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2010 IEEE International Conference on Information Theory and Information Security, ICITIS 2010

作者： Huang, Jianjun Liang, Bin Zhong, Jiagui Wang, Qianqian Cai, Jingjing Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China MOE Beijing 100872 China School of Information Renmin University of China Beijing 100872 China Beijing Venustech Cybervision Co. Ltd Beijing 100094 China

ISBN: (纸本)9781424469406

Web applications become more and more important, and the corresponding security problems have been concerned about. This paper presents TASA, an ASP static analyzer, which employs a path-sensitive, inter-procedural and context-sensitive data flow analysis, mainly concerning the taint propagation and sanitization. This paper also discusses some techniques used in TASA, such as sanitization routines modeling, ASP specific features, alias analysis and path-related routines modeling, to prune false positives. Experiments on four open source applications show that TASA has a rate of false positive of 4.98% and it can avoid certain false warnings owing to the proposed approaches. © 2010 IEEE.

关键词： data flow analysis

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Scientific Value Weights more than Being Open or Toll Access:An analysis of the OA advantage in Nature and Science

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Journal of data and Information Science 2021年第4期6卷 62-75页

作者： Howell Y.Wang Shelia X.Wei Cong Cao Xianwen Wang Fred Y.Ye International Joint Informatics Laboratory&Jiangsu Key Laboratory of Data Engineering and Knowledge Service School of Information ManagementNanjing UniversityNanjing 210023China Nottingham University Business School China University of Nottingham Ningbo ChinaNingbo315100China WISE Lab. Dalian University of TechnologyDalian 116024China

Purpose:We attempt to find out whether OA or TA really affects the dissemination of scientific ***/methodology/approach:We design the indicators,hot-degree,and R-index to indicate a topic OA or TA ***,according to the OA classification of the Web of Science(WoS),we collect data from the WoS by downloading OA and TA articles,letters,and reviews published in Nature and Science during 2010–*** papers are divided into three broad disciplines,namely biomedicine,physics,and ***,taking a discipline in a journal and using the classical Latent Dirichlet Allocation(LDA)to cluster 100 topics of OA and TA papers respectively,we apply the Pearson correlation coefficient to match the topics of OA and TA,and calculate the hot-degree and R-index of every OA-TA topic ***,characteristics of the discipline can be *** qualitative comparison,we choose some high-quality papers which belong to Nature remarkable papers or Science breakthroughs,and analyze the relations between OA/TA and citation ***:The result shows that OA hot-degree in biomedicine is significantly greater than that of TA,but significantly less than that of TA in *** on the R-index,it is found that OA advantages exist in biomedicine and TA advantages do in ***,the dissemination of average scientific discoveries in all fields is not necessarily affected by OA or ***,OA promotes the spread of important scientific discoveries in high-quality *** limitations:We lost some citations by ignoring other open sources such as arXiv and *** limitation came from that Nature employs some strong measures for access-promoting subscription-based articles,on which the boundary between OA and TA became *** implications:It is useful to select hot topics in a set of publications by the hotdegree *** finding comprehensively reflects the differences of OA and TA in different disciplines,which is a u

关键词： Open access Toll access Scientific discovery Academic dissemination data analysis

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A study of SQL-on-Hadoop systems

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8807卷 154-166页

作者： Chen, Yueguo Qin, Xiongpai Bian, Haoqiong Chen, Jun Dong, Zhaoan Du, Xiaoyong Gao, Yanjie Liu, Dehai Lu, Jiaheng Zhang, Huijie Key Laboratory of Data Engineering and Knowledge Engineering MOE Beijing China School of Information Renmin University of China Beijing100872 China

ISBN: (纸本)9783319130200

Hadoop is now the de facto standard for storing and processing big data, not only for unstructured data but also for some structured data. As a result, providing SQL analysis functionality to the big data resided in HDFS becomes more and more important. Hive is a pioneer system that support SQL-like analysis to the data in HDFS. However, the performance of Hive is not satisfactory for many applications. This leads to the quick emergence of dozens of SQL-on-Hadoop systems that try to support interactive SQL query processing to the data stored in HDFS. This paper firstly gives a brief technical review on recent efforts of SQLon- Hadoop systems. Then we test and compare the performance of five representative SQL-on-Hadoop systems, based on some queries selected or derived from the TPC-DS benchmark. According to the results, we show that such systems can benefit more from the applications of many parallel query processing techniques that have been widely studied in the traditional MPP analytical databases. © Springer International Publishing Switzerland 2014.

