This study aims to identify the degree of students of Princess Rahma University College owning e-learning skills related to MOODLE as they perceived in the of light Corona crisis. The researchers' questionnaire consisted of (37) items, distributed in three areas of e-learning skills related to the MOODLE on (147) students were chosen randomly. The results of the study showed that the degree of students 'possession of e-learning skills related to the MOODLE was significant. The results also revealed that there were statistically significant differences in the degree of students' possession of electronic learning skills related to the MOODLE due to sex in favor of females. Finally, there were no statistically significant differences in the degree of students 'possession of e-learning skills related to the MOODLE due to the variable of specialization and academic level.
يهدف هذا البحث الى تقويم الأنشطة والأسئلة التقويمية المتضمنة في محتوى كتاب الحاسوب للصف الخامس الإعدادي وفق التفكير الإبداعي ومقترحات تطويرها، وذلك بالإجابة عن السؤال الآتي: ما نسبة توافر مهارات التفكير الإبداعي في الأنشطة والأسئلة التقويمية المتضمنة في محتوى كتاب الحاسوب المقرر لطلبة الصف الخامس الإعدادي (الاحيائي والتطبيقي، والادبي) من وزارة التربية العراقية/ المديرية العامة للمناهج في العام الدراسي (2
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The current study aims at identifying of the differences of life quality level for the academic instructors at Omar Al-Mukhtar University / Libya according to the city variable that the instructor belong to ( Libya, Iraq, Egypt ), and also according to gender Variable (Male - Female),To achieve the aims of study ,the researcher chose a sample consists of (210) instructors ( 170 males and 40 females) from four colleges at Omar Al- Mukhtar University/ Darna . The researcher built the scale of life quality which consists of (42) items in last version . The researcher has conducted the validity and reliability of the scale. and by using Analysis of Variance via (SPSS program). The research reaches the following results : 1-The life quality o
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ظلت رغبة الانسان في المعرفة وفهم الكون الذي يعيش فيه ، ملازمة له منذ المراحل الاولى لتطور البشرية ، فالانسان بما يتمتع به من امكانات وقدرات وطاقات كامنة استطاع عن طريق تفاعله واحتكاكه الدائم والمستمر والخلاق مع البيئة المحيطة به ان يلاحظ ، ويتخيل ويتذكر ويفكر ويخطط ويبتكر ، مستفيداً من اخطائه في التعرف عليها ، وفي زيادة قدرته على التحكم فيها وتحسينها وتطويره
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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.
... Show MoreAfter 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
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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
... Show MoreDeep 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
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