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.

Process Improvement of Coir Pith Degradation Involving White Rot Fungi By Substitution of Urea With Nitrogen Fixing Bacteria and Application of Biodegraded Coir Pith as Plant Growth Medium

In this study, a novel improved technology could be developed to convert the recalcitrant coir pith into environmental friendly organic manure. The standard method of composting involves the substitution of urea with nitrogen fixing bacteria viz. Azotobacter vinelandii and Azospirillum brasilense leading to the development of an improved method of coir pith. The combined action of the microorganisms could enhance the biodegradation of coir pith. In the present study, Pleurotus sajor caju, an edible mushroom which has the ability to degrade coir pith, and the addition of nitrogen fixing bacteria like Azotobacter vinelandii and Azospirillum brasilense could accelerate the action of the fungi on coir pith. The use of these microorganisms brings about definite changes in the NPK, Ammonia, Organic Carbon and Lignin contents in coir pith. This study will encourage the use of biodegraded coir pith as organic manure for agri/horti purpose to get better yields and can serve as a better technology to solve the problem of accumulated coir pith in coir based industries