Abstract

The current research aims to identify the most prominent beliefs about coronavirus of Baghdad University students, as well as to identify the prominent beliefs toward coronavirus of male and female students. To achieve the research objectives, a questionnaire of (15) items was administered to a sample of (600) male and female students collected from ten different colleges at the university of Baghdad. The findings of the research illustrated that item (8) took priority as students believe there is a misleading about coronavirus spreading by governments, item (2) which indicated that coronavirus is man-made took level two, followed by item (10), it proposes that coronavirus emerged from the American milit

The study aimed to measure the phsycological tolerance and self-efficacy among the students of Baghdad university and knon the significant differences in psychological tolerance and self-efficacy according to the variables (Gender-Specialization)and the interaction between themas well as the study aimed to identify the strength and direction of the relationship between psychological tolerance and self-efficacy of the study sampleincluded asample of the current study(370) students from grades four ,the researcher used the measure of psychological tolerance and self-efficacy prepared by the researcher ,and the results showed that college students Generally have adegree of psychological tolerance and that there are statistically sig

Abstract

The current study aims to identify university students' attitudes towards reading and its relationship to some demographic variables in the universities of the Sultanate of Oman. The study sample consisted of (1434) male and female university students from various Omani public and private universities affiliated with the Ministry of Higher Education. The study covered all (11) governorates of Oman. The researcher adopted the descriptive analytical approach. The researcher employed a scale of reading attitudes to collect the needed data. The study results showed that university students' reading attitudes recorded a high degree. The results also showed there are statistically significant differences at th

Abstract

This study aims to identify the empathy of University Students, as well as the significant differences in sympathy in terms of gender and specialization. To achieve the aims of the study, a scale of empathy was administered to a sample of (450) students collected randomly from Baghdad university. The results showed that the study sample has a level of empathy. There is a significant difference between males and females in empathy, in favor of the female students. There is no significant difference in empathy in terms of specialization (scientific, humanities), and the interaction between males and females. The study came out with a number of recommendations and suggestions. 

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

MM Abdulwahhab, kufa Journal for Nursing sciences, 2017 - Cited by 1

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

       In the pandemic era of COVID19, software engineering and artificial intelligence tools played a major role in monitoring, managing, and predicting the spread of the virus. According to reports released by the World Health Organization, all attempts to prevent any form of infection are highly recommended among people. One side of avoiding infection is requiring people to wear face masks. The problem is that some people do not incline to wear a face mask, and guiding them manually by police is not easy especially in a large or public area to avoid this infection. The purpose of this paper is to construct a software tool called Face Mask Detection (FMD) to detect any face that does not wear a mask in a specific