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35th IEEE International Symposium on Software Reliability engineering, ISSRE 2024

作者： Chen, Ziming Li, Yue Gao, Jianbo Zhang, Jiashuo Wang, Ke Hu, Jianbin Guan, Zhi Chen, Zhong Peking University School of Computer Science Beijing China Taiyuan University of Technology College of Computer Science and Technology Taiyuan China Beijing Jiaotong University Beijing Key Laboratory of Security and Privacy in Intelligent Transportation Beijing China Peking University Chongqing Research Institute of Big Data Chongqing China Peking University National Engineering Research Center for Software Engineering Beijing China

ISBN: (纸本)9798350353884

The application on a blockchain cannot maintain secrecy because its data is replicated across all peers in the network. To remedy this problem, Hyperledger Fabric introduces private data collection (PDC) into its smart contract (i.e. chaincode) to facilitate applications that require privacy. However, recent studies have revealed that PDC is too complex for chaincode developers to fully understand and use correctly, leading to privacy leaks vulnerabilities. In this paper, we present an empirical study on the prevalence of PDC misuse in chaincodes by extracting privacy leakage cases from StackOverflow posts and Hyperledger Fabric repositories on GitHub. Subsequently, we systematically categorize the misuse of PDC into three categories of vulnerabilities resulting in the leakage of private data and provide formal definitions for them. Furthermore, we develop PDChecker, an automated security analysis framework for identifying the privacy and security vulnerabilities in Fabric chaincodes. We evaluated PDChecker on 956 real-world chaincodes applying PDC and found that 67.78% of them contain at least one privacy leakage vulnerability. In addition, PDChecker uncovered 10 zero-day vulnerabilities documented by the China National Vulnerability database. © 2024 IEEE.

关键词： Differential privacy

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Multivariate data Fusion Method Based on 3DGIS and its Application in engineering Management 21

Multivariate Data Fusion Method Based on 3DGIS and its Appli...

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5th International Conference on Electronic Information technology and Computer engineering, EITCE 2021

作者： Liu, Chengkun Ma, Rui Hu, Binbin Fan, Qingsong Changjiang Survey Planning Design and Research Co. Ltd Wuhan China Changjiang Spatial Information Technology Engineering Co. Ltd Wuhan China Water Resources Information Perception and Big Data Engineering Research Center of Hubei Province Wuhan China

ISBN: (纸本)9781450384322

In the life-cycle engineering management of a project, a large amount of diversified and heterogeneous data is involved. How to efficiently manage and visualize various data sources is the basis for realizing the refined management of project construction. Based on the concept of data fusion, this article sorts out the multiple data involved in project engineering management, analyses the data fusion method and process of multivariate structured data and geospatial data. By combining 3DGIS in data integration, management and visualization, data fusion and expression in a three-dimensional environment can be realized. Taking the engineering management system of the bank slope of Song Gang Area as an example, it verifies the validity of the multivariate data fusion method based on 3DGIS in this paper. © 2021 ACM.

关键词： Visualization

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Environmental Drivers and spatial Prediction of the Critically Endangered Species Thuja sutchuenensis in Sichuan-chongqing,China

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Phyton-International Journal of Experimental Botany 2022年第9期91卷 2069-2086页

作者： Liang Xie Peihao Peng Haijun Wang Shengbin Chen College of Earth Science Chengdu University of TechnologyChengdu610059China School of Geoscience and Technology Southwest Petroleum UniversityChengdu610500China Engineering and Technical College Chengdu University of TechnologyLeshan614000China College of Ecology and Environment Chengdu University of TechnologyChengdu610041China Spatial Information Technology and Big Data Mining Research Center Southwest Petroleum UniversityChengdu610500China

