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MRSI brain tumor characterization using wavelet and wavelet packets feature spaces and artificial neural networks

MRSI brain tumor characterization using wavelet and wavelet ...

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

作者： A. Yazdan-Shahmorad H. Soltanian-Zadeh R.A. Zoroofi 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

Magnetic resonance spectroscopic imaging (MRSI) is a non-invasive technique for assessing biochemical fingerprint of tissue composition. The need to differentiate between normal and abnormal tissues and determine type of abnormality before biopsy or surgery motivated development and application of MRSI. There are several technical reasons that make the brain easier than other organs to be examined with MRSI. This work presents our proposed methods and results for the analysis of the brain spectra of patients with three tumor types (malignant glioma, astrocytoma, and oligodendroglioma). After extracting features from MRSI data using wavelet and wavelet packets, we use artificial neural networks to determine the abnormal spectra and the type of abnormality. We evaluated the proposed methods using clinical and simulated MRSI data and biopsy results. The MRSI analysis results were correct 97% of the time when classifying the spectra of the clinical MRSI data into normal tissue, tumor, and radiation necrosis. They were correct 72% and 83% of the time when determining tumor types using the clinical and simulated MRSI data, respectively.

关键词： Wavelet packets Neoplasms Artificial neural networks Biopsy Magnetic resonance Spectroscopy Magnetic resonance imaging Fingerprint recognition Surgery Cancer

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Reactive real time behavior for mobile robots in unknown environments

Reactive real time behavior for mobile robots in unknown env...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： B.B.K. Reddy B. Kimiaghalam A. Homaifar NASA Autonomous Control and 1iformation Technology Center (NASA ACIT) Department of Electrical and Computer Engineering North Carolina Agriculture and Technical State University USA

The objective is to emulate the stimulus-response behavior for robot navigation in unknown environments. The robot's objective is to move from its current position to some predefined coordinates, namely, a predefined goal point. The proposed behavior is reactive and the robot has no prior information about the size and location of the obstacles in the environment. This control algorithm is a combination of two main behaviors: wall following and goal seeking, and is based totally on real-time data acquisition from immediate surroundings of the robot. A carefully designed fuzzy inference system (FlS) is used to determine the change in velocity and direction of the robot based on the sonar sensor and inertial cube (Gyro) sensor readings.

关键词： Mobile robots Robot kinematics Robot sensing systems Tactile sensors NASA Inference algorithms Data acquisition Fuzzy systems Sonar navigation Sensor systems

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Activation detection in multi-subject studies of fMRI using GLRT

Activation detection in multi-subject studies of fMRI using ...

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： S.M. Shams G.A. Hossein-Zadeh H. Soltanian-Zadeh Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department Institute for Studies in Theoretical Physics and Mathematics University of Tehran School of Cognitive Sciences Tehran Iran Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department Institute for Studies in Theoretical Physics and Mathematics and Medical Image Analysis Laboratory Henry Ford Health System University of Tehran School of Cognitive Sciences Iran

A new method based on generalized likelihood ratio test (GLRT) for activation detection in multi-subject studies of functional MRI (fMRI) is proposed. In this method, we test the correlation between the fMRI time series of different subjects and the bases of a signal subspace which increases the flexibility of method in detecting different shapes of hemodynamic response. The proposed multivariate method can be applied to group studies where the conventional cross-correlation method cannot be used due to its univariate property. This method is applied to both experimental and simulated fMRI data and the results are compared to those of general linear model (GLM). We show that the proposed method detects more significant activated regions in analyzing experimental data and more true voxels in simulated data

关键词： Testing Hemodynamics Brain modeling Process control Intelligent control Physics computing Mathematics Time series analysis Magnetic resonance imaging Data analysis

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Electromagnetic fields in the hollow interior region of a monocone antenna

Electromagnetic fields in the hollow interior region of a mo...

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Southeastern Symposium on System Theory

作者： S. Giles D.L. Stachowiak G. Adamovsky Electrical Engineering Department Tuskegee University Tuskegee AL USA Electrical Engineering and Computer Science Department University of Tolctlo and Eötvös Lárand University Toledo OH USA Instrumentation and Control Group NASA Glenn Research Center Cleveland OH USA

A thin, hollow, monocone antenna above a ground plane was constructed and studied. The antenna was used to roughly model the convergent region of a rocket exhaust nozzle. The input impedances and currents on the aluminum antenna were measured. The monocone field expansions were found for the exterior and interior regions of the antenna. Mode matching was used to determine the coefficients of expansion with an edge condition applied to the rim of the antenna. After the approximate electric and magnetic fields were found, the associated time-averaged Poynting vector was produced and mapped.

关键词： Electromagnetic fields USA Councils Impedance Frequency Antenna measurements Ground support Instruments NASA Electromagnetic radiation Bandwidth

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Defending against Internet worm-like infestations

Defending against Internet worm-like infestations

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International Conference on Advanced Information Networking and Applications (AINA)

作者： Shou-Chuan Lai Wen-Chu Kuo Mu-Cheng Hsieh Computer and Communication Center National Tsing Hua University Hsinchu Taiwan Department of Computer Science National Tsing Hua University Hsinchu Taiwan Department of Electrical and Control Engineering National Tsing Hua University Hsinchu Taiwan

The easy access and wide usage of the Internet make it more convenient for technical research and information exchange. However, malicious codes, such as Code Red, Nimda, SQL Slammer and W32/Blaster, also occur more frequently and severely than ever. These self-propagating malicious codes can invade network and paralyze normal network operation. These Internet worms could, in a very short time, cause great damage to network and information infrastructure. Therefore, Internet worms have become vital threats to network and security management. In this paper, we present a proactive responding scheme to deal with Internet worms. Based on this scheme, we designed and implemented a pro-active defending system against Internet worms. This proactive defending system will monitor network traffic, detect hosts with abnormal network behavior and isolate these hosts from the managed network. The results show that it can efficiently mitigate the impact caused by Internet worms and stop the wide-spreading of Internet worms.

