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Exploring the rules of Li-Fa-Fang-Yao on diabetes mellitus within traditional chinese medicine through text mining

Exploring the rules of Li-Fa-Fang-Yao on diabetes mellitus w...

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International conference on computer Sciences and Convergence Information Technology (ICCIT)

作者： Yunyu Huang Shidong Wang Lianjie Wang Xiuchen Yu Miao Jiang Junping Zhan Aiping Lu Guang Zheng Beijing Dongzhimen Hospital Beijing University of Chinese Medicine Beijing China Institute of Basic Research in Clinical Medicine China Academy of Chinese Medical Sciences Beijing China Shanghai University of Traditional Chinese Medicine Shanghai China Hong Kong Baptist University School of Chinese Medicine Hong Kong China School of Information Science-Engineering Lanzhou University Lanzhou China

ISBN: (纸本)9781467308946

Diabetes mellitus, or simply diabetes, is a group of metabolic diseases in which a person has high blood sugar, either because the body does not produce enough insulin, or because cells do not respond to the insulin that is produced. In traditional chinese medicine (TCM), diabetes mellitus is called “Sweet Urine Disease”. Over several thousand years of clinical research and theoretical thoughts, some treatment on diabetes has been accumulated. these treatment rules can be demonstrated through the networks of Li-Fa-Fang-Yao which is of critical importance in clinical practices of TCM. Li-Fa-Fang-Yao, which means principles, methods, formulae, and chinese herbal medicines respectively, indicate the four basic steps of diagnosis and treatment: determining the cause, mechanism and location of the disease according to the medical theories and principles, then deciding the treatment principle and method, and finally selecting a formula as well as proper chinese herbal medicines. In this paper, focused on disease of diabetes, we explored the rules of Li-Fa-Fang-Yao within the framework of traditional chinese medicine. through calculation, four networks i.e., symptom, pattern/syndrome, treatment principle, herbal formula, and chinese herbal medicine were constructed. Based on these four networks, their connections were also demonstrated by the professional knowledge of TCM and thus a whole network of Li-Fa-Fang-Yao was constructed and demonstrated. this Li-Fa-Fang-Yao network might be meaningful for both clinical practise and medical research.

关键词： text mining Li-Fa-Fang-Yao network diabetes mellitus traditional chinese medicine chinese Traditional Medicine Diabetes Mellitus text mining chinese herbal medicine Rule trellis coded modulation Hyperglycemia Network formula clinical practice Insulin Insulins

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A new dataset of Persian handwritten documents and its segmentation

A new dataset of Persian handwritten documents and its segme...

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2011 7th Iranian conference on Machine vision and Image Processing, MVIP 2011

作者： Alaei, Alireza Nagabhushan, P. Pal, Umapada Department of Studies in Computer Science University of Mysore Mysore 570006 India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata-108 India

ISBN: (纸本)9781457715358

In document image analysis and especially in handwritten document image recognition, standard datasets play vital roles for evaluating performances of algorithms and comparing results obtained by different groups of researchers. In this paper, an unconstrained Persian handwritten text dataset (PHTD) is introduced. the PHTD contains 140 handwritten documents of three different categories written by 40 individuals. Total number of text-lines and words/subwords in the dataset are 1787 and 27073, respectively. In most of the PHTD documents either an overlapping or a touching text-lines is present. the average number of text-lines in documents of the PHTD is 13. Two types of ground truths based on pixels information and content information are generated for the dataset. Providing these two types of ground truths for the PHTD, it can be utilized in many areas of document image processing such as sentence recognition/understanding, text-line segmentation, word segmentation, word recognition, and character segmentation. To provide a framework for other researches, recent text-line segmentation results on this dataset are also reported. © 2011 IEEE.

关键词： Image segmentation

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thinning based multipurpose camouflage pattern design

Thinning based multipurpose camouflage pattern design

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2011 7th Iranian conference on Machine vision and Image Processing, MVIP 2011

作者： Hejrandoost, Arash Abdi Safabakhsh, Reza Amirkabir University Tehran Iran

ISBN: (纸本)9781457715358

Traditional generations of camouflage pattern were an artistic and manually work. Most of current computer aided camouflage pattern designs focused on a single background to produce the pattern for. In our proposed method, a multi background camouflage pattern is designed using Fuzzy C-Means (FCM) clustering method followed by a object thinning algorithm to combine clustered backgrounds with each other. the goal is to generate patterns with similarity to all backgrounds. Experimental results and their evaluations demonstrate generated patterns inherited color and texture characteristics of all backgrounds. © 2011 IEEE.

