检索结果-内蒙古大学图书馆

114th Annual ASEE Conference and Exposition, 2007

作者： Eschenbach, Elizabeth Montgomery, Jami Johnson, James Brus, Chris Carlson, Patricia Giammar, Dan Grauer, Bette Hotaling, Liesl Oguntimein, Gbekeloluwa Safferman, Steven Wentling, Tim Humboldt State University United States Department of Environmental Resources Engineering Humboldt State University United States WATERS Network - CLEANER Project Office Network Howard University United States Department of Environmental Engineering College of Engineering Architecture and Computer Sciences Howard University United States American Academy of Environmental Engineers United States University of Iowa United States Program University of Iowa United States Rose-Hulman Institute of Technology United States Department of Rhetoric Rose-Hulman Institute of Technology United States National Research Council U. S. Air Force United States NASA's Classroom of the Future Wheeling WV United States Washington University United States Department of Energy Environmental and Chemical Engineering Washington University St. Louis United States Environmental Studies Program Center for Materials Innovation United States McPherson High School United States McPherson High School McPherson KS United States Stevens Institute of Technology United States Stevens Institute of Technology United States Morgan State University United States Michigan State University United States Biosystems and Agricultural Engineering Department Michigan State University United States University of Dayton United States Education Planning Committee National Center for Supercomputing Applications United States Department of Information Science Graduate School of Library and Information Science National Center for Supercomputing Applications University or Illinois United States Knowledge and Learning Systems Group NCSA United States

The WATERS Network (WATer and Environmental Research Systems Network) will be an integrated real-time distributed observing system which will enable academic and government scientists, engineers, educators, and practitioners to advance effective management of our nation's water resources by understanding human interactions with water and the natural and built environment. WATERS will provide easily accessible real time environmental data as well as analysis tools to engineers, scientists, educators, K- graduate students and policymakers so they can better understand how water quantity, quality and related components of the hydrologic cycle are impacted by natural and human influences. The WATERS strategic plan will be completed by July 2007 and requires constituent input. This paper describes the draft Conceptual Design and the Education Plan of WATERS Network. This paper will highlight the potential impact of WATERS on undergraduate and graduate environmental engineering education in order to elicit input from the environmental engineering education community on how WATERS Network could better meet the future needs of undergraduate and graduate students and educators. More information can be found at ***. © American Society for engineering Education, 2007.

关键词： Water resources

来源：评论

学校读者我要写书评

暂无评论

LANDING AN UNMANNED AIR VEHICLE: VISION BASED MOTION ESTIMATION AND NONLINEAR CONTROL

引用

Asian Journal of Control 2008年第3期1卷

作者： Omid Shakernia Yi Ma T. John Koo Shankar Sastry Dept. of Electrical Engineering & Computer Science University of California at Berkeley Berkeley CA94720-1774 U.S.A. Tak-Kuen John Koo received the B.Eng. degree in 1992 in Electronic Engineering and the M.Phil. in 1994 in Information Engineering both from the Chinese University of Hong Kong. From 1994 to 1995 he was a graduate student in Signal and Image Processing Institute at the University of Southern California. He is currently a Ph.D. Candidate in Electrical Engineering and Computer Sciences at the University of California at Berkeley. His research interests include nonlinear control theory hybrid systems inertial navigation systems with applications to unmanned aerial vehicles. He received the Distinguished M.Phil. Thesis Award of the Faculty of Engineering The Chinese University of Hong Kong in 1994. He was a consultant of SRI International in 1998. Currently he is the team leader of the Berkeley AeRobot Team and a delegate of The Graduate Assembly University of California at Berkeley. He is a student member of IEEE and SIAM. S. Shankar Sastry received his Ph.D. degree in 1981 from the University of California Berkeley. He was on the faculty of MIT from 1980-82 and Harvard University as a Gordon McKay professor in 1994. He is currently a Professor of Electrical Engineering and Computer Sciences and Bioengineering and Director of the Electronics Research Laboratory at Berkeley. He has held visiting appointments at the Australian National University Canberra the University of Rome Scuola Normale and University of Pisa the CNRS laboratory LAAS in Toulouse (poste rouge) and as a Vinton Hayes Visiting fellow at the Center for Intelligent Control Systems at MIT. His areas of research are nonlinear and adaptive control robotic telesurgery control of hybrid systems and biological motor control. He is a coauthor (with M. Bodson) of “Adaptive Control: Stability Convergence and Robustness Prentice Hall 1989.” and (with R. Murray and Z. Li) of “A Mathematical Introduction to Robotic Manipulati

