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	1. IMAGE APPLICATION OF PHOTO-MOSAIC
	wenxiu wang
	Computer Science and Technology 11 January 2008
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	Abstract:Photo Mosaic is an exciting art form made from thousands of small pictures, placed in patterns like original mosaics made from colored cells, but each cell is an actual photo. This application is a little program for to create mosaic made with photos with two different algorithms, one is Mean-Variance and another one is Cauchy-Schwarz Inequality.
	TO cite this article:wenxiu wang. IMAGE APPLICATION OF PHOTO-MOSAIC[OL].[11 January 2008] http://en.paper.edu.cn/en_releasepaper/content/18019


	2. Computerized Feature Quantization of Sublingual Vein Based on Color Information
	Zifei Yan,Kuanquan Wang,Naimin Li
	Computer Science and Technology 07 January 2008
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	Abstract:Characteristics of tongue pose the most important information for Traditional Chinese Medicine diagnosis. So far, extensive studies have been made on extracting tongue surface features, but rarely refer to sublingual vein that is also diagnostically important. This paper focuses on establishing a feature quantization framework for the inspection of sublingual veins, composed of two parts: the segmentation of sublingual veins and the feature quantization of them. Adaptive sublingual vein segmentation algorithm and pixel-based sublingual vein segmentation algorithm for sublingual images with low contrast and visible contrast are proposed respectively. The experiments prove that the proposed methods perform well on the segmentation of sublingual images with both low contrast and visible contrast between sublingual veins and tongue proper. And then, a chromatic system in conformity with diagnostic standard of Traditional Chinese Medicine doctors is established to describe the chromatic feature of sublingual veins. Experimental results show that the distance and chromatic features quantized by the proposed framework are properly consistent with the diagnostic standard summarized by TCM doctors.
	TO cite this article:Zifei Yan,Kuanquan Wang,Naimin Li. Computerized Feature Quantization of Sublingual Vein Based on Color Information[OL].[ 7 January 2008] http://en.paper.edu.cn/en_releasepaper/content/17795

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	3. Sublingual Vein Segmentation Based on Color Features
	Zifei Yan,Kuanquan Wang,Naimin Li
	Computer Science and Technology 06 January 2008
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	Abstract:The Sublingual Vein Diagnosis, one part of Tongue Diagnosis, plays an important role in deciding the healthy condition of humans. So far, extensive studies have been made on extracting tongue surface features, but rarely refer to sublingual vein that is also diagnostically important. This paper presents two approaches to segment the sublingual veins taking the color features of sublingual images into consideration. Experimental results show that, sublingual vein structures can been successfully mapped for 129 out of 150 patients and healthy subjects, when utilizing u component and S component for segmentation, and the average segmentation rate is up to 86%.
	TO cite this article:Zifei Yan,Kuanquan Wang,Naimin Li. Sublingual Vein Segmentation Based on Color Features[OL].[ 6 January 2008] http://en.paper.edu.cn/en_releasepaper/content/17785


	4. An Improved Aggregated One-Dependence Estimator:On Not So Rigid Cross Validation
	Zheng Qinghua
	Computer Science and Technology 06 January 2008
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	Abstract:1The naive Bayesian classifier is a simple and effective approach to classifier learning. However, its conditionally independent assumption doesn’t often hold in the real world and this will lead to accuracy decrease in some applications. LBR, TAN and AODE are several representative algorithms that seek to relax this assumption and have exhibited noticeable prediction performance. However, the computational cost of LBR and TAN is considerable. AODE is creditably an effective classification learning algorithm without increasing computational cost improperly. However, to intently debase computational complexity, AODE avoids model selection and adopts all SPODEs , this may result in insufficiency to improve the prediction accuracy because of the included SPODEs which bring negative effect. Therefore, we propose an improved algorithm in this paper which will improve classification accuracy and classification speed by filtering out those SPODEs which bring negative effect base on original algorithms.
	TO cite this article:Zheng Qinghua . An Improved Aggregated One-Dependence Estimator:On Not So Rigid Cross Validation[OL].[ 6 January 2008] http://en.paper.edu.cn/en_releasepaper/content/17765


	5. Domain Ontology-based Navigation Learning System
	Zheng Qinghua ,Wang Yanye ,Huang Zhibin
	Computer Science and Technology 04 January 2008
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	Abstract:This paper focuses on the design and prototype of domain ontology-based navigation learning system, which can guide the user to learn more efficient. In this system, a navigation structure is built among concepts. So the users can understand what they want to know, and see the knowledge related to what they want to know. It will give the users strategic view of their learning and avoid getting lost in too much information. This system also includes a web answer system based on natural language, to answer the questions of the learners in time. Ontology is introduced as a mechanism for the establishment of domain knowledge library. At last, a way on how to extract concepts and relationship between them using the machine learning method is presented.
	TO cite this article:Zheng Qinghua ,Wang Yanye ,Huang Zhibin . Domain Ontology-based Navigation Learning System[OL].[ 4 January 2008] http://en.paper.edu.cn/en_releasepaper/content/17752


