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Adaptive Fault–Tolerant Control Design Approach for a Wind Turbine Benchmark

IFAC Proceedings Volumes 2012年第20期45卷 319-324页

作者： Silvio Simani Paolo Castaldi The Department of Electrical and Computer Engineering The University of Auckland 92019 Auckland New Zealand School of Aeronautics and Astronautics Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education Shanghai 200240 China

This paper addresses the development of an active fault tolerant control scheme that is applied to a wind turbine simulated benchmark. The proposed methodology is based on a comprehensive scheme relying on adaptive controllers designed by means of the on–line identification of the system model under diagnosis. In this way, the controller reconfiguration mechanism exploits an adaptive regulator implementation, depending on the on–line estimate of system model. One of the advantages of this strategy is that, for example, the original structure of logic–based switching digital controller scheme already implemented for the wind turbine benchmark can be almost preserved. The active fault tolerant control scheme is therefore applied to a wind turbine simulated benchmark, in the presence of disturbance and measurement errors, along nominal operating conditions, including also different realistic fault situations. The achieved results in both fault–free and faulty conditions serve to show the enhancement of the control performances, and the fault accommodation features.

关键词： Fault tolerant systems adaptive control digital control system design nonlinear systems wind turbine benchmark

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Interpolation of Orientation Distribution Functions (ODFs) in Q-ball Imaging

Interpolation of Orientation Distribution Functions (ODFs) i...

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Iranian Conference of Biomedical engineering

作者： Maryam Afzali Emad Fatemizadeh Hamid Soltanian-Zadeh Department of Electrical Engineering Biomedical Signal and Image Processing Laboratory(BiSIPL) Sharif University of Technology Tehran Iran Control and Intelligent Processing Center of Excellence(CIPCE) School of Electrical and Computer Engineering University of Tehran Tehran Iran & Image Analysis Laboratory Radiology Department Henry Ford Health System Detroit Michigan USA

ISBN: (纸本)9781467331289

Diffusion tensor magnetic resonance imaging (DTMRI) is a non-invasive method for investigating the brain white matter structure. It can be used to evaluate fiber bundles in the brain but in the regions with crossing fibers, it fails. To resolve this problem, high angular resolution diffusion imaging (HARDI) with a large number of diffusion encoding directions is used and for reconstruction, the Q-ball method is applied. In this method, orientation distribution function (ODF) of fibers can be calculated. Mathematical models play a crucial role in the field of ODF. For instance, in registering Q-ball images for applications like group analysis or atlas construction, one needs to interpolate ODFs. To this end, principal diffusion directions (PDDs) of each ODF are needed. In this paper, PDDs are defined as vectors that connect the corresponding local maxima of ODF values. Then, ODFs are interpolated using PDDs. The proposed method is evaluated and compared with previous protocols. Experimental results show that the proposed interpolation algorithm preserves the principal direction of fiber tracts without producing any deviations in the tracts. It is shown that changes in the entropy of the interpolated ODFs are almost linear and the bloating effect (blurring of the principal directions) can be removed.

关键词： High angular resolution diffusion imaging (HARDI) Q-ball imaging Orientation distribution function (ODF) Interpolation Principal diffusion direction (PDD)

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Voxel-based treatment prediction of glioblastoma multiform tumor using diffusion tensor imaging

Voxel-based treatment prediction of glioblastoma multiform t...