关键词： Internet computer worms IP networks Information security Telecommunication traffic Software prototyping computer science control engineering Monitoring Military computing

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Transient stability improvement in power systems via firing angle control of TCSC using context based emotional controller

Transient stability improvement in power systems via firing ...

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Proceedings of the Biannual World Automation Congress

作者： C. Lucas F. Rashidi J. Abdi School of Intelligent Systems Institute of Studies in Theoretical Physics and Mathematics Tehran Iran Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department University of Tehran Tehran Iran

This paper proposes a Context Based Emotional controller (CBEC) to Thyrislor controlled Series Capacitor (TCSC), which might have a significant impact on power system dynamics. The role of a CBEC is to control a firing angle of the TCSC. In this case, the CBEC is used for damping the low frequency oscillations caused by disturbances such 3s a sudden change of small or large loads or an outage in the generators or transmission lines. To evaluate the usefulness of the proposed method, we compare the response of CBEC with fumy PI) controller. The simulation results show that our method has the better control performance than fuzzy PD controller.

关键词： Power system transients Power system stability control systems Power system control Power systems Power capacitors Thyristors Frequency Power system dynamics Optimal control

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Stability of linear time invariant systems with interval fractional orders and interval coefficients

Stability of linear time invariant systems with interval fra...

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International Conference on computational Cybernetics (ICCC)

作者： I. Petras YangQuan Chen B.M. Vinagre I. Podlubny Department of Informatics and Process Control BERG Faculty Technical University of Kosice Kosice Slovakia Center for Self-Organizing and Intelligent System (CSOIS) Department of Electrical and Computer Engineering Utah State University UT USA Department of Electronic and Electromechanical Engineering Industrial Engineering School University of Extremadura Badajoz Spain

This paper considers the stability of the fractional-order linear time-invariant systems with interval type uncertainties in both fractional orders and the relevant coefficients. It is an extension of our previous result on the robust stability analysis of the interval type uncertain fractional order LTI systems with crisply known fractional orders. We have proposed a stability check procedure for uncertain LTI systems with interval fractional orders and interval coefficients. The procedure is demonstrated with some simple examples

关键词： Time invariant systems Robust stability Stability analysis System testing Differential equations Polynomials Informatics Proportional control Uncertainty Robustness

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Face recognition using reinforcement learning

Face recognition using reinforcement learning

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IEEE International Conference on Image Processing

作者： M.T. Harandi M.N. Ahmadabadi B.N. Araabi School of Cognitive science (SCS) Institute of Studies in Theoretical Physics and Mathematics Tehran Iran Control and Intelligent Processing Center of Excellence Department of Electrical and Computer Engineering University of Tehran Tehran Iran

Neuroscientists believe that human beings recognize faces not only by utilizing some holistic search among all learned faces, but also through a feature analysis that aimed to specify more important features of each specific face. In this paper, we propose a hierarchical classifier that uses both holistic search and per face dominant feature analysis to recognize faces. Reinforcement learning is used to find a set of dominant features for each image in a training dataset. Wavelet transform is employed as a preprocessing tool, which results in higher discrimination among classes. Simulation studies justify the better performance of the proposed method as compared to that of eigenface method.

关键词： Face recognition Learning Principal component analysis Humans Karhunen-Loeve transforms Training data Wavelet transforms Interpolation Process control Intelligent control

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A new fuzzy-competitive algorithm for removing impulsive noises in digital images

A new fuzzy-competitive algorithm for removing impulsive noi...

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IEEE Conference on Cybernetics and Intelligent Systems

作者： M.T. Harandi C. Lucas School of Cognitive Science (SCS) Institute of Studies in Theoretical Physics and Mathematics Tehran Iran Control and Intelligent Processing Center of Excellence Department of Electrical and Computer Engineering University of Tehran Tehran Iran

Images are often contaminated by impulse noise. The major drawback of median filtering and its variants - that are widely used for removing impulsive noise - is the blurring effect for large window sizes and low noise suppression for small window sizes. In this paper, a fuzzy-competitive algorithm for removing impulse noise in images is proposed. The proposed algorithm utilized fuzzy inference systems for impulse detection. The detected impulses are then removed using long-range correlation information in a competitive scheme. The experimental results show that the performance of our method in removing impulsive noises is better than that of most other state-of-the-art methods

关键词： Digital images Filtering Detectors Hybrid intelligent systems Inference algorithms Fuzzy systems Digital filters Nonlinear filters Decision making Iterative algorithms

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A SVM-based method for face recognition using a wavelet PCA representation of faces

A SVM-based method for face recognition using a wavelet PCA ...

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IEEE International Conference on Image Processing

作者： M. Safari M.T. Harandi B.N. Araabi School of Cognitive Science SCS Institute of Studies in Theoretical Physics and Mathematics Tehran Iran Control and Intelligent Processing Center of Excellence Department of Electrical and Computer Engineering University of Tehran Tehran Iran

This paper proposes a new method of face representation which is used for face recognition by SVM. For face representation we have used a two-step method, first two-dimensional discrete wavelet transform (DWT) is used to transform the faces to a more discriminated space and then principal component analysis (PCA) is applied. The proposed method produced a significant improvement which includes a substantial reduction in error rate and in time of processing during the obtaining PCA orthonormal basis.

关键词： Face recognition Principal component analysis Support vector machines Image recognition Feature extraction Support vector machine classification Humans Authentication Linear discriminant analysis Independent component analysis

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