An Experimental and theoretical study has been conducted on the adsorption of methylene blue dye using activated carbon prepared from babul seed by chemical activation with orthophosphoric acid. BET surface area of the activated carbon was determined as 1060 m2/g. Adsorption kinetics, equilibrium and thermodynamics were investigated as a function of initial dye concentration, temperature and pH. First order Lagergren, pseudo-second order and Elovich kinetic models were used to test the adsorption kinetics. Results were analyzed by the Langmuir, Freundlich and Temkin isotherm models. Based on regression coefficient, the equilibrium data found fitted well to the Langmuir equilibrium model than other models. The characteristics of the prepared activated carbon were found comparable to the commercial activated carbon. It is found that the babul seed activated carbon is very effective for the removal of colouring matter.

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In this work, an attempt has been made to enhance the diagnostic relevance of spirometric pulmonary function test using neural networks and Principal Component Analysis (PCA). For this study, flow-volume curves (N = 175) using spirometers were generated under standard recording protocol. A method based on neural network is used to predict the most significant parameter, FEV(1). Further, PCA is used to analyze the interdependency of the parameters in the measured and predicted datasets. Results show that the back propagation neural network is able to predict FEV(1) both in normal and abnormal cases. The variation in the magnitude and direction of parameters in the contribution of the principal components shows that FEV(1) is a significant discriminator of normal and abnormal datasets and is further confirmed by the percentage variance in the first few principal components. It appears that this method of prediction and principal component analysis on the measured and predicted datasets could be useful for spirometric pulmonary function test with incomplete data.

A critical requirement in the design of Ad hoc networks is the development of an efficient routing protocol which provides efficient communication. The node's in MANET have limited communication resources such as bandwidth, buffer space, battery power etc. The resource constraints in MANET require the traffic to be fairly distributed among the mobile host. Multi-level routing algorithm proposed in this paper facilitates an efficient method for communication with mobile node's. It reduces the communication overhead by fairly distributing the traffic among the wireless nodes. It selects the intermediate node's which have the enough resources and capability to handle the information transmitted in order to reach the destination node. The routing algorithm becomes more suitable as the mobile nodes move, it reduces the average end to end delay and increases the number of control packets sent with respect to increase in the number of node's.