The research examines the mechanism of application of )ISO 21001: 2018( in the Energy Branch- Electromechanical Engineering at the University of Technology to achieve the quality of the educational service to prepare the branch to obtain the certificate of conformity with the requirements of) ISO 21001: 2018(, the necessary data were collected Depending on the (CHEKLIST) of (ISO 21001: 2018), field interviews and records of the concerned department, The researchers reached a number of results, the most prominent of which was the adoption of high quality leadership leaders and their willingness to implement the standard requirements, The university has a basic structure that qualifies it to implement the international standard, as

importumt educational institution as (kindergartens) need teachers which qualified ownes modalities in their education for children , as Marzanu method in a way of learning and own methods of crisis management, because the teachers that own those styles of learning ginekindergarten children knowledge and the childrenIeaving based on theMeaing and knowledge and integration of their information, And teachers that earn methods of crisis management provide for the children of the kindergarten security within the educational institution which in turn affect the growth and development of the Child and then abilities, health physical, mental, psychological …etc.., The aims of the current research have identified to recognize: 1- the dimension

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 b

The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi

IRA Dawood, JOURNAL OF SPORT SCIENCES, 2016 - Cited by 3

This study aims to prepare educational sessions for the strategy (team-pair-solo) in practical volleyball lessons for female students and identifying its effect on learning the accuracy of the spiking skill in volleyball. An experimental design with experimental and control groups was employed on a purposive sample of (30) female students who were to constitute (42.254%) from their community represented by the sophomores at the College of Physical Education and Sports Sciences for Girls / University of Baghdad who are in good standing in the morning study for the academic year (2022-2023), whose total number is (71) students. According to the determinants of the experimental design, participants were divided into two equal groups, a

Objective: To identify the effect of the cube model on visual-spatial intelligence and learning the skill of spikinging in volleyball for female students, The researchers used the experimental method by designing two equivalent groups with pre- and post-measurements. Research methodology: The main research sample of (30) female students was selected from the research community represented by second-stage students in the College of Physical Education and Sports Sciences - University of Baghdad for the academic year (2024-2025). The sample was divided equally into two control and experimental groups. The researchers conducted the sample homogenization process and the equivalence process between the two groups in the variables of visua

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