Validation of key components in designing a social skills training content using virtual reality for high functioning autism youth-A Fuzzy Delphi method.

The use of virtual reality in social skills training for high functioning autism spectrum disorder (HFASD) youth has been found to be engaging and enjoyable. Despite the promising results, previous literature indicates that there has been no consensus on the social skills target in the training content. There is also limited research on how evidence-based strategies like cognitive and behaviour techniques are instantiated into the VR environment to teach social skills. The aim of this study is to determine the key components to design a social skills training content using virtual reality for youths with HFASD. The Fuzzy Delphi method (FDM) was used to obtain expert consensus on social skills difficulties and cognitive behavioral techniques included in the content in three phases. In phase 1, a questionnaire was developed from in-depth interviews and scientific literature review. The in-depth interviews were conducted with 13 HFASD youth, 7 parents and 6 experts. In phase 2, 3 experts rated the relevance of the items in the questionnaire using an item-level content validity index (I-CVI) assessment. In phase 3, the questionnaire was distributed to 10 experts to rate their level of agreement on each component using a 7-point Likert scale. Components that received a value above 75%, threshold value (d) ≤ 0.2, fuzzy score (A) ≥ α - cut value = 0.5 and higher rank based on defuzzification score were prioritized to be included in the content. Items that received higher expert consensus on social skills difficulties included assessing non-verbal responses, initiating, maintaining, and leaving conversations, emotional difficulties and difficulties in perspective taking. Cognitive and behavioral techniques that received higher expert consensus were psychoeducation, modelling, relaxation techniques, reinforcements, and perspective-taking questions. These key components can be used as a framework for the development of virtual learning content for social skills training in future studies.

Micro energy harvesting for IoT platform: Review analysis toward future research opportunities.

Micro-energy harvesting (MEH) is a technology of renewable power generation which is a key technology for hosting the future low-powered electronic devices for wireless sensor networks (WSNs) and, the Internet of Things (IoT). Recent technological advancements have given rise to several resources and technologies that are boosting particular facets of society. Many researchers are now interested in studying MEH systems for ultra-low power IoT sensors and WSNs. A comprehensive study of IoT will help to manage a single MEH as a power source for multiple WSNs. The popular database from Scopus was used in this study to perform a review analysis of the MEH system for ultra-low power IoT sensors. All relevant and important literature studies published in this field were statistically analysed using a review analysis method by VOSviewer software, and research gaps, challenges and recommendations of this field were investigated. The findings of the study indicate that there has been an increasing number of literature studies published on the subject of MEH systems for IoT platforms throughout time, particularly from 2013 to 2023. The results demonstrate that 67% of manuscripts highlight problem-solving, modelling and technical overview, simulation, experimental setup and prototype. In observation, 27% of papers are based on bibliometric analysis, systematic review, survey, review and based on case study, and 2% of conference manuscripts are based on modelling, simulation, and review analysis. The top-cited articles are published in 5 different countries and 9 publishers including IEEE 51%, Elsevier 16%, MDPI 10% and others. In addition, several MEH system-related problems and challenges are noted to identify current limitations and research gaps, including technical, modelling, economic, power quality, and environmental concerns. Also, the study offers guidelines and recommendations for the improvement of future MEH technology to increase its energy efficiency, topologies, design, operational performance, and capabilities. This study's detailed information, perceptive analysis, and critical argument are expected to improve MEH research's viable future.

Systematic Literature Review on Visual Analytics of Predictive Maintenance in the Manufacturing Industry.

The widespread adoption of cyber-physical systems and other cutting-edge digital technology in manufacturing industry production facilities may motivate stakeholders to embrace the idea of Industry 4.0. Some industrial companies already have different sensors installed on their machines; however, without proper analysis, the data collected is not useful. This systematic review's main goal is to synthesize the existing evidence on the application of predictive maintenance (PdM) with visual aids and to identify the key knowledge gaps in areas including utilities, power generation, industry, and energy consumption. After a thorough search and evaluation for relevancy, 37 documents were identified. Moreover, we identified the visual analytics of PdM, including anomaly detection, planning/scheduling, exploratory data analysis (EDA), and explainable artificial intelligence (XAI). The findings revealed that anomaly detection was a major domain in PdM-related works. We conclude that most of the literature lacks depth in terms of an overall framework that combines data-driven and knowledge-driven techniques of PdM in the manufacturing industry. Some works that utilized both techniques indicated promising results, but there is insufficient research on involving maintenance personnel's feedback in the latter stage of PdM architecture. Thus, there are still pertinent issues that need to be investigated, and limitations that need to be overcome before PdM is deployed with minimal human involvement.

