On Szegö’s Type Theorems

This study is to look the effect of change in the ordering of the Fourier system on Szegö’s classical observations of asymptotic distribution of eigenvalues of finite Toeplitz forms.This is done by checking proofs and Szegö’s properties in the new set up.The Fourier system is unconditional [19], any arbitrary ordering of the Fourier system forms a basis for the Hilbert space L2 [-Π, Π].Here study about the classical Szegö’s theorem.Szegö’s type theorem for operators in L2(R+) and check its validity for certain multiplication operators.Since the trigonometric basis is not available in L2(R+) or in L2(R) .This study discussed about the classes of orderings of Haar System in L2 (R+) and in L2(R) in which Szegö’s Type TheoreT Am is valid for certain multiplication operators.It is divided into two sections. In the first section there is an ordering to Haar system in L2(R+) and prove that with respect to this ordering, Szegö’s Type theorem holds for general class of multiplication operators Tƒ with multiplier ƒ ε L2(R+), subject to some conditions on ƒ.Finally in second section more general classes of ordering of Haar system in L2(R+) and in L2(R) are identified in such a way that for certain classes of multiplication operators the asymptotic distribution of eigenvalues exists.

Development of Photorefractive Polymers: Evaluation of Photoconducting and Electro-optic Properties

This Thesis discussed molecules suitable for photorefractive effect. Out of the molecules studied, only one system was used to make photorefractive polymers system. Other molecules, especially, the electro-optic polymer, Poly(3-methacrloyl-1-(4'-nitro-4-azo-1'-phenyl)phenylalanine-co- methyl methacrylate) can be subjected to more detailed studies to explore the possibilities of using them for electro-optic applications. Though not included in the thesis, the efficient photoconductor, Poly(6-tert-butyl-3- phenyl-3,4-dihydro-2H-1,3-benzoxazine) sensitized with C60, which was described in Chapter 3 showed a low magnitude photovoltaic effect. This hints at the possibility of using this system for organic solar cells also. The thesis presented the initial observation of photorefractive effect in a polybenzoxazine based polymer system. A detailed analysis of the effect of C60, ECZ and DR1 can be carried out to check for the possibility of a high efficiency photorefractive system.

Impact of Monetary Policy on Indian Economy in the Post-Reform Period

The present study was an attempt to analyze systematically the techniques of monetary control measures with its relevance and changing importance and to find out their effectiveness in the Indian context especially to achieve the thriving objectives of price stability and economic growth.There is definite and remarkable economic impact of monetary policy on Indian economy in the post-reform period. The importance of monetary policy has been increasing year after year. Its role is very relevant in attaining monetary objectives, especially in managing price stability and achieving economic growth. Along that, the use and importance of monetary weapons like Bank rate, CRR, SLR, Repo rate and Reverse Rate have increased over the years. Repo and Reverse Repo rates are the most frequently used monetary techniques in recent years. The rates are varied mainly for curtailing inflation and absorb the excess liquidity and hence to maintain price stability in the economy. Thus, this short-time objective of price stability is more successful on Indian economy rather than other long-term objectives of development.Monetary policy rules can be active or passive. The passive rule is to keep the money supply constant, which is reminiscent of Milton Friedman’s money growth rule. The second, called a price stabilization rule, is to change the money supply in response to changes in aggregate supply or demand to keep the price level constant. The idea of an active rule is to keep the price level and hence inflation in check. In India, this rule dominates our monetary policy. A stable growth is healthy growth.

