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redundant data Detection and Deletion to Meet Privacy Protection Requirements in Blockchain-Based Edge Computing Environment

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China Communications 2024年第3期21卷 149-159页

作者： Zhang Lejun Peng Minghui Su Shen Wang Weizheng Jin Zilong Su Yansen Chen Huiling Guo Ran Sergey Gataullin Cyberspace Institute Advanced Technology Guangzhou UniversityGuangzhou 510006China College of Information Engineering Yangzhou UniversityYangzhou 225127China School Math&Computer Science Quanzhou Normal UniversityQuanzhou 362000China Computer Science Department City University of Hong KongHong Kong 999077China School of Computer and Software Nanjing University of Information Science and TechnologyNanjing 21004China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and TechnologyAnhui UniversityHefei 230601China Department of Computer Science and Artificial Intelligence Wenzhou UniversityWenzhou 325035China Guangzhou University Library Guangzhou UniversityGuangzhou 510006China Central Economic and Mathematics Institute Russian Academy of Sciences MIREA-Russian Technological University Moscow RegionRussia

With the rapid development of information technology,IoT devices play a huge role in physiological health data *** exponential growth of medical data requires us to reasonably allocate storage space for cloud servers and edge *** storage capacity of edge nodes close to users is *** should store hotspot data in edge nodes as much as possible,so as to ensure response timeliness and access hit rate;However,the current scheme cannot guarantee that every sub-message in a complete data stored by the edge node meets the requirements of hot data;How to complete the detection and deletion of redundant data in edge nodes under the premise of protecting user privacy and data dynamic integrity has become a challenging *** paper proposes a redundant data detection method that meets the privacy protection *** scanning the cipher text,it is determined whether each sub-message of the data in the edge node meets the requirements of the hot *** has the same effect as zero-knowledge proof,and it will not reveal the privacy of *** addition,for redundant sub-data that does not meet the requirements of hot data,our paper proposes a redundant data deletion scheme that meets the dynamic integrity of the *** use Content Extraction Signature(CES)to generate the remaining hot data signature after the redundant data is *** feasibility of the scheme is proved through safety analysis and efficiency analysis.

关键词： blockchain data integrity edge computing privacy protection redundant data

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维普期刊数据库

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Exact Efficient Handling of Interrupted Illumination in Helical Cone-Beam Computed Tomography with Arbitrary Pitch

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Tsinghua Science and Technology 2010年第1期15卷 36-43页

作者： Harald Schndube Karl Stierstorfer Frédéric Noo Department of Radiology University of UtahSalt Lake CityUT 84132-2140USA Siemens Healthcare 91301 ForchheimGermany

We present a theoretically-exact and stable computed tomography （CT） reconstruction algorithm that is capable of handling interrupted illumination and therefore of using all measured data at arbitrary pitch This algorithm is based on a differentiated backprojection （DBP） on M-lines. First, we discuss the problem of interrupted illumination and how it affects the DBP. Then we show that it is possible to take advantage of some properties of the DBP to compensate for the effects of interrupted illumination in a mathematically exact way. From there, we have developed an efficient algorithm which we have successfully implemented. We show encouraging preliminary results using both computer-simulated data and real data. Our results show that our method is capable of achieving a substantial reduction of image noise when decreasing the helix pitch compared with the maximum pitch case. We conclude that the proposed algorithm defines for the first time a theoretically-exact and stable reconstruction method that is capable of beneficially using all measured data at arbitrary pitch.

关键词： computed tomography (CT) theoretically-exact and stable image reconstruction differentiated backprojection M-lines redundant data

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维普期刊数据库

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RFID unreliable data filtering by integrating adaptive sliding Window and Euclidean distance

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Advances in Manufacturing 2014年第2期2卷 121-129页

作者： Li-Lan Liu Zi-Long Yuan Xue-Wei Liu Cheng Chen Ke-Sheng Wang Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai University Department of Production and Quality Engineering Norwegian University of Science and TechnologyTrondheimNorway

Through improving the redundant data filtering of unreliable data filter for radio frequency identification（RFID） with sliding-window,a data filter which integrates self-adaptive sliding-window and Euclidean distance is *** input data required being filtered have been shunt by considering a large number of redundant data existing in the unreliable data for RFID and the redundant data in RFID are the main filtering object with utilizing the filter based on Euclidean *** comparison between the results from the method proposed in this paper and previous research shows that it can improve the accuracy of the RFID for unreliable data filtering and largely reduce the redundant reading rate.

关键词： Radio frequency identification(RFID) Adaptive sliding window Euclidean distance redundant data

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维普期刊数据库

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SVDD-SVM based fault class diagnosis method for incomplete analog circuits

SVDD-SVM based fault class diagnosis method for incomplete a...

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第43届中国控制会议

作者： Zhiqiang Zhang Danlu Yu Aihua Zhang College of Control Science and Engineering Bohai University

A method combining support vector data description(SVDD) and support vector machine(SVM) is proposed to deal with the fault diagnosis problem of analog circuits with incomplete fault *** the new feature vectors are sorted by the contribution of the data by applying principal component analysis,and a weighted Gaussian kernel function is constructed for the contribution of the feature quantities to improve the difference of features between *** the kernel parameters are optimized using the mucosal algorithm(SMA) to improve the robustness of the diagnostic model and the correct identification rate of the sample data to facilitate efficient diagnosis of normal and known fault ***,SVDD is used to partition the sample space for diagnosing unknown fault *** show that this method can efficiently diagnose known faults in analog circuits while judging unknown faults.

关键词： incomplete faults slime mould algorithm support vector machine principal component analysis redundant data

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一种处理生物数据库中数据冗余的方法

一种处理生物数据库中数据冗余的方法

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第二十一届中国数据库学术会议

作者：郭建奎张忠平朱扬勇复旦大学计算机与信息技术系燕山大学计算机科学与工程系

1引言生物数据库中的数据冗余大体可以分成两种类型,即重复序列和近似序列。所谓重复序列是指,组成DNA碱基序列中,重复出现的碱基序列;而近似序列,即组成DNA碱基序列中出现的近似重复序

关键词： redundant data Attribute reduction Rough set

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