Ecotoxic Metal Records and its Degree of Geochemical Symphony in the Niche of Cochin Estuarine System- A Theraptic Perspective

The heavy metal contamination in the environment may lead to circumstances like bioaccumulation and inturn biomagnification. Hence cheaper and effective technologies are needed to protect the precious natural resources and biological lives. A suitable technique is the one which meets the technical and environmental criteria for dealing with a particular remediation problem and should be site-specific due to spatial and climatic variations and it may not economically feasible everywhere. The search for newer technologies for the environmental therapy, involving the removal of toxic metals from wastewaters has directed attention to adsorption, based on metal binding capacities of various adsorbent materials. Therefore, the present study aim to identify and evaluate the most current mathematical formulations describing sorption processes. Although vast amount of research has been carried out in the area of metal removal by adsorption process using activated carbon few specific research data are available in different scientific institutions. The present work highlights the seasonal and spatial variations in the distribution of some selected heavy metals among various geochemical phases of Cochin Estuarine system and also looked into an environmental theraptic/remedial approach by adsorption technique using activated charcoal and chitosan, to reduce and thereby controlling metallic pollution. The thesis has been addressed in seven chapters with further subdivisions. The first chapter is introductory, stating the necessity of reducing or preventing water pollution due to the hazardous impact on environment and health of living organisms and drawing it from a careful review of literature relevant to the present study. It provides a constricted description about the study area, geology, and general hydrology and also bears the major objectives and scope of the present study.

Development of a Biometric Personal Authentication System Based on Fingerprint and Speech

Biometrics deals with the physiological and behavioral characteristics of an individual to establish identity. Fingerprint based authentication is the most advanced biometric authentication technology. The minutiae based fingerprint identification method offer reasonable identification rate. The feature minutiae map consists of about 70-100 minutia points and matching accuracy is dropping down while the size of database is growing up. Hence it is inevitable to make the size of the fingerprint feature code to be as smaller as possible so that identification may be much easier. In this research, a novel global singularity based fingerprint representation is proposed. Fingerprint baseline, which is the line between distal and intermediate phalangeal joint line in the fingerprint, is taken as the reference line. A polygon is formed with the singularities and the fingerprint baseline. The feature vectors are the polygonal angle, sides, area, type and the ridge counts in between the singularities. 100% recognition rate is achieved in this method. The method is compared with the conventional minutiae based recognition method in terms of computation time, receiver operator characteristics (ROC) and the feature vector length. Speech is a behavioural biometric modality and can be used for identification of a speaker. In this work, MFCC of text dependant speeches are computed and clustered using k-means algorithm. A backpropagation based Artificial Neural Network is trained to identify the clustered speech code. The performance of the neural network classifier is compared with the VQ based Euclidean minimum classifier. Biometric systems that use a single modality are usually affected by problems like noisy sensor data, non-universality and/or lack of distinctiveness of the biometric trait, unacceptable error rates, and spoof attacks. Multifinger feature level fusion based fingerprint recognition is developed and the performances are measured in terms of the ROC curve. Score level fusion of fingerprint and speech based recognition system is done and 100% accuracy is achieved for a considerable range of matching threshold

New accelerator system for low temperature curing of elastomers with special reference to NR, NBR and NR/BR blends

The primary objective of this work is to develop an efficient accelerator system for low temperature vulcanization of rubbers. Although xanthates are known to act as accelerators for low temperature vulcanization, a systematic study on the mechanism of vulcanization, the mechanical properties of the vulcanizates at varying temperatures of vulcanization, cure characteristics etc are not reported. Further. xanthate based curing systems are not commonly used because of their chance for premature vulcanization during processing. The proposed study is to develop a novel accelerator system for the low temperature vulcanization of rubbers having enough processing safely. lt is also proposed to develop a method for the prevulcanisation of natural rubber latex at room temperature. As already mentioned the manufacture of rubber products at low temperature will improve its quality and appearance. Also, energy consumption can be reduced by low temperature vulcanization. in addition, low temperature vulcanization will be extremely useful in the area of repair of defective products, since subjecting finished products to high temperatures during the process of repair will adversely affect the quality of the product. Further. room temperature curing accelerator systems will find extensive applications in surface coating industries.

