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Nanda S.K.,Synergy Institute of Technology | Tripathy D.P.,National Institute of Technology Rourkela
Noise and Vibration Worldwide | Year: 2010

Noise is often regarded as a nuisance rather than as an occupational hazard in an opencast mining environment. Prolonged exposure to noise over a period of years generally causes permanent damage to the auditory nerve and/or its sensory components. To maintain the good working environment in mines, appropriate noise survey of machineries should be conducted. The measured sound pressure levels (SPL) of equipment are not accurate due to instrumental error, attenuation due to geometrical aberration, atmospheric attenuation etc. Some of the popular noise prediction models e.g. CONCAWE, VDI and ENM have been applied in mining and allied industries to predict the machineries noise by considering all the attenuation factors. In this paper, authors have predicted machineries noise in an opencast mine using CONCAWE model.


Nanda S.K.,Synergy Institute of Technology | Tripathy D.P.,National Institute of Technology Rourkela | Patra S.K.,National Institute of Technology Rourkela
Noise Control Engineering Journal | Year: 2010

Artificial neural network models are simple to apply and have generated a great deal of interest in engineering. By considering the successfully application of artificial neural networks in complex engineering problems, in this paper, artificial neural network system based noise prediction models were developed for predicting far field noise levels due to operation of specific set of mining machinery. Multi-Layer Perceptron (MLP) and Radial Basis Function Network (RBFN) systems were used to predict the machinery noise in opencast mines. The proposed models were designed with VDI-2714 noise prediction model. It was taken due to simplicity, for design of artificial neural network system based noise prediction models for opencast mines. From the present investigations, it was observed that the RBFN model gave better noise predictions than the MLP model. © 2010 Institute of Noise Control Engineering.


Mohanty R.K.,Synergy Institute of Technology | Pattanayak B.K.,Siksha O' Anusandhan University | Mohapatra D.P.,National Institute of Technology Rourkela
International Journal of Software Engineering and its Applications | Year: 2014

Service Oriented Architecture (SOA) based application can be composed of heterogeneous self-contained independent services on the web. These applications are usually modified to fix bugs or to enhance their functionality. These modifications are quick and they should be supported by rapid verification. Regression Test (RT) is essential to ensure that modifications do not result in adverse effects. Regression Test Selection (RTS), one of the cheapest techniques, aims at decreasing cost of carrying out RT. This paper presents a Control Flow Graph (CFG) based approach that makes it feasible to apply a safe RTS technique to SOA based applications or services in an end-to-end manner. Safe RTS technique guarantees that no modification revealing tests will be left unselected. A simplified navigational subsystem that involves 3 services, is used to elicit our approach. © 2014 SERSC.


Mohanty M.N.,Siksha O' Anusandhan University | Sahu B.,Siksha O' Anusandhan University | Nayak P.K.,Synergy Institute of Technology | Mishra L.P.,Siksha O' Anusandhan University
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2013

Nonlinear dynamic systems are characterized with uncertainties in terms of structure and parameters. These uncertainties cannot be described by deterministic models. The modelling and identification of nonlinear dynamic systems through the measured experimental data is a problem in engineering and technical processes. Therefore, field of system identification have become an important area of research. Fuzzy technology is an effective tool for dealing with complex nonlinear processes that are characterized with uncertain factors. In this paper, a novel approach based on Local Linear method learning in dynamical filter weights neurons for the identification of non-linear dynamic systems is presented. The fuzzy wavelet neural network combines wavelet theory with fuzzy logic and neural networks. Learning fuzzy rules and parameter update in fuzzy wavelet neural network is based on gradient decent method. The proposed approach is said to be Fuzzy Local Linear Wavelet Neural Network based model. It has been explained through examples. The structure is tested for the identification with both wavelet neural network and Fuzzy Local Linear Wavelet Neural Network that shows the comparative performance. © 2013 Springer International Publishing.


Mohanty R.K.,Synergy Institute of Technology | Pattanayak B.K.,Siksha O' Anusandhan University | Mohapatra D.P.,National Institute of Technology Rourkela
ARPN Journal of Engineering and Applied Sciences | Year: 2012

Web services represent the class of Service Oriented Architecture (SOA) based applications with a hugely diversified domain. Web service regression testing presents a set of challenges to the tester which need to be overcome in order to provide a reliable performance of the desired application. Code based regression testing approaches present a lot of difficulties as the tester needs to know the code which is in most cases not possible. In this paper, we address a UML based regression testing method independent of the code using test cases generated from use cases in the context of a case study. © 2006-2012 Asian Research Publishing Network (ARPN).

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