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Prasanna Devi S.,Apollo Engineering College | Suryaprakasa Rao K.,Anna University
Advances in Intelligent Systems and Computing | Year: 2015

The aim of this paper is to study about the awareness among the people in Chennai city, Tamil Nadu, about the causes of pollution. Initially, the k-means clustering method was applied to group variables rather than observations in the design of questionnaires. The first draft of a questionnaire contained more questions than is prudent to ensure a good response rate. When the draft questionnaire is tested on a smaller number of respondents (75 samples), it was observed that the responses to certain groups of questions are highly correlated. Hence, clustering analysis was applied to identify groups of questions that are most predominant in contributing to the reduction in air pollution in Chennai. Thus, the selected questions were used for survey purpose to study the acceptability among different sectors of people. Primary data were collected from 110 people belonging to different sectors of Chennai using questionnaire method. In the second level of cluster analysis, the cluster analysis was carried out to assign observations to groups. These results were further applied to identify the recommendation of suitable transport policies to mitigate vehicular pollution. This method of applying clustering techniques in two levels of the questionnaire analysis has been newly proposed in this paper. © Springer India 2015. Source

Bharathi Sankar A.,Apollo Engineering College
IEEE-International Conference on Advances in Engineering, Science and Management, ICAESM-2012 | Year: 2012

This paper presents the development of design, modeling and simulation for variable speed wind turbine doubly fed induction generator are simulated through computer software tool using MATLAB/SIMULINK. A variable wind speed turbine doubly fed induction generator with power electronics interface is modeled for dynamic simulation analysis. The MATLAB/SIMULINK is provided to implements the wind turbine and doubly fed induction generator components models and equations. Controllable power inverter strategies are intended for capturing the maximum power under variable speed operation and maintaining reactive power generation at a pre-determined level for constant power factor control or voltage regulation control. Control schemes for both wind turbine and doubly fed induction generator are constructed by user-define function provided in the simulation. Simulation case studies provide the variable speed wind doubly fed induction generator dynamic performance for changes in different wind speed. This control scheme of this model can be employed to regulate the real power, reactive power, generated voltage and generated speed at different wind speed in the power system. Simulation results of this model can be validate the real power, reactive power, generated voltage and generated speed at different wind speeds in the power system. Its simulations results are presented. © 2012 Pillay Engineering College. Source

Baskar A.,Apollo Engineering College
International Journal of Industrial Engineering Computations | Year: 2016

Permutation flow shop scheduling problems have been an interesting area of research for over six decades. Out of the several parameters, minimization of makespan has been studied much over the years. The problems are widely regarded as NP-Complete if the number of machines is more than three. As the computation time grows exponentially with respect to the problem size, heuristics and meta-heuristics have been proposed by many authors that give reasonably accurate and acceptable results. The NEH algorithm proposed in 1983 is still considered as one of the best simple, constructive heuristics for the minimization of makespan. This paper analyses the powerful job insertion technique used by NEH algorithm and proposes seven new variants, the complexity level remains same. 120 numbers of problem instances proposed by Taillard have been used for the purpose of validating the algorithms. Out of the seven, three produce better results than the original NEH algorithm. © 2016 Growing Science Ltd. All rights reserved. Source

Nhagopal N.,SKP Engineering College | PonniwalavanProfessor R.,Apollo Engineering College
International Journal of Oceans and Oceanography | Year: 2014

This proposed system for pre-processing and enhancement through Magnetic Resonance Image (MRI) is a gradient based image enhancement method and is based on the first derivative, local statistics. The main objective of this segmentation process is to increase the quality and efficiency of segmentation techniques in CAD system which is used for detection of brain tumor. In this work, image segmentation by metahuristic algorithms Genetic Algorithm and Parallel Ant colony optimization (PACO) methods are developed and applied MR brain image with the aim of segmenting normal tissue from tumor tissue. And also the work deals with the task of optimizing the approach for image segmentation in digitized MR brain image are investigated. © Research India Publications. Source

Baskar A.,Apollo Engineering College | Anthony Xavior M.,Vellore Institute of Technology
Procedia Engineering | Year: 2014

This paper analyses a specific case of permutation flow shop scheduling problem with job and machine priority. Sometimes, a particular job has to precede or succeed another job; or a set of jobs are to be together for a specific reason. Within the set of jobs also, there may be a condition that a particular job has to precede or succeed another job. In such case, the scheduling is done in two or more phases to optimize the makespan. In many occasions, the percentage utilization of a particular machine has to be increased due to several reasons. The machine may be costlier, rented, and highly precise or needs to be operated continuously. In the context of the permutation flow shop scheduling, the percentage utilization is calculated in terms of machining time compared with the makespan. For a fixed number of jobs, the total machining time for each machine is also fixed and reduction in the makespan only can increase the percentage utilization. On the other hand, splitting the machining times and regrouping may also help for achieving the objective. The problem is demonstrated with numerical examples. For trial purpose, the machining time of all the jobs that come before and after the priority machine are split (25% and 50%) individually and also in toto, and combined with the critical machine. The number of jobs and machines is kept the same. Consequently, the makespan and percentage utilization have been computed and compared with the original case. © 2014 The Authors. Source

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