Abstract:
In this study a type of polymeric composites from melting poly propylene as a basic substance with Palm fronds powder were prepared. Evaluation of polymeric composites was done by studying some of it is mechanical properties, which included:Yong modulus (E), Impact Strength (I.S), Brinell hardness (B.H) and Compression Strength (C.S). The polymeric composites were studied before and after reinforcment by comparing between them. There was an increase in resistance of Yong modulus (E), Impact Strength (I.S), Brinell hardness (B.H) and compression Strength (C.S). Also, the effect of some acids were studied such as (HCl, H2SO4, HNO3) with concentrations of (0.5N; 1N and 1.5N) respectively. The physical properties of absorbance and poly propylene's diffusion coefficient were studied before and after reinforcment, The results showed an increase in values of these properties with increasing concentration of acid and time of polymer's immersion in the acidic solution.
In this research، a comparison has been made between the robust estimators of (M) for the Cubic Smoothing Splines technique، to avoid the problem of abnormality in data or contamination of error، and the traditional estimation method of Cubic Smoothing Splines technique by using two criteria of differentiation which are (MADE، WASE) for different sample sizes and disparity levels to estimate the chronologically different coefficients functions for the balanced longitudinal data which are characterized by observations obtained through (n) from the independent subjects، each one of them is measured repeatedly by group of specific time points (m)،since the frequent measurements within the subjects are almost connected an
... Show MoreThe aim of this paper is to estimate a nonlinear regression function of the Export of the crude oil Saudi (in Million Barrels) as a function of the number of discovered fields.
Through studying the behavior of the data we show that its behavior was not followed a linear pattern or can put it in a known form so far there was no possibility to see a general trend resulting from such exports.
We use different nonlinear estimators to estimate a regression function, Local linear estimator, Semi-parametric as well as an artificial neural network estimator (ANN).
The results proved that the (ANN) estimator is the best nonlinear estimator am
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