The stress – strength model is one of the models that are used to compute reliability. In this paper, we derived mathematical formulas for the reliability of the stress – strength model that follows Rayleigh Pareto (Rayl. – Par) distribution. Here, the model has a single component, where strength Y is subjected to a stress X, represented by moment, reliability function, restricted behavior, and ordering statistics. Some estimation methods were used, which are the maximum likelihood, ordinary least squares, and two shrinkage methods, in addition to a newly suggested method for weighting the contraction. The performance of these estimates was studied empirically by using simulation experimentation that could give more varieties for d

In the lifetime process in some systems, most data cannot belong to one single population. In fact, it can represent several subpopulations. In such a case, the known distribution cannot be used to model data. Instead, a mixture of distribution is used to modulate the data and classify them into several subgroups. The mixture of Rayleigh distribution is best to be used with the lifetime process. This paper aims to infer model parameters by the expectation-maximization (EM) algorithm through the maximum likelihood function. The technique is applied to simulated data by following several scenarios. The accuracy of estimation has been examined by the average mean square error (AMSE) and the average classification success rate (ACSR). T

In this paper, we derived an estimators and parameters of Reliability and Hazard function of new mix distribution ( Rayleigh- Logarithmic) with two parameters and increasing failure rate using Bayes Method with Square Error Loss function and Jeffery and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived of Bayesian estimator compared to the to the Maximum Likelihood of this function using Simulation technique by Monte Carlo method under different Rayleigh- Logarithmic parameter and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator in all sample sizes with application

The purpose of this study is to investigate the effect of an elastic wall on the peristaltic flow of Williamson fluid between two concentric cylinders, where the inner tube is cylindrical with an inelastic wall and the outer wall is a regular elastic sine wave.  For this problem, cylindrical coordinates are used with a short wavelength relative to channel width for its length, as well as the governing equations of Williamson fluid in the Navier-Stokes equations. The results evaluated using the Mathematica software program. The Mathematica program used by entering the various data for the parameters, where the program shows the graphs, then the effect of these parameters became clear and the results mentioned in the conclusion. Williamso

The research aims to identify the new reality of Iraq’s international relations through the news
coverage carried out by Al-Iraqiya TV since the size and nature of the coverage indicate the extent
to which these relations have reached. The research problem is summarized by the main question
(what is the size and nature of news coverage of Iraq’s international relations in the Iraqi News
Channel?).
This research is considered a descriptive research, as the researchers used the survey method and the
content analysis method through a partial confinement of the research community consisting of the
main news broadcast for one programmatic period. The content analysis form that was subjected to
evaluation was design

    The purpose of this study is to calculate the effect of the elastic wall of a hollow channel of Jeffrey's fluid by peristaltic flow through two concentric cylinders. The inside tube is cylindrical and the outside is a regular elastic wall in the shape of a sine wave. Using the cylindrical coordinates and assuming a very short wavelength relative to the width of the channel to its length and using governing equations for Jeffrey’s fluid in Navier-Stokes equations, the results of the problem are obtained. Through the Mathematica  program these results are  analysed.

The two dimensional steady, combined forced and natural convection in vertical channel is
investigated for laminar regime. To simulate the Trombe wall channel geometry properly, horizontal
inlet and exit segments have been added to the vertical channel. The vertical walls of the channel are
maintained at constant but different temperature while horizontal walls are insulated. A finite
difference method using up-wind differencing for the nonlinear convective terms, and central
differencing for the second order derivatives, is employed to solve the governing differential
equations for the mass, momentum, and energy balances. The solution is obtained for stream
function, vorticity and temperature as dependent variables

    In this study, we present different methods of estimating fuzzy reliability of a two-parameter Rayleigh distribution via the maximum likelihood estimator, median first-order statistics estimator, quartile estimator, L-moment estimator, and mixed Thompson-type estimator. The mean-square error MSE as a measurement for comparing the considered methods using simulation through different values for the parameters and unalike sample sizes is used. The results of simulation show that the fuzziness values are better than the real values for all sample sizes, as well as  the fuzzy reliability at the estimation  of the Maximum likelihood Method, and Mixed Thompson Method perform better than the other methods in the sense of MSE, so that

     In this paper, Bayesian estimator for the parameter and reliability function of inverse Rayleigh distribution (IRD) were obtained Under three types of loss function, namely, square error loss function (SELF), Modified Square error loss function (MSELF) and Precautionary loss function (PLF),taking into consideration the  informative and non- informative  prior. The performance of such estimators was assessed on the basis of mean square error (MSE) criterion by performing a Monte Carlo simulation technique.