Epoxy (EP) – Silica (SiO2) composites are well known composites used in microelectronic industry . So it is important to study their dielectric behavior under different conditions such as
the presence carbon black (UV absorber) and immersion in the water for 30 days .
Dielectric properties were calculated over the frequency range 102 – 106 Hz for epoxy composites with different weight % of micrometer 1.5μm SiO2 particles (60%, 65% and 70wt%) modified with 0.5wt% silane coupling agent to improve adhesion between EP and SiO2 phases .

 The tax base is one of the bases of the technical organizing of taxes,   and that a good selection of the tax base effects the outcome of the tax and its fairness, and with the expansion of the tax range results a dangerous phenomenon called tax evasion, which became threaten the economies of countries and this phenomenon prevents the achievement of the state to its economic, political and social objectives which seeks to resolve this phenomenon and identifying all human and material potential and realize the real reasons that lie behind it.   The researcher found that tax authorities are weak in terms of it the technical material and financial abilities, the analysis of data show that then is a significant reve

ABSTRACT Background: resin cement type and intraoral temperature fluctuations may affect the fracture performance of successful zirconia restorations. To fill this gap, the purpose of this study is to evaluate and compare the influence of thermocycling on fracture resistance and mode of failure of monolithic zirconia crowns luted with Rely X™ U200 and BreezeTMself-adhesive resin cements as well as imply the effect of adding 2 % of polylysine (PLS) to these cements. Materials: 64 maxillary premolars were milled out of zirconia blocks using CAD/CAM milling system. They were divided into four groups (n = 16) according to the cement type. Four different resin cements were used (RelyXTMU200, Breeze™, RelyX™ U200 with 2 % PLS

Transforming the common normal distribution through the generated Kummer Beta model to the Kummer Beta Generalized Normal Distribution (KBGND) had been achieved. Then, estimating the distribution parameters and hazard function using the MLE method, and improving these estimations by employing the genetic algorithm. Simulation is used by assuming a number of models and different sample sizes. The main finding was that the common maximum likelihood (MLE) method is the best in estimating the parameters of the Kummer Beta Generalized Normal Distribution (KBGND) compared to the common maximum likelihood according to Mean Squares Error (MSE) and Mean squares Error Integral (IMSE) criteria in estimating the hazard function. While the pr

Metasurface polarizers are essential optical components in modern integrated optics and play a vital role in many optical applications including Quantum Key Distribution systems in quantum cryptography. However, inverse design of metasurface polarizers with high efficiency depends on the proper prediction of structural dimensions based on required optical response. Deep learning neural networks can efficiently help in the inverse design process, minimizing both time and simulation resources requirements, while better results can be achieved compared to traditional optimization methods. Hereby, utilizing the COMSOL Multiphysics Surrogate model and deep neural networks to design a metasurface grating structure with high extinction rat

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

In this paper, we used maximum likelihood method and the Bayesian method to estimate the shape parameter (θ), and reliability function (R(t)) of the Kumaraswamy distribution with two parameters l , θ (under assuming the exponential distribution, Chi-squared distribution and Erlang-2 type distribution as prior distributions), in addition to that we used method of moments for estimating the parameters of the prior distributions. Bayes