Mepco Schlenk Engineering College

About: Mepco Schlenk Engineering College is a based out in . It is known for research contribution in the topics: Wavelet & Wavelet transform. The organization has 1307 authors who have published 1665 publications receiving 18690 citations.

Removal of artifact from EEG signal using differential evolution algorithm

Abstract: Electroencephalogram (EEG) is the neurophysiologic measurement of the electrical action of the brain, acquired by recording from electrodes located on the scalp. EEG is a vital clinical tool for diagnosing, monitoring and managing neurological disorders. EEG signal is contaminated with various artifacts such as Electroocculogram (EOG), Electrocardiogram (ECG) and Electromyogram (EMG). In this paper, we propose a novel method called ANFIS-DE (Adaptive Neuro Fuzzy Inference System (ANFIS) tuned by Differential Evolution (DE) algorithm) to estimate the artifacts and to extract the EEG signal from stained EEG signal. Differential Evolution (DE) algorithm is used to find the optimum design parameters of ANFIS to achieve better performance and faster convergence with simpler structure. Quantitative analysis of Signal to Noise Ratio and Mean Square Error reveals that ANFIS parameters tuned with Differential Evolution algorithm (ANFIS-DE) outperforms the ANFIS with general hybrid learning algorithm.

Adaptive fuzzy logic speed controller for brushless DC motor

Abstract: A novel method for speed control of brushless dc motor using adaptive fuzzy logic and PI control algorithms has been presented in this paper. Fuzzy logic and PI controllers are formulated and designed using MATLAB toolbox. The parameters such as rise time, peak overshoot, recovery time, settling time and steady state error of a brushless DC motor are taken for analyzing the performance of the proposed controller. The simulation result demonstrated that the response of brushless dc motor with adaptive fuzzy logic shows satisfactory and well damped performance compared to classical PI controller.

An intensive search evolutionary algorithm for single-machine total-weighted-tardiness scheduling problems

Abstract: In this paper, an intensive search evolutionary algorithm is proposed to solve single machine total weighted tardiness scheduling problems. A specialised locally improved random swap mutation operator and an ordered crossover operator are used for evolution. The proposed algorithm starts with a pair of sequences: one generated by a greedy heuristic, namely, a backward phase heuristic acts as one parent, and a randomly generated sequence acts as the other. A computational experiment is conducted by applying the mutation operator on the backward phase sequence and the proposed algorithm with the same number of generations as the termination criteria. A total of 125 benchmark instances for sizes 40, 50 and 100 available in the OR library are solved and the results are compared with the available best-known results. It is observed that the proposed evolutionary algorithm provides better results than others .

Tumor Detection in Brain Magnetic Resonance Images Using Modified Thresholding Techniques

Abstract: Automated computerized image segmentation is very important for clinical research and diagnosis. The paper deals with two segmentation schemes namely Modified Fuzzy thresholding and Modified minimum error thresholding. The method includes the extraction of tumor along with suspected tumorized region which is followed by the morphological operation to remove the unwanted tissues. The performance measure of various segmentation schemes are comparatively analyzed based on segmentation efficiency and correspondence ratio. The automated method for segmentation of brain tumor tissue provides comparable accuracy to those of manual segmentation.

Investigation of cloudless solar radiation with PV module employing Matlab-Simulink

Abstract: This paper focuses an novel approach on the prediction of Voltage-Current(V-I) characteristics of a Photovoltaic panel under varying weather conditions and also the modelling of hourly cloudless solar radiation to provide the insolation on a PV module of any orientation, located at any site. The empirical model developed in this study uses standard specifications together with actual solar radiation and cell temperature. This proposed work develops a Matlab-Simulink block to generate solar radiation at any location and for any time of the year. A new model for Current-Voltage (I-V) characteristics and Maximum Power operation of a Photovoltaic (PV) module is also presented which aims to model the effect on I-V and P-V curves of varying climatic conditions. Moreover, this model has been implemented using the Matlab-Simulink and is used to investigate the effect of meteorological conditions on the performance of a PV module generator. Thus the combined model of cloudless solar radiation and the photovoltaic module provide a tool that may be loaded in the library for analysis purpose. It is found that the predicted solar radiation strongly agrees with the experimental data.