Development of Bioreactors for Nitrifying Water In Closed System Hatcheries Of Penaeid And Non-Penaeid Prawns

In the present study the development of bioreactors for nitrifying water in closed system hatcheries of penaeid and non-penaeid prawns. This work is an attempt in this direction to cater to the needs of aquaculture industry for treatment and remediation of ammonia and nitrate in penaeid and non-penaeid hatcheries, by developing nitrifying bacteria allochthonous to the particular environment under consideration, and immobilizing them on an appropriately designed support materials configured as reactors. Ammonia toxicity is the major limiting factors in penaeid and non-penaeid hatchery systems causing lethal and sublethal effects on larvae depending on the pH values. Pressing need of the aquaculture industry to have a user friendly and economically viable technology for the removal of ammonia, which can be easily integrated to the existing hatchery designs without any major changes or modifications. Only option available now is to have biological filters through which water can be circulated for the oxidation of ammonia to nitrate through nitrite by a group of chemolithotrophs known as nitrifying bacteria. Two types of bioreactors have been designed and developed. The first category named as in situ stringed bed suspended bioreactor(SBSBR) was designed for use in the larval rearing tanks to remove ammonia and nitrite during larval rearing on a continuous basis, and the other to be used for nitrifying freshly collected seawater and spent water named as ex situ packed bed bioreactior(PBBR). On employing the two reactors together , both penaeid and non-penaeid larval rearing systems can be made a closed recirculating system at least for a season. A survey of literature revealed that the in situ stringed bed suspended reactor developed here is unique in its design, fabrication and mode of application.

Information Discovery in Distributed Systems-A Novel Concept Based on Modelling of Information Elements

Sharing of information with those in need of it has always been an idealistic goal of networked environments. With the proliferation of computer networks, information is so widely distributed among systems, that it is imperative to have well-organized schemes for retrieval and also discovery. This thesis attempts to investigate the problems associated with such schemes and suggests a software architecture, which is aimed towards achieving a meaningful discovery. Usage of information elements as a modelling base for efficient information discovery in distributed systems is demonstrated with the aid of a novel conceptual entity called infotron.The investigations are focused on distributed systems and their associated problems. The study was directed towards identifying suitable software architecture and incorporating the same in an environment where information growth is phenomenal and a proper mechanism for carrying out information discovery becomes feasible. An empirical study undertaken with the aid of an election database of constituencies distributed geographically, provided the insights required. This is manifested in the Election Counting and Reporting Software (ECRS) System. ECRS system is a software system, which is essentially distributed in nature designed to prepare reports to district administrators about the election counting process and to generate other miscellaneous statutory reports.Most of the distributed systems of the nature of ECRS normally will possess a "fragile architecture" which would make them amenable to collapse, with the occurrence of minor faults. This is resolved with the help of the penta-tier architecture proposed, that contained five different technologies at different tiers of the architecture.The results of experiment conducted and its analysis show that such an architecture would help to maintain different components of the software intact in an impermeable manner from any internal or external faults. The architecture thus evolved needed a mechanism to support information processing and discovery. This necessitated the introduction of the noveI concept of infotrons. Further, when a computing machine has to perform any meaningful extraction of information, it is guided by what is termed an infotron dictionary.The other empirical study was to find out which of the two prominent markup languages namely HTML and XML, is best suited for the incorporation of infotrons. A comparative study of 200 documents in HTML and XML was undertaken. The result was in favor ofXML.The concept of infotron and that of infotron dictionary, which were developed, was applied to implement an Information Discovery System (IDS). IDS is essentially, a system, that starts with the infotron(s) supplied as clue(s), and results in brewing the information required to satisfy the need of the information discoverer by utilizing the documents available at its disposal (as information space). The various components of the system and their interaction follows the penta-tier architectural model and therefore can be considered fault-tolerant. IDS is generic in nature and therefore the characteristics and the specifications were drawn up accordingly. Many subsystems interacted with multiple infotron dictionaries that were maintained in the system.In order to demonstrate the working of the IDS and to discover the information without modification of a typical Library Information System (LIS), an Information Discovery in Library Information System (lDLIS) application was developed. IDLIS is essentially a wrapper for the LIS, which maintains all the databases of the library. The purpose was to demonstrate that the functionality of a legacy system could be enhanced with the augmentation of IDS leading to information discovery service. IDLIS demonstrates IDS in action. IDLIS proves that any legacy system could be augmented with IDS effectively to provide the additional functionality of information discovery service.Possible applications of IDS and scope for further research in the field are covered.

