In this paper, the solar surface magnetic flux transport has been simulated by solving the diffusion–advection equation utilizing numerical explicit and implicit methods in 2Dsurface. The simulation was used to study the effect of bipolar tilted angle on the solar flux distribution with time. The results show that the tilted angle controls the magnetic distribution location on the sun’s surface, especially if we know that the sun’s surface velocity distribution is a dependent location. Therefore, the tilted angle parameter has distribution influence.

The Machine learning methods, which are one of the most important branches of promising artificial intelligence, have great importance in all sciences such as engineering, medical, and also recently involved widely in statistical sciences and its various branches, including analysis of survival, as it can be considered a new branch used to estimate the survival and was parallel with parametric, nonparametric and semi-parametric methods that are widely used to estimate survival in statistical research. In this paper, the estimate of survival based on medical images of patients with breast cancer who receive their treatment in Iraqi hospitals was discussed. Three algorithms for feature extraction were explained: The first principal compone

The aim of this research is to diagnose the impact of competitive dimensions represented by quality, cost, time, flexibility on the efficiency of e-learning, The research adopted the descriptive analytical method by identifying the impact of these dimensions on the efficiency of e-learning, as well as the use of the statistical method for the purpose of eliciting results. The research concluded that there is an impact of the competitive dimensions on the efficiency of e-learning, as it has been proven that the special models for each of the research hypotheses are statistically significant and at a level of significance of 5%, and that each of these dimensions has a positive impact on the dependent variable, and the research recommended

This study examines the dynamic relationship between stock market and economic activity in the United States to verify the possibility of using financial indicators to monitor the turning points in the expected path of future economic activity. Has been used methodology (Johansen - Juselius) for the Co-integration and causal (Granger) to test the relationship between the (S & P 500 , DJ) index  and gross domestic product (GDP) in the United States for the period
(1960-2009). The results of the analysis revealed the existence of a causal relationship duplex (two-way) between the variables mentioned. which means the possibility of the use stock market indicators to pre