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International Journal of Multimedia and Ubiquitous Engineering 2016年第9期11卷 29-38页

作者： Xiang, Lingyun Sun, Caixia Liao, Niandong Wang, Weizheng Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation Changsha University of Science and Technology ChangshaHunan Province410114 China School of Computer and Communication Engineering Changsha University of Science and Technology ChangshaHunan Province410114 China

Since the majority of the available steganographic schemes in OOXML format documents suffered the disadvantages of unsatisfactory anti-detection capability and security level, a characteristic-preserving steganographic method with high security is proposed in this paper. The proposed method embeds secret information by replacing the last three bytes of the values of the revision identifiers in the main document body of the OOXML format document, while preserving the normal characteristics of the document. Meanwhile, position marks are added to track the locations of the embedded information. In order to keep the internal data consistency of the document, the newly created values are added into other related parts. Experimental results show that the method not only possesses good imperceptibility and anti-detection capability, but also has high security and large embedding capacity. © 2016 SERSC.

关键词： Anti-detection Characteristic-preserving OOXML Revision identifier Steganography

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Price learning based load distribution strategies for demand response management in smart grid

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International Journal of Smart Home 2016年第11期10卷 79-94页

作者： Tang, Qiang Xie, Ming-Zhong Yang, Kun Luo, Yuan-Sheng Li, Ping Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation Changsha University of Science and Technology Changsha Hunan Province410114 China School of Computer and Communication Engineering Changsha University of Science and Technology Changsha China School of Computer Science and Electronic Engineering University of Essex Colchester United Kingdom

In this paper, a Price learning based Load Distribution Strategy (PLDS) is proposed at first. In PLDS model, Smart Power Service, Utility Company and History Load Curves are included, and by considering both the average electricity consumption cost and the average electricity consumption habit, we proposed a convex optimization model to solve the model. In order to accelerate the convergence of PLDS, a price learning mechanism is proposed, which learns a price curve according to the history price data, and predicts price as a learned price for the next iteration. The optimization cycle of PLDS is one day or 24 hours, and in order to further improve the peak shaving performance, an extended version of PLDS named PLRS (Price learning based Load Redistribution Strategy) is proposed, whose optimization cycle length is 1 hour. The optimization models of PLDS and PLRS are the same, and the differences between them are the optimization cycle and the constraint conditions. In the simulation, we compared the convergence performance, peaking shaving performance and total cost among PLDS, PLRS and other strategy ODC in reference [11], and we found that the convergence performances of PLDS and PLRS are both better than that of ODC. The peak shaving performance of PLRS is better than that of ODC in the long term, and the total cost of PLRS is very close to that of ODC. © 2016 SERSC.

关键词： Costs

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Flickr group recommendation via heterogeneous information networks 15

Flickr group recommendation via heterogeneous information ne...

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7th International Conference on Internet Multimedia Computing and Service, ICIMCS 2015

作者： Wang, Yueyang Xia, Yuanfang Tang, Siliang Wu, Fei Zhuang, Yueting College of Computer Science and Technology Zhejiang University Key Laboratory of Big Data Intelligent Computing of Zhejiang Province Innovation Joint Research Center for ICPS China

ISBN: (纸本)9781450335287

As an important characteristic of social media (i.e. Flickr or Facebook), user communities or groups are beginning to attract increasing attention. Most of the previous studies on group recommendation only consider a homogeneous relationship, such as the rating of users to groups in social network. In real world, each group has its textual descriptions (e.g. the "Sky & Cloud" group in Flickr), and the describing words about a given group may mention particular entities as well as their belonging categories (e.g. "Nature"). In fact, the group recommendation can be conducted in a heterogeneous information network, where informative cues are in general multi-typed. Motivated by the assumption that different types of relationships in heterogeneous information network can be potentially used to boost the performance of the group recommendation. We propose to combine heterogeneous relationship information for users with implicit user feedback. In general, the group recommendation in this paper is formulated as a non-negative matrix factorization (NMF) method regularized with user-user similarity via heterogeneous information networks. Experiments show that our proposed approach outperforms other counterpart recommendation techniques. © 2015 ACM.