Investigations on Photoconductivity and Electrical Switiching in Selected Chalcogenide Glasses

In this thesis, we present the results of our investigations on the photoconducting and electrical switching properties of selected chalcogenide glass systems. We have used XRD and X-ray photoelectron spectroscopy (XPS) analysis for confinuing the amorphous nature of these materials and for confirming their constituents respectively.Photoconductivity is the enhancement in electrical conductivity of materials brought about by the motion of charge carriers excited by absorbed radiation. The phenomenon involves absorption, photogeneration, recombination and transport processes and it gives good insight into the density of states in the energy gap of solids due to the presence of impurities and lattice defects. Photoconductivity measurements lead to the determination of such important parameters as quantum efficiency, photosensiti\'ity, spectral sensitivity and carrier lifetime. Extensive research work on photoconducting properties of amorphous semiconductors has resulted in the development of a variety of very sensitive photodetectors. Photoconductors are finding newer and newer uses eyery day. CdS, CdSe. Sb2S3, Se, ZnO etc, are typical photoconducting materials which are used in devices like vidicons, light amplifiers, xerography equipment etc.Electrical switching is another interesting and important property possessed by several Te based chalcogenides. Switching is the rapid and reversible transition between a highly resistive OFF state, driven by an external electric field and characterized by a threshold voltage, and a low resistivity ON state, Switching can be either threshold type or memory type. The phenomenon of switching could find applications in areas like infonnation storage, electrical power control etc. Investigations on electrical switching in chalcogenide glasses help in understanding the mechanism of switching which is necessary to select and modify materials for specific switching applications.Analysis of XRD pattern gives no further infonuation about amorphous materials than revealing their disordered structure whereas x-ray photoelectron spectroscopy,XPS) provides information about the different constituents present in the material. Also it gives binding energies (b.e.) of an element in different compounds and hence b.e. shift from the elemental form.Our investigations have been concentrated on the bulk glasses, Ge-In-Se, Ge-Bi-Se and As-Sb-Se for photoconductivity measurements and In-Te for electrical switching. The photoconducting properties of Ge-Sb-Se thin films prepared by sputtering technique have also been studied. The bulk glasses for the present investigations are prepared by the melt quenching technique and are annealed for half an hour at temperatures just below their respective glass transition temperatures. The dependence of photoconducting propenies on composition and temperature are investigated in each system. The electrical switching characteristics of In-Te system are also studied with different compositions and by varying the temperature.

Effect of Improving Energy Efficiency on System Reliability

In the present scenario of energy demand overtaking energy supply top priority is given for energy conservation programs and policies. Most of the process plants are operated on continuous basis and consumes large quantities of energy. Efficient management of process system can lead to energy savings, improved process efficiency, lesser operating and maintenance cost, and greater environmental safety. Reliability and maintainability of the system are usually considered at the design stage and is dependent on the system configuration. However, with the growing need for energy conservation, most of the existing process systems are either modified or are in a state of modification with a view for improving energy efficiency. Often these modifications result in a change in system configuration there by affecting the system reliability. It is important that system modifications for improving energy efficiency should not be at the cost of reliability. Any new proposal for improving the energy efficiency of the process or equipments should prove itself to be economically feasible for gaining acceptance for implementation. In order to arrive at the economic feasibility of the new proposal, the general trend is to compare the benefits that can be derived over the lifetime as well as the operating and maintenance costs with the investment to be made. Quite often it happens that the reliability aspects (or loss due to unavailability) are not taken into consideration. Plant availability is a critical factor for the economic performance evaluation of any process plant.The focus of the present work is to study the effect of system modification for improving energy efficiency on system reliability. A generalized model for the valuation of process system incorporating reliability is developed, which is used as a tool for the analysis. It can provide an awareness of the potential performance improvements of the process system and can be used to arrive at the change in process system value resulting from system modification. The model also arrives at the pay back of the modified system by taking reliability aspects also into consideration. It is also used to study the effect of various operating parameters on system value. The concept of breakeven availability is introduced and an algorithm for allocation of component reliabilities of the modified process system based on the breakeven system availability is also developed. The model was applied to various industrial situations.

