“Law on Transboundary Movement of Hazardous Substances through Sea

This study pertain to legal control of pollution from transboundary movement of hazardous substances through sea. It is an emerging area in international maritime law. There is growing environmental awareness that oceans are no longer an inexhaustible resource. This has resulted in a complex system of integrated ocean policies and international legal frame work in this regard. Considering the peculiar nature of hazardous substances, the development of law in this regard has been haphazard. The legal framework in this area is not comprehensive and lacks coherence. India is geo-strategically located in the central part of Indian Ocean through which many international sea routes lie. India is also fast emerging as a maritime hub. Indian legal framework in this respect also suffers from serious pitfalls. In this backdrop, this study makes a sincere attempt to identify and analyse the legal intricacies in this area, in order to evolve a better regime for control of pollution pursuant to transboundary movement of hazardous substances through sea

Some bivariate life time models in discrete time"

The term reliability of an equipment or device is often meant to indicate the probability that it carries out the functions expected of it adequately or without failure and within specified performance limits at a given age for a desired mission time when put to use under the designated application and operating environmental stress. A broad classification of the approaches employed in relation to reliability studies can be made as probabilistic and deterministic, where the main interest in the former is to device tools and methods to identify the random mechanism governing the failure process through a proper statistical frame work, while the latter addresses the question of finding the causes of failure and steps to reduce individual failures thereby enhancing reliability. In the probabilistic attitude to which the present study subscribes to, the concept of life distribution, a mathematical idealisation that describes the failure times, is fundamental and a basic question a reliability analyst has to settle is the form of the life distribution. It is for no other reason that a major share of the literature on the mathematical theory of reliability is focussed on methods of arriving at reasonable models of failure times and in showing the failure patterns that induce such models. The application of the methodology of life time distributions is not confined to the assesment of endurance of equipments and systems only, but ranges over a wide variety of scientific investigations where the word life time may not refer to the length of life in the literal sense, but can be concieved in its most general form as a non-negative random variable. Thus the tools developed in connection with modelling life time data have found applications in other areas of research such as actuarial science, engineering, biomedical sciences, economics, extreme value theory etc.

Open Access Movement for Managing Intellectual Informatics

The present work focuses on various facets of open access movement for managing intellectual output that eventually becomes available and accessible in public domain. Thus, purpose of this paper is to document and share the real time experience of managing and sharing of intellectual wealth of academia of Cochin University of Science & Technology by using open source platforms. This paper is trying to explore different intellectual information resources in the current era and also aims to suggest cost effective strategy of implementing new open access tools and technology for effective managing ofintellectual informatics

Detection of Flock Movement in Spatio-Temporal Database using Clustering Techniques - an Experience

In this paper, moving flock patterns are mined from spatio- temporal datasets by incorporating a clustering algorithm. A flock is defined as the set of data that move together for a certain continuous amount of time. Finding out moving flock patterns using clustering algorithms is a potential method to find out frequent patterns of movement in large trajectory datasets. In this approach, SPatial clusteRing algoRithm thrOugh sWarm intelligence (SPARROW) is the clustering algorithm used. The advantage of using SPARROW algorithm is that it can effectively discover clusters of widely varying sizes and shapes from large databases. Variations of the proposed method are addressed and also the experimental results show that the problem of scalability and duplicate pattern formation is addressed. This method also reduces the number of patterns produced

Discrete wavelet transform de-noising in eukaryotic gene splicing

This paper compares the most common digital signal processing methods of exon prediction in eukaryotes, and also proposes a technique for noise suppression in exon prediction. The specimen used here which has relevance in medical research, has been taken from the public genomic database - GenBank.Here exon prediction has been done using the digital signal processing methods viz. binary method, EIIP (electron-ion interaction psuedopotential) method and filter methods. Under filter method two filter designs, and two approaches using these two designs have been tried. The discrete wavelet transform has been used for de-noising of the exon plots.Results of exon prediction based on the methods mentioned above, which give values closest to the ones found in the NCBI database are given here. The exon plot de-noised using discrete wavelet transform is also given.Alterations to the proven methods as done by the authors, improves performance of exon prediction algorithms. Also it has been proven that the discrete wavelet transform is an effective tool for de-noising which can be used with exon prediction algorithms