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Congress on Evolutionary Computation

作者： M. Ghannad-Rezaie H. Soltanain-Zadeh M.-R. Siadat K.V. Elisevich Henry Ford Health System and Wayne State University Detroit MI USA Radiology Image Analysis Laboratory Henry Ford Health System Detroit MI USA Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Neurosurgery Department Henry Ford Health System Detroit MI USA

In clinical problems, numerous factors are usually involved in a medical syndrome. New advances in medicine provide a broad range of diagnosis methods to cover all aspects of a disease. However, huge amounts of raw information may confuse clinicians and decrease decision accuracy. Computerized knowledge extraction is an active area of research in medical informatics. This paper suggests a new medical data mining approach using an advanced swarm intelligence data mining algorithm. Considering medical knowledge discovery difficulties, this approach addresses common issues such as missing value management and interactive rule extraction. Here, surgery candidate selection in temporal lobe epilepsy is the main target application. However, the general idea can be applied to other medical knowledge discovery problems. Experimental results show noticeable performance improvement in the final rule-set quality while the method is flexible and fast.

关键词： Data mining Particle swarm optimization Temporal lobe Epilepsy Medical diagnostic imaging Biomedical imaging Coronary arteriosclerosis Diseases Surgery Medical services

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Spatially Adaptive Kernels for Adaptive Spatial Filtering of fMRI Data

Spatially Adaptive Kernels for Adaptive Spatial Filtering of...

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International Joint Conference on Neural Networks (IJCNN)

作者： V. Taimouri G.-A. Hossein-Zadeh H. Soltanian-Zadeh Control and Intelligent Processing Centre of Excellence ECE Department Faculty of Engineering University of Tehran Tehran Iran School of Cognitive Sciences Institute of Studies in Theoretical Physics and Mathematics and Medical Image Analysis Laboratory Henry Ford Health System Detroit MI USA

Making use of neighborhood time series is an effective way of noise reduction in fMRI data. However the conventional averaging methods blur activated areas. In this paper, a filter with adaptive kernel is designed such that its kernel size and direction are defined at each voxel. First, for finding the optimum size of kernel, a linear combination of some isotropic Gaussian filters with different variances is used, and optimum value of variance is specified. Then, the appropriate kernel direction is determined by a linear combination of some anisotropic basic filters with various directions. The weights of these linear combinations can be calculated by using the restricted canonical correlation method. The proposed method is compared with a similar method based on the steerable filters and the results show that the proposed method improves the ROC curve and prohibits false spread of the activation areas.

关键词： Kernel Adaptive filters Filtering Nonlinear filters Anisotropic magnetoresistance Magnetic separation Process control Intelligent control Correlation Magnetic resonance imaging

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Announcements, comments, and acknowledgments

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AIAA Journal 2006年第1期44卷 1-10页

作者： Oran, Elaine Kailasanath, Kazhikathra Aggarwal, Suresh K. Ahmadian, Mehdi Alexandrov, Natalia Auweter-Kurtz, Monika Bailly, Christophe Balachandran, Balakumar Berman, Alex Candler, Graham V. Chelliah, Harsha K. Chokani, Ndaona Fujii, Kozo Gaitonde, Datta V. Ghia, Kirti Karman N. Givi, Peyman Gore, Jay P. Kaplan, Carolyn R. Livne, Eli Lucht, Robert P. Messac, Achille Wing, N.G. Palazotto, Anthony N. Pierre, Christophe Plotkin, Allen Roy, Ajit K. Saigal, Sunil Sforza, Pasquale M. Shivakumar, Kunigal N. So, Ronald M.C. Springer, Anthony M. Anatolitumin, Anthony M. Zhong, Xiaolin United States Division of Computational Physics United States United States AIAA United States APS United States National Academy of Engineering United States Center for Reactive Flow and Dynamical Systems Naval Research Laboratory United States Institute of Physics Department of Mechanical Engineering University of Illinois at Chicago United States ASME Combustion Institute Department of Mechanical Engineering Virginia Polytechnic Institute State University United States Aeronautics Systems Analysis Branch NASA Langley Research Center United States SIAM ISSMO Aerospace Engineering Institute of Space Systems Universität Stuttgart Germany Amelia Earhart Italy International Amelia Earhart Award Committee Italy France France Mechanical Engineering University of Maryland College Park United States AAM SPIE ASA ASME Technical Committees of Multi-Body Systems Nonlinear Dynamics Dynamics and Control of Structures and Systems American Helicopter Society United States Aerospace Engineering and Mechanics University of Minnesota United States AIAA Thermophysics Technical Committee Mechanical and Aerospace Engineering University of Virginia United States AIAA Propellants and Combustion Technical Committee AIAA's Transition Study Group Aerodynamics Measurement Technology Technical Committee Thermophysics Technical Committee Japan MOSAIC project on the Technology Pressure-sensitive Paint Measurement System Japan High-Speed Flows Group Air Vehicles Directorate Air Force Research Laboratory Wright-Patterson Air Force Base United States Wright State University United States Aerospace Engineering and Engineering Mechanics United States United States Mechanical Engineering University of Pittsburgh United States School of Mechanical Engineering Purdue University United States Committee on Heat Transfer in Fire and Combustion Systems Japan Board of Advisors Central States Section Combustion Institute United States AIChE United States Tau Beta Pi United States

