OPTIMAL UTILIZATION OF SERVICE FACILITY FOR A k-OUT-OF-n SYSTEM WITH REPAIR BY EXTENDING SERVICE TO EXTERNAL CUSTOMERS IN A RETRIAL QUEUE

In this paper, we study a k-out-of-n system with single server who provides service to external customers also. The system consists of two parts:(i) a main queue consisting of customers (failed components of the k-out-of-n system) and (ii) a pool (of finite capacity M) of external customers together with an orbit for external customers who find the pool full. An external customer who finds the pool full on arrival, joins the orbit with probability and with probability 1− leaves the system forever. An orbital customer, who finds the pool full, at an epoch of repeated attempt, returns to orbit with probability (< 1) and with probability 1 − leaves the system forever. We compute the steady state system size probability. Several performance measures are computed, numerical illustrations are provided.

Application of Imaging to Study the Evolution and Dynamics of Laser Produced Plasma from Solid and Thin Film Li Targets

The present thesis report the results obtained from the studies carried out on the laser blow off plasma (LBO) from LiF-C (Lithium Fluoride with Carbon) thin film target, which is of particular importance in Tokamak plasma diagnostics. Keeping in view of its significance, plasma generated by the irradiation of thin film target by nanosecond laser pulses from an Nd:YAG laser over the thin film target has been characterized by fast photography using intensified CCD. In comparison to other diagnostic techniques, imaging studies provide better understanding of plasma geometry (size, shape, divergence etc) and structural formations inside the plume during different stages of expansion.

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.

Studies on ecophysiology of pfnafus indicus h. milne edwards in the grow-out system

In the present study, the main emphasis was to find out it seasonal and ecosystem specific variations of calcium magnesium, phosphorus, copper and zinc in the water and the sediment has any role to play in altering the concentration of these elements in different tissues of intermoult p.indicus as evidenced by the seasonal studies in the grow out and the marine ecosystems

Bioremediation In Prawn Grow Out Systems

Winter School on 'RECENT ADVANCES IN DIAGNOSIS AND MANAGEMENT OF DISEASES IN MARICULTURE' 7-27 November, 2002 Course Manual,CMFRI

Influence of Frequent Flyer Programme and Airline Service Quality on Re-buy Intentions of Airline Frequent Passengers

The growth potential of service sector, especially the aviation sector in the Indian economy is splendid. Therefore, it is crucial for the airline service providers to realize their customers, design offers and deliver the desired value to their customers. This study reveals the effect of airline passenger satisfactions particularly on re-buy intentions derived from the attributes-level performance dimensions of both service aspects and loyalty programme of an airline. The mediation effect of satisfaction and other selected antecedents on the re-buy intention of a passenger is hypothesized in this study. Critical areas affecting buying intentions such as core service quality and loyalty attribute-level performances, effect of frequent flyer programme and service quality satisfaction, passenger trust on airline, brand image and moderating effects of perceived value, frequent programme status and travel frequency of airline passengers are linked in a structural model to assess the strength of each facet in affecting re-buy intentions. Implications to the airlines were made based on the finding that re-buy intentions cannot be attributed solely to the impacts of frequent flyer programme, rather affected through the mediation effect of airline service quality satisfaction, which is very much valid for the higher FFP status category of frequent travelers. The effects of moderation caused by perceived value, FFP status and flying experience were also found to be significant in making re-buy intentions.