935 resultados para pragmatic problem of induction
Resumo:
The present study gave emphasis on characterizing continuous probability distributions and its weighted versions in univariate set up. Therefore a possible work in this direction is to study the properties of weighted distributions for truncated random variables in discrete set up. The problem of extending the measures into higher dimensions as well as its weighted versions is yet to be examined. As the present study focused attention to length-biased models, the problem of studying the properties of weighted models with various other weight functions and their functional relationships is yet to be examined.
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In the present study an attempt has been made to synthesize some simple complexes of multidentate ligands. Analogous zeolite encapsulated complexes were also synthesized and characterized. Immobilization on to polymer supports through covalent attachment is expected to solve the problem of decomposition of many complexes during catalytic reaction. Hence the work is also extended to the synthesis and characterization of some polymer supported complexes of Schiff base Iigands. All the three types of synthesized complexes, simple, zeolite encapsulated and polystyrene anchored, were subjected to catalytic activity study towards catechol-oxidation reaction. A selected group of complexes were also screened for their catalytic activity towards phenol-oxidation reaction. Biological screening of the synthesized ligands and neat complexes were done with a view to establish the effect of complexation on biological systems.
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The thesis has covered various aspects of modeling and analysis of finite mean time series with symmetric stable distributed innovations. Time series analysis based on Box and Jenkins methods are the most popular approaches where the models are linear and errors are Gaussian. We highlighted the limitations of classical time series analysis tools and explored some generalized tools and organized the approach parallel to the classical set up. In the present thesis we mainly studied the estimation and prediction of signal plus noise model. Here we assumed the signal and noise follow some models with symmetric stable innovations.We start the thesis with some motivating examples and application areas of alpha stable time series models. Classical time series analysis and corresponding theories based on finite variance models are extensively discussed in second chapter. We also surveyed the existing theories and methods correspond to infinite variance models in the same chapter. We present a linear filtering method for computing the filter weights assigned to the observation for estimating unobserved signal under general noisy environment in third chapter. Here we consider both the signal and the noise as stationary processes with infinite variance innovations. We derived semi infinite, double infinite and asymmetric signal extraction filters based on minimum dispersion criteria. Finite length filters based on Kalman-Levy filters are developed and identified the pattern of the filter weights. Simulation studies show that the proposed methods are competent enough in signal extraction for processes with infinite variance.Parameter estimation of autoregressive signals observed in a symmetric stable noise environment is discussed in fourth chapter. Here we used higher order Yule-Walker type estimation using auto-covariation function and exemplify the methods by simulation and application to Sea surface temperature data. We increased the number of Yule-Walker equations and proposed a ordinary least square estimate to the autoregressive parameters. Singularity problem of the auto-covariation matrix is addressed and derived a modified version of the Generalized Yule-Walker method using singular value decomposition.In fifth chapter of the thesis we introduced partial covariation function as a tool for stable time series analysis where covariance or partial covariance is ill defined. Asymptotic results of the partial auto-covariation is studied and its application in model identification of stable auto-regressive models are discussed. We generalize the Durbin-Levinson algorithm to include infinite variance models in terms of partial auto-covariation function and introduce a new information criteria for consistent order estimation of stable autoregressive model.In chapter six we explore the application of the techniques discussed in the previous chapter in signal processing. Frequency estimation of sinusoidal signal observed in symmetric stable noisy environment is discussed in this context. Here we introduced a parametric spectrum analysis and frequency estimate using power transfer function. Estimate of the power transfer function is obtained using the modified generalized Yule-Walker approach. Another important problem in statistical signal processing is to identify the number of sinusoidal components in an observed signal. We used a modified version of the proposed information criteria for this purpose.
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The constitutive production of AMPs in shrimps ensures that animals are able to protect themselves from low-level assaults by pathogens present in the environment. As these molecules play important roles in the shrimp immune defense system, the expression level of these AMPs are possible indicators of the immune state of shrimps. The present study also indicates the antiviral property of AMPs, especially ALF, stressing the importance of their up-regulation through the application of immunostimulants/probiotics as a prophylactic strategy in aquaculture. The present study shows that shrimp defense system is equipped enough to evade WSSV infection to a certain extent, when the animals were maintained on marine yeast and probiotic diet, whereas the control diet fed group succumbed to WSSV infection. This study reveals that marine yeast and probiotic supplemented diet can delay the process of WSSV infection and confer greater protection to the animals. Particularly, the protection conferred by marine yeast, C. haemulonii S27 and Bacillus MCCB101 were highly promising imparting greater hope to the aquaculture community to overcome the prevailing disease problems in aquaculture. It may be inferred from the present study that up-regulation of AMP genes could be effected by the application of immunostimulants and probiotics. Also, AMP expression profile could be used as an effective tool for screening immunostimulants and probiotics for application in shrimp culture. Ultimately, it is likely that no single compound or strategy will provide a solution to the problem of disease within aquaculture and that, in reality, a suite of techniques will be required including the manipulation of the rearing environment, addition of probionts as a matter of routine during culture, and the use of immunostimulants and other supplements during vulnerable growth phases. Finally, the development of good management practices, the control of environmental variables, genetic improvement in the penaeid species, understanding of host-virus interaction, modulation of the shrimp immune system, supported by functional genomics and proteomics of this crustacean, as a whole suggests that the control of WSSV is not far.
