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Position-Aware and Subgraph Enhanced Dynamic Graph Contrastive Learning on Discrete-Time Dynamic Graph

computers, Materials & Continua 2024年第11期81卷 2895-2909页

作者： Jian Feng Tian Liu Cailing Du College of Computer Science&Technology Xi’an University of Science and TechnologyXi’an710054China

Unsupervised learning methods such as graph contrastive learning have been used for dynamic graph represen-tation learning to eliminate the dependence of ***,existing studies neglect positional information when learning discrete snapshots,resulting in insufficient network topology *** the same time,due to the lack of appropriate data augmentation methods,it is difficult to capture the evolving patterns of the network *** address the above problems,a position-aware and subgraph enhanced dynamic graph contrastive learning method is proposed for discrete-time dynamic ***,the global snapshot is built based on the historical snapshots to express the stable pattern of the dynamic graph,and the random walk is used to obtain the position representation by learning the positional information of the ***,a new data augmentation method is carried out from the perspectives of short-term changes and long-term stable structures of dynamic ***,subgraph sampling based on snapshots and global snapshots is used to obtain two structural augmentation views,and node structures and evolving patterns are learned by combining graph neural network,gated recurrent unit,and attention ***,the quality of node representation is improved by combining the contrastive learning between different structural augmentation views and between the two representations of structure and *** results on four real datasets show that the performance of the proposed method is better than the existing unsupervised methods,and it is more competitive than the supervised learning method under a semi-supervised setting.

关键词： Dynamic graph representation learning graph contrastive learning structure representation position representation evolving pattern

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NeurDB: an AI-powered autonomous data system

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science China(Information sciences) 2024年第10期67卷 129-150页

作者： Beng Chin OOI Shaofeng CAI Gang CHEN Yanyan SHEN Kian-Lee TAN Yuncheng WU Xiaokui XIAO Naili XING Cong YUE Lingze ZENG Meihui ZHANG Zhanhao ZHAO School of Computing National University of Singapore College of Computer Science and Technology Zhejiang University Department of Computer Science and Engineering Shanghai Jiao Tong University School of Information Renmin University of China School of Computer Science and Technology Beijing Institute of Technology

In the wake of rapid advancements in artificial intelligence(AI), we stand on the brink of a transformative leap in data systems. The imminent fusion of AI and DB(AI×DB) promises a new generation of data systems, which will relieve the burden on end-users across all industry sectors by featuring AI-enhanced functionalities, such as personalized and automated in-database AI-powered analytics, and selfdriving capabilities for improved system performance. In this paper, we explore the evolution of data systems with a focus on deepening the fusion of AI and DB. We present NeurDB, an AI-powered autonomous data system designed to fully embrace AI design in each major system component and provide in-database AI-powered analytics. We outline the conceptual and architectural overview of NeurDB, discuss its design choices and key components, and report its current development and future plan.

关键词： AI$\times$DB in-database AI intelligent data system

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Compressed Video Enhancement with Spatio-Temporal Multi-Feature Extraction

Compressed Video Enhancement with Spatio-Temporal Multi-Feat...

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2023 China Automation Congress, CAC 2023

作者： Ru, Haihan Chen, Jing Chen, Kemi Zuo, YuTing Chen, Xia College of Information Science and Engineering Huaqiao University Xiamen China College of Computer Science and Technology Huaqiao University Xiamen China

ISBN: (纸本)9798350303759

Bandwidth limitations require transmitting the original video in a compressed format, leading to video artifacts and quality degradation. Therefore, compressed video enhancement is very important. In recent years, deep learning methods have gained prominence in compressed video enhancement due to their ability to efficiently restore lost details in specific frames by extracting features. Information extraction can be influenced by video artifacts in preceding and subsequent frames, even when techniques like optical flow estimation or quality-based frame selection are employed. To better capture artifact removal details, this paper introduces a spatiotemporal multi-feature extraction method for more accurate video reconstruction. The experimental results show that the peak Signal-To-Noise Ratio (PSNR) of the video enhanced by the method proposed in this paper is about 0.06 dB higher(QP37) on average when compared to the video enhanced by some other methods (e.g., MFQE2.0, MFQE1.0, DS-CNN). © 2023 IEEE.

