In this study, industrial fiber and polymer mixtures were used for high-speed impact (ballistic) applications where the effects of polymer (epoxy), polymeric
mixture (epoxy + unsaturated polyester), synthetic rubber (polyurethane), Kevlar fiber, polyethylene fiber (ultra High molecular weight) and carbon fiber.
Four successive systems of samples were prepared. the first system component made of (epoxy and 2% graphene and 20 layer of fiber), then ballistic test was
applied, the sample was successful in the test from a distance of 7 m. or more than, by using a pistol personally Glock, Caliber of 9 * 19 mm. The second
system was consisting of (epoxy, 2% graphene, 36 layers of fiber and one layer of hard rubber), it was succeeded

This research presents a particular designing strategy for a free form of surfaces, constructed by the lofting design method. The regarded surfaces were created by sliding a B-spline curves (profile curves), in addition to describing an automatic procedure for selective identification of sampling points in reverse engineering applications using Coordinate Measurement Machine. Two models have been implemented from (Ureol material) to represent the different cases of B-spline types to clarify its scope of application. The interior data of the desired surfaces was designed by MATLAB software, which then were transformed to UG-NX9 software for connecting the sections that were designed in MATLAB program and obtaining G-code programs for the

          In this work, the modified Lyapunov-Schmidt reduction is used to find a nonlinear Ritz approximation of Fredholm functional defined by the nonhomogeneous Camassa-Holm equation and Benjamin-Bona-Mahony. We introduced the modified Lyapunov-Schmidt reduction for nonhomogeneous problems when the dimension of the null space is equal to two.  The nonlinear Ritz approximation for the nonhomogeneous Camassa-Holm equation has been found as a function of codimension twenty-four.

This research was designed to investigate the factors affecting the frequency of use of ride-hailing in a fast-growing metropolitan region in Southeast Asia, Kuala Lumpur. An intercept survey was used to conduct this study in three potential locations that were acknowledged by one of the most famous ride-hailing companies in Kuala Lumpur. This study used non-parametric and machine learning techniques to analyze the data, including the Pearson chi-square test and Bayesian Network. From 38 statements (input variables), the Pearson chi-square test identified 14 variables as the most important. These variables were used as predictors in developing a BN model that predicts the probability of weekly usage frequency of ride-hai