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Labeling-based centrality approaches for identifying critical edges on temporal graphs

Frontiers of computer science 2025年第2期19卷 89-104页

作者： Tianming ZHANG Jie ZHAO Cibo YU Lu CHEN Yunjun GAO Bin CAO Jing FAN Ge YU School of Computer Science and Technology Zhejiang University of TechnologyHangzhou 310023China School of Computer Science and Technology Zhejiang UniversityHangzhou 310013China Department of Computer Science Northeastern UniversityShenyang 110819China

Edge closeness and betweenness centralities are widely used path-based metrics for characterizing the importance of edges in *** general graphs,edge closeness centrality indicates the importance of edges by the shortest distances from the edge to all the other *** betweenness centrality ranks which edges are significant based on the fraction of all-pairs shortest paths that pass through the ***,extensive research efforts go into centrality computation over general graphs that omit time ***,numerous real-world networks are modeled as temporal graphs,where the nodes are related to each other at different time *** temporal property is important and should not be neglected because it guides the flow of information in the *** state of affairs motivates the paper’s study of edge centrality computation methods on temporal *** introduce the concepts of the label,and label dominance relation,and then propose multi-thread parallel labeling-based methods on OpenMP to efficiently compute edge closeness and betweenness centralities *** types of optimal temporal *** edge closeness centrality computation,a time segmentation strategy and two observations are presented to aggregate some related temporal edges for uniform *** edge betweenness centrality computation,to improve efficiency,temporal edge dependency formulas,a labeling-based forward-backward scanning strategy,and a compression-based optimization method are further proposed to iteratively accumulate centrality *** experiments using 13 real temporal graphs are conducted to provide detailed insights into the efficiency and effectiveness of the proposed *** with state-ofthe-art methods,labeling-based methods are capable of up to two orders of magnitude speedup.

关键词： temporal graph closeness centrality between-ness centrality temporal path

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MulDeF: A Model-Agnostic Debiasing Framework for Robust Multimodal Sentiment Analysis

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IEEE Transactions on Multimedia 2025年 27卷 2304-2319页

作者： Huan, Ruohong Zhong, Guowei Chen, Peng Liang, Ronghua Zhejiang University of Technology College of Computer Science and Technology Hangzhou310023 China

In recent years, multimodal sentiment analysis (MSA) has gained prominence with the proliferation of social media. However, prior studies have often disregarded the possibility of spurious correlations between multimodal data and sentiment labels. Neglecting these factors often results in significant performance degradation, hampering the model's ability to generalize in out-of-distribution (OOD) scenarios. To gain a comprehensive understanding of multimodal knowledge and enhance the model's generalization across diverse distribution scenarios, we present the Multimodal Debiasing Framework (MulDeF). This model-agnostic framework addresses label bias through causal intervention and tackles multimodal biases using counterfactual reasoning. During the training phase, MulDeF rectifies multimodal representations through frontdoor adjustment in causal intervention, effectively eliminating label bias. In order to model conditional expectation calculations within the context of frontdoor adjustment, we introduce multimodal causal attention (MCA). In the inference phase, it employs counterfactual reasoning to eliminate multimodal biases. To further refine our debiasing strategy, we categorize multimodal biases into two distinct types: nonverbal bias and verbal bias. Nonverbal bias is addressed at the utterance level, involving the establishment of unimodal models for audio and visual modalities to estimate their biases concerning sentiment labels. Conversely, verbal bias mitigation occurs at the word level. Here, we mask "harmless" words to generate corresponding counterfactual texts, which are then assessed by the text model to identify word-level bias. Experimental results validate the effectiveness of MulDeF, showcasing its superior performance in OOD settings compared to state-of-the-art methods, while also achieving competitive results in independent and identically distributed (IID) settings. © 1999-2012 IEEE.

关键词： Economic and social effects

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Supervised Enhancement for Fingertip OCT Images Based on Paired Dataset Generation Strategy

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IEEE Transactions on Information Forensics and Security 2025年 20卷 5039-5053页

作者： Miao, Qingran Wang, Haixia Zhou, Jianru Zhang, Yilong Chen, Peng Liang, Ronghua Feng, Yuanjing Zhejiang University of technology College of Information Engineering Hangzhou China Zhejiang University of technology College of Computer Science and Technology Hangzhou China

