The study aimed to reveal the level of knowledge and tendencies of high- study students specializing in curriculum and teaching methods at King Khalid University towards harmonious strategies with brain-based learning (BBL). And Then, putting a proposed concept to develop knowledge and tendencies of high-study students specializing in curriculum and teaching methods at King Khalid University towards harmonious strategies with Brain-based learning (BBL). For achieving this goal, a cognitive test and a scale of tendency were prepared to apply harmonious strategies with brain-based learning. The descriptive approach was used because it suits the goals of the study. The study sample consisted of (70) male and female students of postgraduate students (MA and Ph.D.) who are attending regularly at the Department of Curriculum and Teaching Methods for the academic year 1440/1441 AH. The study has shown a lot of results, the most important one is that the cognitive level and tendency to apply for postgraduate students (MA and Ph.D.) specializing in curriculum and teaching methods for harmonious strategies with brain-based learning principles was Average, and there are statistically significant differences at the level of significance (0.05) between the average of postgraduate students’ degrees in the cognitive level and the tendency towards applying harmonious strategies with brain-based learning which due to the difference in the academic degree, and in the light of the results of the study. A proposed concept was developed to enhance the knowledge and tendencies of postgraduate students specializing in curriculum and teaching methods at King Khalid University for the harmonious strategies with brain-based learning (BBL). The study was ended with a set of suggested recommendations that would activate the use of the harmonious strategies with brain-based learning.
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In this research, the nonparametric technique has been presented to estimate the time-varying coefficients functions for the longitudinal balanced data that characterized by observations obtained through (n) from the independent subjects, each one of them is measured repeatedly by group of specific time points (m). Although the measurements are independent among the different subjects; they are mostly connected within each subject and the applied techniques is the Local Linear kernel LLPK technique. To avoid the problems of dimensionality, and thick computation, the two-steps method has been used to estimate the coefficients functions by using the two former technique. Since, the two-
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Objective: To determine the effectiveness of an Educational Program in Enhancing Nurse’s Knowledge about Occupational Health Hazards at Medical City Hospitals in Baghdad City.
Methodology: The present study employed a quasi-experimental design held at Medical City Hospitals in Baghdad City. A non-probability sample (convenience sample) consisted of (60) nurse. Data were collected by using a self-report questionnaire which consisted of six parts (a) socio-demographic characteristics (b) physical hazards knowledge (c) chemical hazards knowledge (d) biological hazards knowledge (e) psychological hazards knowledge and (f) mechanical hazards knowledge. Data were analyzed using the statistical packag
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Objective: The study aim is to assess knowledge of secondary schools female students regarding dysmenorrhea; find out the effectiveness of education program on secondary schools students and also to identify relationship between education program and certain variables.
Methodology: The quasi-experimental design (pretest and posttest) on one hundred students 4th year in Khawla Bint Al-Azwar secondary school for females at morning shift in Al Nasiriya City, data collection started at 4th March to 18th March 2018. A non-probability (purposive) sample of (100) students (50) student from scientific branch and (50) students from literary branch. Data have been collected through using a questionnaire modeled and made up of
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
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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
... Show MoreResearch aims at evaluating the quality of the teaching skills of math teachers in junior high / scientific branch from their point of view.
The researchers prepared for this purpose a quality of teaching skills standards questionnaire, It consisted of 72 items distributed on four axis, The research sample was 200 teachers The researchers used statistical methods: the arithmetic mean, standard deviation, variance test, test Shiva , The results showed a statistically significance difference Attributed to the qualification variable in the second axis (Planning for teaching topics) And the absence of statistical difference function,
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