关键词： Big data

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Local anatomy for personalised privacy protection

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International Journal of Information and Computer Security 2021年第2-3期15卷 254-271页

作者： Li, Boyu Liu, Yanheng Wang, Minghai Sun, Geng Li, Bin College of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbolic Computation Knowledge Engineering of Ministry of Education College of Computer Science and Technology Jilin University Changchun China Big Data and Network Management Center Jilin University Changchun China College of Mathematics Jilin University Changchun China

Anonymisation technique has been extensively studied and widely applied for privacy-preserving data publishing. However, most existing methods ignore personal anonymity requirements. In these approaches, the microdata consist of three categories of attribute: explicit-identifier, quasi-identifier and sensitive attribute. In fact, the data sensitivity should be determined by individuals. An attribute is semi-sensitive if it contains both QI and sensitive values. In this paper, we propose a novel anonymisation approach, called local anatomy, to address personalised privacy protection. Local anatomy partitions the tuples who consider the value as sensitive into buckets inside each attribute. We conduct some experiments to illustrate that local anatomy can protect all the sensitive values and preserve great information utility. Additionally, we also present the concept of intelligent anonymisation system as our direction of future work. © 2021 Inderscience Enterprises Ltd.

关键词： Sensitive data

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Interference and power constrained broadcast and multicast routing in wireless ad hoc networks using directional antennas

Interference and power constrained broadcast and multicast r...

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作者： Li, Zheng Li, Deying Liu, Ming School of Information Renmin University of China Beijing 100872 China Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China MOE Beijing 100872 China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu 610054 China

In this paper, we address the interference and power constrained broadcast/multicast routing problem (D-IPCB/M) in wireless ad hoc networks using directional antenna as a starting point, which jointly considers low-interference and energy-efficiency issues. Then we study the delay-bounded interference and power constrained broadcast/multicast routing problem (DB-D-IPCB/M). An approximation algorithm and a heuristic algorithm with low time complexity are proposed for the D-IPCB/M and DB-D-IPCB/M problem, respectively. Finally, we explore and investigate the multi-constrained subgraph optimization (MCSO) problem. We prove its NP-hard and propose an approximation scheme with theoretical performance guarantee for this class of optimization problems. This is a general result originated from the study of D-IPCB/M and DB-D-IPCB/M problems, which can be applicable to solve different optimization problems such as the multi-constrained broadcast/multicast routing problems. Broadcast/multicast message by using the routing trees found by our algorithms tends to not only have less channel collisions but also save energy to extend network lifetime. The theoretical results are evaluated by simulation studies. © 2010 Elsevier B.V. All rights reserved.

关键词： Approximation algorithms

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A Heuristic Sampling Method for Maintaining the Probability Distribution

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Journal of Computer Science & Technology 2021年第4期36卷 896-909页

作者： Jiao-Yun Yang Jun-Da Wang Yi-Fang Zhang Wen-Juan Cheng Lian Li Key Laboratory of Knowledge Engineering with Big Data of Ministry of Education Hefei University of Technology Hefei 230601China National Smart EldeTca/re International Science and Technology Coopemtion Base Hefei University of Technology Hefei 230601China School of Computer Science and Information Engirwering Hefei University of TechnologyHefei 230601China School of Mathematics Hefei University of TechnologyHefei 230601China

