My research tagged [the lights of the statement in the first part of the Koran] came to show that the dear book was developed according to a precise linguistic system is not increased by a word or letter or movement - Aldmh and Kira and the hole - and does not lack anything of it except with the wisdom required by the meanings of the Koranic text or Sura generally . The Koran does not come falsehood from his hands or from behind it is infallible and preserved; because it was revealed by the sage Hamid Hamid ﭽﮗ ﮘ ﮙ ﮚ ﮛ ﮜ ﮝ ﮞ ﭼ [stone]. The Qur'an is safe from any verbal or moral dominance and dominates all the heavenly books and exists at any time and place that speaks the truth ﭽ ﯛ ﯜ ﯝ ﯞ ﯟ ﯹ ﯺﭼ [The

Quran is a basic reference of production it is as a source to all sciences, Ayat of Quran would mention the importance of benefits of animals.  Quran contain full surrat named in animal names as Al-Baqara that is to clarify its benefits and importance in human’s life.

The study included examination of three types of different origin and orange juice at the rate of recurring per sample, the results showed that the highest rates of acid (pH) in the A and juice were (4). And salts of calcium is 120 ppm in juice C and 86 ppm of magnesium in the juice B, for heavy metals the highest rate of lead .18 recorded ppm in juice B, 1.32 ppm of copper in juice A, 5 ppm of iron in the juice B, 1.3 ppm of zinc in the juice B, 0.05 ppm of aluminum in each of the sappy B and A, 0.02 ppm of cobalt in the juice B, 0.3 ppm of nickel in the juice B, 170.6 ppm sodium in C juice, but for the acids, organic that the highest rates were 3.2 part Millions of acid in the juice owner a, 260 ppm of the acid in the juice the ascorbi

<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c

It takes a lot of time to classify the banana slices by sweetness level using traditional methods. By assessing the quality of fruits more focus is placed on its sweetness as well as the color since they affect the taste. The reason for sorting banana slices by their sweetness is to estimate the ripeness of bananas using the sweetness and color values of the slices. This classifying system assists in establishing the degree of ripeness of bananas needed for processing and consumption. The purpose of this article is to compare the efficiency of the SVM-linear, SVM-polynomial, and LDA classification of the sweetness of banana slices by their LRV level. The result of the experiment showed that the highest accuracy of 96.66% was achieved by the

The Artificial Neural Network methodology is a very important & new subjects that build's the models for Analyzing, Data Evaluation, Forecasting & Controlling without depending on an old model or classic statistic method that describe the behavior of statistic phenomenon, the methodology works by simulating the data to reach a robust optimum model that represent the statistic phenomenon & we can use the model in any time & states, we used the Box-Jenkins (ARMAX) approach for comparing, in this paper depends on the received power to build a robust model for forecasting, analyzing & controlling in the sod power, the received power come from

        Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and

Objective: The present study aimed to shed light on the role of narghileh and cigarette smoking on immunity status of oral cavity by assess (C3 complement component, Immunoglobulin A, Total protein, α-Amylase and EBV IgG antibody). Method: Saliva levels in two smokers groups the first include 28 narghileh smokers and the second include 32 narghileh and cigarette smokers as well as 30 non-smokers consider as control. Results: As compared control, the levels of C3, IgA and total protein were significantly decreased, and the highest decreased was observed in saliva of narghileh and cigarette smokers, the result was (C3= 0.400±0.194 µg vs. 9.728±3.561 µg; IgA= 2.460±0.492 mg/dl vs. 5.048±0.937 mg/dl; Total protein= 170.20±45.93 mg% vs.

Abstract. In this scientific work, we investigate the problem of the practical necessity of achieving the adequacy of translation activities with active translation from Russian into Arabic in various fields of translation. Based on the material of the latest suffix vocabulary, a serious attempt is made to clarify and specify the rules for the development of translator's intuition when translating from Russian into Arabic and vice versa. Based on the material collected by the latest suffix vocabulary, we try to make an attempt to reveal the role of suffix word creation in highlighting the general rules for achieving translation equivalence. The paper examines the process of creating words in multi-family languages, the difference between th

Developing an efficient algorithm for automated Magnetic Resonance Imaging (MRI) segmentation to characterize tumor abnormalities in an accurate and reproducible manner is ever demanding. This paper presents an overview of the recent development and challenges of the energy minimizing active contour segmentation model called snake for the MRI. This model is successfully used in contour detection for object recognition, computer vision and graphics as well as biomedical image processing including X-ray, MRI and Ultrasound images. Snakes being deformable well-defined curves in the image domain can move under the influence of internal forces and external forces are subsequently derived from the image data. We underscore a critical appraisal