However, because of its dispersed structure with a hub, it is subject to significant security concerns. Since the creation of Bitcoin, blockchain has drawn a lot of attention owing to its decentralized, trustworthy, and secure features. In this article, we suggest SSHTDNS, a brand-brand-new domain name system built on the blockchain. SSHTDNS selects the consortium chain form to ensure the management of Top-Level Domain names, and these consortium nodes use linkable ring signature technology for identity anonymity and vote fairness. Shading protocol is used in multi-chain structures to increase the system's scalability and throughput. A domain name system that combines these methods can be safe, scalable, and high-throughput. © 2023 IEEE.

关键词： Blockchain

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Resource Management allocation in the CC Environments with Multi-Objective Optimization system 3

Resource Management allocation in the CC Environments with M...

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3rd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2023

作者： Bhambu, Pawan Kaur, Gursimran Vivekananda Global University Department of Computer Science Engineering Jaipur India Chandigarh School of Business Department of Master of Computer Application India

ISBN: (纸本)9798350399264

These days, the topic of cloud computing has become a very popular paradigm for providing services online. For the cloud data center to deliver cloud infrastructure services in response to user demand, a set of virtualized resources are required. In order to lower the degree as a result of resource loss and SLA violations, the necessity for optimum resource management becomes a crucial problem in cloud data centers. These issues are classified as NP-hard, and meta heuristics approaches are well suited to solving them. The article develops a multi-objective hybrid fruit fly optimization (MOHFO)-based method for SLA-conscious dynamic resource management in cloud data centers. For the fruit fly optimization technique, the Bald Eagle Search (BES) optimization behavior search capabilities. To balance resource waste and SLA breaches, the proposed solution employs dynamic consolidation and deployment of virtual machines (VMs) mechanism. The suggested technique utilizing Clouds to simulate different data center designs, using QoS measures to assess the experimental outcomes. The proposed MOHFO technique is assessed and contrasted to existing optimization strategies in terms of resource wastage, energy use, communication costs, and migration frequency in order to provide cloud computing with QoS-aware optimal resource provisioning. © 2023 IEEE.

关键词： Virtual machine

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Enhanced face recognition using rank-level fusion with multi-feature vectors and interval type-3 fuzzy set 3

Enhanced face recognition using rank-level fusion with multi...

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3rd IEEE Applied Signal Processing Conference, ASPCON 2023

作者： Ghosh, Manas Sing, Jamuna Kanta Rcc Institute of Information Technology Department of Computer Application Kolkata India Jadavpur University Department of Computer Science & Engineering Kolkata India

ISBN: (纸本)9798350325881

In the near past, interval type-3 fuzzy set theory has been introduced as a more effective means of addressing uncertainty in decision-making than its fuzzy set counterparts. This paper suggests an approach to face recognition which integrates multiple feature vectors and interval type-3 fuzzy sets for fuzzy rank-level fusion. Use of multiple feature vectors resolves inter-class resemblances while incorporating interval type-3 fuzzy membership function in generating fuzzy rank reduces the uncertainty due to intra-class divergences. The output of the classifier is regarded as confidence factor. For each feature vector, the fuzzy ranks are generated by formulating an interval type-3 fuzzy membership function for each of top-ordered H classes based on confidence factors utilizing all training feature vectors and those of the training samples of the respective class. Multiple fuzzy ranks, built upon interval type-3 fuzzy set, are generated by employing of multiple feature vectors. To determine the final score of a class, summation of the fuzzy rank complements is combined with the complement of arithmetic mean of respective classifier's output. Final scores are evaluated to conclude test image's class. Two publicly accessible face databases are used to evaluate the method and it has shown that the solution, advocated here, exhibits an improved effectiveness over its existing related counterparts. © 2023 IEEE.

关键词： Face recognition

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