publishing has become a large space in the field of interactive education and modern pages have become dedicated to the service of the educational effort in this area as the research in this context of the urgent scientific necessities, especially as we consider in Iraq from the new countries in the exploitation of these new technologies and investment possibilities of the information network And the contents of different in the framework of so-called distance education Here lies the problem of research in the possibility of finding scientific solutions for the design of interactive inter active website for students of the preparatory stage in Iraq and to find out the scientific ways to find design The study, which included the problem of

Abstract

The current research aims to identify the psychological security of students in the kindergarten department and identify if there is a significant difference between stage one and stage four students. To do this, the researcher adopted the psychological research scale of (Al-mohamdawi, 2007) that consisted of (30) items. It was administered to (120) female students chosen randomly from the kindergarten department in the college of education for women for the academic year (2029-2021). The results revealed that students in the kindergarten department have psychological security. There is a significant difference between stage one and four students in favor of stage four students.

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

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

Abstact:
Nursery is one of educational institution in the process of developing the
social concepts that it includes a quirking the knowledge and experiences that
help the kid to adjust with environment through arrangement words ,
movements and concrete things which are transferred to the kids so as to
realize these concepts .
Social concepts are numbers of words and statements with social nature
which the kids learn through the family or nursery in order to effect their
educational style of independent and helping the others .
The re searcher adopted this theory because of the little studies in the
filed of social concepts in the nursery.
The aims of the study are as following :
1- building tools for

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

The study aimed to identify the future thinking skills of university students and which of these skills are prevalent. The sample of the study consisted of (400) male and female students from the university students. In order to achieve the goals of the research, the researcher built a measure of future thinking skills based on Torrance theory (2003). Psychometric properties of the standards were extracted, which are represented by honesty and consistency and the application of the measures to the research sample. The researchers found that Future thinking skills of university students, and that the skill of future planning is the most common skill among the research sample.

Abstract

The current research aims to identify psychological resilience among middle school students. a sample of (300) male and female students was chosen from Al- Azmaa Intermediate School for Boys and Ohran Intermediate School for Girls, It is affiliated with the second Rusafa Education Directorate in Baghdad Governorate. To achieve the research objective, the researcher adopted a scale of Luthar & Cicchetti (2000) to measure psychological resilience. The results showed that middle school students have psychological resilience. There is no significant difference in psychological resilience between males and females.

يتناول هذا البحث موضوع (( فعل الامر في صيغة المبني للمجهول في اللغة الاكدية )) وهو يتعلق بقواعد اللغة الاكدية , وقد تضمن هذا البحث مقدمة وشقين : صيغة المبني للمجهول وفعل الامر. اما ما يخص المقدمة فقد شملت تعريف الفعل وانقساماته حسب قوة احرفه , الجذر , المعنى , والفاعل , كما تضمنت المقدمة أيضا الحديث عن الصيغ الفعلية الرئيسة الأربعة التي يتألف الفعل الاكدي منها إضافة الى الصيغ الثانوية التي تتضمنها الصيغ الرئيسة . و