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3rd Sino-Foreign-Interchange Workshop on Intelligent Science and Intelligent Data Engineering, IScIDE 2012

作者： Wen, Jiajun Cui, Jinrong Lai, Zhihui Mi, Jianxun Bio-Computing Research Center Shenzhen Graduate School Harbin Institute of Technology Shenzhen China Key Laboratory of Network Oriented Intelligent Computation Shenzhen China

ISBN: (纸本)9783642366680

In the field of palmprint recognition, traditional classification methods such as PCA and LDA only exploit training samples to build the model of classifiers while ignoring the feedback of test sample during the process of recognition. In this paper, both types of samples will be taken into account to make an optimal representation of the test sample. We first exploit nearest neighbor principle to construct the initial optimal training sample set for representation. This optimal set will be updated by adding a training sample which works well with current optimal set to obtain the least representation error to the test sample. The sample selection step does not stop until we acquire the optimal set with sufficient number of training samples for classification. Comparative experiments have been conducted on PolyU multispectral palmprint database which validates the proposed method. Moreover, a study on parameter points out that a small number of selected training samples is good for recognition in blue and green channels while much more selected training samples are suitable for improving recognition in red channel. © Springer-Verlag 2013.

关键词： Palmprint recognition

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Multifractal analyses of daily rainfall time series in Pearl River basin of China

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Physica A: Statistical Mechanics and its Applications 2014年 405卷 193-202页

作者： Zu-Guo Yu Yee Leung Yongqin David Chen Qiang Zhang Vo Anh Yu Zhou Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan University Xiangtan Hunan 411105 China Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan Hunan 411105 China School of Mathematical Sciences Queensland University of Technology GPO Box 2434 Brisbane Q4001 Australia Department of Geography and Resource Management The Chinese University of Hong Kong Hong Kong China Institute of Environment Energy and Sustainability The Chinese University of Hong Kong Hong Kong China Department of Water Resources and Environment Sun Yat-sen University Guangzhou 510275 China Key Laboratory of Water Cycle and Water Security in Southern China of Guangdong High Education Institute Sun Yat-sen University Guangzhou 510275 China

The multifractal properties of daily rainfall time series at the stations in Pearl River basin of China over periods of up to 45 years are examined using the universal multifractal approach based on the multiplicative cascade model and the multifractal detrended fluctuation analysis (MF-DFA). The results from these two kinds of multifractal analyses show that the daily rainfall time series in this basin have multifractal behavior in two different time scale ranges. It is found that the empirical multifractal moment function K ( q ) of the daily rainfall time series can be fitted very well by the universal multifractal model (UMM). The estimated values of the conservation parameter H from UMM for these daily rainfall data are close to zero indicating that they correspond to conserved fields. After removing the seasonal trend in the rainfall data, the estimated values of the exponent h ( 2 ) from MF-DFA indicate that the daily rainfall time series in Pearl River basin exhibit no long-term correlations. It is also found that K ( 2 ) and elevation series are negatively correlated. It shows a relationship between topography and rainfall variability.

关键词： Daily rainfall time series Multifractal property Universal multifractal model Multifractal detrended fluctuation analysis

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Robust tensor clustering with non-greedy maximization

Robust tensor clustering with non-greedy maximization

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23rd International Joint Conference on Artificial Intelligence, IJCAI 2013

作者： Cao, Xiaochun Wei, Xingxing Han, Yahong Yang, Yi Lin, Dongdai Tianjin Key Laboratory of Cognitive Computing and Application School of Computer Science and Technology Tianjin University China School of Information Technology and Electrical Engineering University of Queensland Australia State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences China

ISBN: (纸本)9781577356332

Tensors are increasingly common in several areas such as data mining, computer graphics, and computer vision. Tensor clustering is a fundamental tool for data analysis and pattern discovery. However, there usually exist outlying data points in realworld datasets, which will reduce the performance of clustering. This motivates us to develop a tensor clustering algorithm that is robust to the outliers. In this paper, we propose an algorithm of Robust Tensor Clustering (RTC). The RTC firstly finds a lower rank approximation of the original tensor data using a L1 norm optimization function. Because the L1 norm doesn't exaggerate the effect of outliers compared with L2 norm, the minimization of the L1 norm approximation function makes RTC robust to outliers. Then we compute the HOSVD decomposition of this approximate tensor to obtain the final clustering results. Different from the traditional algorithm solving the approximation function with a greedy strategy, we utilize a non-greedy strategy to obtain a better solution. Experiments demonstrate that RTC has better performance than the state-ofthe- art algorithms and is more robust to outliers.

