Time filter

Source Type

Thovalai, India

Ansalam Raj T.G.,Csi Institute Of Technology | Narayanan Namboothiri V.N.,Cochin University of Science and Technology
International Journal of Advanced Manufacturing Technology | Year: 2010

Determination of optimal cutting parameters is one of the most important elements in any process planning of metal parts. This paper presents a development of an improved genetic algorithm (IGA) and its application to optimize the cutting parameters for predicting the surface roughness is proposed. Optimization of cutting parameters and prediction of surface roughness is concerned with a highly constrained nonlinear dynamic optimization problem that can only be fully solved by complete enumeration. The IGA incorporating a stochastic crossover technique and an artificial initial population scheme is developed to provide a faster search mechanism. The main advantage of the IGA approach is that the "curse of dimensionality" and a local optimal trap inherent in mathematical programming methods can be simultaneously overcome. The IGA equipped with an improved evolutionary direction operator and a migration operation can efficiently search and actively explore solutions. The IGA approach is applied to predict the influence of tool geometry (nose radius) and cutting parameters (feed, speed, and depth of cut) on surface roughness in dry turning of SS 420 materials conditions based on Taguchi's orthogonal array method. Additionally, the proposed algorithm was compared with the conventional genetic algorithm (CGA), and we found that the proposed IGA is more effective than previous approaches and applies the realistic machining problem more efficiently than does the conventional genetic algorithm (CGA). © 2009 Springer-Verlag London Limited. Source

Linda C.H.,Csi Institute Of Technology
Applied Soft Computing Journal | Year: 2011

Crack of the bone is a very serious medical condition. In medical applications, sensitivity in detecting medical problems and accuracy of detection are often in conflict. Computer detection of cracks can assist the doctors by flagging suspicious cases for closer examinations and thus improve the timeliness and accuracy. This paper presents the detailed image processing procedure including the grid formation, local thresholding, threshold value interpolation, segmentation using fuzzy index measure, background removal, and morphological filtering for the determination of infestation sites of a crack in X-ray image. The image processing procedure was tested with X-ray images of several types of crack bones. Additional tests and analyses were also performed using the developed algorithm on the X-ray images obtained with different image acquisition parameter. Compared to existing methods, this approach enhances the accuracy and reliability of proposed work. © 2011 Elsevier B.V. Source

Franklin S.W.,Csi Institute Of Technology | Rajan S.E.,Mepco Schlenk Engineering College, Sivakasi
Applied Soft Computing Journal | Year: 2014

Diabetic retinopathy (DR) is the major ophthalmic pathological cause for loss of eye sight due to changes in blood vessel structure. The retinal blood vessel morphology helps to identify the successive stages of a number of sight threatening diseases and thereby paves a way to classify its severity. This paper presents an automated retinal vessel segmentation technique using neural network, which can be used in computer analysis of retinal images, e.g., in automated screening for diabetic retinopathy. Furthermore, the algorithm proposed in this paper can be used for the analysis of vascular structures of the human retina. Changes in retinal vasculature are one of the main symptoms of diseases like hypertension and diabetes mellitus. Since the size of typical retinal vessel is only a few pixels wide, it is critical to obtain precise measurements of vascular width using automated retinal image analysis. This method segments each image pixel as vessel or nonvessel, which in turn, used for automatic recognition of the vasculature in retinal images. Retinal blood vessels are identified by means of a multilayer perceptron neural network, for which the inputs are derived from the Gabor and moment invariants-based features. Back propagation algorithm, which provides an efficient technique to change the weights in a feed forward network is utilized in our method. The performance of our technique is evaluated and tested on publicly available DRIVE database and we have obtained illustrative vessel segmentation results for those images. © 2014 Published by Elsevier B.V. Source

Kesavan Nair N.,Csi Institute Of Technology
International Journal of Electrical Power and Energy Systems | Year: 2013

This paper presents the design and implementation of Power System Stabilizers in a multimachine power system based on innovative evolutionary algorithm overtly as Breeder Genetic Algorithm with Adaptive Mutation. For the analysis purpose a Conventional Power System Stabilizer was also designed and implemented in the same system. Simulation results on multimachine systems subjected to small perturbation and three phase fault radiates the effectiveness and robustness of the proposed Power System Stabilizers over a wide range of operating conditions and system configurations. The results have shown that Adaptive Mutation Breeder Genetic Algorithms are well suited for optimal tuning of Power System Stabilizers and they work better than conventional Genetic Algorithm, since they have been designed to work on continuous domain. This proposed Power System Stabilizer is demonstrated through a weakly connected three multi-machine test systems. © 2012 Elsevier Ltd. All rights reserved. Source

Annlin Jeba S.V.,Csi Institute Of Technology | Paramasivan B.,National Engineering College
European Journal of Scientific Research | Year: 2012

Wireless sensor networks are vulnerable to security attacks due to their unattended nature and deployment in hostile environment. Security attacks include false data injection, data forgery and eavesdropping. Adversaries can inject false data reports into the WSN through compromised nodes. The compromised nodes distort data integrity by injecting false data during data forwarding. The injected false data reports lead the en-route nodes and the base station to make false decision. Moreover, false decision depletes the energy of en-route nodes and the base station and creates threat to the lifetime of the sensor nodes. To detect and drop false data number of en-route filtering schemes have been developed. This paper review some of the existing en-route filtering schemes and analyses the performance of those en-route filtering schemes based on their filtering efficiency. Finally a case study about some of the en-route filtering scheme is provided and this provided the aspects for the designers to implement suitable scheme to defend against false data injection attack. © EuroJournals Publishing, Inc. 2012. Source

Discover hidden collaborations