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2025 International Conference on Pervasive Computational Technologies, ICPCT 2025

作者： Shravan, M. Kakad, Shital Mulani, Umar M Sharma, Geeti Tiwari, Mohit Mary Shiba, C. Sr University School of Business Telangana Warangal India Vishwakarma Institute of Technology Artificial Intelligence and Data Science Maharashtra Pune India Kj College of Engineering and Management Research Pune India India Bharati Vidyapeeth's College of Engineering Department of Computer Science and Engineering Delhi Delhi India R.M.K Engineering College Department of Computer Science and Business Systems Thiruvallur India

ISBN: (纸本)9798331508685

Blockchain, initially developed as the underlying technology for Bitcoin, has garnered significant attention for its applications beyond cryptocurrency, particularly in complex non-monetary domains. Utilizing cryptographic methods like hashing and asymmetric encryption, combined with a distributed consensus model, Blockchain-based ledgers achieve high levels of security and immutability, effectively removing the need for third-party intermediaries. Meanwhile, the rapid growth in Internet of Things (IoT) devices being connected to networks raises substantial concerns around security and privacy. Addressing these security challenges is essential for the expanding IoT landscape. This paper explores the blockchain solution by integrating cryptocurrency with IoT for enhanced security, reviewing recent studies and applications to evaluate Blockchain's role in IoT security, pinpoint challenges, and propose Blockchain-driven solutions to improve security in the IoT ecosystem. © 2025 IEEE.

关键词： Blockchain Cryptocurrency Internet of Things privacy Security

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Flexiswap: A Cross-Chain Decentralized Exchange Protocol

Flexiswap: A Cross-Chain Decentralized Exchange Protocol

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International Communication systems and Networks and Workshops, COMSNETS

作者： Kirti Singh Vinay J. Ribeiro Susmita Mandal Department of Computer Science and Engineering Indian Institute of Technology Bombay Mumbai India Institute for Development and Research in Banking Technology Hyderabad India

ISBN: (数字)9798331531195

ISBN: (纸本)9798331531201

Decentralized exchanges (DEXs) have emerged as a promising solution to enhance trustlessness in blockchain ecosystems and mitigate security threats associated with centralized exchanges. While platforms like Uniswap offer certain advantages, their limitation to exchanging tokens within a single blockchain restricts their utility. Moreover, exchanges relying on atomic swaps, such as AtomicDEX, are susceptible to grief attacks and exhibit low success ratios. In response to these challenges, we introduce FlexiSwap, an auction-based decentralized exchange protocol that leverages atomic swaps for exchanging native tokens between smart contract-compatible blockchains. FlexiSwap stands out by combining multiple bids to facilitate one-to-many exchanges, resulting in improved exchange values, successful execution of large-volume exchanges, and an improved success ratio. The protocol incorporates a penalization mechanism to deter grief attacks, ensuring that participants cannot withdraw from an exchange without incurring a loss once the counterparty has committed its assets. We also prove the protocol’s safety, liveness, and grief prevention. Our simulation results demonstrate that combining multiple bids helps achieve better exchange values and order-matching success rates. Additionally, we implemented our protocol on Ethereum-based blockchains. The experimental results show that combining bids increases overall gas usage, but the increase in the average gas user per bid is marginal.

关键词： Protocols Prevention and mitigation Simulation Ecosystems Trustless services Blockchains Safety Security

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Chained HotStuff Under Performance Attack

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IEEE Transactions on Dependable and Secure Computing 2025年

作者： Niu, Jianyu Wang, Minjie Gai, Fangyu Jalalzai, Mohammad M. Feng, Chen Zhang, Yinqian Southern University of Science and Technology Research Institute of Trustworthy Autonomous Systems School of Computer Science and Engineering China University of British Columbia School of Engineering Canada

Chained HotStuff is a state-of-the-art Byzantine fault-tolerant protocol for building decentralized systems like blockchains. Although chained HotStuff has been wildly adopted in many systems, its performance (e.g., throughput and latency) under attacks is still under-explored. In this paper, we develop a multi-metric evaluation framework to quantitatively analyze the performance of chained HotStuff with respect to its chain growth rate, chain quality, and latency. We propose several new attack strategies and evaluate their effects on the performance of chained HotStuff. Our analysis shows that the chain growth rate (resp, chain quality) of chained HotStuff under our attacks can drop to 4/9 (resp, 12/17 ) of that without attacks when one-third of nodes are Byzantine. In addition, we use our framework to evaluate a variant of chained HotStuff, DiemBFT and find that some engineering optimizations render it more vulnerable to some attacks than the original chained HotStuff. Finally, we provide two countermeasures, i.e., broadcasting QCs and the longest chain rule, to thwart these attacks. Our analysis shows that the proposed countermeasures can significantly reduce the latency (almost half of that in chained HotStuff) and make it impossible for an attacker to lower the chain quality by simple attacks. © 2004-2012 IEEE.

