Wide research has been canied out and is still taking place in the field of character, recognition of handwritten English characters. Recognizing English characters is much simpler as there are only 26 letters and each letter is quite distinct from others compared to recognition of Indian language characters. Indian language characters have a base character along with vowels attached, forming single characters (raw characters). Origin of Kannada, a language of southern India, is as old as 5Ih century AD, The fonts have evolved over the centuries. The work involved is implemented in two phases. The first phase of the work incorporates an Artificial Neural Network for identifying the base character. The second phase consists of a Probabilistic Neural Network model designed for the identification of age pertaining to the base character. Characters dated from 3"' century BC to the present day are used for analysis and experimental results.

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This paper presents a prototype of an expert system for alleviation of voltage violations in the day-to-day operation of large power networks. Voltage control for varying load and generation conditions can be achieved by co-ordinated control of switchable shunt VAR Compensating (SVC) devices and On load transformer taps (OLTC), while generator excitations are used in dynamic control of voltage profile. This paper deals with the development of an expert system for voltage corrections for base case and contingency conditions using switchable shunt reactive compensation and transformer tap settings. The performance of the expert system is compared with the conventional optimization technique of voltage control and concurrent results have been obtained. The proposed expert system has been tested with simulated conditions of a few practical power systems. Results obtained for a 24 bus EHV Indian power network have been included for illustration purpose. The expert system is found to be suitable for on-line application in Energy Control Center as the solution is obtained very fast.

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