Tuberculosis (TB) is an infectious disease that can lead towards death if left untreated. TB detection involves extraction of complex TB manifestation features such as lung cavity, air space consolidation, endobronchial spread, and pleural effusions from chest x-rays (CXRs). Deep learning based approach named convolutional neural network (CNN) has the ability to learn complex features from CXR images. The main problem is that CNN does not consider uncertainty to classify CXRs using softmax layer. It lacks in presenting the true probability of CXRs by differentiating confusing cases during TB detection. This paper presents the solution for TB identification by using Bayesian-based convolutional neural network (B-CNN). It deals with the uncertain cases that have low discernibility among the TB and non-TB manifested CXRs. The proposed TB identification methodology based on B-CNN is evaluated on two TB benchmark datasets, i.e., Montgomery and Shenzhen. For training and testing of proposed scheme we have utilized Google Colab platform which provides NVidia Tesla K80 with 12 GB of VRAM, single core of 2.3 GHz Xeon Processor, 12 GB RAM and 320 GB of disk. B-CNN achieves 96.42% and 86.46% accuracy on both dataset, respectively as compared to the state-of-the-art machine learning and CNN approaches. Moreover, B-CNN validates its results by filtering the CXRs as confusion cases where the variance of B-CNN predicted outputs is more than a certain threshold. Results prove the supremacy of B-CNN for the identification of TB and non-TB sample CXRs as compared to counterparts in terms of accuracy, variance in the predicted probabilities and model uncertainty.

Digital transformation in energy sector organizations has huge benefits but also exposes them to cybersecurity challenges. In this paper, we carried out a systematic literature review on cybersecurity challenges and issues in the energy domain. Energy-associated assets are very critical for any nation and cyber-attacks on these critical infrastructures can result in strategic, financial, and human losses. We investigated research papers published between 2019 and 2024 and categorized our work into three domains: oil and gas sector, the electricity sector, and the nuclear energy sector. Our study highlights that there is a need for more research in this important area to improve the security of critical infrastructures in the energy sector. We have outlined research directions for the scientific community to further strengthen the body of knowledge. This work is important for researchers to identify key areas to explore as well as for policymakers in energy sector organizations to improve their security operations by understanding the associated implications of cybersecurity.

Digital transformation of businesses has seen tremendous growth recently, moreover, COVID-19 has increased online shopping. However, it is important for businesses that customers’ online shopping experience is secure and joyful. In this paper, customers’ security perception regarding some leading mobile commerce applications in Saudi Arabia is explored. Our survey questions focused on three aspects, namely: Consumer rating, trustworthiness, and credit card security. The results highlight that consumers perceive that mobile commerce applications in Saudi Arabia need further improvement in security. In this work, a model to improve customers’ security perception in Saudi Arabia is presented. This model can be generalized to other geographical regions as well. The model outlines different actions for practitioners and policymakers that help in improving security infrastructure, authentication mechanisms, and trustworthiness.

Accreditation is widely considered to be a vital tool for quality assurance in higher education; however, there is disagreement in the academic community on the intended benefits of accreditation. Preparing for accreditation requires extensive financial and human resources to complete the required documentation. All accreditation agencies require improvements in institutional infrastructure, enhanced student support, appropriate learning environments, and faculty development, which can directly improve students’ learning experiences. In this paper, we explore the impact of accreditation on students’ learning by using a case study-based approach. We selected four degree programs from a University in Saudi Arabia and compared the performances of students in different courses before and after acquiring local program accreditation (NCAAA). The results highlight that although there is no direct relationship between increased student performance and acquiring accreditation, there is a significant impact on the performance of student learning. However, there is a need for sustained efforts to continuously adopt accreditation-aligned practices to gain a sustained advantage. We have presented a model that can enable academic institutions to continuously adhere to best practices even if no accreditation visit has been scheduled in the near future. This way, academic programs can consistently improve their processes and enhance student learning.

Program outcome assessment is a complex process that demands careful planning and resources in order to accurately assess higher-order thinking skills. A well-defined assessment approach provides detailed insights into program weaknesses and leads to continuous improvement. Whereas a poor assessment approach does not reflect the underlying weaknesses and may result in a useless effort. Furthermore, each accreditation body may have a different recommended outcome measurement approach. As a result, academic institutions may make adhoc choices just to satisfy accreditation requirements rather than designing a sustainable measurement approach. On the other hand, the magnitude of huge tasks for satisfying multiple accreditation bodies results in fatigue and mental stress for academic staff. ABET is a well-known international program accreditation body, and NCAAA is a local accreditation body for academic programs in the Kingdom of Saudi Arabia. In this paper, we have documented that how a sustainable outcome measurement mechanism can be designed to satisfy both ABET and NCAAA requirements. The core contribution of this paper is relevant specifically for academic programs in the Kingdom striving to meet both ABET and NCAAA requirements and is also relevant for all education programs to design an appropriate program assessment approach to ensure a sustainable process to foster better learning among students.

With the evolution of new knowledge, scientific discourses are overlapping, and academic fields are becoming multidisciplinary. This multidisciplinary nature provides flexibility for educational establishments to maneuver academic programs, however teaching such multidisciplinary content is a challenging task for faculty. Human Computer Interaction course is one such example, which has its roots in psychology, sociology, anthropology, cultural studies, information science, computer science and design science. This course is an essential part of many computer science, software engineering and information systems undergraduate programs. In this paper, we present our experience of teaching this course at a University in Saudi Arabia to enrich the body of knowledge for improving the students learning experience.