The aim of this paper is to derive a posteriori error estimates for semilinear parabolic interface problems. More specifically, optimal order a posteriori error analysis in the - norm for semidiscrete semilinear parabolic interface problems is derived by using elliptic reconstruction technique introduced by Makridakis and Nochetto in (2003). A key idea for this technique is the use of error estimators derived for elliptic interface problems to obtain parabolic estimators that are of optimal order in space and time.

تعتبر لعبة كرة اليد من الالعاب الفرقية، وان هذه اللعبة تستند الى قاعدة اساسية وهي الاداء الصحيح للمهارات، وللتقدم في هذه اللعبة يجب تعلم وأتقان اداء المهارات للوصول الى مستوى افضل للتعلم، من خلال الدور الذي يؤديه اسلوب نموذج كولب لأنماط التعلم (التكيفي) الذي يعمل على تحديد اسلوب التفكير والمفضل لكل فرد وتاثيره في تعلم مهارة الطبطبة للطالبات، اذ يعمل على ايصال المعلومات والافكار الخاصة باداء المهارة وحس

The study tackles the market orientation and the organizational learning as independent variables each included three sub-dimensions, and the variable of business performance as affiliated variable. These three variables have interacted to form the framework around which the study revolves. Since the banking sector has become an important part of which service sector is made, as well as it represents the basic pivot for the process of building and the development of the economies of countries, the Iraqi banking sector have been taken to be the sample of this study. A nonrandom sample of nine Iraqi banks was chosen, including four state banks (Al-Rafdain, Al-RaSheed, Industrial Bank, and Agricultural), and five private banks (Bagh

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 .

تُعد دراسة أعلام الفكر العربي والإسلامي من أهم الدراسات التاريخية ولا يمكن للأمم المتحضرة أن تنسى علمائها ومفكريها لما لهم من دور كبير في حاضر الأمة ومستقبلها و تاريخنا الإسلامي يحفل بالعديد من العلماء ورجال المعرفة  الذين ساعدوا على تقدم ورقي العرب والمسلمين على الأمم الأخرى0

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

     This article reviews a decade of research in transforming smartphones into smart measurement tools for science and engineering laboratories. High-precision sensors have been effectively utilized with specific mobile applications to measure physical parameters. Linear, rotational, and vibrational motions can be tracked and studied using built-in accelerometers, magnetometers, gyroscopes, proximity sensors, or ambient light sensors, depending on each experiment design. Water and sound waves were respectively captured for analysis by smartphone cameras and microphones. Various optics experiments were successfully demonstrated by replacing traditional lux meters with built-in ambient light sensors. These smartphone-based measurement

Heart disease identification is one of the most challenging task that requires highly experienced cardiologists. However, in developing nations such as Ethiopia, there are a few cardiologists and heart disease detection is more challenging. As an alternative solution to cardiologist, this study proposed a more effective model for heart disease detection by employing random forest and sequential feature selection (SFS). SFS is an effective approach to improve the performance of random forest model on heart disease detection. SFS removes unrelated features in heart disease dataset that tends to mislead random forest model on heart disease detection. Thus, removing inappropriate and duplicate features from the training set with sequential f

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