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Workshop on imaging science development for cancer prevention and preemption

Cancer Biomarkers 2007年第1期3卷 1-33页

作者： Kelloff, Gary J. Sullivan, Daniel C. Baker, Houston Clarke, Lawrence P. Nordstrom, Robert Tatum, James L. Dorfman, Gary S. Jacobs, Paula Berg, Christine D. Pomper, Martin G. Birrer, Michael J. Tempero, Margaret Higley, Howard R. Petty, Brenda Gumbs Sigman, Caroline C. Maley, Carlo Sharma, Prateek Wax, Adam Ginsberg, Gregory G. Dannenberg, Andrew J. Hawk, Ernest T. Messing, Edward M. Grossman, H. Barton Harisinghani, Mukesh Bigio, Irving J. Griebel, Donna Henson, Donald E. Fabian, Carol J. Ferrara, Katherine Fantini, Sergio Schnall, Mitchell D. Zujewski, Jo Anne Hayes, Wendy Klein, Eric A. DeMarzo, Angelo Ocak, Iclal Ketterling, Jeffrey A. Tempany, Clare Shtern, Faina Parnes, Howard L. Gomez, Jorge Srivastava, Sudhir Szabo, Eva Lam, Stephen Seibel, Eric J. Massion, Pierre McLennan, Geoffrey Cleary, Kevin Suh, Robert Burt, Randall W. Pfeiffer, Ruth M. Hoffman, John M. Roy, Hemant K. Wang, Thomas Limburg, Paul J. El-Deiry, Wafik S. Papadimitrakopoulou, Vali Hittelman, Walter N. MacAulay, Calum Veltri, Robert W. Solomonzz, Diane Jeronimo, Jose Richards-Kortum, Rebecca Johnson, Karen A. Viner, Jaye L. Stratton, Steven P. Rajadhyaksha, Milind Dhawan, Atam NIH/NCI/DCTD Cancer Imaging Program Bethesda MD United States NIH/NCI/DCTD Cancer Imaging Program NCI-Frederick Frederick MD United States NIH/NCI/DCP Early Detection Research Group Bethesda MD United States The Johns Hopkins University School of Medicine Departments of Radiology Pharmacology and Oncology Division of Neuroradiology Baltimore MD United States NIH/NCI/CCR Cell and Cancer Biology Branch Bethesda MD United States University of California San Francisco Department of Medicine Division of Medical Oncology San Francisco CA United States CCS Associates Inc. Mountain View CA United States Wistar Institute Molecular and Cellular Oncogenesis Program Philadelphia PA United States University of Kansas School of Medicine VA Hospital Kansas City MO United States Duke University Department of Biomedical Engineering Medical Physics Program Durham NC United States University of Pennsylvania School of Medicine Department of Gastroenterology Philadelphia PA United States New York Presbyterian Hospital Weill Medical College of Cornell University New York NY United States NIH/NCI/OD Office of Centers for Training and Resources Bethesda MD United States University of Rochester Medical Center Department of Urology Rochester NY United States University of Texas MD Anderson Cancer Center Department of Urology Houston TX United States Massachusetts General Hospital Abdominal Imaging/Interventional Radiology Boston MA United States Boston University Biomedical Engineering Electrical and Computer Engineering and Physics Boston MA United States NIH/NCI/DCP Gastrointestinal and Other Cancers Research Group Bethesda MD United States The George Washington University Cancer Institute Office of Cancer Prevention and Control Washington DC United States University of Kansas Cancer Center Clinical Oncology Kansas City KS United States University of California Davis Department of Biomedical Engineering Davis CA United States Tufts University De

The article provides information on a workshop on the development of imaging systems for cancer prevention and preemption convened by the U.S. National Cancer Institute (NCI) Cancer Imaging Program held in Gaithersburg, Maryland. Doctor Katherine Ferrara of the University of California discussed the function of ultrasound in breast tumor imaging. Ways to close the gap between development and application of imaging approaches were tackled in a roundtable discussion on cervix and skin cancer.

