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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Michel Hell Pyramo Costa Fernando Gomide Department of Computer Engineering and Automation (DCA) Faculty of Electrical and Computer Engineering (FEEC) State University of Campinas Sao Paulo Brazil Graduate Program in Electrical Engineering Pontifical Catholic University of Minas Gerais Belo Horizonte Minas Gerais Brazil

In this paper we introduce a new approach to train neurofuzzy networks using the participatory learning concept. The participatory learning paradigm tends to emulate the human learning mechanism where an acceptance mechanism determines which observation is used for learning based upon their compatibility with the current beliefs. The performance of the proposed learning scheme is illustrated by an example involving a nonlinear system modeling problem: the thermal modeling of power transformers. Comparisons with other methods reported in the literature and between two dual network structures are also included. The experimental results show the effectiveness of participatory learning in neurofuzzy networks training.

关键词： Power system modeling Fuzzy systems Power transformers Training data Humans Nonlinear systems Neural networks Fuzzy sets Power engineering computing Power engineering and energy

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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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7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE

作者： Jesneck, Jonathan L. Mukherjee, Sayan Nolte, Loren W. Lokshin, Anna E. Marks, Jeffrey R. Lo, Joseph Department of Biomedical Engineering Department of Statistical Science Computational Biology and Bioinformatics Program Duke Advanced Imaging Labs. Institute for Genome Sciences and Policy Department of Computer Science Duke University Department of Electrical and Computer Engineering Division of Hematology/Oncology University of Pittsburgh School of Medicine University of Pittsburgh Cancer Institute Pittsburgh PA 15213 United States Department of Experimental Surgery Duke University Medical Center Medical Physics Graduate Program Duke University Durham NC 27708 United States

ISBN: (纸本)1424415098

Current mammographic screeningfor 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. ©2007 IEEE.

关键词： Tissue

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Design and Evaluation of a Grid Computing Based Architecture for Integrating Heterogeneous IDSs

Design and Evaluation of a Grid Computing Based Architecture...

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IEEE GLOBECOM 2007 - IEEE Global Telecommunications Conference

作者： Paulo F. Silva Carlos B. Westphall Carla M. Westphall Marcos Dias de Assuncao Network and Management Laboratory Post-Graduate Program in Computer Science Federal University of Santa Catarina Florianopolis Brazil Grid Computing and Distributed Systems Laboratory Department of Computer Science and Software Engineering University of Melbourne VIC Australia

Intrusion detection systems (IDSs) have been substantially improved in recent past. However, network attacks have become more sophisticated and increasingly complex: many of current attacks are coordinated and originated in multiple networks. To detect these attacks, IDSs need to obtain information on network events from multiple networks or administrative domains. This work demonstrates that a Distributed IDS (DIDS) can be composed of existing IDSs, improving the detection of misuses in a multiple network environment. We use a grid middleware for creating a service-based intrusion detection grid. We demonstrate through experimental results that the proposed DIDS allows the integration of heterogeneous existing IDSs and improves the detection of attacks by exploring the synergy between existing IDSs.

关键词： Grid computing computer architecture Intrusion detection Resource management Laboratories computer science Electronic mail Middleware computer network management engineering management

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A comparison between traditional shift-and-add (SAA) and point-by-point back projection (BP) - Relevance to morphology of microcalcifications for isocentric motion in Digital Breast tomosynthesis (DBT)

A comparison between traditional shift-and-add (SAA) and poi...

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7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE

作者： Chen, Ying Lo, Joseph Y Dobbins III, James T. Department of Electrical and Computer Engineering Southern Illinois University Carbondale Carbondale IL 62901 United States Department of Biomedical Engineering Duke University Duke University Medical Center Durham NC 27710 United States Duke Advanced Imaging Laboratories Duke University Duke University Medical Center Durham NC 27710 United States Medical Physics Graduate Program Duke University Duke University Medical Center Durham NC 27710 United States

ISBN: (纸本)1424415098

Digital breast tomosynthesis (DBT) is a three-dimensional imaging technique providing an arbitrary set of reconstruction planes in the breast with limited series of projection images. This paper describes a comparison between traditional shift-and-add (SAA) and point-by-point back projection (BP) algorithms by impulse response and modulation transfer function (MTF) analysis. Due to the partial isocentric motion of the x-ray tube in DBT, structures such as microcalcifications appear slightly blurred in traditional shift-and-add (SAA) images in the direction perpendicular to the direction of tube 's motion. Point-by-point BP improved rendition of microcalcifications. The sharpness and morphology of calcifications were improved in a human subject images. A Filtered Back Projection (FBP) deblurring approach was used to demonstrate deblurred point-by-point BP tomosynthesis images. The point-by-point BP rather than traditional SAA should be considered as the foundation of further deblurring algorithms for DBT reconstruction. ©2007 IEEE.

