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Palanisamy P.,Paavai Engineering College | Nirmala S.,Center for Advanced Research
2013 International Conference on Information Communication and Embedded Systems, ICICES 2013 | Year: 2013

Femtocell has gained considerable attention to provide indoor ubiquitous mobile broadband coverage at higher data rate along with excellent voice service. It is a low power, short range, user installed Home Base Station for connection of personal equipments such as laptops, notepads and mobile phones provided priority for voice service. Operating at licensed spectrum, femtocells are overlaid on the existing macrocell network, forms a two-tier heterogeneous network. Unplanned ad-hoc manner deployment and restricted access mode of femtocells create much stronger and highly variable interference in the two-tier heterogeneous macro-femtocellular networks. The downlink is more critical in terms of femto-macro interference, because it depends on the proximity of victim UE from base station. If the victim is in much close to the aggressor base station, the QoS of victim gets much affected and there is degradation in overall system capacity and greater outage probability. Emerging interactive and content uploading services stress the need for proper femtocell interference management in such two-tier heterogeneous network. This paper presents a comprehensive study on downlink interference scenarios under co-channel deployment and detailed survey on downlink interference management strategies in such networks. It is concluded that intelligent subchannel allocation using cognitive radio concept and transmit beamforming along codebook restriction, macrocell beam subset selection, ICBM, G-ACCS and partial co-channel deployment schemes play significant role on interference management in OFDMA femtocell networks whereas, in CDMA femtocells distributed adaptive power control, joint power control with admission control and IA code assignment strategy can be used for interference management. Issues such as signaling and channel sensing overhead, computational complexity, potential error in the estimation of RB usage and time complexity in channel selection and power allocation are yet to be solved and indicate rich and clear research prospects in interference management of femtocell networks. © 2013 IEEE.


Madheswaran M.,Center for Advanced Research | Kannan K.,SASTRA University
Progress In Electromagnetics Research B | Year: 2010

The effect of optical radiation on a uniformly doped nanoscale FinFET considering quantum mechanical effects has been theoretically examined and analyzed. The device characteristics are obtained from the self-consistent solution of 3D Poisson-Schrödinger equation using interpolating wavelet method. To our best knowledge this is the first approach for the self-consistent solution to surface potential computations of nanoscale FinFET photodetector using interpolating wavelets. This method provides more accurate results by dynamically adjusting the computational mesh and scales the CPU time linearly with the number of mesh points using polynomial interpolation, hence reducing the numerical cost. A fine mesh can be used in domains where the unknown quantities are varying rapidly and a coarse mesh can be used where the unknowns are varying slowly. The results obtained for dark and illuminated conditions are used to examine the performance of the device for its suitable use as a photodetector.


Madheswaran M.,Center for Advanced Research | Kannan K.,SASTRA University
Journal of Computational Electronics | Year: 2011

A three-dimensional numerical modeling of a uniformly doped nanoscale FinFET including quantummechanical effects has been developed. A self-consistent solution of 3D Poisson-Schrödinger equation has been obtained using multiresolution approach to achieve adaptively refined mesh that can be used to get a solution with the same level of accuracy of a reference, but with a considerable lower number of points. To the best of our knowledge, this is the first approach for the self-consistent solution to surface potential computations of nanoscale FinFET device using interpolating wavelets. It performs an efficient computation by dynamically adjusting the computational mesh in order to obtain surface potential variations during simulation. This method allows non-uniform grids and scales the CPU time linearly with the number of mesh points. The exact potential profile, subthreshold swing (S) and threshold voltage (Vth) rolloff are estimated. The accuracy of the model has been verified with finite difference, finite element and experimental results. This method provides more accurate results than other existing methods. © Springer Science+Business Media LLC 2011.


Santhiyakumari N.,KS Rangasamy College of Technology | Rajendran P.,KS Rangasamy College of Technology | Madheswaran M.,Center for Advanced Research | Suresh S.,Diagnostic Ultrasound Research and Training Center
Medical and Biological Engineering and Computing | Year: 2011

An active contour segmentation technique for extracting the intima-media layer of the common carotid artery (CCA) ultrasound images employing semiautomatic region of interest identification and speckle reduction techniques is presented in this paper. An attempt has been made to test the ultrasound images of the carotid artery of different subjects with this contour segmentation based on improved dynamic programming method. It is found that the preprocessing of ultrasound images of the CCA with region identification and despeckleing followed by active contour segmentation algorithm can be successfully used in evaluating the intima-media thickness (IMT) of the normal and abnormal subjects. It is also estimated that the segmentation used in this paper results an intermethod error of 0.09 mm and a coefficient of variation of 18.9%, for the despeckled images. The magnitudes of the IMT values have been used to explore the rate of prediction of blockage existing in the cerebrovascular and cardiovascular pathologies and also hypertension and atherosclerosis. © 2011 International Federation for Medical and Biological Engineering.