关键词： FORUMS (Discussion & debate) IMAGING systems in medicine CANCER prevention

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Analysis of inductance characteristics in interior permanent magnet synchronous motor considering inductance variation

Analysis of inductance characteristics in interior permanent...

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12th Biennial IEEE Conference on Electromagnetic Field Computation, CEFC 2006

作者： Lee, Sang-Yub Kwak, Sang-Yeop Jung, Sang-Yong Kim, Jae-Kwang Hong, Sun-Ki Lee, Cheol-Gyun Jung, Hyun-Kyo Department of Electrical Engineering and Computer Science Seoul National University San 56-1 Shillim-dong Kwanak-ku Seoul 151-744 Korea Republic of Department of Electrical Engineering Dong-A University 840 Hadan2-dong Saha-ku Busan 604-714 Korea Republic of Division of Electrical Electronics Control and Instrumental Engineering Hoseo University 29-1 Sechul-ri Baebang-myun Asan Chungnam 336-795 Korea Republic of College of Engineering Dong-eui University 995 Eomgwangno Busanjin-ku Busan 614-714 Korea Republic of

ISBN: (纸本)1424403200

D- and q- axis inductance are expected to have ripple characteristics due to the difference of magnetic saturation level of each axis. In this paper, inductance variation of the interior permanent magnet synchronous motor (IPMSM) is calculated with finite element analysis, and cause of inductance variation is analyzed. Finally the validity of this paper is verified by the comparison to the experimental result. © 2006 IEEE.

关键词： Synchronous motors

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Modified Smith Predictor and controller for Time-Delay Process with Uncertainty

Modified Smith Predictor and Controller for Time-Delay Proce...

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World Congress on Intelligent control and Automation (WCICA)

作者： Shihua Wang Bugong Xu Qingyang Wang Yun-Hui Liu Laboratory of Real-Time Control through Internet and Fieldbuses College of Automation Science and Engineering South China University of Technology Guangzhou China Department of Automation and Computer Aided Engineering Chinese University of Hong Kong New Territories Hong Kong China

Smith predictor is very sensitive to uncertain system with variable time-delay. Using dual-locus diagram method, we first analyse the essence of Smith predictor's sensitivity and present a proposition to illustrate the system stability criteria with relation to system gain and time-delay variation. Then a new modified Smith predictor is proposed to compensate the variable time-delay system with uncertain model for set-point tracking. After that, we discuss the system internal stability and give two-degree freedom controller self-adaptive to eliminate the impact of system uncertainty with varying time-delay. Examples show the improved performance compared to previous modified Smith predictor structures

关键词： Process control Uncertainty Automatic control control systems Uncertain systems Feedback loop Tuning Automation Delay systems Robustness

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High-accuracy skew estimation of document images

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International Journal of Fuzzy Systems 2006年第3期8卷 119-126页

作者： Lin, Chin-Teng Fan, Kan-Wei Yeh, Chang-Mao Pu, Her-Chang Wu, Fang-Yi College of Computer Science National Chiao-Tung University 1001 Ta Hsueh Road Hsinchu 300 Taiwan National Chiao Tung University Hsinchu Taiwan Chungchou Institute of Technology Taichung Taiwan Department of Electrical and Control Engineering NCTU Taiwan MediaTek Taiwan

This paper presents a new skew angle estimation algorithm for binary document images based on the FCRM (fuzzy c-regression models) clustering method with the aim to resolve the disadvantages of low accuracy and robustness of the existing approaches. This algorithm consists of four processes. The first process transfers the input image into parallel straight lines through image analysis. The second process uses the operating window selection to accelerate the executing time. The following process magnifies the image by fast interpolation to increase the accuracy of skew angle estimation. Finally, the FCRM method is applied to estimate the skew angle. A test set of 184 documents of different kinds is used to measure the performance of the proposed algorithm. Experimental results show that the proposed method has a high precision rate for different document types;it is able to accurately estimate the skew angles that range between -89° and +89°. © 2006 TFSA.

