This research prepared polymer blend contains from epoxy resin (Ep) and polyurethane
)Pu) as a matrix material of percentage (90 %) from epoxy and ) 10 (% polyurethane and
reinforced by PVC fibers and aluminum fibers two dimension knitted mat with fractional
volume(15 %), and study impact strength before and after reinforcing at temperatures of
(20,40,60(
o
CØŒand the results have shown that the reinforcing matrix materials by fibers
increased impact strength values that rise from(3.387kJ/m2) to (151.62kJ/m2) of composite
material (Ep+Pu+PVC(and thus ) Ep+Pu+PVC+Al.F) at last (Ep+Pu+Al.F (. following
composite material so that temperatures increase led to rise impact strength values except the
polymer blend reinforced with PVC fibers that the temperatures increase led to decrease the
values of impact strength from (151.62kJ/m
2
(at (20°C) to (114.27kJ/m
2
(at (60°C)
A Study of Reinforcing and Temperature Effect of Impact Strength for Polymer Blend
Polymer blends
Epoxy resin
Impact strength
Publication Date
Fri Jan 01 2016
Journal Name
Journal Of Engineering
Mobile Position Estimation using Artificial Neural Network in CDMA Cellular Systems
feed forward neural network
time of arrival
received signal strength
back propagation
optimal positioning method
and average positioning method.
Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through tha
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