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The models with the best prognostic performance had data representations that included limited clinical samples and some behavioral interpretations.
With limited energy resources, it is the need of time to revolutionize the traditional methods of counting visitors inside hotels, recreational places, meeting rooms and cinemas to control the electrical appliances.
In this paper, an application of artificial neural network (ANN) using bayesian regularization (BR) learning algorithm based on multilayer perceptron (MLP) model is presented for computing the operating frequency of C-shaped patch antennas (CPAs) in UHF band.
Firstly, the operating frequencies of 144 CPAs having varied dimensions and electrical parameters were simulated by the XFDTD software package based on the finite-difference time domain (FDTD) method in order to generate the data set for the training and testing processes of the ANN-BR model.
Most of those devices and their applications handle personal, financial, medical and other sensitive data that require security and privacy protection.
In this paper we describe one aspect of such protection – user authentication protocol based on the use of X.509 certificates.