SQL Server数据库入侵检测系统的研究

随着数据库技术的发展,数据库的网络安全威胁问题受到广泛的关注.传统的防火墙技术已经不能满足网络数据库的安全防范需要,入侵检测技术成为数据库安全防范的新的安全技术.通过入侵检测技术提高SQL Server数据库的安全性是研究的重点.对入侵检测系统的安全技术进行了分析,对SQL Server数据库的安全技术进行了研究,结合入侵检测技术对SQL Server数据库入侵检测系统进行了分析和研究.     

基于实体类的数据库访问技术的研究与实现

实体类隔离了代码对数据库的依赖,降低了开发的难度。本文分析了Java语言中传统数据库访问技术与基于实体类的数据库访问技术的优缺点,简述了基于实体类的数据库访问技术的一般过程,并结合一应用实例说明了它的使用方法。     

基于日志的数据库恢复技术的研究

本文详细论述了基于日志的数据库恢复技术，在对常规数据库恢复技术分析研究的基础上。通过引入检查点和数据缓冲技术进一步提高数据库恢复的效率。     

数据库与知识库的结合策略

一、前言近二十年来,数据库技术获得了迅速地发展,已成为计算机领域中一门十分重要的学科,无论在理论上还是技术实现上都对计算机科学的发展产生深远的影响。今天,数据库技术得到广泛的应用,尤其在信息管理系统的应用更加普遍。随着人工智能技术的发展,对数据库系统提出了更高的要求,数据库技术与人工智能技术的结合,成为当今数据库技术研究和发展的方向。数据库机,演译数据库和知识库系统的研究已成为发展智能计算机的重要课题,也为数据库技术的研     

基于Java的SQL Server数据库访问技术

数据库技术和网络技术是当今计算机领域的两大重要应用。针对Java语言对数据库访问技术进行研究,分析了数据库访问技术,对JDBC和建立数据库连接进行了论述;针对网上购物系统进行了阐述,给出了相应的数据模型;利用Java语言实现了商品的查询、添加、删除及修改等常用操作。     

基于CORBA的空间数据库访问技术研究

该文从CORBA技术的概述入手,介绍了基于CORBA的数据库集成技术,并重点阐述了基于CORBA对空间数据库访问的封装。空间数据库技术作为地理信息系统的核心,提供了空间数据的存贮、访问和其它应用,基于CORBA的空间数据库访问技术为实现异种空间数据库的互操作和分布式、组件化的地理信息系统奠定了良好的基础。     

关于JSP技术访问数据库方法的研究

随着当今网站开发的不断发展,JSP技术也随之得到了普遍的应用,对于数据库的访问起着极为重要的作用。在网站的建设过程当中,正确的应用JSP技术访问数据库,在各种不同的环境当中采用相应的数据库访问技术,对于网站运行速度的提高起着至关重要的作用。该文对一些JSP技术的原理进行了简单的介绍,并就网络数据库的结构以及JDBC对数据库的连接等有关JSP技术访问数据库方法问题做了相关方面的阐述。     

Web数据库的连接技术及安全控制

随着Internet/Intranet技术的发展和普及,Web数据库必将逐步取代基于传统的Client/Server模式的数据库系统。对于数据库与Web技术融合的研究具有实际意义。文章就目前常用的几种Web数据库的连接技术进行对比分析,并对利用ASP技术实现Web与数据库的连接和Web数据库系统的安全控制进行了详细阐述。     

数据库中间件的结构分析

在企业网络应用日益发展的今天,实用的数据库技术越来越和企业网络相联系,将数据库与web技术相结合的数据库中间件技术应运而生。相比已往的联接技术,中间件的思想和方式具有相当大的优势和先进性。本文对一种实用的数据库中间件产品进行了分析,建立一般的数据库中间件模型,并从模型的角度将它和已往的CGI技术作了比较。相比而言,数据库中间件结构简单、功能完善,使数据库应用效率大大提高。     

数据库网格:基于网格的多数据库系统

近年来,数据网格技术的快速发展为广域分布环境下的海量数据共享提供了强有力的支持。数据库网格是指主要由各种数据库管理系统构成的数据网格环境,其技术难点是在网格环境下研究解决分布式查询、事务、多数据源视图等传统的数据库领域的问题。该文通过讨论数据网格、数据库网格和多数据库的概念和特点,并比较上述问题在多数据库和数据库网格环境下的异同,对数据库网格的特点进行了总结,对数据库网格技术的研究和发展方向进行了探讨和展望。     

