Electrical Engineering

<p>Shiv Nadar University is a comprehensive, multidisciplinary, research-focused, and student-centric University offering a full range of academic programs at the undergraduate, postgraduate and doctoral level. With state-of-the-art infrastructure, the University comprises of academic wings, sophisticated labs, international standard sports facilities, amphitheaters, auditorium, conference rooms and smart classrooms. The University&rsquo;s goal is to become internationally recognized for the quality of its research and creative endeavors and their applicability to improving quality of life, generating new insights and expanding the boundaries of human knowledge creativity. Committed to excellence in teaching, research and service, the University aims to serve the higher education needs of India and the world beyond.</p>

Shiv Nadar University

This paper presents the experimental studies on self-breakdown-based single-gap plasma cathode electron (PCE) gun (5-20 kV/50-160 A) in argon, gas atmosphere and its performance evaluation based on particle-in-cell (PIC) simulation code OOPIC-Pro. The PCE-Gun works in conducting phase (low energy, high current) of pseudospark discharge. It produces an intense electron beam, which can propagate more than 200 mm in the drift space region without external magnetic field. The profile of this beam in the drift space region at different breakdown conditions (i.e., gas pressures and applied voltages) has been studied and the experimental results are compared with simulated values. It is demonstrated that30% beam current is lost during the propagation possibly due to space charge neutralization and collisions with neutral particles and walls. © Indian Academy of Sciences.

World University root node

(SoE) School of Engineering

Pramana - Journal of Physics

Performance evaluation of self-breakdown-based single-gap plasma cathode electron gun

In this paper we introduce an adaptive channel estimation scheme for two-way relay with node capability. The adaptive filter used is called Block Fast Array Multichannel 2D-Recursive Least Square (BFAM 2D-RLS). The modulation used is Orthogonal Frequency Division Multiplexing (OFDM) and channel estimation is done in the frequency domain. The proposed channel estimator considers correlation of channel frequency response in both time and frequency domain. The computational complexity is calculated and convergence performance of the adaptive channel estimator is studied. This paper also introduces an AOFDM scheme for two-way relay systems. The effect of channel estimation error on performance of Adaptive OFDM (AOFDM) is analyzed for pedestrian A (pedA) channel. All computer simulations are performed using MATLAB ®. © 2014 IEEE.

International Congress on Ultra Modern Telecommunications and Control Systems and Workshops

Performance study of BFAM 2D-RLS channel estimator for AOFDM based two-way relay

Electrodeposited bismuth telluride (Bi2Te3) nanowires using anodic alumina (AAO) templates show anisotropic thermal properties in a direction parallel and perpendicular to the nanowire/nanochannel axis. The present study reports thermal diffusivity measurement of templated Bi 2Te3 nanowires in a direction perpendicular to the nanowire axis, using an active infrared thermography based noncontact technique. Measurements were performed on empty AAO templates of varying pore dimensions, AAO/Bi2Te3 nanocomposites and a single crystal Bi 2Te3 sample. A first order lower bound model estimation showed nearly five-fold reduction of thermal conductivity in 200 nm Bi 2Te3 nanowires as compared to the bulk values. © 2013 Elsevier B.V.

Materials Letters

Thermal diffusivity measurements of templated nanocomposite using infrared thermography

The paper presents a novel framework for large class, binary pattern classification problem by learning-based combination of multiple features. In particular, class of binary patterns including characters/primitives and symbols has been considered in the scope of this work. We demonstrate novel binary multiple kernel learning-based classification architecture for applications including such problems for fast and efficient performance. The character/primitive classification problem primarily concentrates on Gujarati and Bangla character recognition from the analytical and experimental context. A novel feature representation scheme for symbols images is introduced containing the necessary elastic and non-elastic deformation invariance properties. The experimental efficacy of proposed framework for symbol classification has been demonstrated on two public data sets. © 2014, Springer-Verlag Berlin Heidelberg.

International Journal on Document Analysis and Recognition

Feature combination for binary pattern classification

The practically important case of dielectric loaded tape helix enclosed in a perfectly conducting coaxial conductor is analysed in this paper. The dispersion equation for the infinitesimally thin and anisotropically conducting tape is derived from an exact solution of a homogeneous boundary value problem for Maxwell's equation. The boundary value problem is solved to yield the dispersion equation which takes the form of the solvability condition viz., the determinant of the infinite-order coefficient matrix is zero. For the numerical computation of the approximate dispersion characteristics, all the entries of the symmetrically truncated version of the coefficient matrix are estimated by summing an adequate number of the rapidly converging series for them. The numerical computation of dispersion characteristics and phase speed variations for different values of b/a (outer conductor to inner helix radius) and effective dielectric permittivity is presented. © 2014 IEEE.

