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23rd International Conference on database Systems for Advanced Applications, DASFAA 2018

作者： Yue, Zhongwei Zhang, Jingwei Zhang, Huibing Yang, Qing Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin541004 China Guangxi Cooperative Innovation Center of Cloud Computing and Big Data Guilin University of Electronic Technology Guilin541004 China Guangxi Key Laboratory of Automatic Measurement Technology and Instrument Guilin University of Electronic Technology Guilin541004 China

ISBN: (纸本)9783319914541

The popularity of mobile terminals has given rise to an extremely large number of trajectories of moving objects. As a result, it is critical to provide effective and efficient query operations on large-scale trajectory data for further retrieval and analysis. Considering data partition has a great influence on processing large-scale data, we present a time-based partitioning technique on trajectory data. This partitioning technique can be applied on the distributed framework to improve the performance of range queries on massive trajectory data. Furthermore, the proposed method adopts time-based hash strategy to ensure both the partition balancing and less partitioning time. Especially, existing trajectory data are not required to be repartitioned when new data arrive. Extensive experiments on three real data sets demonstrated that the performance of the proposed technique outperformed other partitioning techniques. © Springer International Publishing AG, part of Springer Nature 2018.

关键词： Trajectories

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Research on Star/Galaxy Classification Based on Stacking Ensemble Learning

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Chinese Astronomy and Astrophysics 2020年第3期44卷 345-355页

作者： Chao, L.I. Wen-hui, ZHANG Ran, L.I. Jun-yi, W.A.N.G. Ji-ming, L.I.N. College of Information and Communication Engineering Guilin University of Electronic Technology Guilin 541004 Key Laboratory of Education Ministry for Cognitive Radio and Information Processing Guilin University of Electronic Technology Guilin 541004 Guangxi Cooperative Innovation Center of Cloud Computing and Big Data Guilin University of Electronic Technology Guilin 541004 Guangxi College and University Key Laboratory for Cloud Computing and Complex Systems Guilin University of Electronic Technology Guilin 541004 Guangxi Key Laboratory for Wireless Wideband Communication and Signal Processing Guilin University of Electronic Technology Guilin 541004 Guangxi College and University Key Laboratory for Satellite Navigation and Position Sensing Guilin 541004

Machine learning has achieved great success in many areas today, but the forecast effect of machine learning often depends on the specific problem. An ensemble learning forecasts results by combining multiple base classifiers. Therefore, its ability to adapt to various scenarios is strong, and the classification accuracy is high. In response to the low classification accuracy of the darkest source magnitude set of stars/galaxies in the Sloan Digital Sky Survey (SDSS), a star/galaxy classification algorithm based on the stacking ensemble learning is proposed in this paper. The complete photometric data set is obtained from the SDSS data Release (DR) 7, and divided into the bright source magnitude set, dark source magnitude set, and darkest source magnitude set according to the stellar magnitude. Firstly, the 10-fold nested cross-validation method is used for the darkest source magnitude set, then the Support Vector Machine (SVM), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) algorithms are used to establish the base-classifier model;the Gradient Boosting Decision Tree (GBDT) is used as the meta-classifier model. Finally, based on the classification accuracy of galaxies and other indicators, the classification results are analyzed and compared with the results obtained by the Function Tree (FT), SVM, RF, GBDT, Stacked Denoising Autoencoders (SDAE), Deep Belief Nets (DBN), and Deep Perception Decision Tree (DPDT) models. The experimental results show that the stacking ensemble learning model has improved the classification accuracy of galaxies in the darkest source magnitude set by nearly 10% compared to the function tree algorithm. Compared with other traditional machine learning algorithm, stronger lifting algorithm, and deep learning algorithm, the stacking ensemble learning model also has different degrees of improvement. © 2020

关键词： Galaxies: fundamental parameters methods: data analysis Stars: fundamental parameters techniques: photometric

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Uncertainty-aware complementary label queries for active learning

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Frontiers of Information Technology & Electronic Engineering 2023年第10期24卷 1497-1503页

作者： Shengyuan LIU Ke CHEN Tianlei HU Yunqing MAO Key Lab of Intelligent Computing Based Big Data of Zhejiang Province Zhejiang UniversityHangzhou 310027China State Key Laboratory of Blockchain and Data Security Zhejiang UniversityHangzhou 310027China City Cloud Technology(China)Co. Ltd.Hangzhou 310000China

Many active learning methods assume that a learner can simply ask for the full annotations of some training data from *** methods mainly try to cut the annotation costs by minimizing the number of annotation ***,annotating instances exactly in many realworld classification tasks is still *** reduce the cost of a single annotation action,we try to tackle a novel active learning setting,named active learning with complementary labels(ALCL).ALCL learners ask only yes/no questions in some *** receiving answers from annotators,ALCL learners obtain a few supervised instances and more training instances with complementary labels,which specify only one of the classes to which the pattern does not *** are two challenging issues in ALCL:one is how to sample instances to be queried,and the other is how to learn from these complementary labels and ordinary accurate *** the first issue,we propose an uncertainty-based sampling strategy under this novel setup.

