Development and Evaluation of Blind Identification Techniques for Nonlinear Systems

Identification and Control of Non‐linear dynamical systems are challenging problems to the control engineers.The topic is equally relevant in communication,weather prediction ,bio medical systems and even in social systems,where nonlinearity is an integral part of the system behavior.Most of the real world systems are nonlinear in nature and wide applications are there for nonlinear system identification/modeling.The basic approach in analyzing the nonlinear systems is to build a model from known behavior manifest in the form of system output.The problem of modeling boils down to computing a suitably parameterized model,representing the process.The parameters of the model are adjusted to optimize a performanace function,based on error between the given process output and identified process/model output.While the linear system identification is well established with many classical approaches,most of those methods cannot be directly applied for nonlinear system identification.The problem becomes more complex if the system is completely unknown but only the output time series is available.Blind recognition problem is the direct consequence of such a situation.The thesis concentrates on such problems.Capability of Artificial Neural Networks to approximate many nonlinear input-output maps makes it predominantly suitable for building a function for the identification of nonlinear systems,where only the time series is available.The literature is rich with a variety of algorithms to train the Neural Network model.A comprehensive study of the computation of the model parameters,using the different algorithms and the comparison among them to choose the best technique is still a demanding requirement from practical system designers,which is not available in a concise form in the literature.The thesis is thus an attempt to develop and evaluate some of the well known algorithms and propose some new techniques,in the context of Blind recognition of nonlinear systems.It also attempts to establish the relative merits and demerits of the different approaches.comprehensiveness is achieved in utilizing the benefits of well known evaluation techniques from statistics. The study concludes by providing the results of implementation of the currently available and modified versions and newly introduced techniques for nonlinear blind system modeling followed by a comparison of their performance.It is expected that,such comprehensive study and the comparison process can be of great relevance in many fields including chemical,electrical,biological,financial and weather data analysis.Further the results reported would be of immense help for practical system designers and analysts in selecting the most appropriate method based on the goodness of the model for the particular context.

Pyocyanin (5-methyl-1-hydroxyphenazine) produced by Pseudomonas aeruginosa as antagonist to vibrios in aquaculture: overexpression, downstream process and toxicity

Pyocyanin is a versatile and multifunctional phenazine, widely used as a bio-control agent. Besides its toxicity in higher concentration, it has been applied as bio-control agents against many pathogens including the Vibrio spp. in aquaculture systems. The exact mechanism of the production of pyocyanin in Pseudomonas aeruginosa is well known, but the genetic modification of pyocyanin biosynthetic pathways in P. aeruginosa is not yet experimented to improve the yield of pyocyanin production. In this context, one of the aims of this work was to improve the yield of pyocyanin production in P. aeruginosa by way of increasing the copy number of pyocyanin pathway genes and their over expression. The specific aims of this work encompasses firstly, the identification of probiotic effect of P. aeruginosa isolated from various ecological niches, the overexpression of pyocyanin biosynthetic genes, development of an appropriate downstream process for large scale production of pyocyanin and its application in aquaculture industries. In addition, this work intends to examine the toxicity of pyocyanin on various developmental stages of tiger shrimp (Penaeus monodon), Artemia nauplii, microbial consortia of nitrifying bioreactors (Packed Bed Bioreactor, PBBR and Stringed Bed Suspended Bioreactor, SBSBR) and in vitro cell culture systems from invertebrates and vertebrates. The present study was undertaken with a vision to manage the pathogenic vibrios in aquaculture through eco-friendly and sustainable management strategies with the following objectives: Identification of Pseudomonas isolated from various ecological niches and its antagonism to pathogenic vibrios in aquaculture.,Saline dependent production of pyocyanin in Pseudomonas aeruginosa originated from different ecological niches and their selective application in aquaculture,Cloning and overexpression of Phz genes encoding phenazine biosynthetic pathway for the enhanced production of pyocyanin in Pseudomonas aeruginosa MCCB117,Development of an appropriate downstream process for large scale production of pyocyanin from PA-pUCP-Phz++; Structural elucidation and functional analysis of the purified compoundToxicity of pyocyanin on various biological systems.

Code clones in program test sequence identification

Code clones are portions of source code which are similar to the original program code. The presence of code clones is considered as a bad feature of software as the maintenance of software becomes difficult due to the presence of code clones. Methods for code clone detection have gained immense significance in the last few years as they play a significant role in engineering applications such as analysis of program code, program understanding, plagiarism detection, error detection, code compaction and many more similar tasks. Despite of all these facts, several features of code clones if properly utilized can make software development process easier. In this work, we have pointed out such a feature of code clones which highlight the relevance of code clones in test sequence identification. Here program slicing is used in code clone detection. In addition, a classification of code clones is presented and the benefit of using program slicing in code clone detection is also mentioned in this work.

Arbitrage Pricing Theory and Return Generating Process: A Macroeconomic Approach to Indian Stock Market

A study focusing on the identification of return generating factors and to the extent of their influence on share prices the outcome will be a tool for investment analysis in the hands of investors portfolio managers and mutual funds who are mostly concerned with changing share prices. Since the study takes into account the influence of macroeconomic variables on variations in share returns by using the outcome the government can frame out suitable policies on long term basis and that will help in nurturing a healthy economy and resultant stock market. As every company management tries to maximize the wealth of the share holders a clear idea about the return generating variables and their influence will help the management to frame various policies to maximize the wealth of the shareholders.

A Data Mining Approach for the Identification of Adverse Drug Events (ADE) resulting from Drug-Drug Interactions (DDI) to improve pharmacovigilance

In the current study, epidemiology study is done by means of literature survey in groups identified to be at higher potential for DDIs as well as in other cases to explore patterns of DDIs and the factors affecting them. The structure of the FDA Adverse Event Reporting System (FAERS) database is studied and analyzed in detail to identify issues and challenges in data mining the drug-drug interactions. The necessary pre-processing algorithms are developed based on the analysis and the Apriori algorithm is modified to suit the process. Finally, the modules are integrated into a tool to identify DDIs. The results are compared using standard drug interaction database for validation. 31% of the associations obtained were identified to be new and the match with existing interactions was 69%. This match clearly indicates the validity of the methodology and its applicability to similar databases. Formulation of the results using the generic names expanded the relevance of the results to a global scale. The global applicability helps the health care professionals worldwide to observe caution during various stages of drug administration thus considerably enhancing pharmacovigilance