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The influence of Online Training Courses on Iraqi EFL Instructors Teaching and Learning Process
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For over a decade, educational technology has been used sparingly in our schools and universities. Online training courses have been used since 2003 to fill the gaps in our learning system and to add extra program besides classroom learning. This paper aims to investigate the Iraqi EFL instructors’ participating in online training courses and its influence on the process of teaching and learning.

       The sample of present study consists of 30 instructors from University of Baghdad. The questionnaire of sixteen items was constructed. After ensuring validity and reliability of questionnaire, it was applied on March 2013 and the result shows that most of instructors improve their teaching methods by participating in online training courses and they prefer E-learning to enrich their experience in English language teaching.

      In the light of the findings of the present study, relevant conclusions and recommendations are put forward.

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Publication Date
Tue Jan 02 2018
Journal Name
Journal Of Educational And Psychological Researches
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 Mar 13 2025
Journal Name
Academia Open
Deep Learning and Fusion Techniques for High-Precision Image Matting:
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General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k

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Publication Date
Tue Dec 28 2021
Journal Name
2021 2nd Information Technology To Enhance E-learning And Other Application (it-ela)
Pedestrian and Objects Detection by Using Learning Complexity-Aware Cascades
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Publication Date
Mon Mar 25 2019
Journal Name
Al-academy
The Effectiveness of the Symbol in Iraqi Monodrama Texts: محمد علي ابراهيم
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This research studies the effectiveness of the symbol in the Iraqi monodrama texts. The methodological framework is devoted to the research problem and the need for conducting it, its importance, the purpose of research, and the definition of the most important terms. The research problem dealt with the concept of the effectiveness of the symbol, the monodrama, and the working levels of the symbol in the monodrama texts of the author, in addition to the disclosure of the artistic vision embodied by the playwright in the use of the symbol within the literary product, as well as the development of the creative process. The research problem was defined by the following question: How effective is the symbol in the Iraqi Monodrama texts?
T

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Publication Date
Thu Mar 30 2023
Journal Name
Journal Of Economics And Administrative Sciences
The Possibility of Applying Agile Internal Auditing in the Iraqi Economic Units
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The research problem is that the traditional methods of internal auditing are somewhat heavy with long and rigid procedures for the members of the audit process team, especially in light of the current developments that are reflected in the business environment and internal audit reports, so it is necessary to reconsider the traditional internal audit work method and assess the extent of its development by agile methods to reduce the time of the audit process on the activities and elements that add value and direct the effort and time to the activities and elements that add value to the work of the economic unit and the report of the internal auditor.

The research aims to study the possibility of applying agile internal auditing

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Publication Date
Sat Apr 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
The Appropriateness Of The Iraqi Environment For Establishment Of Hedge Funds In Iraq
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المستخلص

يهدف البحث إلى وضع إطار معرفي ومفاهيمي شامل لموضوع البحث, واغناء القارئ والمستفيد بالمعلومات الوافية عنه وتقليص الفجوات المعرفية للمهتمين به وقياس مدى ما هو متوفر وغير متوفر من المتطلبات الأساسية والضرورية لإنشاء صناديق التحوط في البيئة العراقية, وتمثلت صناديق التحوط بالمتغير الرئيس للبحث اما المتغيرات الفرعية فشملت (المتطلبات المالية, المتطلبات البشرية, البيئة التشريعية, الب

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Publication Date
Thu Apr 01 2021
Journal Name
Biochemical And Cellular Archive
BIOETHANOL PRODUCTION FROM OLIVE SOLID WASTE USING SIMULTANEOUS SACCHARIFICATION AND FERMENTATION PROCESS
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Publication Date
Tue Jul 01 2025
Journal Name
South African Journal Of Chemical Engineering
Electrocoagulation process for cobalt removal from industrial wastewater: Optimization and kinetic study
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Publication Date
Sun Jan 01 2023
Journal Name
Computers, Materials & Continua
An Efficient Method for Heat Recovery Process and燭emperature燨ptimization
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Publication Date
Mon Jan 01 2024
Journal Name
Bio Web Of Conferences
An overview of machine learning classification techniques
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Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed

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