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While the seriousness of the problem of antibiotic resistance is now recognized, the complex web of resistance linking humans, animals, and the environment is getting realized. More often, antibiotics are used as a preventive measure against diseases. Antibiotic use for agriculture leads to the increased resistance in the environment since antibiotics are inevitable element during agriculture/aquaculture and antibiotic residues are excreted as waste that is frequently spread onto farmland as organic fertilizer. Fecal bacteria survive long periods in the environment and spread through runoff into groundwater, rivers, and marine ecosystems.However, horizontal gene transfer occurs in the animals and guts of humans and in a variety of ecosystems, creating a pool of resistance in the rice fields and open waters. Even if people are not in direct contact with resistant disease through food animals, there are chances of contact with resistant fecal pathogens from the environment. Additionally, pathogens that are autochthonous to the environment can acquire resistance genes from the environment. Our study revealed that autochthonous , bacteria Vibrio spp gained antibiotic resistance in the environment. Further, it was evident that horizontal gene transfer occurs in Vibrio by means of plasmids, which further augments the gravity of the problem. Non-pathogenic bacteria may also acquire resistance genes and serve as a continuing source of resistance for other bacteria, both in the environment, and in the human gut. As the effectiveness of antibiotics for medical applications decline, the indiscriminate use of in aquaculture and in humans can have disastrous conditions in future due to horizontal gene transfer and the spread of resistant organisms: We must recognize and deal with the threat posed by overuse of antibiotics.
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The present study was an attempt to analytically approach the problem of farm
poverty in Kerala from an entirely different angle by incorporating an independently
developed and reformulated definition of poverty line in terms of physical units of
operational holdings (say, acre). The entire discussion on farm poverty emerged out of
proper co-ordination of two important factors popularly considered as the distinct
features of I
Resumo:
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.
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Computational Biology is the research are that contributes to the analysis of biological data through the development of algorithms which will address significant research problems.The data from molecular biology includes DNA,RNA ,Protein and Gene expression data.Gene Expression Data provides the expression level of genes under different conditions.Gene expression is the process of transcribing the DNA sequence of a gene into mRNA sequences which in turn are later translated into proteins.The number of copies of mRNA produced is called the expression level of a gene.Gene expression data is organized in the form of a matrix. Rows in the matrix represent genes and columns in the matrix represent experimental conditions.Experimental conditions can be different tissue types or time points.Entries in the gene expression matrix are real values.Through the analysis of gene expression data it is possible to determine the behavioral patterns of genes such as similarity of their behavior,nature of their interaction,their respective contribution to the same pathways and so on. Similar expression patterns are exhibited by the genes participating in the same biological process.These patterns have immense relevance and application in bioinformatics and clinical research.Theses patterns are used in the medical domain for aid in more accurate diagnosis,prognosis,treatment planning.drug discovery and protein network analysis.To identify various patterns from gene expression data,data mining techniques are essential.Clustering is an important data mining technique for the analysis of gene expression data.To overcome the problems associated with clustering,biclustering is introduced.Biclustering refers to simultaneous clustering of both rows and columns of a data matrix. Clustering is a global whereas biclustering is a local model.Discovering local expression patterns is essential for identfying many genetic pathways that are not apparent otherwise.It is therefore necessary to move beyond the clustering paradigm towards developing approaches which are capable of discovering local patterns in gene expression data.A biclusters is a submatrix of the gene expression data matrix.The rows and columns in the submatrix need not be contiguous as in the gene expression data matrix.Biclusters are not disjoint.Computation of biclusters is costly because one will have to consider all the combinations of columans and rows in order to find out all the biclusters.The search space for the biclustering problem is 2 m+n where m and n are the number of genes and conditions respectively.Usually m+n is more than 3000.The biclustering problem is NP-hard.Biclustering is a powerful analytical tool for the biologist.The research reported in this thesis addresses the problem of biclustering.Ten algorithms are developed for the identification of coherent biclusters from gene expression data.All these algorithms are making use of a measure called mean squared residue to search for biclusters.The objective here is to identify the biclusters of maximum size with the mean squared residue lower than a given threshold. All these algorithms begin the search from tightly coregulated submatrices called the seeds.These seeds are generated by K-Means clustering algorithm.The algorithms developed can be classified as constraint based,greedy and metaheuristic.Constarint based algorithms uses one or more of the various constaints namely the MSR threshold and the MSR difference threshold.The greedy approach makes a locally optimal choice at each stage with the objective of finding the global optimum.In metaheuristic approaches particle Swarm Optimization(PSO) and variants of Greedy Randomized Adaptive Search Procedure(GRASP) are used for the identification of biclusters.These algorithms are implemented on the Yeast and Lymphoma datasets.Biologically relevant and statistically significant biclusters are identified by all these algorithms which are validated by Gene Ontology database.All these algorithms are compared with some other biclustering algorithms.Algorithms developed in this work overcome some of the problems associated with the already existing algorithms.With the help of some of the algorithms which are developed in this work biclusters with very high row variance,which is higher than the row variance of any other algorithm using mean squared residue, are identified from both Yeast and Lymphoma data sets.Such biclusters which make significant change in the expression level are highly relevant biologically.
