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E-Learning and Its Relationship with Academic Passion among Middle School Students
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Abstract

The current research aims to identify the level of E-learning among middle school students, the level of academic passion among middle school students, and the correlation between e-learning and academic passion among middle school students. In order to achieve the objectives of the research, the researcher developed two questionnaires to measure the variables of the study (e-learning and study passion) among students, these two tools were applied to the research sample, which was (380) male and female students in the first and second intermediate classes. The research concluded that there is a relationship between e-learning and academic passion among students.

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Publication Date
Fri Mar 31 2023
Journal Name
Tikrit Journal Of Administrative And Economic Sciences
الانفاق العام على التعليم ودوره في تحسين مؤشرات راس المال البشري التعليمية في العراق للمدة 2005-2020 " دراسة تحليلية "
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يتمتع العراق بموارد بشرية هائلة حيث يعد من البلدان الفتية، إلا أنه يعاني من أزمة رأس مال بشري تغذيها أزمة التعليم، ولكون التعليم أبرز مكونات رأس المال البشري فقد ذلك بشكل كبير على مؤشر رأس المال البشري في العراق، من هذا المنطلق وللدور الكبير الذي يلعبه الانفاق العام في أي مجال، جاءت هذه الدراسة للبحث في موضوع "الانفاق العام على التعليم ودوره في تحسين مؤشرات راس المال البشري التعليمية في العراق"، حيث هدف ه

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Publication Date
Wed Mar 30 2022
Journal Name
Journal Of Educational And Psychological Researches
درجة استخدام معلمات الرياضيات لأدوات التقويم البديل من وجهة نظرهن
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هدفت هذه الدراسة إلى التعرف على درجة استخدام معلمات الرياضيات لأدوات التقويم البديل من وجهة نظرهن، وتحديد إذا كانت توجد فروق ذات دلالة إحصائية تعزى لمتغير سنوات الخبرة التدريسية، ولتحقيق أهداف الدراسة تم استخدام المنهج الوصفي. وتكونت عينة الدراسة من 37 معلمة من معلمات الرياضيات في الحلقة الثانية من التعليم الأساسي في محافظة ظفار في سلطنة عُمان. وتم بناء استبانة مكونة من (21) فقرة موزعة على (4) محاور تمثل أدوات

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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
EVALUATION OF ELECTRONIC GOVERNMENT SECURITY ISSUES APPLIED TO COMPUTER CENTER OF BAGHDAD UNIVERSITY (CASE STUDY)
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Information security contributes directly to increase the level of trust between the government’s departments by providing an assurance of confidentiality, integrity, and availability of sensitive governmental information. Many threats that are caused mainly by malicious acts can shutdown the egovernment services. Therefore the governments are urged to implement security in e-government projects.
Some modifications were proposed to the security assessment multi-layer model (Sabri model) to be more comprehensive model and more convenient for the Iraqi government. The proposed model can be used as a tool to assess the level of security readiness of government departments, a checklist for the required security measures and as a commo

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
COVID-19 Diagnosis System using SimpNet Deep Model
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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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Publication Date
Wed Nov 29 2023
Journal Name
International Journal Of Advances In Scientific Research And Engineering (ijasre), Issn:2454-8006, Doi: 10.31695/ijasre
Yolo Versions Architecture: Review
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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

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Publication Date
Tue Aug 31 2021
Journal Name
Inmateh Agricultural Engineering
DETERMINING THE EFFICIENCY OF A SMART SPRAYING ROBOT FOR CROP PROTECTION USING IMAGE PROCESSING TECHNOLOGY
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A system was used to detect injuries in plant leaves by combining machine learning and the principles of image processing. A small agricultural robot was implemented for fine spraying by identifying infected leaves using image processing technology with four different forward speeds (35, 46, 63 and 80 cm/s). The results revealed that increasing the speed of the agricultural robot led to a decrease in the mount of supplements spraying and a detection percentage of infected plants. They also revealed a decrease in the percentage of supplements spraying by 46.89, 52.94, 63.07 and 76% with different forward speeds compared to the traditional method.

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Scopus (8)
Crossref (4)
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Publication Date
Sun Jan 01 2023
Journal Name
International Journal Of Advances In Scientific Research And Engineering
Yolo Versions Architecture: Review
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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

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Publication Date
Fri Feb 21 2025
Journal Name
Applied System Innovation
Utilizing Soft Computing Techniques to Estimate the Axial Permanent Deformation of Asphalt Concrete
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Rutting is a crucial concern impacting asphalt concrete pavements’ stability and long-term performance, negatively affecting vehicle drivers’ comfort and safety. This research aims to evaluate the permanent deformation of pavement under different traffic and environmental conditions using an Artificial Neural Network (ANN) prediction model. The model was built based on the outcomes of an experimental uniaxial repeated loading test of 306 cylindrical specimens. Twelve independent variables representing the materials’ properties, mix design parameters, loading settings, and environmental conditions were implemented in the model, resulting in a total of 3214 data points. The network accomplished high prediction accuracy with an R

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Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Skull Stripping Based on the Segmentation Models
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Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither no

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Publication Date
Wed Jun 12 2019
Journal Name
Dirasat: Human And Social Sciences
Teaching by pause technique in the classroom
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Communication represents the essence of language learning. Since the unspecified evolution of conveying information, human beings have been employing the main constituents of language with short pauses. Although the punctuation marks necessitate short expressions among thought group of words in writing, human language demand for understanding how and when to pause orally. This paper presents the pause technique in the classroom. It signifies the relation between pausing and lecturing in the class and determines its sufficient time-management to interact with college learners of different specializations. The conduct study reviewed teaching pause technique in the empirical studies at Special Education and Communication Disorders of Pennsylva

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