Trident Academy of Technology

Bhubaneshwar, India

Trident Academy of Technology

Bhubaneshwar, India

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Rout G.C.,F M University | Panda S.,Trident Academy of Technology
Solid State Communications | Year: 2010

The spectral density function of neutron scattering is directly proportional to the imaginary part of the dynamic magnetic spin susceptibility. An attempt is made in the present communication to calculate the longitudinal spin susceptibility for the colossal magneto-resistive manganites to observe the resonance peaks at the magnetic and CDW interaction energies. The model Hamiltonian consists of s-d type exchange interaction between the spins of itinerant eg and core t2 g electrons and Heisenberg type t2 g core electron spin interactions. In addition, there exists a CDW interaction in the eg band due to charge disproportion in Mn3 + and Mn4 + ions. The magnetic susceptibility is evaluated by using equations of motion of Zubarev's technique for a two particle Green's function. The effect of CDW interaction on dynamic spin susceptibility is investigated. © 2009 Elsevier Ltd. All rights reserved.


Tripathy A.K.,Trident Academy of Technology
International Journal of Computing Science and Mathematics | Year: 2014

In this paper, a new class of generalised (Φ, ρ)-univex function is introduced. Three approaches for both primal and mixed type dual of a non-differentiable multi-objective fractional programming problems are presented. Also, the necessary and sufficient conditions of efficient solution for fractional programming are established. Weak and strong duality theorems are established under generalised (Φ, ρ)-univexity assumption. Copyright © 2014 Inderscience Enterprises Ltd.


Sahu B.,Trident Academy of Technology | Mishra D.,Siksha ‘O’ Anusandhan University
Procedia Engineering | Year: 2012

Microarray data are often extremely asymmetric in dimensionality, highly redundant and noisy. Most genes are believed to be uninformative with respect to studied classes. This paper proposed a novel feature selection approach for the classification of high dimensional cancer microarray data, which used filtering technique such as signal-tonoise ratio (SNR) score and optimization technique as Particle swarm Optimization (PSO). The proposed method is divided in to two stages. In the first stage the data set is clustered using k-means clustering, SNR score is used to rank each gene in every cluster. The top scored genes from each cluster is gathered and a new feature subset is generated. In the second stage the new feature subset is used as input to the PSO and optimized feature subset is being produced. Support vector machine (SVM), k-nearest neighbor (k-NN) and Probabilistic Neural Network (PNN) are used as evaluators and leave one out cross validation approach is used for validation. We have compared both of our approach and approaches using PSO in the literature. It has been demonstrated that our approach using PSO gives better result than others. © 2012 Published by Elsevier Ltd.


Sahoo S.,National Institute of Technology Durgapur | Das C.K.,Trident Academy of Technology | Maharana L.,Orissa Engineering College, Bhubaneswar
International Journal of Modern Physics A | Year: 2011

B0 qmixing offers a profound probe into the effects of new physics beyond the Standard Model. In this paper, Bs ooverlineBs 0}and Bd 0overlineBd 0}mass differences are considered taking the effect of both Z-and Z′-mediated flavor-changing neutral currents in the B0 qB0 qmixing (q = d, s). Our estimated mass of Z′ boson is accessible at the experiments LHC and B-factories in near future. © 2011 World Scientific Publishing Company.


Pal P.R.,National Institute of Technology Raipur | Panda R.,Trident Academy of Technology
TechSym 2010 - Proceedings of the 2010 IEEE Students' Technology Symposium | Year: 2010

Feature extraction and classification of biosignals is an important issue in development of disease diagnostic expert system (DDES). In this paper we propose a simple method for EEG classification based on Fourier features. Parameters like energy, entropy, power, and kurtosis were considered for discrimination of various categories of EEG signals. After calculating the above mentioned parameters of the discussed signals, we found that without going for rigorous time-frequency domain analysis, only frequency based analysis is well suitable to classify various EEG signals. © 2010 IEEE.


