Leena, Mathew; Dr.Krishnan Nampoothiri, K(Cochin University of Science And Technology, November , 1996)
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Abstract:
NABARD has completed 14 years of operation.ln the light of
its experiences and achievements, the performance ev.ilu.ilion of
the National Bank need to be looked into.This could provide certain
criteria for its strength and weakness which may help in
consolidating the institution for better utilisation of its potentialities.
It is also noteworthy that no evaluative study on the National Bank
has been conducted in Kerala. The Major objective of this study is to evaluate the role of NABARD in catering to the long-term agricultural
requirements of Kerala for 1982 to 1992.This is done by analysing
the quantum and quality of NABARD's schematic
refinance. The qualitative indices like (1) the efficiency of loan
recovery, (2) the impact or financial viability of NABARD refinanced
schemes, (3) the credit gap, (4) the commitment-disbursement gap,
and (5) the imbalances in the NABARD refinance form the core of
the study.Hypotheses were formulated inorder to study and
analyse these qualitative indices. The study is presented in eight chapters
Description:
Department of applied economics, Cochin University of Science And Technology
Anvar,P; Meera Bai,M(Department of Applied Economics, Faculty of Social Sciences, 2003)
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Abstract:
The study makes an attempt to examine the inter regional variations in Kerala in economic development with respect to the important indicators of development over the period 1971 to 2001. The study takes districts as the unit of analysis because this is an attempt to find out the status of districts in Kerala.The study proved that there exists inter district disparities in economic development measured in terms of different indices used for analysis.. statistical estimation of variation proves that there is high degree of variation in industrial sector followed by social and economic infrastructure. The composite index of industrial development shows that the highest index is 1.395 which is five times greater than that of the lowest index 0.273. More or less the same pattern of differences are noticed in most of the indicators of the development. A ranking of the district on the basis of the overall development indicators shows that Malappuram is the least developed district in Kerala. In case of almost all indicators of development Malappuram is lagging behind all other districts.
Sreeja,V N; Dr.Sankaran, P G(Cochin University of Science and Technology, March , 2008)
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Abstract:
Multivariate lifetime data arise in various forms including recurrent event
data when individuals are followed to observe the sequence of occurrences of a
certain type of event; correlated lifetime when an individual is followed for the
occurrence of two or more types of events, or when distinct individuals have
dependent event times. In most studies there are covariates such as treatments, group
indicators, individual characteristics, or environmental conditions, whose
relationship to lifetime is of interest. This leads to a consideration of regression
models.The well known Cox proportional hazards model and its variations, using the
marginal hazard functions employed for the analysis of multivariate survival data in
literature are not sufficient to explain the complete dependence structure of pair of
lifetimes on the covariate vector. Motivated by this, in Chapter 2, we introduced a
bivariate proportional hazards model using vector hazard function of Johnson and
Kotz (1975), in which the covariates under study have different effect on two
components of the vector hazard function. The proposed model is useful in real life
situations to study the dependence structure of pair of lifetimes on the covariate
vector . The well known partial likelihood approach is used for the estimation of
parameter vectors. We then introduced a bivariate proportional hazards model for
gap times of recurrent events in Chapter 3. The model incorporates both marginal
and joint dependence of the distribution of gap times on the covariate vector . In
many fields of application, mean residual life function is considered superior
concept than the hazard function. Motivated by this, in Chapter 4, we considered a
new semi-parametric model, bivariate proportional mean residual life time model, to
assess the relationship between mean residual life and covariates for gap time of
recurrent events. The counting process approach is used for the inference procedures of the gap time of recurrent events. In many survival studies, the distribution of
lifetime may depend on the distribution of censoring time. In Chapter 5, we
introduced a proportional hazards model for duration times and developed inference
procedures under dependent (informative) censoring. In Chapter 6, we introduced a
bivariate proportional hazards model for competing risks data under right censoring.
The asymptotic properties of the estimators of the parameters of different models
developed in previous chapters, were studied. The proposed models were applied to
various real life situations.
Description:
Department of Statistics, Cochin University
of Science and Technology
Jasmin, E A; Dr. Jagathy Raj, V P(Cochin University of Science and Technology, December , 2008)
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Abstract:
One major component of power system operation is generation
scheduling. The objective of the work is to develop efficient control strategies
to the power scheduling problems through Reinforcement Learning approaches.