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IEEE-EMBS International Conference on Biomedical and Health Informatics, BHI 2012. In Conj. with the 8th Int. Symp.on Medical Devices and Biosensors and the 7th Int. Symp. on Biomedical and Health engineering

作者： Sabahi, Hadi Soltanian-Zadeh, Hamid Scarpace, Lisa Mikkelsen, Tom Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran 14395-515 Iran Image Analysis Laboratory Radiology Department Henry Ford Hospital Detroit MI 48202 United States Hermelin Brain Tumor Research Center Neurosurgery Department Henry Ford Health System Detroit MI 48202 United States

ISBN: (纸本)9781457721779

This paper proposes a method to predict the effect of Bevacizumab therapy on Glioblastoma Multiform (GBM) tumors. The prediction is critical for effective treatment planning. The proposed method is developed and evaluated using Diffusion Tensor Imaging (DTI) and post-contrast T1-weighted Magnetic Resonance Images (pc-T1-MRI) of 14 patients with GBM tumors gathered before and after the treatment. First, the proposed method calculates diffusion anisotropy indices (DAI) of all voxels in the brain. These diffusion anisotropy indices are Fractional Anisotropy (FA), Mean Diffusivity (MD), Relative Anisotropy (RA), and Volume Ratio (VR). Then, it registers post-treatment pc-T1-MRI and pre-treatment DAI maps to pre-treatment pc-T1-MRI. Next, it uses a thresholding method to segment the tumor from pc-T1-MRI studies. Comparing Gd-enhanced voxels of the pre- and post-treatment pc-T1-MRI, the DAIs of the tumor are labeled based on their response to the treatment. The voxels of 7 patients are randomly selected to train 4 classifiers (ANN, SVM, KNN, and ANFIS) and then all voxels of the other 7 patients are used to test them. For each classifier, four performance measures (sensitivity, specificity, positive predictive value, and accuracy) are calculated. Experimental results show that the ANFIS is more accurate than the other classifiers in predicting the treatment response. © 2012 IEEE.

关键词： Tumors

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Iterative data adaptive anisotropic image filtering

Iterative data adaptive anisotropic image filtering

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2012 International Conference on Machine Learning and Cybernetics, ICMLC 2012

作者： Yang, Chang-Cai Zheng, Xin-Yi Tian, Jin-Wen Shang, Ke Tian, Xin Hao, Wei Institute for Pattern Recognition and Artificial Intelligence Science and Technology on Multi-Spectral Information Processing Laboratory Huazhong University of Science and Technology Wuhan 430074 China Electrical Engineering and Renewable Energy School China Three Gorges University Yichang 443002 China Institute of Intelligent Vision and Image Information College of Computer and Information Technology China Three Gorges University Yichang 443002 China

ISBN: (纸本)9781467314855

This paper presents a novel data-adaptive anisotropic filtering technique built on top of an iterative scheme. This new technique can preserve the original significant structures while suppressing noises to the largest extent. To achieve this goal, dominant orientation information of all gradients is used to control the local kernel adaptively. This results in elongated and elliptical contours spread along the directions of the local edge structure. With these locally adapted kernels, the smoothing is mostly effective along the edges, rather than across them. Therefore details in the original input can be preserved. The performance of the proposed data-adaptive anisotropic filter together with its iterative scheme are compared with the conventional Gaussian filter, anisotropic diffusion filter, the structure-adaptive anisotropic filter, and the iterative kernel regression scheme. The experimental results on both simulated Gaussian and Poission noisy images indicate that the proposed method performs the best, and the iterative scheme can significantly improve the performance of the noise suppressing while delivering high computation efficiency. © 2012 IEEE.

关键词： Iterative methods

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A performance study of CSMA in wireless networks with successive interference cancellation

A performance study of CSMA in wireless networks with succes...

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IEEE International Conference on Communications (ICC)

作者： Shaohe Lv Weihua Zhuang Xiaodong Wang Chi Liu Xiaofeng Hu Yipin Sun Xingming Zhou Institute of Network Information and Security National University of Defense Technology Changsha China Department of Electrical and Computer Engineering University of Waterloo Waterloo ONT Canada Central South University Changsha China National Laboratory of Parallel and Distributed Processing National University of Defense Technology Changsha China

