Kongu Engineering College

About: Kongu Engineering College is a based out in . It is known for research contribution in the topics: Computer science & Cluster analysis. The organization has 2001 authors who have published 1978 publications receiving 16923 citations.

Imputation of Discrete and Continuous Missing Values in Large Datasets Using Bayesian Based Ant Colony Optimization

Abstract: When preparing large databases, obtaining quality data for analysis without any missing values is almost impossible in many cases. Integration of raw data from multiple heterogeneous sources often results in some values missing leading to loss of valuable information. Even though many methods have been introduced by researchers, only less effort has been spent on handling missing values in heterogeneous attributes (both discrete and continuous) under Missing At Random pattern, the common scenario where missing values have dependency on covariates in the dataset. Also, only few techniques are capable of dealing with missing values in large databases and this demands immediate attention of researchers. This paper addresses both these problems by introducing a single technique called Bayesian Ant colony Optimization (BACO) which combines the searching capability of Ant Colony Optimization with probabilistic nature of Bayesian principles. The algorithm is designed in such a way that missing values in both discrete and continuous attributes in large datasets are efficiently imputed. BACO is implemented in six large real datasets, and it is observed that its imputation accuracy outperforms than that of existing standard techniques. The statistical tests conducted also prove the superior results of BACO in the imputation process.

Synthesis and characterization of Dextran, poly (vinyl alcohol) blend biopolymer electrolytes with NH4NO3, for electrochemical applications

Abstract: New biocompatible biopolymer membranes have been synthesized from naturally occurring bacterial polysaccharide Dextran, which is efficacious versatile polymer known for medicinal applications. In t...

Optimum utilization of grid connected hybrid renewable energy sources using hybrid algorithm

Abstract: An optimal utilization of smart grid connected hybrid renewable energy sources is proposed in this paper. The hybrid technique is the combination of recurrent neural network and adaptive whale opti...

Implementation of Orthogonal Frequency Division Multiplexing (OFDM) Using Software Definable Radio (SDR) Platform

Abstract: Radio platform is one of the upcoming technologies that have the efficient characteristics like flexibility, adaptability and reconfigurability. The best effort service is also provided by this platform. The concepts related to radio flexibility can be defined and explored by the radio platforms. SDR is one of the radio platforms which is adaptive and provides future proof solutions to the wireless networks making them very flexible. The conventional hardware is replaced with reconfigurable, reprogrammable radio. SDR platform also balances against the risky condition of committing to fixed function and inflexible hardware in an environment of changing standards. OFDM is the modulation scheme which is mainly used in wireless communication. The orthogonal property maintained in OFDM eliminates the inter symbol interference which is a common problem in wireless communication. In the existing method wind flex platforms are used in which the modulation and coding techniques are implemented. The wind flex platform is limited to the indoor applications and not meant to support the multi standard operation. In the proposed method SDR platform which can support multi standard operation is used in which modulation and coding techniques can be implemented. The work concentrates on the implementation of OFDM transmitter in SDR platform.

Tamil speech enhancement using non-linear spectral subtraction

Abstract: Speech enhancement is a technique used to reduce the background noise present in the speech signal. It simply means the improvement in intelligibility and quality of degraded speech. The noises present in the speech signal are additive noise, echo, reverbration and speaker interference. The aim of the proposed method is to reduce the background noise present in the speech signal by using spectral subtraction techniques. The magnitude of the spectrum of estimated noise is subtracted from the spectrum of noisy speech signal. Five clean speeches are taken as sample speech. Sample noise such as pink noise, white noise and volvo noise are taken from database (TIMIT & NOIZEUS corpus). By using Non-linear spectral subtraction and Multiband spectral subtraction techniques, enhanced speech is obtained. Performance of the above two methods are compared based on the two parameters namely Signal to Noise Ratio and Log Spectral Distance.