تلعب الاعتمادات المستندية دوراً كبيراً وخطيراً في التجارة الدولية باعتبارها إحدى أوسع أدوات الدفع انتشاراً في العالم سواءاً كان ذلك بالنسبة للمستورد أم للمصدر وتغطيتها للمخاطر المحتملة لكلا الطرفين، فهي تؤمن للمصدر استلام قيمة البضاعة بالكامل عند تنفيذها لشروط العقد، ويسمح للمستورد بعدم الدفع إلا بعد إتمام شحن البضاعة وتقديم المستندات المطلوبة واستلامها.

وتقوم المصارف التجارية المحل

ترك السلطان عبدالحميد الثاني بصماتهُ على أخاديد الزمان وعلى خارطة المشرق العربي الخاضع للسيطرة العثمانية أنذاك ، لكونهُ أهم شخصية أسلامية غير عربية واجهت الخطر الصهيوني ومحاولاتهم الإستيطانية في مشرق الوطن العربي ، على الرغم من صعوبة الظروف التي كانت تمر بها الدولة العثمانية داخليا ً وخارجيا ً، بما فيها من أطماع اقتسامها بين الاوربين ولذا سموها بالرجل المريض .

Eight different Dichloro(bis{2-[1-(4-R-phenyl)-1H-1,2,3-triazol-4-yl-κN3]pyridine-κN})iron(II) compounds, 2–9, have been synthesised and characterised, where group R=CH3 (L2), OCH3 (L3), COOH (L4), F (L5), Cl (L6), CN (L7), H (L8) and CF3 (L9). The single crystal X-ray structure was determined for the L3 which was complemented with Density Functional Theory calculations for all complexes. The structure exhibits a distorted octahedral geometry, with the two triazole ligands coordinated to the iron centre positioned in the equatorial plane and the two chloro atoms in the axial positions. The values of the FeII/III redox couple, observed at ca. −0.3 V versus Fc/ Fc+ for complexes 2–9, varied over a very small potential range of 0.05 V.

       In this paper, we focus on designing feed forward neural network (FFNN) for solving Mixed Volterra – Fredholm Integral Equations (MVFIEs) of second kind in 2–dimensions. in our method, we present a multi – layers model consisting of a hidden layer which has five hidden units (neurons) and one linear output unit. Transfer function (Log – sigmoid) and training algorithm (Levenberg – Marquardt) are used as a sigmoid activation of each unit. A comparison between the results of numerical experiment and the analytic solution of some examples has been carried out in order to justify the efficiency and the accuracy of our method.

New Schiff base [3-(3-acetylthioureido)pyrazine-2-carboxylic acid][L] has been prepared through 2 stages, the chloro acetyl chloride has been reacting with the ammonium thiocyanate in the initial phase for producing precursor [A], after that [A] has been reacting with the 3-amino pyrazine-2-carboxilic acid to provide a novel bidentate ligand [L], such ligand [L] has been reacting with certain metal ions in the Mn(II), VO(II), Ni(II), Co(II), Zn(II), Cu(II), Hg(II), and Cd(II) for providing series of new metal complexes regarding general molecular formula [M(L)2XY], in which; VO(II); X=SO4,Y=0, Co(II), Mn(II), Cu(II), Ni(II), Cd(II), Zn(II), and Hg(II); Y=Cl, X=Cl. Also, all the compounds were characterized through spectroscopic techniques [

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

Deep learning techniques are applied in many different industries for a variety of purposes. Deep learning-based item detection from aerial or terrestrial photographs has become a significant research area in recent years. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed.  A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles and classification probabilities for an image. In layman's terms, it is a technique for instantly identifying and recognizing

Deep learning techniques are used across a wide range of fields for several applications. In recent years, deep learning-based object detection from aerial or terrestrial photos has gained popularity as a study topic. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed. A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles andclassification probabilities for an image. In layman's terms, it is a technique for instantly identifying and rec

يهدف البحث الى تطبيق تزامن تصميم عملية انتاج معجون الاسنان في مصنع المامون التابع للشركة العامة للمنتوجات الغذائية مع نظام تكاليف الجودة المطبق في الشركة لتحقيق الميزة التنافسية. وتمثلت مشكلة البحث في أن الشركة عينة البحث لا تستخدم نظام تكاليف الجودة بالتزامن مع تصميم عملية إنتاج هذا المنتج لاغراض تحقيق الميزة التنافسية حيث تواجه منتجات الشركة منافسة عالية في الاسواق المحلية. إن الشركة تطبق نظام تكاليف الج