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

作者： Zhang, Yuwei Wu, Yan Liu, Yanming Peng, Xinyue College of Electronic and Information Engineering Tongji University Shanghai China School of Software Technology Zhejiang University Hangzhou China College of Electronic and Information Engineering Southeast University Nanjing China

ISBN: (纸本)9798350368741

Extracting valuable visual cues for downstream vision tasks poses a particular challenge under unknown degradations. A straightforward solution is to preprocess images using image restoration methods, but their high computational complexity renders them unsuitable for real-time tasks. Recent efforts have aimed to enhance image representations optimized by downstream task losses. However, these approaches are confined to known single degradation scenarios, constraining their practical applicability in unpredictable environments. Therefore, we propose a Chain-of-thought Prompted Adaptive Enhancer, CPA-Enhancer, for enhancing important features crucial for downstream vision tasks under unknown degradations. Specifically, CPA-Enhancer progressively adapts its enhancement strategies under the step-by-step guidance of CoT prompts that encode degradation-related information. Overall, CPA-Enhancer is a plug-and-play lightweight enhancement model that can be integrated into any vision pipeline and trained with task-related losses, without any prior knowledge of the degradation type. Extensive experiments demonstrate that CPA-Enhancer significantly improves performance across various vision tasks under unknown degradations. The codes is available at https://***/zyw-stu/CPA-Enhancer. © 2025 IEEE.

关键词： adaptive enhancer chain-of-thought prompting unknown degradations

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ACbot:an IIoT platform for industrial robots

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Frontiers of Computer Science 2025年第4期19卷 13-27页

作者： Rui WANG Xudong MOU Tianyu WO Mingyang ZHANG Yuxin LIU Tiejun WANG Pin LIU Jihong YAN Xudong LIU School of Computer Science and Engineering Beihang UniversityBeijing 100191China Zhongguancun Laboratory Beijing 100194China School of Software Beihang UniversityBeijing 100191China School of Mechatronics Engineering Harbin Institute of TechnologyHarbin 150001China Hangzhou Innovation Institute Beihang UniversityHangzhou 310051China School of Information Engineering China University of GeosciencesBeijing 100083China

As the application of Industrial Robots(IRs)scales and related participants increase,the demands for intelligent Operation and Maintenance(O&M)and multi-tenant collaboration *** methods could no longer cover the requirements,while the Industrial Internet of Things(IIoT)has been considered a promising ***,there’s a lack of IIoT platforms dedicated to IR O&M,including IR maintenance,process optimization,and knowledge *** this context,this paper puts forward the multi-tenant-oriented ACbot platform,which attempts to provide the first holistic IIoT-based solution for O&M of *** on an information model designed for the IR field,ACbot has implemented an application architecture with resource and microservice management across the cloud and multiple *** this basis,we develop four vital applications including real-time monitoring,health management,process optimization,and knowledge *** have deployed the ACbot platform in real-world scenarios that contain various participants,types of IRs,and *** date,ACbot has been accessed by 10 organizations and managed 60 industrial robots,demonstrating that the platform fulfills our ***,the application results also showcase its robustness,versatility,and adaptability for developing and hosting intelligent robot applications.

关键词： IIoT platform industrial robots cloud-edge collaboration intelligent applications

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Controlling update distance and enhancing fair trainable prototypes in federated learning under data and model heterogeneity

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Defence technology 2025年 47卷 15-31页

作者： Yin, Kangning Ding, Zhen Ji, Xinhui Wang, Zhiguo School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu610054 China Institute of Public Security Kash Institute of Electronics and Information Industry Kash844000 China Shanghai New Energy Vehicle Public Data Collection and Monitoring Research Center Shanghai200241 China

Heterogeneous federated learning (HtFL) has gained significant attention due to its ability to accommodate diverse models and data from distributed combat units. The prototype-based HtFL methods were proposed to reduce the high communication cost of transmitting model parameters. These methods allow for the sharing of only class representatives between heterogeneous clients while maintaining privacy. However, existing prototype learning approaches fail to take the data distribution of clients into consideration, which results in suboptimal global prototype learning and insufficient client model personalization capabilities. To address these issues, we propose a fair trainable prototype federated learning (FedFTP) algorithm, which employs a fair sampling training prototype (FSTP) mechanism and a hyperbolic space constraints (HSC) mechanism to enhance the fairness and effectiveness of prototype learning on the server in heterogeneous environments. Furthermore, a local prototype stable update (LPSU) mechanism is proposed as a means of maintaining personalization while promoting global consistency, based on contrastive learning. Comprehensive experimental results demonstrate that FedFTP achieves state-of-the-art performance in HtFL scenarios. © 2025 China Ordnance Society

