High resolution optogalvanic spectrum of N2-rotational structure of (11, 7) band in the first positive system

High resolution optogalvanic spectrum of the (11, 7) band in the first positive system of nitrogen molecule has been recorded from 17179 to 17376 cm- 1. Assignment of 432 rotational lines belonging to the 27 branches of this band has been carried out.

Lease Financing in India",

Several related articles have appeared ix: journals and dailies, covering mainly the advantages and disadvantages of leasing. Some have focussed on the leasing scenario in India while others projected the prospects of leasing. However, there are some research articles worth mentioning. An exploratory study done by R. Narayana Swamy expresses -the views of leasing companies, on lease accounting issues in India. It deals only with several aspects of accounting regulation, accounting standard setting, accounting proposals and implications and economic consequences of the proposals for leasing companies and for lessees and users of financial statamnts. Another article dealing with the growth and performance of leasing industry by Rita Vasanls gives just a peripheral view of the performance of leasing companies. Hence an indepth study is attempted to analyse the leasing industry in India, in all its manifestations

Significance Of Classification Techniques In Prediction Of Learning Disabilities

The aim of this study is to show the importance of two classification techniques, viz. decision tree and clustering, in prediction of learning disabilities (LD) of school-age children. LDs affect about 10 percent of all children enrolled in schools. The problems of children with specific learning disabilities have been a cause of concern to parents and teachers for some time. Decision trees and clustering are powerful and popular tools used for classification and prediction in Data mining. Different rules extracted from the decision tree are used for prediction of learning disabilities. Clustering is the assignment of a set of observations into subsets, called clusters, which are useful in finding the different signs and symptoms (attributes) present in the LD affected child. In this paper, J48 algorithm is used for constructing the decision tree and K-means algorithm is used for creating the clusters. By applying these classification techniques, LD in any child can be identified