Some Studies and New Results on Multi Microprocessor Applications

One of the fastest expanding areas of computer exploitation is in embedded systems, whose prime function is not that of computing, but which nevertheless require information processing in order to carry out their prime function. Advances in hardware technology have made multi microprocessor systems a viable alternative to uniprocessor systems in many embedded application areas. This thesis reports the results of investigations carried out on multi microprocessors oriented towards embedded applications, with a view to enhancing throughput and reliability. An ideal controller for multiprocessor operation is developed which would smoothen sharing of routines and enable more powerful and efficient code I data interchange. Results of performance evaluation are appended.A typical application scenario is presented, which calls for classifying tasks based on characteristic features that were identified. The different classes are introduced along with a partitioned storage scheme. Theoretical analysis is also given. A review of schemes available for reducing disc access time is carried out and a new scheme presented. This is found to speed up data base transactions in embedded systems. The significance of software maintenance and adaptation in such applications is highlighted. A novel scheme of prov1d1ng a maintenance folio to system firmware is presented, alongwith experimental results. Processing reliability can be enhanced if facility exists to check if a particular instruction in a stream is appropriate. Likelihood of occurrence of a particular instruction would be more prudent if number of instructions in the set is less. A new organisation is derived to form the basement for further work. Some early results that would help steer the course of the work are presented.

Analysis and Optimization of Machining Process Using Evolutionary Algorithms

To ensure quality of machined products at minimum machining costs and maximum machining effectiveness, it is very important to select optimum parameters when metal cutting machine tools are employed. Traditionally, the experience of the operator plays a major role in the selection of optimum metal cutting conditions. However, attaining optimum values each time by even a skilled operator is difficult. The non-linear nature of the machining process has compelled engineers to search for more effective methods to attain optimization. The design objective preceding most engineering design activities is simply to minimize the cost of production or to maximize the production efficiency. The main aim of research work reported here is to build robust optimization algorithms by exploiting ideas that nature has to offer from its backyard and using it to solve real world optimization problems in manufacturing processes.In this thesis, after conducting an exhaustive literature review, several optimization techniques used in various manufacturing processes have been identified. The selection of optimal cutting parameters, like depth of cut, feed and speed is a very important issue for every machining process. Experiments have been designed using Taguchi technique and dry turning of SS420 has been performed on Kirlosker turn master 35 lathe. Analysis using S/N and ANOVA were performed to find the optimum level and percentage of contribution of each parameter. By using S/N analysis the optimum machining parameters from the experimentation is obtained.Optimization algorithms begin with one or more design solutions supplied by the user and then iteratively check new design solutions, relative search spaces in order to achieve the true optimum solution. A mathematical model has been developed using response surface analysis for surface roughness and the model was validated using published results from literature.Methodologies in optimization such as Simulated annealing (SA), Particle Swarm Optimization (PSO), Conventional Genetic Algorithm (CGA) and Improved Genetic Algorithm (IGA) are applied to optimize machining parameters while dry turning of SS420 material. All the above algorithms were tested for their efficiency, robustness and accuracy and observe how they often outperform conventional optimization method applied to difficult real world problems. The SA, PSO, CGA and IGA codes were developed using MATLAB. For each evolutionary algorithmic method, optimum cutting conditions are provided to achieve better surface finish.The computational results using SA clearly demonstrated that the proposed solution procedure is quite capable in solving such complicated problems effectively and efficiently. Particle Swarm Optimization (PSO) is a relatively recent heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. From the results it has been observed that PSO provides better results and also more computationally efficient.Based on the results obtained using CGA and IGA for the optimization of machining process, the proposed IGA provides better results than the conventional GA. The improved genetic algorithm incorporating a stochastic crossover technique and an artificial initial population scheme is developed to provide a faster search mechanism. Finally, a comparison among these algorithms were made for the specific example of dry turning of SS 420 material and arriving at optimum machining parameters of feed, cutting speed, depth of cut and tool nose radius for minimum surface roughness as the criterion. To summarize, the research work fills in conspicuous gaps between research prototypes and industry requirements, by simulating evolutionary procedures seen in nature that optimize its own systems.

Reinforcement Learning Approaches to Power System Scheduling

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.

