Petrography, Geochemistry and Diagenesis of Coral Deposits of Kavaratti and Minicoy Islands, Lakshadweep, India

In the present thesis the petrographic, geochemical and digenetic variability of the sediments in the islands of Kavaratti and Minicoy has been investigated .The beach profile studies show that in the Kavaratti lagoon beach, the slope is steeper in the southern and south central part than in the northern end’s marginal deposition is taking place in the northern end of the Kavaratti island, whereas a marginal erosion is observed at the southern end. In Minicoy the slope of the lagoon beach is gentle in the south and is slightly steeper at the northern part of the beach. The southern and northern beach sections show a marginal deposition. Based on the mineralogical and geochemical studies it is concluded that the main digenetic changes observed is the transformation of aragonite to LMC.The transformation takes place mainly in the vadose zone and is caused by the abundance of fresh water infiltration.

Consequence modelling,vulnerability assessment and fuzzy fault tree analysis of hazardous storages in an industrial area

The hazards associated with major accident hazard (MAH) industries are fire, explosion and toxic gas releases. Of these, toxic gas release is the worst as it has the potential to cause extensive fatalities. Qualitative and quantitative hazard analyses are essential for the identitication and quantification of the hazards associated with chemical industries. This research work presents the results of a consequence analysis carried out to assess the damage potential of the hazardous material storages in an industrial area of central Kerala, India. A survey carried out in the major accident hazard (MAH) units in the industrial belt revealed that the major hazardous chemicals stored by the various industrial units are ammonia, chlorine, benzene, naphtha, cyclohexane, cyclohexanone and LPG. The damage potential of the above chemicals is assessed using consequence modelling. Modelling of pool fires for naphtha, cyclohexane, cyclohexanone, benzene and ammonia are carried out using TNO model. Vapor cloud explosion (VCE) modelling of LPG, cyclohexane and benzene are carried out using TNT equivalent model. Boiling liquid expanding vapor explosion (BLEVE) modelling of LPG is also carried out. Dispersion modelling of toxic chemicals like chlorine, ammonia and benzene is carried out using the ALOHA air quality model. Threat zones for different hazardous storages are estimated based on the consequence modelling. The distance covered by the threat zone was found to be maximum for chlorine release from a chlor-alkali industry located in the area. The results of consequence modelling are useful for the estimation of individual risk and societal risk in the above industrial area.Vulnerability assessment is carried out using probit functions for toxic, thermal and pressure loads. Individual and societal risks are also estimated at different locations. Mapping of threat zones due to different incident outcome cases from different MAH industries is done with the help of Are GIS.Fault Tree Analysis (FTA) is an established technique for hazard evaluation. This technique has the advantage of being both qualitative and quantitative, if the probabilities and frequencies of the basic events are known. However it is often difficult to estimate precisely the failure probability of the components due to insufficient data or vague characteristics of the basic event. It has been reported that availability of the failure probability data pertaining to local conditions is surprisingly limited in India. This thesis outlines the generation of failure probability values of the basic events that lead to the release of chlorine from the storage and filling facility of a major chlor-alkali industry located in the area using expert elicitation and proven fuzzy logic. Sensitivity analysis has been done to evaluate the percentage contribution of each basic event that could lead to chlorine release. Two dimensional fuzzy fault tree analysis (TDFFTA) has been proposed for balancing the hesitation factor invo1ved in expert elicitation .

E-marketing motivators,inhibitors and critical success factors: A study of small and medium tourism enterprises (SMTES) in Mauritius and Andaman islands, India

Information and Communication Technologies (ICTs) have a dramatic impact on the tourism industry because they force this sector as a whole to rethink the way in which it organises its business . In the light of such rethinking within the tourism industry, this study has focussed on the Small and Medium Tourism Enterprises (SMTEs) in two island destinations, namely Mauritius and Andaman Islands, India.Suggestions. The findings conceming SMTEs in Mauritius and Andaman Islands have been compared to make some destination-specific inferences. The relevance of the findings has been discussed with reference to the SMTEs in the two destinations as well as the possible acceptability in other comparable settings. Suggestions have been made for further research in SMTEs’ use of the Internet for marketing function.