Sampling is a fundamental method for generating data *** many data analysis methods are developed based on probability distributions,maintaining distributions when sampling can help to ensure good data analysis ***,sampling a minimum subset while maintaining probability distributions is still a *** this paper,we decompose a joint probability distribution into a product of conditional probabilities based on Bayesian networks and use the chi-square test to formulate a sampling problem that requires that the sampled subset pass the distribution test to ensure the ***,a heuristic sampling algorithm is proposed to generate the required subset by designing two scoring functions:one based on the chi-square test and the other based on likelihood *** on four types of datasets with a size of 60000 show that when the significant difference level,a,is set to 0.05,the algorithm can exclude 99.9%,99.0%,93.1%and 96.7%of the samples based on their Bayesian networks-ASIA,ALARM,HEPAR2,and ANDES,*** subsets of the same size are sampled,the subset generated by our algorithm passes all the distribution tests and the average distribution difference is approximately 0.03;by contrast,the subsets generated by random sampling pass only 83.8%of the tests,and the average distribution difference is approximately 0.24.

关键词： Bayesian network chi-square test sampling probability distribution

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A Deletable and Modifiable Blockchain Scheme Based on Record Verification Trees and the Multisignature Mechanism

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Computer Modeling in engineering & Sciences 2021年第7期128卷 223-245页

作者： Daojun Han Jinyu Chen Lei Zhang Yatian Shen Yihua Gao Xueheng Wang Henan Key Laboratory of Big Data Analysis and Processing Henan UniversityKaifeng47500China Institute of Data and Knowledge Engineering Henan UniversityKaifeng47500China School of Computer and Information Engineering Henan UniversityKaifeng47500China Department of Network and Finance Agricultural Bank of China Limited Xuchang BranchXuchang461000China School of Software Pingdingshan UniversityPingdingshan467000China Department of Network and Finance Agricultural Bank of China Limited Nanyang BranchNanyang473000China

As one of the most valuable technologies,blockchains have received extensive attention from researchers and industry circles and are widely applied in various ***,data on a blockchain cannot be *** a result,it is impossible to clean invalid and sensitive data and correct erroneous ***,to a certain extent,hinders the application of blockchains in supply chains and Internet of *** address this problem,this study presents a deletable and modifiable blockchain scheme(DMBlockChain)based on record verification trees(RVTrees)and the multisignature scheme.(1)In this scheme,an RVTree structure is designed and added to the block *** RVTree can not only ensure that a record is true and valid but,owing to its unique binary structure,also verify whether modification and deletion requests are valid.(2)In DMBlockChain,the multisignature mechanism is also *** mechanism requires the stakeholders’signatures for each modification or deletion request and thus ensures that a record will not be modified arbitrarily.A user’s request is deemed valid only if it is dually verified by the RVTree and the multisignature *** analysis finds that DMBlockChain can provide a secure and valid means for modifying and deleting records in a block while ensuring the integrity of the block and that DMBlockChain can effectively save space in some scenarios that require frequent records modification.

关键词： Blockchain record verification trees multisignature DMBlockChain

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DGA-Net: Dynamic Gaussian Attention Network for Sentence Semantic Matching 1st

DGA-Net: Dynamic Gaussian Attention Network for Sentence Se...

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1st CAAI International Conference on Artificial Intelligence, CICAI 2021

作者： Zhang, Kun Lv, Guangyi Wang, Meng Chen, Enhong Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology Hefei China School of Computer Science and Information Engineering Hefei University of Technology Hefei China School of Computer Science and Technology University of Science and Technology of China Hefei China

ISBN: (纸本)9783030930486

Sentence semantic matching requires an agent to determine the semantic relation between two sentences, where much recent progress has been made by advancement of representation learning techniques and inspiration of human behaviors. Among all these methods, attention mechanism plays an essential role by selecting important parts effectively. However, current attention methods either focus on all the important parts in a static way or only select one important part at one attention step dynamically, which leaves a large space for further improvement. To this end, in this paper, we design a novel Dynamic Gaussian Attention Network (DGA-Net) to combine the advantages of current static and dynamic attention methods. More specifically, we first leverage pre-trained language model to encode the input sentences and construct semantic representations from a global perspective. Then, we develop a Dynamic Gaussian Attention (DGA) to dynamically capture the important parts and corresponding local contexts from a detailed perspective. Finally, we combine the global information and detailed local information together to decide the semantic relation of sentences comprehensively and precisely. Extensive experiments on two popular sentence semantic matching tasks demonstrate that our proposed DGA-Net is effective in improving the ability of attention mechanism. © 2021, Springer Nature Switzerland AG.

关键词： Gaussian distribution

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RPR-Net: A Point Cloud-Based Rotation-Aware Large Scale Place Recognition Network 17th

RPR-Net: A Point Cloud-Based Rotation-Aware Large Scale Plac...

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17th European Conference on Computer Vision, ECCV 2022

作者： Fan, Zhaoxin Song, Zhenbo Zhang, Wenping Liu, Hongyan He, Jun Du, Xiaoyong Key Laboratory of Data Engineering and Knowledge Engineering of MOE School of Information Renmin University of China Beijing100872 China Department of Management Science and Engineering Tsinghua University Beijing100084 China School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China

ISBN: (纸本)9783031250552

Point cloud-based large scale place recognition is an important but challenging task for many applications such as Simultaneous Localization and Mapping (SLAM). Taking the task as a point cloud retrieval problem, previous methods have made delightful achievements. However, how to deal with catastrophic collapse caused by rotation problems is still under-explored. In this paper, to tackle the issue, we propose a novel Point Cloud-based Rotation-aware Large Scale Place Recognition Network (RPR-Net). In particular, to solve the problem, we propose to learn rotation-invariant features in three steps. First, we design three kinds of novel Rotation-Invariant Features (RIFs), which are low-level features that can hold the rotation-invariant property. Second, using these RIFs, we design an attentive module to learn rotation-invariant kernels. Third, we apply these kernels to previous point cloud features to generate new features, which is the well-known SO(3) mapping process. By doing so, high-level scene-specific rotation-invariant features can be learned. We call the above process an Attentive Rotation-Invariant Convolution (ARIConv). To achieve the place recognition goal, we build RPR-Net, which takes ARIConv as a basic unit to construct a dense network architecture. Then, powerful global descriptors used for retrieval-based place recognition can be sufficiently extracted from RPR-Net. Experimental results on prevalent datasets show that our method achieves comparable results to existing state-of-the-art place recognition models and significantly outperforms other rotation-invariant baseline models when solving rotation problems. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Network architecture

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data Cleaning of Binary Sensor Events in Activity Recognition by Cluster-Based Methods 7th

Data Cleaning of Binary Sensor Events in Activity Recognitio...

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7th International Conference on Human Aspects of IT for the Aged Population, ITAP 2021, held as part of the 23rd International Conference, HCI International 2021

作者： Zhao, Chunyang Que, Xia Yin, Yue Xing, Xiaoman Yang, Jiaoyun An, Ning Key Laboratory of Knowledge Engineering with Big Data of Ministry of Education Hefei University of Technology Hefei China School of Computer Science and Information Engineering Hefei University of Technology Hefei China Medical Imaging Department Chinese Academy of Sciences Suzhou China

ISBN: (纸本)9783030781101

The Ambient Assisted Living (AAL) systems use sensors to detect the daily behavior of older adults and provide necessary assistance based on changes in their cognitive status and physical functions, thus enabling older adults to maintain their independence at home. However, the effectiveness of the AAL systems depends on the accuracy of the data provided by sensors. Namely, when a human error or a hardware failure occurs, the activity recognition model can become inaccurate. This inaccuracy hinders the identification of critical and potentially life-threatening activities. Although there are many methods for cleaning sensor data, there is no method for binary sensors deployed in smart homes. By considering noisy sensor events and unintentional forgetting of turning off the device, this paper proposes two clustering-based methods for denoising and splitting binary sensor events to address possible inaccuracy due to the two mentioned problems. The effectiveness of the proposed methods is verified by the experiments using four machine learning models and three real-world smart home datasets and adopting different sensor configurations. The experimental results demonstrate that compared to the original unprocessed datasets, by combining the two proposed methods, the average accuracy and F-measure are improved by 15.00% and 17.25%, respectively. © 2021, Springer Nature Switzerland AG.

关键词： Automation

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