关键词： Non-negative matrix factorization

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Research on bearing micro deformation based on the frequency domain technique of white light speckle image

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Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument 2016年 37卷 46-52页

作者： Feng, Bo Xu, Chao Shao, Deyang Luo, Shixian Anhui Engineering Laboratory of Agro-Ecological Big Data Anhui University Hefei230601 China Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Hefei230601 China

In this paper, a new method of non contact and on-line measurement is presented for the change of the axis of the rotation axis. Under the condition of a constant light source, the image of the original position and the offset image in the original position are collected by the micro camera, These two pictures are calculated by the improved White light digital image point by point analysis method in this paper, and get the black and white stripes. The number and the angle of the fringe in the white light digital frequency domain interference image can be known as the offset and direction of the rotating shaft in the rotating process. Because this method only use a camera and a light source, and this method is very simple, and it can always detect, and it does not affect the normal work, so there is a wide range of industrial application prospects. This method can provide alarm before the plastic deformation occurs in the shaft, Reduce the risk of shaft damage. © 2016, Science Press. All right reserved.

关键词： Frequency domain analysis

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No reference video quality assessment based on 3D convolutional neural network

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Ruan Jian Xue Bao/Journal of Software 2016年 27卷 103-112页

作者： Wang, Chun-Feng Su, Li Zhang, Wei-Gang Huang, Qing-Ming Key Laboratory on Big Data Mining and Knowledge Management University of Chinese Academy of Sciences Beijing100049 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology The Chinese Academy of Sciences Beijing100190 China Weihai264209 China

No reference video quality assessment (NR-VQA) measures distorted videos quantitatively without the reference of original high quality videos. Conventional NR-VQA methods are generally designed for specific types of distortions, or not consistent with human's perception. This paper innovatively introduces 3D deep convolutional neural network (3D-CNN) into VQA and proposes a 3D-CNN based NR-VQA method, which is universal for non-specific types of distortions. First, the proposed method utilizes 3D patches to learn spatio-temporal features that represent video content effectively. Second, the original 3D-CNN model is modified which is used to classify videos to make it adapt to VQA task. Experiments demonstrate that the proposed method is highly consistent with human's perception across numerous distortions and metrics. Compared with other state-of-the-art no-reference VQA methods, the proposed method runs much faster while keeping the similar performance. As a no-reference VQA method, it is even comparable with many of the state-of-the-art full-reference VQA methods, which provides the proposed method with better application prospects. © Copyright 2016, Institute of Software, the Chinese Academy of Sciences. All rights reserved.

关键词： Convolution

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Neighborhood collaborative classifiers

Neighborhood collaborative classifiers

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Suping Xu Xibei Yang Eric C. C. Tsang Eric A. Mantey Intelligent Information Processing Key Laboratory of Shanxi Province Shanxi University Taiyuan China School of Computer Science and Engineering Jiangsu University of Science and Technology Zhenjiang China Key Laboratory of Oceanographic Big Data Mining & Application of Zhejiang Province Zhejiang Ocean University Zhoushan China School of Economics and Management Nanjing University of Science and Technology Nanjing China Faculty of Information Technology Macau University of Science and Technology Macau China

ISBN: (纸本)9781509003914

In neighborhood rough set model, the majority rule based neighborhood classifier (NC) is easy to be misjudged with the increasing of the size of information granules. To remedy this deficiency, we propose a neighborhood collaborative classifier (NCC) based on the idea of collaborative representation based classification (CRC). NCC first performs feature selection with neighborhood rough set, and then instead of solving the classification problem by the majority rule, NCC solves a similar problem with collaborative representation among the neighbors of each unseen sample. Experiments on UCI data sets demonstrate that: 1) Our NCC achieves satisfactory performance in larger neighborhood information granules when compared with NC; 2) NCC reduces the size of dictionary when compared with CRC.

关键词： Collaboration Rough sets Training Cybernetics Numerical models Error analysis Measurement

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Parallel knowledge acquisition algorithm for big data using MapReduce

Parallel knowledge acquisition algorithm for big data using ...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Jin Qian Min Xia Ping Lv Jiangsu Key Laboratory of Big Data Analysis Technology/B-DAT Nanjing University of Information Science & Technology Nanjing China Key Laboratory of Cloud Computing and Intelligent Information Processing of Changzhou City Jiangsu University of Technology Changzhou China

ISBN: (纸本)9781467372220

With the rapid growth of data volume, knowledge acquisition for big data has become a new challenge. To address this issue, the hierarchical decision table is defined and implemented in this work. The properties of different hierarchical decision tables are discussed under the different granularity of conditional attributes. A novel knowledge acquisition algorithm for big data using MapReduce is proposed. Experimental results demonstrate that the proposed algorithm is able to deal with big data and mine hierarchical decision rules under the different granularity.