IEEE International Vacuum Electronics Conference, IVEC 2014

Wave propagation characteristics in anisotropically conducting dielectric loaded tape helix slow wave structures

Speech feature extraction is the most significant step in any Automatic speaker recognition system. In the last 60 years a lot of research has gone into parametric representation of these speech features. Several techniques are currently being used for Automatic Speaker Recognition. Yet Automatic Speaker Recognition still remains a confront mainly due to variations in speaker's vocal tract with time and health, varying environmental conditions, disparities in the behavior and quality of speech recorders etc. MFCC is a extensively used technique in Automatic speaker recognition. In this paper the performance of MFCC technique was evaluated in a quiet environment. A speaker database containing 30 male and 30 female speakers was created. Two separate experiments were conducted for the performance evaluation of MFCC technique when applied to K means clustering. In the first case the speech features were directly matched. In the second case a VQ codebook was created by clustering the training features of these 60 speakers. A distortion easure based on the minimum Euclidean distance was used for speaker recognition. The failure rate of speaker recognition in first ase was found to be was found to be 10\% while in the second case as found to be 14\%. Matlab-7.10.0 was used for this study © 2014 IEEE.

ICROIT 2014 - Proceedings of the 2014 International Conference on Reliability, Optimization and Information Technology

Mel frequency cepstral coefficients based text independent Automatic Speaker Recognition using matlab

Photovoltaic (PV) arrays produce less power than the array rating due to shading on the array. Since the modules of the arrays receive different solar irradiation, the powervoltage characteristics of photovoltaic (PV) arrays contain multiple local maxima. This paper presents a novel approach to arrange the physical position of modules in Totally Cross Tied (TCT) configuration, without changing the electrical connection of the modules in the array, in such a way that there is an increase of power generation of array under partial shading condition. The modules of TCT configuration are rearranged in such a way that the shading effect is distributed over the array, and it reduces the multiple local maxima in power-voltage characteristics of PV array. Hence tracking of global maximum power point (GMPP) in the present approach is simpler. In this paper, the power generation of array with TCT and proposed configuration is compared. It is demonstrated that the power generation of array with proposed configuration is enhanced under different shading pattern. © 2014 IEEE.

2014 IEEE Innovative Smart Grid Technologies - Asia, ISGT ASIA 2014

Power enhancement of partially shaded PV array by using a novel approach for shade dispersion

The paper presents a novel framework for the application of multiple features for handwritten data based identity recognition. Different types of features characterise different facets of the handwriting. We have designed a scheme for multiple feature based identity establishment using multi-kernel learning. A new formulation for multi-kernel learning using genetic algorithm has been presented. The efficacy of the framework using individual and combination of features is demonstrated for Devanagari script input. © 2013 Elsevier B.V. All rights reserved.

Pattern Recognition Letters

Off-line hand written input based identity determination using multi kernel feature combination

The buckling of conductors of inner windings in transformers is one of the major causes of their failures. It can occur when a large magnitude of radial short-circuit electromagnetic force acts on them. In this paper, initially, mechanical strains developed during winding processes and due to radial short-circuit forces have been determined. The two mechanical strains viz. the short-circuit induced strain and the winding process-induced strain are algebraically added to obtain their resulting strain. The stress corresponding to the resulting strain has been determined by using the Ramberg-Osgood stress-strain relation. The critical buckling stress has been calculated and compared with the resulting stress. The analytically obtained result of the strain induced in the winding conductor during its winding process has been verified using the finite-element method. A case study has been described in which the factor of safety against the buckling strength is determined. © 1986-2012 IEEE.

IEEE Transactions on Power Delivery

Analysis of buckling strength of inner windings in transformers under radial short-circuit forces

The synergy of the two paradigms, neural network and fuzzy inference system, has given rise to rapidly emerging filed, neuro-fuzzy systems. Evolving neuro-fuzzy systems are intended to use online learning to extract knowledge from data and perform a high-level adaptation of the network structure. We explore the potential of evolving neuro-fuzzy systems in reinforcement learning (RL) applications. In this paper, a novel on-line sequential learning evolving neuro-fuzzy model design for RL is proposed. We develop a dynamic evolving fuzzy neural network (DENFIS) function approximation approach to RL systems. Potential of this approach is demonstrated through a case study-two-link robot manipulator. Simulation results have demonstrated that the proposed approach performs well in reinforcement learning problems. © 2014 IFAC.