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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
Wed Mar 20 2030
Journal Name
College Of Islamic Sciences
equality between man and woman                           Among Islamic law               International conventions and agreements
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equality between man and woman
                          Among Islamic law
              International conventions and agreements

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Publication Date
Thu Aug 20 2020
Journal Name
Talent Development & Excellence
Turn-Taking in Conversation between a Chef and Boss and among Chefs
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DBN Rashid, Talent Development & Excellence, 2020

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Publication Date
Sun Jul 05 2026
Journal Name
Al–bahith Al–a'alami
The role of Iraqi newspapers in instilling political culture among the public after 2003, a field study on the audience of the city of Baghdad
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The role of Iraqi newspapers in instilling political culture among the public after 2003, a field study on the audience of the city of Baghdad, University of Baghdad, College of Information, Department of Journalism, 2019,
The problem of research is to investigate the role of Iraqi newspapers in instilling the political culture of individuals after 2003, and monitor this role Through the contents and messages provided by the Iraqi newspapers to the public. the research is classified within descriptive research, it adopts the survey methodology and used the questionnaire tool. In fact, the questionnaire was distributed to a sample of 400 individuals that was selected according to the method of multi-stage cluster sample of those who re

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Publication Date
Sat Feb 01 2025
Journal Name
Journal Of Energy Storage
Massive energy reduction and storage capacity relative to PCM physical size by integrating deep RL clustering and multi-stage strategies into smart buildings to grid reliability
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Publication Date
Mon Oct 03 2022
Journal Name
International Journal Of Nonlinear Analysis And Applications
Use of learning methods for gender and age classification based on front shot face images
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Publication Date
Mon Jan 01 2024
Journal Name
Fusion: Practice And Applications
Proposed Framework for Semantic Segmentation of Aerial Hyperspectral Images Using Deep Learning and SVM Approach
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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Keratoconus Severity Detection From Elevation, Topography and Pachymetry Raw Data Using a Machine Learning Approach
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Publication Date
Wed Jun 04 2025
Journal Name
Engineering, Technology & Applied Science Research
Evaluation of the Accuracy of Machine Learning Classifiers and Spectral Indices in Land Cover Classification
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Population growth and economic and industrial development coupled have significantly accelerated the rate of Land Use and Land Cover (LULC) changes, particularly in developing countries, so finding optimum ways to observe these change has become a pressing issue. Quantification evaluation of these changes is crucial to comprehend and oversee land management conversion, therefore, it is necessary to evaluate the accuracy of various algorithms for LULC classification to determine the most effective classifier for Earth observation applications. The performance of Maximum Likelihood (ML), Support Vector Machines (SVM), Random Forest (RF), and K-Nearest Neighbors (KNN) was examined in this study, based on Sentinel 2A satellite images. T

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Publication Date
Sat Jun 01 2019
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Lung cancer classification using data mining and supervised learning algorithms on multi-dimensional data set
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These With recent developments in machine learning, data mining and computer vision, there is great potential for improvements in early detection of lung cancer using scans and data available. This paper details the methods and techniques used in our project, where the objective is to develop algorithms to determine whether a patient has or is likely to develop lung cancer using dataset images using data mining and machine learning for the classification and examination. We explore approaches to address the problem. Cancer is the most important cause of death globally. The disease diagnosis is a major process to treat the patients who are affected by cancer disease. The diagnosis process is more difficult comparatively known about t

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Publication Date
Mon Jan 01 2024
Journal Name
Pakistan Journal Of Life And Social Sciences (pjlss)
Mental Durability of Postgraduate Students
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