The study aimed to identify the use of the electronic concept maps method in learning some of the skills of the floor exercises in the artistic gymnastics for third graders ,as well as to identify the best group between the two research groups (experimental And the officer to learn and retain some of the skills of the floor exercises in the artistic gymnastics of the research subject , and the experimental method was used and included the sample research on students of the collage of Physical Education and Sports Sciences/University of Baghdad, third grade, and has selected (10) Students for each group of The experimental and controlling groups randomly by lottery and after the completion of the period of implementation of the experiment which lasted for 8 weeks and the reality of two educational units per week and the statistical package of social Sciences (SPSS) was used to address the results of the research, which included mean and Standard deviation and t.test for interrelated and unrelated samples a set of conclusions was reached, the most important of which was that the use of electronic concept maps and the traditional method had a positive effect on learning and retaining some of the skills of the floor exercises in the artistic gymnastics, but that effect two sets of research have varied, as the style of electronic concept maps exceeds the traditional method of learning skills under study .
<span lang="EN-US">This paper presents the comparison between optimized unscented Kalman filter (UKF) and optimized extended Kalman filter (EKF) for sensorless direct field orientation control induction motor (DFOCIM) drive. The high performance of UKF and EKF depends on the accurate selection of state and noise covariance matrices. For this goal, multi objective function genetic algorithm is used to find the optimal values of state and noise covariance matrices. The main objectives of genetic algorithm to be minimized are the mean square errors (MSE) between actual and estimation of speed, current, and flux. Simulation results show the optimal state and noise covariance matrices can improve the estimation of speed, current, t
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أن عملية التعلم لازالت تسير بنفس الاسلوب المتبع الذي لا يعتبر المتعلمة محور اساسي في عملية التعلم مما سبب ظهور الملل وانخفاض الرغبة لدى المتعلمات للتعلم لغياب الحافز, ولكون المهارات الاساسية بكرة السلة كالمناولة الصدرية والطبطبة بتغير الاتجاه والتصويب السلمي تعد من المهارات المهمة في اللعبة تم اجراء هذه الدراسة الذي يهدف الى اعداد منهج تعليمي قائم على انموذج التعلم البنائي والتعرف على تأثيره في بعض ا
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The investor needs to a clear strategy for the purpose of access to the financial market, that is, has a plan to increase The share of the profits thinking entrepreneur and new, and highlights the importance of this in that it sets for the investor when it goes to the market, and when it comes out of it, and at what price to buy or sell the stock, and what is the the amount of money it starts. Fortunately, he does not need to invent his own investment strategy, because over the years the development of effective methods of buying and selling, and once you understand how to work these methods investor can choose the most appropriate methods and adapted image that fit his style investment .
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يهدف البحث الى التعرف على بقاء اثر المعلومة عن طريق الاجابة عن السؤال: ما مدى بقاء اثر التعلم بين التعليم الالكتروني والتعليم الاعتيادي ( الحضوري )؟ تم تطبيق البحث في العام الدراسي( 2020-2021 م) في العراق. تم استخدام المنهج الوصفي بالاسلوب المقارن في عقد مقارنة بين التعليم الالكتروني والتعليم الاعتيادي. وقد تحدد مجتمع البحث لطلبة المرحلة الرابعة كلية التربية للعلوم الصرفة – ابن الهيثم واستخدمت العيتة من قسم
... Show Moreتبنت العديد من المؤسسات الأكاديمية التعلم الإلكتروني منذ سنوات ، وقد أثبت فاعليته في كثير من هذه المؤسسات لاسيما تلك المهتمة بتعلم اللغات الاجنبية. الا انه مع انتشار جائحة كورونا اصبح التعليم الالكتروني ضرورة ملحة في الجامعات في جميع أنحاء العالم ، بما في ذلك الجامعات العراقية. تهدف الدراسة الحالية إلى تقصي أثر هذا الوباء على التعلم الإلكتروني في أحدى الكليات العراقية . يفترض الباحث أن تقبل ال
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Emotion could be expressed through unimodal social behaviour’s or bimodal or it could be expressed through multimodal. This survey describes the background of facial emotion recognition and surveys the emotion recognition using visual modality. Some publicly available datasets are covered for performance evaluation. A summary of some of the research efforts to classify emotion using visual modality for the last five years from 2013 to 2018 is given in a tabular form.
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
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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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