关键词： Federated learning

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Task Consistent Prototype Learning for Incremental Few-Shot Semantic Segmentation 27th

Task Consistent Prototype Learning for Incremental Few-Shot...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Xu, Wenbo Wu, Yanan Jiang, Haoran Wang, Yang Wu, Qiang Zhang, Jian Faculty of Engineering and Information Technology University of Technology Sydney Sydney2007 Australia School of Computer and Information Technology Beijing Jiaotong University Beijing100044 China Department of Computer Science and Software Engineering Concordia University MontrealH3G2J1 Canada

ISBN: (纸本)9783031783463

Incremental Few-Shot Semantic Segmentation (iFSS) tackles a task that requires a model to continually expand its segmentation capability on novel classes using only a few annotated examples. Typical incremental approaches encounter a challenge that the objective of the base training phase (fitting base classes with sufficient instances) does not align with the incremental learning phase (rapidly adapting to new classes with less forgetting). This disconnect can result in suboptimal performance in the incremental setting. This study introduces a meta-learning-based prototype approach that encourages the model to learn how to adapt quickly while preserving previous knowledge. Concretely, we mimic the incremental evaluation protocol during the base training session by sampling a sequence of pseudo-incremental tasks. Each task in the simulated sequence is trained using a meta-objective to enable rapid adaptation without forgetting. To enhance discrimination among class prototypes, we introduce prototype space redistribution learning, which dynamically updates class prototypes to establish optimal inter-prototype boundaries within the prototype space. Extensive experiments on iFSS datasets built upon PASCAL and COCO benchmarks show the advanced performance of the proposed approach, offering valuable insights for addressing iFSS challenges. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Semantic Segmentation

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Predictive Caching of File System for Database Workload Management 1

Predictive Caching of File System for Database Workload Mana...

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1st International Conference on AIML-Applications for engineering and technology, ICAET 2025

作者： Jadhav, Rohini Jadhav, Veena Pawar, Prajakta Kannaujia, Abhishek Kumar, Abhishek Gohil, Jayesh College of Engineering Department of Information Technology Pune India College of Engineering Department of Computer Engineering Pune India Bharati Vidyapeeth College of Engineering Department of Computer Engineering Lavale Pune India Veritas Principal Software Engineering India

ISBN: (纸本)9798350355611

The proactive caching technique known as 'predictive caching' attempts to improve file system performance by anticipating and pre-fetching data that is likely to be requested in the future. Conventional caching strategies, such LRU (Least Recently Used) and LFU (Least Frequently Used), base their decision on which material to keep in the cache on historical access patterns. Although these methods work well in many situations, they could not completely take advantage of the temporal and geographical proximity of file system access patterns, which could result in less-than-ideal cache use. Utilizing machine learning algorithms, statistical analysis, or heuristics, predictive caching makes predictions about future access patterns based on past data, system status, file properties, or user activity. So we propose a predictive caching technique which reduce access latency and boost system performance by pre-fetching and storing pertinent data ahead of time in anticipation of incoming data accesses. © 2025 IEEE.

关键词： Dynamic Data File Access Pattern Predictive Caching Random Forest Classifier

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Energy Consumption Minimization Algorithm in IoT Network Integrating Data and Energy Transfer

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IEEE Access 2025年 13卷 75924-75934页

作者： Wang, Yang Yu, Qin Hu, Jie Yang, Kun University of Electronic Science and Technology of China Huzhou313001 China School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu611731 China School of Intelligent Software and Engineering Nanjing University Suzhou Campus Suzhou215163 China

