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检索条件"机构=The Key Laboratory of Intelligent Computing and Signal Processing"

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Improving product line architecture design and customization by raising the level of variability modeling 1

引用

12th International Conference on Software Reuse, ICSR 2011

作者： Zhu, Jiayi Peng, Xin Jarzabek, Stan Xing, Zhenchang Xue, Yinxing Zhao, Wenyun Shanghai Key Laboratory of Intelligent Information Processing Fudan University Shanghai China School of Computer Science Fudan University Shanghai China School of Computing National University of Singapore Singapore Singapore

ISBN: (数字)9783642213472

ISBN: (纸本)9783642213465

Product Line Architecture (PLA) plays a central role in software product line development. In order to support architecture-level variability modeling, most architecture description languages (ADLs) introduce architectural variation elements, such as optional component, connector and interface, which must be customized during product derivation. Variation elements are many, and design and customization of PLA at the level of individual variation elements are difficult and error-prone. We observed that developers usually perceive architecture variability from the perspective of variant features or variant design decisions that are mapped into groups of architecture variation elements. In the paper, we describe heuristics to identify configurations of variation elements that typically form such groups. We call them variation constructs. We developed an architecture variability management method and a tool that allow developers to work at the variation construct level rather than at the level of individual variation elements. We have applied and evaluated the proposed method in the development and maintenance of a medium-size financial product line. Our experience indicates that by raising variability modeling from variation element to construct level, architecture design and customizations become more intuitive. Not only does our method reduce the design and customization effort, but also better ensures consistent configuration of architectural variation elements, avoiding errors. © 2011 Springer-Verlag.

关键词： Computer software reusability

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MUSIZ: A generic framework for music resizing with stretching and cropping 11

MUSIZ: A generic framework for music resizing with stretchin...

引用

19th ACM International Conference on Multimedia ACM Multimedia 2011, MM'11

作者： Zhang, Liu Wang, Chaokun Ba, Yiyuan Wang, Hao Wang, Jianmin Department of Computer Science and Technology Tsinghua University China School of Software Tsinghua University Beijing 100084 China Tsinghua National Laboratory for Information Science and Technology China Key Laboratory for Information System Security Ministry of Education China Key Laboratory of Intelligent Information Processing Institute of Computing Technology CAS China

ISBN: (纸本)9781450306164

Content-aware music adaption, i.e. music resizing, in temporal constraints starts drawing attention from multimedia communities because of the need of real-world scenarios, e.g. animation production and radio advertisement production. The goal of music resizing is to change the length of a music track to a user preferred length using a series of basic operations, e.g. compression, prolonging, cropping and repeating. The only existing music resizing approach so far, called LyDAR, suffers from some limitations. For example, it cannot support prolonging a music track and cannot compress music pieces with very small stretch rates. In this paper, we propose MUSIZ, a generic framework for MUsic reSIZing. Observing the diversity of quality degradation for different segments, we propose the concept of stretch-resistance to measure the degree of quality degradation after a segment is stretched. MUSIZ stretches high stretch-resistance segments intensively and relieves low stretch-resistance segments to reduce the negative impact on the stretched music piece. For short length resizing requests, we develop a contiguity-preservative cropping algorithm to remove segments before stretching, while smoothing the abrupt change at the joint between two segments. Comprehensive experimental results show that MUSIZ is superior to the existing approaches. © 2011 ACM.

关键词： stretch-resistance music retargeting music resizing

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Study of millimetre-wave generation based on optical frequency multiplication

Study of millimetre-wave generation based on optical frequen...

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IET International Communication Conference on Wireless Mobile and computing, CCWMC 2011

作者： Ding, Yan Zhu, Jun Fang, Wei-Dong Ge, Xiao-Guang Chen, Xiang Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University No.3 Feixi Rd Hefei Anhui 230039 China Shanghai Research Center for Wireless Communications Information Building 1 lane 280 Linhong Rd China Shanghai University No. 149 Yanchang Rd Shanghai 200072 China

ISBN: (纸本)9781849195058

To meet the increasing capacity and mobility as well as decrease the costs in next-generation optical access networks, RoF technology is a promising technique in the emerging optical and wireless convergence network, mm-wave generation is a key technique to realize the convergence network. In this paper, existing optical mm-wave generation technologies are introduced, including direct modulation, optical heterodyning and external modulation. Associated with Shanghai University, a scheme based on Optical Frequency Multiplication employing a dual drive Mach-Zehnder Modulator (DD-MZM) is presented. The novel efficient technique does not require expensive high-frequency electrical equipment. Moreover, no optical filtering is used, which significantly reduces the cost.

