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.

Abstract The current study aims to 1) identify the prevalent Enneagram personality types and the academic self among the sixth-grade students of the distinguished secondary schools; 2) the differences of relationship between the Enneagram personality types and the academic self-concept based on gender; 3) identify the correlation between the Enneagram personality types and the academic self-concept; and 4) identify the contribution of each type of personality types to the academic self-concept. To this end, two instrument were used to collect the data: Riso-Hudson’s scale,1995 was administered to measure enneagram types which had translated to the Arabic language by ( al-yassery,2004), the other instrument was constructed by the author de

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

هدف هذا البحث الى استعمال الأسلوب الرياضي أسلوب التحليل الهرمي وتطبيقه وفق ابعاد بطاقة الاداء المتوازن في تقييم الأداء الاستراتيجي في الهيئة العامة للأثار والتراث، وتمثلت أدوات البحث باستعمال استمارات التحليل الهرمي وطبقت على معايير بطاقة الأداء المتوازن المتمثلة في (المالي، الزبائن، العمليات الداخلية، والتعلم والنمو)، وتم استهداف عينة قصدية متمثلة في رئيس الهيئة والمدراء العامون بعض من مدراء الأقسام ال

In the last two decades, arid and semi-arid regions of China suffered rapid changes in the Land Use/Cover Change (LUCC) due to increasing demand on food, resulting from growing population. In the process of this study, we established the land use/cover classification in addition to remote sensing characteristics. This was done by analysis of the dynamics of (LUCC) in Zhengzhou area for the period 1988-2006. Interpretation of a laminar extraction technique was implied in the identification of typical attributes of land use/cover types. A prominent result of the study indicates a gradual development in urbanization giving a gradual reduction in crop field area, due to the progressive economy in Zhengzhou. The results also reflect degradati

The research deals with the Presidents of the Christians who called themselves (Ghaltka) in the book titled (orient chirsy patriarchs) that talked about their scientific practical biography adding to) that their completeness on the position of Ghaltka with its decrees and caliphs who were contemporaries to them ,as well as their places, deaths, cemeteries and their accomplishments In accordance with the powers granted to them and also it mentions the situation of The Abbasid caliphate with them and with the sons of their sect .

Problems in the Translation of Spanish phraseology to Arabic in the Literary Text (A Comparative Study from the Perspective translatological)

Abstract

One of the most common problems facing the translator is the identification and subsequent search for correspondences of phraseological units. The importance of the phraseological competence in a foreign language is widely recognized by many authors (Howarth, Corpas Pastor, Pamies Bertran, to name a few).

We must lose our fear to recognize that the domain of the phraseology is the highest level of command of any language. The objective of the present study is to clarify the differences in UFS Spanish to Arabi

Abstract:                                                                                                      

         The research aims to measure the impact of infor