Abstract

The study aims to identify the degree of citizenship values practiced by Bisha University students and identify the impact of gender, college, and academic level, on the degree of the practice of University students for citizenship values. The researcher used the descriptive-analytical method including a questionnaire of (44) items. To process the data, the researcher applied the computational averages, standard deviations, percentages, and T-test. The questionnaire was implemented on a sample of (600) of the 2 and 8 levels during the second semester of the academic year (2020-2019) at Bisha University. The study findings revealed that the degree of the pra

The study aimed to identify the self- compassion of the students as well as to identify the differences in the self- compassion according to the variables: sex - the academic specialization - Study level, the sample of the study of (200) students distributed equally by sex (male - female) Specialization (Scientific - Human) compassion. The results showed that there were no differences in the self- compassion according to the variables: gender, academic specialization, and Study level. In light of these results, the researcher Number of the recommendations and proposals

Background: Breast cancer still a major cause of disability and mortality among women throughout the world. Lack of awareness and early detection programs in developing countries is a main reason for escalating the mortality.

Objectives: to assess level of awareness about breast cancer among university female students in Baghdad focusing on knowledge of breast cancer risk factors, warning symptoms and signs and knowledge about the screening method specially breast self-examination.

Methods: A cross-sectional study conducted over two months from first of march through April 2015 and included (240) female students in non- medical colleges at Al-Rusafa and A

It is an analytical study carried out at university of Basra  using a sample included the dean ,assistants and managers of scientific dept. in the university for about(63)managers .The study aimed at discovering  a model of  crises management in the university.The researcher adopted the descriptive survey methodology.To achieve the objective of the study ,a questionnaire of (41)statements was developed covering five main  variables like ,signal detection, prevention and preparedness, response, recovery and learning .The validity of the questionnaire was done by a group of referees .Its stability was determined by Cronbach^,s  Alfa  .The questionnair^,s stability coefficient was(0.

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

In this paper, a new equivalent lumped parameter model is proposed for describing the vibration of beams under the moving load effect. Also, an analytical formula for calculating such vibration for low-speed loads is presented. Furthermore, a MATLAB/Simulink model is introduced to give a simple and accurate solution that can be used to design beams subjected to any moving loads, i.e., loads of any magnitude and speed. In general, the proposed Simulink model can be used much easier than the alternative FEM software, which is usually used in designing such beams. The obtained results from the analytical formula and the proposed Simulink model were compared with those obtained from Ansys R19.0, and very good agreement has been shown. I

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

The construction industry in Iraq suffers from many problems, perhaps the most important of which is the delay in time and the increase in costs. Therefore, it was necessary to try to adopt a new methodology that would help in overcoming these problems. It was suggested to combine building information modeling with the agile management approach because this technique and methodology is modern and helps in reducing time and cost and improving quality. This paper aims to know the status of using Building Information Modeling (BIM) and Agile Project management (APM) in Iraq and to shed light on the merging of this integration, explaining the benefits, difficulties, and workflow practices, finding the most influencing factors on the tim

In this study, the photodegradation of Congo red dye (CR) in aqueous solution was investigated using Au-Pd/TiO₂ as photocatalyst. The concentration of dye, dosage of photocatalyst, amount of H₂O₂, pH of the medium and temperature were examined to find the optimum values of these parameters. It has been found that 28 ppm was the best dye concentration. The optimum amount of photocatalyst was 0.09 g/75 mL of dye solution when the degradation percent was ~ 96 % after irradiation time of 12 hours, while the best amount of hydrogen peroxide was 7μl/75 mL of dye solution at degradation percent ~97 % after irradiation time of 10 hours, whereas pH 5 was the best value to carry out the reaction at the highest deg