Nowadays, Internet of Things (IoT) devices are widely deployed and how to power such massive IoT devices has become a significant challenge. Especially for the battery-powered IoT devices, limited energy storage and continuous energy consumption result in frequent battery replacement and potential environmental pollution. Because radio frequency (RF) signals carry not only information but also energy, Wireless Power Transfer (WPT) in RF domain has been proved to be a reliable and controllable technology to deal with this problem. A typical Data and Energy Integrated Network (DEIN) commonly conceives one DEIN base station and numerable DEIN devices. The DEIN base station is capable of transmitting data and energy integrated signals to the DEIN devices with Simultaneous Wireless information and Power Transfer (SWIPT) technology, and the DEIN devices are capable of harvesting energy from the downlink RF signals for uplink data transmission. In order to coordinate the wireless data and energy transmission and avoid conflicts, a transmission protocol based on the Time-Division Multiple Access (TDMA) scheme is designed. Furthermore, an optimization problem of minimizing the energy consumption of the DEIN base station is formulated. In order to address this problem, this paper proposes an energy-efficient algorithm by jointly optimizing of the transmission power of the DEIN base station, the uplink and downlink time slots and power splitting factors of the IoT devices. Both the effectiveness and efficiency of the proposed joint optimization algorithm have been validated with the simulation. © 2013 IEEE.

关键词： Energy utilization

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Spatial transformation based on integrated artificial intelligence system: a case study of an ancient village in Jiangxi Province 2

Spatial transformation based on integrated artificial intell...

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2nd International Conference on Big Data, Computational Intelligence, and Applications, BDCIA 2024

作者： Zhou, Yanli Liu, Liping Jiangxi Institute of Fashion Technology Nanchang330201 China School of Software Engineering Jiangxi Vocational and Technical College of Information Application Nanchang330043 China

ISBN: (纸本)9781510689053

With the rapid development of technology and people's increasing attention to healthy living quality, deeply integrating intelligent technology into the health field of elderly housing has become an irreversible and important trend. This article proposes an innovative intelligent management system based on artificial intelligence (AI) to meet the urgent needs of health monitoring and care for the elderly. This system cleverly integrates cutting-edge technologies such as the Internet of Things (IoT), big data analysis, and AI, achieving comprehensive and all-weather intelligent monitoring and management of the living environment and health status of the elderly. The system collects real-time physiological data and lifestyle habits of elderly people through intelligent devices, and uses big data algorithms for in-depth analysis to provide personalized health management and nursing advice for each elderly person. At the same time, the intelligent management system can also timely detect and warn potential health risks, ensuring that the elderly receive timely and effective medical care. The practical results show that the application of this intelligent management system can significantly improve the quality of life and happiness of the elderly, and promote the intelligent upgrading of the elderly housing health field. © 2025 SPIE.

关键词： Electronic health record

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ICCG:low-cost and efficient consistency with adaptive synchronization for metadata replication

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Frontiers of Computer Science 2025年第1期19卷 53-70页

作者： Chenhao ZHANG Liang WANG Jing SHANG Zhiwen XIAO Limin XIAO Meng HAN Bing WEI Runnan SHEN Jinquan WANG State Key Laboratory of Software Development Environment Beihang UniversityBeijing 100191China School of Computer Science and Engineering Beihang UniversityBeijing 100191China School of Cyberspace Security Hainan UniversityHaikou 570228China China Mobile Information Technology Center Beijing 100033China

The rapid growth in the storage scale of wide-area distributed file systems (DFS) calls for fast and scalable metadata management. Metadata replication is the widely used technique for improving the performance and scalability of metadata management. Because of the POSIX requirement of file systems, many existing metadata management techniques utilize a costly design for the sake of metadata consistency, leading to unacceptable performance overhead. We propose a new metadata consistency maintenance method (ICCG), which includes an incremental consistency guaranteed directory tree synchronization (ICGDT) and a causal consistency guaranteed replica index synchronization (CCGRI), to ensure system performance without sacrificing metadata consistency. ICGDT uses a flexible consistency scheme based on the state of files and directories maintained through the conflict state tree to provide an incremental consistency for metadata, which satisfies both metadata consistency and performance requirements. CCGRI ensures low latency and consistent access to data by establishing a causal consistency for replica indexes through multi-version extent trees and logical time. Experimental results demonstrate the effectiveness of our methods. Compared with the strong consistency policies widely used in modern DFSes, our methods significantly improve the system performance. For example, in file creation, ICCG can improve the performance of directory tree operations by at least 36.4 times.

