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Recent Papers

Speech Recognition in Noisy Environment-an Implementation on MATLAB

Speech is one of the ways to express ourselves naturally. So, speech can be used as a means to communicate with machines. In this work, using MATLAB as a platform isolated word recognizer is achieved. Speech signals get distorted by many kinds of noises. Hence, it is necessary to reduce the noise contained in the speech signal. This is called speech enhancement. Speech enhancement aims at improving the intelligibility of the speech. Noise has been removed using Spectral Subtraction with Over Subtraction technique. The feature extraction is carried out using MFCC and feature matching is achieved using HMM.

Published by: Nishitha Danthi, Dr. A. R Aswatha

Author: Nishitha Danthi

Paper ID: V3I4-1149

Paper Status: published

Published: July 4, 2017

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On Almost Contra (b, µ)-Continuous Functions.

The purpose of this paper is to introduce the notion of almost contra (b, µ)-continuous function. Also the relationships between almost contra (b, µ)-continuous functions and the other forms are investigated.

Published by: C. Rajan

Author: C. Rajan

Paper ID: V3I4-1148

Paper Status: published

Published: July 4, 2017

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Wavelet Analytical Study of Solar Wind Proton Density

The solar wind is plasma, i.e., an ionized gas that fills the solar system. It results from the supersonic expansion of the solar corona. The solar wind consists primarily of electrons and protons with a smattering of alpha particles and other ionic species at low abundance levels. The structure of the heliosphere is strongly affected by the protons produced by the photo-ionization of the interstellar neutral hydrogen and by the charge exchange of the hydrogen atoms. The wavelet is a new analytical tool for turbulent or chaotic data to the physics community. It allows detection and characterization of short-lived structures in turbulence. Proton density fluctuations are studied using discrete wavelet transforms.

Published by: Anil Kumar

Author: Anil Kumar

Paper ID: V3I4-1145

Paper Status: published

Published: July 4, 2017

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The Postwar Novel as Postmodern: Billy Pilgrim’s Imagination and the Critical Tendency Towards Teleology, Slaughterhouse – Five

This paper is an exploration of Slaughterhouse-Five (1969), an early document of American postmodern literature. In particular, this paper attempts to present the critical discussions surrounding this novel as equidistant to the broader theoretical discussions surrounding the concept of postmodernism. My contention is that, in discussing this novel, due in part to the natural teleological and linear tendencies of literary criticism, and despite the professed openness of postmodern thought to conflict, diligent efforts must be made to periodically reassert collapsed possibilities in literature. With this in mind, I approach Slaughterhouse-Five in an effort to, first, demonstrate how critics have diminished the potential meaning of each novel in imposing their own notions of a literary-historical trajectory, and, second, how readings of marginalized characters in this novel can reveal untapped potential for further exploration of the broadest definitions of the project of postmodernism.

Published by: Suman Rajest .S, Anbarasi

Author: Suman Rajest .S

Paper ID: V3I4-1141

Paper Status: published

Published: July 4, 2017

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Research Paper

An Optimization Technique to Detect the Forgery in Digital Images by Using Ant Colony Optimization

In our society digital images are a powerful and widely used communication medium. They have an important impact on communication and IT industry. The proposed versatile over division calculation sections the host picture into no overlapping and sporadic blocks adaptively. Then, the element focuses are removed from each block as block elements, and the block components are coordinated with each other to find the named highlight focuses; this technique can around show the presumed forgery districts. In past few years, research goes to detecting and classified for copy move forgery images for forensic requirement. So detection is very important challenges for testing in forensic science. In this paper detection and classification by point base and block base features SIFT and SURF Respectively but use ant colony optimization in matching and feature selection phases ,in case of SIFT features and proposed SIFT with ACO features which also use in classification with support vector machine with Gaussian and polynomial kernel

Published by: Neha Jain, Er. Sushil Bansal

Author: Neha Jain

Paper ID: V3I4-1138

Paper Status: published

Published: July 3, 2017

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Research Paper

Novel Framework for Software Defect Classification by Hybridization of Sampling and Classifier Algorithms with Kernel Principle Component Analysis

Machine Learning approaches are great in taking care of issues that have less data. Much of the time, the product space issues portray as a procedure of discovering that rely on upon the different conditions and changes as needs be. A prescient model is built by utilizing machine learning methodologies and characterized them into faulty and non-damaged modules. Machine learning methods help designers to recover valuable data after the arrangement and empower them to examine information from alternate points of view. Machine learning methods are turned out to be valuable as far as programming bug. In this paper forecast by SVM with Gaussian and polynomial kernel and use SVM method with component base learning adaptive boost

Published by: Deepak, Maninder Kaur

Author: Deepak

Paper ID: V3I4-1143

Paper Status: published

Published: July 3, 2017

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