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An image compression method based on block truncation coding and linear regression

Journal of information Hiding and Multimedia Signal processing 2016年第1期7卷 198-215页

作者： Lyu, Wan-Li Chang, Chin-Chen Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei230039 China Department of Information Engineering and Computer Science Feng Chia University 100 Wenhwa Rd Seatwen Taichung40724 Taiwan Department of Computer Science and Information Engineering Asia University Taichung41354 Taiwan

This paper describes an image compression method based on block truncation coding (BTC) and linear regression coding (LRC) hybrid strategy. BTC is simple and easy to use, but only two representative values can not adequately represent the visual feature of image blocks. However, LRC can obtain different values of points with the line function by recording the coefficient of the regression line while the data distribution shows a linear relationship. The proposed method designs a hybrid strategy to combine the advantages of the two methods to improve image quality. In the paper, first, models are designed to rearrange the data of image blocks to satisfy a linear distribution, and then these models are used to code the image blocks. The experimental results indicated that the proposed method is superior to the BTC scheme in terms of image quality, and it can be used for image compression applications. © 2016.

关键词： Linear regression

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Regression-based execution time prediction in hadoop environment

Regression-based execution time prediction in hadoop environ...

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International Conference on information Technology and Computer Application Engineering, ITCAE 2014

作者： Wu, Xiao Dong Zeng, Yu Zhu Zhao, C.T. Faculty of Mathematics and Computer Science Quanzhou Normal University China Fujian Provincial Key Laboratory of Data Intensive Computing China Key Laboratory of Intelligent Computing and Information Processing Fujian Province University China

ISBN: (纸本)9781138027176

Hadoop MapReduce has been proven an effective computing model to deal with big data for the last few years. However, one technical challenge facing this framework is how to predict the execution time of an individual job. In this paper, we propose a regression-based method to predict the execution times of Hadoop jobs. The proposed prediction method consists of three phases: learning data sampling, regression analysis and making prediction. Experimental results show that the predicted execution time obtained by our method is close to the actual execution time. © 2015 Taylor & Francis Group, London.

关键词： Regression analysis

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Bayesian localization microscopy based on intensity distribution of fluorophores

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Protein & Cell 2015年第3期6卷 211-220页

作者： Fan Xu Mingshu Zhang Zhiyong Liu Pingyong Xu Fa Zhang Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China Laboratory of Non Coding RNA Institute of Biophysics Chinese Academy of Sciences Beijing 100101 China

Super-resolution microscopy techniques have overcome the limit of optical diffraction. Recently, the Bayesian analysis of Bleaching and Blinking data （3B） method has emerged as an important tool to obtain super-resolution fluorescence images. 3B uses the change in information caused by adding or removing fiuorophores in the cell to fit the date. When adding a new fluorophore, 3B selects a random initial position, optimizes this position and then determines its reliability. However, the fluorophores are not evenly distributed in the entire image region, and the fluorescence intensilty at a given position positively correlates with the probability of observing a fluorophore at this position. In this paper, we present a Bayesian analysis of Bleaching and Blinking microscopy method based on fluorescence intensity distribution （FID3B）. We utilize the intensity distribution to select more reliable positions as the initial positions of fluorophores. This approach can improve the reconstruction results and significantly reduce the computational time. We validate the perfor. mance of our method using both simulated date and experimental date from cellular structures. The results confirm the effectiveness of our method.

关键词： super-resolution fluorescence image 3B,intensity distribution

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Runtime model based approach to IoT application development

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Frontiers of Computer Science 2015年第4期9卷 540-553页

作者： Xing CHEN College of Mathematics and Computer Science Fuzhou University Fuzhou 350116 China Fujian Provincial Key Laboratory of Networking Computing and Intelligent Information Processing Fuzhou 350116 China Key Laboratory of High Confidence Software Technologies (Ministry of Education) Beijing 100871 China School of Electronics Engineering and Computer Science Peking University Beijing 100871 China

The internet of things （loT） attracts great interest in many application domains concerned with monitoring and ：ontrol of physical phenomena. However, application devel- opment is still one of the main hurdles to a wide adoption of IoT technology. Application development is done at a low level, very close to the operating system and requires pro- grammers to focus on low-level system issues. The under- lying APIs can be very complicated and the amount of data collected can be huge. This can be very hard to deal with as a developer. In this paper, we present a runtime model based approach to IoT application development. First, the manage- ability of sensor devices is abstracted as runtime models that are automatically connected with the corresponding systems. Second, a customized model is constructed according to a personalized application scenario and the synchronization be- tween the customized model and sensor device runtime mod- els is ensured through model transformation. Thus, all the application logic can be carried out by executing programs on the customized model. An experiment on a real-world ap- plication scenario demonstrates the feasibility, effectiveness, and benefits of the new approach to IoT application develop- ment.

