Those interested in the educational process and lesson management sought to invest the information experience with industrial intelligence and technology because of its importance in increasing the effectiveness of lesson management and developing the creative capabilities of the teacher in directing and managing his lesson. Field research for sports educational institutions that are interested in managing the lesson and preparing mathematical teaching cadres is an important issue and necessary means for identifying the most important phenomena that accompany the process of managing the educational process, as the teacher's success in providing the appropriate conditions to provide rich and influencing experiences in managing and directing

We have provided in this research model multi assignment  with  fuzzy function goal has been to build programming model is correct Integer Programming fogging  after removing the case from the objective function data and convert it to real data .Pascal triangular graded mean using Pascal way to the center of the triangular.

The data processing to get rid of the case fogging which is surrounded by using an Excel 2007 either model multi assignment  has been used program LNDO to reach the optimal solution, which represents less than what can be from time to accomplish a number of tasks by the number of employees on the specific amount of the Internet, also included a search on some of the

Kurdish language multifunctional morphemes indicate the different functional morphological, syntactical, and semantic tasks of the morphemes. The present study discusses the multifunctional task of the Morpheme Le in Kurdish Language. The Morpheme Le has marginally been included in other studies, yet up to the present times, there has not been a research inclusively dedicated to thoroughly discuss and clarify its multifunctional aspects. The  present study is divided into two chapters:

       Chapter one discusses the theoretical aspect of chapter two that is entirely concerned with the practical aspect of the morpheme Le. The first part of chapte

The main reason for the emergence of a deepfake (deep learning and fake) term is the evolution in artificial intelligence techniques, especially deep learning. Deep learning algorithms, which auto-solve problems when giving large sets of data, are used to swap faces in digital media to create fake media with a realistic appearance. To increase the accuracy of distinguishing a real video from fake one, a new model has been developed based on deep learning and noise residuals. By using Steganalysis Rich Model (SRM) filters, we can gather a low-level noise map that is used as input to a light Convolution neural network (CNN) to classify a real face from fake one. The results of our work show that the training accuracy of the CNN model

Objectives: The study objectives are to determine the impact of education program upon the academic nurses'
practice concerning documentation of nursing sheets, and to find out the relationship between nurses knowledge
and their demographic characteristics, which include age, sex, and years of experience in medical and surgical
wards.
Methodology: A quasi- experimental study was carried out at the medical and surgical wards in teaching
hospitals in Sulaimani governorate from the beginning of March up to June 2007٠
To reach the objectives of the study anon-probability (purposive) sample of (25) academic nurses who work in
the medical and surgical wards in teaching hospitals.
The data were collected through the use

In this paper, some estimators of the unknown shape parameter and reliability function  of Basic Gompertz distribution (BGD) have been obtained, such as MLE, UMVUE, and MINMSE, in addition to estimating Bayesian estimators under Scale invariant squared error loss function assuming informative prior represented by Gamma distribution and non-informative prior by using Jefferys prior. Using Monte Carlo simulation method, these estimators of the shape parameter and R(t), have been compared based on mean squared errors and integrated mean squared, respectively