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.

Creation and Annihilation of Fluxons in ac‐driven Semi-annular Josephson Junction

A new geometry (semiannular) for Josephson junction has been proposed and theoretical studies have shown that the new geometry is useful for electronic applications [1, 2]. In this work we study the voltage‐current response of the junction with a periodic modulation. The fluxon experiences an oscillating potential in the presence of the ac‐bias which increases the depinning current value. We show that in a system with periodic boundary conditions, average progressive motion of fluxon commences after the amplitude of the ac drive exceeds a certain threshold value. The analytic studies are justified by simulating the equation using finite‐difference method. We observe creation and annihilation of fluxons in semiannular Josephson junction with an ac‐bias in the presence of an external magnetic field.

An Alternative Approach To Computer System Security Monitoring And Enhancement Through System Call Sequence Analysis

Modern computer systems are plagued with stability and security problems: applications lose data, web servers are hacked, and systems crash under heavy load. Many of these problems or anomalies arise from rare program behavior caused by attacks or errors. A substantial percentage of the web-based attacks are due to buffer overflows. Many methods have been devised to detect and prevent anomalous situations that arise from buffer overflows. The current state-of-art of anomaly detection systems is relatively primitive and mainly depend on static code checking to take care of buffer overflow attacks. For protection, Stack Guards and I-leap Guards are also used in wide varieties.This dissertation proposes an anomaly detection system, based on frequencies of system calls in the system call trace. System call traces represented as frequency sequences are profiled using sequence sets. A sequence set is identified by the starting sequence and frequencies of specific system calls. The deviations of the current input sequence from the corresponding normal profile in the frequency pattern of system calls is computed and expressed as an anomaly score. A simple Bayesian model is used for an accurate detection.Experimental results are reported which show that frequency of system calls represented using sequence sets, captures the normal behavior of programs under normal conditions of usage. This captured behavior allows the system to detect anomalies with a low rate of false positives. Data are presented which show that Bayesian Network on frequency variations responds effectively to induced buffer overflows. It can also help administrators to detect deviations in program flow introduced due to errors.

Growth And Characterization Of Te-Se System And Some Tei.I.Urioes

The physical properties of solid matter are basically influenced by the existence of lattice defects; as a result the study of crystal defects has assumed a central position in solid state physics and materials science. The study of dislocations ixa single crystals can yield a great deal of information on the mechanical properties of materials. In order to secure a full understanding of the processes taking place in semiconducting materials, it is important to investigate the microhardness of these materials-—the most reliable method of determining the fine structure of crystals, the revelation of micro—inhomogenities in the distribution of impurities, the effect of dislocation density on the mechanical properties of crystals etc. Basically electrical conductivity in single crystals is a defect controlled phenomenon and hence detailed investigation of the electrical properties of these materials is one of the best available methods for the study of defects in them. In the present thesis a series of detailed studies carried out in Te—Se system, Bi2Te3 and In2Te3 crystals using surface topographical, dislocation and microindentation analysis as well as electrical measurements are presented

Efficacy of Cluster- Based Approach for the revival of Handloom Co-operative Societies in Kerala- with special reference to Thiruvananthapuram and Kannur Districts

