Computing median and antimedian sets in median graphs

The median (antimedian) set of a profile π = (u1, . . . , uk) of vertices of a graphG is the set of vertices x that minimize (maximize) the remoteness i d(x,ui ). Two algorithms for median graphs G of complexity O(nidim(G)) are designed, where n is the order and idim(G) the isometric dimension of G. The first algorithm computes median sets of profiles and will be in practice often faster than the other algorithm which in addition computes antimedian sets and remoteness functions and works in all partial cubes

Studies on the prevalence of algal blooms along Kerala coast, India

Algal blooms are naturally occurring phenomena in the aquatic environment. These blooms cause mass mortalities of wild and farmed fish and shellfish, human intoxications which sometimes result in death, alteration of marine trophic structure through adverse effects on larvae and other life history stages of commercially important species and death of marine animals. Occurrences of harmful algal blooms and associated mortality have been reported along the coastal waters of India since the early period of the last century. The present study was taken up to study the dynamics of major phytoplankton blooms, which occur along the Kerala coast. The results of quantitative and qualitative analysis of phytoplankton in the coastal waters of Vizhinjam and Chombala, their species diversity and community structure is presented and the major algal blooms recorded along the coast of Kerala during the study period is described and their occurrence is related to the hydrographic and meteorological variations. There is a clear evident from these works in the Indian region that the fishes avoid areas where these harmful algae bloom, either due to the toxicity or due to some irritant property of the chemicals secreted by the algae. Taxonomic diversity studies indicated a change in the community structure of commercial finfishes, crustaceans and molluscs due to the bloom of C.marina and funnel plots indicated the deviation in taxonomic distinctness during the bloom period from theoretical mean for the region.

Queueing Theory And Other Applications Of Stochastic Processes Queueing And Inventory Models With Rest Periods

In this thesis we study the effect of rest periods in queueing systems without exhaustive service and inventory systems with rest to the server. Most of the works in the vacation models deal with exhaustive service. Recently some results have appeared for the systems without exhaustive service.

“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.

Evolution of Better Wavelet Coefficients for Fingerprint Image Compression using cropped images

This paper explains the Genetic Algorithm (GA) evolution of optimized wavelet that surpass the cdf9/7 wavelet for fingerprint compression and reconstruction. Optimized wavelets have already been evolved in previous works in the literature, but they are highly computationally complex and time consuming. Therefore, in this work, a simple approach is made to reduce the computational complexity of the evolution algorithm. A training image set comprised of three 32x32 size cropped images performed much better than the reported coefficients in literature. An average improvement of 1.0059 dB in PSNR above the classical cdf9/7 wavelet over the 80 fingerprint images was achieved. In addition, the computational speed was increased by 90.18 %. The evolved coefficients for compression ratio (CR) 16:1 yielded better average PSNR for other CRs also. Improvement in average PSNR was experienced for degraded and noisy images as well

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.