In this work chemical vapor deposition method (CVD) for the production of carbon nanotubes (CNTs) have been improved by the addition of S. Steel mesh container (SSMC) inside which the catalyst (Fe/Al2O3) was placed. Scanning electron microscopy (SEM) investigation method used to study nanotubes produced, showed that high yield of two types of (CNTs) obtained, single wall carbon nanotube (SWCNTs) with diameter and length of less than 50nm and several micrometers respectively and nanocoil tubes with a diameter and length of less than 100nm and several micrometers respectively. The chemical analysis of (CNTs) reveals that the main component is carbon (94%) and a little amount of Al (0.32%), Fe (2.22%) the reminder is oxygen. It was also fou

     Cloth simulation and animation has been the topic of research since the mid-80's in the field of computer graphics. Enforcing incompressible is very important in real time simulation. Although, there are great achievements in this regard, it still suffers from unnecessary time consumption in certain steps that is common in real time applications.   This research develops a real-time cloth simulator for a virtual human character (VHC) with wearable clothing. This research achieves success in cloth simulation on the VHC through enhancing the position-based dynamics (PBD) framework by computing a series of positional constraints which implement constant densities. Also, the self-collision and collision wit

A second-order sliding mode control is used for high-order uncertain plants using equivalent control approach to improve the performance of control systems. They combine backstepping with quasi-continuous controller and twisting controllers. This paper considers a two of the most popular controllers that are used to solve the nonlinearities problem which are the backstepping quasi-continuous control (BQCC) and backstepping twisting controllers to control the angular velocity of a hydraulic motor to improve tracking performance and robustness to uncertainties. For the system dynamics, a linear state feedback with suitable high gain was designed as the virtual controller, where steady state error can be made arbitrarily small according to the

Survival analysis is widely applied to data that described by the length of time until the occurrence of an event under interest such as death or other important events. The purpose of this paper is to use the dynamic methodology which provides a flexible method, especially in the analysis of discrete survival time, to estimate the effect of covariate variables through time in the survival analysis on dialysis patients with kidney failure until death occurs. Where the estimations process is completely based on the Bayes approach by using two estimation methods: the maximum A Posterior (MAP) involved with Iteratively Weighted Kalman Filter Smoothing (IWKFS) and in combination with the Expectation Maximization (EM) algorithm. While the other

A condense study was done to compare between the ordinary estimators. In particular the maximum likelihood estimator and the robust estimator, to estimate the parameters of the mixed model of order one, namely ARMA(1,1) model.

Simulation study was done for a varieties the model.  using: small, moderate and large sample sizes, were some new results were obtained. MAPE was used as a statistical criterion for comparison.