关键词： Impulse response

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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

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MARKOV DECISION PROCESSES WITH UNCERTAIN TRANSITION RATES: SENSITIVITY AND MAX HYPHEN MIN CONTROL

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Asian Journal of Control 2008年第2期6卷

作者： Suresh Kalyanasundaram Edwin K. P. Chong Ness B. Shroff Motorola India Electronics Limited No. 66/1 Plot 5 Bagmane Techpark C. V. Raman Nagar Post Bangalore 560 093 India. Department of Electrical and Computer Engineering Colorado State University Fort Collins CO 80523-1373 USA. Professor Edwin K. P. Chong received the B.E.(Hons.) degree with First Class Honors from the University of Adelaide South Australia in 1987 graduating top of his class and the M.A. and Ph.D. degrees in 1989 and 1991 respectively both from Princeton University where he held an IBM Fellowship. He joined the School of Electrical and Computer Engineering at Purdue University in 1991 where he was named a University Faculty Scholar in 1999 and promoted to Full Professor in 2001. Since August 2001 he has been a Professor of Electrical and Computer Engineering and Professor of Mathematics at Colorado State University. His current interests are in communication networks and optimization methods. He coauthored the best-selling book An Introduction to Optimization 2nd Edition Wiley-Interscience 2001. He received the NSF CAREER Award in 1995 and the ASEE Frederick Emmons Terman Award in 1998. He coauthored a paper that was awarded Best Paper in the journal Computer Networks 2003. Professor Chong is a Fellow of the IEEE. He was founding chairman of the IEEE Control Systems Society Technical Committee on Discrete Event Systems and until recently served as an IEEE Control Systems Society Distinguished Lecturer. He has been on the editorial board of the IEEE Transactions on Automatic Control. He is currently on the editorial board of the journal Computer Networks. He has also served on the organizing committees of several international conferences. He has been on the program committees for the IEEE Conference on Decision and Control the American Control Conference the IEEE International Symposium on Intelligent Control IEEE Symposium on Computers and Communications and the IEEE Global Telecommunications Conference. He has also served in the executive committees for the IEEE Co

Solution techniques for Markov decision problems rely on exact knowledge of the transition rates, which may be difficult or impossible to obtain. In this paper, we consider Markov decision problems with uncertain transition rates represented as compact sets. We first consider the problem of sensitivity analysis where the aim is to quantify the range of uncertainty of the average per-unit-time reward given the range of uncertainty of the transition rates. We then develop solution techniques for the problem of obtaining the max-min optimal policy, which maximizes the worst-case average per-unit-time reward. In each of these problems, we distinguish between systems that can have their transition rates chosen independently and those where the transition rates depend on each other. Our solution techniques are applicable to Markov decision processes with fixed but unknown transition rates and to those with time-varying transition rates.

关键词： Markov decision processes sensitivity max-min control call admission control policy iteration

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Enabling a strong U.S. engineering workforce for technological innovation: A national partnership in graduate professional education with industry to enhance U.S. competitiveness and economic development

Enabling a strong U.S. engineering workforce for technologic...

