Taxonomy, Bionomics and Biofouling of Bryozoans from the Coasts of India and the Antarctic Waters

The study of bryozoans, an important group of coelomates in the marine environment is an integral part of faunistic investigations. Bryozones are an ancient, aberrant phylum of microscopic but fascinating and often beautiful animals that build intricate colonies sometimes resembling minicolonies. In this study taxonomy, bionomics and biofouling of bryozoans from the coasts of India and the Antarctic waters. The marine biofouling is found to be hazardous. Bryozoans are microscopic , sessile,colonical coelomates that are permanently fastened in exoskeletal cases or gelatinous material of their own secretion.It is hoped that this work would help the future researchers to devote attention on microbenthos of the continental shelf of India when samples are made available through collections conducted by any ocean going vessel. In the present work an extensive study on the bryozoan foulers that occur at five selected sites of the cochin estury had to be examined and since the hydrographic parameters such as salinity, temperature, pH and dissolved oxygen in the estury,vary greatly from that in the open ocean, a frequent monitoring of these parameters was essential.

STUDIES ON TAXONOMY, DISTRIBUTION, ECOLOGY AND REPRODUCTIVE POTENTIAL OF ROTIFERS FROM SELECTED CENTRES IN COCHIN BACKWATER SYSTEM, KERALA

The studies were conducted in nine stations with varying ecological characteristics along Cochin backwaters and adjoining canals. Many workers opined that the distribution of rotifers is cosmopolitan. The significance of rotifers as first food for early larvae was indicated by Fujita. Aquaculture is a fast growing field in fisheries sector and it is gaining more importance as the fish landings and supply are getting irregular. A consistent supply of fish/shellfish can only be achieved through aquaculture. The success of any culture activity depends on the timely production of seeds of finfishes/shellfishes. The availability of wild seed is seasonal and erratic. So, a dependable source of seed of fishes and shellfishes is possible only through large scale production in hatchery. A successful seed production activity depends on the availability of a variety of suitable live feed organisms in sufficient quantities at the proper time for use in the larval stages. As the live feeds promote high growth rates, easy digestion, assimilation and the quality of not contaminating the culture water when compared to other artificial feeds, make the culture of live feed organisms the principal means of providing food for the larvae of finfishes and shellfishes. Rotifers are considered to be an excellent and indispensable food for larvae of many finfishes and crustaceans. It (1960) was the first to culture Brachionus plicatilis for feeding marine fish larvae, and now it is being extensively used as live feed in hatcheries all over the world. They are a group of microscopic organisms coming under the Phylum Rotifera which comprises of about 2000 species. Their slow swimming habits, ability to tolerate a wide range of salinities, parthenogenetic mode of reproduction and ability to get enriched easily, make rotifers an ideal live feed organism. The major factors such as temperature, salinity and food that influence the reproductive potential and thereby the population size of rotifer, Salinity is one of the most important aspect influencing the reproductive rate of rotifers. The feed type and feed concentration play a vital role in influencing the reproductive rate of rotifers. For culture of rotifers, the commonly used micro algae belong to Chlorella, Nannochloropsis, Isochrysis and Tetraselmis. While some studies have suggested that, algal diet has little effect on reproductive rates in 1979 while using the rotifer, Brachionus plicatilis as feed for the larvae of red sea bream, Pagrus major. It is generally accepted that rotifers play a pivotal role in the successful rearing of marine fish larvae.

INDIAN AND ANTARCTIC BRYOZOANS - TAXONOMY AND OBSERVATIONS ON TOXICOLOGY

This thesis embodies findings on a taxonomical investigation of a group of lower marine invertebrates belonging to the category coelomata. Bryozoans are well known both in fossil and recent taxonomical history. They comprise of about 5,000 living and 16000 fossil species. Bryozoans are well known for their taxonomic abundance and structural diversity,representing the various ecological niches ranging from the intertidal to the abyssal benthic. At a time when global marine biological diversity has become a concern of not only to the scientists but also to the policy makers,an understanding of species diversity and abundance are cardinal aspects of biological studies. Geological time scales which is known that by Pre-Cambrian, marine invertebrate diversity reach the maximum and this diversity has become more comprehensive as time advanced. Taxonomists a vanishing species of scientists have become more concerned in discerning patterns of species diversity. The basic tool for this is identification fo animals. with this idea in mind a detailed study of taxonomy of bryozoan was undertaken . The major part of this thesis is devoted to describe various species of bryozoans with detailed description and ecotypical variations.The pattern of distribution and abundance which are important aspects of animal groups have also been documented. Possible effects of heavy metal contamination on the tolerance and growth of bryozoans, a few species of which have been eliminated from the chronically polluted areas of Cochin backwaters have also been documented.

