Mahmoud Maqableh

Accurate retinal vessel segmentation is an important component of automated retinal image analysis, supporting remote assessment and connected healthcare applications. However, detecting small retinal blood vessels while limiting false positives remains challenging. This study proposes a hybrid retinal vessel segmentation method that combines optic disc exclusion with a genetic algorithm-optimized Gaussian matched filter (GMF). The method localizes and masks the optic disc and uses a genetic algorithm to optimize three GMF parameters, with the area under the receiver operating characteristic curve (AUC) as the fitness function. Filtering, thresholding, and morphological operations are then applied to generate the final vessel segmentation. The proposed method was evaluated using two public retinal image databases, DRIVE and STARE. On DRIVE, the method achieved an average AUC of 0.9659 and a mean accuracy (MA) of 0.9444, while on STARE it achieved an average AUC of 0.9625 and an MA of 0.9530. The results demonstrate competitive overall retinal vessel segmentation performance, while the proposed optimization specifically targets the response to small retinal vessels. The method therefore shows potential as an image-analysis component for connected retinal screening systems. However, practical IoMT deployment requires further evaluation of computational efficiency, data protection, and resilience to image manipulation.

Online learning has become prevalent across the globe since the COVID-19 pandemic. With this change and continuing growth of online learning, understanding its impact on student learning outcomes is critical. This paper focuses on different learning outcomes in online learning. The authors extend the online learning effectiveness literature by investigating the role of quality on student online learning outcomes. Further, the impact of quality is examined on various dimensions of student outcomes, including cognitive outcomes (engagement), psychological outcomes (flow), affective outcomes (satisfaction), and academic outcomes (learning performance). They conducted an online survey among students (N=910) to examine the impact of quality on students' learning outcomes. They found that overall quality positively impacts students' actual use of the online learning system, and students' online learning system use significantly affects students' outcomes.

Social media addiction has undergone a remarkable transformation among regular users, but limited research has been conducted on exploring the antecedents of addiction. The purpose of this study is to investigate the relationship between continuance intention and addiction. Moreover, it investigates the moderating role of satisfaction and trust on the relationship between continuance intention and addiction. The developed conceptual model suggests that continuance intention is the antecedent of addiction, while satisfaction and trust act as moderators between continuance intention and addiction. The antecedents of continuance intention are emotional, informational, social, and hedonic values. A survey was conducted to collect data from 572 voluntary participants, and the analysis was performed using SPSS and AMOS. The statistical result showed the effects of emotional, informational, and hedonic values on Facebook use continuance intention, but the effect of social value was not supported. Results also confirmed a significant effect of continuance intention on Facebook addiction. Additionally, it confirmed the moderating role of satisfaction on the impact of continuance intention on Facebook addiction, but the moderating role of trust was not supported. The results of this study provide insight for Facebook users, managers, and policymakers regarding treatment and intervention for Facebook addiction. It discusses several theoretical and practical implications. In this research, we proposed a new model based on extending the associations between perceived value and continuance behaviours theory.

This study investigates the impact of integrating essential factors on academic performance in university students’ context. The proposed model examines the influence of continuance intention, satisfaction, information value, and Internet addiction on academic performance. Additionally, it investigates the mediating role of continuance intention on the relationship of satisfaction and information value on academic performance among university students. A survey questionnaire method was adopted to collect data from university students in Jordan. Data was collected from 476 voluntary participants, and the analysis was conducted using SPSS and AMOS. The analysis results show that continuance intention, satisfaction, information value have a significant positive influence on academic performance. Besides, the results show that satisfaction and information value positively and significantly influence continuance intention. While continuance intention full mediation the relationship between satisfaction and academic performance, it partial mediation the relationship between information value and academic performance. This study is the first to examine the integrating of continuance intention, satisfaction, information value, and Internet addiction on students’ academic performance. Furthermore, this study is also distinguished from other studies by investigating the mediating role of continuance intention gap.