关键词： IoT application development software architec-ture models at runtime

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The analysis of big Data application mode and security risk

The analysis of big Data application mode and security risk

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International Conference on information Sciences,Machinery,Materials and Energy（ICISMME 2015）

作者： ZENG Tai-sheng Faculty of Mathematics and Computer Science Quanzhou Normal University Fujian Provincial Key Laboratory of Data Intensive Computing Key Laboratory of Intelligent Computing and Information Processing Fujian Province University

ISBN: (纸本)9789462520677

In the current social background,Existing facilities and tools already can not meet the needs of big data in expanding and analysis ***'s data storage and analysis work is achieved under cloud conditions and Hadoop were set *** the conditions for cloud computing,cloud computing applications who have remote data files were not authorized to read its contents,which results in unauthorized manipulation,and it will produce a lot of security risks for large *** this paper,according to the cloud of different modes,Hadoop different stages of the operation,subject to the threat of non- confidence and security to steal big data generated to analyze a variety of privacy,with threat model as an example,it explores ways to address security threats.

关键词： big data security analysis Hadoop

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An improved performance metric for multiobjective evolutionary algorithms with user preferences

An improved performance metric for multiobjective evolutiona...

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IEEE Congress on Evolutionary Computation, CEC 2015

作者： Yu, Guo Zheng, Jinhua Li, Xiaodong School of Information Engineering Xiangtan University Hunan China Key Laboratory of Intelligent Computing Information Processing of Ministry of Education China School of Computer Science and IT RMIT University Melbourne Australia

ISBN: (纸本)9781479974924

This paper proposes an improved performance metric for multiobjective evolutionary algorithms with user preferences. This metric uses the idea of decomposition to transform the preference information into m+1 points on a constructed preference-based hyperplane, then calculates the Euclidean distances and the angles between the obtained solutions by algorithms and those obtained m+1 points, respectively. By means of these distances and angles, the proposed metric can evaluate effectively both the convergence and diversity of the obtained solution set, with consideration of the preference information. This makes easier and allows meaningful comparisons between different multiobjective evolutionary algorithms using preference information. © 2015 IEEE.

关键词： Evolutionary algorithms

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Online hot event discovery based on Association Link Network

Online hot event discovery based on Association Link Network

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作者： Liu, Yang Luo, Xiangfeng Xuan, Junyu School of Computer Engineering and Science Shanghai University China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Science Beijing China

Online hot event discovery has become a flourishing frontier where online document streams are monitored to discover newly occurring events or assigned to previously detected events. However, hot events have the nature to evolve, and their inherent topically related words are also likely to evolve. It makes event discovery a challenging task for traditional-mining approaches. Combining word association and semantic community, Association Link Network (ALN) organizes the loosely distributed associated resources. This paper presents an ALN-based novel online hot event discovery approach. Technically, this approach is enacted around three stages. In the first stage, we extract significant features to represent the content of each document from the online document stream. During the second stage, we classify the online document stream into topically related detected events considering event evolution in the form of ALN. At the third stage, we create an ALN-based event detection algorithm, which is used to timely discover newly occurring hot events. The online datasets used in our empirical studies are acquired from Baidu News, which spans a range of 1315 hot events and 236,300 documents. Experimental results demonstrate the hot events discovery ability with respect to high accuracy, good scalability, and short runtime. © 2015 John Wiley & Sons, Ltd.

关键词： Semantics

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Multi-path SDN route selection subject to multi-constraints 3

Multi-path SDN route selection subject to multi-constraints

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3rd International Conference on Cyberspace Technology, CCT 2015

作者： Pan, Qingfeng Zheng, Xianghan College of Mathematics and Computer Science Fuzhou University Fuzhou350108 China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou350108 China

ISBN: (纸本)9781785610899

Multi-constrained optimal routing problem and disjoint path selection are NP-hard problem. The conventional single-path and single constraint routing can not meet people's needs. The reliability of network data transmission and packet loss rate can be decreased when the route or the transmission fails. To solve the problems, we need to study the routing path selection strategies. This paper optimizes the routing path that meets the QoS constraints under the SDN pre planning routing, and proposes a routing mechanism that can solve problems in polynomial time. Firstly, the paper combined with Clustering and Gauss algorithm to simulate the network simulation, obtain the initial experimental data. It can reflect the network status more accurately. Secondly, simplify the multi-objectives based on the AHP, It reduces the complexity of the problem and meets QoS requirements. Finally, select the disjoint communication paths and backup paths with the heuristic algorithms in order to balance the load of network and improve the transmission reliability. The selection mechanism can improve the efficiency of data transmission, and the survival of network communication.

关键词： Heuristic algorithms

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On Secrecy Performance of MISO SWIPT Systems with TAS and Imperfect CSI

On Secrecy Performance of MISO SWIPT Systems with TAS and Im...

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作者： Pan, Gaofeng Lei, Hongjiang Deng, Yansha Fan, Lisheng Yang, Jing Chen, Yunfei Ding, Zhiguo Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing School of Electronic and Information Engineering Southwest University Chongqing400715 China School of Computing and Communications Lancaster University LancasterLA14YW United Kingdom Chongqing Key Laboratory of Mobile Communications Technology Chongqing University of Posts and Telecommunications Chongqing400065 China Centre for Telecommunications King's College London LondonWC2R2LS United Kingdom School of Computer Science and Educational Software Guangzhou University Guangzhou510000 China Department of Electronic Engineering Shantou University Guangdong515063 China School of Information Engineering Yangzhou University Yangzhou225009 China School of Engineering University of Warwick CoventryCV47AL United Kingdom

In this paper, a multiple-input single-output (MISO) simultaneous wireless information and power transfer (SWIPT) system, including one base station (BS) equipped with multiple antennas, one desired single-antenna information receiver (IR), and N (N > 1) single-antenna energy-harvesting receivers (ERs) is considered. Assuming that the information signal to the desired IR may be eavesdropped by ERs if ERs are malicious, we investigate the secrecy performance of the target MISO SWIPT system when imperfect channel state information (CSI) is available and adopted for transmit antenna selection at the BS. Considering that each eavesdropping link experiences independent but not necessarily identically distributed Rayleigh fading, the closed-form expressions for the exact and the asymptotic secrecy outage probability, and the average secrecy capacity are derived and verified by simulations. Furthermore, the optimal power splitting factor is derived for each ER to realize the tradeoff between the energy harvesting and the information eavesdropping. Our results reveal the impact of the imperfect CSI on the secrecy performance of MISO SWIPT systems in the presence of multiple wiretap channels. © 2016 IEEE.

关键词： Energy harvesting

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Some applications of nonlinear science methods and support vector machine methods to protein problems

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Mini-Reviews in Organic Chemistry 2015年第6期12卷 493-505页

作者： Hana, Guo Sheng Yu, Zu-Guo Zhao, Zhi-Qin Hunan Key Laboratory for Computation and Simulation in Science and Engineering and Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University XiangtanHunan411105 China School of Mathematical Sciences Queensland University of Technology GPO Box 2434 BrisbaneQ4001 Australia

Protein folding, prediction of protein structure and functions are most important problems in bioinformatics. The protein fold process mainly reflects in the kinetic order of folding. Predicting the structural classes of low-homology protein is a difficult problem in the prediction of protein structure. In order to understanding the mechanism of programmed cell death, it is very necessary to obtain the information about subcellular locations and functions of apoptosis proteins. Predicting protein subnuclear localizations is a challenging problem which is harder than predicting protein subcellular locations. Predicting membrane protein types is related to the structure and function of proteins. In this review, we introduce some applications of nonlinear science methods and support vector machine methods to the above protein problems. The nonlinear science methods including the horizontal visibility network, kernel method, recurrence quantification analysis, global descriptor, Lempel-Ziv complexity, and Hilbert-Huang transform are used to extract features in these approaches. © 2015 Bentham Science Publishers.

关键词： Support vector machines

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