关键词： Tensors

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A hybrid model for grammatical error correction 17

A hybrid model for grammatical error correction

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17th Conference on Computational Natural Language Learning: Shared Task, CoNLL 2013

作者： Xiang, Yang Yuan, Bo Zhang, Yaoyun Wang, Xiaolong Zheng, Wen Wei, Chongqiang Intelligent Computing Research Center Key Laboratory of Network Oriented Intelligent Computation Computer Science and technology Department Harbin Institute of Technology Shenzhen Graduate School Shenzhen Guangdong518055 China

ISBN: (纸本)9781937284718

This paper presents a hybrid model for the CoNLL-2013 shared task which focuses on the problem of grammatical error correction. This year’s task includes determiner, preposition, noun number, verb form, and subject-verb agreement errors which is more comprehensive than previous error correction tasks. We correct these five types of errors in different modules where either machine learning based or rule-based methods are applied. Pre-processing and post-processing procedures are employed to keep idiomatic phrases from being corrected. We achieved precision of 35.65%, recall of 16.56%, F1 of 22.61% in the official evaluation and precision of 41.75%, recall of 20.29%, F1 of 27.3% in the revised version. Some further comparisons employing different strategies are made in our experiments. © 2013 Association for Computational Linguistics.

关键词： Error correction

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An Event-Driven Service-Oriented Architecture for the Internet of Things

An Event-Driven Service-Oriented Architecture for the Intern...

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IEEE Asia-Pacific Conference on Services computing (APSCC)

作者： Lina Lan Fei Li Bai Wang Lei Zhang Ruisheng Shi School of Network Education Beijing University of Posts and Telecommunications Beijing China Information Systems Institute Vienna University of Technology Vienna Austria Beijing University of Posts and Telecommunications Beijing Beijing CN School of Computer Beijing University of Posts and Telecommunications Beijing China Education Ministry Key Laboratory of Trustworthy Distributed Computing and Service Beijing University of Posts and Telecommunications Beijing China

IoT (Internet of Things) bridges the physical world and information space. IoT services are environment sensitive and event-driven. The new IoT service architecture should adapt to these features. This paper analyses IoT sensing service characteristics and proposes the future services architecture. It is focused on the middleware architecture and the interface presentation technology. In the middleware layer, the traditional SOA architecture is insufficient in the real-time response and parallel process of services execution, this paper proposes that the new sensing service system based on EDSOA (Event Driven SOA) architecture to support real-time, event-driven, and active service execution. At presentation layer, this paper presents the new IoT browser features including using augmented reality technology to input and output, and realize the superposition presentation of the physical world and abstract information. Through a use case and proof-of-concept implementation-road manhole covers monitoring system - we verify the feasibility of the proposed ideas and frameworks.

关键词： Service-oriented architecture Sensors Computer architecture Real-time systems Browsers Cameras

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Object coding on the semantic graph for scene classification 13

Object coding on the semantic graph for scene classification

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21st ACM International Conference on Multimedia, MM 2013

作者： Chen, Jingjing Han, Yahong Cao, Xiaochun Tian, Qi School of Computer Science and Technology Tianjin University China State Key Laboratory of Information Security Chinese Academy of Sciences China Tianjin Key Laboratory of Cognitive Computing and Application China Department of Computer Science University of Texas at San Antonio United States

ISBN: (纸本)9781450324045

In the scene classification, a scene can be considered as a set of object cliques. Objects inside each clique have semantic correlations with each other, while two objects from different cliques are relatively independent. To utilize these correlations for better recognition performance, we propose a new method - Object Coding on the Semantic Graph to address the scene classification problem. We first exploit prior knowledge by making statistics on a large number of labeled images and calculating the dependency degree between objects. Then, a graph is built to model the semantic correlations between objects. This semantic graph captures semantics by treating the objects as vertices and the objects affinities as the weights of edges. By encoding this semantic knowledge into the semantic graph, object coding is conducted to automatically select a set of object cliques that have strongly semantic correlations to represent a specific scene. The experimental results show that the Object Coding on semantic graph can improve the classification accuracy.,. Copyright © 2013 ACM.