MFR (Multipurpose Field Robot) for installing construction materials

The objective of the study was to propose a MFR (Multipurpose Field Robot) in hazardous operation environments. This system combines a basic system composed of a multi-DOF (Degree Of Freedom) manipulator and a mobile platform with an additional module for construction, national defense and emergency-rescue. According to an additional module type combined with a basic system, it can be used in a various fields. In this study, we describe a prototype of construction robot which helps a human operator handle easily construction materials in case of using the cooperation system on construction site. This study introduces an additional module for construction and a robot control algorithm for a HRC (Human-Robot Cooperation). In addition, it proposes a novel construction method to install construction materials with robot on construction site. Seung Yeol Lee received the B.S. degree from the Department of Mechanical Engineering, Myungji University, Seoul, Korea in 2002, and the M.S. degree from the Department of Mechatronics Engineering, Hanyang University, Seoul, Korea in 2005. He is a Ph.D. degree candidate from the Department of Mechanical Engineering, Hanyang University, Seoul, Korea. From 2003, He is currently a visiting researcher in the Research Institute of Technology, Construction Group at the Samsung Corporation, Korea conducting the design and implementation of construction robot and automation system for construction project. His research interests include design, control, and application of construction robots, field robotic systems and ergonomic design of robotic systems. He is a member of the Korea Society of Mechanical Engineers, Architectural Institute of Korea, and Ergonomics Society of Korea. Yong Seok Lee received the B.S. degree from the Department of Precision Mechanical Engineering, Kunsan national University, Kunsan, Korea in 2002, and the M.S. degree from the Department of Precision Mechanical Engineering, Hanyang University, Seoul, Korea in 2005. Currently, he is the Post Master in Hanyang University, Korea. His major interests include design and kinematic/dynamic analysis on multi-purpose field robots and service robots. He is a member of the Architectural Institute of Korea. Bum Seok Park received the B.S. degree from the Department of Mechanical Engineering, Hanyang University, Ansan, Kyung-gi Do, Korea in 1993, and the M.S. degree from the Department of Mechatronics Engineering, Hanyang University, Seoul, Korea in 1998. He is a Ph.D. from the Department of Mechatronics System Engineering, Hanyang University, Seoul, Korea From 2006. He is currently the post-doctor in Hanyang University, Korea. His major interests include embedded robot control system on multi-purpose field robot and service robot. He is a member of the Korea Society of Mechanical Engineers, Korean Society of Machine Tool Engineers. Sang Heon Lee graduated with the B.S. degree in Precision Mechanical Engineering from Hanyang University, Seoul, Korea in 1992. He received the M.S. degree in Precision Engineering from KAIST, Taejon, Korea in 1994 and the Ph.D. degree in Mechanical Engineering from KAIST in 2001. Currently, he is a senior researcher in Samsung Corporation, Korea. His major interests include the kinematic/dynamic analysis on multi-body system, application of field robots, and automation in construction. ChangSoo Han received the B.S. degree from the Department of Mechanical Engineering, Seoul National University Technology, Seoul, Korea in 1983, and the M.S. and Ph.D. degrees from the Department of Mechanical Engineering, University of Texas at Austin, in 1985 and 1989, respectively. From May 1988 to September 1989, he was a Research Assistant, Robotics Lab in Mechanical Engineering about manufacturing of the high resolution micro manipulator module. In March 1990, he joined Hanyang University, Ansan, Kyungki-Do, Korea as a Professor, Department of Mechanical Engineering. From March 1993 to February 1995, he was a Vice President, The Research Institute of Engineering & Technology of the Hanyang University. From August 1996 to July 1997, he was a Visiting Professor, Univ. of California at Berkeley. From September 1997 to February 1999, he was a Director, Hanyang Business Incubator. In August 2000, he joined a Branch President, The Korean Society of Mechanical Engineers. In January 2002, he joined a Committee Member, The Korean Society of Mechanical Engineers. From January 2001 to December 2001, he was an International Cooperation Director, The Institute of Control, Automation and Systems, Korea. His research interests include design, control, and application of robot, automation systems, and advanced vehicle.     