The three important active power scheduling problems are Unit Commitment,
Economic Dispatch and Automatic Generation Control. Numerical solution
methods proposed for solution of power scheduling are insufficient in handling
large and complex systems. Soft Computing methods like Simulated Annealing,
Evolutionary Programming etc., are efficient in handling complex cost
functions, but find limitation in handling stochastic data existing in a practical
system. Also the learning steps are to be repeated for each load demand which
increases the computation time.Reinforcement Learning (RL) is a method of learning through
interactions with environment. The main advantage of this approach is it does
not require a precise mathematical formulation. It can learn either by interacting
with the environment or interacting with a simulation model. Several
optimization and control problems have been solved through Reinforcement
Learning approach. The application of Reinforcement Learning in the field of
Power system has been a few. The objective is to introduce and extend
Reinforcement Learning approaches for the active power scheduling problems
in an implementable manner. The main objectives can be enumerated as:(i) Evolve Reinforcement Learning based solutions to the Unit
Commitment Problem.(ii) Find suitable solution strategies through Reinforcement Learning
approach for Economic Dispatch.
(iii) Extend the Reinforcement Learning solution to Automatic Generation
Control with a different perspective.
(iv) Check the suitability of the scheduling solutions to one of the existing
power systems.First part of the thesis is concerned with the Reinforcement Learning
approach to Unit Commitment problem. Unit Commitment Problem is
formulated as a multi stage decision process. Q learning solution is developed
to obtain the optimwn commitment schedule. Method of state aggregation is
used to formulate an efficient solution considering the minimwn up time I down
time constraints. The performance of the algorithms are evaluated for different
systems and compared with other stochastic methods like Genetic Algorithm.Second stage of the work is concerned with solving Economic Dispatch
problem. A simple and straight forward decision making strategy is first
proposed in the Learning Automata algorithm. Then to solve the scheduling
task of systems with large number of generating units, the problem is
formulated as a multi stage decision making task. The solution obtained is
extended in order to incorporate the transmission losses in the system. To make
the Reinforcement Learning solution more efficient and to handle continuous
state space, a fimction approximation strategy is proposed. The performance of
the developed algorithms are tested for several standard test cases. Proposed
method is compared with other recent methods like Partition Approach
Algorithm, Simulated Annealing etc.As the final step of implementing the active power control loops in
power system, Automatic Generation Control is also taken into consideration.Reinforcement Learning has already been applied to solve Automatic
Generation Control loop. The RL solution is extended to take up the approach
of common frequency for all the interconnected areas, more similar to practical
systems. Performance of the RL controller is also compared with that of the
conventional integral controller.In order to prove the suitability of the proposed methods to practical
systems, second plant ofNeyveli Thennal Power Station (NTPS IT) is taken for
case study. The perfonnance of the Reinforcement Learning solution is found to
be better than the other existing methods, which provide the promising step
towards RL based control schemes for practical power industry.Reinforcement Learning is applied to solve the scheduling problems in
the power industry and found to give satisfactory perfonnance. Proposed
solution provides a scope for getting more profit as the economic schedule is
obtained instantaneously. Since Reinforcement Learning method can take the
stochastic cost data obtained time to time from a plant, it gives an
implementable method. As a further step, with suitable methods to interface
with on line data, economic scheduling can be achieved instantaneously in a
generation control center. Also power scheduling of systems with different
sources such as hydro, thermal etc. can be looked into and Reinforcement
Learning solutions can be achieved.
