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This study aims to explicate the strategic utilisation of e-learning is of upmost significance as e-learning plays a pivotal role in the improvement of healthcare learning and knowledge transfer, especially in developing countries and in pursuing of Millennium Development Goals (MDGs). Rapid technology changes in the learning and knowledge transfer landscape markedly, the swift pace of e-learning leaving healthcare providers no choice if they want to remain competitive. Human capital, an important element in contemporary employee relations scenario, has become the most significant competitive advantage in healthcare delivery systems. As such, healthcare providers need a new strategy for learning and training of their employees. Besides, the knowledge and competencies of healthcare providers are not only vital component but also essential to the quality of care and health of the society. Thus, these rationales exert that today's healthcare providers are embracing e-learning. The benefits of e-learning are extremely compelling. They include a reduction in costs associated with employee travelling; reduction in time spent away from the patients and reduced learning times. Also, this study describes the United Nations University International Institute for Global Health (UNU-IIGH) strategies, best practices and experiences in delivering e-learning to healthcare workforce of developing countries.

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Usage and adoption of cloud computing (CC) outperform its usage in educational institutions. Studies that are related to the adoption of cloud based e-learning (CBEL) are limited. The purpose of this paper is to investigate the effect of individual factors (PE, EE, SI, and SA) on the BI to adopt CBEL. It also aims to test the mediating effect of TR and the moderating effect of ITK. The population of this study is student from four Lebanese universities. Stratified random sampling was deployed. A total of 422 complete and usable responses were collected and data was analyzed using Partial Least Square (PLS). Individual factors affect significantly the BI toward CBEL. SA is the most important determinant followed by PE, SI and EE. BI affects positively the UB and TR partial mediates the effect of individual factors on BI while ITK does not moderate this effect. This study tested the UTAUT in CBEL and it included TR and ITK with UTAUT. The study also enriched the literature in the developing countries and the literature of CBEL

The study reviews and attempts to identify the Information Culture factors that impact the users' attitudes toward the adoption of Health Information System (HIS) in developing counties. It is based on a review and a critical analysis of previous research related to the adoption of HIS, especially in developing countries. The study discovered Information Culture related adoption factors: Information Need, Compatibility, Access to Health Information Resources, Information Sharing, Self-efficacy, Attitudes and Awareness towards the importance of HIS. These factors are known to effect the adoption of HIS in developing countries. All these factors suit the context of the current study. Thus, the review outlines the details of each factor and its relevance to the research issue. The outcome of the review-based study revealed that such crucial factors co-exist in two domain areas; Information Culture and HIS adoption.

Organizations in various industries have widely developed the artificial intelligence (AI) maturity model as a systematic approach. This study aims to review state-of-the-art studies related to AI maturity models systematically. It allows a deeper understanding of the methodological issues relevant to maturity models, especially in terms of the objectives, methods employed to develop and validate the models, and the scope and characteristics of maturity model development. Our analysis reveals that most works concentrate on developing maturity models with or without their empirical validation. It shows that the most significant proportion of models were designed for specific domains and purposes. Maturity model development typically uses a bottom-up design approach, and most of the models have a descriptive characteristic. Besides that, maturity grid and continuous representation with five levels are currently trending in maturity model development. Six out of 13 studies (46%) on AI maturity pertain to assess the technology aspect, even in specific domains. It confirms that organizations still require an improvement in their AI capability and in strengthening AI maturity. This review provides an essential contribution to the evolution of organizations using AI to explain the concepts, approaches, and elements of maturity models.

The global expansion of the Visual Internet of Things (VIoT)’s deployment with multiple devices and sensor interconnections has been widespread. Frame collusion and buffering delays are the primary artifacts in the broad area of VIoT networking applications due to significant packet loss and network congestion. Numerous studies have been carried out on the impact of packet loss on Quality of Experience (QoE) for a wide range of applications. In this paper, a lossy video transmission framework for the VIoT considering the KNN classifier merged with the H.265 protocols. The performance of the proposed framework was assessed while considering the congestion of encrypted static images transmitted to the wireless sensor networks. The performance analysis of the proposed KNN-H.265 protocol is compared with the existing traditional H.265 and H.264 protocols. The analysis suggests that the traditional H.264 and H.265 protocols cause video conversation packet drops. The performance of the proposed protocol is estimated with the parameters of frame number, delay, throughput, packet loss ratio, and Peak Signal to Noise Ratio (PSNR) on MATLAB 2018a simulation software. The proposed model gives 4% and 6% better PSNR values than the existing two methods and better throughput.

Of recent, Building Information Modelling (BIM) has become an influential paradigm for the development of better project delivery practices to improve construction and operational efficiencies. In the last 6 years, a significant number of studies have been published on the integration of BIM in Internet of Things (IoT). This paper aims to examine the general research productivity, demographics, and trends shaping the research domain. Hence, the paper will also help to identify, categorize, and synthesize important studies in the research domain. In doing so, we adopt an evidence-based systematic mapping methodology to ensure the coverage of key studies through a systematic and unbiased selection and evaluation process which results in the final selection of 55 relevant studies. The results of the mapping study show that the research on the integration of BIM in IoT is gaining more attention in last 6 years with stable and consistent publication output. Prominent application domains, validation methods, contribution facets, research types, and simulation tools in the field of study were identified and presented. Five research types were also identified, i.e. solution proposal, experience paper, evaluation research, validation research, and opinion paper, with solution proposals getting more research attention. In general, the overall demographics of the research domain were presented and discussed.