关键词： Convolution

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Ensemble Prototype Networks for Unsupervised Cross-modal Hashing with Cross-Task Consistency

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IEEE Transactions on Multimedia 2025年 27卷 3476-3488页

作者： Liu, Xiaoqing Zeng, Huanqiang Shi, Yifan Zhu, Jianqing Yang, Kaixiang Yu, Zhiwen Huaqiao University School of Information Science and Engineering Xiamen361021 China Huaqiao University School of Engineering Quanzhou362021 China South China University of Technology School of Computer Science and Engineering Guangzhou510641 China

In the swiftly advancing realm of information retrieval, unsupervised cross-modal hashing has emerged as a focal point of research, taking advantage of the inherent advantages of the multifaceted and dynamism inherent in multimedia data. Existing unsupervised cross-modal hashing methods rely mainly on initial pre-trained correlations among cross-modal features, and the inaccurate neighborhood correlations impacts the presentation of common semantics throughout the optimization. To address the aforementioned issues, we propose Ensemble Prototype Networks (EPNet), which delineates class attributes of cross-modal instances through an ensemble clustering methodology. EPNet seeks to extract correlation information between instances by leveraging local correlation aggregation and ensemble clustering from multiple perspectives, aiming to reduce initialization effects and enhance cross-modal representations. Specifically, the local correlation aggregation is first proposed within a batch of semantic affinity relationships to generate a precise and compact hash code among cross-modal instances. Secondly, the ensemble prototype module is employed to discern the class attributes of deep features, thereby aiding the model in extracting more universally applicable feature representations. Thirdly, an early attempt to constrict the representational congruity of local semantic affinity relationships and deep feature ensemble prototype correlations using cross-task consistency loss aims to enhance the representation of cross-modal common semantic features. Finally, EPNet outperforms several state-of-the-art cross-modal retrieval methods on three real-world image-text datasets in extensive experiments. © 2025 IEEE.

关键词： Semantics

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Starlet:Network defense resource allocation with multi-armed bandits for cloud-edge crowd sensing in IoT

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Digital Communications and Networks 2024年第3期10卷 586-596页

作者： Hui Xia Ning Huang Xuecai Feng Rui Zhang Chao Liu College of Computer Science and Technology Ocean University of ChinaQingdao266100China

The cloud platform has limited defense resources to fully protect the edge servers used to process crowd sensing data in Internet of *** guarantee the network's overall security,we present a network defense resource allocation with multi-armed bandits to maximize the network's overall ***,we propose the method for dynamic setting of node defense resource thresholds to obtain the defender(attacker)benefit function of edge servers(nodes)and ***,we design a defense resource sharing mechanism for neighboring nodes to obtain the defense capability of ***,we use the decomposability and Lipschitz conti-nuity of the defender's total expected utility to reduce the difference between the utility's discrete and continuous arms and analyze the difference ***,experimental results show that the method maximizes the defender's total expected utility and reduces the difference between the discrete and continuous arms of the utility.

关键词： Internet of things Defense resource sharing Multi-armed bandits Defense resource allocation

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Efficiency and mechanism of controlling phosphorus release from sediment using a biological aluminum-based P-inactivation agent

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Journal of Environmental sciences 2025年第4期150卷 594-603页

作者： Changxiong Chen Fei Li Chunhua Shen Xueping Tang Mazhan Zhuang Zhenming Zhou Denghong Wang College of Civil Engineering Huaqiao UniversityXiamen 361021China Xiamen Institute of Environmental Science Xiamen 361021China College of Civil Engineering and Architecture Zhejiang Tongji Vocational College of Science and TechnologyHangzhou 311231China