	6. Research on E-learner Personality Grouping Based on Fuzzy Clustering Analysis
	Tian Feng ,Wang Shibin ,Cheng Zheng,Zheng Qinghua
	Computer Science and Technology 04 January 2008
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	Abstract:Many clustering methods have been adopted by personalized e-learning system to find interested groups or common characteristics of members within the same group. However, hard boundary during discretization of collected data or subjective influences was introduced, and corresponding methods were utilized. Aiming at this problem, a fuzzy clustering method based on fuzzy statistic is proposed to cluster the learners according to their personality and learning strategy data collected from an online system. Then, an analysis method based on frequent pattern is introduced to testify the result of the proposed unsupervised clustering methods. The clustering results correspond with viewpoints of pedagogy.
	TO cite this article:Tian Feng ,Wang Shibin ,Cheng Zheng, et al. Research on E-learner Personality Grouping Based on Fuzzy Clustering Analysis[OL].[ 4 January 2008] http://en.paper.edu.cn/en_releasepaper/content/17727


	7. DMIN: Dynamic Multi-hop Infrastructure Network for Wireless Home Networking
	Zhuge Jianwei,Li Xiaodong,Ye Zhiyuan,Han Xinhui
	Computer Science and Technology 03 January 2008
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	Abstract:In this paper, we propose a generic wireless network topology model, namely, Dynamic Multi-hop Infrastructure Network (DMIN). First, we describe its self-organization, adaptation to dynamic changes and routing algorithm. Secondly, an extended model DMIN-U is introduced to support unidirectional links between wireless nodes. To support wireless home networking (WHN), we investigate the issues across the physical, MAC and routing layers based on the DMIN topology model. Finally, we present simulation results that show the proposed DMIN model and its routing algorithm is more suitable for WHN as compared to MANET with AODV and DSR routing algorithms.
	TO cite this article:Zhuge Jianwei,Li Xiaodong,Ye Zhiyuan, et al. DMIN: Dynamic Multi-hop Infrastructure Network for Wireless Home Networking[OL].[ 3 January 2008] http://en.paper.edu.cn/en_releasepaper/content/17670


	8. A New Local PCA SOM Algorithm
	Huang Dong ,Zhang Yi,Pu Xiaorong
	Computer Science and Technology 18 December 2007
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	Abstract:This paper proposes a Local PCA-SOM algorithm. The new competition measure is computational efficient, and implicitly incorporates the Mahalanobis distance and the reconstruction error. The matrix inversion or PCA decomposition for each data input is not needed as compared to the previous models. Moreover, the local data distribution is completely stored in the covariance matrix instead of the pre-defined numbers of the principal components. Thus, no priori information of the optimal principal subspace is required. Experiments on both the synthesis data and a pattern learning task are carried out to show the performance of the proposed method.
	TO cite this article:Huang Dong ,Zhang Yi,Pu Xiaorong . A New Local PCA SOM Algorithm[OL].[18 December 2007] http://en.paper.edu.cn/en_releasepaper/content/17102


	9. Shape Recovery by a Generalized Topology Preserving SOM
	Huang Dong ,Zhang Yi
	Computer Science and Technology 18 December 2007
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	Abstract:This paper proposes a new deformable model, i.e., gTPSOM, for object shape recovery. Inspired by ViSOM and Region-Aided Active Contour, the proposed model is formulated as generalized chain SOM with an adaptive force field. The adaptive force field is adjusted during the evolvement of the neuron chain according to local consistency of the image edge map. With the topology preserving property inherited from the data mapping model, i.e. ViSOM, the proposed model is suitable for both the precise edge detection and the complex shape recovery with boundary strength variations. Detailed formulation and analysis of the proposed model are given. Experiments on both synthesis and real images are carried out to demonstrate the performances.
	TO cite this article:Huang Dong ,Zhang Yi. Shape Recovery by a Generalized Topology Preserving SOM[OL].[18 December 2007] http://en.paper.edu.cn/en_releasepaper/content/17083


	10. Quantum Particle swarm optimization based network Intrusion feature selection and Detection
	Zhang Hongmei,Gao Haihua,Wang Xingyu
	Computer Science and Technology 14 December 2007
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	Abstract:Considering the relevance among features, which filter-based feature selection method fails to deal with, a kind of hybrid quantum particle swarm optimization and support vector machines based network intrusion feature selection wrapper algorithm is put forward. The subset of features is represented using quantum superposition characteristic and probability representation, among which superposition characteristic can make a single particle represent several states, thus potentially increases population diversity. Every particle in the quantum particle swarm stands for a selected subset of features. A probabilistic mutation is adopted to avoid local optimal and a taboo search table is used to enlarge particle swarm’s search space and avoid repeated computation. The fitness of particle is defined as the correct classification percentage by SVM using a training set whose patterns are represented using only the selected subset of features. The results of experiments demonstrate that the proposed method can be an effective and efficient way for feature selection and detection via using the data sets of KDD cup 99.
	TO cite this article:Zhang Hongmei,Gao Haihua,Wang Xingyu. Quantum Particle swarm optimization based network Intrusion feature selection and Detection[OL].[14 December 2007] http://en.paper.edu.cn/en_releasepaper/content/16964

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