Identifying the ecological environment suitable for the growth of Thuja sutchuenensis and predicting other potential distribution areas are essential to protect this endangered species. After selecting 24 environmental factors thatcould affect the distribution of T. sutchuenensis, including climate, topography, soil and Normalized DifferenceVegetation Index (NDVI), we adopted the Random Forest-MaxEnt integrated model to analyze our data. Basedon the Random Forest study, the contribution of the mean temperature of the warmest quarter, mean temperatureof the coldest quarter, annual mean temperature and mean temperature of the driest quarter was large. Based onMaxEnt model prediction outputs, the potential distribution map not only identified areas that originallyrecorded T. sutchuenensis, such as Xuanhan County, Kai County and Chengkou County, but also identified highlysuitable distribution areas where T. sutchuenensis may exist, including Wanyuan County, Sichuan Province, andthe junction of chongqing and Hubei Province. This provides a more explicit geographic range for ex situ conservation and reintroduction of T. sutchuenensis. Our results also indicate that, in addition to climate factors,topography and soil factors are also important environmental factors that affect distribution. This provides a theoretical basis for subsequent laboratory construction to simulate the indoor growth of T. sutchuenensis.

关键词： Thuja sutchuenensis environmental drivers spatial prediction conservation Random Forest-MaxEnt model

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Analysis of spatial indexing mechanism and its application in data management: A case study on spatialite database 7

Analysis of spatial indexing mechanism and its application i...

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7th Annual International Conference on Geo-spatial Knowledge and Intelligence, GSKI 2019

作者： Liu, Chengkun Ma, Rui Zhang, Li Changjiang Survey Planning Design and Research Co. Ltd Wuhan China Changjiang Spatial Information Technology Engineering Co.Ltd Wuhan China Water Resources Information Perception and Big Data Engineering Research Center of Hubei Province Wuhan China

Lightweight spatial database spatialite is playing an increasing role in the current geographic information applications and other fields. This paper discusses the data organization and spatial indexing mechanism of spatialite database in detail, studies the use of spatialite database for data organization and index establishment, and utilizes the retrieval and spatial analysis methods supported by spatial index. The experiment takes urban pipeline data management as an example, through the visual application of urban pipeline data management in the 3DGIS environment, it provides a good solution for data management application of lightweight spatial database. © Published under licence by IOP Publishing Ltd.

关键词： Information management

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research on Conversion and Integration Framework from BIM data to 3DGIS Scene

Research on Conversion and Integration Framework from BIM Da...

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2020 International Conference on Industrial Applications of big data and Artificial Intelligence, BDAI 2020

作者： Liu, Chengkun Zhang, Li Ma, Rui Zhang, Xiong Qiu, Xin Changjiang Survey Planning Design and Research Co. Ltd Wuhan China Changjiang Spatial Information Technology Engineering Co. Ltd Wuhan China Water Resources Information Perception and Big Data Engineering Research Center of Hubei Province Wuhan China

There are large differences between BIM and 3DGIS in model scale, data standards, information expression, etc., which brings great challenges to the conversion and integration between them. Through in-depth analysis of the current status, problems and difficulties about the integration of BIM models in 3DGIS scenes, aiming to the optimization of graphic information conversion, extraction and integration of attribute information, model light-weighting, shared scheduling, and integrated management of the entire life cycle, combined with IFC and CityGML, a framework for the transformation and integration of BIM models to 3DGIS scenes is proposed. Taking the management information system of the Changjiang Water Resources Committee as an example, after forming a preliminary three-dimensional terrain scene and building appearance model, the process of transforming and integrating a BIM building model into 3DGIS scene is discussed. The results show that the framework can effectively guide the entire process of conversion, publication, integration and application of BIM models in 3DGIS scene, and proves good practicability and operability. © Published under licence by IOP Publishing Ltd.

关键词： Scheduling

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Advancing biological fluorescence microscopy with deep learning:a bibliometric perspective

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Medical data Mining 2022年第4期5卷 42-55页

作者： Li Fu Cheng-Liang Yin Jia-Lei Wang Xiao-Zhu Liu College of Materials and Environmental Engineering Hangzhou Dianzi UniversityHangzhou 310018China Medical Big Data Research Center Medical Innovation Research Division of PLA General HospitalBeijing 100853China National Engineering Laboratory for Medical Big Data Application Technology Chinese PLA General HospitalBeijing 100853China Department of Algorithm Shining3D Technology Company LimitidHangzhou 311258China Department of Cardiology The Second Affiliated Hospital of Chongqing Medical UniversityChongqing 400010China