Targeted Public Distribution System in Food Grains:Extent of Utlization by the Tribal Population in Kerala

In India, Food Security meant supply of food grains and the medium was Public Distribution System. Public Distribution System (PDS) is a rationing mechanism that entitles households to specified quantities of selected commodities at subsidized prices. The Objectives of PDS are maintaining Price Stability, rationing during times of scarcity, welfare of the poor, and keeping a check on private trade. Kerala has registered remarkable improvement in poverty reduction in general over the years among all social sections, including scheduled caste and scheduled tribe population. As part of the structural adjustment intended to reduce public expenditure, PDS has been modified as Revamped PDS (RPDS) during 1992 and later on as Targeted PDS (TPDS) in 1997, intended to target households on the basis of income criterion, classifying people as Below Poverty Line (BPL) and Above Poverty Line (APL). TPDS provides 25Kg. of food gra.ins through the Fair Price Shops per month @ Rs.3/- per Kg. of rice/ wheat to the BPL category and @Rs.8.90 and Rs.6.7O for rice and wheat respectively to the APL category of people. Since TPDS is intended to target the poor people, the subsidy spent by the government for the scheme should be beneficial to the poor people and naturally they should utilize the benefits by purchasing the food grains allotted under the scheme. Several studies have shown that there is underutilization of the allotments under TPDS. Therefore, the extent of utilization of TPDS in food grains, how and why remains as a major hurdle, in improving the structure and system of PDS. Livelihood of the tribal population being under threat due to increasing degradation of the resources, the targeting system ought to be effective among the tribal population. Therefore, performance of the TPDS in food grains, in terms of the utilization by the tribal population in Kerala, impact thereof and the factors, if any, affecting proper utilization were considered as the research problem in this study. The study concentrated on the pattern of consumption of food grains by the tribal people, whether their hunger needs are met by distribution of food grains through the TPDS, extent to which TPDS in food grains reduce their share of expenditure on food in the total household expenditure, and the factors affecting the utilization of the TPDS in food grains by the tribal population. Going through the literature, it has been noted that only few studies concentrated on the utilization of TPDS in food grains among the tribal population in Kerala.The Research Design used in this study is descriptive in nature, but exploratory in some aspects. Idukki, Palakkad and Wayanad have more than 60% of the population of the tribals in the state. Within the three districts mentioned above, 14 villages with scheduled tribe concentration were selected for the study. 95 tribal colonies were selected from among the various tribal settlements. Collection of primary data was made from 1231 households with in the above tribal colonies. Analysis of data on the socio-economic factors of the tribal people, pattern of food consumption, extent of reduction in the share of expenditure on food among the household expenditure of the tribal people and the impact of TPDS on the tribal families etc. and testing of hypotheses to find out the relation/association of each of the six variables, using the data on BPL and APL categories of households separately have resulted in findings such as six percent of the tribal families do not have Ration Cards, average per capita consumption of food grains by the tribal people utilizing TPDS meets 62% of their minimum requirement, whereas the per capita consumption of food grains by the tribal people is higher than the national average per capita consumption, 63% deficiency in food grains may be felt by tribal people in general, if TPDS is withdrawn, and the deficit for BPL tribal people may be 82%, TPDS facilitates a reduction of 9.71% in the food expenditure among the total household expenditure of the tribal people in general, share of food to non-food among BPL category of tribals is 55:45 and 40:60 among the APL, Variables, viz. household income, number of members in the family and distance of FPS from tribal settlements etc. have influence on the quantity of rice being purchased by the tribal people from the Fair Price Shops, and there is influence of household income and distance of FPS from tribal settlements on the quantity of rice being purchased by the tribal people from the open market. Rationing with differential pricing on phased allotments, rectification of errors in targeting, anomalies in norms and procedures for classifying tribal people as BPL/APL, exclusive Income Generation for tribal population, paddy cultivation in the landholdings possessed by the tribal people, special drive for allotment of Ration Cards to the tribal people, especially those belonging to the BPL category, Mobile Fair Price Shops in tribal settlements, ensure quality of the food grains distributed through the TPDS, distribution of wheat flour in packed condition instead of wheat through the Fair Price Shops are recommended to address the shortcomings and weaknesses of the TPDS vis-avis the tribal population in Kerala.

