Phase Transitions of Trace Metals in the Aquatic Environment of Kuttanad, Kerala

This thesis is a modest attempt in assessing the trace metal levels and their behavior in the aquatic environment of Kuttanad, an aquatic system that is severely affected by man’s intervention on natural processes, by study seriously evaluating the levels of trace metals in dissolved and particulate phases and also in the different chemical fractions of the sediments. Understanding of the distributions, variations and transfer processes of trace metals in different environmental phases in the backwaters of Kuttanad is vital for the assessment of the water pollution problems and study the ecology of the area which contributes 20% of the rice production in the State of Kerala. Kuttand is a low-lying, shallow bay formed as a result of geological uplift. The major economic activity is agriculture involving 40% of the population. About 1.5% of the people are engaged in aquaculture. The trace metal distribution in the Kuttand backwaters is considerably influenced by the tropical features of the location and by human activities including agricultural activities and construction of salinity barrier. In this study an attempt is made to differentiate the metals in the sediment into exchangeable, reducible and resistant fractions in the sediments.

Design and Development of data mining models for the predictions of manpower placement in the technical Domain

Data mining is one of the hottest research areas nowadays as it has got wide variety of applications in common man’s life to make the world a better place to live. It is all about finding interesting hidden patterns in a huge history data base. As an example, from a sales data base, one can find an interesting pattern like “people who buy magazines tend to buy news papers also” using data mining. Now in the sales point of view the advantage is that one can place these things together in the shop to increase sales. In this research work, data mining is effectively applied to a domain called placement chance prediction, since taking wise career decision is so crucial for anybody for sure. In India technical manpower analysis is carried out by an organization named National Technical Manpower Information System (NTMIS), established in 1983-84 by India's Ministry of Education & Culture. The NTMIS comprises of a lead centre in the IAMR, New Delhi, and 21 nodal centres located at different parts of the country. The Kerala State Nodal Centre is located at Cochin University of Science and Technology. In Nodal Centre, they collect placement information by sending postal questionnaire to passed out students on a regular basis. From this raw data available in the nodal centre, a history data base was prepared. Each record in this data base includes entrance rank ranges, reservation, Sector, Sex, and a particular engineering. From each such combination of attributes from the history data base of student records, corresponding placement chances is computed and stored in the history data base. From this data, various popular data mining models are built and tested. These models can be used to predict the most suitable branch for a particular new student with one of the above combination of criteria. Also a detailed performance comparison of the various data mining models is done.This research work proposes to use a combination of data mining models namely a hybrid stacking ensemble for better predictions. A strategy to predict the overall absorption rate for various branches as well as the time it takes for all the students of a particular branch to get placed etc are also proposed. Finally, this research work puts forward a new data mining algorithm namely C 4.5 * stat for numeric data sets which has been proved to have competent accuracy over standard benchmarking data sets called UCI data sets. It also proposes an optimization strategy called parameter tuning to improve the standard C 4.5 algorithm. As a summary this research work passes through all four dimensions for a typical data mining research work, namely application to a domain, development of classifier models, optimization and ensemble methods.

”Public Health Protection through Air Quality Controls”

Health is an important aspect of everybody’s life. Today, there is an increasing recognition and commitment to the pursuit of health both within government and beyond. Any attempt on the part of the " State to protect and promote people’s health, in turn, must be accompanied by effective controls on air quality, as air constitutes ‘ one of the important elements of man’s life and the consequences of air pollution covers a very wide spectrum ranging from material ---damage to personal discomfort and illness. The broad social and economic objectives adumbrated in the Directive Principles of State Policy including the commitment to improve public health underlying in Article 47 and the obligation to preserve and protect-the natural environment cast under Article 48A of the Constitution are being used as versatile weapons by the State to regulate the public health scenario. Preservation and maintenance of air quality is a significant area within the sphere of public health, where the regulatory arm of the law is not adequately touched and in this arena urgent State intervention through legislative and administrative action is called for in the well-being of the society. Judiciary also plays a pivotal role in this arena in the larger interest of the society and for the benefit of the present and future generations. The research study is an attempt to analyze how far the existing legal system, for maintaining air quality and in controlling air pollution, is effective in protecting public health. The study also analyzes the limitations of the control mechanisms. The study focuses on industrial air pollution, indoor and personal air pollution, vehicular pollution and noise pollution which are today appearing as the major public health hazards affecting the air quality. However, this is not to overlook the importance of controls required under other areas of public health.