In this paper, we use computer vision as a feedback sensor in a control loop for landing an unmanned air vehicle (UAV) on a landing pad. The vision problem we address here is then a special case of the classic ego-motion estimation problem since all feature points lie on a planar surface (the landing pad). We study together the discrete and differential versions of the ego-motion estimation, in order to obtain both position and velocity of the UAV relative to the landing pad. After briefly reviewing existing algorithm for the discrete case, we present, in a unified geometric framework, a new estimation scheme for solving the differential case. We further show how the obtained algorithms enable the vision sensor to be placed in the feedback loop as a state observer for landing control. These algorithms are linear, numerically robust, and computationally inexpensive hence suitable for real-time implementation. We present a thorough performance evaluation of the motion estimation algorithms under varying levels of image measurement noise, altitudes of the camera above the landing pad, and different camera motions relative to the landing pad. A landing controller is then designed for a full dynamic model of the UAV. Using geometric nonlinear control theory, the dynamics of the UAV are decoupled into an inner system and outer system. The proposed control scheme is then based on the differential flatness of the outer system. For the overall closed-loop system, conditions are provided under which exponential stability can be guaranteed. In the closed-loop system, the controller is tightly coupled with the vision based state estimation and the only auxiliary sensor are accelerometers for measuring acceleration of the UAV. Finally, we show through simulation results that the designed vision-in-the-loop controller generates stable landing maneuvers even for large levels of image measurement noise. Experiments on a real UAV will be presented in future work.

关键词： Motion estimation computer vision based control unmanned air vehicle differential flatness

来源：评论

学校读者我要写书评

暂无评论

Special Issue on Variable Structure System Control — New Designs and applications

引用

Asian Journal of Control 2008年第4期5卷

作者： Prof. Jian-Xin Xu Prof. Leonid Fridman Department of Electrical and Computer Eng. National University of Singapore 4 Engineering Drive 3 Singapore 117576 Tel +65 6874-2566 Fax +65 6779-1103 Dr Jian-Xin Xu received his Bachelor degree from Zhejiang University China in 1982. He attended the University of Tokyo Japan where he received his Master's and Ph.D. degrees in 1986 and 1989 respectively. All his degrees are in Electrical Engineering. He worked for one year in the Hitachi research Laboratory Japan and for more than one year in Ohio State University U.S.A. as a Visiting Scholar. In 1991 he joined the National University of Singapore and is currently an associate professor in the Department of Electrical Engineering. His research interests lie in the fields of learning control variable structure control fuzzy logic control discontinuous signal processing and applications to motion control and process control problems. He is the associate editor of Asian Journal of Control member of TC on variable structure systems and sliding mode control of IEEE Control Systems Society and a senior member of IEEE. He has produced more than 90 peer-refereed journal papers near 160 technical papers in conference proceedings and authored/edited 4 books. Division de Estudios de Posgrado Facultad de Ingenieria National Autonomous University of Mexico DEP-FI UNAM Edificio “A” Circuito Exterior Ciudad Universitaria A. P. 70–256 C.P.04510 Mexico D.F. Mexico Tel +52 55 56223014 Fax +52 55 56161719 Dr. Leonid M. Fridman received his M.S in mathematics from Kuibyshev (Samara) State University Russia Ph.D. in Applied Mathematics from Institute of Control Science (Moscow) and Dr. of Science degrees in Control Science from Moscow State University of Mathematics and Electronics in 1976 1988 and 1998 respectively. In 1976–1999 Dr. Fridman was with the Department of Mathematics at the Samara State Architecture and Civil Engineering Academy Samara Russia. In 2000–2002 he was with the Department of Postgraduate Study and Investigations at the Chihuahu

来源：评论

学校读者我要写书评

暂无评论

High capacity lossless secure image a steganography using wavelets

High capacity lossless secure image a steganography using wa...