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The thesis mainly focuses on material characterization in different environments: freely available samples taken in planar fonn, biological samples available in small quantities and buried objects.Free space method, finds many applications in the fields of industry, medicine and communication. As it is a non-contact method, it can be employed for monitoring the electrical properties of materials moving through a conveyor belt in real time. Also, measurement on such systems at high temperature is possible. NID theory can be applied to the characterization of thin films. Dielectric properties of thin films deposited on any dielectric substrate can be determined. ln chemical industry, the stages of a chemical reaction can be monitored online. Online monitoring will be more efficient as it saves time and avoids risk of sample collection.Dielectric contrast is one of the main factors, which decides the detectability of a system. lt could be noted that the two dielectric objects of same dielectric constant 3.2 (s, of plastic mine) placed in a medium of dielectric constant 2.56 (er of sand) could even be detected employing the time domain analysis of the reflected signal. This type of detection finds strategic importance as it provides solution to the problem of clearance of non-metallic mines. The demining of these mines using the conventional techniques had been proved futile. The studies on the detection of voids and leakage in pipes find many applications.The determined electrical properties of tissues can be used for numerical modeling of cells, microwave imaging, SAR test etc. All these techniques need the accurate determination of dielectric constant. ln the modem world, the use of cellular and other wireless communication systems is booming up. At the same time people are concemed about the hazardous effects of microwaves on living cells. The effect is usually studied on human phantom models. The construction of the models requires the knowledge of the dielectric parameters of the various body tissues. lt is in this context that the present study gains significance. The case study on biological samples shows that the properties of normal and infected body tissues are different. Even though the change in the dielectric properties of infected samples from that of normal one may not be a clear evidence of an ailment, it is an indication of some disorder.ln medical field, the free space method may be adapted for imaging the biological samples. This method can also be used in wireless technology. Evaluation of electrical properties and attenuation of obstacles in the path of RF waves can be done using free waves. An intelligent system for controlling the power output or frequency depending on the feed back values of the attenuation may be developed.The simulation employed in GPR can be extended for the exploration of the effects due to the factors such as the different proportion of water content in the soil, the level and roughness of the soil etc on the reflected signal. This may find applications in geological explorations. ln the detection of mines, a state-of-the art technique for scanning and imaging an active mine field can be developed using GPR. The probing antenna can be attached to a robotic arm capable of three degrees of rotation and the whole detecting system can be housed in a military vehicle. In industry, a system based on the GPR principle can be developed for monitoring liquid or gas through a pipe, as pipe with and without the sample gives different reflection responses. lt may also be implemented for the online monitoring of different stages of extraction and purification of crude petroleum in a plant.Since biological samples show fluctuation in the dielectric nature with time and other physiological conditions, more investigation in this direction should be done. The infected cells at various stages of advancement and the normal cells should be analysed. The results from these comparative studies can be utilized for the detection of the onset of such diseases. Studying the properties of infected tissues at different stages, the threshold of detectability of infected cells can be determined.
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This thesis entitled “ Educational rights of the minorities under article 30 of the indian constitution.The study is divided into nine chapters.The object of the present study is to explore whether the judiciary has been successful in balancing the conflicting rights of the minorities and the state. The study also seeks to bring forth those judicial principles which have governed the operation of these rights and determined the limits of their application. Article 30 confers a special right on minorities to establish educational institutions of their own choice.This is an expression of the liberal and tolerent culture of our nation which is reflected in the Constitution. The idea is to foster unity' in diversity, ea unique characteristic of the Indian way of life.This study suggested that where a minority is a minority’ in the historical or national context and its claim is based on religion it must be defined and ascertained in terms of the population of the whole country irrespective of its being a numerical majority' in any particular State and the minority status. of linguistic group has to be ascertained in terms of the population of any particular State irrespective of its being a numerical minority in terms of the population of the whole country.A religious denomination also can be treated as a religion within the meaning of Article 30(1) provided it is having a separate organisation with doctrines and tenets and rites and practices of its own.
