Research ArticleOpen accessAll words, across the recordPrediction of Double Layer Grids' Maximum Deflection Using Neural NetworksReza Kamyab Moghadas, Kok Keong ChoongEfficient neural networks models are trained to predict the maximum deflection of two-way on two-way grids with variable geometrical parameters (span and height) as well as cross-sectional areas of the element groups. Backpropagation (BP) and Radial Basis Function (RBF) neural networks are employed for the mentioned purpose. The inputs of the neural networks are the length of the spans, L, … …American Journal of Applied Sciences, Vol. 5, Issue 11 · 30 Nov 2008 · 6,488 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordAerodynamic Noise Prediction Using stochastic Turbulence ModelingArash Ahmadzadegan, Mehran TadjfarAmongst many approaches to determine the sound propagated from turbulent flows, hybrid methods, in which the turbulent noise source field is computed or modeled separately from the far field calculation, are frequently used. For basic estimation of sound propagation, less computationally intensive methods can be developed using stochastic models of the turbulent fluctuations (turbulent noise source field). A simple and … …American Journal of Applied Sciences, Vol. 5, Issue 9 · 30 Sep 2008 · 7,223 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordERROR DETECTION SCHEMES FOR FINITE FIELD MULTIPLIERSB. Sargunam, R. DhanasekaranFinite field multipliers are widely used in the field of cryptography for the purpose of scalar multiplication. The outputs of the finite field multipliers may consist of errors due to certain natural radiations which further leads to the failure of the cryptosystems. Here two Concurrent Error Detection (CED) schemes namely time redundancy and modular inversion based error detection schemes for … …American Journal of Applied Sciences, Vol. 11, Issue 1 · 11 Dec 2013 · 6,913 accessesView PDFCite