Modeling and Analysis of Some Heavy Tailed Time Series

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.

Recurrence Quantification Analysis of System Signals for Detecting Tool and Chatter in Turning

In this thesis, the applications of the recurrence quantification analysis in metal cutting operation in a lathe, with specific objective to detect tool wear and chatter, are presented.This study is based on the discovery that process dynamics in a lathe is low dimensional chaotic. It implies that the machine dynamics is controllable using principles of chaos theory. This understanding is to revolutionize the feature extraction methodologies used in condition monitoring systems as conventional linear methods or models are incapable of capturing the critical and strange behaviors associated with the metal cutting process.As sensor based approaches provide an automated and cost effective way to monitor and control, an efficient feature extraction methodology based on nonlinear time series analysis is much more demanding. The task here is more complex when the information has to be deduced solely from sensor signals since traditional methods do not address the issue of how to treat noise present in real-world processes and its non-stationarity. In an effort to get over these two issues to the maximum possible, this thesis adopts the recurrence quantification analysis methodology in the study since this feature extraction technique is found to be robust against noise and stationarity in the signals.The work consists of two different sets of experiments in a lathe; set-I and set-2. The experiment, set-I, study the influence of tool wear on the RQA variables whereas the set-2 is carried out to identify the sensitive RQA variables to machine tool chatter followed by its validation in actual cutting. To obtain the bounds of the spectrum of the significant RQA variable values, in set-i, a fresh tool and a worn tool are used for cutting. The first part of the set-2 experiments uses a stepped shaft in order to create chatter at a known location. And the second part uses a conical section having a uniform taper along the axis for creating chatter to onset at some distance from the smaller end by gradually increasing the depth of cut while keeping the spindle speed and feed rate constant.The study concludes by revealing the dependence of certain RQA variables; percent determinism, percent recurrence and entropy, to tool wear and chatter unambiguously. The performances of the results establish this methodology to be viable for detection of tool wear and chatter in metal cutting operation in a lathe. The key reason is that the dynamics of the system under study have been nonlinear and the recurrence quantification analysis can characterize them adequately.This work establishes that principles and practice of machining can be considerably benefited and advanced from using nonlinear dynamics and chaos theory.

Strip-loaded hollow dielectric H-plane sectoral horn antennas for square radiation pattern

The radiation characteristics of a new type of hollow dielectric H-plane sectoral horn antenna are presented. Metallic strips of optimum length are loaded on the H-walls of the sectoral horns. The effects of strip loading for producing square patterns in the H plane are discussed.

Systematics, Germplasm evaluation and pattern of distribution and abundance of freshwater fishes of Kerala (lndia)

The overall focus of the thesis involves the systematics,germplasm evaluation and pattern of distribution and abundance of freshwater fishes of kerala (india).Biodiversity is the measure of variety of Life.With the signing on the convention on biodiversity, the countries become privileged with absolute rights and responsibility to conserve and utilize their diverse resources for the betterment of mankind in a sustainable way. South-east Asia along with Africa and South America were considered to be the most biodiversity rich areas in the world .The tremendous potential associated with the sustainable utilization of fish germplasm resources of various river systems of Kerala for food, aquaculture and ornamental purposes have to be fully tapped for economic upliftment of fisherman community and also for equitable sharing of benefits among the mankind without compromising the conservation of the rare and unique fish germplasm resources for the future generations.The study was carried during April 2000 to December 2004. 25 major river systems of Kerala were surveyed for fish fauna for delineating the pattern of distribution and abundance of fishes both seasonally and geographically.The results of germplasm inventory and evaluation of fish species were presented both for the state and also river wise. The results of evaluation of fish species for their commercial utilization revealed that, of the 145, 76 are ornamental, 47 food and 22 cultivable. 21 species are strictly endemic to Kerala rivers. The revalidation on biodiversity status of the fishes assessed based on IUCN is so alarming that a high percentage of fishes (59spp.) belong to threatened category which is inclusive of 8 critically ndangered (CR), 36 endangered and 15 species under vulnerable (VU) category.The river wise fish germplasm inventory surveys were conducted in 25 major river systems of Kerala.The results of the present study is indicative of existence of several new fish species in the streams and rivulets located in remote areas of the forests and therefore, new exclusive surveys are required to surface fish species new to science, new distributional records etc, for the river systems.The results of fish germplasm evaluation revealed that there exist many potential endemic ornamental and cultivable fishes in Kerala. It is found imperative to utilize these species sustainably for improving the aquaculture production and aquarium trade of the country which would definitely fetch more income and generate employment.

Household Energy consumption pattern in rural Kerala

The present thesis critically analyzes the micro level issues that influence the rural household energy behavior in Kerala. The aim of the study is to examine the energy consumption pattern at the household level in rural Kerala and to assess the variations in rural household energy consumption pattern across geo-climatic and socio-economic clusters. The researcher assess the attitudes of the rural households towards energy sources, uses and devices. The study tries to identify the factors influencing the adoption of energy conservation practices and shift to the improved energy

Pattern of Executive Remuneration in the Manufacturing Public Enterprises in Kerala

The study is undertaken by the researcher with the object of examining the remuneration pattern of executive personnel in the manufacturing public enterprises in Kerala so as to find out whether there is any rationale or criteria involved in remunerating executives. It is also envisaged to find out the pattern of executive remuneration in the various categories of industries and inter—industry disparities among the public sector enterprises. This is considered to be a very fruitful area for investigation, particularly in view of the generally prevailing notion that public sector executives in Kerala are not remunerated properly and glaring inequalities and disparities are existing among the various categories of industries and within the same industry. Therefore the study is to explore the criteria used for the determination of executive remuneration and the relative weightage of various factors such as size of the firm, rate of return sales volume etc of the organisation and various other factors such as qualification, experience, level of job and functions of executives. Further the study is extended to find out the role of 'pay' towards motivation and efficiency of the executive personnel