Development of solar air heaters & thermal energy storage system for drying applications in food processing industries

In the present work, the author has designed and developed all types of solar air heaters called porous and nonporous collectors. The developed solar air heaters were subjected to different air mass flow rates in order to standardize the flow per unit area of the collector. Much attention was given to investigate the performance of the solar air heaters fitted with baffles. The output obtained from the experiments on pilot models, helped the installation of solar air heating system for industrial drying applications also. Apart from these, various types of solar dryers, for small and medium scale drying applications, were also built up. The feasibility of ‘latent heat thermal energy storage system’ based on Phase Change Material was also undertaken. The application of solar greenhouse for drying industrial effluent was analyzed in the present study and a solar greenhouse was developed. The effectiveness of Computational Fluid Dynamics (CFD) in the field of solar air heaters was also analyzed. The thesis is divided into eight chapters.

Design And Development Of A Named Entity Based Question Answering System For Malayalam Language

This is a Named Entity Based Question Answering System for Malayalam Language. Although a vast amount of information is available today in digital form, no effective information access mechanism exists to provide humans with convenient information access. Information Retrieval and Question Answering systems are the two mechanisms available now for information access. Information systems typically return a long list of documents in response to a user’s query which are to be skimmed by the user to determine whether they contain an answer. But a Question Answering System allows the user to state his/her information need as a natural language question and receives most appropriate answer in a word or a sentence or a paragraph. This system is based on Named Entity Tagging and Question Classification. Document tagging extracts useful information from the documents which will be used in finding the answer to the question. Question Classification extracts useful information from the question to determine the type of the question and the way in which the question is to be answered. Various Machine Learning methods are used to tag the documents. Rule-Based Approach is used for Question Classification. Malayalam belongs to the Dravidian family of languages and is one of the four major languages of this family. It is one of the 22 Scheduled Languages of India with official language status in the state of Kerala. It is spoken by 40 million people. Malayalam is a morphologically rich agglutinative language and relatively of free word order. Also Malayalam has a productive morphology that allows the creation of complex words which are often highly ambiguous. Document tagging tools such as Parts-of-Speech Tagger, Phrase Chunker, Named Entity Tagger, and Compound Word Splitter are developed as a part of this research work. No such tools were available for Malayalam language. Finite State Transducer, High Order Conditional Random Field, Artificial Immunity System Principles, and Support Vector Machines are the techniques used for the design of these document preprocessing tools. This research work describes how the Named Entity is used to represent the documents. Single sentence questions are used to test the system. Overall Precision and Recall obtained are 88.5% and 85.9% respectively. This work can be extended in several directions. The coverage of non-factoid questions can be increased and also it can be extended to include open domain applications. Reference Resolution and Word Sense Disambiguation techniques are suggested as the future enhancements