No abstract available

关键词： Institute of Space and Astronautical Science American Society of Mechanical Engineers Direct Numerical Simulation Aerospace engineering MDO Propellant Air Forces Aerodynamics Heterogeneous Combustion NASA Langley Research Center

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Assessing the technical value of FACTS-based wide-area damping control loops

Assessing the technical value of FACTS-based wide-area dampi...

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2005 IEEE Power engineering Society General Meeting

作者： Kamwa, I. Heniche, A. Trudel, G. Dobrescu, M. Grondin, R. Lefebvre, D. IEEE Hydro-Québec IREQ1800 boul. Lionel-Boulet Varennes Que. J3X 1S1 Canada Hydro-Québec TransÉnergie Complexe Desjardins Montréal Que. H5B1H7 Canada HydroQuebec Research Institute CIGRÉ System Dynamic Performance Committee AdCom Power System Analysis Operation and Control Department IEEE Power Engineering Society System Planning Department Hydro-Quebec TransEnergie Division Hydro-Quebec research institute IREQ

ISBN: (纸本)078039156X

Engineers intuit that, as power systems interconnect more and more to exchange large amounts of power over longer transmission lines, wide-area damping control should become increasingly rewarding. However, given the current technological and psychological barriers, decision makers need tools to assess whether the inherent advantages of wide-area control over local control can outweigh the risk incurred by the additional complexity of the underlying telecommunication and SCADA systems. This paper devises a simple small signal analysis-based methodology for pinpointing control sites where wide-area control has a substantial technical advantage over a purely local control. Using a novel fuzzy logic-based PSS scheme applicable to both Static Var Compensators (SVC) and Synchronous Condensers (SC), the authors first demonstrate the claims of their paper on an interesting three-area power system proposed by Anderson and Farmer. Based on small- and large-signal studies, the findings are then generalized to a large study network from Québec's provincial ISO, equipped with SVCs and SCs at six and four 735-kV substations respectively, all of them included in the scope of this study. Overall, wide-area control is consistently three to 20 times more efficient technically than the competing local control, depending on the network and the control site. © 2005 IEEE.

关键词： control systems

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systematic model identification of complex bioprocesses: Application to a CHO-K1 cell culture 9th

Systematic model identification of complex bioprocesses: App...

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9th IFAC International Symposium on Computer Applications in Biotechnology, CAB 2004

作者： Haag, Jens E. Wouwer, Alain Vande Remy, Marcel Bogaerts, Philippe Control Department Faculty of Engineering Boulevard Dolez 31 MonsB-7000 Belgium Control Engineering and System Analysis Department Université Libre de Bruxelles Avenue F. D. Roosevelt 50 CP 165/55 BrusselsB-1050 Belgium

Modeling and parameter identification are important prerequisites for state estimation and control of complex biological systems in bioengineering. Due to the great variety of cell lines and the rapidity of developments in genetics, biosystems have to be investigated in a fast and efficient way to identify the major metabolic phenomena. This paper proposes a systematic modeling procedure, which enables the description of the most important experimental settings and biological effects in terms of stoichiometry, kinetics and metabolic regulation. This procedure is successfully applied to the real case of a perfused mammalian cell culture of non-transfected CHO-K1 cells in suspension. Copyright © IFAC Computer Applications in Biotechnology, Nancy, France, 2004.

关键词： Parameter estimation

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systematic Model Identification of Complex Bioprocesses: Application to a CHO-K1 Cell Culture

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IFAC Proceedings Volumes 2004年第3期37卷 97-102页

作者： Jens E. Haag Alain Vande Wouwer Marcel Remy Philippe Bogaerts Control Department Faculty of Engineering Boulevard Dolez 31 B-7000 Mons Belgium Control Engineering and System Analysis Department Université Libre de Bruxelles Avenue F. D. Roosevelt 50 CP 165/55 B-1050 Brussels

关键词： dynamic modeling parameter estimation macroscopic reaction schemes C-identifiability mammalian cell culture

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Stochastic hybrid observer for bioprocess state estimation 9th

Stochastic hybrid observer for bioprocess state estimation

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9th IFAC International Symposium on Computer Applications in Biotechnology, CAB 2004

作者： Hulhoven, X. Hanus, R. Bogaerts, Ph. Université Libre de Bruxelles General Chemistry and Biosystems Department Av. F.-D. Roosevelt 50 CP 165/55 Brussels1050 Belgium Université Libre de Bruxelles Control Engineering and System Analysis Department Av. F.-D. Roosevelt 50 CP 165/55 Brussels1050 Belgium

State observers provide estimates of non-measured variables based on a mathematical model of the process and some available hardware sensor signals. On the one hand, exponential observers, such as the full horizon observer (FHO) or Kaiman filters, have an adjustable rate of convergence, but strongly rely on the accuracy of the process model. On the other hand, asymptotic observers use a state transformation in order to avoid using the (usually uncertain) kinetic model, but have a rate of convergence imposed by the process dilution rate. In an attempt to combine the advantages of both techniques, a hybrid observer is developed. The principle of this hybrid observer is to compare the observations made by the two observers in order to perform a test on the process model quality and to provide, accordingly, a state estimation that evolves between the two above-mentioned limit observations (observations from an exponential or the asymptotic observer). Copyright © IFAC Computer Applications in Biotechnology, Nancy, France, 2004.

关键词： State estimation

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Stochastic full horizon-asymptotic hybrid observer applied to a simulated cell culture 9th

Stochastic full horizon-asymptotic hybrid observer applied t...

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9th IFAC International Symposium on Computer Applications in Biotechnology, CAB 2004

作者： Hulhoven, X. Hanus, R. Bogaerts, Ph. Université Libre de Bruxelles General Chemistry and Biosystems Department Av. F.-D. Roosevelt 50 CP 165/61 Brussels1050 Belgium Université Libre de Bruxelles Control Engineering and System Analysis Department Av. F.-D. Roosevelt 50 CP 165/61 Brussels1050 Belgium

In an attempt to combine the advantages of an exponential state observer (i.e. fast convergence with an accurate model) and an asymptotic one (i.e. convergence without any knowledge about the kinetic model), a stochastic hybrid observer, which compares the observations made by the two observers has been developed (Hulhoven et al., 2003). This comparison is made in order to perform a test on the process model quality and to provide a state estimation that evolves, accordingly, between the state estimation provided by the exponential observer and the one from the asymptotic one. In this contribution, the stochastic hybrid observer is established by using a full horizon observer as the exponential observer. The performances of this hybrid observer, are then tested on a simulated fed-batch cell culture. Copyright © IFAC Computer Applications in Biotechnology, Nancy, France, 2004.

关键词： State estimation

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Clustering-based framework for comparing fMRI analysis methods

Clustering-based framework for comparing fMRI analysis metho...

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IEEE International Symposium on Biomedical Imaging

作者： G.-A. Hossein-Zadeh A.-M. Golestani H. Soltanian-Zadeh Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department Faculty of Engineering University of Tehran Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Health System Detroit MI USA

In this paper, a cluster-based framework is introduced for comparing analysis methods of functional magnetic resonance images (fMRI). In the proposed framework, fMRI data is replaced with a feature space and each method considered as a clustering method in the new space. As a result, different methods can be compared by means of a cluster validity measure. The feature space is computed using a non-parametric method (principal component analysis-PCA). Four subjects have been analyzed with three methods and the proposed cluster-based framework has evaluated performance of the methods. The results are identical to those of the modified receiver operating characteristics (ROC). This validates the proposed approach.

关键词： Clustering algorithms Algorithm design and analysis Image analysis Clustering methods Magnetic analysis Testing Accuracy Reproducibility of results Radiology Magnetic resonance

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Multiresolution automatic segmentation of T1-weighted brain MR images

Multiresolution automatic segmentation of T1-weighted brain ...

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IEEE International Symposium on Biomedical Imaging

作者： M. Zeydabadi R.A. Zoroofi H. Soltanian-Zadeh Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department Faculty of Engineering University of Tehran Tehran Iran Radiology Department Henry Ford Health System Image Analysis and Communications Laboratory Detroit MI USA

Automatic segmentation of brain tissues is crucial to many medical imaging applications. We use a multi-resolution analysis and a power transform to extend the well-known Gaussian mixture model expectation maximization based algorithm for segmentation of white matter, gray matter, and cerebrospinal fluid from T1-weighted magnetic resonance images (MRI) of the brain. Experimental results with near 4000 synthetic and real images are included. The results illustrate that the proposed method outperforms six existing methods.

关键词： Image resolution Image segmentation Biomedical imaging Multiresolution analysis Image analysis Magnetic analysis Algorithm design and analysis Brain modeling Magnetic liquids Magnetic resonance

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