Fog computing (FC) has been presented as a modern distributed technology that will overcome the different issues that Cloud computing faces and provide many services. It brings computation and data storage closer to data resources such as sensors, cameras, and mobile devices. The fog computing paradigm is instrumental in scenarios where low latency, real-time processing, and high bandwidth are critical, such as in smart cities, industrial IoT, and autonomous vehicles. However, the distributed nature of fog computing introduces complexities in managing and predicting the execution time of tasks across heterogeneous devices with varying computational capabilities. Neural network models have demonstrated exceptional capability in prediction tasks because of their capacity to extract insightful patterns from data. Neural networks can capture non-linear interactions and provide precise predictions in various fields by using numerous layers of linked nodes. In addition, choosing the right inputs is essential to forecasting the correct value since neural network models rely on the data fed into the network to make predictions. The scheduler may choose the appropriate resource and schedule for practical resource usage and decreased make-span based on the expected value. In this paper, we suggest a model Neural Network model for fog computing task time execution prediction and an input assessment of the Interpretive Structural Modeling (ISM) technique. The proposed model showed a 23.9% reduction in MRE compared to other methods in the state-of-arts.

This study investigates the application and effectiveness of modern teaching techniques in improving reading literacy among elementary school students in Kazakhstan. In the rapidly evolving educational landscape, the integration of innovative pedagogical strategies is essential to foster student reading skills and general literacy. This study aims to explore how these modern teaching techniques can be applied to improve reading literacy among elementary school students in Kazakhstan. The study sample includes 64 respondents to the research. The key modern teaching techniques explored in this study include the use of digital learning tools, interactive reading sessions, differentiated instruction, and collaborative learning activities. The findings reveal significant improvements in reading literacy among students exposed to these techniques, highlighting the potential of modern pedagogy to bridge literacy gaps and promote educational equity. Furthermore, the study discusses the challenges and opportunities to implement these techniques within the Kazakhstani educational system. The results provide valuable information for educators, policymakers, and stakeholders aiming to improve reading literacy through innovative teaching practices.

Amidst China’s escalating aging population challenge, the efficacy and quality of private elderly care services are garnering increasing scrutiny. This research focuses on evaluating how service quality and customer perceived value influence the loyalty of elderly clients, with customer satisfaction acting as a mediating factor. Grounded in established service quality frameworks and loyalty theories, the study utilizes a quantitative methodology, administering surveys across eight private elderly care institutions in H city, China. A total of 600 surveys were collected, providing a comprehensive data set that encompasses five dimensions of service quality—tangibility, assurance, responsiveness, reliability, and empathy—as well as customer perceived value, satisfaction, and loyalty. Structural Equation Modeling (SEM) was employed to validate the hypothesized relationships. Findings reveal that service quality significantly boosts customer perceived value and satisfaction, which in turn markedly enhance customer loyalty. Notably, customer satisfaction emerged as a crucial mediator between service quality and loyalty, as well as between perceived value and loyalty. This study not only advances theoretical understanding of service quality impacts but also offers actionable insights for enhancing service delivery and customer loyalty in the context of private elderly care.

This study investigates the influence of service quality, destination facilities, destination image, and tourist satisfaction on tourist loyalty in the Pasar Lama Chinatown area of Tangerang City. Utilizing data from 400 respondents, the study employed structured questionnaires analyzed through descriptive statistics, reliability analysis, exploratory and confirmatory factor analysis, and structural equation modeling (SEM). The results reveal that service quality (β = 0.47, p < 0.001), destination facilities (β = 0.33, p < 0.001), and destination image (β = 0.4, p < 0.001) all significantly enhance tourist satisfaction, which in turn has a strong positive effect on loyalty (β = 0.58, p < 0.001). Direct paths also show that service quality, destination facilities, and destination image independently contribute to tourist loyalty. Bootstrapping confirms satisfaction’s mediating role between these factors and loyalty. Practical recommendations suggest prioritizing service quality improvements, facility enhancements, and a positive destination image to foster loyalty and promote tourism sustainability in Pasar Lama, China. These insights assist tourism managers in developing strategies to enhance long-term visitor retention and engagement in the area.

Promoting travelling intention within social media is significant for stakeholders to grasp a new tourism market and cultivate a new model for development of tourism industry. This study aims to understand path of destination image affecting travelling intention, and to investigate the mediation role of perceived value, furthermore, to uncover the role of moderator of situational involvement. This paper conducts a survey on tourists visiting Guilin, collecting 435 questionnaires, and uses the structural equation modeling method to explore how the image of the tourism destination affects tourists’ willingness to travel. The research results indicate that cognitive image, emotional image, and projected image all have a significant positive impact on perceived value, perceived value as a significant mediator to bridge the relationship among the destination image and tourists’ travel intention. Furthermore, situational involvement plays a negative moderating role in the mediating effect of emotional value. This study endeavor will serve to enrich the understanding of perceived value theory, destination image theory, and tourism consumer behavior theory. It will also provide theoretical foundations and policy recommendations for guiding tourism consumer behavior, analyzing destination image perception, and destination marketing.