Studies On Some Boring And Fouling Crustaceans

The present work comprises studies on the salinity tolerance and respiratory metabolism of a mood-boring sphaeromid, Sphaeroma annandalei, Stabbing and two free living,foulers of the family Cirolanidae, Cirolana fluviatilis Stabbing and C. uilleyi Stabbing. Except for the systematic accounts and general observations by Pillai (1961) and the preliminary studies on the salinity tolerance and respiration of C. fluviatilis by Nagabhushanam and Gopalakrishnamurthy (1965, 1965a) very little is known about these isopods From Indian waters. Studies by John (1968) on the habits, structure, and development of Sphaeroma terebrans and by Cheriyan (1973) on the eoéphysiology of the same are the recent major contributions on this interesting group of animals. 5. annandalei is closely related to S. terebrans and has been reported to occur on timber along with the latter (Pillai, 1951). s. gggandalei is a serious pest attacking wood along the Kerala coast, but detailed works on this species have not been undertaken so Far

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.