Each phenomenon contains several variables. Studying these variables, we find mathematical formula to get the joint distribution and the copula that are a useful and good tool to find the amount of correlation, where the survival function was used to measure the relationship of age with the level of cretonne in the remaining blood of the person. The Spss program was also used to extract the influencing variables from a group of variables using factor analysis and then using the Clayton copula function that is used to find the shared binary distributions using multivariate distributions, where the bivariate distribution was calculated, and then the survival function value was calculated for a sample size (50) drawn from Yarmouk Ho

This deals with estimation of Reliability function and one shape parameter (?) of two- parameters Burr – XII , when ?(shape parameter is known) (?=0.5,1,1.5) and also the initial values of (?=1), while different sample shze n= 10, 20, 30, 50) bare used. The results depend on empirical study through simulation experiments are applied to compare the four methods of estimation, as well as computing the reliability function . The results of Mean square error indicates that Jacknif estimator is better than other three estimators , for all sample size and parameter values

In this work, electron number density calculated using Matlab program code with the writing algorithm of the program. Electron density was calculated using Anisimov model in a vacuum environment. The effect of spatial coordinates on the electron density was investigated in this study. It was found that the Z axis distance direction affects the electron number density (ne). There are many processes such as excitation; ionization and recombination within the plasma that possible affect the density of electrons. The results show that as Z axis distance increases electron number density decreases because of the recombination of electrons and ions at large distances from the target and the loss of thermal energy of the electrons in high distance

This study aims to evaluate the biocompatibility of a novel filler material intended to improve the longevity of polymer systems used in prosthetics in respect of cytotoxicity and skin irritation. RTV50F silicone elastomer incorporated with various percentages of hexagonal boron nitride (H-BN) (0.1, 0.3, 0.5, 0.7, and 1 wt%) have been tested. Silicone without H-BN was utilized as the control for comparison. The in vitro cytotoxicity test includes specimens (n=18) with 10 mm in diameter and 2 mm in thickness applied directly to the normal human fibroblast cell line (NHF) and incubated for 72 hours, then 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay was used to determine the cell viability. The skin irritati

The present work studies the mechanical properties of SiO2 μPs, and NPs in St/PVA blends. The samples were prepared by casting method as PVA, St/PVA blends at different concentrations (30, 40, 50, and 60 %). DSC and TGA tests were carried out to the samples evolved. The result showed a single glass transition temperature (Tg) for all St /PVA blends that was attributed to the good miscibility of the blends involved. It was found that (Tg) decrease with starch ratio increase. It was seen that (PVA) of (Tg=105 oC); The glass transition temperature which was decrease with starch ratio that was attributed to glass transition relaxation process due to micro-Brownian motion of the main chain back bond. The endothermic peak at 200 oC was attrib

The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

Chemical bath deposition was used to synthesize ZnO nanorods (NRs) on glass and fluorine^_doped tin oxide (FTO) substrates. X-ray diffraction was performed to examine the crystallinity of ZnO nanorod. Results showed that ZnO NRs had a wurtzite crystal structure. Field emission scanning electron microscopy images showed that glass sample had rod-like structure distribution with (50 nm) diameter and average length of approximately (700 nm), whereas the FTO-coated glass sample had 25 nm diameter and average length of approximately 950 nm. The direct optical transition band gaps of the glass and FTO^_coated glass samples were( 4 and 4.43 eV), respectively. The structural and optical properties of the synthesized ZnO p

             In general, researchers and statisticians in particular have been usually used non-parametric regression models when the parametric methods failed to fulfillment their aim to analyze the models  precisely. In this case the parametic methods are useless so they turn to non-parametric methods for its easiness in programming. Non-parametric methods can also used to assume the parametric regression model for subsequent use. Moreover, as an advantage of using non-parametric methods is to solve the problem of Multi-Colinearity between explanatory variables combined with nonlinear data. This problem can be solved by using kernel ridge regression which depend o

Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing artificial TABU algorithm to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as sport, chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement.