Child labour in India

This thesis entitled “Child labour in india”Children are "supremely important assets" of the nation, India proudly asserts in the National Policy for Children (1974) gracefully acknowledging that they are future citizens on whose shoulders the destiny of our nation rests.Childhood is a time of discovery as the world and all it contains are new to children. It is a time of excitement and anticipation. lt is a time of dreams and fantasies. And it is a time of receiving love and appreciation. Paradoxically, a picture of contrast is a common experience in India as a vast majority of children who are starved of basic needs of nutrition, health and education are made to work at an early age in exploitative conditions. The specter of child labour is a glaring anomaly in a country graciously adorning human right. In an exposition of the problem involving human rights abuse, Chapters from Two to Five of this study have shot into focus the human rights jurisprudence with special reference to the rights of children. Children have a particular identity as children and they also have a universal identity as human beings.The concern for mankind expressed unequivocally and transcending the globe will be real and moving and not mere rhetoric and ritual if and only when it begins with children, as, to quote the words of Nehru, the human being counts much more as a child than as a grown up.The first three of these rights namely right to health, right to nutritive food and right to education are dealt with in Chapter Four. Finally, the positive effects of education have been sketched in that chapter to impress upon its significance in the development of human capitals.legitimization. The theme of legitimacy was rationalised on the ground of poverty as a strategy for achieving eradication of child labour ultimately by enforcing minimum wages, shorter working hours, leave compensation, non-formal education etc., as the employer would soon discover that child labour is not cheap and would be obliged to substitute adult labour. However, humanising the work life is only a promise to the detriment of children as the Act of 1986 enacted as a part of the new strategy is nearingcompletion of a decade of existence but nowhere near the fulfilment of the mission.As similar urge is more necessary and overdue, it has been suggested that a special body be established with all powers for cognisance of human rights abuse of children.It is proposed to conclude this study with a brief summary of the inferences drawn from the foregoing chapters along with a few suggestions emerging out of those inferences

Statistical Machine Learning Techniques for the Prediction of Learning Disabilities in School-Age Children

Learning Disability (LD) is a general term that describes specific kinds of learning problems. It is a neurological condition that affects a child's brain and impairs his ability to carry out one or many specific tasks. The learning disabled children are neither slow nor mentally retarded. This disorder can make it problematic for a child to learn as quickly or in the same way as some child who isn't affected by a learning disability. An affected child can have normal or above average intelligence. They may have difficulty paying attention, with reading or letter recognition, or with mathematics. It does not mean that children who have learning disabilities are less intelligent. In fact, many children who have learning disabilities are more intelligent than an average child. Learning disabilities vary from child to child. One child with LD may not have the same kind of learning problems as another child with LD. There is no cure for learning disabilities and they are life-long. However, children with LD can be high achievers and can be taught ways to get around the learning disability. In this research work, data mining using machine learning techniques are used to analyze the symptoms of LD, establish interrelationships between them and evaluate the relative importance of these symptoms. To increase the diagnostic accuracy of learning disability prediction, a knowledge based tool based on statistical machine learning or data mining techniques, with high accuracy,according to the knowledge obtained from the clinical information, is proposed. The basic idea of the developed knowledge based tool is to increase the accuracy of the learning disability assessment and reduce the time used for the same. Different statistical machine learning techniques in data mining are used in the study. Identifying the important parameters of LD prediction using the data mining techniques, identifying the hidden relationship between the symptoms of LD and estimating the relative significance of each symptoms of LD are also the parts of the objectives of this research work. The developed tool has many advantages compared to the traditional methods of using check lists in determination of learning disabilities. For improving the performance of various classifiers, we developed some preprocessing methods for the LD prediction system. A new system based on fuzzy and rough set models are also developed for LD prediction. Here also the importance of pre-processing is studied. A Graphical User Interface (GUI) is designed for developing an integrated knowledge based tool for prediction of LD as well as its degree. The designed tool stores the details of the children in the student database and retrieves their LD report as and when required. The present study undoubtedly proves the effectiveness of the tool developed based on various machine learning techniques. It also identifies the important parameters of LD and accurately predicts the learning disability in school age children. This thesis makes several major contributions in technical, general and social areas. The results are found very beneficial to the parents, teachers and the institutions. They are able to diagnose the child’s problem at an early stage and can go for the proper treatments/counseling at the correct time so as to avoid the academic and social losses.