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114th Annual ASEE Conference and Exposition, 2007

作者： Keating, Donald Stanford, Thomas Bardo, John Dunlap, Duane DeLoatch, Eugene Tricamo, Stephen Deoew, Dennis Bertoline, Gary Schuver, Mark McHenry, Albert Lindquist, Timothy Tidwell, Joseph Palmer, Harvey Smith, Mark Morrison, Raymond Egbert, Norm Quick, David Olson, Roger Truesdale, Samuel Noori, Mohamad Sullivan, Edward Rencis, Joseph Purdy, Carla University of South Carolina United States Department of Mechanical Engineering University of South Carolina United States ASEE-Graduate Studies Division Department of Chemical Engineering University of South Carolina United States Western Carolina University United States Kimmel School Western Carolina University United States Morgan State University United States School of Engineering Morgan State University United States ASEE New Jersey Institute of Technology United States Department of Industrial and Manufacturing Engineering Purdue University United States College of Technology Purdue University United States Rolls-Royce-Purdue Master's Degree Program Purdue University United States Arizona State University United States Arizona State University Polytechnic United States Boeing Co. United States JACMET Arizona State University Polytechnic United States ASEE-College Industry Partnership Division Rochester Institute of Technology United States Kate Gleason College of Engineering Rochester Institute of Technology United States Lockheed Martin Aeronautics Co. United States Engineering Integration and Strategy Lockheed Martin Aeronautics Company United States ASEE-Corporate Rolls-Royce Corporation United States Rolls-Royce North American Technologies United States California State Polytechnic University United States College of Engineering California State Polytechnic University United States Graduate Programs and Research College of Engineering California State Polytechnic University United States University of Arkansas United States Department of Mechanical Engineering University of Arkansas Fayetteville United States ASEE-Mechanical Engineering Division ASME Mechanical Engineering Department University of Cincinnati United States Department of Electrical and Computer Engineering University of Cincinnati United States

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A constant revenue model for telecommunication networks

A constant revenue model for telecommunication networks

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International Conference on Networking, International Conference on Systems andInternational Conference on Mobile Communications and Learning Technologies, ICN/ICONS/MCL'06

作者： Sukasdadi, Hapsara R. Verma, Pramode K. Graduate Program in Telecommunication System Department of Electrical and Computer Engineering

ISBN: (纸本)0769525520

It is well known that the quality of service provided by a telecommunication network as measured by the probability of blocking decreases rapidly when the incident traffic exceeds the design limits of the network. A higher probability of blocking results in reduced throughput and loss of revenue for the service provider. This paper presents a mechanism that introduces priority in a telephone system with the objective of providing a defined grade of service to priority traffic carrying a higher price tag. The non-priority traffic carries a lower price tag and a lower grade of service. The proposed pricing scheme maintains the overall revenue associated with the network at a constant level over a wide range of incident traffic. © 2006 IEEE.

关键词： Telecommunication networks

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A comparison between traditional shift-and-add (SAA) and point-by-point back projection (BP) -- relevance to morphology of microcalcifications for isocentric motion in Digital Breast tomosynthesis (DBT)

A comparison between traditional shift-and-add (SAA) and poi...

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IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： Ying Chen Joseph Y. Lo James T. Dobbins Department of Electrical and Computer Engineering Southem Illinois University Carbondale Carbondale IL USA Duke Adavanced Imaging Laboratories Duke University Medical Center Duke University Durham NC USA Department of Biomedical Engineering Duke University and Duke University Medical Center Durham North Carolina 27710 Duke Advanced Imaging Laboratories Duke University and Duke University Medical Center Durham North Carolina 27710 Medical Physics Graduate Program Duke University and Duke University Medical Center Durham North Carolina 27710

Digital breast tomosynthesis (DBT) is a three-dimensional imaging technique providing an arbitrary set of reconstruction planes in the breast with limited series of projection images. This paper describes a comparison between traditional shift-and-add (SAA) and point-by-point back projection (BP) algorithms by impulse response and modulation transfer function (MTF) analysis. Due to the partial isocentric motion of the x-ray tube in DBT, structures such as microcalcifications appear slightly blurred in traditional shift-and-add (SAA) images in the direction perpendicular to the direction of tube's motion. Point-by-point BP improved rendition of microcalcifications. The sharpness and morphology of calcifications were improved in a human subject images. A filtered back projection (FBP) deblurring approach was used to demonstrate deblurred point-by-point BP tomosynthesis images. The point-by-point BP rather than traditional SAA should be considered as the foundation of further deblurring algorithms for DBT reconstruction.

关键词： Morphology Image reconstruction X-ray imaging Back Image edge detection Breast cancer Detectors Biomedical engineering Transfer functions Humans

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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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