Numerical Simulation of Two-Part Underwater Towing System

The motion instability is an important issue that occurs during the operation of towed underwater vehicles (TUV), which considerably affects the accuracy of high precision acoustic instrumentations housed inside the same. Out of the various parameters responsible for this, the disturbances from the tow-ship are the most significant one. The present study focus on the motion dynamics of an underwater towing system with ship induced disturbances as the input. The study focus on an innovative system called two-part towing. The methodology involves numerical modeling of the tow system, which consists of modeling of the tow-cables and vehicles formulation. Previous study in this direction used a segmental approach for the modeling of the cable. Even though, the model was successful in predicting the heave response of the tow-body, instabilities were observed in the numerical solution. The present study devises a simple approach called lumped mass spring model (LMSM) for the cable formulation. In this work, the traditional LMSM has been modified in two ways. First, by implementing advanced time integration procedures and secondly, use of a modified beam model which uses only translational degrees of freedoms for solving beam equation. A number of time integration procedures, such as Euler, Houbolt, Newmark and HHT-α were implemented in the traditional LMSM and the strength and weakness of each scheme were numerically estimated. In most of the previous studies, hydrodynamic forces acting on the tow-system such as drag and lift etc. are approximated as analytical expression of velocities. This approach restricts these models to use simple cylindrical shaped towed bodies and may not be applicable modern tow systems which are diversed in shape and complexity. Hence, this particular study, hydrodynamic parameters such as drag and lift of the tow-system are estimated using CFD techniques. To achieve this, a RANS based CFD code has been developed. Further, a new convection interpolation scheme for CFD simulation, called BNCUS, which is blend of cell based and node based formulation, was proposed in the study and numerically tested. To account for the fact that simulation takes considerable time in solving fluid dynamic equations, a dedicated parallel computing setup has been developed. Two types of computational parallelisms are explored in the current study, viz; the model for shared memory processors and distributed memory processors. In the present study, shared memory model was used for structural dynamic analysis of towing system, distributed memory one was devised in solving fluid dynamic equations.

Design and Development of a Frame Based MT System for English-to-ISL

This paper presents the design and development of a frame based approach for speech to sign language machine translation system in the domain of railways and banking. This work aims to utilize the capability of Artificial intelligence for the improvement of physically challenged, deaf-mute people. Our work concentrates on the sign language used by the deaf community of Indian subcontinent which is called Indian Sign Language (ISL). Input to the system is the clerk’s speech and the output of this system is a 3D virtual human character playing the signs for the uttered phrases. The system builds up 3D animation from pre-recorded motion capture data. Our work proposes to build a Malayalam to ISL

Intelligent Agent-based Multilingual Information Retrieval System

The goal of this work is to develop an Open Agent Architecture for Multilingual information retrieval from Relational Database. The query for information retrieval can be given in plain Hindi or Malayalam; two prominent regional languages of India. The system supports distributed processing of user requests through collaborating agents. Natural language processing techniques are used for meaning extraction from the plain query and information is given back to the user in his/ her native language. The system architecture is designed in a structured way so that it can be adapted to other regional languages of India

An Online Character Recognition System to Convert Grantha Script to Malayalam

This paper presents a novel approach to recognize Grantha, an ancient script in South India and converting it to Malayalam, a prevalent language in South India using online character recognition mechanism. The motivation behind this work owes its credit to (i) developing a mechanism to recognize Grantha script in this modern world and (ii) affirming the strong connection among Grantha and Malayalam. A framework for the recognition of Grantha script using online character recognition is designed and implemented. The features extracted from the Grantha script comprises mainly of time-domain features based on writing direction and curvature. The recognized characters are mapped to corresponding Malayalam characters. The framework was tested on a bed of medium length manuscripts containing 9-12 sample lines and printed pages of a book titled Soundarya Lahari writtenin Grantha by Sri Adi Shankara to recognize the words and sentences. The manuscript recognition rates with the system are for Grantha as 92.11%, Old Malayalam 90.82% and for new Malayalam script 89.56%. The recognition rates of pages of the printed book are for Grantha as 96.16%, Old Malayalam script 95.22% and new Malayalam script as 92.32% respectively. These results show the efficiency of the developed system

A Realization Of An Fpga Sub System For Reducing Odometric Localization Errors In Wheeled Mobile Robots