关键词： metadata management metadata replication consistency directory tree replica index

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A Lightweight Authentication Protocol for RFID-Assisted Supply Chain Management System

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IEEE Internet of Things Journal 2025年第9期12卷 12845-12852页

作者： Tariq, Tayyaba Kuo, Wen-Chung Mahmood, Khalid Shamshad, Salman Das, Ashok Kumar Alenazi, Mohammed J. F. National Yunlin University of Science and Technology Graduate School of Engineering Science and Technology Yunlin Douliu64002 Taiwan National Yunlin University of Science and Technology Department of Computer Science and Information Engineering Douliu64002 Taiwan National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Yunlin Douliu64002 Taiwan University of Lahore Department of Software Engineering Lahore54590 Pakistan International Institute of Information Technology Hyderabad Center for Security Theory and Algorithmic Research Hyderabad500032 India Korea University College of Informatics Department of Computer Science and Engineering Seoul02841 Korea Republic of King Saud University College of Computer and Information Sciences Department of Computer Engineering Riyadh11451 Saudi Arabia

In the evolving landscape of supply chain management, the integration of radio-frequency identification (RFID) technology has marked a significant milestone. This development has led to the emergence of a new system in RFID-based supply chain management, which is intricately linked with the advances in the Internet of Things (IoT). RFID technology employs electromagnetic fields to identify and track tags on objects and revolutionizes the management and tracking of items in the supply chain. However, the public communication among RFID tags, RFID readers, and supply chain infrastructure predominantly escalates security and privacy challenges. Several authentication protocols have been proposed to overcome these challenges. However, the vulnerability of most proposed protocols to numerous security attacks renders them inefficient. Therefore, to address these crucial challenges, we devised an RFID-based authentication protocol for supply chain management systems. The incorporation of a physically unclonable function (PUF) into the protocol fortifies the system against physical tampering attacks. To validate the security and effectiveness of the devised protocol, both informal and formal security analysis are conducted. The formal security analysis is conducted using the widely used random oracle model. The informal security analysis reveals that the devised protocol provides enhanced and efficient security features. Furthermore, we perform a comparative analysis with related protocols, focusing on critical performance metrics like communication cost, computation cost, and overall security features. The results of the comparative analysis are promising, indicating a substantial 30.92% reduction in computational cost and a 23.98% reduction in communication cost in comparison to related protocols, thus highlighting the protocol’s superior performance and resource efficiency. © 2014 IEEE.

关键词： Authentication Protocol

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Autonomous sortie scheduling for carrier aircraft fleet under towing mode

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Defence technology(防务技术) 2025年第1期43卷 1-12页

作者： Zhilong Deng Xuanbo Liu Yuqi Dou Xichao Su Haixu Li Lei Wang Xinwei Wang Department of Engineering Mechanics State Key Laboratory of Structural AnalysisOptimization and CAE Software for Industrial EquipmentDalian University of TechnologyDalian116024China School of Mathematical Sciences Dalian University of TechnologyDalian 116024China Naval Aviation University Yantai 264001China China State Shipbuilding Corporation Systems Engineering Research Institute Beijing 100094China Department of Automation School of Information Science and TechnologyTsinghua UniversityBeijing 100084China

Safe and efficient sortie scheduling on the confined flight deck is crucial for maintaining high combat effectiveness of the aircraft *** primary difficulty exactly lies in the spatiotemporal coordination,i.e.,allocation of limited supporting resources and collision-avoidance between heterogeneous dispatch *** this paper,the problem is investigated in the perspective of hybrid flow-shop scheduling problem by synthesizing the precedence,space and resource ***,eight processing procedures are abstracted,where tractors,preparing spots,catapults,and launching are virtualized as *** analyzing the constraints in sortie scheduling,a mixed-integer planning model is *** particular,the constraint on preparing spot occupancy is improved to further enhance the sortie *** basic trajectory library for each dispatch entity is generated and a delayed strategy is integrated to address the collision-avoidance *** efficiently solve the formulated HFSP,which is essentially a combinatorial problem with tightly coupled constraints,a chaos-initialized genetic algorithm is *** solution framework is validated by the simulation environment referring to the Fort-class carrier,exhibiting higher sortie efficiency when compared to existing *** animation of the simulation results is available at ***/video/BV14t421A7Tt/.The study presents a promising supporting technique for autonomous flight deck operation in the foreseeable future,and can be easily extended to other supporting scenarios,e.g.,ammunition delivery and aircraft maintenance.

关键词： Carrier aircraft Autonomous sortie scheduling Resource allocation Collision-avoidance Hybrid flow-shop scheduling problem

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