Studies on the Deep - Water Crab Charybdis (Goniohellenus ) Smithii Macleay From the Seas Around India

The present study deals with a general introduction which outlines the objective of the study providing an exhaustive review of works on crabs with particular reference to deep-sea forms. In the first section, Taxonomy and Geographical disribution of the crab are dealt with. The species is described in detail based on several male and female specimens obtained from the pelagic and bottom collections, and its identity in Indian waters is established. It is also distinguished from a closely allied species so far not reported from Indian waters. The second section comprises the biology of the species and it is dealt with under four subheading, namely Habit and Habitats, Reproduction, Food and feeding and Proximate composition. The different habitats occupied by juveniles, subadults and adults of the species have been described and discussed in the light of available information on differential distribution of other related species. The reproductive biology is described in various details touching on gross anatomy and histology of the reproductive systems, spermatogenesis, oogenesis, size at maturity, ovarian maturation process, fecundity, egg carriage and breeding. The food and feeding habits of the species have been studied with reference to the different life stages such as juveniles, subadults and adults during the different phases of life based on stomach content analysis. The percentage of meat recovery and protein, carbohydrate and lipid content of meat have been described in the section dealing with proximate composition. In section three the distribution and abundance of the crab for the entire Indian EEZ and some contiguous ares have been described and illustrated in detail separately for pelagic and benthic realms. The size frequency disrtibution, sex ratios, length weight relationship and relative abundance of breeding population in the experimental catches have been dealt with in detail and discussed.

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.

Threshold Autoregressive Model for a Time Series Data

In this paper we try to fit a threshold autoregressive (TAR) model to time series data of monthly coconut oil prices at Cochin market. The procedure proposed by Tsay [7] for fitting the TAR model is briefly presented. The fitted model is compared with a simple autoregressive (AR) model. The results are in favour of TAR process. Thus the monthly coconut oil prices exhibit a type of non-linearity which can be accounted for by a threshold model.

Studies on the microbial pathogens salmonella and vibrio parahfamolyticus in selected marine products

This thesis deals initially with a literature reference survey ,taxonomy, their incidence in selected food fishes and shellfishes, and their incidence and distribution, their survival during different types of processing, their heat survival at temperatures of 50 ,55 and 60 degree centigrade their growth initiation at different low levels of pHs(4.0 to 10) ,and their developmental resistance to various chemical agents. The trials for the study were collected from various landing centre at cochin and the retail outlets. Based on these data collections the researcher was able to obtain more knowledge of the processing technology and the survival of pathogens like salmonella and vibrio parahaemolyticus.

ARMA modeling of time series based on rational approximation of spectral density function

This study is concerned with Autoregressive Moving Average (ARMA) models of time series. ARMA models form a subclass of the class of general linear models which represents stationary time series, a phenomenon encountered most often in practice by engineers, scientists and economists. It is always desirable to employ models which use parameters parsimoniously. Parsimony will be achieved by ARMA models because it has only finite number of parameters. Even though the discussion is primarily concerned with stationary time series, later we will take up the case of homogeneous non stationary time series which can be transformed to stationary time series. Time series models, obtained with the help of the present and past data is used for forecasting future values. Physical science as well as social science take benefits of forecasting models. The role of forecasting cuts across all fields of management-—finance, marketing, production, business economics, as also in signal process, communication engineering, chemical processes, electronics etc. This high applicability of time series is the motivation to this study.

Studies on meroplankton

Plankton community, drawn from a vary wide variety of animal phyla, formed the basic food supply of marine life and indicators of water mass. The term meroplankton generally referred to that portion of the zooplankton which is transient in nature, remaining rest of their lives in the nektonic or benthic environment. This group was selected for intensive studies, considering the role of meroplankton in the economy of the sea and the scarcity of literature on them from the Indian Ocean. The preser .udy besides providing information regarding the fixation and preservation !e _ iniques and biochemical aspects of tropical meroplankton, also consolidates information regarding their zoogeography in the Indian Ocean region, with a view to amplifying the limited information available from this area. The distribution studies are based on the collections made during the International Indian Ocean Expedition (1960-65), whereas the material for preservation and biochemical studies was collected from the coastal waters during 1968-1978. Salient features:- 2% of formaldehyde buffered with 2% borax, added to the plankton in the ratio of 9:1 was found the best fixative. On fixation the plankton underwent shrinkage due to loss of 15 to 87% water. Addition of antioxidants prevented colour fading. Narcotization by different specific reagents prior to fixation reduced distortions due to violent reaction and improved morphological conditions. One percent formaldehyde solution in sea water buffered with borax or neutralised with calcium carbonate perfectly preserved majority of meroplankton. Equally good was one percent propylene phenoxetol buffered with borax. Biochemical compostion of vaioous taxa showed variations according to their age class, size groups metamorphosing stage, feeding mechanism, type of organism fed and time of collection. General distribution studies of 4 meroplankton taxa - Anthozoan larvae, cirripedia larvae, sipunculoid larvae and gastropod larvae stowed abundance in the coastal areas especially during the SW monsoon period. Based on the larval distribution different zoo-geographical areas in the Indian Ocean are differentiated.

Risk Assessment of Rooftop- Collected Rainwater for Individual Household and Community Use in Central Kerala, India

Water quality of rooftop-collected rainwater is an issue of increased interest particularly in developing countries where the collected water is used as a source of drinking water. Bacteriological and chemical parameters of 25 samples of rooftop-harvested rainwater stored in ferrocement tanks were analyzed in the study described in this article. Except for the pH and lower dissolved oxygen levels, all other physicochemical parameters were within World Health Organization guidelines. Bacteriological results revealed that the rooftop-harvested rainwater stored in tanks does not often meet the bacteriological quality standards prescribed for drinking water. Fifty percent of samples of harvested rainwater for rural and urban community use and 20% of the samples for individual household use showed the presence of E. coli. Fecal coliform/fecal streptococci ratios revealed nonhuman animal sources of fecal pollution. Risk assessment of bacterial isolates from the harvested rainwater showed high resistance to ampicillin, erythromycin, penicillin, and vancomycin. Multiple antibiotic resistance (MAR) indexing of the isolates and elucidation of the resistance patterns revealed that 73% of the isolates exhibited MAR

Checklist of freshwater fishes collected from Ernakulam District, Kerala, India

Journal of Threatened Taxa | September 2009 | 1(9): 493-494

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.

High Selectivity Filter Employing Stepped Impedance Resonators, Series Capacitors and Defected Ground Structures for Ultra Wide Band Applications

The paper presents a compact planar Ultra Wide Band ¯lter employing folded stepped impedance resonators with series capacitors and dumb bell shaped defected ground structures. An interdigital quarter wavelength coupled line is used for achieving the band pass characteristics. The transmission zeros are produced by stepped impedance resonators. The ¯lter has steep roll o® rate and good attenuation in its lower and upper stop bands, contributed by the series capacitor and defected ground structures respectively.

Enhancement of Calcifications in Mammograms using Volterra Series based Quadratic Filter

The paper summarizes the design and implementation of a quadratic edge detection filter, based on Volterra series, for enhancing calcifications in mammograms. The proposed filter can account for much of the polynomial nonlinearities inherent in the input mammogram image and can replace the conventional edge detectors like Laplacian, gaussian etc. The filter gives rise to improved visualization and early detection of microcalcifications, which if left undetected, can lead to breast cancer. The performance of the filter is analyzed and found superior to conventional spatial edge detectors