4 resultados para Gray, Walter de, Archbishop of York, d. 1255.
em Cochin University of Science
Resumo:
The problem investigated is on the haematological aspects of two freshwater pulmonate snails, Indoplanorbis exustus (Deshayes),and Lymnaea acuminata f.rufescens (Gray). An important aspect of the present investigation is to emphasize the utilization of freshwater organisms as models for research directed at understanding the basic biomedical problems that remain unresolved. Another aspect is to demonstrate how haemolymph can be treated as a tissue because of late, it has been shown that several parameters of blood can be taken as reliable indicators for diagnostic purposes, and also to monitor environmental pollution. The various haematological parameters studied are total haemocyte number,packed cell volume, haemoglobin, and inorganic as well organic constituents in three size groups of both the snail species. The effect of copper toxicity was measured in terms of total haemocyte count, and the activity pattern of selected phosphatases and transaminases.The study concluded that enzyme activity levels can be taken as reliable indicators to monitor pollution. Age is a factor that determines several of the physiological, biochemical and metabolic activities. This study also indicates that haemolymph can be taken as an organ system to study the various changes taking place at organ systems levels.
Resumo:
Department of Physics, Cochin University of Science & Technology
Resumo:
The thesis explores the area of still image compression. The image compression techniques can be broadly classified into lossless and lossy compression. The most common lossy compression techniques are based on Transform coding, Vector Quantization and Fractals. Transform coding is the simplest of the above and generally employs reversible transforms like, DCT, DWT, etc. Mapped Real Transform (MRT) is an evolving integer transform, based on real additions alone. The present research work aims at developing new image compression techniques based on MRT. Most of the transform coding techniques employ fixed block size image segmentation, usually 8×8. Hence, a fixed block size transform coding is implemented using MRT and the merits and demerits are analyzed for both 8×8 and 4×4 blocks. The N2 unique MRT coefficients, for each block, are computed using templates. Considering the merits and demerits of fixed block size transform coding techniques, a hybrid form of these techniques is implemented to improve the performance of compression. The performance of the hybrid coder is found to be better compared to the fixed block size coders. Thus, if the block size is made adaptive, the performance can be further improved. In adaptive block size coding, the block size may vary from the size of the image to 2×2. Hence, the computation of MRT using templates is impractical due to memory requirements. So, an adaptive transform coder based on Unique MRT (UMRT), a compact form of MRT, is implemented to get better performance in terms of PSNR and HVS The suitability of MRT in vector quantization of images is then experimented. The UMRT based Classified Vector Quantization (CVQ) is implemented subsequently. The edges in the images are identified and classified by employing a UMRT based criteria. Based on the above experiments, a new technique named “MRT based Adaptive Transform Coder with Classified Vector Quantization (MATC-CVQ)”is developed. Its performance is evaluated and compared against existing techniques. A comparison with standard JPEG & the well-known Shapiro’s Embedded Zero-tree Wavelet (EZW) is done and found that the proposed technique gives better performance for majority of images
Resumo:
This thesis is an outcome of the investigations carried out on the development of an Artificial Neural Network (ANN) model to implement 2-D DFT at high speed. A new definition of 2-D DFT relation is presented. This new definition enables DFT computation organized in stages involving only real addition except at the final stage of computation. The number of stages is always fixed at 4. Two different strategies are proposed. 1) A visual representation of 2-D DFT coefficients. 2) A neural network approach. The visual representation scheme can be used to compute, analyze and manipulate 2D signals such as images in the frequency domain in terms of symbols derived from 2x2 DFT. This, in turn, can be represented in terms of real data. This approach can help analyze signals in the frequency domain even without computing the DFT coefficients. A hierarchical neural network model is developed to implement 2-D DFT. Presently, this model is capable of implementing 2-D DFT for a particular order N such that ((N))4 = 2. The model can be developed into one that can implement the 2-D DFT for any order N upto a set maximum limited by the hardware constraints. The reported method shows a potential in implementing the 2-D DF T in hardware as a VLSI / ASIC