Women Industrial Cooperatives- An Analysis of Its Structure, Performance and Growth in Kannur District

In the present study made an attempt to analyse the structure, performance and growth of women industrial cooperatives in kannur district, Kerala. The study encompasses all women industrial cooperatives registered at the district industries center, kannur and that currently exist. The women industrial cooperatives are classified into two ie; group with network and another group without network. In Kannur there are 54 units working as women industrial cooperatives. One of the main problems the women cooperatives face is the lack of working capital followed marketing problem. The competition between cooperatives and private traders is very high. The variables examined to analyse the performance of women industrial cooperatives in Kannur showed that there exists inter unit differences in almost all the variables. The financial structure structure shows that the short term liquidity of women cooperatives in Kannur favour more the units which have political networks; but the long term financial coverage is seen to be highly geared in this group, not because of a decline is net worth but due to highly proportionate increase in financial liabilities in the form of borrowings. The encouragement given by the government through financial stake and other incentives has been the major factor in the formation and growth of women cooperatives. As a result both productivity and efficiency improves in the cooperatives. In short the present study helped to capture the impact, role and dynamics of networking in general and socio political network in particular in relation to intra and inter unit differences on the structure, growth and performance of women industrial cooperatives societies in Kannur district

"Statistical Methods in Gear Selectivity and Gear Efficiency Studies”

The preceding discussion and review of literature show that studies on gear selectivity have received great attention, while gear efficiency studies do not seem to have received equal consideration. In temperate waters, fishing industry is well organised and relatively large and well equipped vessels and gear are used for commercial fishing and the number of species are less; whereas in tropics particularly in India, small scale fishery dominates the scene and the fishery is multispecies operated upon by nmltigear. Therefore many of the problems faced in India may not exist in developed countries. Perhaps this would be the reason for the paucity of literature on the problems in estimation of relative efficiency. Much work has been carried out in estimating relative efficiency (Pycha, 1962; Pope, 1963; Gulland, 1967; Dickson, 1971 and Collins, 1979). The main subject of interest in the present thesis is an investigation into the problems in the comparison of fishing gears. especially in using classical test procedures with special reference to the prevailing fishing practices (that is. with reference to the catch data generated by the existing system). This has been taken up with a view to standardizing an approach for comparing the efficiency of fishing gear. Besides this, the implications of the terms ‘gear efficiency‘ and ‘gear selectivity‘ have been examined and based on the commonly used selectivity model (Holt, 1963), estimation of the ratio of fishing power of two gear has been considered. An attempt to determine the size of fish for which a gear is most efficient.has also been made. The work has been presented in eight chapters

Offline Handwritten Malayalam Character Recognition Based on Chain Code Histogram

Optical Character Recognition plays an important role in Digital Image Processing and Pattern Recognition. Even though ambient study had been performed on foreign languages like Chinese and Japanese, effort on Indian script is still immature. OCR in Malayalam language is more complex as it is enriched with largest number of characters among all Indian languages. The challenge of recognition of characters is even high in handwritten domain, due to the varying writing style of each individual. In this paper we propose a system for recognition of offline handwritten Malayalam vowels. The proposed method uses Chain code and Image Centroid for the purpose of extracting features and a two layer feed forward network with scaled conjugate gradient for classification