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Research of unconventional emergency evolution state transfer rule

ICIC Express Letters, Part B: Applications 2013年第4期4卷 1023-1030页

作者： Li, Tong Xia, Zhangli Zhou, Qing Yang, Wei Management College Hangzhou Dianzi University No. 1 2nd Ave Xiasha Higher Education Zone Hangzhou 310018 China Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University No. 10 Xuefu Ave Jinzhou Xinqu Dalian 116622 China

Unconventional emergency is essentially a developing process that event state variable changes from steady to transient, then to a new steady state. This paper uses plant growth dynamics theory to study microcosmic dynamical mechanism of unconventional emergency state space transformation. Under the effect of microcosmic dynamical mechanism, the state space transformation path may be countless. Herein we do not study each possible developing path of unconventional emergency individually, but focus on the analysis of the probability distribution of different paths, then determine the impact of controlling variable on probability distribution and confirm new steady points of unconventional emergency. This paper reveals the scenario elements and coping strategies that the unconventional emergency scenario evolution process faced, and finally provides scientific basis to cope with unconventional emergency. © 2013 ISSN 2185-2766.

关键词： Probability distributions

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Facial expression recognition based on multi-scale vector triangle

Facial expression recognition based on multi-scale vector tr...

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IEEE/SICE International Symposium on System Integration

作者： He Jiang Min Hu Hongbo Chen Kun Li Xiaohua Wang Fuji Ren School of Computer and Information Affective Computing and Advanced Intelligent Machines AnHui Key Laboratory Hefei China Fellow of the Japan Federation of Engineering Societies University of Tokushima Shinkura-cho Tokushima Japan

Image description is not sufficient in traditional facial expression recognition (FER) methods, therefore this paper proposes a FER method based on multi-scale vector triangle. It combines vector triangle pattern with image pyramid to extract facial expression features. Firstly, construct a facial image pyramid to produce images in different scales. Secondly, divide each image into blocks, and extract vector triangle features of each sub-image. Then, use histogram to statistical characteristics, and calculate Euclidean distance between the histograms. Finally, fusion weighted eigenvalues and come to the recognition results. Multi-scale vector triangle pattern can not only avoid the loss of information in image asymmetric regions, but also reflect image features in different scales. It can describe images more adequately. In order to verify the effectiveness of the algorithm, this paper uses the Japanese Female Facial Expression (JAFFE) database to do the experiments and compare the results with Complete Local Binary Patterns (CLBP), Gabor wavelet, Active Appearance Models (AAM) and so on. Experimental results indicate that this method has higher recognition rate and better real-time effect.

关键词： Vectors Feature extraction Face recognition Conferences Databases Histograms Affective computing

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Facial expression recognition algorithm based on feature fusion adaptive weighted HLAC

Facial expression recognition algorithm based on feature fus...

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IEEE/SICE International Symposium on System Integration

作者： Rui Li Zhuguo Yu Min Hu Zhong Huang Fuji Ren Institute of Intelligent Machines(IIM) Chinese Academy of Sciences School of Computer and Information Affective Computing and Advanced Intelligent Machines AnHui Key Laboratory Hefei China Japan Federation of Engineering Societies University of Tokushima Shinkura-cho Tokushima Japan

In this paper, a novel method of facial expression recognition based on adaptive weighted higher-order local autocorrelation coefficient (WHLAC) is presented. Firstly, The method gets whole face region and sub-regions of eyebrows, eyes, nose and mouth. Secondly, the global features of the face regions and local features of the sub-regions are extracted by HLAC, the weights of sub-regions are calculated by fisher linear discriminant (FLD), and then these two parts features are fused together by the weights. Finally, the fused features are classified by FLD. The experimental results show that the proposed method has higher recognition rate and lower computational cost than Gabor, WLBP, HLAC for facial expression recognition.