Optical Coherence Tomography (OCT) is a high-resolution, non-invasive imaging technology increasingly used for biometric data collection from fingertips. OCT captures volume data up to 3mm below the skin surface in the form of a series of B-scan images, enabling the reconstruction of internal fingerprints (IF) and internal sweat pores (ISP), thereby enhancing the security of biometric recognition. Despite the advantages, OCT images suffer from speckle noise and tissue discontinuity, making the extraction of subcutaneous biometric features challenging. Traditional hardware and software-based enhancement methods often result in over-smoothing and structural loss. Recent advancements in deep learning (DL) offer promising alternatives, with supervised DL methods showing efficacy when trained with high-quality paired datasets. However, the absence of ground-truth (GT) data makes it impossible to apply these models. This study proposes a novel supervised enhancement method for fingertip OCT images, with a paired dataset generation strategy. An OCT few-shot GAN and a Quality Estimation Module are proposed and incorporated into the strategy to realize translation from minimal GT manual augmentation to high-quality paired dataset, effectively addressing the challenge of data scarcity. A Fast Supervised Enhancement GAN (FSE-GAN) is proposed thereafter to perform simultaneous speckle noise reduction and tissue structure restoration, facilitating accurate extraction of internal fingerprints and sweat pores. Experiments demonstrate that the enhanced images significantly simplify IF and ISP extraction while achieving outstanding result quality. © 2005-2012 IEEE.

关键词： Image enhancement

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Chasing in virtual environment:Dynamic alignment for multi-user collaborative redirected walking

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虚拟现实与智能硬件(中英文) 2025年第1期7卷 26-46页

作者： Tianyang DONG Shuqian LV Hubin KONG Huanbo ZHANG College of Computer Science and Technology Zhejiang University of TechnologyHangzhou 310004China

Background The redirected walking(RDW)method for multi-user collaboration requires maintaining the relative position between users in a virtual environment(VE)and physical environment(PE).A chasing game in a VE is a typical virtual reality game that entails multi-user *** a user approaches and interacts with a target user in the VE,the user is expected to approach and interact with the target user in the corresponding PE as *** methods of multi-user RDW mainly focus on obstacle avoidance,which does not account for the relative positional relationship between the users in both VE and *** To enhance the user experience and facilitate potential interaction,this paper presents a novel dynamic alignment algorithm for multi-user collaborative redirected walking(DA-RDW)in a shared PE where the target user and other users are *** algorithm adopts improved artificial potential fields,where the repulsive force is a function of the relative position and velocity of the user with respect to dynamic *** the best alignment,this algorithm sets the alignment-guidance force in several cases and then converts it into a constrained optimization problem to obtain the optimal ***,this algorithm introduces a potential interaction object selection strategy for a dynamically uncertain environment to speed up the subsequent *** balance obstacle avoidance and alignment,this algorithm uses the dynamic weightings of the virtual and physical distances between users and the target to determine the resultant force *** The efficacy of the proposed method was evaluated using a series of simulations and live-user *** experimental results demonstrate that our novel dynamic alignment method for multi-user collaborative redirected walking can reduce the distance error in both VE and PE to improve alignment with fewer collisions.

关键词： Virtual reality Multi-user redirected walking User collisions Dynamic alignment

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NeOR: neural exploration with feature-based visual odometry and tracking-failure-reduction policy

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Optoelectronics Letters 2025年第5期21卷 290-297页

作者： ZHU Ziheng LIU Jialing CHEN Kaiqi TONG Qiyi LIU Ruyu College of Computer Science and Technology College of Software Zhejiang University of Technology School of Information Science and Technology Hangzhou Normal University

Embodied visual exploration is critical for building intelligent visual agents. This paper presents the neural exploration with feature-based visual odometry and tracking-failure-reduction policy(Ne OR), a framework for embodied visual exploration that possesses the efficient exploration capabilities of deep reinforcement learning(DRL)-based exploration policies and leverages feature-based visual odometry(VO) for more accurate mapping and positioning results. An improved local policy is also proposed to reduce tracking failures of feature-based VO in weakly textured scenes through a refined multi-discrete action space, keyframe fusion, and an auxiliary task. The experimental results demonstrate that Ne OR has better mapping and positioning accuracy compared to other entirely learning-based exploration frameworks and improves the robustness of feature-based VO by significantly reducing tracking failures in weakly textured scenes.

关键词： A

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Improving Multitasking DBMS Fuzzing With More Accurate Coverage and Testcase Trimming

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IEEE Transactions on Dependable and Secure Computing 2025年第3期22卷 2756-2770页

作者： Li, Jiaqi Zhou, Yajin Wu, Lei Zhejiang University College of Computer Science and Technology Hangzhou310027 China

Coverage-guided fuzzing is prevalent in detecting DBMS (Database Management System) bugs. However, current coverage-guided DBMS fuzzers suffer from two limitations that prevent fuzzers from discovering bugs efficiently. First, the coverage feedback is imprecise which prevents fuzzers from making optimal decisions on fuzzing strategies. Second, DBMS fuzzers lack testcase trimming to control the increasing input sizes. The large input size makes DBMS execution slower and reduces the likelihood that a mutation would touch important structures. In this paper, we proposed corresponding methods to overcome these limitations. Specifically, the work-task coverage tracking and unstable edge filtering improve the coverage accuracy with low instrumentation overhead. Based on more accurate coverage, we further propose testcase trimming to improve the speed of bug detection. We implemented a prototype named Tuzz and evaluated it on three popular DBMSs. The evaluation result shows that Tuzz explores 16.3%, 26.1%, and 26.6% more edges than the state-of-the-art fuzzer in PostgreSQL, MySQL, and MariaDB, respectively. More importantly, Tuzz has discovered 10 and 4 previously unknown bugs in MySQL and MariaDB. © 2004-2012 IEEE.