关键词： big data Hierarchical Rough Set Knowledge Acquisition MapReduce big data Information Extraction Decision tables

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Completion time-a ware flow scheduling in heterogenous networks 1

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15th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2015

作者： He, Shiming Xie, Kun Zhang, Dafang Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation School of Computer and Communication Engineering Hunan Province Engineering Research Center of Electric Transportation and Smart Distributed Network Changsha University of Science and Technology Changsha410114 China College of Computer Science and Electronics Engineering Hunan University Changsha410082 China Department of Electrical and Computer Engineering State University of New York at Stony Brook NY United States

ISBN: (数字)9783319271194

ISBN: (纸本)9783319271187

In China, the expressway isn’t free. When a vehicle exits, the exit toll station needs to calculate the toll according to the vehicle trajectory obtained by sending a trajectory query task to the trajectory center remotely. For the accurate of toll and keep the exit smoothly, transmitting the trajectory result reliably and in time is a key issue. There are three heterogenous networks in expressway, Fibernet, Telecommunications Network and 3G. We concurrently exploit three heterogenous networks by allocating the trajectory result into three sub-flows where each sub-flow is transmitted in one kind of networks. But existing multipath transfer solution(FMTCP) doesn’t consider the difference of completed time among all sub-flows and can’t make sure the completed time in time. Therefore, we formulate the sub-flows schedule as a integer programming problem, which is proved to be NP-hard problem, and propose a Completion time-aware Flow Scheduling scheme (CaFS) which calculates the size of sub-flows. For the reliably, it exploits generation-based network coding. For the transmission in time, CaFS allocates the size of sub-flow into suitable generation and scheduling the generations. The simulation results demonstrate that, comparing with the FMTCP, CaFS improves 31. 9% in completion time and 30% in task finished rate. © Springer International Publishing Switzerland 2015.

关键词： Network coding

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Privacy preserving for network coding in smart grid 15th

Privacy preserving for network coding in smart grid

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15th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2015

作者： He, Shiming Zeng, Weini Xie, Kun Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation School of Computer and Communication Engineering Hunan Province Engineering Research Center of Electric Transportation and Smart Distributed Network Changsha University of Science and Technology Changsha410114 China The 716th Research Institute China Shipbuilding Industry Corporation Lianyungang222061 China College of Computer Science and Electronics Engineering Hunan University Changsha410082 China Department of Electrical and Computer Engineering State University of New York at Stony Brook New York United States

ISBN: (纸本)9783319271361

In smart grid, privacy implications to individuals and their family is an important issue, due to the fine-grained usage data collection. Wireless communications are considered by many utility companies to obtain information. Network coding is exploited in smart grids, to enhance network performance in terms of throughput, delay, robustness, and energy consumption. However, Network Coding introduces new challenge for privacy preserving due to the encoding of packet in forwarder nodes. We propose a distributed privacy preserving scheme for network coding in smart grid, which considers the converged flows character of smart grid and exploits a homomorphic encryption function to decrease the complex in forwarder node. The message content of packet is encrypted and the tag of packet is encrypted by homomorphic encryption function. Then the forwarder node linear random codes the encrypted message contents and directly processes the tags cryptotext based on the homomorphism feature. It offers message content confidentiality privacy preserving feature, which can efficiently thwart traffic analysis. Extensive security analysis and performance evaluations demonstrate the validity and efficiency of the proposed scheme. © Springer International Publishing Switzerland 2015.

关键词： Smart power grids

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Risk Management Using big Real Time data

Risk Management Using Big Real Time Data

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IEEE International Conference on Cloud Computing Technology and Science (CloudCom)

作者： Jie Cheng Chunming Rong Huijuan Ye Xianghan Zheng Department of Electrical Engineering and Computer Science Risk Management Using Big Real Time Data Department of Computer Science and Electronic Engineering University of Stavanger Stavanger Norway College of Mathematics and Computer Science Fuzhou University Fuzhou China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou China

Adding to societal changes today, are the miscellaneous big data produced in different fields. Coupled with these data is the appearance of risk management. Admittedly, to predict future trend by using these data is conducive to make everything more efficient and easy. Now, no matter companies or individuals, they increasingly focus on identifying risks and managing them before risks. Effective risk management will lead them to deal with potential problems. This thesis focuses on risk management of flight delay area using big real time data. It proposes two different prediction models, one is called General Long Term Departure Prediction Model and the other is named as Improved Real Time Arrival Prediction Model. By studying the main factors lead to flight delay, this thesis takes weather, carrier, National Aviation System, security and previous late aircraft as analysis factors. By utilizing our models can do not only long time but also short term flight delay predictions. The results demonstrate goodness of fit. Besides the theory part, it also presents a practical and beautiful web application for real time flight arrival prediction based on our second model.

关键词： Delays Biological system modeling Meteorology Atmospheric modeling Predictive models Airports Splines (mathematics)

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