Studies on taxonomy and ecology of Mysidacea from the EEZ of India

Members of the order Mysidacea are important component in marine and estuarine plankton inhabiting all regions of the oceans. There are many brackish water species and few species occur in fresh water, some have become adapted to the specialized environments of caves and wells. They are omnivores, responsible for remineralisation of a substantial portion of the detritus in the water column. They form an important link in the food chain (between microbial producers and secondary consumers) and therefore play a major role in the cycling of energy within the aquatic ecosystem. In tropical and subtropical waters, swarms of mysids are exploited commercially and marketed as preserved cooked food. Mysids have been used in fish farming as live feed resource. They are also excellent experimental organism, extremely useful in the studies of potential impact of various pollutants in the aquatic environment. Mysids are also used in wood pulp effluent plants.Considering the significant role of mysids in the productivity of tropical and coastal ecosystems,the present study has been undertaken to extend our knowledge on the systematics, species composition, distribution,abundance and ecology of mysid fauna of the Indian EEZ and adjoining areas. The present study therefore will undoubtedly fumish valuable information on Mysidacea of the Indian waters.

Studies on the taxonomy of interstitial Fauna of some prominent beaches of Kerala

The oceans in their expanse cover, seven - tenths of the Earth surface. Despite being restricted in size, the littoral zone or the intertidal zone (beach) has the greatest variation in environment factors of any marine area .Stemming from this variation ,a treamendous diversity of life, which may be great as or greater than that found in the more extensive sub tidal habits exist in this realm. the study beaches harbour diverse and abundant assemblage of marine organisms. Besides macro funna, microscopic organisms belonging to the lower and higher invertebrate taxa profusely inhabit these beaches. The ecological realm where these animals exist is known as the interstitial environment, which in principle includes the pore spaces in between the sand grains containing copious supply of nutrient rich oxygenated seawater. An astonishing diversity of taxa could be found within the interstitial fauna.

“Improved Feature Extraction and Classification Techniques for Multispectral Brain Magnetic Resonance Images”

Magnetic Resonance Imaging (MRI) is a multi sequence medical imaging technique in which stacks of images are acquired with different tissue contrasts. Simultaneous observation and quantitative analysis of normal brain tissues and small abnormalities from these large numbers of different sequences is a great challenge in clinical applications. Multispectral MRI analysis can simplify the job considerably by combining unlimited number of available co-registered sequences in a single suite. However, poor performance of the multispectral system with conventional image classification and segmentation methods makes it inappropriate for clinical analysis. Recent works in multispectral brain MRI analysis attempted to resolve this issue by improved feature extraction approaches, such as transform based methods, fuzzy approaches, algebraic techniques and so forth. Transform based feature extraction methods like Independent Component Analysis (ICA) and its extensions have been effectively used in recent studies to improve the performance of multispectral brain MRI analysis. However, these global transforms were found to be inefficient and inconsistent in identifying less frequently occurred features like small lesions, from large amount of MR data. The present thesis focuses on the improvement in ICA based feature extraction techniques to enhance the performance of multispectral brain MRI analysis. Methods using spectral clustering and wavelet transforms are proposed to resolve the inefficiency of ICA in identifying small abnormalities, and problems due to ICA over-completeness. Effectiveness of the new methods in brain tissue classification and segmentation is confirmed by a detailed quantitative and qualitative analysis with synthetic and clinical, normal and abnormal, data. In comparison to conventional classification techniques, proposed algorithms provide better performance in classification of normal brain tissues and significant small abnormalities.

Feature Extraction Methods Based on Linear Predictive Coding and Wavelet Packet Decomposition for Recognizing Spoken Words in Malayalam

Speech signals are one of the most important means of communication among the human beings. In this paper, a comparative study of two feature extraction techniques are carried out for recognizing speaker independent spoken isolated words. First one is a hybrid approach with Linear Predictive Coding (LPC) and Artificial Neural Networks (ANN) and the second method uses a combination of Wavelet Packet Decomposition (WPD) and Artificial Neural Networks. Voice signals are sampled directly from the microphone and then they are processed using these two techniques for extracting the features. Words from Malayalam, one of the four major Dravidian languages of southern India are chosen for recognition. Training, testing and pattern recognition are performed using Artificial Neural Networks. Back propagation method is used to train the ANN. The proposed method is implemented for 50 speakers uttering 20 isolated words each. Both the methods produce good recognition accuracy. But Wavelet Packet Decomposition is found to be more suitable for recognizing speech because of its multi-resolution characteristics and efficient time frequency localizations

Effectiveness Of Feature Detection Operators On The Performance Of Iris Biometric Recognition System

Iris Recognition is a highly efficient biometric identification system with great possibilities for future in the security systems area.Its robustness and unobtrusiveness, as opposed tomost of the currently deployed systems, make it a good candidate to replace most of thesecurity systems around. By making use of the distinctiveness of iris patterns, iris recognition systems obtain a unique mapping for each person. Identification of this person is possible by applying appropriate matching algorithm.In this paper, Daugman’s Rubber Sheet model is employed for irisnormalization and unwrapping, descriptive statistical analysis of different feature detection operators is performed, features extracted is encoded using Haar wavelets and for classification hammingdistance as a matching algorithm is used. The system was tested on the UBIRIS database. The edge detection algorithm, Canny, is found to be the best one to extract most of the iris texture. The success rate of feature detection using canny is 81%, False Accept Rate is 9% and False Reject Rate is 10%.