Dey N.,Larsen and Toubro Ltd | Dash T.P.,Trident Academy of Technology
International Journal of Biomedical Engineering and Technology | Year: 2011

Nowadays, Electrocardiogram (ECG) plays an important role in the primary diagnosis, prediction and survival analysis of cardiac diseases. Electrocardiography has had a profound influence on the practice of medicine. The ECG signal contains an important amount of information that can be exploited in different manners. The ECG signal allows for the analysis of anatomic and physiologic aspects of the whole cardiac muscle. Noise reduction in ECG signals is one of the main problems, which appear during analysis of electrical activity of the heart. Such noises are difficult to remove using typical filtering procedures. Efficient analytical tool, which allows increasing signal to noise ratio, is a technique of averaging of cardiac cycles. Effectiveness of this method strictly depends on stable sinus rhythm. Different ECG signals are used to verify the proposed method using MATLAB platform. In this paper, we have proposed Functional Link Artificial Neural Network (FLANN) for the denoising of the ECG signal. Copyright © 2011 Inderscience Enterprises Ltd.


Behera D.K.,Trident Academy of Technology
Smart Innovation, Systems and Technologies | Year: 2015

Clustering is the unsupervised classification of patterns which has been addressed in many contexts and by researchers in many disciplines. Fuzzy clustering is recommended than crisp clustering when the boundaries among the clusters are vague and uncertain. Popular clustering algorithms are K-means, K-medoids, Hierarchical Clustering, fuzzy-c-means and their variations. But they are sensitive to number of potential clusters and initial centroids. Fuzzy rule based Classifier is supervised and is not sensitive to number of potential clusters. By taking the advantages of supervised classification, this paper intended to design an unsupervised clustering algorithm using supervised fuzzy rule based classifier. Fuzzy rule with certainty grade plays vital role in optimizing the rule base which is exploited in this paper. The proposed classifier and clustering algorithm have been implemented in Matlab R2010a and tested with various benchmarked multidimensional datasets. Performance of the proposed algorithm is compared with other popular baseline algorithms. © Springer India 2015.


Rout G.C.,F M University | Panda S.,Trident Academy of Technology | Behera S.N.,National Institute of Science and Technology
Journal of Physics Condensed Matter | Year: 2011

We present a model study of magnetoresistance through the interplay of magnetisation, structural distortion and external magnetic field for the manganite systems. The manganite system is described by the Hamiltonian which consists of the sd type double exchange interaction, Heisenberg spinspin interaction among the core electrons, and the static and dynamic band JahnTeller (JT) interaction in the e g band. The relaxation time of the e g electron is found from the imaginary part of the Greens function using the total Hamiltonian consisting of the interactions due to the electron and phonon. The calculated resistivity exhibits a peak in the pure JT distorted insulating phase separating the low temperature metallic ferromagnetic phase and the high temperature paramagnetic phase. The resistivity is suppressed with the increase of the external magnetic field. The e g electron band splitting and its effect on magnetoresistivity is reported here. © 2011 IOP Publishing Ltd.


In this chapter, a new generalized class of higher order (F, ρ, d)-type 1 univex function is introduced with examples. KKT necessary and sufficient conditions for efficient solution for fractional programming with higher order (F, ρ, d)-type 1 univex function are established. Higher order mixed type duality for nonsmooth multiobjective fractional programming (MFP) is formulated and using the generalized higher order (F, ρ, d)-type 1 univexity assumption in the functions involved, the duality results are established. At the end, some special cases are discussed. © 2014, Operational Research Society of India.


Barik R.N.,Trident Academy of Technology
Journal of Engineering Thermophysics | Year: 2016

The effects of a steady two-dimensional laminar MHD mixed convection flow and heat transfer against a heated vertical semi-infinite permeable surface in a porous medium are discussed. The coupled nonlinear partial differential equations describing the conservation of mass, momentum, and energy are solved by a perturbation technique. The results are presented to illustrate the influence of Hartmann number (M), Prandtl number (Pr), permeability parameter (Kp), suction/blowing parameter (fw), heat generation/absorption coefficient (ϕ), and mixed convection or buoyancy parameter (γ). The effects of different parameters on the velocity and temperature as well as the skin friction and wall heat transfer are discussed with the help of figures. © 2016, Pleiades Publishing, Ltd.

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