Automated implementation of rule-based expert systems with neural networks for time-critical applications

In fault diagnosis, control and real-time monitoring, both timing and accuracy are critical for operators or machines to reach proper solutions or appropriate actions. Expert systems are becoming more popular in the manufacturing community for dealing with such problems. In recent years, neural networks have revived and their applications have spread to many areas of science and engineering. A method of using neural networks to implement rule-based expert systems for time-critical applications is discussed here. This method can convert a given rule-based system into a neural network with fixed weights and thresholds. The rules governing the translation are presented along with some examples. We also present the results of automated machine implementation of such networks from the given rule-base. This significantly simplifies the translation process to neural network expert systems from conventional rule-based systems. Results comparing the performance of the proposed approach based on neural networks vs. the classical approach are given. The possibility of very large scale integration (VLSI) realization of such neural network expert systems is also discussed

Efficiency of S&P CNX Nifty Index Option of the National Stock Exchange (NSE), India, using Box Spread Arbitrage Strategy

Box spread is a trading strategy in which one simultaneously buys and sells options having the same underlying asset and time to expiration, but different exercise prices. This study examined the efficiency of European style S&P CNX Nifty Index options of National Stock Exchange, (NSE) India by making use of high-frequency data on put and call options written on Nifty (Time-stamped transactions data) for the time period between 1st January 2002 and 31st December 2005 using box-spread arbitrage strategy. The advantages of box-spreads include reduced joint hypothesis problem since there is no consideration of pricing model or market equilibrium, no consideration of inter-market non-synchronicity since trading box spreads involve only one market, computational simplicity with less chances of mis-specification error, estimation error and the fact that buying and selling box spreads more or less replicates risk-free lending and borrowing. One thousand three hundreds and fifty eight exercisable box-spreads were found for the time period considered of which 78 Box spreads were found to be profitable after incorporating transaction costs (32 profitable box spreads were identified for the year 2002, 19 in 2003, 14 in 2004 and 13 in 2005) The results of our study suggest that internal option market efficiency has improved over the years for S&P CNX Nifty Index options of NSE India.    

The Expectation Disconfirmation Theory of Green Banking Practices of State Bank of India with special reference to Kerala - A Structural Equation Modeling Approach

In light of Agenda 2030, sustainability awareness is steadily growing worldwide. All institutions, including banks and financial institutions, are working to reduce their carbon footprints. Several indirect problems have arisen for India as a result of the banking process, such as global warming, climate change, irregular monsoon, air pollution, heavy rain, poor air quality, health problems, ozone depletion, fossil fuel use, recurrent destruction of forests for daily use, improper e-waste disposal. These issues can be overcome with sustainable banking practices (Green banking), which benefit the customer's satisfaction and quality of life. However, sustainability can be achieved only when the customers accept green banking and are satisfied with it. In order to do that, the bank must understand the level of expectations and perception of its customers toward green initiatives and to what extent the initiatives satisfy their day-to-day needs. This paper provides an overview of Expectancy disconfirmation integrations into customer satisfaction of India's largest public sector banks. As part of the present theoretical analysis, we first examine the level of awareness, expectations, and perception differences of customers to determine their satisfaction level. We then provide some evidence from SBI in Kerala regarding dissatisfying factors in green banking practices