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Study on Construction of Platform Supported by science and Technology Service of Southern Asia Characterized Cultivation Industry Clusters

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Study on Construction of Platform Supported by Science and T...

Research of Feature Extraction of BCI Based on Common Spatial Pattern and Wavelet Packet Decomposition

第三届国际计算机及计算技术农业应用学术会议

作者： Shuangyin Liu~(1 *) Longqin Xu~1 and Yuli Shen~2 1 college of Information Guangdong Ocean University Zhanjiang Guangdong Province 524025 china 2 college of computer science and engineering Zhongkai University of Agricultural and engineering Guangzhou 510225 china

＜正＞In order to solve the universal problems in the field of agricultural technology service system such as the incomplete and separated agricultural knowledge,deficient ability in data analysis and processing, etc.,this article starts with the construction of a shared and reusable platform supported by science-and-technology service of Southern Asia characterized cultivation industry *** detailed cases about system development,this article is directed at some technology bottlenecks in the process of system construction and explores the innovation mode of the service,the platform structure,the expression of cultivation technology,knowledge sharing and reusability,and knowledge reasoning and integration technology,etc.

关键词： Cultivation Industry Clusters Agricultural Knowledge System Knowledge Expression Knowledge Sharing Knowledge Reasoning and Integration

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Research of Feature Extraction of BCI Based on Common Spatia...

Theoretical analysis of alloy multiplying factor by the empirical electron theory of solids and molecules

2009中国控制与决策会议

作者： Ye Ning~1,Mei Zhan~2,Sun Yuge~1,Wang Xu~1 1.Information science & engineering college,Northeastern University,Shenyang,110004 china 2.college of computer science and engineering,Shenyang University of Chemical Technology,Shenyang 110142,china

＜正＞Brain-computer Interface（BCI） is to establish a new communication system that translates human intentions reflected by EEG into a control signal for an output device such as a *** paper classified the EEG of two kinds of motor *** feature extraction method combines wavelet packet decomposition and common spatial *** k-nearest neighbors（KNN） is applied as classification *** raw multi-channel EEG data is pre-processed by wavelet packet decomposition,with CSP method to extract the feature,and the best classification accuracy can reach 95.3%.If the EEG data is not decomposed by wavelet packet, the classification accuracy is only 83.3%.The result shows that if wavelet packet function and level is selected properly,the classification accuracy can improve effectively.

关键词： Brain-computer Interface(BCI) EEG Common Spatial Pattern(CSP) Wavelet Packet(WP)

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science china(Technological sciences) 2007年第6期50卷 807-814页

作者： SONG YuePeng1,2, LIU GuoQuan2, LI ZhiLin3, FENG ChengMing1 1 Mechanical and Electronic engineering college, Shandong Agricultural University, Tai’an 271018, china 2 college of Materials science and engineering, University of science and Technology, Beijing 100083, china 3 college of Material science and engineering, Beijing University of Chemical Technology, Beijing 100029, china Mechanical Electronic engineering college Shandong Agricultural University Tai’an 271018 China college of Materials science engineering University of Science Technology Beijing 100083 China college of Material science engineering Beijing University of Chemical Technology Beijing 100029 China

By introducing the distribution probability of structural units in austenite contain- ing alloying elements and considering its effects on phase transformation, this paper establishes a calculation model of distribution probability of structural units. A new valence electron structure (VES) parameter-transformation effect coefficient of alloying elements (HL), is defined and then studied both theoretically and ex- perimentally. The relationship between the parameter HL and the multiplying factor (the quenching capability factor) of alloying elements is studied. The results indi- cate that the two parameters (HL and the quenching capability factor) have the same variation characteristic and substance feature. Therefore, the multiplying factor virtually expresses the relative quantity of structural units in the alloying elements-containing austenite.