关键词： Millimeter waves

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Cooperative Synthetic Aperture Radar Image Segmentation Using Learning Sparse Representation Based Clustering Scheme

Cooperative Synthetic Aperture Radar Image Segmentation Usin...

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International Workshop on Multi-Platform/Multi-Sensor Remote Sensing and Mapping

作者： Shuyuan Yang Junlin Zhu Zailin Hu Min Wang Licheng Jiao Institute of Intelligent Information Processing National Key Laboratory of Radar Signal Processing Department of Electrical Engineering Xidian University Xi'an China

Based on a recent proposed and popular sparse representation based classifier (SRC), in this paper we presented a novel Learning Sparse Representation based Clustering (LSRC) scheme for Synthetic Aperture Radar (SAR) segmentation. LSRC introduces the examples-based dictionary learning technology in SRC to find a dictionary that is adaptable to sparsely representing samples, which is liable to provide more accurate approximation of samples and subsequently achieve higher classification accuracy rate. Moreover, for the intrinsic supervised nature of LSRC, we adopt an unsupervised-clustering cooperative approach to provide training samples for LSRC, in which some "good" samples with higher membership degrees are selected from the clustering result of K-means algorithm. Some experiments are taken on segmentation of both the texture images and SAR images to investigate the performance of our proposed method, and the results prove its superiority to its counterparts.

关键词： Dictionaries Image segmentation Classification algorithms Clustering algorithms Training Pixel Synthetic aperture radar

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Novel Super Resolution Restoration of Remote Sensing Images Based on Compressive Sensing and Example Patches-Aided Dictionary Learning

Novel Super Resolution Restoration of Remote Sensing Images ...

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International Workshop on Multi-Platform/Multi-Sensor Remote Sensing and Mapping

作者： Shuyuan Yang Fenghua Sun Min Wang Zhizhou Liu Licheng Jiao Institute of Intelligent Information Processing National Key Laboratory of Radar Signal Processing Department of Electrical Engineering Xidian University Xi'an China

A novel machine learning and compressive sensing (CS) based super-resolution (SR) algorithm for the restoration of remote sensing images is proposed in this paper. This new algorithm relies on the idea that high-resolution (HR) image patches can be correctly recovered from the downsampled low-resolution (LR) image patches under two mild conditions, i.e., the sparsity of image patches, and the incoherence between the sensing and projection matrix. Consequently if most of HR image patches can be represented as a sparse linear combination of elements from a dictionary that is incoherent with sensing matrix, the HR image patches can be recovered accurately from its LR version. To find a dictionary which can sparsely represent HR image patches to guarantee the reconstruction error over a set of patches be minimal, an example patches-aided dictionary learning algorithm named KSVD algorithm is adopted. Moreover, the incoherence between the learned dictionary and sensing matrix is experimentally investigated. The new proposed method is tested on the restoration of remote sensing images came from USC-SIPI Image Database, and the results show that the proposed algorithm can provide substantial improvement in resolution of remote sensing images, and the restored images are superior in quality to that of other related methods.

关键词： Dictionaries Remote sensing Image restoration Image reconstruction PSNR Spatial resolution

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High Resolution Radar Imaging Based on Compressed Sensing and Fast Bayesian Matching Pursuit

High Resolution Radar Imaging Based on Compressed Sensing an...

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International Workshop on Multi-Platform/Multi-Sensor Remote Sensing and Mapping

作者： Min Wang Shuyuan Yang Yanyan Wan Jing Wang Institute of Intelligent Information Processing National Key Laboratory of Radar Signal Processing Department of Electrical Engineering Xidian University Xi'an China

Recently the rapid imaging based on the compressive sensing (CS) theory have attracted increasing interests, which simultaneously sampling and compressing signals or images. Radar imaging based CS is a potential way to obtain the high-resolution radar images without the constraint of Nyquist sampling rate. In this paper, we proposed a radar remote-sensing imaging approach based on compressive sensing and fast Bayesian matching pursuit (FBMP) recovery algorithm. Some experiments are taken and the results indicate that an accurate reconstruction of high-resolution radar images are obtained, with fewer measurements than most its counterparts(e.g., MP, OMP, StOMP, GPSR),but resulting in lower normalized MSE(NMSE). Although BCS obtains lower NMSE than FBMP,simultaneously with higher time complexity and sparsity.