关键词： Fault tolerance

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Leveraging Edge Optimize Vision Transformer for Monkeypox Lesion Diagnosis on Mobile Devices

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computers, Materials & Continua 2025年第5期83卷 3227-3245页

作者： Poonam Sharma Bhisham Sharma Dhirendra Prasad Yadav Surbhi Bhatia Khan Ahlam Almusharraf Chitkara University Institute of Engineering and Technology Chitkara UniversityRajpura140401PunjabIndia Centre for Research Impact and Outcome Chitkara UniversityRajpura140401PunjabIndia Department of Computer Engineering&Applications G.L.A.UniversityMathura281406India Department of Data Science University of SalfordManchesterM54WTUK University Centre for Research and Development Chandigarh UniversityMohali140413PunjabIndia Division of Research and Development Lovely Professional UniversityPhagwara144411India Department of Management College of Business AdministrationPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Rapid and precise diagnostic tools for Monkeypox(Mpox)lesions are crucial for effective treatment because their symptoms are similar to those of other pox-related illnesses,like smallpox and *** morphological similarities between smallpox,chickenpox,and monkeypox,particularly in how they appear as rashes and skin lesions,which can sometimes make diagnosis *** lesions appear in many simultaneous phases and are more diffuse,often beginning on the *** contrast,monkeypox lesions emerge progressively and are typically centralized on the face,palms,and *** provide accessible diagnostics,this study introduces a novel method for automated monkeypox lesion classification using the HMTNet(Hybrid Mobile Transformer Network).The convolutional layers and Vision Transformers(ViT)are combined to enhance the spatial *** addition,we replace the classical MHSA(Multi-head self-attention)with the WMHSA(Window-based Multi-Head Self-Attention)to effectively capture long-range dependencies within image patches and depth-wise separable convolutions for local feature *** trained and validated HMTNet on the two datasets for binary and multiclass *** model achieved 98.38% accuracy for multiclass classification using cross-validation and 99.25% accuracy for binary *** findings show that the model has the potential to be a useful diagnostic tool for monkeypox,especially in environments with limited resources.

关键词： Monkeypox disease classification local global transformer

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research on Task Migration Problem Based on Link Uncertainty in Adversarial Scenarios 25th

Research on Task Migration Problem Based on Link Uncertainty...

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25th International Conference on Parallel and Distributed Computing, Applications and Technologies, PDCAT 2024

作者： Xing, Xiangxiang Li, Pan Zuo, Tianyu Jiang, Yuanshuang Di, Kai Wang, Xin Jiao, Xun Jiang, Yichuan Chen, Dan School of Cyber Science and Engineering Southeast University Jiangsu Nanjing211189 China School of Computer Science and Engineering Southeast University Jiangsu Nanjing211189 China No. 8511 Research Institute of CASIC Jiangsu Nanjing210007 China Institute of Systems Engineering Academy of Military Science Beijing China College of Electronics and Information Engineering Beibu Gulf University Guangxi Qinzhou535000 China

ISBN: (纸本)9789819642069

With developments in artificial intelligence, computer science, and network technologies, modern confrontational scenarios are increasingly related to multi-agent systems characterized by multi-network. To reduce the effects of external factors on task execution, a task migration algorithm based on link uncertainty in adversarial scenarios is designed. Firstly, this thesis models the underlying problem as an integer programming problem, defining the optimization objectives and constraints accordingly. Subsequently, inter- and intra-network layer task migration is carried out based on gene expression programming to ensure the optimization objective and improve the load balance. Finally, experimental results demonstrate the algorithm’s efficacy in improving migration benefits and mitigating the impact of uncertainty. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Gene expression programming Optimization Objectives Task migration Uncertainty

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SPDGrNet: A Lightweight and Efficient Image Classification Network for Zea mays Diseases

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Journal of Crop Health 2025年第3期77卷 1-12页

作者： Xu, Laixiang Cao, Bingxu Su, Jing feng Zhang, Fengyue Song, Hongyun Zhao, Junmin School of Computer and Data Science Research Center of Smart City and Big Data Engineering of Henan Province Henan University of Urban Construction Pingdingshan 467036 China School of Information Engineering Luohe Vocational Technology College Henan Luohe China Institute of Technology University of Technology Luohe Luohe 462000 China School of Computer and Data Science Innovation Laboratory of Smart Traffic and Big Data Development of Hainan Province Henan University of Urban Construction Pingdingshan 467036 China School of Computer and Data Science Henan University of Urban Construction Pingdingshan 467036 China School of Computer and Data Science Research Center of Smart City and Big Data Engineering of Henan Province Research Center of Intelligent Campus Application Engineering of Henan Province Innovation Laboratory of Smart Traffic and Big Data Development of Hainan Province Henan University of Urban Construction Pingdingshan 467036 China

