POPULATION GENETIC STUDIES ON THE OIL SARDINE ( Sardinella longiceps )

The objective of present investigation was to study the population genetic structure of S. longiceps by applying three different basic population genetic techniques such as cytogenetics, non-enzymatic biochemicalgenetics (general protein) and morphomeristics/metrics.

Generation of Variability for Salt Tolerance in Rice Using Tissue Culture Techniques

The study deals with the generation of variability for salt tolerance in rice using tissue culture techniques. Rice is the staple food of more than half of the world’s population. The management of drought, salinity and acidity in soils are all energy intensive agricultural practices. The Genetic variability is the basis of crop improvement. Somaclonal and androclonal variation can be effectively used for this purpose. In the present study, eight isozymes were studied and esterase and isocitric dehydrogenase was found to have varietal specific, developmental stage specific and stress specific banding pattern in rice. Under salt stress thickness of bands and enzyme activity showed changes. Pokkali, a moderately salt tolerant variety, had a specific band 7, which was present only in this variety and showed slight changes under stress. This band was faint in tillering and flowering stage .Based on the results obtained in the present study it is suggested that esterase could possibly be used as an isozyme marker for salt tolerance in rice. Varietal differences and stage specific variations could be detected using esterase and isocitric dehydrogenase . Moreover somaclonal and androclonal variation could be effectively detected using isozyme markers.

Population Genetic Structure of the Marine Penaeid Prawn- Penaeus Indicus H. Milne Edwards 1837

The thesis contains the results of an investigation on the " Population Genetic Structure of the Penaeus indicus " from southeast and southwest coasts of India. The P.indicus, popularly known as the Indian white prawn, is distributed widely in the Indo-Pacific, starting from New South wales in Australia in the east to the east coast of Africa in the west. Its heavy demand in the export market, the species has been exploited intensively from all along its areas of distribution in Indian waters. The population genetic characteristics of the species were examined by three independent but complementary techniques, namely, morphometrics (truss network), biochemical genetics (isozyme electrophoresis ) and molecular genetics (RFLP and RAPD). The east and west coast populations of the species may be genetically different. Due to certain constraints, the results obtained from the studies of restriction fragment length 70 polymorphism (RFLP) were limited. The significant difference in the number of bands in the sample populations strongly suggests that these two populations have considerably different population genetic structures

Design Techniques for Sigmadelta based ADC for Wireless Applications

Analog-to digital Converters (ADC) have an important impact on the overall performance of signal processing system. This research is to explore efficient techniques for the design of sigma-delta ADC,specially for multi-standard wireless tranceivers. In particular, the aim is to develop novel models and algorithms to address this problem and to implement software tools which are avle to assist the designer's decisions in the system-level exploration phase. To this end, this thesis presents a framework of techniques to design sigma-delta analog to digital converters.A2-2-2 reconfigurable sigma-delta modulator is proposed which can meet the design specifications of the three wireless communication standards namely GSM,WCDMA and WLAN. A sigma-delta modulator design tool is developed using the Graphical User Interface Development Environment (GUIDE) In MATLAB.Genetic Algorithm(GA) based search method is introduced to find the optimum value of the scaling coefficients and to maximize the dynamic range in a sigma-delta modulator.

Molecular genetic characterization of endemic red -tailed barb,Gonoproktoptems curmuca (Hamilton - Buchanan, 1807)

The family Cyprinidae is the largest of freshwater fishes and, with the possible exception of Gobiidae, the largest family of vertebrates.Various members of this family are important as food fish, as aquarium fish, and in biological research. In this study, a fish species from this family exclusively found in the west flowing rivers originating from the Western Ghat region — Gonoproktopterus curmuca — was taken for population genetic analysis.There was an urgent need for restoration ecology by the development of apt management strategies to exploit resources judiciously. One of the strategies thus developed for the scientific management of these resources was to identify the natural units of the fishery resources under exploitation (Altukov, 1981). These natural units of a species can otherwise be called as stocks. A stock can be defined as a panmictic population of related individuals within a single species that is genetically distinct from other such populations.It is believed that a species may undergo micro evolutionary process and differentiate into genetically distinct sub-populations or stocks in course of time, if reproductively and geographically isolated.In recent times, there has been a wide spread degradation of natural aquatic environment due to anthropogenic activities and this has resulted in the decline and even extinction of some fish species. In such situations, evaluation of the genetic diversity of fish resources assumes important to conservation.The species selected for the study, was short-listed as one of the candidates for stock-specific, propagation assisted rehabilitation and management programme in rivers where it is naturally distributed. In connection with this, captive breeding and milt cryopreservation techniques of the species have been developed by the National Bureau of Fish Genetic Resources, Lucknow. However, for a scientific stock-specific rehabilitation programme, information on the stock structure and basic genetic profile of the species are essential and that is not available in case of G. curmuca. So the present work was taken up to identify molecular genetic markers like allozymes, microsatellites and RAPDs and, to use these markers to discriminate the distinct populations of the species, if any, in areas of its natural distribution. The genetic markers were found to be powerful tools to analyze the population genetic structure of the red-tailed barb and demonstrated clear cut genetic differentiation between pairs of populations examined. Geographic isolation by land distance is likely to be the factor that contributed to the restricted gene flow between the river systems. So the present study emphasizes the need for stock-wise, propagation assisted-rehabilitation of the natural populations of red-tailed barb, Gonoprokfopterus curmuca.