Description:
School of Engineering,
Cochin University of Science and Technology
Vineshkumar, B; Dr.Unnikrishnan Nair, N(Cochin University of Science and Technology, May 30, 2012)
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Abstract:
Reliability analysis is a well established branch of statistics that deals with the statistical study of different aspects of lifetimes of a system of components. As we pointed out earlier that major part of the theory and applications in connection with reliability analysis were discussed based on the measures in terms of distribution function. In the beginning chapters of the thesis, we have described some attractive features of quantile functions and the relevance of its use in reliability analysis. Motivated by the works of Parzen (1979), Freimer et al. (1988) and Gilchrist (2000), who indicated the scope of quantile functions in reliability analysis and as a follow up of the systematic study in this connection by Nair and Sankaran (2009), in the present work we tried to extend their ideas to develop necessary theoretical framework for lifetime data analysis. In Chapter 1, we have given the relevance and scope of the study and a brief outline of the work we have carried out. Chapter 2 of this thesis is devoted to the presentation of various concepts and their brief reviews, which were useful for the discussions in the subsequent chapters .In the introduction of Chapter 4, we have pointed out the role of ageing concepts in reliability analysis and in identifying life distributions .In Chapter 6, we have studied the first two L-moments of residual life and their relevance in various applications of reliability analysis. We have shown that the first L-moment of residual function is equivalent to the vitality function, which have been widely discussed in the literature .In Chapter 7, we have defined percentile residual life in reversed time (RPRL) and derived its relationship with reversed hazard rate (RHR). We have discussed the characterization problem of RPRL and demonstrated with an example that the RPRL for given does not determine the distribution uniquely
Description:
Department of Statistics, Cochin University of Science and Technology
Shelbi, Joseph; Dr.Jagathy Raj, V P(Cochin University of Science And Technology, June , 2014)
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Abstract:
Software systems are progressively being deployed in many facets
of human life. The implication of the failure of such systems, has an
assorted impact on its customers. The fundamental aspect that supports a
software system, is focus on quality. Reliability describes the ability of
the system to function under specified environment for a specified
period of time and is used to objectively measure the quality. Evaluation
of reliability of a computing system involves computation of hardware
and software reliability. Most of the earlier works were given focus on
software reliability with no consideration for hardware parts or vice
versa. However, a complete estimation of reliability of a computing
system requires these two elements to be considered together, and thus
demands a combined approach. The present work focuses on this and
presents a model for evaluating the reliability of a computing system.
The method involves identifying the failure data for hardware
components, software components and building a model based on it, to
predict the reliability. To develop such a model, focus is given to the
systems based on Open Source Software, since there is an increasing
trend towards its use and only a few studies were reported on the
modeling and measurement of the reliability of such products. The
present work includes a thorough study on the role of Free and Open
Source Software, evaluation of reliability growth models, and is trying
to present an integrated model for the prediction of reliability of a
computational system. The developed model has been compared with
existing models and its usefulness of is being discussed.
Chiranjivi Jayaram,Ch V; Dr. Balchand, A N(Cochin University of Science & Technology, May , 2011)
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Abstract:
In this thesis, a variety of available satellite data products have been made use of
to bring out a synergistic analysis on the upwelling phenomenon in SEAS. Basic
concepts of remote sensing, upwelling and linked oceanography topics have been
dealt in this work .Auxiliary data products utilized in this study are described
in chapter 2. The climatological monthly variability of the upwelling signatures
are detailed under chapter 3. Chapter 4 presents the forcing factors that trigger
the upwelling process in SEAS. Chapter 5 describes the oceanic response to the
forcing factors with respect to the SST cooling and CHLA blooms. Chapter 6
presents the heat budget of the region and the variability of heat budget terms
with respect to upwelling. Chapter 7 describes the inter-annual variability of
upwelling intensity in SEAS and the influence of climatic events on upwelling.
Ajitha Kumar, B S; Dr.Alagarswami, K(Cochin University of Science And Technology, March , 1984)
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Abstract:
This thesis deals with the reproductive physiology of the two species of Indian sea mussels, namely the brown mussel perna indica and the green mussel p viridis .The major aspects of the study include ecophysiology of reproduction linking up the animal reproductive cycle of the animals with the ecological conditions of the natural mussel beds, biochemical and histochemical changes associated with reproduction and neurosecretory cycle in synchrony with the reproductive cycle. Some basic studies on gamete morphology and certain aspects of gamete physiology have been taken up. The experimental work deals with the influence of different feeding levels on gamatogenesis and maturation and the effect of ganglia ablation on spawning. The material for the investigation on perna indica were collected from the natural mussel beds at Vizhinjam near Trivandrum and on p.viridic from Elathur, near Calicut. The period of observation extended from October 1981 to December 1982.
Description:
Central marine fisheries research institute, Cochin University of Science And Technology