Statistical Machine Learning Techniques for the Prediction of Learning Disabilities in School-Age Children

Learning Disability (LD) is a general term that describes specific kinds of learning problems. It is a neurological condition that affects a child's brain and impairs his ability to carry out one or many specific tasks. The learning disabled children are neither slow nor mentally retarded. This disorder can make it problematic for a child to learn as quickly or in the same way as some child who isn't affected by a learning disability. An affected child can have normal or above average intelligence. They may have difficulty paying attention, with reading or letter recognition, or with mathematics. It does not mean that children who have learning disabilities are less intelligent. In fact, many children who have learning disabilities are more intelligent than an average child. Learning disabilities vary from child to child. One child with LD may not have the same kind of learning problems as another child with LD. There is no cure for learning disabilities and they are life-long. However, children with LD can be high achievers and can be taught ways to get around the learning disability. In this research work, data mining using machine learning techniques are used to analyze the symptoms of LD, establish interrelationships between them and evaluate the relative importance of these symptoms. To increase the diagnostic accuracy of learning disability prediction, a knowledge based tool based on statistical machine learning or data mining techniques, with high accuracy,according to the knowledge obtained from the clinical information, is proposed. The basic idea of the developed knowledge based tool is to increase the accuracy of the learning disability assessment and reduce the time used for the same. Different statistical machine learning techniques in data mining are used in the study. Identifying the important parameters of LD prediction using the data mining techniques, identifying the hidden relationship between the symptoms of LD and estimating the relative significance of each symptoms of LD are also the parts of the objectives of this research work. The developed tool has many advantages compared to the traditional methods of using check lists in determination of learning disabilities. For improving the performance of various classifiers, we developed some preprocessing methods for the LD prediction system. A new system based on fuzzy and rough set models are also developed for LD prediction. Here also the importance of pre-processing is studied. A Graphical User Interface (GUI) is designed for developing an integrated knowledge based tool for prediction of LD as well as its degree. The designed tool stores the details of the children in the student database and retrieves their LD report as and when required. The present study undoubtedly proves the effectiveness of the tool developed based on various machine learning techniques. It also identifies the important parameters of LD and accurately predicts the learning disability in school age children. This thesis makes several major contributions in technical, general and social areas. The results are found very beneficial to the parents, teachers and the institutions. They are able to diagnose the child’s problem at an early stage and can go for the proper treatments/counseling at the correct time so as to avoid the academic and social losses.

Professional Services

This is a study on “Professional Services: Civil Liability for Deficiency”. This study is made with special reference to medical profession. The importance of qualitative professional services does not require any emphasis. It is a matter of great concern for the people as they are consumers.This study is divided into 12 chapters. The introductory chapter deals with characteristics of profession, basis of professional liability and international efforts to check abuse of position by professional men. Consumers as laymen can not perceive the intricacies of professional services. As a result professional men could misuse their superior position to expose consumers to hardship through deficient services. This is obvious from the fact that deficiency in professional services has assumed a menacing proportion. It is indicative of failure of internal control through self-regulation to check the abuse of position by the professional men. The professional bodies entrusted with the task of enforcing disciplinary measures show a very callous and indifferent attitude towards the repressive conduct of their members. These bodies are more concerned to protect the interest of their members. They are not free from institutional bias. They have put the interest of consumers into oblivion. In effect remedies through professional bodies has become a myth. All these factors make the external control of professional services mandatory to protect the consumers from the clutches of unscrupulous professional men, who abuse their superior position. The professional men who abuse their position are exposed to liability. Their liability arises under contract, tort and statutory law. The present study substantially concentrates on professional liability of medical men. The obvious reason is that of all professional services medical services are the frequently availed services by the consumers. Medical negligence cases account for bulk of the professional negligence cases. ln India also large number of cases are coming before consumer forae. The legal principles evolved in this sphere of professional service confers an insight into legal control of other professional services as well. The same principles are applied to other professions also, as by and large all the professions share common characteristics. Such principles are modified wherever necessary to make room for differential aspects of particular profession

Behaviour of laterised normal and self compacting concrete subjected to elevated temperatures