A Writer Identification System For Handwritten Malayalam Documents

Handwriting is an acquired tool used for communication of one's observations or feelings. Factors that inuence a person's handwriting not only dependent on the individual's bio-mechanical constraints, handwriting education received, writing instrument, type of paper, background, but also factors like stress, motivation and the purpose of the handwriting. Despite the high variation in a person's handwriting, recent results from different writer identification studies have shown that it possesses sufficient individual traits to be used as an identification method. Handwriting as a behavioral biometric has had the interest of researchers for a long time. But recently it has been enjoying new interest due to an increased need and effort to deal with problems ranging from white-collar crime to terrorist threats. The identification of the writer based on a piece of handwriting is a challenging task for pattern recognition. The main objective of this thesis is to develop a text independent writer identification system for Malayalam Handwriting. The study also extends to developing a framework for online character recognition of Grantha script and Malayalam characters

Antibiotic resistance pattern of motile aeromonads from farm raised fresh water fish

Motile aeromonads isolated from the intestines of farm-raised freshwater fish such as Catla catla, Labeo rohita and Ctenopharyngodon idella have been characterized to species level. Morphological and physiological grouping revealed 61% Aeromonas hydrophila, 30% Aeromonas caviae, 7% Aeromonas sobria and 2% which remained unidentified. Hemolytic activity was detected mostly in A. hydrophila, while only half of the A. sobria and A. caviae showed this activity. Antibiotic resistance patterns of the strains revealed that they had acquired a relatively higher resistance to oxytetracycline, amoxycillin, ampicillin, novobiocin and polymixin-B, implicating possible use of these antibiotics in the aquaculture systems.

Virulence Potential And Antibiotic Susceptibility Pattern Of Motile Aeromonads Associated With Freshwater Ornamental Fish Culture Systems: A Possible Threat To public Health

Aeromonas spp. are ubiquitous aquatic organisms, associated with multitude of diseases in several species of animals, including fishes and humans. In the present study, water samples from two ornamental fish culture systems were analyzed for the presence of Aeromonas. Nutrient agar was used for Aeromonas isolation, and colonies (60 No) were identified through biochemical characterization. Seven clusters could be generated based on phenotypic characters, analyzed by the programme NTSYSpc, Version 2.02i, and identified as: Aeromonas caviae (33.3%), A. jandaei (38.3%) and A. veronii biovar sobria (28.3%). The strains isolated produced highly active hydrolytic enzymes, haemolytic activity and slime formation in varying proportions. The isolates were also tested for the enterotoxin genes (act, alt and ast), haemolytic toxins (hlyA and aerA), involved in type 3 secretion system (TTSS: ascV, aexT, aopP, aopO, ascF–ascG, and aopH), and glycerophospholipid-cholesterol acyltransferase (gcat). All isolates were found to be associated with at least one virulent gene. Moreover, they were resistant to frequently used antibiotics for human infections. The study demonstrates the pathogenic potential of Aeromonas, associated with ornamental fish culture systems suggesting the emerging threat to public health

Ultrasound Image Despeckling using Local Binary Pattern Weighted Linear Filtering

Speckle noise formed as a result of the coherent nature of ultrasound imaging affects the lesion detectability. We have proposed a new weighted linear filtering approach using Local Binary Patterns (LBP) for reducing the speckle noise in ultrasound images. The new filter achieves good results in reducing the noise without affecting the image content. The performance of the proposed filter has been compared with some of the commonly used denoising filters. The proposed filter outperforms the existing filters in terms of quantitative analysis and in edge preservation. The experimental analysis is done using various ultrasound images

Learning disability prediction tool using ANN and ANFIS

Learning Disability (LD) is a neurological condition that affects a child’s brain and impairs his ability to carry out one or many specific tasks. LD affects about 15 % of children enrolled in schools. The prediction of LD is a vital and intricate job. The aim of this paper is to design an effective and powerful tool, using the two intelligent methods viz., Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System, for measuring the percentage of LD that affected in school-age children. In this study, we are proposing some soft computing methods in data preprocessing for improving the accuracy of the tool as well as the classifier. The data preprocessing is performed through Principal Component Analysis for attribute reduction and closest fit algorithm is used for imputing missing values. The main idea in developing the LD prediction tool is not only to predict the LD present in children but also to measure its percentage along with its class like low or minor or major. The system is implemented in Mathworks Software MatLab 7.10. The results obtained from this study have illustrated that the designed prediction system or tool is capable of measuring the LD effectively

Pattern Analysis Techniques for the Recognition of Unconstrained Handwritten Malayalam Character Images

The objective of the study is to develop a hand written character recognition system that could recognisze all the characters in the mordern script of malayalam language at a high recognition rate

Social Media- A relevant tool for tourism and hospitality marketing

Tourism is an industry which is heavily dependent on marketing. Mouth to mouth communication has played a major role in shaping a number of destinations.This is particularly true in modern parlance.This is social networking phenomenon which is fast spreading over the internet .Many sites provide visitors a lot of freedom to express their views.Promotion of a destination depends lot on conversation and exchange of information over these social networks.This paper analyses the social networking sites their contribution to marketing tourism and hoapitality .The negetive impacts phenomena are also discussed