Compaction curves are widely used in civil engineering especially for road constructions, embankments, etc. Obtaining the precise amount of Optimum Moisture Content (OMC) that gives the Maximum Dry Unit weight g_dmax. is very important, where the desired soil strength can be achieved in addition to economic aspects.

In this paper, three peak functions were used to obtain the OMC and g_dmax. through curve fitting for the values obtained from Standard Proctor Test. Another surface fitting was also used to model the Ohio’s compaction curves that represent the very large variation of compacted soil types.

The results showed very good correlation between the values obtained from some publ

In this paper, we investigate the behavior of the bayes estimators, for the scale parameter of the Gompertz distribution under two different loss functions such as, the squared error loss function, the exponential loss function (proposed), based different double prior distributions represented as erlang with inverse levy prior, erlang with non-informative prior, inverse levy with non-informative prior and erlang with chi-square prior.

The simulation method was fulfilled to obtain the results, including the estimated values and the mean square error (MSE) for the scale parameter of the Gompertz distribution, for different cases for the scale parameter of the Gompertz distr

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).  

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Four local hemolysin producer bacterial isolates were selected, tow of them gram negative bacteria (Escherichia coli ,Pseudomonas aeruginosa ) and the other two were gram positive bacteria (Staphylococcus aureus , Bacillus cereus ). Minimum inhibitory concentration of the aqueous and alcoholic extracts of Punica granatum L. pericarp were determined towards the four bacterial isolates ,results obtaind showed that MICs of the aqueous extract were 200 mg/ml for E .coli and P. aeruginosa isolates while were 5 mg/ml and 2 mg/ml for B. cereus, S. aureus , respectively The MICs for the ethanolic extract were 50 mg/ml , 20 mg/ml ,1 mg/ml ,0.5 mg/ml for E. coli ,P. aeruginosa ,B. cereus ,S. aureus , respectively. The effect of Sub-MICs o

Abstract
The concept of unipolar has allowed the united states of America to
control the rest of the internations community units through the rxclusively of
control in international affairs without enabling other countries who have the
ability to compete with it to appear this comes as a result of it's position to all
kinds of powers like military, economic and technical powers that enable it to
continue dominating other countries, this superior control enabled it to be the
(hyper power) on the international political scene so that it allowed it to
exercise and implement the policy of domination against all this appeared
after its empire superiority became clear, in a unique way that have never
been known in

In this paper, the Azzallini’s method used to find a weighted distribution derived from the standard Pareto distribution of type I (SPDTI) by inserting the shape parameter (θ) resulting from the above method to cover the period (0, 1] which was neglected by the standard distribution. Thus, the proposed distribution is a modification to the Pareto distribution of the first type, where the probability of the random variable lies within the period  The properties of the modified weighted Pareto distribution of the type I (MWPDTI) as the probability density function ,cumulative distribution function, Reliability function , Moment and  the hazard function are found. The behaviour of probability density function for MWPDTI distrib

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.