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Naval Engineers Journal 2009年第5期112卷

作者： Dr. Roy L. Streit Since 1992 Dr. Streit has focused a significant amount of his energy to assignment problems in acoustic warfare data fusion systems. This work led him to the formulation of the PDD Principle a broadly useful theoretical method that enables the derivation of new classes of discrete-continuous estimation algorithms for solving assignment problems without requiring enumeration and pruning. In recognition of his outstanding work in this area Dr. Streit received the NAVSEA Scientist of the Year Award for 1997. Dr. Streit has also been pursuing avenues for analyzing the loss in broadband detection performance of an acoustic array in the presence of interferences. Because examining all possible separations between the signal and many interferers is infeasible he has proposed a Poisson process model for the number and location (s) of the interferers. In this same time period Dr. Streit has also been investigating issues in environmental modeling and localization by proposing a novel integral method for solving the bearings-only target motion analysis problem which enables a natural heuristic for compensating for mismatch between the model predictions and the real world. Most recently Dr. Streit has proposed the Numerical ACoustic Hull ARray (NACHAR) Project as a revolutionary and ambitious approach to hull array design. Its premise is that optimizing the detection capability of large hull arrays requires the full integration of hull sensor array and beamformer design processes. Because NACHAR crosses an unusual number of technical disciplines it involves researchers from several departments. The diversity of Dr. Streif s technical background makes him uniquely suited to lead the project Dr. Streifs truly impressive scientific achievements are complemented by a noteworthy list of professional activities that accentuate his value to Division Newport and the Navy. He represents the United States in The Technical Cooperation Program Maritime Activities Panel 9 (Sonar Technology) and participates in the Division New

for his significant engineering research and development in sonar array research and acoustic transient signals as set forth in the following

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Contributors to the Lab on a Chip cell and tissue engineering in microsystems special issue

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Lab on a Chip 2007年第6期7卷 667-671页

作者： Bhatia, Sangeeta N. Chen, Christoper Bashir, Rashid Beebe, David J. Desai, Tejal Gottwald, Eric Khademhosseini, Ali Langer, Robert S. Piel, Matthieu Takayama, Shuichi Thorsen, Todd Tien, Joe Voldman, Joel Vunjak-Novakovic, Gordana Wu, Mingming Yu, Hanry Massachusetts Institute of Technology Harvard-MIT Division of Health Sciences and Technology Department of Electrical Engineering and Computer Science United States Laboratory for Multiscale Regenerative Technologies United States Department of Innovation University of Pennsylvania Department of Bioengineering United States Cell Biology and Physiology Program Cell Growth and Cancer Program Tissue Microfabrication Laboratory Department of Electrical and Computer Engineering and Biomedical Engineering Purdue University United States Department of Electronics University of Glasgow United Kingdom Department of Physiology and Bioengineering University of California San Francisco CA United States California Institute for Quantitative Biomedical Research UCSF/UC Berkeley Graduate Group in Bioengineering United States Laboratory of Therapeutic Micro and Nanotechnology Institute for Biological Interfaces Germany 3D-Cell Culture Techniques Group Institute for Biological Interfaces Germany Department of Medicine and Health Sciences and Technology Massachusetts Institute of Technology (MIT) United States Institut Curie UMR 144 IC/CNRS France Biomedical Engineering Department University of Michigan United States Department of Biomedical Engineering Macromolecular Science and Engineering Program United States Sibley School of Mechanical and Aerospace Engineering School of Chemical and Molecular Engineering Cornell University United States National University of Singapore Singapore Institute of Bioengineering and Nanotechnology A STAR Singapore

A graphical abstract is available for this content

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MODELING AND CONTROL OF ELEVATORS BY STATECHARTS

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Asian Journal of Control 2008年第2期6卷