Concrete is a universal material in the construction industry. With natural resources like sand and aggregate, fast depleting, it is time to look for alternate materials to substitute these in the process of making concrete. There are instances like exposure to solar radiation, fire, furnaces, and nuclear reactor vessels, special applications like missile launching pads etc., where concrete is exposed to temperature variations In this research work, an attempt has been made to understand the behaviour of concrete when weathered laterite aggregate is used in both conventional and self compacting normal strength concrete. The study has been extended to understand the thermal behaviour of both types of laterised concretes and to check suitability as a fire protection material. A systematic study of laterised concrete considering parameters like source of laterite aggregate, grades of Ordinary Portland Cement (OPC) and types of supplementary cementitious materials (fly ash and GGBFS) has been carried out to arrive at a feasible combination of various ingredients in laterised concrete. A mix design methodology has been proposed for making normal strength laterised self compacting concrete based on trial mixes and the same has also been validated. The physical and mechanical properties of laterised concretes have been studied with respect to different variables like exposure temperature (200°C, 400°C and 600°C) and cooling environment (air cooled and water cooled). The behaviour of ferrocement elements with laterised self compacting concrete has also been studied by varying the cover to mesh reinforcement (10mm to 50mm at an interval of 10mm), exposure temperature and cooling environment.

Parasite distribution and histopathological studies on certain commercially important fishes of cochin area

In order to check the damage caused by the parasites, even though it is difficult in open waters, a proper understanding of the seasonal variation in the distribution of the parasite and other factors like age of the host, sex of the host, which affect distribution of parasite is a must. Although several workers have carried out investigations on the taxonomy of metazoan parasites of marine and brackish water Fishes of India, very little attempt is made to correlate such investigations with the host and the environment. In this thesis such an attempt is made by the researcher. In chapter one the literature related to the prevalence, mean intensity of infection, and histopathological changes caused by the metazoan parasites, in particular by helminths, copepods and isopods, was reviewed. Chapter two contains observations on the distribution pattern of parasites in relation to the season, sex, and size of the host. It was found that the prevalence rate of radiorynchus_indicus infecting the alimentary canal of Tachysurugs mgacuglatus, Ergasilus sp. infecting the gills of T maculatus, and Lernaeeniicus ramosus found on the body surface of Qeimgipteirfugs jagonicus was higher during monsoon season. But agarna malayi found in the opercular chamber and Ehilometra cephalus infecting the gonads of valamugil speiglari showed a higher prevalence rate during the postmonsoon season. This was discussed on the basis of the hydrographical characteristics prevailing in the study area during the three different seasons. It was also observed that the sex of the host did not influence significantly the distribution pattern of the parasites. The reasons for this were also discussed. Invariably, the size of the host was found to influence the parasite distribution pattern. It was observed that the prevalence rate showed an increase with increase in size of the fish. This was discussed on the basis of food habits of the host, along with other aspects An attempt was made in chapter three to study the histopathological effects of‘ the various parasites on their respective sites of attachments on host Fishes. It was found that except Rhadinorhyhchugs indicus, all other parasites produced damages of varying intensity, in the form of hypertrophy, rhyperplasia, haemorrhage, tissue disruption and ulcers. Interestingly, E. indicus, an acantho— cephalid with a powerful proboscis for attachment was found not to cause any serious damage to the intestine of the host Fish. All these aspects are included in the third and final chapter of the thesis.

Nonparametric Estimation of Survivor Function in Bivariate Competing Risk Models’

So far, in the bivariate set up, the analysis of lifetime (failure time) data with multiple causes of failure is done by treating each cause of failure separately. with failures from other causes considered as independent censoring. This approach is unrealistic in many situations. For example, in the analysis of mortality data on married couples one would be interested to compare the hazards for the same cause of death as well as to check whether death due to one cause is more important for the partners’ risk of death from other causes. In reliability analysis. one often has systems with more than one component and many systems. subsystems and components have more than one cause of failure. Design of high-reliability systems generally requires that the individual system components have extremely high reliability even after long periods of time. Knowledge of the failure behaviour of a component can lead to savings in its cost of production and maintenance and. in some cases, to the preservation of human life. For the purpose of improving reliability. it is necessary to identify the cause of failure down to the component level. By treating each cause of failure separately with failures from other causes considered as independent censoring, the analysis of lifetime data would be incomplete. Motivated by this. we introduce a new approach for the analysis of bivariate competing risk data using the bivariate vector hazard rate of Johnson and Kotz (1975).