Background:Fluorescence microscopy has increasingly promising applications in life *** bibliometrics-based review focuses on deep learning assisted fluorescence microscopy imaging ***:Papers on this topic retrieved by Core Collection on Web of Science between 2017 and July 2022 were used for the *** addition to presenting the representative papers that have received the most attention,the process of development of the topic,the structure of authors and institutions,the selection of journals,and the keywords are analyzed in detail in this ***:The analysis found that this topic gained immediate popularity among scholars from its emergence in 2017,gaining explosive growth within three *** phenomenon is because deep learning techniques that have been well established in other fields can be migrated to the analysis of fluorescence *** 2020 onwards,this topic tapers off but has attracted a few stable research groups to tackle the remaining *** this topic has been very popular,it has not attracted scientists from all over the *** USA,China,Germany,and the UK are the key players in this *** analysis and clustering are applied to understand the different focuses on this ***:Based on the bibliometric analysis,the current state of this topic to date and future perspectives are summarized at the end.

关键词： deep learning fluorescence microscopy signal-to-noise ratio convolutional neural network cell segmentation

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A Predictive-Trend-Aware and Critical-Path-Estimation-Based Method for Workflow Scheduling Upon Cloud Services

A Predictive-Trend-Aware and Critical-Path-Estimation-Based ...

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IEEE International Conference on Services Computing (SCC)

作者： Yi Pan Xiaoning Sun Yunni Xia Wanbo Zheng Xin Luo College of Computer Science Chongqing University Chongqing China Data Science Research Center Faculty of Science Kunming University of Science and Technology Kunming China Chongqing Engineering Research Center of Big Data Application for Smart Cities Chongqing Key Laboratory of Big Data and Intelligent Computing Chongqing Institute of Green and Intelligent Technology Chinese Academy of Sciences Chongqing China Hengrui (Chongqing) Artificial Intelligence Research Center Cloudwalk China

ISBN: (数字)9781728187891

ISBN: (纸本)9781728187907

The cloud computing paradigm is featured by its ability to offer elastic computational resource provisioning patterns and deliver on-demand and versatile services. It's thus getting increasingly popular to build business process and workflow-based applications upon cloud computing platforms. However, it remains a difficulty to guarantee cost-effectiveness and quality of service of cloud-based workflows because real-world cloud services are usually subject to real-time performance variations or fluctuations. Existing researches mainly consider that cloud are with constant performance and formulate the scheduling decision-making as a static optimization problem. In this work, instead, we consider that scientific computing processes to be supported by decentralized cloud infrastructures are with fluctuating QoS and aim at managing the monetary cost of workflows with the completion-time constraint to be satisfied. We address the performance-trend-aware workflow scheduling problem by leveraging a time-series-based prediction model and a Critical-Path-Duration-Estimation-based (CPDE for short) scheduling strategy. The proposed method is capable of exploiting real-time trends of performance changes of cloud infrastructures and generating dynamic workflow scheduling plans. To prove the effectiveness of our proposed method, we build a large-prime-number-generation workflow supported by real-world third-party commercial clouds and show that our method clearly beats existing approaches in terms of cost, workflow completion time, and Service-Level-Agreement (SLA) violation rate.

关键词： Cloud computing Processor scheduling Computational modeling Quality of service Predictive models Dynamic scheduling Real-time systems

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Convergence Analysis of a Fast Non-negative Latent Factor Model

Convergence Analysis of a Fast Non-negative Latent Factor Mo...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Yue Zhou Zhigang Liu Xiaojiang Yu Yajuan Wu Chongqing Engineering Research Center of Big Data Application for Smart Cities and Chongqing Key Laboratory of Big Data and Intelligent Computing Chongqing Institute of Green and Intelligent Technology Chinese Academy of Sciences Chongqing China Computer School of China West Normal University Nanchong Sichuan China

A fast non-negative latent factor (FNLF) model adopts a single latent factor-dependent, non-negative, multiplicative and momentum-incorporated update (SLF-NM 2 U) algorithm, which can ensure fast convergence on a high-dimensional and sparse (HiDS) matrix according to empirical studies in prior researches. However, it is crucial to investigate the theoretical proof regarding the reason why incorporation of a generalized momentum method into an SLF-NM 2 U algorithm can ensure the fast convergence of an FNLF model, which has not been addressed in previous work. Therefore, this paper aims to unveil how a generalized momentum method improves the convergence rate of an FNLF model in the discrete time case by combining physical analysis. The FNLF model is superior to the NLF model in terms of the convergence rate and the prediction accuracy of missing data. This conclusion is obtained by empirically research on the HiDS matrix in industrial applications, which also provides empirical basis for theoretical proof.

