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Self-organized learning strategies and self-competence among talented students
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Investigating the strength and the relationship between the Self-organized learning strategies and self-competence among talented students was the aim of this study. To do this, the researcher employed the correlation descriptive approach, whereby a sample of (120) male and female student were selected from various Iraqi cities for the academic year 2015-2016.  the researcher setup two scales based on the previous studies: one to measure  the Self-organized learning strategies which consist of (47) item and the other to measure the self-competence that composed of (50) item. Both of these scales were applied on the targeted sample to collect the required data

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Publication Date
Thu Oct 29 2026
Journal Name
Journal Of Baghdad College Of Dentistry
The relation among ramal width and length with some cervical and cranio-facial measurements in different skeletal classes
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Background: The purpose of this study was to assess the relation among the ramal length and width with various cervical and cranio-facial measurements for a sample of Iraqi adults with different skeletal classes. Materials and method: The sample composed of 71 Iraqi adults (36 females and 35 males) with an age ranged between 17-30 years and had different skeletal mal-relations using SNA, SNB and ANB to differentiate between them and assorting them into CL.I, CL.II and CL.III mal-relation. Each individual was subjected to clinical examination and digital true lateral cephalometric radiograph that had been analyzed using AutoCAD 2007 software computer program to determine sixteen linear and ten angular measurements. Descriptive statistics wer

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Publication Date
Tue Jan 03 2023
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn 2789-3219 )
Knowledge, Attitudes, and Perceptions about COVID-19 and its Vaccine among Patients with Rheumatoid Arthritis: A Qualitative Study
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Background: Despite the importance of vaccines in preventing COVID-19, the willingness to receive COVID-19 vaccines is lower among RA patients than in the general population. Objective: To determine the extent of COVID-19 knowledge among RA patients and their attitudes and perceptions of COVID-19 vaccines. Methods: A qualitative study with a phenomenology approach was performed through face-to-face, individual-based, semi-structured interviews in the Baghdad Teaching Hospital, Baghdad, Iraq, rheumatology unit. A convenient sample of RA patients using disease-modifying anti-rheumatic drugs was included until the point of saturation. A thematic content analysis approach was used to analyze the obtained data. Results: Twenty-five RA pa

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Publication Date
Sat Jun 15 2024
Journal Name
Alustath Journal For Human And Social Sciences
The Effect of the PQ5R Stategy on the Achievement of Chemistry Among Fifth Grade Science Studen
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The research aims to identify the effect of the PQ5R strategy on the achievement of chemistry among fifth-grade science students in government secondary and preparatory schools. Al-Zumar Girls High School was chosen as its students as the research sample affiliated with the Diyala Education Directorate, Diyala Education Department, for the academic year (2023-2024). and Two divisions were chosen from among divisions. The fifth scientific grade was chosen randomly, one of them was the experimental group taught according to the PQ5R strategy, and the other was the control group taught according to the usual method. The equality of the two research groups was verified with a set of variables, which were (chronological age in months, previous a

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Publication Date
Sat Nov 03 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Assessment of the fear of Delivery among Women at Labor
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Objective: To assess the fear of laboring women regarding the delivery on themselves and their
newborns.
Methodology : A descriptive study was conducted on (100) pregnant women who where admitted to
labor room in Al- Yarmock Teaching Hospital/Maternity Units, Fatima Al- Zahra and Ibn-Al Baladi
Maternity and Pediatric Hospital. The questionnaire was consisted of pregnant women
socio-demographic data, reproductive data and fear items of labor. Data were collected by using a
questionnaire format, through interview technique and reviewing pregnant records, descriptive and
inferential statistical procedure were used to analyze the data.
Results: The main results of the study revealed a high mean of scores with moderate

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Publication Date
Tue Jan 01 2008
Journal Name
Journal Of Educational And Psychological Researches
تقويم مادة فلسفة التربية /للمرحلة الرابعة/ قسم العلوم التربوية والنفسية/كلية التربية / ابن رشد من وجهة نظر الطلبة
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 مشكلة البحث:

تعد مناهج كليات التربية العمود الفقري لإعداد مدرسين تربويين تقع على عاتقهم مهمة تربية وتعليم الجيل الذي سيتحمل مسؤولية بناء المجتمع وتطويره من خلال بناء وإعداد الأفراد في العديد من المجالات. ولما كان التغيير والتطوير المستمرين هما من السمات المميزة للعصر الذي نعيش فيه لذا تتطلب العملية التربوية مراجعة مستمرة لمناهجها بغية تقويمها وتطويرها بما يتناسب ومت

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Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science (ijeecs)
Increasing validation accuracy of a face mask detection by new deep learning model-based classification
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

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Publication Date
Wed Nov 05 2025
Journal Name
Irrigation And Drainage
Predicting Potential Salinity in River Water for Irrigation Water Purposes Using Integrative Machine Learning Models
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ABSTRACT<p>Accurate prediction of river water quality parameters is essential for environmental protection and sustainable agricultural resource management. This study presents a novel framework for estimating potential salinity in river water in arid and semi‐arid regions by integrating a kernel extreme learning machine (KELM) with a boosted salp swarm algorithm based on differential evolution (KELM‐BSSADE). A dataset of 336 samples, including bicarbonate, calcium, pH, total dissolved solids and sodium adsorption ratio, was collected from the Idenak station in Iran and was used for the modelling. Results demonstrated that KELM‐BSSADE outperformed models such as deep random vector funct</p> ... Show More
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Publication Date
Wed Dec 01 2021
Journal Name
Computers &amp; Electrical Engineering
Utilizing different types of deep learning models for classification of series arc in photovoltaics systems
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Publication Date
Wed Mar 20 2024
Journal Name
Journal Of Petroleum Research And Studies
Advanced Machine Learning application for Permeability Prediction for (M) Formation in an Iraqi Oil Field
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Permeability estimation is a vital step in reservoir engineering due to its effect on reservoir's characterization, planning for perforations, and economic efficiency of the reservoirs. The core and well-logging data are the main sources of permeability measuring and calculating respectively. There are multiple methods to predict permeability such as classic, empirical, and geostatistical methods. In this research, two statistical approaches have been applied and compared for permeability prediction: Multiple Linear Regression and Random Forest, given the (M) reservoir interval in the (BH) Oil Field in the northern part of Iraq. The dataset was separated into two subsets: Training and Testing in order to cross-validate the accuracy

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Publication Date
Thu Jan 01 2026
Journal Name
Ieee Transactions On Human-machine Systems
Deep Learning-Driven Decision Fusion: Spatio-Spectrogram Features for Inner Speech Recognition From Electroencephalogram Signals
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