引用

14th International Conference on Advanced Computing and Communications, ADCOM 2006

作者： Raja, K.B. Vikas Venugopal, K.R. Patnaik, L.M. Department of Computer Science Engineering University Visvesvaraya College of Engineering Bangalore University Bangalore India Microprocessor Applications Laboratory Indian Institute of Science Bangalore India

ISBN: (纸本)142440715X

The modern steganography presents a challenging task of embedding data that should be imperceptible to the Human Visual System (HVS) and also escape the detection of powerful machine vision of computers. In this paper we present a high capacity, lossless, secure wavelet steganographic algorithm in which Payload bitstream is encrypted and embedded into the wavelet coefficients of the cover image to derive a stego-image. The payload is embedded in the Approximation band of the wavelet domain that increases its robustness. It is observed through simulations that Mean Square Error (MSE), Mean Absolute Error (MAE), Bit Error Rate (BER) and Histogram analysis that the pay load is retrieved without any errors and its performance is better than the earlier Insignificant Coefficient Replacement (ICR) technique. © 2006 IEEE.

关键词： Steganography

来源：评论

学校读者我要写书评

暂无评论

Indexing XML documents using self adaptive genetic algorithms for better retrieval

Indexing XML documents using self adaptive genetic algorithm...

引用

8th Asia-Pacific Web Conference, APWeb 2006: Frontiers of WWW Research and Development

作者： Srinivasa, K.G. Sharath, S. Venugopal, K.R. Patnaik, Lalit M. Department of Computer Science and Engineering University Visvesvaraya College of Engineering Bangalore - 560001 India Infosys Technologies Bangalore India Microprocessor Applications Laboratory Indian Institute of Science India

ISBN: (纸本)3540311424

The next generation of web is often characterized as the Semantic Web. Machines which are adept in processing data, will also perceive the semantics of the data. The XML technology, with its self describing and extensible tags, is significantly contributing to the semantic web. In this paper, a framework for information retrieval from XML documents using Self Adaptive Migration model Genetic Algorithms(SAGAXsearch) is proposed. Experiments on real data performed to evaluate the precision and the query execution time indicate that the framework is accurate and efficient compared to the existing techniques. © Springer-Verlag Berlin Heidelberg 2006.

关键词： XML

来源：评论

学校读者我要写书评

暂无评论

An m-ary tree based frequent temporal pattern (FTP) mining algorithm

An m-ary tree based frequent temporal pattern (FTP) mining a...

引用

2006 Annual India Conference, INDICON

作者： Gopalan, N.P. SivaSelvan, B. Department of Computer Applications National Institute of Technology Tiruchirapalli Tamil Nadu 620015 India Department of Computer Science and Engineering National Institute of Technology Tiruchirappali Tamil Nadu 620015 India

ISBN: (纸本)1424403707

Frequent Set Mining (FSM), an important phase of Association Rule Mining, is the process of generating frequent sets that satisfy a specified minimum support threshold. This paper explores FSM in temporal data domain or FTP mining and proposes an efficient algorithm for the same. Existing algorithms for FTP mining are based on Apriori's level wise principle. In conventional or transactional data domain, Apriori has been proven to suffer from the repeated scans limitation and has been succeeded by several algorithms that overcome the setback. The proposed algorithm eliminates Apriori's repeated scans limitation in temporal domain, requiring only two overall scans of the original input. Experimental results demonstrate the significant improvements in execution time of the proposed algorithm as opposed to the Apriori based one. © 2006 IEEE.