关键词： multiplying factor (the quenching capability factor), empirical electron theory of solids and molecules, transformation effect coefficient of alloying elements, structural units in austenite containing alloying elements

Optimization of thermomechanical processes in Cu-Cr-Zr lead frame alloy using neural networks and genetic algorithms

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science china(Technological sciences) 2005年第5期48卷 510-520页

作者： SU Juanhua1,2, LIU Ping2, DONG Qiming2 & LI Hejun1 1. college of Materials science and engineering, Northwestern Polytechnical University, Xi’an 710072, china 2. college of Materials science and engineering, Henan University of science and Technology, Luoyang 471003, china 1. college of Materials science and engineering Northwestern Polytechnical University 710072 Xi’an China 2. college of Materials science and engineering Henan University of Science and Technology 471003 Luoyang China

The thermomechanical treatment process is effective in enhancing the properties of the lead frame copper alloy. In this study, an optimal pattern of the thermomechanical processes for Cu-Cr-Zr was investegated using an intelligent control technique consisting of neural networks and genetic algorithms. The input parameters of the artificial neural network (ANN) are the reduction ratio of cold rolling, aging temperature and aging time. The outputs of the ANN model are the two most important properties of hardness and conductivity. Based on the successfully trained ANN model, genetic algorithms (GA) are used to optimize the input parameters of the model and select perfect combinations of thermomechanical processing parameters and properties. The good generalization performance and optimized results of the integrated model are achieved.

关键词： Cu-Cr-Zr alloy, thermomechanical processing optimization, artificial neural network, genetic algorithms.

Image corner detection using topology learning

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The Journal of china Universities of Posts and Telecommunications 2010年第6期17卷 101-105页

作者： SUN Wei,YANG Xuan college of computer science and Software engineering,Shenzhen University,Shenzhen 518060,china [a] college of computer science Software engineering Shenzhen University Shenzhen 518060 China

Image corner detection plays an important role in image analysis and recognition. This paper presents a novel corner detector based on the growing neural gas （GNG） network and this proposed detector is called GNG-C. With the GNG network,image topology information can be learned and used to implement corner detection. The GNG-C approach can be described as consisting of the following steps. First,a canny edge detector is used to acquire the contour information of the input image. This edge information is used to train a modified GNG network. A special stopping criterion is defined to terminate network learning. Second,vectors formed between network nodes and their neighbors are used to measure curvatures. Third,dynamic regions of support （ROS） are determined based on these curvatures. These ROS are used to suppress curvature noise. The curvature values of the nodes are then analyzed to estimate the candidate corners. Finally,the candidates are distilled by a non-maxima suppression process to obtain the final set of corners. Experiments on both artificial and real images show that the proposed corner detection method is feasible and effective.

关键词： corner detection GNG topology learning self-organizing map

Web Application Comprehension Based on Dependence Analysis

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Wuhan University Journal of Natural sciences 2004年第5期9卷 731-734页

作者： WU Jun-hua 1,2 , XU Bao-wen 1 , JIANG Ji-xiang 1 1.Department of computer science and engineering, Southeast University, Nanjing 210096, Jiangsu, china 2.college of computer science and engineering, Nanjing University of Technology, Nanjing 210009, Jiangsu , china Southeast University Department of Computer Science and Engineering Nanjing Jiangsu China (GRID:grid.263826.b) (ISNI:***) Najing University of Technology College of Computer Science and Engineering Nanjing Jiangsu China (GRID:grid.41156.37) (ISNI:***) Southeast University Department of Computer Science and Engineering Nanjing Jiangsu China (GRID:grid.263826.b) (ISNI:***)

Many research indicate a lot of money and time are spent on maintaining and modifying program delivered. So the policies to support program comprehension are very important. Program comprehension is a crucial and difficult task. Insufficient design, illogical code structure, short documents will enhance the comprehensive difficulty. Developing Web application is usually a process with quick implementation and delivery. In addition, generally a Web application is coded by combining mark language statements with some embedded applets. Such programming mode affects comprehension of Web applications disadvantageously. This paper proposes a method to improving understanding Web by dependence analysis and slice technology. Key words Web application comprehension - program dependence - hyper graph - pogram slicing CLC number TP 311 Foundation item: Supported in part by the Young Scientist’s Fund of NSFC (60373066, 60303024). National Grand Fundamental Research 973 Program of china (2002CB312000) and National Research Foundation for the Doctoral Program of Higher Education of chinaBiography: WU Jun-hua (1965-), female, Ph. D. research direction: software engineering.

关键词： Web application comprehension program dependence hyper graph pogram slicing

Theory and techniques of data mining in CGF behavior modeling

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science china(Information sciences) 2011年第4期54卷 717-731页

作者： YIN YunFei 1,2,GONG GuangHong 2 & HAN Liang 2 1 college of computer science,Chongqing University,Chongqing 400044,china 2 School of Automation science and Electrical engineering,Beijing University of Aeronautics and Astronautics,Beijing 100083,china 1. college of computer science Chongqing University Chongqing 400044 China2. School of Automation Science and Electrical Engineering Beijing University of Aeronautics and Astronautics Beijing 100083 China

For the large quantity of data,rules and models generated in the course of computer generated forces (CGFs) behavior modeling,the common analytical methods are statistical methods based on the tactical rules,tactical doctrine and empirical ***,from the viewpoint of data mining,we can find many of these analytical methods are also each-and-every different data mining *** this paper,we survey the data mining theory and techniques that have appeared in the course of CGF behavior modeling from the viewpoint of data ***,we redefine and reclassify these theories and techniques according to the research requirements of data mining (the knowledge structure of data mining).We aim to help the CGF investigators to learn the key points and the research methods of the data intelligent processing in the CGF behavior modeling,and thus we can provide the references for the colleagues who are engaged in the research and practice of the CGF behavior modeling by this *** also introduce our ongoing work on the CGF behavior modeling based on data mining.

关键词： CGF CGF behavior modeling data mining theory and techniques

Dynamic damage and stress-strain relations of ultra-high performance cementitious composites subjected to repeated impact

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science china(Technological sciences) 2010年第6期53卷 1520-1525页

作者： LAI JianZhong1 & SUN Wei2 1 Department of Materials science and engineering,Nanjing University of science and Technology,Nanjing 210094,china 2 college of Materials science and engineering,Southeast University,Nanjing 211189,china 1. Department of Materials science and engineering Nanjing University of Science and Technology Nanjing 210094 China2. College of Materials Science and Engineering Southeast University Nanjing 211189 China

Ultra-high performance cementitious composites (UHPCC) were prepared by replacing 60% of cement with ultra-fine industrial waste *** dynamic damage and compressive stress-strain relations of UHPCC were studied using split Hopkinson pressure bar (SHPB).The damage of UHPCC subjected to repeated impact was measured by the ultrasonic pulse velocity *** show that the dynamic damage of UHPCC increases linearly with impact times and the abilities of repeated impact resistance of UHPCC are improved with increasing fiber volume *** stress waves on impact were recorded and the average stress,strain and strain rate of UHPCC were calculated based on the wave propagation *** effects of strain rate,fibers volume fraction and impact times on the stress-strain relations of UHPCC were *** show that the peak stress and elastic modulus decrease while the strain rate and peak strain increase gradually with increasing impact times.

关键词： ultra-high performance cementitious composites (UHPCC) split Hopkinson pressure bar (SHPB) repeated impact damage stress-strain

A centrality measure based on spectral optimization of modularity density

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science china(Information sciences) 2010年第9期53卷 1727-1737页

作者： FU LiDong1,2*,GAO Lin1 & MA XiaoKe1 1School of computer science and engineering,Xidian University,Xi'an 710071,china 2college of computer,Xi'an University of science and Technology,Xi'an 710054,china 1. School of computer science and engineering Xidian University Xi’an 710071 China2. College of Computer Xi’an University of Science and Technology Xi’an 710054 China

Centrality analysis has been shown to be a valuable method for the structural analysis of complex *** is used to identify key elements within networks and to rank network elements such that experiments can be tailored to interesting *** this paper,we show that the optimization process of modularity density can be written in terms of the eigenspectrum of kernel *** on the eigenvectors belonging to the largest eigenvalue of kernel matrix,we present a new centrality measure that characterizes the contribution of each node to its assigned community in a network,called modularity density *** measure is illustrated and compared with the standard centrality measures by using respectively an artificial example and a classic network data *** statistical distribution of modularity density centrality is investigated by considering large computer generated graphs and two large networks from the real *** results show the significance of the proposed approach.

关键词： centrality modularity density centrality kernel matrix eigenspectrum