Abstract

 The miraculous of al-Quran has been surrounded by the attention of scholars, as it is the one that has astonished the rhetoricians with its eloquence. So , they paid attention to every part of it  and hugely they studied it with accuracy in respect to its Surah  ad Ayahs.   It is considered the most important source from which Arab scholars and early grammarians drew, given their unanimity that it is the highest degree of eloquence and the best record of the common literary language.

Among these sciences is the science of Grammar, and without Qur’an, this science would not have emerged, which later had control over every science of Arabic

Abstract

     Machining residual stresses correlate very closely with the cutting parameters and the tool geometries. This research work aims to investigate the effect of cutting speed, feed rate and depth of cut on the surface residual stress of steel AISI 1045 after face milling operation. After each milling test, the residual stress on the surface of the workpiece was measured by using X-ray diffraction technique. Design of Experiment (DOE) software was employed using the response surface methodology (RSM) technique with a central composite rotatable design to build a mathematical model to determine the relationship between the input variables and the response. The results showed that both

This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur

A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m

This research deals with the use of a number of statistical methods, such as the kernel method, watershed, histogram, and cubic spline, to improve the contrast of digital images. The results obtained according to the RSME and NCC standards have proven that the spline method is the most accurate in the results compared to other statistical methods.

The present search aims to develop a test for selective attention, cognitive load and thinking mistakes and measuring these concepts among Baghdad university students. To make a comparison between the selective attention, cognitive load, and the mistakes of thinking among students in term of gender. To identify the relationship among the selective attention, cognitive load and the mistakes of thinking of university students. To achieve these purposes, the searcher has developed a test for selective attention, cognitive load, and the mistakes of thinking. Then, these tools were applied to a sample of (200) university students were selected from (21) college. The researcher used t-test of one sample, t-test of two independent