Successive interference cancellation (SIC) is an effective way of multipacket reception to combat interference. As conventional CSMA (Carrier Sense Multiple Access) is designed for single packet reception, it is unclear whether or not CSMA performs well to exploit the SIC capability. In this paper, we analyze the performance of a simple CSMA protocol in a network with SIC. For a given link, we derive the residing areas of an interfering node when simultaneous transmission is allowed and when the interference is harmful, respectively. We show that, though SIC provides many new transmission opportunities, CSMA cannot effectively exploit them. There is a fundamental tradeoff in a CSMA protocol between exploiting the transmission opportunities from SIC and capturing the harmful interference. In many cases, when CSMA achieves its best performance, almost all new transmission opportunities are not exploited. It is therefore very necessary to design a new distributed access protocol in wireless networks with SIC.

关键词： Silicon carbide Multiaccess communication Interference Receivers Propagation losses Protocols Wireless networks

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Information Generation and Lagrangian Coherent Structures in Multiscroll Attractors *

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IFAC Proceedings Volumes 2012年第12期45卷 93-98页

作者： Filipe I. Fazanaro Diogo C. Soriano Ricardo Suyama Marconi K. Madrid Romis Attux José Raimundo de Oliveira Modular Robotic Systems Laboratory (LSMR) Department of Computer Engineering and Industrial Automation (DCA) School of Electrical and Computer Engineering (FEEC) UNICAMP Brazil Centro de Engenharia Modelagem e Ciências Sociais Aplicadas Universidade Federal do ABC (UFABC) Santo André Brazil LSMR Department of Energy Control and Systems (DSCE) FEEC UNICAMP Laboratory of Signal Processing for Communications (DSPCom) DCA FEEC UNICAMP

The present work aims to apply a recently alternative approach to estimate the Lyapunov exponents that is suitable for such piecewise linear model in order of characterizing - with the aid of the metric entropy - the degree of information generated by several kinds of multiscroll attractors. Another analytical path is followed with the extraction of the corresponding Lagrangian coherent structures, which allows the determination of the dynamical system separatrices and also of the folding/stretching behavior that results in chaos. Overall, the reported study can be understood as an investigation, from distinct theoretical standpoints, of key aspects regarding the dynamic behavior of systems capable of engendering multiscroll structures.

关键词： chaotic behavior fractal dimension information generation Lagrangian coherent structures Lyapunov exponents multiscroll chaotic attractors non-smooth models

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Single camera-based full depth map estimation using color shifting property of a multiple color-filter aperture

Single camera-based full depth map estimation using color sh...

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International Conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Seungwon Lee Junghyun Lee Monson H. Hayes Aggelos K. Katsaggelos Joonki Paik Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul South Korea Department of Electrical Engineering and Computer Science Northwestern University Evanston IL USA

A multiple color-filter aperture (MCA) camera can provide depth information as well as color and intensity in the single-camera framework, where the MCA generates misalignment between color channels depending on the distance of a region-of-interest. In this paper, we present a single camera-based estimation of the full depth map using the color shifting property of the MCA. For estimating the color shifting vectors (CSVs) among red, green, and blue color channels, edges are extracted at each color channel. At the edge, we estimate CSVs using normalized cross correlation combined with color shifting mask map. A full depth map is then generated by depth interpolation using the matting Laplacian method from sparsely estimated CSVs at an edge location. Experimental results show that the proposed method can not only estimate the full depth map but also correct the misaligned color image to generate photorealistic color images using a single camera equipped with MCA.

关键词： Image color analysis Cameras Estimation Channel estimation Image edge detection Interpolation Apertures

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Development of a MATLAB-Based Toolbox for Brain computer Interface Applications in Virtual Reality

Development of a MATLAB-Based Toolbox for Brain Computer Int...

