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MR-COF:A Genetic MapReduce Configuration Optimization Framework

MR-COF:A Genetic MapReduce Configuration Optimization Framew...

The 7th International Symposium on Parallel Architectures, Algorithms and Programming, PAAP2015(2015年第七届国际并行体系结构,算法和编程研讨会)

作者： Chao Liu Deze Zeng Hong Yao Chengyu Hu Xuesong Yan Yuanyuan Fan China Services Computing Technology and System Lab and Cluster and GridComputing Lab Huazhong University of Science and TechnologyWuhan 430074China Hubei Key Laboratory of Intelligent Geo-Information Processing China University of GeosciencesWuhan 430074China

Hadoop/MapReduce has emerged as a de facto programming framework to explore cloud-computing *** has many configuration parameters,some of which are crucial to the performance of MapReduce *** practice,these parameters... 详细信息

ISBN: (纸本)9783319271392

关键词： Mapreduce Massive data processing Parameter configuration Performance optimization Search algorithm

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Stabilization of Time-Delay Markovian Jump systems via Probability Rate Synthesis and State Feedback

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IFAC Proceedings Volumes 2014年第3期47卷 10415-10420页

作者： Shan Ma Junlin Xiong CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei 230026 China

This paper considers the stabilization problem for Markovian jump systems with time delays. Both the probability rate matrix and the state feedback control law are to be designed. A sufficient condition is established for such designs such that the resulting closed-loop Markovian jump system is stochastically stable. This condition is given in terms of a system of linear matrix inequalities with rank constraints, and can be solved using some existing algorithms. When the system has polytopic uncertainties, the robust stabilization problem is studied as well. Finally, a numerical example is given to show the validity of the proposed method.

关键词： Markovian jump systems time delay state feedback stabilization

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Encoding spatial Context for Large-Scale Partial-Duplicate Web Image Retrieval

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Journal of Computer Science & technology 2014年第5期29卷 837-848页

作者：周文罡李厚强卢亦娟田奇 Chinese Academy of Sciences Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China Department of Electronic Engineering and Information Science University of Science and Technology of China Department of Computer Science Texas State UniversitySan Marcos TX 78666 U.S.A. MemberACMIEEE Department of Computer Science University of Texas at San AntonioSan Antonio TX 78249 U.S.A. Senior MemberIEEE

Many recent state-of-the-art image retrieval approaches are based on Bag-of-Visual-Words model and represent an image with a set of visual words by quantizing local SIFT（scale invariant feature transform） features. Feature quantization reduces the discriminative power of local features and unavoidably causes many false local matches between images, which degrades the retrieval accuracy. To filter those false matches, geometric context among visual words has been popularly explored for the verification of geometric consistency. However, existing studies with global or local geometric verification are either computationally expensive or achieve limited accuracy. To address this issue, in this paper, we focus on partialduplicate Web image retrieval, and propose a scheme to encode the spatial context for visual matching verification. An efficient affine enhancement scheme is proposed to refine the verification results. Experiments on partial-duplicate Web image search, using a database of one million images, demonstrate the effectiveness and efficiency of the proposed *** on a 10-million image database further reveals the scalability of our approach.

关键词： large-scale image retrieval spatial context coding spatial verification affine estimation

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Descriptor systems State-space Conditions to Guarantee Negative Imaginary Properties without Minimality Restrictions

Descriptor Systems State-space Conditions to Guarantee Negat...

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IEEE Annual Conference on Decision and Control

作者： Junlin Xiong Alexander Lanzon Ian R. Petersen CAS Key Lab of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei 230026 China Control Systems Centre School of Electrical and Electronic Engineering University of Manchester Manchester M13 9PL U.K. School of Engineering and Information Technology University of New South Wales at the Australian Defence Force Academy Canberra ACT 2600 Australia

ISBN: (纸本)9781479978878

This paper is concerned with negative imaginary lemmas for descriptor systems. Without the minimal state-space realization assumption, sufficient conditions are developed for a negative imaginary lemma and a strictly negative imaginary lemma, respectively. As corollaries, sufficient conditions are derived to ensure the systems are both admissible and negative imaginary. Also, new sufficient negative imaginary lemmas are found for standard linear systems as special cases. The developed negative imaginary lemmas are applicable to descriptor systems with impulse modes. Two examples are used to illustrate the theory.

关键词： Theorem Negative Linear system Descriptors Lemma Sufficient conditions

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A Multicast Architecture of SVC Streaming Over OpenFlow Networks

A Multicast Architecture of SVC Streaming Over OpenFlow Netw...

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IEEE Global Communications Conference

作者： Enzhong Yang Yongyi Ran Shuangwu Chen Jian Yang CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China

ISBN: (纸本)9781479935130

In video streaming service, multicast mode is a promising way to complement unicast delivery of content, since it deliveries the video content to a broad range of receivers. It is considered as an efficient scheme to reduce redundant traffic in the networks. In this paper, we propose an OpenFlow based architecture for implementing Scalable Video Coding (SVC) multicast streaming. It enables in-network identifying, processing and manipulating the media streams, which makes prompt bitrate adaptation possible in response to network fluctuations. The heterogeneous video quality demand from the heterogeneous device also can be satisfied by customizing the multicast traffic through a centralized OpenFlow controller. We implement a testbed following the proposed architecture in our campus. With OpenFlow, we deploy IP multicast in a new way without Internet Group Management Protocol (IGMP) or any multicast addresses. Experiments implemented on the testbed show that our approach can provide a flexible and controllable video multicast streaming service and improve the usage of bandwidth resource in the condition of guaranteeing multicast receivers' Quality of Experience (QoE).