关键词： Trees (mathematics)

来源：评论

学校读者我要写书评

暂无评论

Automatic Road Extraction Using Particle Filters from High Resolution Images

引用

Journal of China University of Mining and Technology 2006年第4期16卷 490-493页

作者： YE Fa-mao SU Lin TANG Jiang-long Department of Computer Science and Engineering Nanchang University Nanchang Jiangxi 330029 China Institute of Remote Sensing Applications Chinese Academy of Sciences Beijing 100101 China East China Institute of Technology Fuzhou Jiangxi 344000 China

Road extraction plays an important role in many applications such as car navigation, but the manual extraction of roads is a laborious, tedious task. To speed the extraction of roads, an approach based on particle filtering to extract automatically roads from high resolution imagery is proposed. Particle filtering provides a statistical framework for propagating sample-based approximations of posterior distributions and has almost no restriction on the ingredients of the model. We integrate the similarity of grey value and the edge point distribution of roads into particle filtering to deal with complex scenes. To handle road appearance changes the tracking algorithm is allowed to update the road model during temporally stable image observations. A fully automatic initialization strategy is used. Experimental results show that the proposed approach is a promising and fully automatic method for extracting roads from images, even in the presence of occlusions.

关键词： road extraction particle filters high resolution images

来源：评论

学校读者我要写书评

暂无评论

Online testing and assessment of textual responses using NOVEL

引用

Information Technology Journal 2006年第6期5卷 1018-1022页

作者： Selvi, P. Gopalan, N.P. Department of Computer Science and Engineering National Institute of Technology Tiruchirapalli India Department of Computer Applications National Institute of Technology Tiruchirapalli India

Testing and assessment remain an integral part of instructional systems design for traditional classroom based courses as well as online training courses. The goal of testing is to determine if learning objectives have been accomplished. Formative evaluation using online testing helps students assess their level of knowledge of course material. In addition it gives the instructor a better idea of what students understand as well as the concepts that still need clarification. This study proposed NOVEL algorithm, a method to assess the short essays written by students. It is a statistical method for inferring meaning from a text. We conclude that, although it is only applicable to a restricted category of questions, NOVEL attains better results than other keyword-based procedures. Its simplicity and language-independence makes it is a good candidate to be combined with other well-studied computer assessment scoring procedures. This study explains how NOVEL works and explains how NOVEL is particularly suited to web-assessment. © 2006 Asian Network for Scientific Information.

关键词： computer aided instruction

来源：评论

学校读者我要写书评

暂无评论

An efficient fuzzy based neuro – genetic algorithm for stock market prediction

引用

International Journal of Hybrid Intelligent Systems 2006年第2期3卷 63-81页

作者： Srinivasa, K.G. Venugopal, K.R. Patnaik, L.M. Department of Computer Science and Engineering University Visvesvaraya College of Engineering Bangalore 560001 India Microprocessor Applications Laboratory Indian Institute of Science Bangalore 560012 India

Stock market prediction is a complex and tedious task that involves the processing of large amounts of data, that are stored in ever growing databases. The vacillating nature of the stock market requires the use of data mining techniques like clustering for stock market analysis and prediction. Genetic algorithms and neural networks have the ability to handle complex data. In this paper, we propose a fuzzy based neuro-genetic algorithm – Fuzzy based Evolutionary Approach to Self Organizing Map(FEASOM) to cluster stock market data. Genetic algorithms are used to train the Kohonen network for better and effective prediction. The algorithm was tested on real stock market data of companies like Intel, General Motors, Infosys, Wipro, Microsoft, IBM, etc. The algorithm consistently outperformed regression model, backpropagation algorithm and Kohonen network in predicting the stock market values.

关键词： Machine learning Kohonen network genetic algorithms data mining prediction clustering

来源：评论

学校读者我要写书评

暂无评论

Sensor fusion for 3D human body tracking with an articulated 3D body model

Sensor fusion for 3D human body tracking with an articulated...

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： S. Knoop S. Vacek R. Dillmann Industrial Applications of Informatics and Microsystems Institute of Computer Science and Engineering University of Karlsruhe Germany

This paper proposes a tracking system called VooDoo for 3D tracking of human body movements based on a 3D body model and the iterative closest point (ICP) algorithm. The proposed approach is able to incorporate raw data from different input sensors, as well as results from feature trackers in 2D or 3D. All input data is processed within the same model fitting step by modeling all input measurements in 3D model space. The system has been implemented and runs in realtime at appr. 10-14 Hz. Experiments with complex human movements exhibit the characteristics and advantages of the proposed approach

关键词： Sensor fusion Biological system modeling Tracking Sensor systems Magnetic sensors Human robot interaction Robot sensing systems Image reconstruction Cameras computer industry

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：