Raja K.B.,PSNA College of Engineering and Technology | Madheswaran M.,Center for Advanced Research | Thyagarajah K.,PSNA College of Engineering and Technology
Machine Vision and Applications | Year: 2010

A study on ultrasound kidney images using proposed dominant Gabor wavelet is made for classifying a few important kidney categories. Three kidney categories, namely, normal (NR), medical renal diseases (MRD) and cortical cyst (CC) are considered for the analysis. Of the 30 Gabor wavelets, a unique dominant Gabor wavelet is determined by maximizing the similarity between original pre-processed image and reconstructed Gabor image. The dominant Gabor features "μ D mn" and "AAD D mn" are then evaluated to characterize the tissues of kidney region and compared with the Gabor features derived by considering all Gabor wavelets individually and as a whole using the resultant classification efficiency. The results obtained show that the proposed dominant Gabor wavelet features provide the classification efficiency of 86.66% for NR, 76.66% for MRD and 83.33% for CC, while individual wavelet features offer less than 70%, 63.33% and 66% for NR, MRD and CC. The overall classification efficiency improves by 18.89% with dominant Gabor features when compared to the classification efficiency obtained by considering all the Gaborwavelets features. The outputs of the proposed technique are validated with medical experts to assess the actual efficiency. The overall discriminating ability of the systems is also evaluated with performance evaluation measures, F-score and ROC. It has been observed that the dominant Gabor wavelet improves the classification efficiency appreciably and explores the possibility of implementing a computer-aided diagnosis system exclusively for ultrasound kidney images. © Springer-Verlag 2008.


Nagarajan C.,Bharath University | Madheswaran M.,Center for Advanced Research
Electric Power Components and Systems | Year: 2011

A closed-loop inductance capacitance inductance-T (LCL-T) series parallel resonant converter has been simulated and presented in this article. The fuzzy logic controller has been used for closed-loop operation, and the performance of the proposed converter has been estimated with a closed-loop condition. The steady-state stability analysis of the LCL-T series parallel resonant converter has been analyzed using the state-space model and simulated using MATLAB (The MathWorks, Natick, Massachusetts, USA). The proposed approach is expected to provide better voltage regulation for dynamic load conditions. A prototype 300-W, 100-kHz converter is designed and built for experimental demonstrations, and transient and steady-state performances for the LCL-T series parallel resonant converter are compared from the simulation studies. Copyright © Taylor & Francis Group, LLC.


Kumar S.J.J.,Rajaas Engineering College | Madheswaran M.,Center for Advanced Research
Journal of Medical Systems | Year: 2012

An improved Computer Aided Clinical Decision Support System has been developed to classify the retinal images using Neural Network and presented in this paper. The Optic Disc Parameters, thickness of the blood vessels, main vessel, and branch vessel and vein diameter have been extracted. Various types of Neural Network have been used for classification. The percentage of False Acceptance Rate and False Rejection Rate of the SVM classifier is found less than other classifiers. The accuracy of the proposed system has been verified and found to be 97.47%. © 2012 Springer Science+Business Media, LLC.


Muruganandam M.,Center for Advanced Research | Madheswaran M.,Center for Advanced Research
International Journal of Control, Automation and Systems | Year: 2013

The attempt is made to enhance the performance of a closed loop control of DC series motor fed by DC chopper (DC-DC buck converter) by hybridization of PID controller with an intelligent control using ANN (Artificial Neural Network) controller. This system consists of inner current controller loop and outer PID-ANN based speed controller loop. The current controller allows the PWM (Pulse Width Modulation) signal when the motor current is less than set value. The PID-ANN speed controller controls the motor voltage by controlling the duty cycle of the chopper thereby the motor speed is regulated. The PID-ANN controller performances are analyzed in both steady state and dynamic operating condition with various set speed and various load torque. The rise time, maximum over shoot, settling time, steady state error and speed drops are taken for comparison with conventional PID controller and existing work. The steady state stability analysis of the system also is made by using the transfer function model with MATLAB. The training data for PID-ANN controller is taken from conventional PID controller. The Hybrid PID-ANN controller with DC chopper has better control over the conventional PID controller and the reported existing work. This system is simulated using MATLAB/Simulink and also it is implemented with a NXP 80C51 family Microcontroller (P89V51RD2 BN) based Embedded System. © 2013 Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg.


Santhiyakumari N.,k-Technology | Rajendran P.,k-Technology | Madheswaran M.,Center for Advanced Research
Journal of Digital Imaging | Year: 2011

The objective of this work is to develop and implement a medical decision-making system for an automated diagnosis and classification of ultrasound carotid artery images. The proposed method categorizes the subjects into normal, cerebrovascular, and cardiovascular diseases. Two contours are extracted for each and every preprocessed ultrasound carotid artery image. Two types of contour extraction techniques and multilayer back propagation network (MBPN) system have been developed for classifying carotid artery categories. The results obtained show that MBPN system provides higher classification efficiency, with minimum training and testing time. The outputs of decision support system are validated with medical expert to measure the actual efficiency. MBPN system with contour extraction algorithms and preprocessing scheme helps in developing medical decision-making system for ultrasound carotid artery images. It can be used as secondary observer in clinical decision making. © Society for Imaging Informatics in Medicine 2010.


Suganthi M.,Center for Advanced Research | Madheswaran M.,Center for Advanced Research
Journal of Medical Systems | Year: 2012

An improved Computer Aided Clinical Decision Support System has been developed to classify the tumor and identify the stages of the cancer using neural network and presented in this paper. The texture and shape features have been extracted and the optimal feature set has been obtained using multiobjective genetic algorithm (MOGA). The multilayer back propagation neural network with Ant Colony Optimization and Particle Swarm Optimization has been used. The accuracy of the proposed system has been verified and found that the accuracy of 99.5% can be achieved. The proposed system can provide valuable information to the physicians in clinical pathology. © Springer Science+Business Media, LLC 2010.

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