Controlling diseases on the foliage of cultivated plants has a major impact on crop yield and quality. Leaf symptoms and environmental information are the basis of crop disease and pest identification. Due to the complexity and diversity of disease leaf symptoms and environmental information, the accuracy of crop disease detection methods has decreased. Aiming at low disease identification efficiency and difficult feature modeling, we propose a new deep learning algorithm and obtain ideal results. We used improved convolutional neural networks (CNNs) SPDNet and GrNet (SPDGrNet) to perform Zea mays disease identification. The proposed research and analysis focus on four categories of Zea mays symptoms: healthy, leaf blight, southern leaf blight and grey spot. The experimental results and analysis confirm that the proposed approach outperforms other excellent plant disease recognition algorithms and achieves an overall classification accuracy of 98.96%. When compared to AlexNet, VGG-16, Inception-V4, ShuffleNet-V3, and Efficient-B7, the proposed model achieves accuracy improvements of 27.78%, 19.05%, 14.59%, 10.28%, and 7.06%, respectively, with corresponding accuracies of 71.18%, 79.91%, 84.37%, 88.68%, and 91.9%. The proposed model has outstanding generalization ability in open-source databases, such as the PlantifyDr, Plant Pathology, and New Plant Diseases Dataset. The suggested strategy can provide ideas for transplanting models into mobile disease detection equipment. This is very helpful in the intelligent development of agricultural systems and crop leaf disease analysis. © The author(s), exclusively licensed to Springer-Verlag GmbH Germany, a part of Springer Nature 2025.

关键词： Crop leaf disease control Deep learning Disease detection Generalization Zea mays

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Advancements in Wearable Healthcare Technologies for Remote Patient Monitoring 12th

Advancements in Wearable Healthcare Technologies for Remote ...

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12th International Conference on Frontiers of Intelligent Computing: Theory and Applications, FICTA 2024

作者： Pareek, Shashank Chohan, Jasgurpreet Singh Anand, Rohit Goyal, Bhawna Dogra, Ayush Alkhayyat, Ahmed Department of Computer Science Engineering Chandigarh University Mohali India School of Mechanical Engineering Rayat Bahra University Punjab Mohali India New Delhi India University Center for Research and Development Chandigarh University Punjab Mohali India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India College of Technical Engineering The Islamic University Najaf Iraq

ISBN: (纸本)9789819601424

The widespread availability of wearable healthcare devices has significantly altered the landscape of remote patient monitoring. This study explores the complex interplay between research, practical applications, and the disruptive potential of emerging technologies in the healthcare sector. It provides a thorough overview of the present state of the art in wearable healthcare devices through a thorough examination of the current literature and a detailed analysis of the approaches used. These days, you can track a lot more than just your steps and heart rate with a wearable device. They incorporate a number of sensors able to monitor physiological parameters, identify outliers, and wirelessly transmit this information in real time. Implications for patient care and health system administration are explored, as are the sorts of sensors used to collect the data. The importance of connectivity and data transfer in facilitating open lines of communication between patients and medical professionals is also investigated. The study also explores the many shapes and styles available for these gadgets to meet a variety of user requirements. Several areas of medicine can benefit from remote patient monitoring. Wearable healthcare technologies are demonstrating their value in a wide range of settings, from the management of chronic diseases to postsurgery and recovery monitoring, care for the elderly, and even mental health and well-being. In order to demonstrate how these technologies have been adopted and integrated into various healthcare contexts, the paper includes case studies and examples that emphasize their efficacy. Integration of real-time data analysis and AI is a major development in this area. In this paper, we will look at how artificial intelligence algorithms process the mountain of data produced by wearables to extract useful information for healthcare professionals in real time. The integration of electronic health records (EHRs) and remote patient monitori

关键词： Electronic health record

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Quality of Service-aware 6G-Enabled NB-IoT for Health Monitoring in Long Distance High-Speed Trains

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IEEE Transactions on Consumer Electronics 2025年

作者： Roy, Bipasha Guha Roy, Deepsubhra Guha Dutta, Piyali Khan, Surbhi Bhatia Asiri, Fatima Ayadi, Manel Institute of Engineering and Management Kolkata India Institute of Engineering and Management Kolkata India University of Salford Chitkara University Institute of Engineering and Technology Chitkara University Department of Data Science United Kingdom University Centre for Research and Development Chandigarh University India Centre for Research Impact and Outcome Punjab Rajpura140401 India King Khalid University College of computer science Informatics and computer systems department Saudi Arabia Princess Nourah bint Abdulrahman University College of Computer and Information Sciences Department of Information Systems Riyadh11671 Saudi Arabia