This paper introduces a simple and efficient method and its implementation in an FPGA for reducing the odometric localization errors caused by over count readings of an optical encoder based odometric system in a mobile robot due to wheel-slippage and terrain irregularities. The detection and correction is based on redundant encoder measurements. The method suggested relies on the fact that the wheel slippage or terrain irregularities cause more count readings from the encoder than what corresponds to the actual distance travelled by the vehicle. The standard quadrature technique is used to obtain four counts in each encoder period. In this work a three-wheeled mobile robot vehicle with one driving-steering wheel and two-fixed rear wheels in-axis, fitted with incremental optical encoders is considered. The CORDIC algorithm has been used for the computation of sine and cosine terms in the update equations. The results presented demonstrate the effectiveness of the technique

Core sediment biogeochemistry in specific zones of Cochin Estuarine System (CES)

Geochemical composition is a set of data for predicting the climatic condition existing in an ecosystem. Both the surficial and core sediment geochemistry are helpful in monitoring, assessing and evaluating the marine environment. The aim of the research work is to assess the relationship between the biogeochemical constituents in the Cochin Estuarine System (CES), their modifications after a long period of anoxia and also to identify the various processes which control the sediment composition in this region, through a multivariate statistical approach. Therefore the study of present core sediment geochemistry has a critical role in unraveling the benchmark of their characterization. Sediment cores from four prominent zones of CES were examined for various biogeochemical aspects. The results have served as rejuvenating records for the prediction of core sediment status prevailing in the CES

Design of a Knowledge-Based Geographic Information System

A GIS has been designed with limited Functionalities; but with a novel approach in Aits design. The spatial data model adopted in the design of KBGIS is the unlinked vector model. Each map entity is encoded separately in vector fonn, without referencing any of its neighbouring entities. Spatial relations, in other words, are not encoded. This approach is adequate for routine analysis of geographic data represented on a planar map, and their display (Pages 105-106). Even though spatial relations are not encoded explicitly, they can be extracted through the specially designed queries. This work was undertaken as an experiment to study the feasibility of developing a GIS using a knowledge base in place of a relational database. The source of input spatial data was accurate sheet maps that were manually digitised. Each identifiable geographic primitive was represented as a distinct object, with its spatial properties and attributes defined. Composite spatial objects, made up of primitive objects, were formulated, based on production rules defining such compositions. The facts and rules were then organised into a production system, using OPS5

Geochemical metal fractionation profile of the core sediment in the Cochin estuarine system

Geochemical composition is a set of data for predicting the climatic condition existing in an ecosystem. Both the surficial and core sediment geochemistry are helpful in monitoring, assessing and evaluating the marine environment. The aim of the research work is to assess the relationship between the biogeochemical constituents in the Cochin Estuarine System (CES), their modifications after a long period of anoxia and also to identify the various processes which control the sediment composition in this region, through a multivariate statistical approach. Therefore the study of present core sediment geochemistry has a critical role in unraveling the benchmark of their characterization. Sediment cores from four prominent zones of CES were examined for various biogeochemical aspects. The results have served as rejuvenating records for the prediction of core sediment status prevailing in the CES

Improved Biometric Authentication System Using Multimodal Cue Integration

Biometrics is an efficient technology with great possibilities in the area of security system development for official and commercial applications. The biometrics has recently become a significant part of any efficient person authentication solution. The advantage of using biometric traits is that they cannot be stolen, shared or even forgotten. The thesis addresses one of the emerging topics in Authentication System, viz., the implementation of Improved Biometric Authentication System using Multimodal Cue Integration, as the operator assisted identification turns out to be tedious, laborious and time consuming. In order to derive the best performance for the authentication system, an appropriate feature selection criteria has been evolved. It has been seen that the selection of too many features lead to the deterioration in the authentication performance and efficiency. In the work reported in this thesis, various judiciously chosen components of the biometric traits and their feature vectors are used for realizing the newly proposed Biometric Authentication System using Multimodal Cue Integration. The feature vectors so generated from the noisy biometric traits is compared with the feature vectors available in the knowledge base and the most matching pattern is identified for the purpose of user authentication. In an attempt to improve the success rate of the Feature Vector based authentication system, the proposed system has been augmented with the user dependent weighted fusion technique.