This paper is concerned with the problem of measuring market response to a "communications mix" -the various means which a firm employs to transmit sales messages to potential buyers. Distributed lag models are applied to time series data for an ethical drug to estimate the short-run and long-run effects on market share of expenditures made for journal advertising, direct mail advertising and s...

Industrial pollution is often considered to be one of the prime factors contributing to air, water and soil pollution. Sectoral pollution loads (ton/yr) into different media (i.e. air, water and land) in Lagos were estimated using Industrial Pollution Projected System (IPPS). These were further studied using Artificial neural Networks (ANNs), a data mining technique that has the ability of dete...

Forecasting a hydrologic time series has been one of the most complicated tasks owing to the wide range of data, the uncertainties in the parameters influencing the time series and also due to the non availability of adequate data. Recently, Artificial Neural Networks (ANNs) have become quite popular in time series forecasting in various fields. This paper demonstrates the use of ANNs to foreca...

The use of virtual reality has been demonstrated to be very useful in the visualization of science and the synthesis of vast amounts of data. Further, advances in high-speed networks makes feasible the coupling of remote supercomputer simulations and virtual environments. The critical performance issue to be addressed with this coupling is the end-to-end lag time (i.e., the delay between a user...

A recurrent neural network is applied for minimizing the infinity-norm of joint torques in redundant manipulators. The recurrent neural network explicitly minimizes the maximum component of joint torques in magnitude while keeping the relation between the joint torque and the end-effector acceleration satisfied. The end-effector accelerations are given to the recurrent neural network as its inp...