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This thesis Entitled Bayesian inference in Exponential and pareto populations in the presence of outliers. The main theme of the present thesis is focussed on various estimation problems using the Bayesian appraoch, falling under the general category of accommodation procedures for analysing Pareto data containing outlier. In Chapter II. the problem of estimation of parameters in the classical Pareto distribution specified by the density function. In Chapter IV. we discuss the estimation of (1.19) when the sample contain a known number of outliers under three different data generating mechanisms, viz. the exchangeable model. Chapter V the prediction of a future observation based on a random sample that contains one contaminant. Chapter VI is devoted to the study of estimation problems concerning the exponential parameters under a k-outlier model.
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This thesis entitled seasonal and interannual variability of sea level and associated surface meteorological parameters at cochin.The interesting aspect of studying sea level variability on different time scales can be attributed to the diversity of its applications.Study of tides could perhaps be the oldest branch of physical oceanography.The thesis is presented in seven chapters. The first chapter gives, apart from a general introduction, a survey of literature on sea level variability on different time scales - tidal, seasonal and interannual (geological scales excluded), with particular emphasis on the work carried out in the Indian waters. The second chapter is devoted to the study of observed tides at Cochin on seasonal and interannual time scales using hourly water level data for the period 1988-1993. The third chapter describes the long-term climatology of some important surface oceanographic and meteorological parameters (at Cochin) which are supposed to affect the sea level. The fourth chapter addresses the problem of seasonal forecasting of the meteorological and oceanographic parameters at Cochin using autoregressive, sinusoidal and exponentially weighted moving average techniques and testing their accuracy with the observed data for the period 1991-1993. The fifth chapter describes the seasonal cycles of sea level and the driving forces at 16 stations along the Indian subcontinent. It also addresses the observed interannual variability of sea level at 15 stations using available multi-annual data sets. The sixth chapter deals with the problem of coastal trapped waves between Cochin and Beypore off the Kerala coast using sea level and atmospheric pressure data sets for the year 1977. The seventh and the last chapter contains the summary and conclusions and future outlook based on this study.
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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
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The problems associated with emigration, inward remittances and economic development of Herala have not received ample attention. Kerala depends much on the inward remittances sent by Keralites employed abroad. It is a State that experience chronic unemployment problem. Emigration cannot provide a lasting solution to the problem of unemployment since its direction is governed mainly by the social, political and ecnonomic factors of the host countries. The present study is an attempt to focus attention on the major problems associated with emigration from Kerala. It also tries to deal with the issues involved in diverting the inward remittances to the development of the state which has some vital policy implications The problems associated with emigration, inward remittances and economic development of Herala have not received ample attention. Kerala depends much on the inward remittances sent by Keralites employed abroad. It is a State that experience chronic unemployment problem. Emigration cannot provide a lasting solution to the problem of unemployment since its direction is governed mainly by the social, political and ecnonomic factors of the host countries. The present study is an attempt to focus attention on the major problems associated with emigration from Kerala. It also tries to deal with the issues involved in diverting the inward remittances to the development of the state which has some vital policy implications Investment proepect of non~resident Keralites is the theme oi Chapter VIII. It examines the various measures taken to promote industrial development by attracting non~resident investment tc industrial ventures. Chapter IX diecusses the future of emigration from Kerale especially in the light of declining international oil prices. It also deals with the role o¥ emigration as a safety valve t: the chronic problem of unemployment in Kerala. The last Chapter presents the summary and conclusions of the study
Resumo:
The major objective of the researcher was to assess the gains or losses in relationship between spouses after sterilization of the wife. The second objective was to gauge the impact of sterilisation upon parent—child relationships. Factors that were responsible in motivating women to accept sterilization were subjected to enquiry with the conviction that the information would give insight into the inadequacies of the official Family Planning Programme, offering prospects for feasible and salutary changes. The report is arranged under six chapters. The first chapter, Introduction, has three parts. The global and natural dimension of the problem of population is considered in Part I; The Importance of the topic studied namely sterilisation is discussed in the second Part: and Part III explains the background and methodology %f the study. The second chapter is a description of tubecto~ mized women who were the respondents. Their personal and family data, economic, social, educational and demographic profilesform its contents. The direct and indirect influences that were-responsible to make women decide in favour of sterilization are dealt with in the Third chapter. The Fourth Chapter is an analysis of the interspouse relations pre and post—operatively and an assessment of gains and losses in the area subsequent to sterilisation. How children have benefitted physically and emotionally as a consequence of improved care/attention from parents post~operatively constitutes the analysis attempted in the Fifth chapter.