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20th ACM International Conference on Multimedia, MM 2012

作者： Zhou, Rong Chen, Liuli Zhang, Liqing MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781450310895

We propose a real-time image retrieval system which allows users to search target images whose objects are similar to the query in contour, regardless of their sizes and positions appearing in the images. Even in a complicated scene, as long as the object's contour is most salient in the target image, the system is still able to capture it and lists the image in the retrieval results. Therefore, the system has better retrieval rate than existing systems and algorithms. One typical application of the proposed system is to help the computer understand what does the user draw or upload. It is based on the statistical distributions of tags of retrieved images, and the proposed system feeds back some candidate tags related to the query image. Such tags could be used for further retrieval to refine the result list. In addition, the system provides a friendly interactive interface with multiple queries. These queries are from different combinations of tags, a hand-drawn sketch and a natural image, and could help users search images flexibly and conveniently. The system runs on a database of 1.3 million images and could achieve a real-time retrieval speed. The results in the demonstration show excellent retrieval performance of the proposed system. © 2012 Authors.

关键词： Search engines

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An Ant Colony System Algorithm for The Problem of Server Consolidation in Virtualized Data Centers

An Ant Colony System Algorithm for The Problem of Server Con...

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2012年全国理论计算机科学学术年会(NCTCS2012)

作者： Yongqiang Gao Haibing Guan Zhengwei Qi Shanghai Key Laboratory of Scalable Computing and Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China Shanghai Key Laboratory of Scalable Computing and Systems Department of Computer Science and Engineering Shanghai Jiao Tong University

e problem of server sprawl is common in today's data ***-based server consolidation is a vital mechanism to solve the server sprawl problem in modern data centers by consolidating multiple virtualized servers ...

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IncMR: Incremental data processing based on MapReduce

IncMR: Incremental data processing based on MapReduce

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2012 IEEE 5th International Conference on Cloud computing, CLOUD 2012

作者： Yan, Cairong Yang, Xin Yu, Ze Li, Min Li, Xiaolin Department of Computer Science and Technology Donghua University Shanghai China Scalable Software Systems Laboratory University of Florida FL United States

ISBN: (纸本)9780769547558

MapReduce programming model is widely used for large scale and one-time data-intensive distributed computing, but lacks flexibility and efficiency of processing small incremental data. IncMR framework is proposed in this paper for incrementally processing new data of a large data set, which takes state as implicit input and combines it with new data. Map tasks are created according to new splits instead of entire splits while reduce tasks fetch their inputs including the state and the intermediate results of new map tasks from designate nodes or local nodes. Data locality is considered as one of the main optimization means for job scheduling. It is implemented based on Hadoop, compatible with the original MapReduce interfaces and transparent to users. Experiments show that non-iterative algorithms running in MapReduce framework can be migrated to IncMR directly to get efficient incremental and continuous processing without any modification. IncMR is competitive and in all studied cases runs faster than that processing the entire data set. © 2012 IEEE.

关键词： MapReduce

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ECG classification based on non-cardiology feature 1

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9th International Symposium on Neural Networks, ISNN 2012

作者： Huang, Kai Zhang, Liqing Wu, Yang MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (数字)9783642313622

ISBN: (纸本)9783642313615

As for ECG auto-diagnosis, Classification accuracy is a vital factor for providing diagnosis decision support in remote ECG diagnosis. The final accuracy depends on ECG preprocessing process, feature extraction, feature selection and classification. However, different heart diseases are with different ECG wave shapes, in addition, there is large numbers of heart diseases, so it is hard to accurately extract cardiology features from diverse ECG wave forms. Also the extracted cardiology features are always with large error which to some extent influence the classification accuracy. To deal with these problems, we propose a feature extraction method of PCA and ICA approach. We calculate a adaptive basis with ICA and PCA for the given disease type ECG and extract the coefficients in the respect of trained basis which will be used as the classification features combined with cardiology features. To prevent the dimension disaster problem brought by the additional ICA and PCA feature, a minimal redundancy maximal relevance feature selection method is adapted to reduce the dimension of feature vector. Experiment shows that our method can effectively exclude the influence of not accurate cardiology features and greatly improve the classification accuracy for heart diseases. © 2012 Springer-Verlag.

关键词： Electrocardiograms

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On the Security of Double-Block-Length Hash Functions with Rate 1

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电子学报(英文版) 2012年第3期21卷 566-570页

作者： GONG Zheng LUO Yiyuan LAI Xuejia CHEN Kefei School of Computer Science South China Normal University Guangzhou 510631 China Department of Computer Science Shanghai Jiaotong University Shanghai 200240 China Shanghai Key Laboratory of Scalable Computing and Systems Shanghai China

The security of double-block-length hash functions with rate 1, which are based on a block cipher with a block length of n bits and a key length of 2n bits, was analyzed by Satoh et al. and Hirose. In this paper, we reconsider the security of this general class of hash functions (named FDBL-II for brevity). The new counter-examples and attacks are presented on FDBL-II, which reveal some flaws in the necessary conditions proposed by Satoh et al. and Hirose. Moreover, our analysis shows that all rate-1 hash functions in FDBL-II fail to be optimally (second) preimage resistant. Finally, the necessary conditions are revised for ensuring that a subclass of hash functions in FDBL-II can be optimally secure against collision attacks.

关键词：安全性分析密钥长度 Hash函数安全散列函数汇率碰撞攻击块密码比特

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EMP: Exploiting Mobility Patterns for Collaborative Localization in Sparse Mobile Networks

EMP: Exploiting Mobility Patterns for Collaborative Localiza...