Eutrophication is a significant challenge for surface water,with sediment phosphorus(P)release being a key *** biological aluminum-based P-inactivation agent(BA-PIA)has shown effectiveness in controlling P release from sediment,the efficiency and mechanism by BA-PIA capping is still not fully *** study explored the efficiency and mechanism of using BA-PIA capping controlling P release from *** main mechanisms controlling P release from sediment via BA-PIA capping involved transforming mobile and less stable fractions into stable ones,passivating DGT-labile P and establishing a 13 mm’P static layer’within the ***,BA-PIA’s impact on Fe redox processes significantly influenced P release from the *** BA-PIA capping,notable reductionswere observed in total P,soluble reactive P(SRP),and diffusive gradient in thin-films(DGT)-measured labile P(DGT-labile P)concentration in the overlying water,with reduction rates of 95.6%,92.7%,and 96.5%,*** BA-PIA capping,the diffusion flux of SRP across the sediment-water interface and the apparent P diffusion flux decreased by 91.3%and 97.8%,***,BA-PIA capping led to reduced concentrations of SRP,DGT-labile P,and DGT-measured labile Fe(II)in the sediment interstitial ***,BA-PIA capping significantly reduced P content and facilitated transformation in the 0∼30 mm sediment layers but not in the 30∼45 mm and 45∼60 mm sediment layers for NaOH-extractable inorganic P and HCl-extracted *** findings offer a theoretical basis and technical support for the practical application of BA-PIA capping to control P release from sediment.

关键词： Biological aluminum-based p-inactivation agent Active capping Sediment Phosphorus release

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Vector Dominance with Threshold Searchable Encryption (VDTSE) for the Internet of Things

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computers, Materials & Continua 2024年第6期79卷 4763-4779页

作者： Jingjing Nie Zhenhua Chen College of Safety Science and Engineering Xi’an University of Science and TechnologyXi’an710054China College of Computer Science and Technology Xi’an University of Science and TechnologyXi’an710054China

The Internet of Medical Things(IoMT)is an application of the Internet of Things(IoT)in the medical *** is a cutting-edge technique that connects medical sensors and their applications to healthcare systems,which is essential in smart ***,Personal Health Records(PHRs)are normally kept in public cloud servers controlled by IoMT service providers,so privacy and security incidents may be ***,Searchable Encryption(SE),which can be used to execute queries on encrypted data,can address the issue ***,most existing SE schemes cannot solve the vector dominance threshold *** response to this,we present a SE scheme called Vector Dominance with Threshold Searchable Encryption(VDTSE)in this *** use a Lagrangian polynomial technique and convert the vector dominance threshold problem into a constraint that the number of two equal-length vectors’corresponding bits excluding wildcards is not less than a threshold ***,we solve the problem using the proposed technique modified in Hidden Vector Encryption(HVE).This technique makes the trapdoor size linear to the number of attributes and thus much smaller than that of other similar SE schemes.A rigorous experimental analysis of a specific application for privacy-preserving diabetes demonstrates the feasibility of the proposed VDTSE scheme.

关键词： Internet of Things(IoT) Internet of Medical Things(IoMT) vector dominance with threshold searchable encryption(VDTSE) threshold comparison electronic healthcare

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A survey on cross-user federated recommendation

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science China(Information sciences) 2025年第4期68卷 7-32页

作者： Enyue YANG Yudi XIONG Wei YUAN Weike PAN Qiang YANG Zhong MING College of Computer Science and Software Engineering Shenzhen University School of Electrical Engineering and Computer Science The University of Queensland WeBank AI Lab WeBank Department of Computer Science and Engineering Hong Kong University of Science and Technology College of Big Data and Internet Shenzhen Technology University Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ)

