An Improvised Machine Learning Model Based on Mutual Information Feature Selection Approach for Microbes Classification.

The accurate classification of microbes is critical in today's context for monitoring the ecological balance of a habitat. Hence, in this research work, a novel method to automate the process of identifying microorganisms has been implemented. To extract the bodies of microorganisms accurately, a generalized segmentation mechanism which consists of a combination of convolution filter (Kirsch) and a variance-based pixel clustering algorithm (Otsu) is proposed.

Apert's Syndrome.

A case of Apert's syndrome in a one year old female child is described and literature reviewed. She was the first born of a young couple. She had congenital syndactyl of toes and fingers, acro-cephalic skull, flat facies, exophthalmos, hypertelorism and greasy skin.