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A unified user behavior model for trajectory-based tasks with different types of path constraints

Science China(Information Sciences) 2023年第10期66卷 316-318页

作者： Hao ZHANG Jin HUANG Huawei TU Feng TIAN Guozhong DAI Hongan WANG Beijing Key Laboratory of Human-Computer Interaction Institute of Software Chinese Academy of Sciences School of Computer Science and Technology University of Chinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences Department of Computer Science and Information Technology La Trobe University

An important research branch of human-computer interaction(HCI) is to develop predictive models for human performance in fundamental interactions [1]. On today's graphical user interface(GUI), users often implicitly perform various trajectory-based interactions, such as navigating through menus [2], entering the boundary of a button,

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ForkXplorer:an approach of fork summary generation

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Frontiers of computer Science 2022年第2期16卷 1-15页

作者： Zhang ZHANG Xinjun MAO Chao ZHANG Yao LU Key Laboratory of Software Engineering for Complex Systems College of ComputerNational University of Defense TechnologyChangsha 410073China

Pull-based development has become an important paradigm for distributed software *** this model,each developer independently works on a copied repository(i.e.,a fork)from the central *** is essential for developers to maintain awareness of the state of other forks to improve collaboration *** this paper,we propose a method to automatically generate a summary of a *** first use the random forest method to generate the label of a fork,i.e.,feature implementation or a bug *** on the information of the fork-related commits,we then use the TextRank algorithm to generate detailed activity information of the ***,we apply a set of rules to integrate all related information to construct a complete fork *** validate the effectiveness of our method,we conduct 30 groups of manual experiment and 77 groups of case studies on *** propose Fea_(avg)to evaluate the performance of Fea_(avg)the generated fork summary,considering the content accuracy,content integrity,sentence fluency,and label extraction *** results show that the average of of the fork summary generated by this method is *** than 63%of project maintainers and the contributors believe that the fork summary can improve development efficiency.

关键词： open source software pull-based development fork summary distributed cooperative development

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Introduction to the Special Issue on Formal Methods and Models for System Design

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ACM Transactions on Embedded Computing Systems 2025年第3期24卷 1-3页

作者： Brandt, Jens Saha, Indranil Zhang, Lijun Hochschule Niederrhein Krefeld Germany Department of Computer Science and Engineering Indian Institute of Technology Kanpur Kanpur India State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China

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Achieving dynamic privacy measurement and protection based on reinforcement learning for mobile edge crowdsensing of IoT

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Digital Communications and Networks 2024年第2期10卷 380-388页

作者： Renwan Bi Mingfeng Zhao Zuobin Ying Youliang Tian Jinbo Xiong Fujian Provincial Key Laboratory of Network Security and Cryptology College of Computer and Cyber SecurityFujian Normal UniversityFuzhou350117China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic TechnologyGuilin541004China Faculty of Data Science City University of Macao999078MacaoChina State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang550025China

With the maturity and development of 5G field,Mobile Edge CrowdSensing(MECS),as an intelligent data collection paradigm,provides a broad prospect for various applications in ***,sensing users as data uploaders lack a balance between data benefits and privacy threats,leading to conservative data uploads and low revenue or excessive uploads and privacy *** solve this problem,a Dynamic Privacy Measurement and Protection(DPMP)framework is proposed based on differential privacy and reinforcement ***,a DPM model is designed to quantify the amount of data privacy,and a calculation method for personalized privacy threshold of different users is also ***,a Dynamic Private sensing data Selection(DPS)algorithm is proposed to help sensing users maximize data benefits within their privacy ***,theoretical analysis and ample experiment results show that DPMP framework is effective and efficient to achieve a balance between data benefits and sensing user privacy protection,in particular,the proposed DPMP framework has 63%and 23%higher training efficiency and data benefits,respectively,compared to the Monte Carlo algorithm.