Internet of Things connectivity in home health monitoring is a high-in-demand application area. The electronics industry and procedural researchers seek high-end, secured, on-time, cost-effective ways to build reliable quality of service (QoS) proved autonomous systems using existing wireless techniques. Also, the continuous availability of a traffic-free gateway, particularly in isolated places, is necessary for large-scale data gathering and real-time data update processes to function the sensor nodes in an Internet of Things (IoT) network. Improved Narrowband IoT (NB-IoT) is one of the most desirable networks offered by 6th generation (6G) connectivity in IoT-associated remote-monitoring proceedings. In this article, we propose a QoS-aware narrow bandwidth allocation-based prototype model for healthcare monitoring in long-distance high-speed trains during the patient transfer from home to the healthcare center or vice versa. This article demonstrates a possible enhancement in social aspects of cognitive IoT applications with large data systems in industrial informatics. © 1975-2011 IEEE.

关键词： Frequency allocation

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Co-Attention Based Multi-Channel TF-GridNet for Speech Separation with Ad-Hoc Microphone Arrays

Co-Attention Based Multi-Channel TF-GridNet for Speech Separ...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Guo, Hongmei Feng, Linfeng Chen, Yijiang Li, Xueqing Zhu, Boyu Wang, Hao-Yu Zhang, Xiao-Lei Li, Xuelong China Telecom Beijing China School of Marine Science and Technology Northwestern Polytechnical University Xi'an China Research & Development Institute Northwestern Polytechnical University in Shenzhen Shenzhen China School of Systems Engineering and Intelligent Manufacturing Southern University of Science and Technology Shenzhen China

ISBN: (纸本)9798350368741

Speech separation using ad-hoc microphone arrays has been explored, but there is still significant room for improvement, especially in complex scenarios with varying channel conditions. Co-attention, a feature fusion mechanism, is widely used in multimodal fusion to capture the cooperation between modalities and enhance the representation of extracted features. In this paper, we propose a co-attention-based multi-channel model for speech separation with ad-hoc microphone arrays. The co-attention mechanism is integrated into the model to enhance the interaction between different speakers across multiple channels, enabling efficient channel fusion. To the best of our knowledge, this is the first work to apply co-attention for speech separation. Experimental results demonstrate that the proposed method significantly outperforms existing approaches, underscoring the importance of co-attention in optimizing channel fusion for speech separation in challenging acoustic environments. © 2025 IEEE.

关键词： ad-hoc microphone arrays AI flow co-attention mechanism Speech separation

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Chat with MES: LLM-driven user interface for manipulating garment manufacturing system through natural language

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Journal of Manufacturing systems 2025年 80卷 1093-1107页

作者： Yuan, Zhaolin Li, Ming Liu, Chang Han, Fangyuan Huang, Haolun Dai, Hong-Ning Institute of Artificial Intelligence University of Science and Technology Beijing Beijing China Shunde Innovation School University of Science and Technology Beijing Guangdong China Department of Industrial and Systems Engineering The Hong Kong Polytechnic University Hong Kong Research Institute of Advanced Manufacturing The Hong Kong Polytechnic University Hong Kong Research Centre for Digital Transformation of Tourism The Hong Kong Polytechnic University Hung Hom Hong Kong Centre for Transformative Garment Production Hong Kong Science Park Pak Shek Kok Hong Kong Department of Computer Science Hong Kong Baptist University Hong Kong School of Intelligent Systems Science and Engineering Jinan University Zhuhai China

This paper presents Chat with MES (CWM), an AI agent system, which integrates LLMs into the Manufacturing Execution System (MES), serving as the "ears, mouth, and the brain". This system promotes a paradigm shift in MES interactions from Graphical User Interface (GUI) to natural language interface", offering a more natural and efficient way for workers to manipulate the manufacturing system. Compared with the traditional GUI, both the maintenance costs for developers and the learning costs and the complexity of use for workers are significantly reduced. This paper also contributes two technical improvements to address the challenges of using LLM-Agent in serious manufacturing scenarios. The first one is Request Rewriting, designed to rephrase or automatically follow up on non-standardized and ambiguous requests from users. The second innovation is the Multi-Step Dynamic Operations Generation, which is a pre-execution planning technique similar to Chain-of-Thought (COT), used to enhance the success rate of handling complex tasks involving multiple operations. A case study conducted on a simulated garment MES with 55 manually designed requests demonstrates the high execution accuracy of CWM (80%) and the improvement achieved through query rewriting (9.1%) and Multi-Step Dynamic operations generation (18.2%). The source code of CWM, along with the simulated MES and benchmark requests, is publicly accessible. © 2025 The Authors

关键词： Graphical user interfaces

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