关键词： complementary instance ordinary

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Distributed Fault-tolerant Tracking Control for Multi-agent System in the Environments with Obstacles 35

Distributed Fault-tolerant Tracking Control for Multi-agent ...

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第35届中国控制会议

作者： HUANG Jie ZHOU Ning CHEN Hongzhi Faculty of Mathematics and Natural Sciences University of Groningen Institute of the Cloud Computing and Big Data for Smart Agriculture and Forestry College of Computer and Information SciencesFujian Agriculture and Forestry University State Key Laboratory of Hybrid Process Industry Automation System and Equipment Technology China Iron and Steel Research Institute Group

ISBN: (纸本)9781509009107

This paper investigates the problem of collision-free coordination tracking control for multi-agent system under modeling uncertainties,actuator faults and *** syncretizing the Null-Space-based Behavioral(NSB) control and finite-time control method,a novel reference velocity signal is predesigned to achieve finite-time obstacle avoidance and coordination *** a set of finite-time coordination control laws are presented to guarantee all the agents to track a dynamic target while avoiding obstacles/***,numerical simulation is presented to demonstrate the efficacy of the control strategy.

关键词： Distributed Control Obstacle Avoidance Fault-tolerant Control Finite-time Control Modeling Uncertainties

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Online Test Paper Composition Based on Genetic Algorithm

Online Test Paper Composition Based on Genetic Algorithm

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2018 3rd International Conference on Modelling, Simulation and Applied Mathematics(MSAM 2018)

作者： Wanli Song School of Information Engineering Nanjing Xiaozhuang University Key Laboratory of Trusted Cloud Computing and Big Data Analysis Nanjing XiaoZhuang University

The application of online examination is used more and more widely. Test paper composition is the core function in this application. Online examination system requires that the test paper should be quick and flexible, and the composition of questions should be reasonable and random. Test paper should not only meet the specific needs of users, ensure fairness, impartiality, but also be accurate and efficient. The intelligent test paper composition algorithm based on genetic algorithm is studied in this paper. Then this method is used to organize the structure of the test paper automatically, composites the examination content. Proposals are put forward to examines the degree of students' mastery of knowledge based on this method. This algorithm can automatically composite test papers according to the conditions of difficulty degree, knowledge coverage, and the proportion of questions. It can automatically composite test papers for online assessment. The practice of online testing system based on this algorithm shows that the algorithm is scientific and effective. On the premise of guaranteeing the quality of the test paper, it greatly improves the efficiency and pertinence of online testing. It is beneficial to improve students' learning efficiency and intellectualization of education.

关键词： test paper composition education intellectualization genetic algorithm E-learning

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News Recommendation System Based on Collaborative Filtering and SVM

News Recommendation System Based on Collaborative Filtering ...

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2018 3rd International Conference on Automation, Mechanical and Electrical Engineering (AMEE 2018)

作者： Wan-li SONG School of Information Engineering Nanjing Xiaozhuang University Key Laboratory of Trusted Cloud Computing and Big Data Analysis Nanjing Xiao Zhuang University

News system requires news classification and personalized recommendation to improve user's efficiency and interest, and to enhance user's experiences. This paper constructed a news automatic classification and recommendation system through natural language processing, text classification, collaborative filtering algorithm. The published news contents were word-segmented and model-trained automatically first to determine which category the news belonging to. Users can also manually modify the classification so that later classification can be updated and improved. After that, the similarity between users was calculated by collaborative filtering and the users having higher similarity with the recommended users were selected. The news seen by the certain users were recommended to the users that were divided into the same group. This paper takes the news corpus of Fudan University's text classification research center as experimental data. Text classification accuracy is tested by this corpus. The experimental results show that the system can serve the news users well. It achieves effective classification and recommendation of news personally.

关键词： Recommendation algorithm Automatic classification Similarity Collaborative filtering

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A Blockchain-based Revocable Certificateless Signature Scheme for IoT Device

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International Journal of Network Security 2021年第6期23卷 1012-1027页

作者： Chen, Yushuang Zheng, Dong Guo, Rui Zhang, Yinghui Tao, Xiaoling School of Cyberspace Security Xi’an University of Posts and Telecommunications Xi’an710121 China State Key Laboratory of Integrated Services Networks Xidian University Xi’an710071 China National Engineering Laboratory for Wireless Security Xi’an University of Posts and Telecommunications Guilin University of Electronic Technology Guilin541004 China Guangxi Cooperative Innovation Center of Cloud Computing and Big Data Guilin University of Electronic Technology Guilin541004 China