关键词： Imaging systems

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HYPERON POLARIZATION IN QUARK-DIQUARK CASCADE MODEL

HYPERON POLARIZATION IN QUARK-DIQUARK CASCADE MODEL

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The 19th International Conference on Ultra-Relativistic Nucleus-Nucleus Collisions

作者： T. Tashiro H. Noda S. Nakariki K. Fukuma Department of Computer Simulation Okayama University of Science Ridai-cho Okayama 700-0005 Japan Department of Mathematical Science Ibaraki University Bunkyou Mito 310-8512 Japan Department of Computer Simulation Okayama University of Science Ridai-cho Okayama 700-0005 Japan Department of Control Engineering Takuma National College of Technology Mitoyo Kagawa 769-1192 Japan

It is well known that leading hyperons produced in unpolarized proton-proton and proton-nucleus collisions are polarized transversely to the production plane of the hyperon and various models have been proposed. In the forward hadron production, the valence quark in the projectile plays an important role. We discuss the polarization of inclusively produced hyperons in the framework of the constituent quark-diquark cascade model with SU(6) wave functions for

关键词： HYPERON POLARIZATION IN QUARK-DIQUARK CASCADE MODEL

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PUSHER REHEATING FURNACE control: A FUZZY-NEURAL MODEL PREDICTIVE STRATEGY

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IFAC Proceedings Volumes 2006年第19期39卷 165-170页

作者： Z.A. Icev M.J. Stankovski T.D. Kolemishevska J. Zhao G.M. Dimirovski SS Cyril and Methodius University Faculty of Electrical Engineering ASE Institute P.O.B. 574 MK-1000 Skopje Republic of Macedonia Northeastern University College of Information Science and Engineering Institute of Control Theory Shenyang Liaoning 110004 P.R. of China Dogus University Faculty of Engineering Computer Engineering Department Acibadem Zeamet Sk. 21 Kadikoy TR-34722 Istanbul Republic of Turkey

A design of fuzzy model-based predictive control for industrial furnaces has been derived and applied to the model of three-zone 25 MW RZS pusher furnace at Skopje Steelworks. The fuzzy-neural variant of Takagi-Sugeno fuzzy model, as an adaptive neuro-fuzzy implementation, is employed as a predictor in a predictive controller. In order to build the predictive controller the adaptation of the fuzzy model using dynamic process information is carried out. Optimization procedure employing a simplified gradient technique is used to calculate predictions of the future control actions.

关键词： Fuzzy-neural models fuzzy model predictive control optimization setpoint control time-delay processes

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M3S-based Electrical Wheelchair with Head-controlled Device

M3S-based Electrical Wheelchair with Head-controlled Device

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Show-Hong Chen Yu-Luen Chen Te-Son Kuo Chiung-Yu Chu Chao-Nan Hung Department of Electrical Engineering National Taiwan University Taipei Taiwan Realtek Semiconductor Corporation Hsinchu Taiwan Department of Electronic Engineering Hwa-Hsia College of Technology and Commerce Taipei Taiwan Department of Electrical and Control Engineering National Chiao Tung University Hsinchu Taiwan Department of Computer Science and Information Engineering Tung Nan Institute of Technology Taipei Taiwan

The motivation of this research is to improve the ability of ambulation for people with a certain degree of disability. The control of the wheelchair is using two tilt sensors as an input-controlling module. One of the tilt sensors detects the anterior/posterior tilting of the head and moves the wheelchair forward/backward, the other distinguishes the left/right swing of the head. In order to increase the safety of this system, the M3S protocol established by the European Commission is also applied to this research. The system based on M3S protocol has the advantage of real-time signal transmission and emergent status monitoring for SCI patients with C2-C4 level

