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Biswal M.,Silicon Institute of Technology | Dash P.K.,Siksha O' Anusandhan University
Digital Signal Processing: A Review Journal | Year: 2013

This paper proposes fast variants of the discrete S-transform (FDST) algorithm to accurately extract the time localized spectral characteristics of nonstationary signals. Novel frequency partitioning schemes along with band pass filtering are proposed to reduce the computational cost of S-transform significantly. A generalized window function is introduced to improve the energy concentration of the time-frequency (TF) distribution. An application of the proposed algorithms is extended for detection and classification of various nonstationary power quality (PQ) disturbances. The relevant features required for classification were extracted from the time-frequency distribution of the nonstationary power signal patterns. An automated decision tree (DT) construction algorithm was employed to select optimal set of features based on a specified optimality criterion for extraction of the decision rules. The set of decision rules thus obtained were used for identification of the PQ disturbance types. Various single as well as simultaneous power signal disturbances were considered in this paper to prove the efficiency of proposed classification scheme. A comparison of the classification accuracies with techniques proposed earlier, clearly demonstrates the improved performance. The major contributions of this manuscript are new FDST algorithms for fast and accurate time-frequency representation and an efficient classification algorithm for identifying PQ disturbances. The advantages of the classification algorithm are (i) accurate feature derivation from the TF distribution and optimum feature selection by the DT construction algorithm, (ii) robust performance at different signal-to-noise ratios, (iii) simple decision rules for classification, and (iv) recognition of simultaneous PQ events. © 2013 Elsevier Inc. All rights reserved.

Mohapatra A.G.,Silicon Institute of Technology
Sensors and Transducers | Year: 2011

Collision Avoidance System solves many problems caused by traffic congestion worldwide and a synergy of new information technologies for simulation, real-time control and communications networks. The above system is characterized as an intelligent vehicle system. Traffic congestion has been increasing world-wide as a result of increased motorization, urbanization, population growth and changes in population density. Congestion reduces utilization of the transportation infrastructure and increases travel time, air pollution, fuel consumption and most importantly traffic accidents. The main objective of this work is to develop a machine vision system for lane departure detection and warning to measure the lane related parameters such as heading angle, lateral deviation, yaw rate and sideslip angle from the road scene image using standard image processing technique that can be used for automation of steering a motor vehicle. The exact position of the steering wheel can be monitored using a steering wheel sensor. This core part of this work is based on Hough transformation based edge detection technique for the detection of lane departure parameters. The prototype designed for this work has been tested in a running vehicle for the monitoring of real-time lane related parameters. © 2011 IFSA.

Biswal M.,Silicon Institute of Technology | Dash P.K.,Siksha O' Anusandhan University
IET Science, Measurement and Technology | Year: 2012

The S-transform (ST) finds widespread application in non-stationary signal analysis. However, the relatively high computational complexity of the ST remains as a challenge. Further, the optimum choice of the window function and the discretisation side effects of the ST need to be addressed for accurate time-frequency localisation. This study proposes a fast adaptive discrete generalised ST (FDGST) algorithm based on a new frequency scaling named selective frequency scaling, window cropping and an adaptive window function. The proposed algorithm optimises the shape of the window function for each analysis frequency to improve the energy concentration of the time-frequency distribution, and applies folded window functions to minimise aliasing affect owing to discretisation. Further, the algorithm is applied for analysis and measurement of parameters in various types of power quality waveforms. Standard transient and steady-state indices calculation from the FDGST analysis is also illustrated. The improved performance of the proposed algorithm is supported by simulations using synthetic as well as practical signals. © 2012 The Institution of Engineering and Technology.

Routray M.,Silicon Institute of Technology
ICACCS 2015 - Proceedings of the 2nd International Conference on Advanced Computing and Communication Systems | Year: 2015

Physical interactions between the proteins in a living organism helps in identification of most protein-protein interaction data. The annotated proteins are previously known by their functions. Their knowledge is definite. The un-Annotated proteins are annotated based on estimation of such similar functions. Generally a cluster containing annotated nodes with their adjacent unlabeled nodes is assumed to have homogeneity of functions within. Though the interaction data are generally very noisy, a Bayesian model is presented to predict protein functions after a series of known experiments or several hypotheses over neighborhood properties are conducted or assumed. The experimental results in this effort have shown that there is a better performance in evaluation of weighted accuracy of functions over prediction of data set. © 2015 IEEE.

Lal D.K.,Sambalpur University | Dash B.B.,Silicon Institute of Technology | Akella A.K.,National Institute of Technology Jamshedpur
International Journal on Electrical Engineering and Informatics | Year: 2011

A large proportion of the world's population lives in remote rural areas that are geographically isolated and sparsely populated. This paper proposed a hybrid power generation system suitable for remote area application. The concept of hybridizing renewable energy sources is that the base load is to be covered by largest and firmly available renewable source(s) and other intermittent source(s) should augment the base load to cover the peak load of an isolated mini electric grid system. The study is based on modeling, simulation and optimization of renewable energy system in rural area in Sundargarh district of Orissa state, India. The model has designed to provide an optimal system conFigureuration based on hour-by-hour data for energy availability and demands. Various renewable/alternative energy sources, energy storage and their applicability in terms of cost and performance are discussed. The homer software is used to study and design the proposed hybrid alternative energy power system model. The Sensitivity analysis was carried out using Homer program. Based on simulation results, it has been found that renewable/alternative energy sources will replace the conventional energy sources and would be a feasible solution for distribution of electric power for stand alone applications at remote and distant locations.

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