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Associations Between Phonological Processing and Working Memory in Students with and without Reading disabilities in Basic Education Cycle One Schools in Muscat
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The study aimed to examine the phonological processing profile for students with and without reading disabilities in cycle 1 schools of basic education in the Governorate of Muscat, Sultanate of Oman. The study participants included 306 students, 165 students with reading disabilities and 141 students without reading disabilities. The Comprehensive Test of Phonological Processing (CTOPP) and Working Memory Test (WMT) were administered to the participants. The results of the study showed that the mean score of students without reading disabilities was higher than that of students of reading disabilities in all measures of phonological processing, and that there are statistically significant differences on the  case of students in all scales of composite phonological processing , and there are statistically significant differences for the grade on students' scores in the scales of phonological awareness, phonological memory, rapid naming and alternative scale of rapid naming . There are also statistically significant differences for the interaction between the grade and the case on the students' grades in the rapid naming, there is no statistically significant effect of gender, case-gender interaction, class-gender interaction, gender-case-grade interaction on students' scores on composite phonological processing scales. The results also resulted in statistically significant differences between students with reading disabilities and student without reading disabilities attributed to the interaction between the grade and the case, while there is no statistically significant effect of the interaction between the case and the gender and the interaction between the grade and the case and the gender in the sub-acoustic phonological processing scales. The results also indicate a statistically significant correlation between the phonological awareness test and the working memory test among students with and student without reading disabilities. The phonological memory test was only significant with students with reading disabilities. As for the sub-tests, the word pronunciation test after deleting part of it, and the test of merging syllables indicated a statistically significant relationship with the working memory test with students with reading disabilities and student without reading disabilities, while the test of remembering numbers and the test of the rapid naming of things were only significant with students with reading disabilities. In light of the results, we hope that phonological processing skills will be incorporated into the school curriculum, and that comprehensive testing of phonological processing will be used as a diagnostic tool for students in basic education.

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Publication Date
Sat Oct 09 2021
Journal Name
مجلةالعلوم الاجتماعية
العلاقة بين قلق الاختبار والكفاءة الرياضية لطلبة كلية التربية ابن الهيثم
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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

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Publication Date
Mon Feb 28 2022
Journal Name
Journal Of Educational And Psychological Researches
A Suggested Proposal to Activate Educational Supervision Based on Professional Learning Societies
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Professional learning societies (PLS) are a systematic method for improving teaching and learning performance through designing and building professional learning societies. This leads to overcoming a culture of isolation and fragmenting the work of educational supervisors. Many studies show that constructing and developing strong professional learning societies - focused on improving education, curriculum and evaluation will lead to increased cooperation and participation of educational supervisors and teachers, as well as increases the application of effective educational practices in the classroom.

The roles of the educational supervisor to ensure the best and optimal implementation and activation of professional learning soci

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Publication Date
Sun Apr 01 2007
Journal Name
Journal Of Educational And Psychological Researches
الانموذج الخلدوني لاستراتيجيات التعلم والتعليم مبادى وفنون
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المقدمة

ما كان للعرب في تاريخهم الطويل قبل الإسلام، وبعده أن يبدعوا ما أبدعوه في صنع الحضارة وتاريخها ، لولا اعتمادهم أنظمة تربوية سليمة في التنشئة والتعليم، ولولا ان عصورهم قد عرفت مربين ، ومعلمين، وعلماء اسهموا في تقديم نظريات تربوية آثرت في تقدم الفكر التربوي وفي تقدم الإنسان.

 فمن الطبيعي أن تكون للعرب تربية منظمة، ولمفكريهم عناية بهذه التربية في كل حقب تاريخهم الطويل، ما د

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Publication Date
Fri Jul 01 2022
Journal Name
International Journal Of Nonlinear Analysis And Applications
Survey on distributed denial of service attack detection using deep learning: A review
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Distributed Denial of Service (DDoS) attacks on Web-based services have grown in both number and sophistication with the rise of advanced wireless technology and modern computing paradigms. Detecting these attacks in the sea of communication packets is very important. There were a lot of DDoS attacks that were directed at the network and transport layers at first. During the past few years, attackers have changed their strategies to try to get into the application layer. The application layer attacks could be more harmful and stealthier because the attack traffic and the normal traffic flows cannot be told apart. Distributed attacks are hard to fight because they can affect real computing resources as well as network bandwidth. DDoS attacks

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
Arabic Sentiment Analysis (ASA) Using Deep Learning Approach
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Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l

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Publication Date
Sat Jun 01 2024
Journal Name
Journal Of Engineering
Intelligent Dust Monitoring System Based on IoT
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Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Science
Computer Vision of Optimal Geometric Concentration Ratio for the Solar Ball Lens
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      This research evaluates the optical properties of an inhomogeneous and non-paraxial system using a solar ball lens (SBL) as a new thermal solar concentrated collector. This evaluation is based on detecting a diacaustic curve in a straightforward and accurate manner, with the diagnostic relying on image processing as a computational tool using the MATLAB program rather than a complicated numerical analytic procedure. The circle of least confusion (CLC) of the (SBL), (Fluorinated ethylene propylene (FEP) polymer – water core), was calculated. Furthermore, the study evaluated the maximum geometrical concentration ratio (G C) of refracted solar radiation that can be captured by a receiver of the (SBL). Without energy losses due

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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
Optimum Median Filter Based on Crow Optimization Algorithm
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          A novel median filter based on crow optimization algorithms (OMF) is suggested to reduce the random salt and pepper noise and improve the quality of the RGB-colored and gray images. The fundamental idea of the approach is that first, the crow optimization algorithm detects noise pixels, and that replacing them with an optimum median value depending on a criterion of maximization fitness function. Finally, the standard measure peak signal-to-noise ratio (PSNR), Structural Similarity, absolute square error and mean square error have been used to test the performance of suggested filters (original and improved median filter) used to removed noise from images. It achieves the simulation based on MATLAB R2019b and the resul

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Publication Date
Mon Jul 31 2017
Journal Name
Journal Of Engineering
Assessment of Water Clarity within Dokan Lake Using Remote Sensing Techniques
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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
An Effective Hybrid Deep Neural Network for Arabic Fake News Detection
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Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural

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