关键词： Wheelchairs Switches Protocols Communication system control Voltage Patient monitoring Safety devices Head Switching circuits Gravity

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Pedestrian detection system

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International Journal of Fuzzy Systems 2005年第2期7卷 45-52页

作者： Lin, Chin-Teng Chung, Jen-Feng Pu, Her-Chang Department of Computer Science Engineering National Chiao Tung University 1001 Ta Hsueh RD. Hsinchu 300 Taiwan Department of Electrical and Control Engineering Taiwan College of Electrical Engineering and Computer Science Taiwan Brain Research Center NCTU Taiwan IEEE Taiwan Tau Beta Pi Eta Kappa Nu Phi Kappa Phi Honorary Societies United States Department of Electrical and Control Engineering NCTU Taiwan

In this paper, we propose a new pedestrian detection algorithm, and use it to develop a real-time pedestrian detection system. The pedestrian detection algorithm can be functionally partitioned into two parts: moving object segmentation and pedestrian recognition. In moving object segmentation, we segment the moving objects in the scene by modified temporal differencing method. This method combines general temporal differencing method with detection nets. In pedestrian recognition, we obtain multi-type wavelet templates from input images. Interest points are extracted from wavelet templates. Then, feature points are extracted by statistical method from interest point templates. Finally, these feature points are fed into a trained multilayer back-propagation neural network. The output of the neural network implies the result - pedestrian or non-pedestrian. From experiments, accuracy rate of recognition achieves 95%. We implement this algorithm in a real-time pedestrian detection system. The system can detect pedestrians in the scene in real time. The pedestrian detection rate is 92.58%. © 2005 TFSA.

关键词： Algorithms

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New horizon for CNN: With fuzzy paradigms for multimedia

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IEEE Circuits and Systems Magazine 2005年第2期5卷 20-35页

作者： Lin, Chin-Teng Chang, Chun-Lung Chung, Jen-Feng Dept. of Electrical and Control Engineering National College of Electrical Engineering and Computer Science Chiao-Tung University 1001 Ta Hsueh Road Hsinchu 300 Taiwan National Chiao-Tung University 1001 Ta Hsueh Road Hsinchu 300 Taiwan

The cellular neural network (CNN) is a powerful technique to mimic the local function of biological neural circuits for real-time image and video processing. Recently, it is widely accepted that using a set of CNNs in parallel can achieve higher-level information processing and reasoning functions either from application or biologics points of views. We introduce a novel framework for constructing a multiple-CNN integrated neural system called recurrent fuzzy CNN (RFCNN). This system can automatically learn its proper network structure and parameters simultaneously. In the RFCNN, each learned fuzzy rule corresponds to a CNN. Hence, each CNN takes care of a fuzzily separated problem region, and the functions of all CNNs are integrated through the fuzzy inference mechanism. Some on-line clustering algorithms are introduced for the structure learning, and the ordered-derivative calculus is applied to derive the recurrent learning rules of CNN templates in the parameter-learning phase. RFCNN provides a solution to the current dilemma on the decision of templates and/or fuzzy rules in the existing integrated (fuzzy) CNN systems. The capability of the RFCNN is demonstrated on the real-world vision-based defect inspection and image descreening problems proving that the RFCNN scheme is effective and promising. ©2005 IEEE.

关键词： Multimedia systems

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PREFACE

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International Journal on Artificial Intelligence Tools 2006年第3期15卷 331-333页

作者： GEORGE D. MAGOULAS GEORGIOS DOUNIAS DEREK A. LINKENS School of Computer Science and Information Systems Birkbeck College University of London Malet Street London WC1E 7HX UK Department of Financial and Management Engineering University of the Aegean 31 Fostini Street 82100 CHIOS GR Greece Department of Automatic Control and Systems Engineering The University of Sheffield Mappin Street Sheffield S1 3JD UK

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