Arabic calligraphy is one of the ancient arts rooted in history, And that he grew up conflicting views and writings addressed as a, communication tool for the linguistic The teaching calligraphy note an art and science because it depends on the fixed assets and precise rules in his art because centered Beauty It targets teach Arabic calligraphy speed as the education and recitation helps to write fast Which have great interest in the field of education and in life both Also accompanied Arabic calligraphy and scientific renaissance significant knowledge in the Ara

Interest in the teaching profession is one of the most important steps on the road to education reform to develop the quality of education is not only through the teacher's professional competencies required, interest in the teaching profession in any society stems from fingerprints left by the teacher on his behavior and morals and their minds and their personalities. Today we are going to provide scientific, technical and research is enormous, we need more powerful skills and ways of thinking that must be acquired by the teacher. The current search is gaining importance in terms of:

1. This is the first of its kind on the researcher's knowledge _ which deals with the modern trends in t

Abstract:

Robust statistics Known as, resistance to errors caused by deviation from the stability hypotheses of the statistical operations (Reasonable, Approximately Met, Asymptotically Unbiased, Reasonably Small Bias, Efficient ) in the data selected in a wide range of probability distributions whether they follow a normal distribution or a mixture of other distributions deviations different standard .

power spectrum function lead to, President role in the analysis of Stationary random processes, form stable random variables organized according to time, may be discrete random variables or continuous. It can be described by measuring its total capacity as function in frequency.

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Estimation the unknown parameters of a two-dimensional sinusoidal signal model is an important and a difficult problem , The importance of this model  in modeling Symmetric gray- scale texture image . In this paper, we propose employment Deferential Evaluation algorithm and the use of Sequential approach to estimate the unknown frequencies and amplitudes of the 2-D sinusoidal components when the signal is affected by noise. Numerical simulation are performed for different sample size, and various level of standard deviation to observe the performance of this method in estimate the parameters of 2-D sinusoidal signal model , This model was used for modeling  the Symmetric gray scale texture image and estimating by using

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Gross domestic product (GDP) is an important measure of the size of the economy's production. Economists use this term to determine the extent of decline and growth in the economies of countries. It is also used to determine the order of countries and compare them to each other. The research aims at describing and analyzing the GDP during the period from 1980 to 2015 and for the public and private sectors and then forecasting GDP in subsequent years until 2025. To achieve this goal, two methods were used: linear and nonlinear regression. The second method in the time series analysis of the Box-Jenkins models and the using of statistical package (Minitab17), (GRETLW32)) to extract the results, and then comparing the two methods, T

The research aimed to identify and build two specialized scales for cognitive load and mental stress and to identify the level of each of them among 110-meter steeplechase runners among youth, and to prepare a psychological counseling approach to reduce the level of cognitive load and mental stress among 110-meter steeplechase runners among youth, so that the two research hypotheses are that there are differences. There are statistically significant differences between the results of the pre- and post-tests of the experimental group in measuring cognitive load. There are statistically significant differences between the results of the pre- and post-tests of the experimental group in measuring mental stress. The experimental method w