“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

k-NN based On-Line Handwritten Character recognition system

On-line handwriting recognition has been a frontier area of research for the last few decades under the purview of pattern recognition. Word processing turns to be a vexing experience even if it is with the assistance of an alphanumeric keyboard in Indian languages. A natural solution for this problem is offered through online character recognition. There is abundant literature on the handwriting recognition of western, Chinese and Japanese scripts, but there are very few related to the recognition of Indic script such as Malayalam. This paper presents an efficient Online Handwritten character Recognition System for Malayalam Characters (OHR-M) using K-NN algorithm. It would help in recognizing Malayalam text entered using pen-like devices. A novel feature extraction method, a combination of time domain features and dynamic representation of writing direction along with its curvature is used for recognizing Malayalam characters. This writer independent system gives an excellent accuracy of 98.125% with recognition time of 15-30 milliseconds

On-Line Handwritten Character Recognition using Kohonen Networks

This paper presents an efficient Online Handwritten character Recognition System for Malayalam Characters (OHR-M) using Kohonen network. It would help in recognizing Malayalam text entered using pen-like devices. It will be more natural and efficient way for users to enter text using a pen than keyboard and mouse. To identify the difference between similar characters in Malayalam a novel feature extraction method has been adopted-a combination of context bitmap and normalized (x, y) coordinates. The system reported an accuracy of 88.75% which is writer independent with a recognition time of 15-32 milliseconds