关键词： Feature extraction Face recognition Eyebrows Nose Mouth Educational institutions Correlation

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Laplacian coordinates-based motion transition for data-driven motion synthesis

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IET Image Processing 2012年第9期6卷 1331-1337页

作者： Yi, P. Zhang, Q. Wei, X. School of Mechanical and Engineering Dalian University of Technology Dalian 116024 China Key Laboratory of Advanced Design and Intelligent Computing Dalian University Ministry of Education Dalian 116622 China

As a fundamental technique in data-driven (or example-based) methods, motion blending has been employed to produce new motion clip from two or more clips or introduced as a medium to improve the final result of other method, for example, motion graphs. As methods of motion blending always require the system or users to classify the motion samples, it is difficult to accomplish motion blending automatically and to preserve local details, such as angular accelerations of joints of original motions. In this study, the authors developed a framework based on Laplacian coordinates to produce transitions between two motion clips, emphasising on preserving local details, without any need of motion classification. At first, multidimensional Laplacian coordinates are introduced to present local details of joints' angle. Then an error function is deduced to measure how much result motions differ from original ones in local details. By minimising such error function, new motions can then finally generated, which can preserve local details of input motion clips as much as possible. The following experiments show the effectiveness of the authors' framework. © The Institution of Engineering and Technology 2012.

关键词： Laplace transforms

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Microblogging hot events emotion analysis based on Ren-CECps

Microblogging hot events emotion analysis based on Ren-CECps

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IEEE/SICE International Symposium on System Integration

作者： Ning Liu Fuji Ren Xiao Sun Changqin Quan AnHui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine HeFei University of Technology HeFei China P.R. The Japan Federation of Engineering Societies University of Tokushima Shinkura-cho Tokushima Japan

Since Sina microblogging was first launched in August 2009, that seems to have become the major social media communication platform in China, microblogging is increasingly deep into life. In this study, we analyze the sentiment of microbloging hot events based on Ren-CECps. According to hot events in chronological, choosing the microblogging hot events of “Beijing Heavy Fog” and “Xi Jinping, Peng Liyuan Visit” for instance, crawling through sina microblogging we can get the corpus that contains the specified events. The method uses word frequency statistics for access microblogging corpus, analyzing trends in specific keywords concerns. At the same time, according to specific keywords related to micro-Bo, we can calculate the emotions of related microblogging via Ren-CECps. Finally, according to changes from time to time, we make a corresponding data charts, visual display of such trends. In this study, we illustrate that we can get a good result of emotion analysis using Ren-CECps in such a microblogging Chinese text with fragmentation and discrete feature. As a further indication of such excellent Chinese emotion corpus, the practical and research value in it are enormous.

关键词： Blogs Market research Educational institutions Kernel Twitter Computers Polynomials

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A new preprocessing algorithm and local binary pattern based facial expression recognition

A new preprocessing algorithm and local binary pattern based...

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IEEE/SICE International Symposium on System Integration

作者： Yao Qian Fuji Ren Changqin Quan Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei University of Technology Hefei China P. R University of Tokushima Tokushima Japan Hefei University of Technology Hefei Anhui CN

This paper presents a new preprocessing algorithm with local binary pattern for facial expression recognition. Firstly, we establish the skin color model to extract the face region, and then we use the cumulative projection to obtain the completely face region. Secondly, we rotate the inclined faces, normalize all the images, and remove the effect of light to get the required experimental samples. Finally, we use rotation invariance uniform local binary pattern operator to get the facial expression features, and then the support vector machine classifier is used for expression classification. The algorithm is implemented with Matlab and experimented on Indian male facial expression database. The proposed method obtained an accuracy of 72.75% which shows the effectiveness of the proposed algorithm.

关键词： Skin Image color analysis Face Histograms Color Feature extraction Databases

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Attribute reduction based on approximation dependency degree

Journal of Computers (Finland)

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Journal of Computers (Finland) 2013年第4期8卷 920-928页

作者： Li, Min Deng, ShaoBo Feng, Shengzhong Fan, Jianping NanChang Institute of Technology Nanchang Jiangxi 330099 China Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen Guangdong 518055 China Key laboratory of intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China

Attribute reduction is one of the core research content of Rough sets theory. Many existing algorithms mainly are aimed at the reduction of consistency decision table, and very little work has been done for attribute reduction aimed at inconsistency decision table. In fact, the methods finding Pawlak reduction from consistent decision table are not suitable for inconsistency decision table. In this paper, we introduce the approximation dependency reduction modal and present the Quick Attribution Reduction based on Approximation Dependency Degree (Quick-ARADD), which can retain the original boundary region and the original positive region unchanged, and keep the approximation accuracy unchanged for all decision equivalence classes (the partition of universe on decision attributes) of a decision table. Theoretical analysis and experimental results show that the Quick-ARADD algorithm is effective and feasible. © 2013 ACADEMY PUBLISHER.