Fuzzy risk analysis based on the ranking of generalized trapezoidal fuzzy numbers

In this paper, we present a new method for fuzzy risk analysis based on the ranking of generalized trapezoidal fuzzy numbers. The proposed method considers the centroid points and the standard deviations of generalized trapezoidal fuzzy numbers for ranking generalized trapezoidal fuzzy numbers. We also use an example to compare the ranking results of the proposed method with the existing centroid-index ranking methods. The proposed ranking method can overcome the drawbacks of the existing centroid-index ranking methods. Based on the proposed ranking method, we also present an algorithm to deal with fuzzy risk analysis problems. The proposed fuzzy risk analysis algorithm can overcome the drawbacks of the one we presented in [7]. Shi-Jay Chen was born in 1972, in Taipei, Taiwan, Republic of China. He received the B.S. degree in information management from the Kaohsiung Polytechnic Institute, Kaohsiung, Taiwan, and the M.S. degree in information management from the Chaoyang University of Technology, Taichung, Taiwan, in 1997 and 1999, respectively. He received the Ph.D. degree at the Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, in October 2004. His research interests include fuzzy systems, multicriteria fuzzy decisionmaking, and artificial intelligence. Shyi-Ming Chen was born on January 16, 1960, in Taipei, Taiwan, Republic of China. He received the Ph.D. degree in Electrical Engineering from National Taiwan University, Taipei, Taiwan, in June 1991. From August 1987 to July 1989 and from August 1990 to July 1991, he was with the Department of Electronic Engineering, Fu-Jen University, Taipei, Taiwan. From August 1991 to July 1996, he was an Associate Professor in the Department of Computer and Information Science, National Chiao Tung University, Hsinchu, Taiwan. From August 1996 to July 1998, he was a Professor in the Department of Computer and Information Science, National Chiao Tung University, Hsinchu, Taiwan. From August 1998 to July 2001, he was a Professor in the Department of Electronic Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan. Since August 2001, he has been a Professor in the Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan. He was a Visiting Scholar in the Department of Electrical Engineering and Computer Science, University of California, Berkeley, in 1999. He was a Visiting Scholar in the Institute of Information Science, Academia Sinica, Republic of China, in 2003. He has published more than 250 papers in referred journals, conference proceedings and book chapters. His research interests include fuzzy systems, information retrieval, knowledge-based systems, artificial intelligence, neural networks, data mining, and genetic algorithms. Dr. Chen has received several honors and awards, including the 1994 Outstanding Paper Award o f the Journal of Information and Education, the 1995 Outstanding Paper Award of the Computer Society of the Republic of China, the 1995 and 1996 Acer Dragon Thesis Awards for Outstanding M.S. Thesis Supervision, the 1995 Xerox Foundation Award for Outstanding M.S. Thesis Supervision, the 1996 Chinese Institute of Electrical Engineering Award for Outstanding M.S. Thesis Supervision, the 1997 National Science Council Award, Republic of China, for Outstanding Undergraduate Student's Project Supervision, the 1997 Outstanding Youth Electrical Engineer Award of the Chinese Institute of Electrical Engineering, Republic of China, the Best Paper Award of the 1999 National Computer Symposium, Republic of China, the 1999 Outstanding Paper Award of the Computer Society of the Republic of China, the 2001 Institute of Information and Computing Machinery Thesis Award for Outstanding M.S. Thesis Supervision, the 2001 Outstanding Talented Person Award, Republic of China, for the contributions in Information Technology, the 2002 Institute of information and Computing Machinery Thesis Award for Outstanding M.S. Thesis Supervision, the Outstanding Electrical Engineering Professor Award granted by the Chinese Institute of Electrical Engineering (CIEE), Republic of China, the 2002 Chinese Fuzzy Systems Association Best Thesis Award for Outstanding M.S. Thesis Supervision, the 2003 Outstanding Paper Award of the Technological and Vocational Education Society, Republic of China, the 2003 Acer Dragon Thesis Award for Outstanding Ph.D. Dissertation Supervision, the 2005 “Operations Research Society of Taiwan” Award for Outstanding M.S. Thesis Supervision, the 2005 Acer Dragon Thesis Award for Outstanding Ph.D. Dissertation Supervision, the 2005 Taiwan Fuzzy Systems Association Award for Outstanding Ph.D. Dissertation Supervision, and the 2006 “Operations Research Society of Taiwan” Award for Outstanding M.S. Thesis Supervision. Dr. Chen is currently the President of the Taiwanese Association for Artificial Intelligence (TAAI). He is a Senior Member of the IEEE, a member of the ACM, the International Fuzzy Systems Association (IFSA), and the Phi Tau Phi Scholastic Honor Society. He was an administrative committee member of the Chinese Fuzzy Systems Association (CFSA) from 1998 to 2004. He is an Associate Editor of the IEEE Transactions on Systems, Man, and Cybernetics - Part C, an Associate Editor of the IEEE Computational Intelligence Magazine, an Associate Editor of the Journal of Intelligent & Fuzzy Systems, an Editorial Board Member of the International Journal of Applied Intelligence, an Editor of the New Mathematics and Natural Computation Journal, an Associate Editor of the International Journal of Fuzzy Systems, an Editorial Board Member of the International Journal of Information and Communication Technology, an Editorial Board Member of the WSEAS Transactions on Systems, an Editor of the Journal of Advanced Computational Intelligence and Intelligent Informatics, an Associate Editor of the WSEAS Transactions on Computers, an Editorial Board Member of the International Journal of Computational Intelligence and Applications, an Editorial Board Member of the Advances in Fuzzy Sets and Systems Journal, an Editor of the International Journal of Soft Computing, an Editor of the Asian Journal of Information Technology, an Editorial Board Member of the International Journal of Intelligence Systems Technologies and Applications, an Editor of the Asian Journal of Information Management, an Associate Editor of the International Journal of Innovative Computing, Information and Control, and an Editorial Board Member of the International Journal of Computer Applications in Technology. He was an Editor of the Journal of the Chinese Grey System Association from 1998 to 2003. He is listed in International Who's Who of Professionals, Marquis Who's Who in the World, and Marquis Who's Who in Science and Engineering.     