关键词： Trimming

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PerFedKG: two-stage information-loop federated knowledge graph for personalized privacy-preserving recommendation systems

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science China(Information sciences) 2025年第4期68卷 98-99页

作者： Fan WANG Xuyun ZHANG Weiming LIU Li LI Yuwen LIU Zhongyuan ZHANG Guanfeng LIU Shengye PANG Xiaolong XU Lianyong QI College of Computer Science and Technology Zhejiang University Department of Computing Macquarie University College of Computer Science and Technology China University of Petroleum (East China) School of Software Nanjing University of Information Science and Technology

Knowledge graphs(KGs) effectively mitigate data sparsity in recommendation systems(RSs) by providing valuable auxiliary information [1]. However, traditional centralized KG-based RSs increase the risk of user privacy *** learning(FL) enhances RS's privacy by enabling model training on decentralized data [2]. Although integrating KG and FL can address both data sparsity and privacy issues in RSs [3], several challenges persist. CH1,Each client's local model relies on a consistent global model from the server, limiting personalized deployment to endusers.

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Hydrogen-bond enhanced urea-glycerol eutectic electrolyte to boost low-cost and long-lifespan aqueous sodium-ion batteries

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Journal of Energy Chemistry 2025年第5期104卷 462-471页

作者： Menglu Lu Tianqi Yang Wenkui Zhang Yang Xia Xinping He Xinhui Xia Yongping Gan Hui Huang Jun Zhang College of Materials Science and Engineering Zhejiang University of TechnologyHangzhou 310014ZhejiangChina

Aqueous sodium-ion batteries(ASIBs)have garnered significant attention as promising candidates for large-scale energy storage *** interest is primarily due to their abundant resource availability,environmental friendliness,cost-effectiveness,and high ***,their electrochemical performance is limited by the thermodynamic properties of water molecules,resulting in inadequate cycling stability and insufficient specific energy *** address these challenges,this study developed a hydrogen-bond enhanced urea-glycerol eutectic electrolyte(UGE)to expand the electrochemical stability window(ESW)of the electrolyte and suppress corresponding side *** eutectic component disrupts the original hydrogen bonding network in water,creating a new,enhanced network that reduces the activity of free water and forms a uniform,dense passivation layer on the *** a result,the optimized composition of UGE exhibits a broad ESW of up to 3 V(-1.44 to 1.6 V ***/AgCl).The Prussian blue(PB)/UGE/NaTi_(2)(PO_(4))_(3)@C full cell exhibits an exceptionally long lifespan of 10,000 cycles at 10 *** study introduces a low-cost,ultra-long-life ASIB system,utilizing a green and economical eutectic electrolyte,which expands the use of eutectic electrolytes in aqueous batteries and opens a new research horizon for constructing efficient electrochemical energy storage and conversion.

关键词： Hydrogen-bond Urea Glycerol Eutectic electrolyte Aqueous sodium-ion battery

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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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StepIdeator: Utilizing Mixed Representations to Support Step-By-Step Design With Generative Artificial Intelligence

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Journal of Mechanical Design 2025年第7期147卷 071703页

作者： Yao, Jiayi Chen, Pei Li, Zhuoshu Cai, Yichen Wu, Yexinrui You, Weitao Sun, Lingyun School of Software Technology Zhejiang University Ningbo315048 China College of Computer Science and Technology Zhejiang University Hangzhou310027 China

In the product conceptual design, designers utilize multiple design representations to ideate, externalize, and refine concepts iteratively. Mixed representations, defined as the simultaneous presentation of multiple representations, foster deeper insights and facilitate broader exploration compared to focusing on a single representation. However, designers often struggle with the cumbersome process of creating, transforming, and refining these representations. Advanced artificial intelligence (AI) capabilities now significantly lower the barriers to creating text, images, and 3D models, presenting substantial potential for application in design practice. However, the current design tools based on generative AI tend to produce polished product images directly, hindering designers from continuously deliberating on mixed representations and thus limiting their creative potential. Therefore, on the basis of a formative study, we propose StepIdeator, a step-by-step design tool driven by generative AI. This tool facilitates seamless transition and refinement of mixed-design representations. Through a comparative study (N = 16), we validated StepIdeator's effectiveness in improving idea externalization and enhancing creativity. Furthermore, the results revealed that designers perceived greater confidence, ownership, and sense of contribution when collaborating with StepIdeator. © 2025 by ASME.

关键词： Product design

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