The development of sustainable IoT E-waste management guideline for households.

The introduction of new technology, such as the Internet of Things (IoT), entails a growth in digital devices, which could ultimately result in a high amount of electronic trash (e-waste) production if they are not appropriately managed. Apart from that, the regulation on possible "IoT E-waste" generation is yet to be regulated, probably due to the new development and implementation of IoT globally. Hence, this paper proposed a Sustainable IoT E-waste Management guideline for households. This guideline could assist government agencies and policymakers in their strategies, planning, development, and implementation of a sustainable household IoT e-waste management initiatives in Malaysia. This study is an exploratory study that adopts a qualitative case study research method. The guideline was developed based on the Integrated Sustainable Waste Management (ISWM) Model. This guideline contributes to Malaysia's sustainability agenda in reducing carbon emissions intensity towards 2030 by 45 percent.

An Overview of Ontologies in Virtual Reality-Based Training for Healthcare Domain.

Virtual reality (VR) is one of the state-of-the-art technological applications in the healthcare domain. One major aspect of VR applications in this domain includes virtual reality-based training (VRT), which simplifies the complicated visualization process of diagnosis, treatment, disease analysis, and prevention. However, not much is known on how well the domain knowledge is shared and considered in the development of VRT applications. A pertinent mechanism, known as ontology, has acted as an enabler toward making the domain knowledge more explicit. Hence, this paper presents an overview to reveal the basic concepts and explores the extent to which ontologies are used in VRT development for medical education and training in the healthcare domain. From this overview, a base of knowledge for VRT development is proposed to initiate a comprehensive strategy in creating an effective ontology design for VRT applications in the healthcare domain.

Business process improvement methods in healthcare: a comparative study.

PURPOSE: According to the literature concerned with this study, less than satisfactory outcomes have been achieved through implementing business process improvements methods (BPIMs) in industries, in general, and in healthcare, in particular. The existing methods used need to be enhanced in order to create more effective outcomes. There has also been a lack of studies documenting gaps or shortfalls in implementing BPIMs, to be presented to the BPI research community. Therefore, researchers of this paper have attempted to fill gaps between theory and practice. On the contrary, there is also a need to link practical outcomes in the healthcare domain with those of the BPI research community. The purpose of this paper is to review popular BPIMs, techniques and tools applied in the healthcare domain; it seeks to examine and highlight their significant roles, clarify their pros and cons, and find opportunities to enhance their impact on the achievement of more sustainable improvements in the healthcare domain. DESIGN/METHODOLOGY/APPROACH: This study has been carried out by using a methodology combining an in-depth literature review with a comparison framework, which is called as the "Framework for Comparing Business Process Improvement Methods." The framework is composed of seven dimensions and has been adapted from four recognized, related frameworks. In addition to the in-depth review of related literature and the adapted comparison framework, researchers have conducted several interviews with healthcare BPI practitioners in different hospitals, to attain their opinions of BPI methods and tools used in their practices. FINDINGS: The main results have indicated that significant improvements have been achieved by implementing BPIMs in the healthcare domain according to related literature. However, there were some shortfalls in the existing methods that need to be resolved. The most important of these has been the shortfall in representing and analyzing targeted domain knowledge during improvement phases. The tool currently used for representing the domain, specifically flowcharts, is very abstract and does not present the domain in a clear form. The flowchart tool also fails to clearly present the separation of concerns between business processes and the information systems processes that support a business in a given domain. PRACTICAL IMPLICATIONS: The findings of this study can be useful for BPI practitioners and researchers, mainly within the healthcare domain. The findings can help these groups to understand BPIMs shortfalls and encourage them to consider how BPIMs can be potentially improved. ORIGINALITY/VALUE: This researchers of this paper have proposed a comparison framework for highlighting popular BPIMs in the healthcare domain, along with their uses and shortfalls. In addition, they have conducted a deep literature review based on the practical results obtained from different healthcare institutions implementing unique BPIMs around the world. There has also been valuable interview feedback attained from BPI leaders of specific hospitals in Saudi Arabia. This combination is expected to contribute to knowledge of BPIMs from both theoretical and practical points of view.