作者： Yi-Sheng Huang Sheng-Luen Chung Mu-Der Jeng Department of Aeronautical Engineering Chung Cheng Institute of Technology National Defense University Tashi Taoyuan 335 Taiwan R.O.C. Department of Electrical Engineering National Taiwan University of Science and Technology Taipei 106 Taiwan R.O.C. Department of Electrical Engineering National Taiwan Ocean University Kellung 202 Taiwan R.O.C. MuDer Jeng received the Ph.D. degree in computer and systems engineering from Rensselaer Polytechnic Institute Troy NY in 1992. Since August 1992 Dr. Jeng has been with National Taiwan Ocean University Keelung Taiwan where he is currently a full Professor at the Department of Electrical Engineering. His current research interests include Petri nets discrete event systems computer integrated manufacturing semiconductor factory automation embedded systems. Dr. Jeng is the author/co-author of over 120 book chapters journal papers and conference papers. Dr. Jeng received the Franklin V. Taylor Outstanding Paper Award from the IEEE Systems Man and Cybernetics Society in 1993. He was granted the Research Award by the National Science Council of Taiwan annually from 1994 to 2000. He is an Associate Editor for IEEE Transactions on Systems Man and Cybernetics-Part A IEEE Transactions on Robotics and Automation IEEE Transactions on Robotics and serves on the Editorial Board of International Journal of Computer Integrated Manufacturing. He has been a Guest Editor for eight leading journals. Dr. Jeng is the Chair of the Technical Committee on Discrete Event Systems of the IEEE SMC Society and the Founding Chair of the Technical Committee on Semiconductor Factory Automation of the IEEE Robotics and Automation Society. He served as the Exhibitions Chair of 2003 IEEE International Conference on Robotics and Automation and the Special Sessions Chair of 2004 IEEE International Conference on Networking Sensing and Control. He serves as a Program Co-Chair of 2005 IEEE International Conference on Networking Sensing and Control and the Organization Commit

Statechart has been utilized as a visual formalism for the modeling of complex and interactive systems for its illuminating features on describing properties of causality, concurrency, and synchronization. This paper presents the application of satechart to the modeling, design and implementation of an elevator system, whose system behavior involves aggregating complexity of state descriptions, and imposition of underlying control policy. Based on the operational flow of an elevator, we derive the associated statechart model by looking into the inherent hierarchical structure of the elevator. The advantage of the proposed approach is the clear presentation of system behavior in terms of conditions and events that cause the transitions in system dynamics. Implementation of the controlled elevator based on the modeled statechart is also presented.

关键词： Statechart interactive systems elevator

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

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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

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Decision Fusion of Circulating Markers for Breast Cancer Detection in Premenopausal Women

Decision Fusion of Circulating Markers for Breast Cancer Det...

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IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： Jonathan L. Jesneck Sayan Mukherjee Loren W. Nolte Anna E. Lokshin Jeffrey R. Marks Joseph Lo Duke Advanced Imaging Labs Institute for Genome Sciences and Policy Department of Computer Science Duke University USA Department of Electrical and Computer Engineering Division of Hematology/Oncology University of Pittsburgh School of Medicine Pittsburgh PA USA Division of Hematology/Oncology University of Pittsburgh Cancer Institute Pittsburgh PA USA Division of Hematology/Oncology University of Pittsburgh Cancer Institute Pittsburgh PA Institute for Genome Sciences and Policy Department of Experimental Surgery Medical Center Duke University USA Department of Experimental Surgery Duke University Medical Center Medical Physics Graduate Program Duke University Durham NC USA

Current mammographic screening for breast cancer is less effective for younger women. To complement mammography for premenopausal women, we investigated the feasibility screening test using 98 blood serum proteins. Because the data set was very noisy and contained only weak features, we used a classifier designed for noisy data: decision fusion. Decision fusion outperformed both a support vector machine (SVM) and linear regression with forward stepwise feature selection on all three two-class classification tasks: normal tissue vs. cancer, normal tissue vs. benign lesions, and benign lesions vs. cancer. Decision fusion detected cancer moderately well (AUC=0.84 on normal vs. cancer), demonstrating promise as a screening tool. Decision fusion also detected benign lesions similarly well (AUC=0.83 on normal vs. benign lesions) and was the only classifier to achieve any success in separating benign from malignant lesions (AUC=0.64 on benign vs. cancer). The classification results suggest that the assayed proteins are more indicative of a secondary effect, such as immune response, rather than specific for breast cancer. In conclusion, the decision fusion classifier demonstrated some promise in detecting breast lesions and outperformed other classifiers, especially for the very noisy classification problem of distinguishing benign from malignant lesions.

关键词： Breast cancer Cancer detection Lesions Proteins Support vector machines Support vector machine classification Mammography Testing Blood Linear regression

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Carbon nanostructure field emission devices

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Journal of Vacuum science and Technology B: Microelectronics and Nanometer Structures 2006年第2期24卷 1008-1012页

作者： Wong, Y.M. Kang, W.P. Davidson, J.L. Soh, K.L. Choi, B.K. Hofmeister, W. Department of Electrical Engineering and Computer Science Vanderbilt University Nashville TN 37235 Interdisciplinary Graduate Program in Material Science Vanderbilt University Nashville TN 37235 Department of Chemical Engineering Vanderbilt University Nashville TN 37235