COMBINED FEATURE EXTRACTION TECHNIQUES AND NAIVE BAYES CLASSIFIER FOR SPEECH RECOGNITION

Speech processing and consequent recognition are important areas of Digital Signal Processing since speech allows people to communicate more natu-rally and efficiently. In this work, a speech recognition system is developed for re-cognizing digits in Malayalam. For recognizing speech, features are to be ex-tracted from speech and hence feature extraction method plays an important role in speech recognition. Here, front end processing for extracting the features is per-formed using two wavelet based methods namely Discrete Wavelet Transforms (DWT) and Wavelet Packet Decomposition (WPD). Naive Bayes classifier is used for classification purpose. After classification using Naive Bayes classifier, DWT produced a recognition accuracy of 83.5% and WPD produced an accuracy of 80.7%. This paper is intended to devise a new feature extraction method which produces improvements in the recognition accuracy. So, a new method called Dis-crete Wavelet Packet Decomposition (DWPD) is introduced which utilizes the hy-brid features of both DWT and WPD. The performance of this new approach is evaluated and it produced an improved recognition accuracy of 86.2% along with Naive Bayes classifier.

A Comparative Study of Wavelet Based Feature Extraction Techniques in Recognizing Isolated Spoken Words

Speech is a natural mode of communication for people and speech recognition is an intensive area of research due to its versatile applications. This paper presents a comparative study of various feature extraction methods based on wavelets for recognizing isolated spoken words. Isolated words from Malayalam, one of the four major Dravidian languages of southern India are chosen for recognition. This work includes two speech recognition methods. First one is a hybrid approach with Discrete Wavelet Transforms and Artificial Neural Networks and the second method uses a combination of Wavelet Packet Decomposition and Artificial Neural Networks. Features are extracted by using Discrete Wavelet Transforms (DWT) and Wavelet Packet Decomposition (WPD). Training, testing and pattern recognition are performed using Artificial Neural Networks (ANN). The proposed method is implemented for 50 speakers uttering 20 isolated words each. The experimental results obtained show the efficiency of these techniques in recognizing speech

FEATURE SELECTION AND COMPARISON OF TWO NAÏVE BAYES CLASSIFICATION METHODS IN THE CONTEXT OF SPAM FILTERING

Treating e-mail filtering as a binary text classification problem, researchers have applied several statistical learning algorithms to email corpora with promising results. This paper examines the performance of a Naive Bayes classifier using different approaches to feature selection and tokenization on different email corpora

Multifinger Feature Level Fusion Based Fingerprint Identification

Fingerprint based authentication systems are one of the cost-effective biometric authentication techniques employed for personal identification. As the data base population increases, fast identification/recognition algorithms are required with high accuracy. Accuracy can be increased using multimodal evidences collected by multiple biometric traits. In this work, consecutive fingerprint images are taken, global singularities are located using directional field strength and their local orientation vector is formulated with respect to the base line of the finger. Feature level fusion is carried out and a 32 element feature template is obtained. A matching score is formulated for the identification and 100% accuracy was obtained for a database of 300 persons. The polygonal feature vector helps to reduce the size of the feature database from the present 70-100 minutiae features to just 32 features and also a lower matching threshold can be fixed compared to single finger based identification

Population characteristics and taxonomy of lantern fishes of genus Diaphus (Family Myctophidae) off south west coast of India

Globally most of the conventional fish stocks have reached a state of optimum exploitation or even over-exploitation; efficient utilization of non-conventional resources is necessary to meet the supply-demand gap for protein supply. Mesopelagic fishes can be considered as one such promising resource for the future, if appropriate harvest and post-harvest technologies are developed. Increasing human population and increasing demand for cheaper food fishes has made myctophids a possible potential resource for future exploitation and utilization. Earlier studies indicated the abundance of Diaphus spp. in the eastern and northeastern Arabian Sea. The present study also indicates the dominance of Diaphus spp. in the deep sea trawling grounds of south west coast of India. Commercial viability of the myctophid fishing in the Indian waters has to be worked out. The present catch estimation is based on the Stratified Random Sampling Method from the landing data. As the coverage of sampling area was limited and the gear efficiency was not standardized, the data generated are not precise. A counter check for the estimates is also not possible due to the absence of comparable works in the study area. Fish biomass estimation by acoustics survey coupled with direct fishing would only confirm the accuracy of estimates. Exploratory surveys for new fishing areas to be continued, for gathering the distribution, abundance, biological and ecological data and map the potential fishing ground on a GIS platform and the data should be provided to the commercial entrepreneurs. Generally non-conventional and non-targeted resources are under low fishing pressure and exploitation rates. Low values of fishing mortality and exploitation rates indicate that removal from the stock by fishing was only nominal from the present fishing grounds. The results indicate that the stock is almost at virgin state and remains grossly underexploited. Since the extent of distribution and abundance of the stock in the ecosystem remains to be ascertained, sustainable yield could not be estimated. Also the impact of myctophids harvest, on other commercially important fishes, has to be studied.

Molecular Taxonomy of Deep Sea Fishes Off the southern coast of India

CMFRI,