Recommender systems are effective in mitigating information overload, yet the centralized storage of user data raises significant privacy concerns. Cross-user federated recommendation(CUFR) provides a promising distributed paradigm to address these concerns by enabling privacy-preserving recommendations directly on user devices. In this survey, we review and categorize current progress in CUFR, focusing on four key aspects: privacy, security, accuracy, and efficiency. Firstly,we conduct an in-depth privacy analysis, discuss various cases of privacy leakage, and then review recent methods for privacy protection. Secondly, we analyze security concerns and review recent methods for untargeted and targeted *** untargeted attack methods, we categorize them into data poisoning attack methods and parameter poisoning attack methods. For targeted attack methods, we categorize them into user-based methods and item-based methods. Thirdly,we provide an overview of the federated variants of some representative methods, and then review the recent methods for improving accuracy from two categories: data heterogeneity and high-order information. Fourthly, we review recent methods for improving training efficiency from two categories: client sampling and model compression. Finally, we conclude this survey and explore some potential future research topics in CUFR.

关键词： cross-user federated recommendation federated recommendation federated learning recommender systems user privacy

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A Federated Learning Incentive Mechanism for Dynamic Client Participation:Unbiased Deep Learning Models

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computers, Materials & Continua 2025年第4期83卷 619-634页

作者： Jianfeng Lu Tao Huang Yuanai Xie Shuqin Cao Bing Li School of Computer Science and Technology Wuhan University of Science and TechnologyWuhan430065China College of Computer Science South-Central Minzu UniversityWuhan430074China School of Computer Science and Technology Zhejiang Normal UniversityJinhua321004China

The proliferation of deep learning(DL)has amplified the demand for processing large and complex datasets for tasks such as modeling,classification,and ***,traditional DL methods compromise client privacy by collecting sensitive data,underscoring the necessity for privacy-preserving solutions like Federated Learning(FL).FL effectively addresses escalating privacy concerns by facilitating collaborative model training without necessitating the sharing of raw *** that FL clients autonomously manage training data,encouraging client engagement is pivotal for successful model *** overcome challenges like unreliable communication and budget constraints,we present ENTIRE,a contract-based dynamic participation incentive mechanism for *** ensures impartial model training by tailoring participation levels and payments to accommodate diverse client *** approach involves several key ***,we examine how random client participation impacts FL convergence in non-convex scenarios,establishing the correlation between client participation levels and model ***,we reframe model performance optimization as an optimal contract design challenge to guide the distribution of rewards among clients with varying participation *** balancing budget considerations with model effectiveness,we craft optimal contracts for different budgetary constraints,prompting clients to disclose their participation preferences and select suitable contracts for contributing to model ***,we conduct a comprehensive experimental evaluation of ENTIRE using three real *** results demonstrate a significant 12.9%enhancement in model performance,validating its adherence to anticipated economic properties.

关键词： Federated learning deep learning non-IID data dynamic client participation non-convex optimization contract

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A Survey of Reliability Issues Related to Approximate Circuits

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Journal of computer science & technology 2023年第2期38卷 273-288页

作者：王真徐荣臣陈嘉诚肖杰 College of Computer Science and Technology Shanghai University of Electric PowerShanghai 200090China College of Computer Science and Technology Zhejiang University of TechnologyHangzhou 310000China

As one of the most promising paradigms of integrated circuit design,the approximate circuit has aroused widespread concern in the scientific *** takes advantage of the inherent error tolerance of some applications and relaxes the accuracy for reductions in area and power *** paper aims to provide a comprehensive survey of reliability issues related to approximate circuits,which covers three concerns:error characteristic analysis,reliability and test,and reliable design involving approximate *** error characteristic analysis is used to compare the outputs of the approximate circuit with those of its precise counterpart,which can help to find the most appropriate approximate design for a specific application in the large design *** the approximate design getting close to physical realization,manufacturing defects and operational faults are inevitable;therefore,the reliability prediction and vulnerability test become increasingly ***,the research on approximate circuit reliability and test is insufficient and needs more ***,although there is some existing work combining the approximate design with fault tolerant techniques,the reliability-enhancement approaches for approximate circuits are lacking.

关键词： approximate circuit error metric fault tolerance test reliability

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