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.

Studies on The Ecophysiology Of Some Heterotrophic and Indicator Bacteria In The Marine Environments of Kerala

The thesis entitled "Studies on the eco-physiology of heterotrophic and indicator bacteria in the marine environments of Kerala" embodies the results of an investigation carried out by the candidate at the Central Marine Fisheries Research Institute, Cochin. It is presentedd under 4 chapters in two parts (Parts A & B) and includes 6 sections. The material for the study was collected in the Cochin backwater during April 1972 to February. 1973, March 1974 to February 1975, July 1975 to June 1976 and in the ishore area during January to October, 1978 and an account of the heterotropic and indicator bacteria are given with intensity charts and tables. Samples from all the stations contained significant quantities of heterotrophs (Part A, Section I) and faecal pollution indicators (Section II). Maximum number of heterotrophic bacteria was observed during the postmonsoon period. The total counts betwen one station and the other did not vary as much as the counts between months did. The distribution was characterised by overdispersion. During 1972-73 in all the stations except the fourth the minimum heterotrophs (Total counts) were recorded during the monsoon period. Minimum counts were observed during the premonsoon period, with an increasing trend from the premonsoon to postmonsoon seasons. Maximum counts were recorded during monsoon months during 1974-75. No significant difference was noted in the total plate count between stations, months and regions. Seasonal variations in sea water was meagre during 1975-76, whereas in sediments variations were prominent during monsoon in Station I - near the mouth of the sewage effluent of Cochin City and in postmonsoon at Station II in the Mattancherry Channel and Station III near barmouth

THE SOCIAL ENVIRONMENTS IN HINDI LITERATURE OF BHAKTI PERIOD

HINDI

Operational Flexibility: A Model for Effective Project Management

The aim of this study is to investigate the role of operational flexibility for effective project management in the construction industry. The specific objectives are to: a) Identify the determinants of operational flexibility potential in construction project management b) Investigate the contribution of each of the determinants to operational flexibility potential in the construction industry c) Investigate on the moderating factors of operational flexibility potential in a construction project environment d) Investigate whether moderated operational flexibility potential mediates the path between predictors and effective construction project management e) Develop and test a conceptual model of achieving operational flexibility for effective project management The purpose of this study is to findout ways to utilize flexibility inorder to manage uncertain project environment and ultimately achieve effective project management. In what configuration these operational flexibility determinants are demanded by construction project environment in order to achieve project success. This research was conducted in three phases, namely: (i) exploratory phase (ii) questionnaire development phase; and (iii) data collection and analysis phase. The study needs firm level analysis and therefore real estate developers who are members of CREDAI, Kerala Chapter were considered. This study provides a framework on the functioning of operational flexibility, offering guidance to researchers and practitioners for discovering means to gain operational flexibility in construction firms. The findings provide an empirical understanding on kinds of resources and capabilities a construction firm must accumulate to respond flexibly to the changing project environment offering practitioners insights into practices that build firms operational flexibility potential. Firms are dealing with complex, continuous changing and uncertain environments due trends of globalization, technical changes and innovations and changes in the customers’ needs and expectations. To cope with the increasingly uncertain and quickly changing environment firms strive for flexibility. To achieve the level of flexibility that adds value to the customers, firms should look to flexibility from a day to day operational perspective. Each dimension of operational flexibility is derived from competences and capabilities. In this thesis only the influence on customer satisfaction and learning exploitation of flexibility dimensions which directly add value in the customers eyes are studied to answer the followingresearch questions: “What is the impact of operational flexibility on customer satisfaction?.” What are the predictors of operational flexibility in construction industry? .These questions can only be answered after answering the questions like “Why do firms need operational flexibility?” and “how can firms achieve operational flexibility?” in the context of the construction industry. The need for construction firms to be flexible, via the effective utilization of organizational resources and capabilities for improved responsiveness, is important because of the increasing rate of changes in the business environment within which they operate. Achieving operational flexibility is also important because it has a significant correlation with a project effectiveness and hence a firm’s turnover. It is essential for academics and practitioners to recognize that the attainment of operational flexibility involves different types namely: (i) Modification (ii) new product development and (iii) demand management requires different configurations of predictors (i.e., resources, capabilities and strategies). Construction firms should consider these relationships and implement appropriate management practices for developing and configuring the right kind of resources, capabilities and strategies towards achieving different operational flexibility types.