one of the key sectors, identified by the Department of Industries Government of Kerala, for the cluster development initiative is Handloom, which gives employment to over over 50,000 people directly. Despite its age old tradition and fame, the performance of the sector vis-à-vis power looms is not very rosy owing to (i) competition from cheap power loom cloth from other states (ii) scarcity of quality yarn (iii) price escalation of yarn, dyes, chemicals and other raw materials (iv) the shrinking market for handlooms in Kerala (v) non-demand based production and inadequacy of new designs and (vi) inefficiencies in the system, particularly in the co-operative sector. Cluster based approach is adopted in the handloom sector with the objective of providing necessary support mechanism to come out of the crisis that the sector faces now. While four cluster schemes are being implemented in Kerala, it is under IHDS-CDP that the State got a sizeable number of clusters benefiting a large number of societies and weavers- 24 handloom clusters, bringing 152 handloom co-operative societies and over 19,800 handloom workers under the Programme. This research attempts to revisit the underlying rationale and context of the new direction and would attempt to broadly analyze the growth trends under the influence of cluster model adopted by the State IHDS-CDP for the revival of handloom sector through a detailed study of the handloom co-operative societies in Kerala. If handloom sector in Kerala can be revived using cluster based approach, it can be easily concluded that cluster is capable of taking the MSME in Kerala to a ‘high growth path.’ The study is aimed at understanding how best clusters emerge as appropriate industrial organization suitable for the current global structure of manufacture

Performance Improvement of Fuzzy and Neuro Fuzzy Systems: Prediction of Learning Disabilities in School-age Children

Learning Disability (LD) is a classification including several disorders in which a child has difficulty in learning in a typical manner, usually caused by an unknown factor or factors. LD affects about 15% of children enrolled in schools. The prediction of learning disability is a complicated task since the identification of LD from diverse features or signs is a complicated problem. There is no cure for learning disabilities and they are life-long. The problems of children with specific learning disabilities have been a cause of concern to parents and teachers for some time. The aim of this paper is to develop a new algorithm for imputing missing values and to determine the significance of the missing value imputation method and dimensionality reduction method in the performance of fuzzy and neuro fuzzy classifiers with specific emphasis on prediction of learning disabilities in school age children. In the basic assessment method for prediction of LD, checklists are generally used and the data cases thus collected fully depends on the mood of children and may have also contain redundant as well as missing values. Therefore, in this study, we are proposing a new algorithm, viz. the correlation based new algorithm for imputing the missing values and Principal Component Analysis (PCA) for reducing the irrelevant attributes. After the study, it is found that, the preprocessing methods applied by us improves the quality of data and thereby increases the accuracy of the classifiers. The system is implemented in Math works Software Mat Lab 7.10. The results obtained from this study have illustrated that the developed missing value imputation method is very good contribution in prediction system and is capable of improving the performance of a classifier.

Spatial Variability and Contamination of Heavy Metals in the Inter-tidal Systems of a Tropical Environment

Heavy metals in the surface sediments of the two coastal ecosystems of Cochin, southwest India were assessed. The study intends to evaluate the degree of anthropogenic influence on heavy metal concentration in the sediments of the mangrove and adjacent estuarine stations using enrichment factor and geoaccumulation index. The inverse relationship of Cd and Zn with texture in the mangrove sediments suggested the anthropogenic enrichment of these metals in the mangrove systems. In the estuarine sediments, the absence of any significant correlation of the heavy metals with other sedimentary parameters and their strong interdependence revealed the possibility that the input is not through the natural weathering processes. The analysis of enrichment factor indicated a minor enrichment for Pb and Zn in mangrove sediments. While, extremely severe enrichment for Cd, moderate enrichment for Zn and minor enrichment of Pb were observed in estuarine system. The geo accumulation index exhibited very low values for all metals except Zn, indicating the sediments of the mangrove ecosystem are unpolluted to moderately polluted by anthropogenic activities. However, very strongly polluted condition for Cd and a moderately polluted condition for Zn were evident in estuarine sediments

A study on mitigating the effect of sulphates in lime stabilised Cochin marine clays

