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2010 6th International Conference on Natural Computation, ICNC'10

作者： Zhang, De-Gan Li, Chao Wang, Dong Zhang, Xiao-Li Tianjin Key Lab. of Intelligent Computing and Novel Software Technology Tianjin University of Technology 300191 China Key Laboratory of Computer Vision and System Tianjin University of Technology Ministry of Education 300191 China

ISBN: (纸本)9781424459612

The image data are obtained by a variety of multimedia, information equipment, which include amount of information, extensive coverage, and redundancy in ubiquitous computing paradigm. In order to make use of these information reasonably and efficiently, it is necessary to fuse such massive data, therefore the multi-sensor image information fusion become a key technology to ubiquitous computing. A new approach of image data fusion based on fuzzy neural network (FNN) is presented in this paper. Here, neural network is a parallel information processing model, there are more adaptive and self-organization, and can accomplish the complexity of real-time computing and mass data retrieval, it demonstrate its unique superiority of image understanding, pattern recognition and the handling of incomplete information. In the new approach, fuzzy theory has the advantages such as: easy-to-understand, flexible and inclusive of non-precise data, as well as using expert knowledge and based on the natural language. The fuzzy neural network system developed by us has used in multi-sensor image fusion, proved that the fusion is fast, effective, good, and can meet the real-time requirements of ubiquitous computing. ©2010 IEEE.

关键词： Fuzzy neural networks

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A clustering algorithm use SOM and K-Means in Intrusion Detection

A clustering algorithm use SOM and K-Means in Intrusion Dete...

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International Conference on E-Business and E-Government (ICEE)

作者： Wang, Huai-Bin Yang, Hong-Liang Xu, Zhi-Jian Yuan, Zheng Tianjin Key Lab. of Intelligent Computing and Novel Software Technology Tianjin University of Technology 300191 Tianjin China Key Laboratory of Computer Vision and System Ministry of Education 300191 Tianjin China Key Laboratory of Computer Vision and System Ministry of Education China

ISBN: (纸本)9780769539973

Improving detection definition is a pivotal problem for intrusion detection. Many intelligent algorithms were used to improve the detection rate and reduce the false rate. Traditional SOM cannot provide the precise clustering results to us, while traditional K-Means depends on the initial value serious and it is difficult to find the center of cluster easily. Therefore, in this paper we introduce a new algorithm, first, we use SOM gained roughly clusters and center of clusters, then, using K-Means refine the clustering in the SOM stage. At last of this paper we take KDD CUP-99 dataset to test the performance of the new algorithm. The new algorithm overcomes the defects of traditional algorithms effectively. Experimental results show that the new algorithm has a good stability of efficiency and clustering accuracy. © 2010 IEEE.

关键词： Self organizing maps

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A pervasive service discovery strategy based on peer to peer model

A pervasive service discovery strategy based on peer to peer...

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作者： Zhang, De-Gan Chen, Xu-Yan Li, Chao Li, Lin-Qing Tianjin Key Lab of Intelligent Computing and Novel Software Technology Tianjin University of Technology 300191 China Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology 300191 China

ISBN: (纸本)9780955529337

In order to improve the efficiency of service discovery in the pervasive environment, this paper presents a new strategy of service discovery based on p2p network model. Reference the ring topology of chord algorithm and tbe algorithm used by DDT, tbe traditional single finger-table witch be maintained by each node in the ring will be changed into double finger-table: the Neigbbor-Finger-Table and Long-distance Finger-Table. The structure of the Neighbor-Finger-Table is the same as the traditional single finger-table's. The Long-distance Finger-Table can construct small-world network. Some similar algorithm uses random method to select remote access node, the new strategy is different from that, tbrough tbe calculation of the local node, it can ensure the scope of service can cover tbe entire network. The simulation shows the algorithm can effectively reduce the path length of service discovery, improve the service success rate, and control the path length of magnitude.

关键词： Small-world networks

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A new method for image fusion based on fuzzy neural network

A new method for image fusion based on fuzzy neural network

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作者： Zhang, De-Gan Wang, Yuan-Yuan Liu, Wei-Wei Zhang, Xiao-Li Tianjin Key Lab of Intelligent Computing and Novel Software Technology Tianjin University of Technology 300191 China Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology 300191 China

ISBN: (纸本)9780955529337

In pervasive computing paradigm, the image data obtained by a variety of multimedia, information equipment. In order to make use of these information reasonably and efficiently, a new method for image fusion based on fuzzy neural network has presented in this paper. It can fuse massive data from the multi-sensor image. Here, fuzzy neural network is a paraDel information processing model, there are more adaptive and self-organization, and can accomplish the complexity of real-time computing and mass data retrieval, it demonstrate its unique superiority of image understanding, pattern recognition and the handling of incomplete information. The fuzzy neural network system developed by us can be used in multi- sensor image fusion. Based on our experiments, it has been proved that the fusion is fast, effective, and can meet the real-time requirements of pervasive computing.

关键词： Fuzzy neural networks

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Vector-valued Chan-Vese model driven by local histogram for texture segmentation

Vector-valued Chan-Vese model driven by local histogram for ...

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IEEE International Conference on Image Processing

作者： Yuanquan Wang Yue Xiong Liping Lv Hua Zhang Zuoliang Cao Degan Zhang Tianjin Key Laboratory of Intelligent Computing and Novel Software Technology Tianjin University of Technology Tianjin China

The Chan-Vese model is one of the most popular region-based active contours, and its vector-valued extension is also powerful for multichannel images. Very recently, the histogram is introduced into the Chan-Vese model due to the effectiveness of histogram to model region information. Motivated by the fact that the histogram is also a powerful tool to characterize texture, it is introduced into the vector-valued Chan-Vese model for texture segmentation in this work. In order to determine an optimal number of bins in the histogram, a Bayesian method is adopted. Experiments are conducted and the results show that the proposed strategy is effective for texture segmentation.

