Economics Of Korai Mat Weaving In Thanjavur District

The main purpose of the study is to examine the economic aspects of the korai mat weaving industry.

L-Glutaminase production by an immobilized marine Pseudomonas sp. BTMS -51

The present study is about the Pseudomonas sp. BTMS-51 isolated from the marine sediments of Cochin Coast. In the present study, it is concluded that marine bacteria are ideal candidates for immobilization using either Ca-alginate entrapment or physical adsorption on to synthetic inert supports and the process of immobilization does not negatively influence them. Thus, Ca-alginate entrapment of the bacteria was found to be well suited for reuse of the biomass and extended operational stability during continuous operation. Adherence of the bacterium to inertsupports was observed to be strong and it imparted minimal stress on the immobilized bacterium and allowed detachment and relocation on the supports which enabled the formation of a dynamic equilibrium maintaining a stable cell loading. This is particularly desirable in the industry for extended operational stability and maintenance of consistently higher outputs. Marine Pseudomonas sp. BTMS-51 is ideal for industrial production of extra cellular L-glutaminase and immobilization on to synthetic inert support such as polyurethane foam could be an efficient technique, employing packed bed reactor for continuous production of the enzyme. Temperature and glutamine concentration had significant effects on enzyme production by cells immobilized on polyurethane foam (PUF).

Optimisation of the Mechanical Properties of HDPE/PP Blends and Their Recyclable Composites

This study was undertaken in order to upgrade blends of HDPE and PP, two of the most widely used standard plastics so as to widen their application spectrum. Dicumyl peroxide was used as the modifier for the upgradation. Optimum concentration of dicumyl peroxide required for modification was detennined by measurement of mechanical, rheological, thermal and morphological properties. Selected blends were used to prepare recyclable composites with nylon clothes by compression moulding. The composites were characterized by measurement of mechanical and thermal properties. The composites were recycled and the mechanical propertics of the recycled material were determined.

Development of novel surface coatings based on acrylic copolymers

The present study describes the preparation of Vinyl acetate-Butyl acrylate copolymer lattices of varying compositions and solid contents by semicontinuous emulsion polymerization method. This copolymer lattices were used as binder to develop a new surface coating formulation. The properties of this surface coating were improved by using nano TiO2 colloidal sol as a pigment. Antimicrobial activity of surface coatings was improved by the addition of carboxymethyl chitosan as biocide. Uniformly dispersed tyre crumb was used to give a mat finish to the coating. The mechanical properties adhesive properties, thermal properties etc. of the coatings are presented in thesis.

Performance Improvement of Fuzzy and Neuro Fuzzy Systems: Prediction of Learning Disabilities in School-age Children

Learning Disability (LD) is a classification including several disorders in which a child has difficulty in learning in a typical manner, usually caused by an unknown factor or factors. LD affects about 15% of children enrolled in schools. The prediction of learning disability is a complicated task since the identification of LD from diverse features or signs is a complicated problem. There is no cure for learning disabilities and they are life-long. The problems of children with specific learning disabilities have been a cause of concern to parents and teachers for some time. The aim of this paper is to develop a new algorithm for imputing missing values and to determine the significance of the missing value imputation method and dimensionality reduction method in the performance of fuzzy and neuro fuzzy classifiers with specific emphasis on prediction of learning disabilities in school age children. In the basic assessment method for prediction of LD, checklists are generally used and the data cases thus collected fully depends on the mood of children and may have also contain redundant as well as missing values. Therefore, in this study, we are proposing a new algorithm, viz. the correlation based new algorithm for imputing the missing values and Principal Component Analysis (PCA) for reducing the irrelevant attributes. After the study, it is found that, the preprocessing methods applied by us improves the quality of data and thereby increases the accuracy of the classifiers. The system is implemented in Math works Software Mat Lab 7.10. The results obtained from this study have illustrated that the developed missing value imputation method is very good contribution in prediction system and is capable of improving the performance of a classifier.