Environmental impact of sand mining

This thesis Entitled Environmental impact of Sand Mining :A case Study in the river catchments of vembanad lake southwest india.The entire study is addressed in nine chapters. Chapter l deals with the general introduction about rivers, problems of river sand mining, objectives, location of the study area and scope of the study. A detailed review on river classification, classic concepts in riverine studies, geological work of rivers and channel processes, importance of river ecosystems and its need for management are dealt in Chapter 2. Chapter 3 gives a comprehensive account of the study area - its location, administrative divisions, physiography, soil, geology, land use and living and non-living resources. The various methods adopted in the study are dealt in Chapter 4. Chapter 5 contains river characteristics like drainage, environmental and geologic setting, channel characteristics, river discharge and water quality of the study area. Chapter 6 gives an account of river sand mining (instream and floodplain mining) from the study area. The various environmental problems of river sand mining on the land adjoining the river banks, river channel, water, biotic and social / human environments of the area and data interpretation are presented in Chapter 7. Chapter 8 deals with the Environmental Impact Assessment (EIA) and Environmental Management Plan (EMP) of sand mining from the river catchments of Vembanad lake.

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.

Sustainability of Participatory Projects: Study of Productive Sector under Peoples’ Planning in Chempu Village Panchayat of Kottayam District

The study has wider policy implications as it identifies the possible variables which influence the sustainability of participatory productive sector projects. The method which is developed to study the sustainability of projects under People’s Planning in Chempu Panchayat could be used for studying the same in other panchayats also. Unlike the case of the standard features of sustainability identified, the independent variables vary according to the nature of the project. Hence, this needs to be modified accordingly while applying the method in a dissimilar domain. Selection of a single panchayat for the present study is relevant on the basis of a common package of inputs for decentralised planning which is forwarded by the State Planning Board respectively for the three-tier panchayat system in Kerala. The dynamic filed realities could be brought out in view of a comprehensive planning approach through an in depth study of specific cases.The assessment of the nature and pattern of productive sector projects in the selected Village Panchayat puts the projects under close scrutiny. The analysis has depended largely on secondary sources of information, especially from panchayat level plan documents, and also on the primary information obtained using direct observation and on-site inspection of project sites. An analysis of the nature and pattem of productive sector projects is important as it gives all necessary information regarding follow-up, monitoring/evaluation and even termination of a particular project. It has also revealed the tendencies of including infrastructure and service sector projects under ‘productive’ category, especially for maintaining the stipulated ratio (40:30:30) of grant-in-aid distribution. The study regarding the allocation and expenditure pattern of plan funds is vital in policy level as it reveals the under-noticed allocation and expenditure pattern of plan funds other than grant-in-aid. One major limitation of the study has been the limited availability of secondary data, especially regarding project-wise expenditure and monitoring/evaluation reports of various project committees.

Legal Protection for Consumer of Pharmaceutical Products

The overall focus of the thesis involves the legal protection for consumers of pharmaceutical products.The work on “Legal Protection for Consumers of Pharmaceutical Products” is undertaken to study the legal framework that is existing for this purpose and the functioning of regulating mechanism that is envisaged under it. The purpose of the study is to analyse how far these measures are effective in adequately protecting various aspects of consumer interest. Methodology adopted for the study is analytical.The present study revealed that the theory of freedom of contract is only an ideal relevant when the parties are assumed to be on equal footing.In a more complicated social and economic society, it ceased to have any relevance. Many countries in the world enacted legislations to protect the consumers of pharmaceutical products.The meaning of ‘consumers of drugs’ provided in the law is inclusive and not exhaustive one. The definition of ‘drug’ as interpreted by the courts is comprehensive enough to take in it not only medicines but also substances. The meaning of the word substances has been widened by the interpretation of the courts so as to include all the things used in treatment.The definition of the word ‘consumer’ has been liberally interpreted by the courts so as to provide protective net to a large section of the public.The studies subsequent to this report also revealed that there is a shortage of essential drugs necessary to cure local diseases like tuberculosis and malaria where as drugs containing vitamins and other combinations which are more profitable for the manufacturers are produced and marketed in abundance.The study of the provisions in this regard revealed that the duty of the drug controlling authorities is confined to scrutinize the data of the clinical test already conducted by the sponsor of the drug.Study of the clinical trial procedure under the U.S. law revealed that there is a continuous supervision over clinical trials and controls are provided on the treatment use of an investigational productStudy of the clinical trial procedure under the U.S. law revealed that there is a continuous supervision over clinical trials and controls are provided on the treatment use of an investigational product.the study of the provisions of the Drugs and Cosmetics Act and the rules framed under it revealed that the law in this regard is comprehensive to protect the consumer provided it is sufficiently supported by adequately equipped enforcement machinery.

“Reconstruction of Gene Regulatory Network from Expression Profile of Plasma RNA Data of Colorectal Cancer Patients using Soft Computing Techniques”

Microarray data analysis is one of data mining tool which is used to extract meaningful information hidden in biological data. One of the major focuses on microarray data analysis is the reconstruction of gene regulatory network that may be used to provide a broader understanding on the functioning of complex cellular systems. Since cancer is a genetic disease arising from the abnormal gene function, the identification of cancerous genes and the regulatory pathways they control will provide a better platform for understanding the tumor formation and development. The major focus of this thesis is to understand the regulation of genes responsible for the development of cancer, particularly colorectal cancer by analyzing the microarray expression data. In this thesis, four computational algorithms namely fuzzy logic algorithm, modified genetic algorithm, dynamic neural fuzzy network and Takagi Sugeno Kang-type recurrent neural fuzzy network are used to extract cancer specific gene regulatory network from plasma RNA dataset of colorectal cancer patients. Plasma RNA is highly attractive for cancer analysis since it requires a collection of small amount of blood and it can be obtained at any time in repetitive fashion allowing the analysis of disease progression and treatment response.

Prediction of Key Symptoms of Learning Disabilities in School-Age Children Using Rough Sets

This paper highlights the prediction of learning disabilities (LD) in school-age children using rough set theory (RST) with an emphasis on application of data mining. In rough sets, data analysis start from a data table called an information system, which contains data about objects of interest, characterized in terms of attributes. These attributes consist of the properties of learning disabilities. By finding the relationship between these attributes, the redundant attributes can be eliminated and core attributes determined. Also, rule mining is performed in rough sets using the algorithm LEM1. The prediction of LD is accurately done by using Rosetta, the rough set tool kit for analysis of data. The result obtained from this study is compared with the output of a similar study conducted by us using Support Vector Machine (SVM) with Sequential Minimal Optimisation (SMO) algorithm. It is found that, using the concepts of reduct and global covering, we can easily predict the learning disabilities in children

Prediction of Learning Disabilities in School Age Children using SVM and Decision Tree

This paper highlights the prediction of Learning Disabilities (LD) in school-age children using two classification methods, Support Vector Machine (SVM) and Decision Tree (DT), with an emphasis on applications of data mining. About 10% of children enrolled in school have a learning disability. Learning disability prediction in school age children is a very complicated task because it tends to be identified in elementary school where there is no one sign to be identified. By using any of the two classification methods, SVM and DT, we can easily and accurately predict LD in any child. Also, we can determine the merits and demerits of these two classifiers and the best one can be selected for the use in the relevant field. In this study, Sequential Minimal Optimization (SMO) algorithm is used in performing SVM and J48 algorithm is used in constructing decision trees.