Problems And Prospects Of Marketing Indian Cardamom At Home And Abroad

The main objective of the study has been to analyse the marketing problems of Indian cardamom at home and abroad and examine possible courses of action which would lead to increased consumption of cardamom, both within India and abroad. This has been done in the context of the anticipated increases in the Indian and world supply of cardamom. Field studies were undertaken to understand the cost of production of cardamom and cost of export. This study was also directed at examining how far price fluctuations in cardamom can be controlled in the Indian context, so as to have a reasonable and stable income for primary producers which will ensure adequate encouragement for higher production and better export earnings.

Attribute reduction and missing value imputing with ANN: prediction of learning disabilities

Learning disability (LD) is a neurological condition that affects a child’s brain and impairs his ability to carry out one or many specific tasks. LD affects about 10% of children enrolled in schools. There is no cure for learning disabilities and they are lifelong. The problems of children with specific learning disabilities have been a cause of concern to parents and teachers for some time. Just as there are many different types of LDs, there are a variety of tests that may be done to pinpoint the problem The information gained from an evaluation is crucial for finding out how the parents and the school authorities can provide the best possible learning environment for child. This paper proposes a new approach in artificial neural network (ANN) for identifying LD in children at early stages so as to solve the problems faced by them and to get the benefits to the students, their parents and school authorities. In this study, we propose a closest fit algorithm data preprocessing with ANN classification to handle missing attribute values. This algorithm imputes the missing values in the preprocessing stage. Ignoring of missing attribute values is a common trend in all classifying algorithms. But, in this paper, we use an algorithm in a systematic approach for classification, which gives a satisfactory result in the prediction of LD. It acts as a tool for predicting the LD accurately, and good information of the child is made available to the concerned