Studies on the seaweeds of andaman and nicobar group of islands

The importance of marine algae, often referred to as seaweeds, has been felt over a long time and is appreciated more and more in modern times. The economic value of marine algae is understood both indirectly and directly. The indirect benefit is due to the role of marine phytoplankton as well as the benthic macrophyte biomass along the shore and in the continental shelf, in primary production of the sea. Direct benefit includes the use of marine algae as food, feed, fertilizer and as source of various products of commercial importance such as agar and alginic acid. Hence to understand the potential resources of seaweeds, their distribution, density, standing crop and interrelated environmental parameters, a detailed study (survey and ecological work) was carried out for a period of 20 months from August 1988 to March 1990 in South Andaman, North Andaman, Middle Andaman, Havelock, Neil, Car Nicobar, Terassa, Chowra and Bumpoka islands. However in South Andaman, data were collected from five fixed stations fortnightly during this period for the purpose of modelling and system analysis.

Studies on seed pathology and seedling diseases of some important indigenous tree species of kerala

In forestry, availability of healthy seeds is an important factor in raising planting stock. Initial seed health and storage conditions are the major factors governing the germinability of seeds. Like seeds of agricultural and horticultural crops, forest tree seeds are also liable to be affected by micro-organisms during storage, which affects the germination, and reduces the viability. Further introduction of seed-borne diseases into newly sown crops/areas on account of using unhealthy seeds is also not ruled out. Availability of healthy stock of seedlings is intrinsic for raising plantations and to meet this requirement elimination of nursery diseases by appropriate chemicals is of prime imortance. As exotic tree species may become susceptible to various native pathogens, it is generally considered better to select indigenous tree species for large scale plantations as they are well adapted to local environment. However, before taking up large scale afforestation progranme involving any indigenous tree species, it is essential to have knowledge about seed disorders and seedling diseases and their management. with a View to select appropriate tree species with fewer seed disorders and seedling disease problems for use in further plantation programme, four indigenous tree species such as Albizia odoratissima (L.f) Benth., Lagerstroemia microcazpa Wt., Pterocazpus marsupiwn Roxb. and Xylia xylocarpa (Roxb.) Taub. were evaluated to meet the above parameters

Customary Laws of Lakshadweep Islands

The customary laws of Union Territory of Lakshadweep islands are a challenge for judicial institution as well as administrative machinery. With the peculiarities of socio-legal institutions, Lakshadweep system stands apart from the mainstream of legal systems in India. How far do the charismatic modernisation trends flowing into the Lakshadweep society affect the people already protected by the uncodified laws of the past? Many are the issues at this stage. This study analyses them. It examines the growth, evolution and development of the legal system in the islands vis-a-vis the administrative mechanism imposed by the mainland ethos and culture.

A Novel Decision Tree Algorithm for Numeric Datasets - C 4.5*Stat

Decision trees are very powerful tools for classification in data mining tasks that involves different types of attributes. When coming to handling numeric data sets, usually they are converted first to categorical types and then classified using information gain concepts. Information gain is a very popular and useful concept which tells you, whether any benefit occurs after splitting with a given attribute as far as information content is concerned. But this process is computationally intensive for large data sets. Also popular decision tree algorithms like ID3 cannot handle numeric data sets. This paper proposes statistical variance as an alternative to information gain as well as statistical mean to split attributes in completely numerical data sets. The new algorithm has been proved to be competent with respect to its information gain counterpart C4.5 and competent with many existing decision tree algorithms against the standard UCI benchmarking datasets using the ANOVA test in statistics. The specific advantages of this proposed new algorithm are that it avoids the computational overhead of information gain computation for large data sets with many attributes, as well as it avoids the conversion to categorical data from huge numeric data sets which also is a time consuming task. So as a summary, huge numeric datasets can be directly submitted to this algorithm without any attribute mappings or information gain computations. It also blends the two closely related fields statistics and data mining

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.