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2008 9th International Conference on Signal processing(ICSP’2008)

作者： S.H.Rezatofighi R.A.Zoroofi R.Sharifian H.Soltanian-Zadeh Control and Intelligent Processing Center of Excellence Department of Electrical and Computer EngineeringFaculty of EngineeringUniversity of TehranTehran 14395-515Iran Hematology-Oncology and BMT Research Center Tehran University of Medical SciencesTehranIran Control and Intelligent Processing Center of Excellence Univ.of TehranTehranIran Henry Ford Hospital DetroitMIUSA

Automatic recognition of white blood cells in hematological can be divided into four major parts:preprocessing,image segmentation,feature extraction and *** to the multifarious nature of these cells and uncertainty in the hematological images,segmentation of white blood cells is one of the most important stages in this process.A scrupulous segmentation obviously reduces errors of next *** this paper,we introduce a novel method based on Gram-Schmidt process and parametric deformable models for segmenting the nucleus and ***,we propose a new preprocessing method for improving the results of cytoplasm ***,for finding the initial contour for parametric deformable model,an automatic scheme is *** results show that our proposed method is capable of segmenting the white blood cells in the hematological *** evaluate the proposed algorithm quantitatively,we compare its results with the manual segmentations by a *** study shows robustness of the proposed *** feature of the proposed method is that it is simple to implement.

关键词： image Segmentation of Nucleus and Cytoplasm of White Blood Cells Using Gram-Schmidt Orthogonalization and Deformable Models Nucleus

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An improvement on LEACH algorithm with a fuzzy processor

An improvement on LEACH algorithm with a fuzzy processor

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Asia-Pacific Conference on Communications

作者： M. Hamzeh S. Arab S. M. Fakhraie C. Lucas Silicon Intelligence and VLSI Signal Processing Lab School of ECE University of Tehran Iran Center of Excellence for Control and Intelligent Processing University of Tehran and School of Cognitive Science IPM Iran

Power dissipation management and hence increasing lifetime in wireless sensor networks (WSNs) is the most critical issue in the design procedure of the modern WSNs. There are many approaches through which power dissipation and lifetime of the WSNs are moderated. In this paper, we present a fuzzy rule based methodology in order to increase the power saving in LEACH algorithm. We propose a fuzzy processor to be in charge of performing fuzzy instructions. This processor is applied to track the best path online for forwarding packets instead of traditional offline table based forwarding process. In addition, this processor is capable of aggregating input data by which the network traffic is extremely reduced. Simulation results show the numerous efficiency of our methodology not only in balancing the power dissipation through network, but also in lifetime improvement, traffic management, and network availability.

关键词： Wireless sensor networks Signal processing algorithms Routing Energy consumption Clustering algorithms Telecommunication traffic Traffic control Decision making Power dissipation Energy management

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Tactile based fuzzy-Bayesian controller for prosthetic hand

Tactile based fuzzy-Bayesian controller for prosthetic hand

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International Symposium on Mechatronics and Its Applications, ISMA

作者： Hamed Khandan Caro Lucasa Research Center for Science and Technology In Medicine Tehran University of Medical Sciences Tehran Iran ECE Department Center of Excellence for Control and Intelligent Processing University of Tehran Tehran Iran

In the experience documented in this paper, we have demonstrated the ability of our novel fuzzy-Bayesian approach to machine cognition, called fuzzy-Bayesian inference system, by making it control a virtual prosthetic hand according to the feedback from its tactile sensors. The hand model is designed based on the characteristics of an average adult hand and is simulated using Java 3D technology with our own developed precise collision determination algorithm and tactile sensors simulator. In this experience, this hand could successfully learn how to pick a fragile subject like a glass without hurting it, in a few experiments.

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Implementing an XML based Unified Knowledge Manipulation Languages for SOAR cognitive architecture

Implementing an XML based Unified Knowledge Manipulation Lan...