关键词： Mobile edge crowdsensing Dynamic privacy measurement Personalized privacy threshold Privacy protection Reinforcement learning

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Ordered Momentum for Asynchronous SGD 38

Ordered Momentum for Asynchronous SGD

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Shi, Chang-Wei Yang, Yi-Rui Li, Wu-Jun National Key Laboratory for Novel Software Technology School of Computer Science Nanjing University Nanjing China

Distributed learning is essential for training large-scale deep models. Asynchronous SGD (ASGD) and its variants are commonly used distributed learning methods, particularly in scenarios where the computing capabilities of workers in the cluster are heterogeneous. Momentum has been acknowledged for its benefits in both optimization and generalization in deep model training. However, existing works have found that naively incorporating momentum into ASGD can impede the convergence. In this paper, we propose a novel method called ordered momentum (OrMo) for ASGD. In OrMo, momentum is incorporated into ASGD by organizing the gradients in order based on their iteration indexes. We theoretically prove the convergence of OrMo with both constant and delay-adaptive learning rates for non-convex problems. To the best of our knowledge, this is the first work to establish the convergence analysis of ASGD with momentum without dependence on the maximum delay. Empirical results demonstrate that OrMo can achieve better convergence performance compared with ASGD and other asynchronous methods with momentum. © 2024 Neural information processing systems foundation. All rights reserved.

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An energy constraint position-based dynamics with corrected SPH kernel

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Science China(Information Sciences) 2023年第1期66卷 144-157页

作者： Wei CAO Luan LYU Zhixin YANG Enhua WU College of Computer Science and Technology China University of Petroleum Faculty of Science and Technology University of Macau State Key Laboratory of Internet of Things for Smart City University of Macau State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Guangzhou Greater Bay Area Virtual Reality Research Institute

We introduce an improved position-based dynamics method with corrected smoothed particle hydrodynamics(SPH) kernel to simulate deformable solids. Using a strain energy constraint that follows the continuum mechanics, the method can maintain the efficiency and stability of the position-based approach while improving the physical plausibility of the simulation. We can easily simulate the behavior of anisotropic and plastic materials because the method is based on physics. Unlike the previous position-based simulations of continuous materials, we use weakly structured particles to discretize the model for the convenience of deformable object cutting. In this case, a corrected SPH kernel function is adopted to measure the deformation gradient and calculate the strain energy on each particle. We also propose a solution for the interparticle inversion and penetration in large deformation. To perform complex interaction scenarios, we provide a simple method for collision detection. We demonstrate the flexibility, efficiency, and robustness of the proposed method by simulating various scenes, including anisotropic elastic deformation, plastic deformation, model cutting, and large-scale elastic collision.

关键词： position-based dynamics deformable solids continuum mechanics

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Indexing dynamic encrypted database in cloud for efficient secure k-nearest neighbor query

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Frontiers of computer Science 2024年第1期18卷 187-198页

作者： Xingxin LI Youwen ZHU Rui XU Jian WANG Yushu ZHANG College of Computer Science and Technology Nanjing University of Aeronautics and AstronauticsNanjing 210016China Department of Mathematical Informatics University of TokyoTokyo 113-8654Japan Guangxi Key Laboratory of Trusted Software Guilin University of Electronic TechnologyGuilin 541004China School of Computer Science China University of GeosciencesWuhan 430074China

Secure k-Nearest Neighbor(k-NN)query aims to find k nearest data of a given query from an encrypted database in a cloud server without revealing privacy to the untrusted cloud and has wide applications in many areas,such as privacy-preservingmachine elearning gand secure biometric *** solutions have been put forward to solve this challenging ***,the existing schemes still suffer from various limitations in terms of efficiency and *** this paper,we propose a new encrypt-then-index strategy for the secure k-NN query,which can simultaneously achieve sub-linear search complexity(efficiency)and support dynamical update over the encrypted database(flexibility).Specifically,we propose a novel algorithm to transform the encrypted database and encrypted query points in the *** indexing the transformed database using spatial data structures such as the R-tree index,our strategy enables sub-linear complexity for secure k-NN queries and allows users to dynamically update the encrypted *** the best of our knowledge,the proposed strategy is the first to simultaneously provide these two *** theoretical analysis and extensive experiments,we formally prove the security and demonstrate the efficiency of our scheme.

关键词： cloud computing secure k-NN query sub-linear complexity dynamicupdate

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An Approach to Optimize Symbolic Execution in Ethereum Smart Contracts 24

An Approach to Optimize Symbolic Execution in Ethereum Smart...

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24th IEEE International Conference on software Quality, Reliability and Security Companion, QRS-C 2024

作者： Liu, Yi Cai, Lizhi Chai, Chenchen Ma, Yuan School of Information Science and Engineering East China University of Science and Technology Shanghai China Shanghai Development Center of Computer Software Technology Shanghai Key Laboratory of Computer Software Testing & Evaluating Shanghai China

ISBN: (纸本)9798350365658

As the application of smart contracts in blockchain technology becomes increasingly widespread, their security issues have emerged as a focal point of both research and practice. Although symbolic execution technology has been extensively applied for the detection of security vulnerabilities in smart contracts, its limitations in terms of execution efficiency and code coverage remain significant. In response to these challenges, this study introduces an innovative method named HoneyToken-DetectorRev, which optimizes traditional symbolic execution through program slicing technology, aiming to enhance the efficiency and effectiveness of smart contract security detection. By selecting ten smart contracts from the Ethereum platform, which vary in business logic and complexity, we conducted an empirical analysis of HoneyToken-DetectorRev. The experimental results demonstrate that this method significantly improves the efficiency of smart contract detection without sacrificing precision. This research not only provides an effective technical approach for the security detection of smart contracts but also offers theoretical and practical guidance for further enhancing the security of blockchain applications. © 2024 IEEE.

关键词： Smart contract

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MSEs Credit Risk Assessment Model Based on Federated Learning and Feature Selection

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computers, Materials & Continua 2023年第6期75卷 5573-5595页

作者： Zhanyang Xu Jianchun Cheng Luofei Cheng Xiaolong Xu Muhammad Bilal School of Computer and Software Nanjing University of Information Science&TechnologyNanjing210044China State Key Laboratory Novel Software Technology Nanjing UniversityNanjing210023China Department of Computer and Electronics Systems Engineering Hankuk University of Foreign StudiesYongin-siGyeonggi-do17035Korea

Federated learning has been used extensively in business inno-vation scenarios in various *** research adopts the federated learning approach for the first time to address the issue of bank-enterprise information asymmetry in the credit assessment ***,this research designs a credit risk assessment model based on federated learning and feature selection for micro and small enterprises(MSEs)using multi-dimensional enterprise data and multi-perspective enterprise *** proposed model includes four main processes:namely encrypted entity alignment,hybrid feature selection,secure multi-party computation,and global model ***,a two-step feature selection algorithm based on wrapper and filter is designed to construct the optimal feature set in multi-source heterogeneous data,which can provide excellent accuracy and *** addition,a local update screening strategy is proposed to select trustworthy model parameters for aggregation each time to ensure the quality of the global *** results of the study show that the model error rate is reduced by 6.22%and the recall rate is improved by 11.03%compared to the algorithms commonly used in credit risk research,significantly improving the ability to identify ***,the business operations of commercial banks are used to confirm the potential of the proposed model for real-world implementation.

关键词： Federated learning feature selection credit risk assessment MSEs

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Iterative Android automated testing

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Frontiers of computer Science 2023年第5期17卷 15-26页

作者： Yi ZHONG Mengyu SHI Youran XU Chunrong FANG Zhenyu CHEN State Key Laboratory for Novel Software Technology Nanjing UniversityNanjing 210093China School of Big Data and Computer Science Chongqing College of Mobile CommunicationChongqing 400065China

With the benefits of reducing time and workforce,automated testing has been widely used for the quality assurance of mobile applications(APPs).Compared with automated testing,manual testing can achieve higher coverage in complex interactive *** the effectiveness of manual testing is highly dependent on the user operation process(UOP)of experienced *** on the UOP,we propose an iterative Android automated testing(IAAT)method that automatically records,extracts,and integrates UOPs to guide the test logic of the tool across the complex Activity *** feedback test results can train the UOPs to achieve higher coverage in each *** extracted 50 UOPs and conducted experiments on 10 popular mobile APPs to demonstrate IAAT’s effectiveness compared with Monkey and the initial automated *** experimental results show a noticeable improvement in the IAAT compared with the test logic without human *** the 60 minutes test time,the average code coverage is improved by 13.98%to 37.83%,higher than the 27.48%of Monkey under the same conditions.

关键词： quality assurance automated testing UOP test coverage

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