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International Conference on Mobile Ad-hoc and Sensor Networks, MSN

作者： Zhenzhen Tian Yanmin Zhu Shanghai Key Laboratory of Scalable Computing and Systems Department of Computer Science and Engineering Shanghai Jiaotong University China

ISBN: (纸本)9781467358088

Location awareness plays an indispensable role in a wide variety of application domains such as environment monitoring, and vehicle tracking. In this paper we focus on the localization of mobile users in sparse mobile networks which exist in many practical scenarios where users are distributed over a vast area. The unique characteristics of sparse mobile networks present several challenges for accurate localization, such as constant movement and little information from anchors. By analyzing five large datasets of real users traces with entropy analysis from five sites, we make an important observation that there is strong patterns with user mobility. Motivated by this observation, we propose a localization approach called EMP by exploiting mobility patterns of users for localization in sparse mobile networks. EMP implements a range-free distributed algorithm, with which each user collaboratively estimates its current location by fusing two localization sources, i.e., network connectivity with other nodes and mobility patterns. With trace driven simulations, we demonstrate that EMP significantly improves the localization accuracy, comparing with other existing localization approaches.

关键词： Mobility Patterns Collaborative Localization Sparse Mobile Networks electromagnetic pulses mobile networking Consumers Location awareness environmental monitoring Current Position Boat anchors

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EEG-based emotion recognition in listening music by using support vector machine and linear dynamic system 1

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19th International Conference on Neural Information Processing, ICONIP 2012

作者： Duan, Ruo-Nan Wang, Xiao-Wei Lu, Bao-Liang Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China MOE Key Laboratory of Systems Biomedicine Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China

ISBN: (数字)9783642344787

ISBN: (纸本)9783642344770

This paper focuses on the variation of EEG at different emotional states. We use pure music segments as stimuli to evoke the exciting or relaxing emotions of subjects. EEG power spectrum is adopted to form features, power spectrum, differential asymmetry, and rational asymmetry. A linear dynamic system approach is applied to smooth the feature sequence. Minimal-redundancy-maximal-relevance algorithm and principal component analysis are used to reduce the dimension of features. We evaluate the performance of support vector machine, k-nearest neighbor classifiers and least-squares classifiers. The accuracy of our proposed method reaches 81.03% on average. And we show that the frequency bands, beta and theta, perform better than other frequency bands in the task of emotion recognition. © 2012 Springer-Verlag.

关键词： Emotion Recognition

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Decidability of behavioral equivalences in process calculi with name scoping

Decidability of behavioral equivalences in process calculi w...

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4th IPM International Conference on Fundamentals of Software Engineering, FSEN 2011

作者： He, Chaodong Fu, Yuxi Fu, Hongfei BASICS Department of Computer Science Shanghai Jiao Tong University Shanghai 200240 China MOE-MS Key Laboratory for Intelligent Computing and Intelligent Systems China

ISBN: (纸本)9783642293191

Local channels and their name scoping rules play a significant role in the study of the expressiveness of process calculi. The paper contributes to the understanding of the expressiveness in the context of CCS by studying the decidability issues of the bisimilarity/similarity checking problems. The strong bisimilarity for a pair of processes in the calculi with only static local channels is shown Π10-complete. The strong bisimilarity between those processes and the finite state processes is proved decidable. The strong similarity between the finite state processes and the processes without name-passing capability is also shown decidable. © 2012 Springer-Verlag.

关键词： Computability and decidability

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Online vigilance analysis combining video and electrooculography features

Online vigilance analysis combining video and electrooculogr...

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19th International Conference on Neural Information Processing, ICONIP 2012

作者： Du, Ruo-Fei Liu, Ren-Jie Wu, Tian-Xiang Lu, Bao-Liang Center for Brain-like Computing and Machine Intelligence Department of Computer Science and Engineering Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China MOE-Microsoft Key Lab. for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China MOE Key Laboratory of Systems Biomedicine Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China

ISBN: (纸本)9783642344992

In this paper, we propose a novel system to analyze vigilance level combining both video and Electrooculography (EOG) features. For one thing, the video features extracted from an infrared camera include percentage of closure (PERCLOS) and eye blinks, slow eye movement (SEM), rapid eye movement (REM) are also extracted from EOG signals. For another, other features like yawn frequency, body posture and face orientation are extracted from the video by using Active Shape Model (ASM). The results of our experiments indicate that our approach outperforms the existing approaches based on either video or EOG merely. In addition, the prediction offered by our model is in close proximity to the actual error rate of the subject. We firmly believe that this method can be widely applied to prevent accidents like fatigued driving in the future. © 2012 Springer-Verlag.

关键词： Eye movements

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EEG-based fatigue classification by using parallel hidden Markov model and pattern classifier combination 1

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19th International Conference on Neural Information Processing, ICONIP 2012

作者： Sun, Hui Lu, Bao-Liang Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China MOE-Microsoft Key Lab. for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China MOE Key Laboratory of Systems Biomedicine Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China

ISBN: (数字)9783642344787

ISBN: (纸本)9783642344770

Fatigue is the most important reason leading to traffic accidents. In order to ensure traffic safety, various methods based on electroencephalogram (EEG) are proposed. But most of them, either regression or classification, are focused on the relationship between feature space and observation values, so the changing patterns of features are ignored or discarded. In this paper, we propose a new fatigue classification method by using parallel hidden-Markov-model and pattern classifier combination techniques, where each model represents a particular fatigue-high-related feature. In the experiment, subjects are asked to accomplish some simple tasks, and both their fatigue states and their EEG signals are recorded simultaneously. Experimental results indicate that the mean error rate obtained by using our new method are 11.15% for classifying 3 states and 16.91% for classifying 4 states, respectively, while the existing approach can only reach 16.45% and 23.55% under the same condition. © 2012 Springer-Verlag.

关键词： Electroencephalography

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