The Effectiveness Degree of Distance Learning at Zarqa University in Light of Corona Pandemic from Faculty Members’ and Students’ Point of View

This study aims at finding out the effectiveness degree of distance learning at Zarqa University in light of Corona Pandemic from faculty members’ and students’ point of view. The descriptive survey methodology is used. The study is applied to a stratified random sample of faculty members and students at Zarqa University, whose number was (210) faculty members and (1261) male and female students. The questionnaire, which consists of (40) items, distributed into three domains, is used as a tool to collect data, after ensuring its validity and reliability. The findings show that the mean of the effectiveness degree of distance learning at the university is medium from faculty members’ point of view with a mean (3.67) and a standard deviation of (0.47). The study found that the effectiveness degree of distance learning at the university is also medium from the students’ point of view. The mean is (3.36) with a standard deviation of (0.62). The findings indicate that there are significant differences at (α ≤ 0.05) between the views of faculty members and students’ views on the overall degree and the three domains in favor of faculty members. There are no significant differences at (α ≤ 0.05) of the degree of effectiveness of distance learning at the university from the faculty members’ point of view due to the academic rank and gender variables. While there are significant differences attributed to the variable of the faculty, in favor of the humanities faculties. There are significant differences in the degree of effectiveness of distance learning at the university from the students’ point of view in the total score and the three domains attributed to gender, in favor of males. There are significant differences due to the variable of the faculty in the domains of (Distance learning effectiveness and Distance learning system) in favor of humanities faculties. There were no significant differences in the domain of (Distance learning obstacles). © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

A Scoping Review on COVID-19's Early Detection Using Deep Learning Model and Computed Tomography and Ultrasound

Since the end of 2019, a COVID-19 outbreak has put healthcare systems worldwide on edge. In rural areas, where traditional testing is unfeasible, innovative computer-aided diagnostic approaches must deliver speedy and cost-effective screenings. Conducting a full scoping review is essential for academics despite several studies on the use of Deep Learning (DL) to combat COVID-19. This review examines the application of DL techniques in CT and ULS images for the early detection of COVID-19. In this review, the PRISMA literature review approach was followed. All studies are retrieved from IEEE, ACM, Medline, and Science Direct. Performance metrics were highlighted for each study to measure the proposed solutions' performance and conceptualization;A set of publicly available datasets were appointed;DL architectures based on more than one image modality such as CT and ULS are explored. Out of 32 studies, the combined U-Net segmentation and 3D classification VGG19 network had the best F1 score (98%) on ultrasound images, while ResNet-101 had the best accuracy (99.51%) on CT images for COVID-19 detection. Hence, data augmentation techniques such as rotation, flipping, and shifting were frequently used. Grad-CAM was used in eight studies to identify anomalies on the lung surface. Our research found that transfer learning outperformed all other AI-based prediction approaches. Using a UNET with a predefined backbone, like VGG19, a practical computer-assisted COVID-19 screening approach can be developed. More collaboration is required from healthcare professionals and the computer science community to provide an efficient deep learning framework for the early detection of COVID-19.

Attitude, Awareness, and Knowledge of Saudi Citizens towards COVID-19 Vaccination in Qassim Region - Saudi Arabia

Cross sectional study was conducted to evaluate the Attitudes and awareness level of Citizens towards COVID-19 vaccination in Qassim region. The present study's results showed that awareness of COVID-19 Vaccination in Qassim region- Saudi Arabia shows that the mean score of awareness was 3.49 (SD 0.864) out of 5. Regarding vaccination decision among Saudi citizens in Qassim region, (22.7%) of the participants were undecided, (14.7%) refused, and (62.6%) agreed to get a vaccine against COVID-19. Reason for vaccine refusal mainly was they don't believe the vaccine. 96 Participants (32.0%) were working in the healthcare sector, (44.8%) of them had received the COVID-19 Vaccine, and (38.5%) refused. The level of awareness among healthcare participants was (80.2%). The average knowledge score was 3.49 (SD =.864) out of a possible 5. Participants who reported having a graduate level of education had a considerably higher mean knowledge score. The mean score of attitudes was 1.95 (SD=1.176) out of 5, with majority of positive attitude score 62.7%. ((65.7% They received the first dose, and 6.0% they received the first dose and second dose)). Participants with age group 55 years and above years, are more aware towards COVID-19 Vaccination than other age groups. Married persons are more aware towards COVID-19 Vaccination than other categories. Participants with graduate educational level are more aware towards COVID-19 Vaccination than other educational levels. Employed persons are more aware towards COVID-19 Vaccination than other categories. Whereas, there is no relation between age and awareness among Saudi citizens towards COVID-19 (P-value= 0.140). As well, there is no relation between employed citizens and awareness among Saudi citizens towards COVID-19 (P-value =0.136), and there is relation between marital status and awareness among Saudi citizens (P-value = 0.013).