The research aims to know the relation between positive thinking and self academic motivation, trend towards teaching profession. So a sample of (344) male and female student of the morning study of education colleges from the two universities of Baghdad and al Mustansria for the academic year 2012-2013.

So three tools had been used to achieve the procedures of the research which are: the scale of positive thinking constracted by Abdal satar Ibrahim year 2010, the scale of self academicmotivation constracted by (Gottfried) and adapted by Hanan Hussan year 2010, the scale of teaching profession trend constracted by Enayat Zaki year 1974.

And by using the statistical means of person

Bacterial strains were isolated from oil-contaminated soil, in 2018, these isolates were identified, and with the aim of finding out the ability of these isolates to degrede the oil compounds, the color change of medium which added to it isolates was read by the method of Pacto Bushnell Hans. Then the change in the petroleum compounds was read by gas chromatography, for the most effective isolates.

The nine isolated bacterial showed different degrees of color change, and the isolates (Pseudomonas, Bacillus, Micrococcus) outperformed the color change amount (78, 78, 77) %, respectively, compared to the control, and the three isolates together showed the best color change of 90.7. % Compared to the control, and the

This research aims to study the methods of reduction of dimensions that overcome the problem curse of dimensionality when traditional methods fail to provide a good estimation of the parameters So this problem must be dealt with directly . Two methods were used to solve the problem of high dimensional data, The first method is the non-classical method Slice inverse regression ( SIR ) method and the proposed weight standard Sir (WSIR) method and principal components (PCA) which is the general method used in reducing dimensions,    (SIR ) and (PCA) is based on the work of linear combinations of a subset of the original explanatory variables, which may suffer from the problem of heterogeneity and the problem of linear

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.

This paper study two stratified quantile regression models of the marginal and the conditional varieties. We estimate the quantile functions of these models by using two nonparametric methods of smoothing spline (B-spline) and kernel regression (Nadaraya-Watson). The estimates can be obtained by solve nonparametric quantile regression problem which means minimizing the quantile regression objective functions and using the approach of varying coefficient models. The main goal is discussing the comparison between the estimators of the two nonparametric methods and adopting the best one between them

Background: In December 2019, an episode of COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARSCoV2) was reported in Wuhan, China and has spread around the world, increasing the number of contagions. Cytomegalovirus (CMV) and Epstein-Barr virus (EBV) are common herpesviruses that can cause persistent latent infections and affect the developing immune system.The study was conducted to explore the prevalence and reactivation of CMV and EBV antibodies in COVID-19 patients group in comparison to healthy group and to investigate the association between the presence of these viruses with each of severity of disease and oral hygiene. Materials and Methods: Eighty Five subjects were participated in this case control study (5

Microorganisms establish both structural and functional construction in the marine environment, despite scientific advances, the identification of marine bacterial species is still considered as a common challenge in microbiology. Nevertheless, the present study aims to make an effort, although it seems modest, but it could establish a basis for studying the bacterial diversity in the Iraqi marine area, because of what this aspect entails of the poverty of studies related to this aspect in the studied area. The current results show the marine studied area are classified within worming area, where the average temperature ranged from 23.17 to 26.17 ºC. The recorded number of bacteria was increased with temperature increasing (0.210, 0.250

In this paper we used frequentist and Bayesian approaches for the linear regression model to predict future observations for unemployment rates in Iraq. Parameters are estimated using the ordinary least squares method and for the Bayesian approach using the Markov Chain Monte Carlo (MCMC) method. Calculations are done using the R program. The analysis showed that the linear regression model using the Bayesian approach is better and can be used as an alternative to the frequentist approach. Two criteria, the root mean square error (RMSE) and the median absolute deviation (MAD) were used to compare the performance of the estimates. The results obtained showed that the unemployment rates will continue to increase in the next two decade

Abstract:

      In this research we discussed the parameter estimation and variable selection in Tobit quantile regression model in present of multicollinearity problem. We used elastic net technique as an important technique for dealing with both multicollinearity and variable selection. Depending on the data we proposed Bayesian Tobit hierarchical model with four level prior distributions . We assumed both tuning parameter are random variable and estimated them with the other unknown parameter in the model .Simulation study was used for explain the efficiency of the proposed method and then we compared our approach with (Alhamzwi 2014 & standard QR) .The result illustrated that our approach

The major goal of this research was to use the Euler method to determine the best starting value for eccentricity. Various heights were chosen for satellites that were affected by atmospheric drag. It was explained how to turn the position and velocity components into orbital elements. Also, Euler integration method was explained. The results indicated that the drag is deviated the satellite trajectory from a keplerian orbit. As a result, the Keplerian orbital elements alter throughout time. Additionally, the current analysis showed that Euler method could only be used for low Earth orbits between (100 and 500) km and very small eccentricity (e = 0.001).