关键词： Convergence Analytical models Sparse matrices data models Computational modeling Acceleration Friction

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Lightweight Human Pose Estimation Based on Multi-Attention Mechanism

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Journal of Shanghai Jiaotong University (Science) 2024年 1-12页

作者： Lin, Xiao Lu, Meichen Gao, Mufeng Li, Yan Institute of Artificial Intelligence on Education Research College of Information Mechanical and Electrical Engineering Shanghai Normal University Shanghai200234 China Shanghai Intelligent Education Big Data Engineering Technology Research Center Shanghai Normal University Shanghai200234 China Shanghai Online Education Research Base for Primary and Secondary Schools Shanghai200234 China School of Physical Education Shanghai Normal University Shanghai200234 China

Human pose estimation has received much attention from the research community because of its wide range of applications. However, current research for pose estimation is usually complex and computationally intensive, especially the feature loss problems in the feature fusion process. To address the above problems, we propose a lightweight human pose estimation network based on multi-attention mechanism (LMANet). In our method, network parameters can be significantly reduced by lightweighting the bottleneck blocks with depth-wise separable convolution on the high-resolution networks. After that, we also introduce a multi-attention mechanism to improve the model prediction accuracy, and the channel attention module is added in the initial stage of the network to enhance the local cross-channel information interaction. More importantly, we inject spatial cross-awareness module in the multi-scale feature fusion stage to reduce the spatial information loss during feature extraction. Extensive experiments on COCO2017 dataset and MPII dataset show that LMANet can guarantee a higher prediction accuracy with fewer network parameters and computational effort. Compared with the high-resolution network HRNet, the number of parameters and the computational complexity of the network are reduced by 67% and 73%, respectively. © 2023, Shanghai Jiao Tong University.

关键词： Complex networks

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Accurate Latent Factor Analysis via Particle Swarm Optimizers

Accurate Latent Factor Analysis via Particle Swarm Optimizer...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Jia Chen Xin Luo MengChu Zhou School of Cyber Science and Technology Beihang University Beijing China Chongqing Key Lab. of Big Data and Intelligent Computing and the Chongqing Engineering Research Center of Big Data Application for Smart Cities Chongqing Institute of Green and Intelligent Technology Chongqing School University of Chinese Academy of Sciences Chongqing China New Jersey Institute of Technology Newark NJ USA

ISBN: (纸本)9781665442084

A stochastic-gradient-descent-based Latent Factor Analysis (LFA) model is highly efficient in representative learning of a High-Dimensional and Sparse (HiDS) matrix. Its learning rate adaptation is vital in ensuring its efficiency. Such adaptation can be realized with an evolutionary computing algorithm. However, a resultant model tends to suffer from two issues: a) the pre-mature convergence of the swarm of learning rates as caused by an adopted evolution algorithm, and b) the pre-mature convergence of the LFA model as caused jointly by evolution-based learning rate adaptation and an optimization algorithm. This paper focuses on the methods to address such issues. A Hierarchical Particle-swarm-optimization-incorporated Latent factor analysis (HPL) model with a two-layered structure is proposed, where the first layer pre-trains desired latent factors with a position-transitional particle-swarm-optimization-based LFA model, and the second layer performs latent factor refining with a newly-proposed mini-batch particle swarm optimizer. With such design, an HPL model can well handle the pre-mature convergence, which is supported by the positive experimental results achieved on HiDS matrices from industrial applications.

关键词： Adaptation models Analytical models Computational modeling Refining Predictive models Sparse matrices Particle swarm optimization

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