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Bhubaneshwar, India

Das S.R.,Siksha O' Anusandhan University | Das K.,Siksha O' Anusandhan University | Mishra D.,Siksha O' Anusandhan University | Shaw K.,Gandhi Engineering College | Mishra S.,Siksha O' Anusandhan University
Procedia Engineering | Year: 2012

Classification is a vital tool for understanding the relationships of living things using which similar things can be grouped together. Classification of elements into groups makes the study relatively easy. Therefore, classification is necessary to know salient features and characteristics of living organisms as well as their inter relationship among different group of organisms, as the correct classification of a person's disease is important for proper treatment. Support vector machine (SVM) was the first proposed kernel-based method, which uses a kernel function to transfer data from input space into high dimensional feature space; it searches for a separating hyper-plane. SVM is based on simple ideas which originated in statistical learning theory; hence the aim is to solve only the problem of interest without solving a more difficult problem as an intermediate step. SVM apply a simple linear method to the data but in a high-dimensional feature space non-linearly related to the input space. Even though we can think of SVM as a linear algorithm in high dimensional space, but in practice it docs not involve any computations in that high- dimensional space. As dimensionality is curse to gene expression data set, in this paper Principal Component Analysis (PCA) is used for feature reduction to breast canccr, lung cancer and cardiography data sets, and SVM is trained by linear, polynomial and radial basis function (RBF) kernels applied on each of these data sets and the comparison among them shows that RBF is better for the three data sets. © 2012 Published by Elsevier Ltd. Source

Muduli N.,Gandhi Engineering College | Palai G.,Gandhi Institute for Technological Advancement | Tripathy S.K.,National Institute of Science and Technology
2013 Annual International Conference on Emerging Research Areas, AICERA 2013 and 2013 International Conference on Microelectronics, Communications and Renewable Energy, ICMiCR 2013 - Proceedings | Year: 2013

The various optical properties like effective mode area, effective mode index, dispersion and confinement loss of chalcogenide hexagonal photonic crystal fiber (PCF) is investigated thoroughly discussed in this paper. This paper also deals with the same properties with respect to number of air hole rings. Finite difference time domain (FDTD) technique is used to find out the modal distribution of the aforesaid PCF. Using this technique, a linear variation of both effective mode index and effective mode area are observed. Similarly an interesting result is also revealed in case of dispersion and confinement loss with respect to number of air hole rings and wavelength. © 2013 IEEE. Source

Mohanta C.K.,Gandhi Engineering College
Journal of Mechanical Engineering and Sciences | Year: 2015

The study of characterizing and featuring different kinds of flames has become more important than ever in order to increase combustion efficiency and decrease particulate emissions, especially since the study of industrial flames requires more attention. In the present work, different kinds of combustion flames have been characterized by means of digital image processing (DIP) in a 500 kW PF pilot swirl burner. A natural gas flame and a set of pulverized fuel flames of coal and biomass have been comparatively analyzed under co-firing conditions. Through DIP, statistical and spectral features of the flame have been extracted and graphically represented as two-dimensional distributions covering the root flame area. Their study and comparison leads to different conclusions about the flame behavior and the effect of co-firing coal and biomass in pulverized fuel flames. Higher oscillation levels in co-firing flames versus coal flames and variations in radiation regimen were noticed when different biomasses are blended with coal and brought under attention. © 2015 Universiti Malaysia Pahang, Malaysia. Source

Palai G.,Gandhi Institute for Technological Advancement | Tripathy S.K.,National Institute of Science and Technology | Muduli N.,Gandhi Engineering College | Patnaik D.,Gandhi Institute for Technological Advancement | Patnaik S.K.,National Institute of Science and Technology
AIP Conference Proceedings | Year: 2011

A novel method to measure the strength of Cygel™ is presented in this paper. The principle of measurement is based on linear variation of photonic band gap with the strength of Cygel™. Photonic band gap is obtained using plane wave expansion (PWE) method. Source

Dash S.,Siksha O' Anusandhan University | Dash S.,Gandhi Engineering College | Padhee R.,Siksha O' Anusandhan University | Das P.R.,Siksha O' Anusandhan University | Choudhary R.N.P.,Siksha O' Anusandhan University
Phase Transitions | Year: 2014

The polycrystalline sample of (Bi0.5Li0.5)(Fe 0.5Nb0.5)O3 was prepared by a solid-state reaction method. Preliminary X-ray structural analysis of the sample suggests the formation of a tetragonal phase with a new unit cell configuration. Dielectric, electrical, impedance and modulus properties of the material were investigated in a wide range of temperature (25-500 °C) and frequency (1 kHz-1 MHz). Two dielectric anomalies observed at 295 °C and 400 °C clearly suggest the existence of magnetic phase transition and two relaxation processes in the system. Dielectric properties have greatly been improved on addition of LiNbO3 to BiFeO3. The appearance of a hysteresis loop at room temperature confirms the ferroelectric properties of the material. The nature of the Nyquist plot confirms the presence of both bulk and grain boundary effects in the material. The ac conductivity was found to obey Jonscher's power law. The dc conductivity variation with temperature follows the Arrhenius equation. The induced voltage changes with the applied magnetic field, showing that the sample is multiferroic. © 2013 © 2013 Taylor & Francis. Source

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