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The Impact of Industry 4.0 on Innovative Organisations, A Thematic Review using the PRISMA Statement 2020
Get PDFThe fast growth of technologies during the Industry 4.0 era resulted in new or evolved organisations forming. Throughout the Fourth Industrial Revolution, the interaction between technology and humans evolved. Furthermore, the skills and capacities of individuals and organisations are changing due to the abundance of technology. This study investigated the impact of industry 4.0 on innovative organisations and used thematic analysis to identify the major themes. VOS viewer content analysis and critical terms of occurrences analysis were used to identify the major themes. In addition, the PRISMA statement 2020 is applied for the methodological part. The results indicate three significant themes business models, innovative organisations, and digital transformation. The findings show that changes in the global economy and market needs are forcing businesses to adopt technical breakthroughs made possible by digital transformation. it is considered that adequate resources, experienced and capable workers, and well-organized, adequately adaptable, and creative procedures are required for innovative organisations. In addition, HRM practises in the digital era must incorporate teleworking, promote employee engagement in achieving the aim of digital transformation, and incentivise a proper leadership style. Also, technological advancement drives businesses to innovate in their everyday production, supply, value chains, and numerous operations, allowing them to adapt quickly to client requests.
 
Corporate Digital Literacy Mandates: Using SDT-Based Strategies to Circumvent “Quiet Quitting” Syndrome
Get PDFEnvision an employee showing up faithfully every day for work but cognitively checked out every minute (i.e., quiet quitting). This article adapts a futurist perspective to describe the adult education pedagogy of experiential learning in juxtaposition to the limitations of behaviorist employee training incentives. The authors conceptually apply Spiral Dynamic Theory (SDT) based predictive strategies to capitalize on the assumptions of intrinsic and extrinsic motivation themes among contemporary adult workers. The field of Adult and Continuing Education caters its teaching and learning to people who are 25 years of age and older. As employees, they bring to the corporate work environment a unique set of skills and life experiences that require pedagogical delivery that is innovative and motivating. Research shows that older adults are often technology averse. Therefore, scaffolding the employee’s use of technology and social media as expectations of the work tasks could help improve low digital literacy and increase self-efficacy. This paper offers Spiral Dynamic Theory (SDT) as an instrument for adult training and professional development design. 
Watermarking in Medical Image
Get PDFMedical image security is possible using digital watermarking techniques. Important information is included in a host medical image in order to provide integrity, consistency, and authentication in the healthcare information system. This paper introduces a proposed method for embedding invisible watermarking in the 3D medical image. The cover medical image used is DICOM which consists of a number of slices, each one representing a sense, firstly must separate the ROI (Region of Interest) and NROI (Not Region Of Interest) for each slice, the separation process performed by the particular person who selected by hand the ROI. The embedding process is based on a key generated from Arnold's chaotic map used as the position of a pixel in the slices with the highest saturation for embedding a secret message in the NROI because the ROI contains the information of the ill, so it cannot be modified. The evaluation of the proposed method using PSNR and MSE shows good results according to both requirements of the watermark system, the invisibility and quality of the watermarked medical image where the PSNR value is up to 43.3936 and MSE is up to 0.000041
Does the Sentiment Index Help Predict Crude Oil Prices?
Get PDFThe price fluctuations in the crude oil market remarkably influence the global economy since crude oil is an essential source of energy and plays a determinant role in most industrial sectors. The tremendous development of social media has generated many applications that can be used for sentiment analysis to improve the prediction of crude oil prices. Many researchers have also used technical indicators to predict oil prices. This study integrated several machine learning approaches—random forest, support vector machine, and long short-term memory—with a dynamic expanding moving window and fixed moving window to forecast one-period-ahead West Texas Intermediate (WTI) spot prices. We assessed the forecasting performance of these models using the root mean squared error and then compared prediction accuracy among the sentiment indicator, the technical indicator, and the lagged values of WTI spot prices using the Diebold–Mariano test. The forecasting simulation and empirical results show that the sentiment indicator is preferable to the technical indicator for forecasting WTI spot prices with machine learning approaches. Interestingly, we also find that using the sentiment indicator provides a better prediction performance than using lagged values of crude oil prices
Investigation and Analysis of Private Doctors Helping the Elderly Care Market
Get PDFChina has a high degree of population aging, pension has become a hot topic. Based on this, this study focuses on the private doctor service assisted pension market, and investigates doctors, young people and the elderly respectively. The correlation analysis was used to obtain the relationship between respondents' willingness to accept private doctors and various factors. Further with the help of Logistic regression model, it is concluded that doctors in private hospitals, young and middle-aged elderly men and elderly people living alone and with high cost of living are more willing to accept the service of private doctors
Influence of AI-driven Inquiry Teaching on Learning Outcomes