Sixty years of cybernetics

Fundamental aspects of cybernetics, such as goals, problems, methods, tools, brief history, and correlation with other sciences, are considered. Cybernetics in its classical interpretation is the science of information management, communication, and processing. As cybernetics developed, this definition was formalized as the science of methods and processes of information acquisition, storage, processing, analysis, and evaluation, which allows it to apply to decision making in complex control systems. These systems include all engineering, biological, administrative, social, ecological, and economical systems. The main thesis that determined the goals, problems, subject matter, and development of cybernetics as a whole up to the present is the similarity in management and communication processes in machines, living organisms, and both animal and human societies. First of all, these are processes of transfer, storage, and processing of information, i.e., various signals, messages, and data. Any signal and any information may be considered independently from its particular content and destination as a certain choice between two or more values having the known probabilities (selective concept of information). It allows us to treat all processes on the basis of a unified measure and statistical apparatus. The idea of the general theory of control and communication, that is, cybernetics, is based on this hypothesis.     

Nondegeneracy tests for hexahedral cells

The aims of the paper are to consider the nondegeneracy requirement for computational grids and to analyze eight tests used to check the nondegeneracy of hexahedral cells. The paper starts with consideration of nondegeneracy requirement and formulation of definitions and common theorems utilized for estimation of nondegeneracy of grids both structured and unstructured. Then hexahedral cells are introduced and sufficient nondegeneracy conditions (Ushakova, 2000) for them are given. Sufficient nondegeneracy conditions are 27 inequalities for 32 tetrahedral volumes. Besides sufficient nondegeneracy conditions other conditions are applied as nondegeneracy tests in grid generation theory and practice. Considered nondegeneracy tests are the checks for positivity of different values. Tests 1, 2, 3, 4, 5, 6 check the positivity of 8, 10, 24, 32, 58, 48 tetrahedral volumes, correspondingly. Test 7 verifies the positivity of the volume of a cell. Test 8 checks the positivity of the Jacobian of the mapping used for generation of a cell. The check is performed at the corners of a cell and hex center. Tests 1, 7, 8 are often used in commercial packages. For the most part, nondegeneracy tests are not sufficient nondegeneracy conditions, however they are used for the purpose of constructing nondegenerate grids and, some times, instead of sufficient nondegeneracy conditions. The effectiveness and reliability of such substitutions are investigated in special numerical experiments with random numbers. In the numerical experiment for each test, hexahedral cells are generated randomly. Results of such experiments are the following. Among eight tests, test 2 is considered the best since it verifies the volumes of only 10 tetrahedra for positiveness, guarantees the nondegeneracy in most of cases (68.7% randomly generated hexahedral cells satisfying test 2) and covers a wide class of cells (about 60% of nondegenerate cells). Tests 1, 3, 4, 5, 6, 7, 8 have success in 31.7%, 83.1%, 100%, 100%, 39.5%, 0.2%, 34% of cases and cover 100%, 7.9%, 7.9%, 4.2%, 59.5%, 100%, 100% of nondegenerate cells, correspondingly. Because of high rate of success, tests 3, 4, 5 also can be used for grid generation purpose. All tests are illustrated by the examples of structured grids.     