关键词： Radar imaging Matching pursuit algorithms Compressed sensing Imaging Image reconstruction Bayesian methods

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Multitask Learning and Sparse Representation Based Super-Resolution Reconstruction of Synthetic Aperture Radar Images

Multitask Learning and Sparse Representation Based Super-Res...

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International Workshop on Multi-Platform/Multi-Sensor Remote Sensing and Mapping

作者： Shuyuan Yang Zhizhou Liu Min Wang Fenghua Sun Licheng Jiao Institute of Intelligent Information Processing National Key Laboratory of Radar Signal Processing Department of Electrical Engineering Xidian University Xi'an China

In earth observing remote sensing fields, to recognize objects whose size approaches the limiting spatial resolution scale especially in Synthetic Aperture Radar (SAR) images, spatial resolution enhancement is usually required. In this paper, we proposed a multi-task learning and K-SVD based Superresolution image restoration method where K-SVD algorithm is employed to learn a redundant dictionary from some example image patches. In order to learn more accurate dictionary and reduce the complexity of dictionary learning, multitask learning concept is adopted to learn multiple dictionaries from the samples classified by K-means clustering. Some experiments are taken to investigate the performance of our proposed method, and the visual result and numerical guidelines both prove its superiority to some start-of-art SRIR methods.

关键词： Dictionaries Image reconstruction Training signal resolution Optimization Spatial resolution

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Dual form back propagation on the EM algorithm

Dual form back propagation on the EM algorithm

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IEEE International Conference on Granular computing (GRC)

作者： Hong Hu Zhongzhi Shi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

Vladimir N. Vapnik. (1998) pointed out that maxlikelihood functions in EM algorithms are just a special risk function. Based on this opinion, a novel EM algorithm uses a risk function differ with maxlikelihood functions, in stead, a risk formula based on the least square method is used. The gradient descending approach should be used in such kind approaches. Such kind EM algorithms can estimate the parameters of a random model from both labeled and unlabeled samples, and are suitable for semi-supervised learning.

关键词： Gaussian distribution Error analysis Maximum likelihood estimation Least squares methods Information processing Laboratories

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DETECTING OPERATIONS THAT POTENTIALLY VIOLATE WELL-FORMEDNESS CONSTRAINTS FOR METADATA REPOSITORY SYSTEMS

DETECTING OPERATIONS THAT POTENTIALLY VIOLATE WELL-FORMEDNES...

引用

2011 IEEE International Conference on Cloud computing and Intelligence Systems(2011年第一届IEEE云计算与智能系统国际会议 IEEE CCIS2011)

作者： Xiaofei Zhao Zhongzhi Shi The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

The organization of the metadata in repository systems exhibits a complex structure which is layered, multi-level and dynamically adaptable;the validating of well-formedness constraints is insufficiently specified in existing repository system standard, the above two reasons make it becomes a major challenge how to validate well-formedness constraints for MOF-based metadata repository systems. In this paper we propose a method to automatically detect the operations that may potentially violate a well-formedness constraint in the meta-level. Our approach can detect potentially violating operations by determining the construction actions that may violate the constraint and checking whether those actions appear in the operation specification. Our approach helps to improve efficiency of well-formedness constraint checking since its results can be used to discard many irrelevant tests.

关键词： Repository System Meta Object Facility(MOF) Well-Formedness Constraint Construction Action Internal Action

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An Orientation Model for Hierarchical Phrase-Based Translation

An Orientation Model for Hierarchical Phrase-Based Translati...

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International Conference on Asian Language processing (IALP)

作者： Xinyan Xiao Jinsong Su Yang Liu Qun Liu Shouxun Lin Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

The hierarchical phrase-based (HPB) translation exploits the power of grammar to perform long distance reorderings, without specifying nonterminal orientations against adjacent blocks or considering the lexical information covered by nonterminals. In this paper, we borrow from phrase-based system the idea of orientation model to enhance the reordering ability of HPB translation. We distinguish three orientations (monotone, swap, discontinuous) of a nonterminal based on the alignment of grammar, and select the appropriate orientation of nonterminal using lexical information covered by it. By incorporating the orientation model, our approach significantly outperforms a standard HPB system up to 1.02 Bleu on large scale NIST Chinese-English translation task, and 0.51 Bleu on WMT German-English translation task.

关键词： Training Mathematical model Grammar Frequency estimation Probability Equations Entropy

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