关键词： IP networks multicast communication telecommunication traffic video coding video streaming IP multicast OpenFlow networks bandwidth resource usage improvement bitrate adaptation centralized OpenFlow controller controllable video multicast streaming service heterogeneous device heterogeneous video quality demand media streams multicast SVC streaming architecture multicast receivers quality-of-experience multicast traffic network fluctuations redundant traffic reduction scalable video coding multicast streaming unicast content delivery Control systems Ports (Computers) Receivers Servers Static VAr compensators Streaming media

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Discovering bursty topics from news stream with a unified statistical model

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Journal of Computational information systems 2014年第18期10卷 7825-7832页

作者： Qi, Xiang Huang, Yu Liu, Xiaoyan Fu, Kun Wang, Hongqi Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Institute of Electronics University of Chinese Academy of Sciences Beijing China

This paper focuses on discovering bursty topics from news stream. Previous work usually apply Kleinberg's modeling of burst to topics estimated by a topic model such as Latent Dirichlet Allocation (LDA) and Dynamic Topic Model (DTM). However, Kleinberg's model is originally proposed for the burst of keywords, the frequency counts it models are not proper to describe the burst states of topics, leading to some unwanted results. A more reasonable way is to model the influence burst states put on each document's topic distribution. Considering this, we propose a unified statistical model that takes the burst states as markov latent variables that influence the topic allocation of documents. We derive a Gibbs sampling algorithm for the proposal. Experiment results confirm our model's advantages both qualitatively and quantitatively.

关键词： Bayesian networks

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Category-based dynamic recommendations adaptive to user interest drifts

Category-based dynamic recommendations adaptive to user inte...

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International Conference on Wireless Communications and Signal processing (WCSP)

作者： Kaixiang Lin Dong Liu CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei China

ISBN: (纸本)9781479973408

How to make dynamic recommendations under volatile user interest drifts has been a problem of great interest in modern recommender systems, where challenges lie in accurate and efficient measurement, modeling, and prediction of the user interest drifts. This paper studies a category-based approach to the problem with the key idea that items are aggregated into categories and recommendations are made on each category. In our approach, we use the category-wise rating matrix to measure the changing preferences of users; we design a dynamic adaptive model (DAM) to describe the patterns of interest drifts; and we utilize linear regression to predict the future interests of users in a category-based manner. We have built a category-based dynamic recommender system and tested it with two well-known datasets. Experimental results show that our proposed approach achieves superior performance on category-based rating prediction compared with state-of-the-art dynamic recommendation algorithms.

关键词： Vectors Adaptation models Clustering algorithms Recommender systems Optimization Predictive models Data models

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Visualization of user interests in online music services

Visualization of user interests in online music services

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IEEE International Conference on Multimedia and Expo Workshops (ICMEW)

作者： Jingxian Zhang Dong Liu CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei China

ISBN: (纸本)9781479947164

Online music services have been popular for end users to obtain music, where user interests, as reflected by their downloading records, are crucial for service providers to understand users and thus to provide personalization. However, the raw downloading records are of huge volume and difficult to analyze intuitively. We study a visualization approach to analyzing downloading records so as to present user interests. To reveal the underlying relevance between music tracks, we utilized not only the metadata of music (especially genres), but also collaborative relevance that is voted by users. To present time varying user interests, we designed several new figures, namely Bean plot, Instrument plot, and Transitional Pie plot, that are capable in displaying different aspects of user interests variation. We have performed experiments with a real-world data set, and the results show the effectiveness of our proposed visualization method. Our work is also inspiring for visualization of time varying data in other applications.

关键词： Instruments Collaboration Color Statistical distributions Data visualization Neck Educational institutions

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Image annotation via social diffusion analysis with common interests

Image annotation via social diffusion analysis with common i...

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IEEE International Conference on Multimedia and Expo Workshops (ICMEW)

作者： Chenyi Lei Dong Liu CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei China

Automatic annotation of images is of crucial importance in image retrieval and management systems. Most of the existing annotation methods rely on content-based approach to annotation, whose effectiveness is restricted due to the semantic gap between low-level features and semantic annotations, as well as the irrelevance between annotations and image content. Recently, social media analysis has been investigated for image annotation. Inspired by the abundant social diffusion records of images in online social networks, we propose a novel image annotation approach based on social diffusion analysis. We present a common-interest model to interpret social diffusion, i.e. different images have different social diffusion routes due to the preferences of users, and such preferences are represented as common interests of pairwise users rather than personalized interests. We propose an image annotation framework that consists of learning of common interests, feature extraction from social diffusion records, and automatic annotation by learning to rank. Experimental results on a real-world dataset show that our proposed approach outperforms content-based and user-preference-based annotation methods.

关键词： Abstracts Vectors Positron emission tomography

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Hybrid transform for HEVC-based lossless coding

Hybrid transform for HEVC-based lossless coding

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IEEE International Symposium on Circuits and systems (ISCAS)

作者： Fangdong Chen Jinlei Zhang Houqiang Li CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei China

ISBN: (纸本)9781479934331

The High Efficiency Video Coding (HEVC) with the transform bypass mode is simple but inefficient for lossless coding. For this reason, we propose a novel transform to further eliminate the redundancy between residues of different blocks in intra prediction. Dependent on intra prediction modes, the proposed transform is adaptable to exploit correlations of residues formed by different modes. In order to accurately obtain parameters of the transform matrix, an approach similar to the Wiener filtering method is adopted. Experimental results show that on top of the lossless coding mode in HEVC, our method offers the performance with a 7.4% bit-rate reduction on average for All Intra Main configuration. Compared with other representative algorithms, our proposal still shows an improvement in the compression ratio, without substantial increases of computational complexity in the encoder or decoder.

关键词： Encoding Transforms Video coding Redundancy Prediction algorithms Proposals Standards

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