关键词： Semantics

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Embedding change rate estimation based on ensemble learning 13

Embedding change rate estimation based on ensemble learning

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1st ACM Workshop on Information Hiding and Multimedia security, IH and MMSec 2013

作者： Li, Zhenyu Hu, Zongyun Luo, Xiangyang Lu, Bin State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou 450002 China Zhengzhou Institute of Information Science and Technology Zhengzhou 450002 China State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing 100093 China

ISBN: (纸本)9781450320818

In order to achieve higher estimation accuracy of the embedding change rate of a stego object, an ensemble learning-based estimation method is presented. First of all, a framework of embedding change rate estimation based on estimator ensemble is proposed. Then an algorithm of building the estimator ensemble, the core of the framework, is concretely described. Finally, a pruning method for estimator ensemble is proposed in consideration of both the diversity among the base estimators and accuracy of each of them. The experimental results for three modern steganographic algorithms (nsF5, PQ and PQt) indicate that the proposed method acquired better performance than the existed typical method. Furthermore, the pruned estimator ensemble with less base estimators maintained, even slightly improved the estimation accuracy, compared to the one without purning. © 2013 ACM.

关键词： Steganography

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Steganalysis of F5-like steganography based on selection of joint distribution features 13

Steganalysis of F5-like steganography based on selection of ...

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5th International Conference on Internet Multimedia computing and Service, ICIMCS 2013

作者： Liu, Yuan Luo, Xiangyang Lu, Jicang Gong, Daofu Zhengzhou Information Science and Technology Institute Zhengzhou 450001 China State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing 100093 China Zhengzhou Information Science and Technology Institute State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou 450001 China

ISBN: (纸本)9781450322522

For steganalysis of F5-like steganography with two types of widely used joint distribution statistical features: co-occurrence matrix and Markov transition probability matrix, a feature selection and fusion method based on separability comparison is proposed in this paper. Firstly, the changing ways of F5-like steganography to image data is analyzed. Then, according to different affecting ways of the changing to two types of features, the separability of each feature component is analyzed and compared. At last, based on the comparison conclusion, a new feature is obtained by selection and fusion. Experimental results show that, compared with existing typical features, the proposed new feature can achieve higher steganalytic accuracy and enhance the detection reliability. © 2013 ACM.

关键词： Steganography

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A model of three points for location estimation in wireless sensor networks

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2013 2nd International Symposium on Materials Science and Engineering technology, ISMSET 2013

作者： Xie, Shao Guo Hu, Yan Jun Wang, Yi Jiang, Fang Liu, Jing Jing Wang, Ying Guan Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education AnHui University Hefei China Key Laboratory of Wireless Sensor Network and Communication Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences 865 Changning Road Shanghai 200050 China

ISBN: (纸本)9783037858028

In this paper, we propose a novel model of three points named TP for location estimation in wireless sensor networks (WSNs) with random deployment of anchor nodes. In this model, we select three anchor nodes which have the strongest received signal strength (RSS) for location estimation, the centroid algorithm and the method of intersection of judgment are used to estimate the location of unknown nodes. To further exploit three nearest intersection points in TP, the enhanced TP (ETP) is proposed. The simulation results show that the proposed models outperform MMSE and BML in terms of the localization accuracy for WSNs. Moreover, the localization accuracy of the proposed models in scenario 2 with random deployment of anchor nodes are better than in scenario 1 with planned deployment of anchor nodes. Additionally, compared with MMSE and BML, ETP and TP can reduce the environmental impact on location estimation. © (2013) Trans Tech Publications, Switzerland.

关键词： Location

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Research on the degeneration problem of key sequence based on chaos

Research on the degeneration problem of key sequence based o...

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5th IEEE International Conference on Intelligent networking and Collaborative Systems, INCoS 2013

作者： Wang, Jing-Jing Wei, Ping Chen, Jia-Yong Key Laboratory of Network and Information Security of APF Department of Electronic Technology Engineering University of APF Xi'an 710086 China Laboratory-Center of Computer Department of Information Engineering Engineering University of APF Xi'an 710086 China Laboratory of Information and Network of APF Department of Information Engineering Engineering University of APF Xi'an 710086 China

ISBN: (纸本)9780769549880

In view of the degeneration problem of chaos characteristics of the secret-key sequences, a new key sequence generation system was designed, combining chaos and cryptography. The simulation results shows that, not only can the system generate its own parameters randomly, but also it can generate chaos secret-key sequences, which have the merits of long periodicity, great complexity and strong security, etc. © 2013 IEEE.

关键词： Cryptography

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