Although the number of implants has increased gradually and consistently over the years to around one million per year globally, there is still far more potential for advancement in the field of dental implantology which is typically growing quickly. This study investigates the effect of nanofiller reinforcement high-performance polymer matrix to enhance mechanical and physical characteristics. Calcium silicate (CS)/Polyetherketoneketone (PEKK) biomedical composite (G0 as a control group) is reinforced with different weight percentages (G1-G4) of tellurium dioxide nanoparticles (TeO₂NPs) ( n = 5). This research uses ethanol as a binder for mixing various weight percentages (wt%) of TeO₂NPs w

The Middle East fat tailed sheep Ovis aries L. examined within the boundaries of Al-Anbar province, western Iraq was found to acquire seven species of ixodid ticks namely, Hyalomma
anatolicum, H. excxavatum, H. marginatum turanicum, H. detritum, Hyalomma sp., Rhipicephalus turanicus and R. s. sanguineus. The results discussed with the pertinent
literature.

     This paper concerned with estimation reliability (­ for K components parallel system of the stress-strength model with non-identical components which is subjected to a common stress, when the stress and strength follow the Generalized Exponential Distribution (GED) with unknown shape parameter α and the known scale parameter θ (θ=1) to be common. Different shrinkage estimation methods will be considered to estimate ­ depending on maximum likelihood estimator and prior estimates based on simulation using mean squared error (MSE) criteria. The study approved that the shrinkage estimation using shrinkage weight function was the best.

 This paper is concerned with preliminary test single stage shrinkage estimators for the mean (q) of normal distribution with known variance s2 when a prior estimate (q0) of the actule value (q) is available, using specifying shrinkage weight factor y( ) as well as pre-test region (R).         Expressions for the Bias, Mean Squared Error [MSE( )] and Relative Efficiency [R.Eff.( )] of proposed estimators are derived. Numerical results and conclusions are drawn about selection different constants including in these expressions. Comparisons between suggested estimators with respect to usual estimators in the sense of Relative Efficiency are given. Furthermore, comparisons with the earlier existi

A non-parametric kernel method with Bootstrap technology was used to estimate the confidence intervals of the system failure function of the log-normal distribution trace data. These are the times of failure of the machines of the spinning department of the weaving company in Wasit Governorate. Estimating the failure function in a parametric way represented by the method of the maximum likelihood estimator (MLE). The comparison between the parametric and non-parametric methods was done by using the average of Squares Error (MES) criterion. It has been noted the efficiency of the nonparametric methods based on Bootstrap compared to the parametric method. It was also noted that the curve estimation is more realistic and appropriate for the re

In this paper, we derived an estimator of reliability function for Laplace distribution with two parameters using Bayes method with square error loss function, Jeffery’s formula and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived Bayesian estimator compared to the maximum likelihood of this function and moment method using simulation technique by Monte Carlo method under different Laplace distribution parameters and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator and moment estimator in all samples sizes

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.