Multi-objective assembly job shop scheduling using genetic algorithm and tabu search

Assembly job shop scheduling problem (AJSP) is one of the most complicated combinatorial optimization problem that involves simultaneously scheduling the processing and assembly operations of complex structured products. The problem becomes even more complicated if a combination of two or more optimization criteria is considered. This thesis addresses an assembly job shop scheduling problem with multiple objectives. The objectives considered are to simultaneously minimizing makespan and total tardiness. In this thesis, two approaches viz., weighted approach and Pareto approach are used for solving the problem. However, it is quite difficult to achieve an optimal solution to this problem with traditional optimization approaches owing to the high computational complexity. Two metaheuristic techniques namely, genetic algorithm and tabu search are investigated in this thesis for solving the multiobjective assembly job shop scheduling problems. Three algorithms based on the two metaheuristic techniques for weighted approach and Pareto approach are proposed for the multi-objective assembly job shop scheduling problem (MOAJSP). A new pairing mechanism is developed for crossover operation in genetic algorithm which leads to improved solutions and faster convergence. The performances of the proposed algorithms are evaluated through a set of test problems and the results are reported. The results reveal that the proposed algorithms based on weighted approach are feasible and effective for solving MOAJSP instances according to the weight assigned to each objective criterion and the proposed algorithms based on Pareto approach are capable of producing a number of good Pareto optimal scheduling plans for MOAJSP instances.

“Reconstruction of Gene Regulatory Network from Expression Profile of Plasma RNA Data of Colorectal Cancer Patients using Soft Computing Techniques”

Microarray data analysis is one of data mining tool which is used to extract meaningful information hidden in biological data. One of the major focuses on microarray data analysis is the reconstruction of gene regulatory network that may be used to provide a broader understanding on the functioning of complex cellular systems. Since cancer is a genetic disease arising from the abnormal gene function, the identification of cancerous genes and the regulatory pathways they control will provide a better platform for understanding the tumor formation and development. The major focus of this thesis is to understand the regulation of genes responsible for the development of cancer, particularly colorectal cancer by analyzing the microarray expression data. In this thesis, four computational algorithms namely fuzzy logic algorithm, modified genetic algorithm, dynamic neural fuzzy network and Takagi Sugeno Kang-type recurrent neural fuzzy network are used to extract cancer specific gene regulatory network from plasma RNA dataset of colorectal cancer patients. Plasma RNA is highly attractive for cancer analysis since it requires a collection of small amount of blood and it can be obtained at any time in repetitive fashion allowing the analysis of disease progression and treatment response.

Faster techniques to evolve wavelet coefficients for better fingerprint image compression

In this article, techniques have been presented for faster evolution of wavelet lifting coefficients for fingerprint image compression (FIC). In addition to increasing the computational speed by 81.35%, the coefficients performed much better than the reported coefficients in literature. Generally, full-size images are used for evolving wavelet coefficients, which is time consuming. To overcome this, in this work, wavelets were evolved with resized, cropped, resized-average and cropped-average images. On comparing the peak- signal-to-noise-ratios (PSNR) offered by the evolved wavelets, it was found that the cropped images excelled the resized images and is in par with the results reported till date. Wavelet lifting coefficients evolved from an average of four 256 256 centre-cropped images took less than 1/5th the evolution time reported in literature. It produced an improvement of 1.009 dB in average PSNR. Improvement in average PSNR was observed for other compression ratios (CR) and degraded images as well. The proposed technique gave better PSNR for various bit rates, with set partitioning in hierarchical trees (SPIHT) coder. These coefficients performed well with other fingerprint databases as well.

A Faster 2D Technique for the design of Combinational Digital Circuits Using Genetic Algorithm

Combinational digital circuits can be evolved automatically using Genetic Algorithms (GA). Until recently this technique used linear chromosomes and and one dimensional crossover and mutation operators. In this paper, a new method for representing combinational digital circuits as 2 Dimensional (2D) chromosomes and suitable 2D crossover and mutation techniques has been proposed. By using this method, the convergence speed of GA can be increased significantly compared to the conventional methods. Moreover, the 2D representation and crossover operation provides the designer with better visualization of the evolved circuits. In addition to this, a technique to display automatically the evolved circuits has been developed with the help of MATLAB

An Improved Design of Combinational Digital Circuits with Multiplexers using Genetic Algorithm

This paper presents a new approach to the design of combinational digital circuits with multiplexers using Evolutionary techniques. Genetic Algorithm (GA) is used as the optimization tool. Several circuits are synthesized with this method and compared with two design techniques such as standard implementation of logic functions using multiplexers and implementation using Shannon’s decomposition technique using GA. With the proposed method complexity of the circuit and the associated delay can be reduced significantly