关键词： Histograms Active contours Image segmentation Image edge detection Computational modeling Filter bank Computer vision

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A new method for image fusion based on fuzzy neural network

A new method for image fusion based on fuzzy neural network

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International Conference on Modelling, Identification and Control (ICMIC)

作者： De-gan Zhang Yuan-yuan Wang Wei-wei Liu Xiao-li Zhang Tianjin Key Lab of Intelligent Computing & Novel software Technology Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology China

In pervasive computing paradigm, the image data obtained by a variety of multimedia, information equipment. In order to make use of these information reasonably and efficiently, a new method for image fusion based on fuzzy neural network has presented in this paper. It can fuse massive data from the multi-sensor image. Here, fuzzy neural network is a parallel information processing model, there are more adaptive and self-organization, and can accomplish the complexity of real-time computing and mass data retrieval, it demonstrate its unique superiority of image understanding, pattern recognition and the handling of incomplete information. The fuzzy neural network system developed by us can be used in multi-sensor image fusion. Based on our experiments, it has been proved that the fusion is fast, effective, and can meet the real-time requirements of pervasive computing.

关键词： Image resolution Annealing Weight measurement Adaptation model Gain measurement

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Tunnel morph model for time frequency bio-signal waveform processing

Tunnel morph model for time frequency bio-signal waveform pr...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Gang Zheng Shiliu Lian Shanling Mou Jia Qi Laboratory of Biological Signal and Intelligent Processing Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology Tianjin China Tianjin University of Technology Tianjin CN China

In this paper, we proposed a tunnel morph model for bio-signal waveform in measuring their similarity. Firstly, the formal specifications of bio-signal waveforms are given. And then, a series of model establishing related definitions are presented. These definitions contain waveform segmentation; waveforms distance measurement, and tunnel width computation. Moreover, on the base of the model, a similarity measuring strategy which takes the curve feature of bio-signal into account was presented. In the end, the strategy was compared with other similarity measurement methods by AECG (Ambulatory Electrocardiogram) waveform data. The data are adopted from MIT/BIH arrhythmia database. Experiment results show that the sensitivity and the positive predictivity of the strategy based on tunnel morph model are prior to other strategies.

关键词： Electrocardiography Equations Biological system modeling Correlation Sensitivity Mathematical model

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A novel epidemic model with transmission medium on complex networks

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ICIC Express Letters 2010年第5 B期4卷 1785-1790页

作者： Xia, Chengyi Ma, Junhai Chen, Zengqiang School of Management Tianjin University Tianjin 300072 China Tianjin Key Laboratory of Intelligent Computing and Novel Software Technology Tianjin University of Technology Tianjin 300191 China Department of Automation Nankai University Tianjin 300071 China

Based on the susceptible-infective-removed-susceptible (SIRS) compartmental model, a novel epidemic model with transmission medium is proposed to investigate the role of infective media in epidemic spreading on complex networks. The mean-field analysis and numerical simulation both indicate that the infective media can greatly reduce the infection threshold on heterogeneous and homogeneous networks. These results are helpful for us to prevent the epidemic outbreaks and design some feasible containment strategies. © 2010 ICIC International.

关键词： Epidemiology

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Application of multidimensional association rule techniques in manufacturing resource planning system

Application of multidimensional association rule techniques ...

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Fayu Wang Key Laboratory of Computer Vision and System Ministry of Education Ministry of Education Tianjin China Tianjin Key Lab of Intelligent Computing & Novel Software Technology Tianjin university of technology Tianjin China

Association rules mining is a popular and well researched method in data mining research field , its purpose is to mine interesting relations between attributes in transaction database. Classic Apriori algorithm is one of the most influential association rules in mining boolean frequent itemsets algorithms, However, it has some disadvantages such as inefficient in generating candidate itemsets and frequently scanning database, it is not suitable for mining multiple dimensional data model which rise in recent years. A “second cut” method is proposed, which is on the basis of the Apriori algorithm. The algorithm applies to multidimensional mining association rules, and to some extent improved the efficiency of the algorithm. Referring to the manufacturing resource planning system (MRP) features of the retail points, the article sets up the sales association analysis data model based on the above algorithm. It proves that it can increase the sales dramatically by applying this methodology to the real business environment.

关键词： Association rules Itemsets Algorithm design and analysis Manufacturing Planning

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Research on face detection based on combination of Haar and skin colors features

Research on face detection based on combination of Haar and ...

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Congress on Image and Signal Processing, CISP

作者： Fayu Wang Baokun Qi Yong Xing Baoan Lu Tianjin Key Laboratory of Intelligent Computing & Novel Software Technology Tianjin University of Technology Tianjin China Key Laboratory of Computer Vision and System(TUT) Ministry of Education Tianjin University of Technology Tianjin P. R China 300191

Face detection and recognition is a hot research subject in the fields of image processing, pattern recognition and computer vision, which emphasize on the enhancement of the precision of detection in as short a time as possible. This paper expounds on how to detect human faces accurately from complex pictures by means of the technology of judgement based on the combination of the feature of Haar and the features of skin colors, and depicts in detail the principles and methods of detection. By the combination of the two methods, we can draw on each other's strength and promote the performance of the algorithm. It has been justified by experiments that this algorithm can produce better detection result, and, for other machinery vision application systems, it is of high value to make use of it as reference.

关键词： Image color analysis Skin Face detection Feature extraction Face Humans Pixel

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