The microwave plasma chemical vapor deposition (MPCVD) method is capable of synthesizing various forms of carbon allotropes such as diamond, carbon nanotubes (CNTs), and diamondlike carbon (DLC) while varying the growth parameters or utilizing substrate coated with catalytic thin film. In this article, needlelike carbon nanostructures (CNs) were synthesized utilizing high power (5 kW) and high working pressure (120 Torr) MPCVD on a thin catalytic film of nickel with a diffusion barrier layer of titanium on a micropatterned silicon substrate. The effects of in situ doping by trimethylboron (TMB) on the morphologies and field emission properties of the CNs were also investigated. Straight, needlelike CNs with random orientation were obtained for 15 min growth time with or without TMB doping. However, the CNs appear to transform into diamondlike nanocrystals after prolonged growth of 30 min with TMB doping. Unlike MPCVD grown CNTs, it was found that the CNs have strong adhesion to the substrate and could withstand postgrowth processing such as ultrasonic agitation cleaning in solvents. Field emission tests performed show that in situ TMB doping of the patterned needlelike CNs lowers the turn-on field of the cathode. A vacuum field emission triode with self-aligned gate utilizing CNs as the field emitter is also fabricated. © 2006 American Vacuum Society.

关键词： Carbon nanotubes

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Genetic programming with incremental learning for grammatical inference

Genetic programming with incremental learning for grammatica...

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6th international Conference on Hybrid Intelligent Systems and 4th Conference on Neuro-Computing and Evolving Intelligence, HIS-NCEI 2006

作者： Rodrigues, Ernesto Lopes, Heitor Silvério Graduate Program in Electrical Engineering and Computer Science Federal University of Technology - Paraná Av. 7 de setembro 3165 80230-901 Curitiba Brazil

ISBN: (纸本)0769526624

We present an evolutionary algorithm for the inference of context-free grammars from positive and negative examples. The algorithm is based on genetic programming and uses a local optimization operator that is capable of improving the learning task. Ordinary genetic operators are modified so as to bias the search. The system was evaluated using Tomita 's language examples and results were compared with another similar approach. Results show that the proposed approach is promising and more robust than the other one. © 2006 IEEE.

关键词： Context free grammars

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GA optimization of OBF TS fuzzy models with linear and non linear local models

GA optimization of OBF TS fuzzy models with linear and non l...

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9th Brazilian Symposium on Neural Networks, SBRN'06

作者： Medeiros, Anderson V. Amaral, Wagner C. Campello, Ricardo J. G. B. State University of Campinas School of Electrical and Computer Engineering Campinas SP 13083-970 Brazil Catholic University of Santos Graduate Program in Computer Science Santos SP 11070-906 Brazil

ISBN: (纸本)0769526802

OBF (Orthonormal Basis Function) Fuzzy models have shown to be a promising approach to the areas of nonlinear system identification and control since they exhibit several advantages over those dynamic model topologies usually adopted in the literature. Although encouraging application results have been obtained, no automatic procedure had yet been developed to optimize the design parameters of these models. This paper elaborates on the use of a genetic algorithm (GA) especially designed for this task, in which a fitness function based on the Akaike information criterion plays a key role by considering both model accuracy and parsimony aspects. The use of linear (actually affine) and nonlinear local models is also investigated. The proposed methodology is evaluated in the modeling of a real nonlinear magnetic levitation system. © 2006 IEEE.

关键词： Fuzzy sets

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Genetic programming with Incremental Learning for Grammatical Inference

Genetic Programming with Incremental Learning for Grammatica...

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international Conference on Hybrid Intelligent Systems (HIS)

作者： Ernesto Rodrigues Heitor Silverio Lopes Graduate Program in Electrical Engineering and Computer Science Federal University of Technology of Paraná (UTFPR) Curitiba Brazil

We present an evolutionary algorithm for the inference of context-free grammars from positive and negative examples. The algorithm is based on genetic programming and uses a local optimization operator that is capable of improving the learning task. Ordinary genetic operators are modified so as to bias the search. The system was evaluated using Tomitas language examples and results were compared with another similar approach. Results show that the proposed approach is promising and more robust than the other one.

关键词： Grammar Production Genetic programming Sociology Statistics Inference algorithms

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GA Optimization of OBF TS Fuzzy Models with Linear and Non Linear Local Models

GA Optimization of OBF TS Fuzzy Models with Linear and Non L...

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Brazilian Symposium on Neural Networks

作者： Anderson V. Medeiros Wagner C. Amaral Ricardo J. G. B. Campello School of Electrical and Computer Engineering State University of Campinas Sao Paulo Brazil Graduate Program in Computer Science Catholic University of Santos Sao Paulo Brazil

ISBN: (纸本)9780769531960

关键词： Fuzzy control Fuzzy systems Nonlinear systems Control system synthesis Automatic control Nonlinear control systems Nonlinear dynamical systems Topology Design optimization Genetic algorithms

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