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IEEE Conference on Cybernetics and intelligent Systems

作者： Hamed Khandan Caro Lucas Research Center for Science and Technology In Medicine Tehran University of Medical Sciences Tehran Iran Director Center of Excellence for Control and Intelligent Processing ECE Department University of Tehran Tehran Iran

SOAR is a major exemplar of architectural approach to machine cognition with numerous applications including speech recognition, machine perception, robotic, and strategy planning. We have replaced language used in SOAR architecture with our own developed XML based unified knowledge manipulation language (UKML) to demonstrate this language as a shared platform for procedural knowledge representation in cognitive architectures, and enhance SOAR with some valuable new features including the ability of manipulating XML formatted factual knowledge, greatly improved code readability and organization, and elimination of some ambiguities of Soar traditional language. This paper is a report on this implementation of UMKL, enriched with some examples and their results.

关键词： XML Cognition Knowledge representation Natural languages Biomedical imaging intelligent robots Web sites Process control intelligent control Machine intelligence

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Modified Wavelet Transform Features for Characterizing Different Plaque Types in IVUS Images;A Feasibility Study

Modified Wavelet Transform Features for Characterizing Diffe...

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2008 9th International Conference on Signal processing(ICSP’2008)

作者： A.Roodaki A.Taki S.K.Setarehdan N.Navab Control and Intelligent Processing Center of Excellence Faculty of Electrical and Computer EngineeringUniversity of TehranTehranIran Computer Aided Medical Procedures(CAMP)-TU Munich Germany

Atherosclerosis is a leading cause of most cardiovascular *** intravascular ultrasound(IVUS) image processing techniques do not allow adequate and effective identification of the coronary artery *** can be improved by defining more discriminative features for each kind of artery *** this paper,the effectiveness of a modified wavelet transform feature extraction method and the Gabor filter were studied for automated characterization of the atherosclerosis plaques within the IVUS *** methods are applied on 100 IVUS images obtained from five different *** vector machine was employed in the classification *** a result an accuracy rate of about 8o% was achieved for all methods.

关键词： filter image Modified Wavelet Transform Features for Characterizing Different Plaque Types in IVUS Images A Feasibility Study Gabor Wavelet

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Lipschitz Numbers: A Medium for Delay Estimation

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IFAC Proceedings Volumes 2008年第2期41卷 7468-7473页

作者： Iman Makaremi Alireza Fatehi Babak Nadjar Araabi Advanced Process Automation & Control (APAC) Research Group Faculty of Electrical Eng. K.N. Toosi University of Technology Tehran Iran Control & Intelligent Processing Center of Excellence School of Electrical & Computer Eng. University of Tehran Tehran Iran

The paper deals with problem of estimating input channel delay in nonlinear system with a model-free approach. The proposed method is based on Lipschitz theory. It is an extension to the Lipschitz method which was proposed for determining the order of a model. Our algorithm consists of two parts which in the first one estimation is made on the proper number of dynamics on the input and in the second part the pure delay of the input is obtained. The method is applied for estimation of the delay of two different models and the estimation was as accurate as possible.

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Real-Time Level Plant control Using Improved BELBIC

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IFAC Proceedings Volumes 2008年第2期41卷 4631-4635页

作者： M. Masoudinejad R. Khorsandi A. Fatehi C. Lucas S. Fakhimi Derakhshan M.R. Jamali Advanced Process Automation & Control (APAC) Research Group Faculty of Electrical Engineering K. N. Toosi University of Technology Tehran Iran Center of Excellence for Control and Intelligent Processing Electrical and Computer engineering Department University of Tehran Iran

Brain emotional learning based intelligent controller (BELBIC) is based on computational model of limbic system in the mammalian brain. In recent years, this model was applied in many linear and nonlinear control applications. Previous studies show that this controller has fast response, simple implementation and robustness with respect to disturbances. It is also possible to define emotional signal based on control application objectives. But in the previous studies, internal instability of this controller was not considered and control task were done in limited time period. In this article mathematical description of BELBIC is investigated and improved to avoid internal instability. Simulation and implementation of improved model was done on level plant. The obtained results showed that instability of model has been solved in the new model without loss of performance by using Integral Anti Windup (IAW).