关键词： C (programming language)

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A Matching Algorithm for IR/Visual Images Based on the Invariant Moment of Histogram

A Matching Algorithm for IR/Visual Images Based on the Invar...

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7th Symposium on Multispectral Image Processing and pattern recognition (MIPPR) - pattern recognition and computer vision

作者： Zhu Ying-hong Li Jun-shan Zhu Yi-juan Xian Res Inst High Tech Xian 710025 Peoples R China Chinese Peoples Armed Police Force Shanghai Peoples R China

ISBN: (纸本)9780819485786

the concept of invariant moment of gradient orientation histogram and a novel line matching algorithm based on the invariant moment of histogram are proposed to resolve the problem of matching typical objects in the IR and visible images. First, line segments are extracted. Second, the average gradient vector direction of each pixel on the line is adopt as the main direction of the line. third, the line is divided into non-overlapped sub-regions with the same size. the gradient vector direction of each sub-region are constructed, and the weighted invariant moment of histogram in each sub-region are calculated to build the line descriptor. Finally, the feature matching is realized via the NNDR(nearest/next ratio) method. Experimental results show that the proposed algorithm can match the typical objects in the IR and visible images efficiently and correctly.

关键词： infrared image visual image invariant moment of histogram edge extraction line matching

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A simple and efficient saliency extraction method based on multi-scale horizon-directional filter for infrared dim small target detection

A simple and efficient saliency extraction method based on m...

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7th Symposium on Multispectral Image Processing and pattern recognition (MIPPR) - pattern recognition and computer vision

作者： Xia, Renbo Zhao, Jinbin Hui, Bin Chang, Zheng Zhou, Guangchao Chinese Acad Sci Shenyang Inst Automat Shenyang 110016 Peoples R China

ISBN: (纸本)9780819485786

this paper presents a simple and computationally efficient saliency extraction method for detecting dim small target from single frame in heterogeneous background. the proposed method is based on background subtraction (BS), which identifies targets from the portion of a image that differs significantly from a background model. A set of horizon-directional filters (HDF) with multi-scales are first implemented to effectively recover the background maps from the input image. As a result, the foreground maps are extracted by computing the absolute difference between the input image and the estimated background maps. then the foreground maps are fused into the total saliency map using a simple scheme. Finally, the experimental results of various cluttered background images show that the proposed method is efficient and has an outstanding performance in dim small target detection just by thresholding the saliency map.

关键词： horizon-directional filter dim small target detection saliency detection background subtraction

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Practical notes on corruption resistance of Hopfield neural network in chinese characters pattern recall

Practical notes on corruption resistance of Hopfield neural ...

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2011 7th International conference on Natural Computation, ICNC 2011

作者： Chen, Ken Shen, Jiajia Jiang, Gangyi Batur, Celal College of Information Science and Engineering Ningbo University Ningbo Zhejiang 315211 China College of Engineering University of Akron Akron OH 44325 United States

ISBN: (纸本)9781424499533

Digital Hopfield neural networks (DHNN) are well known for its pattern recall capability in noisy circumstances. In this paper, a number of tests are conducted for primarily exploring the recall competency of DHNN in restoring a given set of corrupted chinese characters. the character patterns are separately corrupted with uniformly distributed random noises, limited translations and rotations. Some author-defined parameters are introduced such as character pattern complexity, similarity, full recall rate, etc. in order to quantify the recall quality. the test findings are tabulated and analyzed accordingly. the results are expected to contribute certain referential data to the prospective research on application of DHNN in chinese characters recognition with machine vision technologies. © 2011 IEEE.

关键词： Hopfield neural networks

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Artificial Intelligence Applications and Innovations 2011

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丛书名： IFIP Advances in Information and Communication Technology

2011年

作者： Lazaros S. Iliadis Ilias Maglogiannis Harris Papadopoulos

ISBN: (数字)9783642239601

ISBN: (纸本)9783642239595

the two-volume set IFIP AICT 363 and 364 constitutes the refereed proceedings of the 12th International conference on Engineering Applications of Neural Networks, EANN 2011, and the 7th IFIP WG 12.5 International conference, AIAI 2011, held jointly in Corfu, Greece, in September 2011. the 52 revised full papers and 28 revised short papers presented together with 31 workshop papers were carefully reviewed and selected from 150 submissions. the second volume includes the papers that were accepted for presentation at the AIAI 2011 conference. they are organized in topical sections on computer vision and robotics, classification/pattern recognition, financial and management applications of AI, fuzzy systems, learning and novel algorithms, recurrent and radial basis function ANN, machine learning, generic algorithms, data mining, reinforcement learning, Web applications of ANN, medical applications of ANN and ethics of AI, and environmental and earth applications of AI. the volume also contains the accepted papers from the First Workshop on Computational Intelligence in Software Engineering (CISE 2011) and the Workshop on Artificial Intelligence Applications in Biomedicine (AIAB 2011).