With the rapid development of Internet of Things (IoT) technology, completing a transaction with intelligent devices has been an essential communication mode in our daily life. Generally, lightweight smart devices conduct transactions relying on the third-party payment platform, which takes several inherent challenges of mutual distrust, data authentication and low efficiency in the IoT environment. To mitigate these issues, in this paper, we design a paring-free revocable certificateless signature (CLS) scheme with high efficiency based on the blockchain technique. Our scheme is a viable approach to enhance the performance without bilinear parings operation in the IoT lightweight equipment. And there are two different address lists stored in the blockchain to record the secret and public transaction data, respectively. According to this method, not only can the key management of the user be implemented in an efficient solution, but also enables the public verification to be performed transparently between the two parties. Furthermore, with the help of cloud server, it generates a time key for the user to accomplish revocation with low computation cost. We also make an analysis on the security to demonstrate that our proposal is existential unforgeability against adaptive chosen message attacks (EUF-CMA) under the elliptic curve discrete logarithm (ECDL) problem. Finally, the performance comparison indicates that our protocol is better than other related schemes. © 2021. International Journal of Network Security. All Rights Reserved.

关键词： Blockchain

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Secure searchable encryption: a survey

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Journal of Communications and Information Networks 2017年第4期1卷 52-65页

作者： Wang, Yunling Wang, Jianfeng Chen, Xiaofeng State Key Laboratory of Integrated Service Networks (ISN) Xidian University Xian China Guangxi Cooperative Innovation Center of Cloud Computing and Big Data Guilin University of Electronic Technology Guilin China

cloud computing facilitates convenient and on-demand network access to a centralized pool of resources. Currently, many users prefer to outsource data to the cloud in order to mitigate the burden of local storage. However, storing sensitive data on remote servers poses privacy challenges and is currently a source of concern. SE (Searchable Encryption) is a positive way to protect users sensitive data, while preserving search ability on the server side. SE allows the server to search encrypted data without leaking information in plaintext data. The two main branches of SE are SSE (Searchable Symmetric Encryption) and PEKS (Public key Encryption with keyword Search). SSE allows only private key holders to produce ciphertexts and to create trapdoors for search, whereas PEKS enables a number of users who know the public key to produce ciphertexts but allows only the private key holder to create trapdoors. This article surveys the two main techniques of SE: SSE and PEKS. Different SE schemes are categorized and compared in terms of functionality, efficiency, and security. Moreover, we point out some valuable directions for future work on SE schemes.

关键词：

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Real-time network traffic classification based on CDH pattern matching 14

Real-time network traffic classification based on CDH patter...

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14th International Conference on Computational Intelligence and Security, CIS 2018

作者： Li, Xunzhang Wang, Yong Ke, Wenlong Feng, Hao School of Computer Science and Information Security Guilin University of Electronic Technology Guilin Guangxi541004 China School of Information and Communication Guilin University of Electronic Technology Guilin Guangxi541004 China Guangxi Cooperative Innovation Center of Cloud Computing and Big Data Guilin University of Electronic Technology Guilin Guangxi541004 China Guangxi Colleges and Universities Key Laboratory of Cloud Computing and Complex Systems Guilin University of Electronic Technology Guilin Guangxi541004 China

ISBN: (纸本)9781728101699

In recent years, with the rapid development of the Internet, the data scale of application behavior and application traffic have exploded. How to classify the real-time traffic of network becomes a big challenge. How to balance the accuracy and real-time of traffic classification is a difficult problem in technology. Therefore, this paper proposes a pattern matching real-time traffic classification method named PM, which first uses jpcap to accept network traffic data in real time, and then uses pattern matching to perform real-time matching traffic characteristics to achieve traffic classification. Among them, the use of the distributed message system kafka and the parallel computing framework Spark significantly improve the execution efficiency of the program. The experimental results show that PM has good performance in terms of accuracy. © 2018 IEEE.

关键词： Pattern matching

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Secure searchable encryption:a survey

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Journal of Communications and Information Networks 2016年第4期1卷 52-65页

作者： WANG Yunling WANG Jianfeng CHEN Xiaofeng State Key Laboratory of Integrated Service Networks(ISN) Xidian UniversityXian 710071China Guangxi Cooperative Innovation Center of Cloud Computing and Big Data Guilin University of Electronic TechnologyGuilin 541004China

cloud computing facilitates convenient and on-demand network access to a centralized pool of ***,many users prefer to outsource data to the cloud in order to mitigate the burden of local ***,storing sensitive data on remote servers poses privacy challenges and is currently a source of ***(Searchable Encryption)is a positive way to protect users sensitive data,while preserving search ability on the server *** allows the server to search encrypted data without leaking information in plaintext *** two main branches of SE are SSE(Searchable Symmetric Encryption)and PEKS(Public key Encryption with keyword Search).SSE allows only private key holders to produce ciphertexts and to create trapdoors for search,whereas PEKS enables a number of users who know the public key to produce ciphertexts but allows only the private key holder to create *** article surveys the two main techniques of SE:SSE and *** SE schemes are categorized and compared in terms of functionality,efficiency,and ***,we point out some valuable directions for future work on SE schemes.

关键词： cloud storage encrypted data searchable encryption searchable symmetric encryption public key encryption with keyword search.

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