Unconstrained Handwritten Malayalam Character Recognition using Wavelet Transform and Support vector Machine Classifier

This paper presents the application of wavelet processing in the domain of handwritten character recognition. To attain high recognition rate, robust feature extractors and powerful classifiers that are invariant to degree of variability of human writing are needed. The proposed scheme consists of two stages: a feature extraction stage, which is based on Haar wavelet transform and a classification stage that uses support vector machine classifier. Experimental results show that the proposed method is effective

Using Neural Network Classifier Support Vector Machine Regression for the prediction of Melting Point of Drug – like compounds

In our study we use a kernel based classification technique, Support Vector Machine Regression for predicting the Melting Point of Drug – like compounds in terms of Topological Descriptors, Topological Charge Indices, Connectivity Indices and 2D Auto Correlations. The Machine Learning model was designed, trained and tested using a dataset of 100 compounds and it was found that an SVMReg model with RBF Kernel could predict the Melting Point with a mean absolute error 15.5854 and Root Mean Squared Error 19.7576

Mosquito larvae borne viruses from the central travancore region of kerala: isolation and characterization

The present study was initiated when several massive outbreaks of Chikungunya, Dengue and Japanese Encephalitis were frequently reported across the State of Kerala. Multiple symptoms persisted among the affected individuals and the public health officials were in search of aetiological agents responsible for the out breaks and, other than clinical samples no resources were available. In this context, a study was undertaken to focus on mosquito larvae to investigate the viruses borne by them which remain silently prevalent in the environment. The study was not a group specific investigation limited to either arbovirus or enterovirus, but had a broad spectrum approach. The study encompassed the viral pathogens that could be isolated, their impact when passaged through cell lines, growth kinetics, titer of the working stocks in specific cell line, the structure by means of transmission electron microscopy(TEM), the one step growth and molecular characterization using molecular tools.