The main objective of the present work is to find a method increases the efficiency of the airfoil that is used for blade in wind turbine, wing in aircraft, propeller and helicopter (like NACA 4412). By overcoming the separation of flow at high angle of attacks, a slotted airfoil had been used and solved numerically through connecting the pressure side in the bottom surface with the suction side in the top surface of the airfoil to energize the separated flow. Slot exit, width and slope were considered as a parameters of slot configuration to determine the effective design of consideration. Reynolds number was taken as [1.6 x106 ] and the angle of attacks were ranged from (0o - 20o ). The numerical solution with Ansys Fluent commercial prog

Background: Denture relining is the process of resurfacing of the tissue side of the ill fitting denture, the bond strength at the relining-denture base interface is most important for denture durability.The aim of present study was to evaluate the shear bond strength between the thermosens as relining material and different denture base materials that bonded by thermo fusing liquid. As this corrective procedureis the common chair side procedure in the dental clinic. Material and method: Sixty samples were prepared and divided into three main groups according to the type of denture base materials.Group (A) referred to the heat cure acrylic samples which consisted of 20 samples. Group (B) referred to the high impact acrylic samples which con

شَهِدَت منطقة الخليج العربي والسَّاحِل العُماني تصاعد مُستوى الحِراك الشعبي، والمُطالبات بتحقيق الاِستقلال التام، وإنهاء الاِلتِزامات والاِرتِباطات الدولـيَّة سواء كانت في إطار الحِماية أو الاِستِشارة أو الصِّداقة، وأصبحت واجِهات ملحوظة من قِبل الفِئات المُـثـقَّـفة في بدايات العقد الثاني من القرن العشرين، وعبَّرت فيها القِوى الوطنيَّة عن حاجاتها في إجراء عملـيَّات التغيير والتحوّل الاِجتِماعي وعلى

The proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue

Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col

This study aimed identify the teachers of sociology. In the development of creative thinking. I have students in middle school .llvra literary. In schools. Second Karkh From the perspective of the teachers and the students themselves  numbered (41), a teacher and a school. As The study population   encompassed of some students the fourth and fifth preparatory stage in the Karkh II schools, totaling 200 male and female students. As the study sample were consisted of (7) and a teacher (34) and accented (85) of male students (115) were female student The researcher the questionnaire which consisted of (39) items And to achieve the objectives of the study it was ascertained sincerity And stability. And

Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To