Marketing orientation of small Firms- a study with reference to Trivandrum district

The small business has attracted very little attention of the historians in the ancient times, or public mind inspite of the fact that its impact on the various civilisations has been phenominal. Even in recent times economists considered the small firms as inappropriate, obselate and anacronistic as it cannot assimilate the full potential of technological change in the production system. But today everybody agrees that the small business has a definite role in shaping the human destiny and enhancing the quality of life in any society. In a developing country like India small firms are necessary to generate employment for millions, high standared of personal choice to consumers, provide competition and act as a check to monopoly power; further the small firms provide an important source of innovation and in turn it paves the way for entrepreneur development in the society. In many countries the small enterprises played a significant role in the growth and development of their economic system. Italy and Japan are quoted as classic examples . In India, too, with the abundance of labour and scarce capital resources small firms have been promoted and protected by the government. But one must say that the small firm owners/managers in India have been shy in developing a market orientation in themeselves. Due to this many firms failed and closed. The alarming rate of sickness among the small firms in India may be attributed to the lack of market driven/customer orientation approach among the owner/managers of small business. So the study on the market oreintation of the small firms has never been in the mind of marketing experts and academicians. Thus, an attempt is made to enquire into them systematically and scientifically. For the study, Trivandrum district in Kerala has been selected. The data for the study has been collected by the help of a schedule which has been prepared after consulting the relevant literature and after consultation with experts in the field, academicians and practising managers.

Development of a portable composite equipment for coastal fishery and hydrographic investigations

This thesis reports on the details of the works done to develop a complete system for acquisition of the important marine environmental parameters namely, current, current direction, salinity, temperature and depth. It encompaéps transducers,signalconditioners display arrangements and remote controlled multiplexer which constitue the system. The various associate instruentation and environmental requisites and problems have been discussed and solved to considerable extend. The design and development features of this composite system includes an integrated approach in order to make the final equipment to be simple, inexpensive and easy for operation from small and large boats. This could be achieved with the successful development of all required components with features matching between them, such as sensors, signals conditioners remote operated multiplexers, comon display methods, quick performance check and calibration methods. The major success rests on the development of sensors with excellent performance characteristics suitable for marine environment. out of the 5 sensors. that of current salinity and depth are quite noval types with specific advantages. The environmental effects have been eliminated to the required extend. The common signal conditioner for salinity, temperature and depth has noval design features for achieving simplicity, reliability and accomodating the three sensors of different functional requirements.

Speaker identification using models for phonemes

Motivation for Speaker recognition work is presented in the first part of the thesis. An exhaustive survey of past work in this field is also presented. A low cost system not including complex computation has been chosen for implementation. Towards achieving this a PC based system is designed and developed. A front end analog to digital convertor (12 bit) is built and interfaced to a PC. Software to control the ADC and to perform various analytical functions including feature vector evaluation is developed. It is shown that a fixed set of phrases incorporating evenly balanced phonemes is aptly suited for the speaker recognition work at hand. A set of phrases are chosen for recognition. Two new methods are adopted for the feature evaluation. Some new measurements involving a symmetry check method for pitch period detection and ACE‘ are used as featured. Arguments are provided to show the need for a new model for speech production. Starting from heuristic, a knowledge based (KB) speech production model is presented. In this model, a KB provides impulses to a voice producing mechanism and constant correction is applied via a feedback path. It is this correction that differs from speaker to speaker. Methods of defining measurable parameters for use as features are described. Algorithms for speaker recognition are developed and implemented. Two methods are presented. The first is based on the model postulated. Here the entropy on the utterance of a phoneme is evaluated. The transitions of voiced regions are used as speaker dependent features. The second method presented uses features found in other works, but evaluated differently. A knock—out scheme is used to provide the weightage values for the selection of features. Results of implementation are presented which show on an average of 80% recognition. It is also shown that if there are long gaps between sessions, the performance deteriorates and is speaker dependent. Cross recognition percentages are also presented and this in the worst case rises to 30% while the best case is 0%. Suggestions for further work are given in the concluding chapter.