关键词： Decision tables

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Feature fusion of HOG and WLD for facial expression recognition

Feature fusion of HOG and WLD for facial expression recognit...

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IEEE/SICE International Symposium on System Integration

作者： Xiaohua Wang Chao Jin Wei Liu Min Hu Liangfeng Xu Fuji Ren AnHui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei University of Technology China School of Computer and Information Hefei University of Technology China The Japan Federation of Engineering Societies University of Tokushima Shinkura-cho Tokushima Japan

A considerable amount of research work has been done for facial expression recognition using local or global feature extraction methods. Weber Local Descriptor (WLD), a simple and robust local image descriptor, is recently developed for local feature extraction. In facial expression recognition, the information contained in the local is important for the recognition result. The Histograms of Oriented Gradients (HOG) can well describe the local area information using gradient and orientation density distribution of the edge. In order to solve the lack of contour and shape information only by WLD features and to extract facial local features more efficiently, we propose a hybrid approach that combines the WLD with HOG features. We divide the images into blocks and weight each of them, then extract the two features and fuse them. At last, the weighted fused histograms are used to classify facial expressions by chi-square distance and the nearest neighbor method. The proposed method is applied on popular JAFFE and Cohn-Kanade facial expression databases and recognition rate is up to 93.97% and 95.86%. Compared with the Gabor Wavelet, LBP, and AAM and experimental results show that the proposed method achieves better performance for facial expression recognition.

关键词： Feature extraction Histograms Databases Face recognition Equations Active appearance model Data mining

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Enhanced hybrid search algorithm for protein structure prediction using the 3D-HP lattice model

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Journal of molecular modeling 2013年第9期19卷 3883-91页

作者： Changjun Zhou Caixia Hou Qiang Zhang Xiaopeng Wei Key Laboratory of Advanced Design and Intelligent Computing Dalian University Dalian China. zhou-chang231@***

The problem of protein structure prediction in the hydrophobic-polar (HP) lattice model is the prediction of protein tertiary structure. This problem is usually referred to as the protein folding problem. This paper presents a method for the application of an enhanced hybrid search algorithm to the problem of protein folding prediction, using the three dimensional (3D) HP lattice model. The enhanced hybrid search algorithm is a combination of the particle swarm optimizer (PSO) and tabu search (TS) algorithms. Since the PSO algorithm entraps local minimum in later evolution extremely easily, we combined PSO with the TS algorithm, which has properties of global optimization. Since the technologies of crossover and mutation are applied many times to PSO and TS algorithms, so enhanced hybrid search algorithm is called the MCMPSO-TS (multiple crossover and mutation PSO-TS) algorithm. Experimental results show that the MCMPSO-TS algorithm can find the best solutions so far for the listed benchmarks, which will help comparison with any future paper approach. Moreover, real protein sequences and Fibonacci sequences are verified in the 3D HP lattice model for the first time. Compared with the previous evolutionary algorithms, the new hybrid search algorithm is novel, and can be used effectively to predict 3D protein folding structure. With continuous development and changes in amino acids sequences, the new algorithm will also make a contribution to the study of new protein sequences.

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A RGB image encryption algorithm based on DNA encoding and chaos map

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Computers and Electrical Engineering 2012年第5期38卷 1240-1248页

作者： Lili Liu Qiang Zhang Xiaopeng Wei Key Laboratory of Advanced Design and Intelligent Computing Dalian University Ministry of Education Dalian 116622 China

In this paper, a RGB image encryption algorithm based on DNA encoding combined with chaotic map is proposed aiming at characteristics of RGB image. The algorithm firstly carries out DNA encoding for R, G, B components of RGB image; then realizes the addition of R, G, B by DNA addition and carries out complement operation by using the DNA sequence matrix controlled by Logistic; three gray images are got after decoding; finally gets the encrypted RGB images by reconstructing R, G, B components which use image pixels disturbed by Logistic chaotic sequence. Simulation result shows that the proposed algorithm has a large secret key space and strong secret key sensitivity. Meanwhile, it can resist exhaustive attack, statistical attack, and thus it is suitable for RGB image encryption.

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