Constraining the active tectonic deformation of Andaman-Nicobar Arc in the background of December 26,2004 Great Sumatra-Andaman Earthquake

The Andaman-Nicobar Islands in the Bay of Bengal lies in a zone where the Indian plate subducts beneath the Burmese microplate, and therefore forms a belt of frequent earthquakes. Few efforts, not withstanding the available historical and instrumental data were not effectively used before the Mw 9.3 Sumatra-Andaman earthquake to draw any inference on the spatial and temporal distribution of large subduction zone earthquakes in this region. An attempt to constrain the active crustal deformation of the Andaman-Nicobar arc in the background of the December 26, 2004 Great Sumatra-Andaman megathrust earthquake is made here, thereby presenting a unique data set representing the pre-seismic convergence and co-seismic displacement.Understanding the mechanisms of the subduction zone earthquakes is both challenging sCientifically and important for assessing the related earthquake hazards. In many subduction zones, thrust earthquakes may have characteristic patterns in space and time. However, the mechanism of mega events still remains largely unresolved.Large subduction zone earthquakes are usually associated with high amplitude co-seismic deformation above the plate boundary megathrust and the elastic relaxation of the fore-arc. These are expressed as vertical changes in land level with the up-dip part of the rupture surface uplifted and the areas above the down-dip edge subsided. One of the most characteristic pattern associated with the inter-seismic era is that the deformation is in an opposite sense that of co-seismic period.This work was started in 2002 to understand the tectonic deformation along the Andaman-Nicobar arc using seismological, geological and geodetic data. The occurrence of the 2004 megathrust earthquake gave a new dimension to this study, by providing an opportunity to examine the co-seismic deformation associated with the greatest earthquake to have occurred since the advent of Global Positioning System (GPS) and broadband seismometry. The major objectives of this study are to assess the pre-seismic stress regimes, to determine the pre-seismic convergence rate, to analyze and interpret the pattern of co-seismic displacement and slip on various segments and to look out for any possible recurrence interval for megathrust event occurrence for Andaman-Nicobar subduction zone. This thesis is arranged in six chapters with further subdivisions dealing all the above aspects.

“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.

CRITICAL WORKS or ACHARYA NANDADULARE VAJPAI

HINDI

An Analytical Study of the Works of Vijayadev Narayan Sahi

HINDI

A STUDY OF THE ELEMENTS OF ALIENATION IN THE WORKS OF MOHAN RAKESH

Hindi

AN ANQYTICAL STUDY OF THE SUKTIS IN THE COMPLETE WORKS OF TULSIDAS

HINDI

A STUDY OF THE MYTHICAL AND ARCHETYPAL ELEMENTS IN THE PDETICAL WORKS DF AJNEYA IN THE LIGHT OF THE THEORY PRDPDUNDED BY JUNG

Hindi

PREDOMINANT FEATURES OF THE POETICAL WORKS OF HARIBANSRAI BACCHAN

HINDI

CONCEPT OF POETRY IN THE WORKS OF MODERN HINDI POETS

HINDI