Soft clays known for their high compressibility, low stiffness and low shear strength are always associated with large settlement. In place soil treatment using calcium-based stabilizers like lime and cement is a feasible solution to readdress strength deficiencies and problematic shrink/swell behaviour of unstable subgrade soils. Out of these, lime has been proved unambiguously as the most effective and economical stabilising agent for marine clays. Lime stabilisation creates long-term chemical changes in unstable clay soils to create strong, but flexible, permanent structural layers in foundations and other pavement systems. Even though calcium-based stabilizers can improve engineering properties of soft clays, problems can arise when they are used in soils rich in sulphates. It is possible for marine clays to be enriched with sulphates, either by nature or due to the discharge of nearby industrial wastes containing sulphates. The presence of sulphates is reported to adversely affect the cation exchange and pozzolanic reactions of cement and lime treated soil systems. The anions of sulphates may combine with the available calcium and alumina, and form insoluble ettringite in the soil system. Literature on sulphate attack in lime treated marine clays reports that formation of ettringite in lime-sodium sulphate-clay system is capable of adversely affecting the engineering behavior of marine clays. Only very few studies have been conducted on soft marine clays found along the coastal belt of Kerala and that too, is limited to Cochin marine clays. The studies conducted also have the limitation that the strength behaviour of lime stabilised clay was investigated only for one year. Practically no data pertaining to long term adverse effects likely to be brought about by sulphates on the strength and compressibility characteristics of Cochin marine clays is available. The overriding goal of this investigation was thus to examine the effectiveness of lime stabilisation in Cochin marine clays under varying sulphate contents. The study aims to reveal the changes brought about by varying sulphate contents on both physical and engineering properties of these clays stabilised by lime and the results for various curing periods up to two years is presented in this thesis. Quite often the load causing an unacceptable settlement may be less than the load required to cause shear failure and therefore attempt has been made in this research to highlight sulphate induced changes in both the compressibility and strength characteristics of lime treated Cochin marine clays. The study also aimed at comparing the available IS methods for sulphate quantification and has attempted to determine the threshold level of sulphate likely make these clays vulnerable by lime stabilisation. Clays used in this study were obtained from two different sites in Kochi and contained sulphate in two different concentrations viz., 0.5% and 0.1%. Two different lime percentages were tried out, 3% and 6%. Sulphate content was varied from 1% to 4% by addition of reagent grade sodium sulphate. The long term influence of naturally present sulphate is also investigated. X-ray diffraction studies and SEM studies have been undertaken to understand how the soil-lime reactions are affected in the presence of sodium sulphate. Natural sulphate content of 0.1% did not seem to have influenced normal soil lime reactions but 0.5% sulphate could induce significant changes adversely in both compressibility and strength behaviour of lime treated clays after long duration. Compressibility is seen to increase drastically with increasing sulphate content suggesting formation of ettringite on curing for longer periods. Increase in compression index and decrease in bond strength with curing period underlined the adverse effects induced in lime treated marine clays by the presence of sulphates. Presence of sulphate in concentrations ranging from 0.5 % to 4% is capable of adversely affecting the strength of lime treated marine clays. Considerable decrease is observed with increasing concentrations of sulphate. Ettringite formation due to domination of sodium ions in the system was confirmed in mineralogical studies made. Barium chloride and barium hydroxide is capable of bringing about beneficial changes both in compressibility and strength characteristics of lime treated Cochin marine clays in the presence of varying concentrations of sulphate and is strongly influenced by curing time. Clay containing sodium sulphate has increased strength values when either of barium compounds was used with lime ascompared with specimens treated with lime only. Barium hydroxide is observed to remarkably increase the strength as compared to barium chloride,when used in conjunction with lime to counteract the effect of sulphate.

Improved Biometric Authentication System Using Multimodal Cue Integration

Biometrics is an efficient technology with great possibilities in the area of security system development for official and commercial applications. The biometrics has recently become a significant part of any efficient person authentication solution. The advantage of using biometric traits is that they cannot be stolen, shared or even forgotten. The thesis addresses one of the emerging topics in Authentication System, viz., the implementation of Improved Biometric Authentication System using Multimodal Cue Integration, as the operator assisted identification turns out to be tedious, laborious and time consuming. In order to derive the best performance for the authentication system, an appropriate feature selection criteria has been evolved. It has been seen that the selection of too many features lead to the deterioration in the authentication performance and efficiency. In the work reported in this thesis, various judiciously chosen components of the biometric traits and their feature vectors are used for realizing the newly proposed Biometric Authentication System using Multimodal Cue Integration. The feature vectors so generated from the noisy biometric traits is compared with the feature vectors available in the knowledge base and the most matching pattern is identified for the purpose of user authentication. In an attempt to improve the success rate of the Feature Vector based authentication system, the proposed system has been augmented with the user dependent weighted fusion technique.