In this paper, the error distribution function is estimated for the single index model by the empirical distribution function and the kernel distribution function. Refined minimum average variance estimation (RMAVE) method is used for estimating single index model. We use simulation experiments to compare the two estimation methods for error distribution function with different sample sizes, the results show that the kernel distribution function is better than the empirical distribution function.

Drag has long been identified as the main reason for the loss of energy in fluid transmission like pipelines and other similar transportation channels. The main contributor to this drag is the viscosity as well as friction against the pipe walls, which will results in more pumping power consumption.

   The aim in this study was first to understand the role of additives in the viscosity reduction and secondly to evaluate the drag reduction efficiency when blending with different solvents.

   This research investigated flow increase (%FI) in heavy oil at different flow rates (2 to 10 m3/hr) in two pipes (0.0381 m & 0.0508 m) ID By using different additives (toluene and naphtha) with different concent

There are many images you need to large Khneh space With the continued evolution of storage technology for computers, there is a continuing need and are required to reduce Alkhoznip space Pictures Zguet pictures in a good way, the way conversion Alamueja to Purifiers

This deals with estimation of Reliability function and one shape parameter (?) of two- parameters Burr – XII , when ?(shape parameter is known) (?=0.5,1,1.5) and also the initial values of (?=1), while different sample shze n= 10, 20, 30, 50) bare used. The results depend on empirical study through simulation experiments are applied to compare the four methods of estimation, as well as computing the reliability function . The results of Mean square error indicates that Jacknif estimator is better than other three estimators , for all sample size and parameter values

The goal beyond this Research is to review methods that used to estimate Logistic distribution parameters. An exact estimators method which is the Moment method, compared with other approximate estimators obtained essentially from White approach such as: OLS, Ridge, and Adjusted Ridge as a suggested one to be applied with this distribution. The Results of all those methods are based on Simulation experiment, with different models and variety of  sample sizes. The comparison had been made with respect to two criteria: Mean Square Error (MSE) and Mean Absolute Percentage Error (MAPE).