The concept of intertextuality was one of the problems that occupied the attention of critics and critics in targeting the structure of textual intertextuality between texts and their overlap in the process of producing meaning. Until intertextuality became a stable term and it can be monitored in the structure of the theatrical text and determining the mechanisms of this intertextuality between texts through fields and classifications agreed upon by the most important critics who wrote and considered intertextuality. Perhaps our previous research (the approach of exposure in the epistemological hallway to intertextuality) was an attempt to interview a terminology, which the researcher intended to monitor, through the mechanisms of inter

That the main feature of  the economics many countries in general is a tendency towards defining the role of the public sector in economic activity and the tendency towards encourage the private sector to investment in public projects especially in countries those tendency towards market economy actually.

That increased economic development proven failure in achieving more economic growth both individually in many countries especially developing countries socialist, by researchers this led one way or another to direction of corrective reforms in their economic was one of them in Transformation of public companies into Shareholding companies contributes to the public sector in resources and expertise

The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow

In this paper we estimate the coefficients and scale parameter in linear regression model depending on the residuals are of type 1 of extreme  value distribution for the largest values . This can be regard as an improvement for the studies with the smallest values . We study two estimation methods ( OLS  & MLE ) where we resort to Newton – Raphson (NR) and Fisher Scoring methods to get MLE estimate because the difficulty of using the usual approach with MLE . The relative efficiency criterion is considered beside to the statistical inference procedures for the extreme value regression model of type 1 for largest values . Confidence interval , hypothesis testing for both scale parameter and regression coefficients

It is a moral presumption that includes the object for its sake, and it is called the object for it or the object for its sake, which is the present tense after (lam, ki, fa, willn, and then), and it is not an excuse for the occurrence of the matter (1), and it requires a connection between the two sides of (a cause with a cause) united by a reason for a specific purpose (2). The object has a reason or an excuse, because it is an explanation of what came before it, of the cause. The reason for the occurrence of the action, being the motive for causing the action and the bearer of it (3), indicates that the infinitive is restricted to a special reason. So if I said: (I came to you with the hope of honoring you), then I attributed the coming

A condense study was done to compare between the ordinary estimators. In particular the maximum likelihood estimator and the robust estimator, to estimate the parameters of the mixed model of order one, namely ARMA(1,1) model.

Simulation study was done for a varieties the model.  using: small, moderate and large sample sizes, were some new results were obtained. MAPE was used as a statistical criterion for comparison.

In this paper, a compact genetic algorithm (CGA) is enhanced by integrating its selection strategy with a steepest descent algorithm (SDA) as a local search method to give I-CGA-SDA. This system is an attempt to avoid the large CPU time and computational complexity of the standard genetic algorithm. Here, CGA dramatically reduces the number of bits required to store the population and has a faster convergence. Consequently, this integrated system is used to optimize the maximum likelihood function lnL(φ1, θ1) of the mixed model. Simulation results based on MSE were compared with those obtained from the SDA and showed that the hybrid genetic algorithm (HGA) and I-CGA-SDA can give a good estimator of (φ1, θ1) for the ARMA(1,1) model. Anot