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Iranian Conference on electrical engineering

作者： Fardin Afdideh Mohammad Bagher Shamsollahi Seyed Navid Resalat Biomedical Signal and Image Processing Laboratory (BiSPL) School of Electrical Engineering Sharif University of Technology Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering College of Engineering University of Tehran

ISBN: (纸本)9781467311496

Brain computer interface (BCI) is a widely used system to assist the disabled and paralyzed people by creating a new communication channel. Among the various methods used in BCI area, motor imagery (MI) is the most popular and the most common one due to its the most natural way of communication for the subject. Some software applications are used to implement BCI systems, and some toolboxes exist for EEG signal processing. In recent years virtual reality (VR) technology has entered into the BCI research area to simulate the real world situations and enhance the subject performance. In this work, a completely MATLAB-based Mi-based BCI system is proposed and implemented in order to navigate into a virtual environment. In addition, a variety of features types were employed to select the best ones in the proposed system with the use of linear discriminant analysis (LDA) classifier through some interactive graphical user interfaces (GUIs). The results show the feasibility of the proposed BCI system in the subject training with or without feedback and even navigation into a virtual home.

关键词： Brain computer Interface (BCI) MATLAB Motor Imagery (MI) Virtual Reality (VR) Real-time EEG signal processing

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3D computational modeling of epiretinal prosthesis stimulation of the ganglion cell

3D computational modeling of epiretinal prosthesis stimulati...

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IEEE EMBS International Conference on Information Technology Applications in Biomedicine (ITAB)

作者： Shabnam Novin Hamid Abrishami Moghaddam Amir Masoud Sodagar Amin Mahnam Research Laboratory for Integrated Circuits and Systems (I CAS) Department of Electrical and Computer Engineering K.N. Toosi University of Technology Tehran Iran Research Laboratory for Machine Vision and Medical Image Processing (MVMIP) Department of Electrical and Computer Engineering K.N. Toosi University of Technology Tehran Iran Ecole Polytechnique de Montreal Montreal QUE Canada Department of Biomedical Engineering School of Engineering University of Isfahan Isfahan Iran

Here we present a modeling for electrical stimulation of retinal ganglion cell. This modeling can be used in epiretinal prosthesis to come up with proper electrical stimulation parameters. The model that we present is a novel one based on the anatomy of the cell. The excitation process of the electrically stimulated retinal cells is simulated in a two step procedure. In the first step the ganglion target cell is represented considering all of its compartments and in a second step the extracellular potential along the neural structure is calculated and finally the membrane voltage response to the applied stimulations is analyzed. A monopolar point electrode was positioned above the cell in an infinite and homogenous environment and the monophasic and biphasic pulses were used as stimulating current. The results show that the responses are in accordance with the values and diagrams of experimental results more than the previous models.

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Hippocampal shape analysis in the Laplace Beltrami feature space for temporal lobe epilepsy diagnosis and lateralization

Hippocampal shape analysis in the Laplace Beltrami feature s...

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IEEE International Symposium on Biomedical Imaging

作者： Rosita Shishegar Ziba Gandomkar Hamid Soltaman-Zadeh Seyed Reza Moghadasi Control and Intelligent Processing Centre of Excellence (CIPCE) School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Radiology Image Analysis Laboratory Henry Ford Health System Detroit MI USA Department of Mathematics Sharif University of Technology Tehran Iran

Shape analysis plays an important role in many medical imaging studies. One of the recent shape analysis methods uses the Laplace Beltrami operator which is also used in this paper for hippocampal shape comparison. We proposed a feature vector which consists of size measures and shape descriptors based on Laplace Beltrami eigenvalues and eigenfunctions. The aforementioned feature space is utilised for automatic differentiating normal subjects from epileptic patients as well as distinguishing epileptic patients with left temporal lobe epilepsy (LTLE) from patients with right temporal lobe epilepsy (RTLE). Achieved results are diagnostic accuracy of 93% with 95% sensitivity and lateralization accuracy of 86%. The results are comparable to spherical harmonic based shape analysis results and notably improved in comparison to volumetric analysis results.

关键词： Shape Temporal lobe Epilepsy Abstracts Indexes Eigenvalues and eigenfunctions Feature extraction

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