Trace Elements (Cd, Pb, Cu, Zn, Ni) level were examined in hair of donors from industrial areas, cities and village, and in permanent contact with a polluted workplace environment in lattakia. Hair sample were analyzed for their contents of the trace elements by inductivity coupled plasma- mass spectrometer (ICP- MS). It was found that the contents of (Cd, Pb, Cu, Zn, Ni) in the hair were significantly higher in the industrial areas and cities, while in the village had the lower concentration of elements. Correlation coefficients between the levels of the elements in hair found in this study showed that hair is a good indicator of Environmental Pollution.

Because of the experience of the mixture problem of high correlation and the existence of linear MultiCollinearity between the explanatory variables, because of the constraint of the unit and the interactions between them in the model, which increases the existence of links between the explanatory variables and this is illustrated by the variance inflation vector (VIF), L-Pseudo component to reduce the bond between the components of the mixture.

    To estimate the parameters of the mixture model, we used in our research the use of methods that increase bias and reduce variance, such as the Ridge Regression Method and the Least Absolute Shrinkage and Selection Operator (LASSO) method a

Urban Balance is one of the important indicators that leads to an assessment of the urbanization process in a particular country  , province or even a city that is multi-centered. By examining  the data related to Anba  province, it was found that the value of this indicator is equal to 0.96, which is less than the absolute one, and therefore the urbanization in the province is distributed collectively  

The development of a mathematical or statistical model for estimating urban growth is a complex process due to the overlap between indicators or variables that can be adopted to calculate estimate growth rates Al-Qaim city has been considered as an example to develop a statistical method by which changes

As the process of  estimate for model and variable selection significant is a crucial process in the semi-parametric modeling At the beginning of the modeling process often At there are many explanatory variables to Avoid the loss of any explanatory elements may be important as a result , the selection of significant variables become necessary , so the process of variable selection is not intended to simplifying  model complexity explanation , and also predicting. In this research was to use some of the semi-parametric methods (LASSO-MAVE , MAVE and The proposal method (Adaptive LASSO-MAVE) for variable selection and estimate semi-parametric single index model (SSIM) at the same time .

Objective: preparing exercises for the third intensity zone for strength and speed for the legs, and identifying their effect on some physiological and biochemical indicators for (the level of lactic acid concentration, the concentration of sodium bicarbonate, the concentration level of (potassium K+) and (sodium Na+) in the blood, and the number of breathing times (RF) Research methodology: the experimental research method was adopted by designing the experimental and control groups on a sample of Army Sports Club players amounting to (16) players, deliberately selected (100%) from their community using a comprehensive enumeration method, and then divided into two groups of equal number, After determining the tests for physiologica

The multiple linear regression model is an important regression model that has attracted many researchers in different fields including applied mathematics, business, medicine, and social sciences , Linear regression models involving a large number of independent variables are poorly performing due to large variation and lead to inaccurate conclusions , One of the most important problems in the regression analysis is the multicollinearity Problem, which is considered one of the most important problems that has become known to many researchers  , As well as their effects on the multiple linear regression model, In addition to multicollinearity, the problem of outliers in data is one of the difficulties in constructing the reg

Began the process of re-engineering processes in the private sector as a way to assist organizations in re-thinking how to run the business in order to improve production processes and reduce operational cost, to get to compete on a global level. That was a major restructuring by further evolution in the use of technology to support innovative operations.

 Entered the technology in all areas of life and different regulations, This led to use as a change in all aspects The companies achieved success and progress today through the use of resources so as to ensure the wishes of the customers and their needs, and the requirements of the market primarily, Which is reflected on the basis of building strate

The aim of this research is to estimate the parameters of the linear regression model with errors following ARFIMA model by using wavelet method depending on maximum likelihood and approaching general least square as well as ordinary least square. We use the estimators in practical application on real data, which were the monthly data of Inflation and Dollar exchange rate obtained from the (CSO) Central Statistical organization for the period from 1/2005 to 12/2015. The results proved that (WML) was the most reliable and efficient from the other estimators, also the results provide that the changing of fractional difference parameter (d) doesn’t effect on the results.

The aim of this work is to produce samples from Iraqi raw materials like Husyniat Bauxite (raw and burnt) and to study the effect of some additives like white Doekhla kaolin clays and alumina on that material properties were using sodium silica as a binding material. Five mixtures were prepared from Bauxite (raw and burnt) and kaolin clays, with an additive of (40) ml from sodium silica and alumina of (2.5, 5, 7.5,10 wt %) percentage as a binding material. the size grading was through sieving. The formation of all specimens was conducted by a measured gradually semi-dry pressing method under a compression force of (10) Tons and humidity ratio ranging from (5-10) % from mixture weight. Drying all specimens was done and then they were burn

    Multivariate Non-Parametric control charts were used to monitoring the data that generated by using the simulation, whether they are within control limits or not. Since that non-parametric methods do not require any assumptions about the distribution of the data.  This research aims to apply the multivariate non-parametric quality control methods, which are Multivariate Wilcoxon Signed-Rank ( ) , kernel principal component analysis (KPCA) and k-nearest neighbor ( −