Neural network algorithms for analyzing multidimensional time series for predicting events and their application to study of Sun-Earth relations

In the paper, an original neural network algorithm for analysis of time series is presented. This algorithm allows predicting the occurrence of a certain event and finding a time interval to which a phenomenon (a precursor or a cause of the event) belongs. The characteristics of the algorithm functioning are investigated applied to the study of the solar-terrestrial relationship. Yu. V. Orlov. Candidate in Physics and Mathematics. Researcher at the Institute of Nuclear Physics, Moscow State University. Scientific interests: neural networks, genetic algorithms, algorithms of pattern recognition and image analysis. Yu. S. Shugai. Researcher at the Institute of Nuclear Physics, Moscow State University. Scientific interests: neural networks, genetic algorithms, algorithms of pattern recognition and image analysis, algorithms of classification and prediction. I. G. Persiantsev. Professor, Doctor in Mathematics and Physics. Head of the Laboratory, Leading Researcher at the Institute of Nuclear Physics, Moscow State University Scientific interests: neural networks, genetic algorithms, algorithms of pattern recognition and image analysis, algorithms of classification and prediction, inverse problems. Laureate of the USSR State Prize. S. A. Dolenko. Candidate in Physics and Mathematics. Senior Researcher at the Institute of Nuclear Physics, Moscow State University. Scientific interests: neural networks, genetic algorithms, algorithms of pattern recognition and image analysis, algorithms of classification and prediction, inverse problems.     

Wiener estimation method in estimating of spectral reflectance from RGB images

Color is one of the most important features in digital images. The representation of color in digital form with a three-component image (RGB) is not very accurate, hence the use of a multiple-component spectral image is justified. At the moment, acquiring a spectral image is not as easy and as fast as acquiring a conventional three-component image. One answer to this problem is to use a regular digital RGB camera and estimate its RGB image into a spectral image by the Wiener estimation method, which is based on the use of a priori knowledge. In this paper, the Wiener estimation method is used to estimate the spectra of icons. The experimental results of the spectral estimation are presented. The text was submitted by the authors in English. Pekka Tapani Stigell. Year of birth 1976. Year of graduation and name of institution: Last year undergraduate student in the Department of Computer Science in the University of Joensuu, Finland. Affiliation: InFotoics Center, Department of Computer Science, University of Joensuu. Position: Trainee. Area of research: Color research. Number of publications: 1. Membership to scientific societies: Pattern Recognition Society of Finland, member-society of IAPR (International Association for Pattern Recognition). Prizes for achievements in research or applications: The best young scientist award in PRIA-7-2004 (shared with two other scientists). Kimiyoshi Miyata. Year of birth: 1966. Year of graduation and name of institution: 2000. Graduate School of Science and Technology, Chiba University, Japan. Year of graduation: 1990, BE degree (Chiba University), 1992, ME degree (Chiba University), 2000, Ph.D degree (Chiba University). Affiliation: Museum Science Division, Research Department, National Museum of Japanese History. Position: Assistant Professor. Area of research: Improvement of image quality, color management, application of imaging science and technology to museum activities. Number of publications: 11. Membership to scientific societies: Society of Photographic Science and Technology of Japan, Optical Society of Japan, Institute of Image Electronics Engineers of Japan, Society for Imaging Science and Technology. Prizes for achievements in research or applications: Progressing Award from Society of Photographic Science and Technology of Japan in 2000, Itek Award from Society for Imaging Science and Technology in 2000. Markku Hauta-Kasari. Year of birth: 1970. Graduation and name of the institution: University of Technology, Lappeenranta, Finland. Year of graduation: 1999, Ph.D. degree (University of Technology, Lappeenranta). Affiliation: InFotonics Center, Department of Computer Science, University of Joensuu. Position: Director. Area of research: Color research, neural computation, pattern recognition, optical pattern recognition, computer vision, image processing. Number of publications: Articles in refereed international scientific journals: 5, Articles in refereed international scientific conferences: 9, Other Scientific Publications: 40. Membership to academies: Chairman of the Pattern Recognition Society of Finland May 2003. Membership to scientific societies: Pattern Recognition Society of Finland, member-society of IAPR (International Association for Pattern Recognition), Finnish Information Processing Association, Finnish Union of University Researchers and Teachers, Optical Society of Japan, Optical Society of America. Prizes for achievements in research or applications: The best Ph.D.-thesis award in the field of pattern recognition in 1998–1999 in Finland. Award was issued by the Pattern Recognition Society of Finland on April 25, 2000.     

