Inter- State Variations in Productivity trends and Technological Change in Indian industry

The present study entitled ‘Inter-State Variations in Manufacturing Productivity and Technological Changes in India’ covers a period of 38 years from l960 tol998-99. The study is mainly based on ASI data. The study starts with a discussion of the major facilitating factors of industrialization, namely, historical forces, public policy and infrastructure facilities. These are discussed in greater details in the context of our discussion on Perrox’s (1998) ‘growth pole’ and ‘development pole’, Hirschman’s (1958) ‘industrial centers’ and Myrdal’s ‘spread effect’ Most of the existing literature more or less agrees that the process of industrialization has not been unifonn in all Indian states. There has been a decline in inter-state industrial disparities over time. This aspect is dealt at some length in the third chapter. An important element that deserves detailed attention is the intra-regional differences in industrialisation. Regional industrialisation implies the emergence of a few focal points and industrial regions. Calcutta, Bombay and Madras were the initial focal points. Later other centers like Bangalore, Amritsar, Ahemedabad etc. emerged as nodal points in other states. All major states account for focal points. The analysis made in the third chapter shows that industrial activities generally converge to one or two focal points and industrial regions have emerged out of the focal points in almost all states. One of the general features of these complexes and regions is that they approximately accommodate 50 to 75 percent of the total industrial units and workers in the state. Such convergence is seen hands in glow with urbanization. It was further seen that intra-regional industrial disparity comes down in industrial states like Maharashtra, Gujarat and Uttar Pradesh.

Development of a Biometric Personal Authentication System Based on Fingerprint and Speech

Biometrics deals with the physiological and behavioral characteristics of an individual to establish identity. Fingerprint based authentication is the most advanced biometric authentication technology. The minutiae based fingerprint identification method offer reasonable identification rate. The feature minutiae map consists of about 70-100 minutia points and matching accuracy is dropping down while the size of database is growing up. Hence it is inevitable to make the size of the fingerprint feature code to be as smaller as possible so that identification may be much easier. In this research, a novel global singularity based fingerprint representation is proposed. Fingerprint baseline, which is the line between distal and intermediate phalangeal joint line in the fingerprint, is taken as the reference line. A polygon is formed with the singularities and the fingerprint baseline. The feature vectors are the polygonal angle, sides, area, type and the ridge counts in between the singularities. 100% recognition rate is achieved in this method. The method is compared with the conventional minutiae based recognition method in terms of computation time, receiver operator characteristics (ROC) and the feature vector length. Speech is a behavioural biometric modality and can be used for identification of a speaker. In this work, MFCC of text dependant speeches are computed and clustered using k-means algorithm. A backpropagation based Artificial Neural Network is trained to identify the clustered speech code. The performance of the neural network classifier is compared with the VQ based Euclidean minimum classifier. Biometric systems that use a single modality are usually affected by problems like noisy sensor data, non-universality and/or lack of distinctiveness of the biometric trait, unacceptable error rates, and spoof attacks. Multifinger feature level fusion based fingerprint recognition is developed and the performances are measured in terms of the ROC curve. Score level fusion of fingerprint and speech based recognition system is done and 100% accuracy is achieved for a considerable range of matching threshold

Temporal pattern of fish production in a microtidal tropical estuary in the south-west coast of India

The status of fisheries and seasonal variation in fish diversity in the Kodungallur-Azhikode Estuary (KAE) were investigated. Total annual average fish production in the estuary declined significantly to 908.6 t with average yield of 5.4 kg ha-1 day-1, when compared to earlier study; where 2747 t was reported. During the present study, 60 species of finfishes (belonging to 34 finfish families), 6 species of penaeid shrimps, 2 species of palaemonid prawns, 2 species of crabs (4 crustacean families), 6 species of bivalves and 2 species of edible oysters (3 molluscan families) were noticed. Finfishes were the major group that contributed 69.62% of total fishery in the estuary and crustaceans (23.47%), bivalves (6.84%) and oysters (0.07%) also formed good fishery. Many of the fish species in the estuary were observed as threatened (Horabagrus brachysoma, Channa striatus, Channa marulius, Clarias batrachus, Heteropneustes fossilis and Wallago attu). The major fishing gears employed in the estuary were gillnets, cast nets, stake nets, scoop nets, ring nets, traps and Chinese dip nets. Gillnets contributed 45% of the total fish catch. Gillnets also showed highest catch per unit effort (CPUE) of 6.91 kg h -1 followed by cast nets (1.85 kg h -1), Chinese dip nets (3.20 kg h -1), stake nets (3.05 kg h -1), ring nets (1.27 kg h -1), hooks and lines (1.35 kg h -1) and scoop nets (0.92 kg h -1). The study implies that temporal changes in fish landing pattern of the KAE was mainly due to environmental variability, habitat modification and fish migration; under the influence of south-west monsoon and anthropogenic activities in the KAE. Results of the study suggest that spatio-temporal variations in the fish community structure could be an indicator for anthropogenic stress and it should be considered for restoration programmes.