Get PDFIn the field of educational informatization, the integration of information technology with education and teaching is deepening. Rich information technologies, such as artificial intelligence (AI), have provided efficient support for optimizing the teaching process and improving teaching quality. Inquiry teaching aims to cultivate students’ learning abilities in all aspects. AI can assist teachers in organizing effective inquiry activities, formulating scientific explanations, highlighting the relationship between problems and assumptions, and utilizing empirical evidence to solve related problems, thereby enhancing the teaching effectiveness of the course. In this study, we comprehensively examined the teaching process of inquirybased teaching. We analyzed the impact of four components of AI-driven inquiry teaching (questioning, evidence acquisition, explanation focus, and evaluation summary) on learning outcomes. Additionally, we investigated the variations in learning outcomes resulting from college students’ familiarity with artificial intelligence. Results show that the Cronbach’s α coefficient of the questionnaire is 0.863 and the KMO value is 0.865. The four components of inquiry-based teaching, namely questioning, evidence acquisition, explanation focusing, and evaluation summary, have been found to enhance learners’ learning outcomes by 10%, 5%, 1%, and 10%, respectively. The level of familiarity of college students with AI displays a significance level of 0.05 (F = 2.682, p = 0.032). The study results have significant reference value for analyzing the appeal of AI-driven education and teaching reform, summarizing the process of AI-driven inquiry teaching, and assisting teachers in using AI technology to enhance classroom teaching and improve teaching effectiveness
AI-Assisted Emotion Recognition: Impacts on Mental Health Education and Learning Motivation
Get PDFWith the rapid advancements in artificial intelligence (AI) technology, its deployment in the field of education has gained considerable attention, particularly in the context of mental health education. Addressing the mounting academic and social pressures faced by contemporary students necessitates the utilization of cutting-edge techniques to accurately discern their emotional states and deliver customized learning resources. Existing methodologies for mental health education often fall short due to an over-reliance on educators’ experience and observations, as well as challenges in handling complex multimodal data. This research aims to investigate the integration of multimodal audio-visual features using a transformer architecture for emotion recognition. An enhanced probabilistic matrix factorization (PMF) model has been concurrently developed to facilitate tailored content recommendations for students. The goal is to provide a more accurate and effective approach to health education
A Phenomenological Analysis of Challenges and Benefits of Online Learning Transformation in the Masters of Health Professions Education
Get PDFLearning that challenges preconceived notions and inspires the development of fresh perspectives on the world has been referred to as transformative learning. This study offers a thorough analysis of how changes in learning have been reflected, including how they have an impact on curricula, in order to guide the master of health professions education’s potential field applications. Through purposive sampling, 15 students of MHPE from Islamic International Medical College, Rawalpindi, Pakistan have been chosen. The study design is phenomenological in nature. A semi-structured interview has been used. All the interviews were audio-recorded and separately transcribed. The transcribed interviews were then imported into NVivo software version 11 for analysis. A thematic analysis has been done and six themes are generated. The applications of distance learning positively related to teaching and learning practices and students identified a change in their attitudes toward distance learning. Major factors recognized were student-centered learning, small group discussions, peer-assisted learning, technology awareness, personal grooming, and motivation. About three-fourths of the sample population experienced a transformation in their distance learning after going through a Master’s in Health Professionals Education. The impact of hands-on activities and small group discussions turned out to be the strongest factors that caused the transformation in distance learning
Designing a Production-oriented Approach-Based Mobile-Assisted Interpreting Learning Module Using Fuzzy Delphi Method
Get PDFThis research addresses a significant gap in the field of interpreting education. While interpreting is widely acknowledged as a complex language skill, it has received minimal attention in educational research. Despite the advancements in language education, mobile-assisted learning has gained popularity as an effective teaching method. However, it remains largely unexplored in interpreting education. This study stands out by introducing a novel mobile-assisted interpreting learning (MAIL) module based on the productionoriented approach, which combines mobile technology with language learning. To ensure the credibility of the module, a fuzzy Delphi method (FDM) involving fifteen experts was employed. This method resulted in a strong consensus on the elements, objectives, content, procedure, and design of the mobile device. Notably, 37 out of the 39 elements received unanimous approval from the experts. The final output is a practical and implementable module called production-oriented approach-based mobile-assisted interpreting learning (POMAIL). It includes a clear flowchart designed for educators and researchers. This research makes a significant contribution to the field of education by providing valuable guidance in mobile-assisted learning and language education. It has the potential to reshape the field
Motivation Risks in Teaching Students at Secondary Technical Schools
Get PDFMotivation has long been of interest to many educational researchers, as it is seen as an essential ingredient in effective teaching and learning. Motivated students are more likely to be eager to learn and more willing to accept the challenges that come with the learning process. In our research, we wanted to specify the attitudes of secondary technical school students towards their studies and to find out what motivates and demotivates them. We aimed to determine potential risks to motivation (demotivators). We hypothesized that students’ intrinsic motivation could be strengthened by teachers if classes were seen as useful, interesting, and inspiring. Having chosen a questionnaire as our research method, we addressed more than 200 secondary technical schools from a public database and asked their management for permission to send a questionnaire on motivation risks to their students. The body of the questionnaire included items asking students to assess 8 potential negative factors, which could represent risks in motivation. Our research sample included 665 responses from 10 technical study programs. The Fuller method of paired comparison was used for our data analysis. The answers from students from various schools, school locations, years of study, and study programs did not show many differences when respondents indicated the primary motivation risks for their study. The impact of risky situations on students’ motivation to study technical subjects was dominantly connected with their cognitive needs, followed by social needs. Surprisingly, in the students’ answers, not much attention was dedicated to the achievement needs