伦理智能体及其设计:现状和展望

智能体一直是人工智能的主要研究领域之一,任何独立的能够同环境交互并自主决策的实体都可以抽象为智能体.随着人工智能从计算智能到感知智能,再到认知智能的发展,智能体已逐步渗透到无人驾驶、服务机器人、智能家居、智慧医疗、战争武器等人类生活密切相关的领域.这些应用中,智能体与环境、尤其是与人类和社会的交互愈来愈突出,其中的伦理...     

On optimizing the satisfiability (SAT) problem

1IntroductionThesatisfiability(SAT)problemistodeterminewhetherthereexistsanassignmentofvaluesin{0,1}toasetofBooleanvariables{x1,xm}thatmakesaconjunctivenormalform(CNF)formulatrue.ThesatisfiabilityproblemofaCNFformulawithatmostlliteralsineachclauseiscalledthel-SATproblem.Theoretically,for>3,theSATproblemisawell-knownNP-completeproblem.Andthus,thereexistsnopolynomialtimealgorithmfortheSATproblemontheassumptionthatPNP.Ontheotherhand,theSATproblemisfundamentalinsolvingmanypracticalprob…     

Adaptive filtering under minimum information divergence criterion

Traditional filtering theory is always based on optimization of the expected value of a suitably chosen function of error, such as the minimum mean-square error (MMSE) criterion, the minimum error entropy (MEE) criterion, and so on. None of those criteria could capture all the probabilistic information about the error distribution. In this work, we propose a novel approach to shape the probability density function (PDF) of the errors in adaptive filtering. As the PDF contains all the probabilistic information, the proposed approach can be used to obtain the desired variance or entropy, and is expected to be useful in the complex signal processing and learning systems. In our method, the information divergence between the actual errors and the desired errors is chosen as the cost function, which is estimated by kernel approach. Some important properties of the estimated divergence are presented. Also, for the finite impulse response (FIR) filter, a stochastic gradient algorithm is derived. Finally, simulation examples illustrate the effectiveness of this algorithm in adaptive system training. Recommended by Editorial Board member Naira Hovakimyan under the direction of Editor Jae Weon Choi. This work was supported in part by the National Natural Science Foundation of China under grants 50577037 and 60604010. Badong Chen received the B.S. and M.S. degrees in Control Theory and Engineering from Chongqing University, Chongqing, China, in 1997 and 2003, respectively, and the Ph.D. degree in Computer Science and Technology from Tsinghua University, Beijing China, in 2008. He is currently a Postdoctor of the Institute of Manufacturing Engineering, Department of Precision Instruments and Mechanology, Tsinghua University, Beijing, China. His research interests are in signal processing, adaptive control, and information theoretic aspects of control systems. Yu Zhu received the B.S. of Radio Electronics in 1983 at Beijing Normal University, and the M.S. of Computer Applications in 1993, and the Ph.D. of Mechanical Design and Theory in 2001 at China University of Mining & Technology. He is now a Professor of the Institute of Manufacturing Engineering of Department of Precision and Mechanology of Tsinghua University. His current research interests are parallel machanism and theory, two photon micro-fabrication, ultra-precision motion system and motion control. Jinchun Hu received the Ph.D. in Control Science and Engineering from Nanjing University of Science and Technology, Nanjing, China, in 1998. Since then, he has been a postdoctoral researcher in Nanjing University of Aeronautics and Astronautics in 1999 and Tsinghua University in 2002 respectively. His research interests are in flight control, aerial Robot and intelligent control. Dr. Hu is currently an Associate Professor of the Department of Computer Science and Technology of Tsinghua University, Beijing, China. Zengqi Sun received the B.S. degree from the Department of Automatic Control, Tsinghua University, Beijing, China, in 1966 and the Ph.D. degree in Control Engineering from the Chalmas University of Technology, Sweden, in 1981. He is currently a Professor of the Department of Computer Science and Technology, Tsinghua University, Beijing, China. He is the author or coauthor of more than 100 paper and eight books on control and robotics. His research interests include robotics, intelligent control, fuzzy system, neural networks, and evolutionary computation.