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Learning Local Binary patterns with enhanced boosting for face recognition

Learning Local Binary Patterns with enhanced boosting for fa...

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2011 7th International conference on Computational Intelligence and Security, CIS 2011

作者： Xiao, Fanyi Liang, Yixiong Qu, Xiaohui Institute of Computer Vision and Virtual Reality Central South University Changsha China Department of Automatics Central South University Changsha China

ISBN: (纸本)9780769545844

Due to its invariance to monotonic grayscale transformation and simple computation, Local Binary pattern (LBP) is broadly used as feature extractor in face recognition tasks in recent years[3]. In previous work, people have proposed methods of using Adaboost to select most representative features in samples. Zhang et al. proposed a method applying Adaboost algorithm to select those most distinctive features from which they extract LBP features. though LBP features selected by Adaboost represent local textures effectively. their method, however, neglects exploitation of holistic spatial information in nature of image samples. To solve this problem, we proposed the spatial enhanced multi-level boosing using uniform LBP and multilevel Adaboost algorithm. In this paper, we select most distinctive features which then being concatenated to represent spatial information using multi-level boosting algorithm. Experiments on ORL database yielded an exciting recognition rate of 98.96%. © 2011 IEEE.

关键词： Local binary pattern

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Image super-resolution enhancement based on online learning and blind sparse decomposition

Image super-resolution enhancement based on online learning ...

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7th Symposium on Multispectral Image Processing and pattern recognition (MIPPR) - pattern recognition and computer vision

作者： Lu, Jinzheng Zhang, Qiheng Xu, Zhiyong Peng, Zhenming Chinese Acad Sci Inst Opt & Elect Chengdu 610209 Peoples R China Univ Elect Sci & Technol China Sch Optoelect Informat Chengdu 610054 Peoples R China Grad Univ Chinese Acad Sci Beijing 100039 Peoples R China

ISBN: (纸本)9780819485786

this paper presents a different learning-based image super-resolution enhancement method based on blind sparse decomposition, in order to improve its resolution of a degraded one. Firstly, sparse decomposition based image super-resolution enhancement model is put forward according to the geometrical invariability of local image structures under different conditions of resolution. Secondly, for reducing the complexity of dictionary learning and enhancing adaptive representation ability of dictionary atoms, the over-complete dictionary is constructed using online learning fashion of the given low resolution image. thirdly, since the fixed sparsity of the conventional matching pursuit algorithms for sparse decomposition can not fit all types of patches, the approach to sparse decomposition with blind sparsity can achieve relatively higher accurate sparse representation of an image patch. Lastly, atoms of high resolution dictionary and coefficients of representation of the given low-resolution image are synthesized to the desired SR image. Experimental results of the synthetic and real data demonstrate that the suggested framework can eliminate blurring degradation and annoying edge artifacts in the resulting images. the proposed method can be effectively applied to resolution enhancement of the single-frame low-resolution image.

关键词： Sparse decomposition sparse representation dictionary learning super-resolution reconstruction

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Improved Fourier descriptors in model-based pose estimation

Improved Fourier descriptors in model-based pose estimation

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7th Symposium on Multispectral Image Processing and pattern recognition (MIPPR) - pattern recognition and computer vision

作者： Tang Hui-jun Wen Jia Ma Cai-wen Hu Hai-bin Zhou Ren-kui Chinese Acad Sci Xian Inst Opt & Precis Mech Xian 710119 Peoples R China Grad Sch CAS Beijing 100039 Peoples R China Beijing Inst Tracking & Telecommun Technol Beijing 100094 Peoples R China

ISBN: (纸本)9780819485786

We use Fourier descriptors (FD's) to represent shape in model-based pose estimation. Specific invariance and normalization requirements for shape descriptors concerning to pose estimation are proposed. FD's are improved to meet such requirements. Common issues and techniques for such application are focused on. Starting point of the shape contour is fixed to the upper left corner point. Distance pairs instead of edge coordinate pairs recast the shape sequence. Moving average filtering is proceeded to remove the noises of the shape sequence. Shape sequence is re-sampled to make it definite length. FD's amplitude is normalized to the range of 0 to 1. Variance of sequences between observed and library FD's is defined as the shape matching objective function. For simulation, we use a missile model of Milkshape3d format. Results show that by adopting the improved FD's, we can arrive at a pose estimation practically by randomly optimal search of library FD's.

关键词： Fourier descriptors invariance normalization shape matching optimal search model-based pose estimation

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