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Approximation of a map and its derivatives with an RBF Network using input-output clustering

Approximation of a map and its derivatives with an RBF Netwo...

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International Joint Conference on Neural Networks (IJCNN)

作者： Fatemeh Tahersima Babak Nadjar Araabi Control and Intelligent Processing Center of Excellence School of Electrical & Computer Engineering University of Tehran Tehran Iran School of Cognitive Sciences Institute of Studies in Theoretical Physics and Mathematics Tehran Iran

Radial Basis Function Networks (RBFNs) are widely used in curve-fitting problems and nonlinear dynamical systems modelling. Using the gradient of the function during the training phase leads to a smooth approximation of both the function itself, and its derivatives. The knowledge about gradient of the function in some identification and control tasks is desired, particularly when the stability and robustness of the system are studied. In this paper, a new clustering based algorithm for learning an Input-Output map along with its derivatives using RBFN is proposed. The input-output clustering (IOC) algorithm for the training of an RBFN is modified to improve the performance of the network in approximating a nonlinear single-input single-output map along with its derivatives utilizing a set of input-output data and the first derivative of the function in each data point. The advantage of the proposed algorithm, in comparison with orthogonal least square (OLS), is demonstrated with an example in the field of data interpolation.

关键词： Training data Approximation algorithms Approximation methods Clustering algorithms Function approximation Training Artificial neural networks

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Automatic segmentation of brain structures from MRI integrating atlas-based labeling and level set method

Automatic segmentation of brain structures from MRI integrat...

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Canadian Conference on Electrical and Computer Engineering (CCECE)

作者： Matineh Shaker Hamid Soltanian-Zadeh Control and Intelligent Processing Center of Excellence Department of Electrical and Computer University of Tehran Tehran Iran Image Analysis Laboratory Department of Radiology Henry Ford Hospital Detroit MI USA

The purpose of this study is to segment hippocampus, amygdala and entorhinal cortex in magnetic resonance images (MRI) of temporal lobe epilepsy (TLE) patients. The proposed method consists of two separate parts. First, we use an atlas-based segmentation method to obtain initial segmentation results for desired structures. Using additional preprocessing steps for image registration and gray matter (GM) segmentation is the specification of this stage of the work. Then, all of the GM voxels are labeled using an anatomical atlas. In the next stage, variational level set formulation without re-initialization is applied on the images. We use the boundaries obtained by atlas-based segmentation as the contour for initialization of level set function. Automatic generation of initial contour makes the final segmentation results operator-independent. The proposed approaches are evaluated by comparing automatic and expertpsilas segmentation results and confirming their similarity.

关键词： Brain Magnetic resonance imaging Labeling Level set Image segmentation Hippocampus Magnetic resonance Temporal lobe Epilepsy Image registration

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Hybrid error concealment in image communication using data hiding and spatial redundancy

Hybrid error concealment in image communication using data h...

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International Conference on Telecommunications (ICT)

作者： Alireza Kenarsari Anhari Shabnam Sodagari Alireza Nasiri Avanaki Department of Electrical and Computer Engineering University of British Columbia Vancouver BC Canada Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran

Designed to diminish the artifacts caused by application of the state-of-the-art error concealment methods, a hybrid error concealment scheme is introduced. The proposed scheme stands out by using the inherent spatial redundancy of natural images along with a data hiding technique to obtain the information required for reconstruction of the lost parts of the image at the receiver. Furthermore, to maintain the quality of the received image in high packet loss conditions, an alternative scheme is proposed which will be activated in response to a receiverpsilas feedback reporting a high packet loss ratio. Our simulation results show that the proposed scheme outperforms the existing methods in terms of the quality of the received image and computational cost.

关键词： Transform coding Watermarking Image coding Decoding Approximation methods Interpolation Estimation

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