In this research the Empirical Bayes method is used to Estimate the affiliation parameter in the clinical trials and then we compare this with the Moment Estimates for this parameter using Monte Carlo stimulation , we assumed that the distribution of the observation is binomial distribution while the distribution with the unknown random parameters is beta distribution ,finally we conclude that the Empirical bayes method for the random affiliation parameter is efficient using Mean Squares Error (MSE) and for different Sample size .

      The objective of this research is employ the special cases of  function  trapezoid in the composition of fuzzy sets to make decision within the framework of the theory of games traditional to determine the best strategy for the mobile phone networks in the province of  Baghdad and Basra, has been the adoption of different periods of the  functions belonging to see the change happening in the matrix matches and the impact  that the strategies  and decision-making  available to each player and the impact on  societ

Background: Study looking into cardiovascular disorders (CVD) medicines or analgesics cost-saving activities during dispensing process is lacking.

Aim: To determine differences in factors and costs associated with refused CVD medicines or analgesics during dispensing process

Method: This study was approved by Medical Research and Ethics Committee (MREC) (Registration number: NMRR-20-177-53153(IIR)). Participants receiving CVD medicines or analgesics during dispensing process were recruited via convenience sampling technique between February and March 2020 at the Specialist Pharmacy Department of Jerantut Hospital, Malaysia. Refusal to medications and its reasons were asked based on the questionnaire developed by the resea

In this research, we find the Bayesian formulas and the estimation of Bayesian expectation for product system of Atlas Company.  The units of the system have been examined by helping the technical staff at the company and by providing a real data the company which manufacturer the system.  This real data include the failed units for each drawn sample, which represents the total number of the manufacturer units by the company system.  We calculate the range for each estimator by using the Maximum Likelihood estimator.  We obtain that the expectation-Bayesian estimation is better than the Bayesian estimator of the different partially samples which were drawn from the product system after  it checked by the