Using Factor Analysis to Determine the Most Important Factors Affecting Student Absenteeism at Cihan University- Erbil

The review of the relevant literature reveals that the issue of absenteeism among students was not new. The researcher intended to explore the factors affecting absenteeism and to find a solution to solve this issue. For this purpose, a mixed methods research was designed. To analyze this problem, both quantitative and qualitative research methods were adopted in this study. In quantitative approach a close ended questionnaire was developed to collect data. The sample comprised of 470 students out of total population of (4892). A descriptive and inferential statistical techniques were used to analyze the data. ‎Transcriptions were analyzed through Thematic Description Approach under the qualitative ‎methods using IBM SPSS version 25.0. The results revealed significant factors of the phenomenon. It was delimited to the Cihan University-Erbil only, but the findings can be generalized all over Kurdistan Region, because of the many similarities in our educational system (examination, large scale assessment and resources)

The Full Factorial Design Approach to Determine the Attitude of University Lecturers towards e-Learning and Online Teaching due to the COVID-19 Pandemic

The purpose of this study was to determine faculty members' attitudes toward online learning in Kurdistan region universities. The study examined the biographic and personal characteristics of the lecturer towards e-learning. The data was collected among faculty members at Cihan University-Sulaimaniya, and to analyze the data, a full factorial design with five main factors at two levels and no central points was applied for this specific purpose. The study's findings indicated that there was no significant relationship between gender and lecturer attitude towards e-learning. In comparison to teachers with an MSc degree, those with a PhD have a more negative attitude toward e-learning. Furthermore, full-time faculty members have a greater positive effect on teachers' attitudes than part-time lecturers. Likewise, the results indicate that lecturers who earned their most recent education degrees outside of Iraq have a more favorable attitude. Similarly, lecturers in the sciences are more favorable to e-learning than those in the arts and social sciences. In addition, the findings demonstrated that the interaction factors (Gender) and (Education Degree) have a negative effect on lecturers' attitudes when they are combined. Besides that, the interaction of factors (Country of Last Education Degree) and (Faculty Member Types) improves attitudes toward e-learning. Based on the results, it is suggested that academic staff receive e-learning training to deepen their knowledge and understanding of such a modern teaching system. There is also a need to enhance factors related to positive attitudes towards e-learning among university lecturers. The findings of this study are necessarily significant to both teachers and educational organizations in Kurdistan Region universities. &nbsp

Applying Knowledge Management Processes to ‎Improve Institutional Performance ‎

This study aimed to identify the role of knowledge management ‎processes in improving ‎the level of institutional performance in Cihan ‎University- Erbil, Iraq. For the purpose of ‎achieving the study objectives, a hypothesis has been formulated with two sub-‎hypotheses. The study relied on a descriptive analytical approach. The data were collected ‎by a questionnaire distributed randomly to 90 academic staff at Cihan University-Erbil ‎Campus, 74 valid responses were received. The results showed that knowledge ‎management ‎processes play an important role in improving the institutional performance ‎‎level of the institution studied. Also, the processes of ‎generating and storing knowledge ‎show have stronger correlation than the ‎processes of distributing and applying knowledge ‎in improving the institutional ‎performance level in the University. ‎The novelty of this ‏article comes from ‏its results and the set of ‎recommendations that will contribute to ‎raising the level of ‎institutional performance.

Personal Digital Marketing Influence on Successful Marketing Campaign in Today’s Digital Age

Personal digital marketing is an essential aspect of modern marketing campaigns. It involves using digital channels such as social media, email marketing, and content marketing to create a unique identity and promote it to a target audience. The article aims to examine the influence of personal digital marketing on successful marketing campaign. This study uses a descriptive and quantitative approach to test the effect of independent variables (digital personal marketing elements) on the degree of success in personal marketing campaign. The data were collected by a questionnaire distributed to 300 marketers, owners, and young entrepreneurs. A regression analysis was applied to test the study hypothesis. The results showed that personal marketing elements: branding, content creation, networking, social media management, personal website and personal development, directly affect the degree of success in personal marketing campaign

A New Hybridization of Bilateral and Wavelet Filters for Noisy De-Noisy Images

In this work we propose, a hybrid noise reduction algorithm that is a combination of a spatial field binary filter and a hybrid wave field threshold function. These two methods are used to stop Gaussian noise. The hybrid filter is a nonlinear filter that deals with spatial averaging of non-uniform edges. We found it to be an effective technique for image reduction. Determining filter parameters for the mixed filter is important to avoid large differences in results, besides the issue of acceleration velocity. This hybrid model, binary filtering, and Wavelet Thresholding have tried standard images, such as normal eyes, MRI, Roya Face, Ultrasound, X-Ray, and Rawa. Different Gaussian noise was added with different standard deviations σ = 10, 20, 35, 40, and 50. The peak-to-noise ratio (PSNR) signal, MSE, VIF, IQI, and the proposed model MSE between pixels were used as quantitative measures of performance of the relative noise reduction algorithms and then were compared to the models