This study conducts a systematic review to explore the applications of Artificial Intelligence (AI) in mobile learning to support indigenous communities in Malaysia. It also examines the AI techniques used more broadly in education. The main objectives of this research are to investigate the role of Artificial Intelligence (AI) in support the mobile learning and education and provide a taxonomy that shows the stages of process that used in this research and presents the main AI applications that used in mobile learning and education. To identify relevant studies, four reputable databases—ScienceDirect, Web of Science, IEEE Xplore, and Scopus—were systematically searched using predetermined inclusion/exclusion criteria. This screening process resulted in 50 studies which were further classified into groups: AI Technologies (19 studies), Machine Learning (11), Deep Learning (8), Chatbots/ChatGPT/WeChat (4), and Other (8). The results were analyzed taxonomically to provide a structured framework for understanding the diverse applications of AI in mobile learning and education. This review summarizes current research and organizes it into a taxonomy that reveals trends and techniques in using AI to support mobile learning, particularly for indigenous groups in Malaysia.

The main objective of the study is to discuss the application of a participatory approach that involves the community of a small rural area in Italy to develop and maintain a sustainable local food system based on a very ancient and high-quality typical local bean. The efficacy of the approach in terms of the active involvement of local actors (farming communities, local administration, social associations, and civil society) and knowledge transfer for preserving the local food culture has been demonstrated. Possible improvements to the approach through digital technologies for stimulating the effective engagement of teenagers have also been discussed.

The article aims to evaluate the participation of below-poverty-line local community in tourism-related business activity in Himalayan state of Uttarakhand. Further, this article addressed for those who work in the tourism sector. The study employs a mix of methods, including survey data from 500 respondents with a random sampling approach, using Analysis of variance (ANOVA) statistical tools for analysis, other methods were interviews and observations at six tourism sites in Garhwal and four sites in Kumaun. Our findings showed that there has declined in community participation in tourism development, due to the lack of economic benefits obtained in the tourism sector, many believe that the tourism sector does not provide much income growth for them and does not make a significant contribution to the development of their region. Moreover, lack of understanding is considered the basis for community’s inability to play an active role, and lack of stakeholders’ involvement in encouraging them to improve their economy and culture through the tourism sector. Ultimately, this research also underlines the existence of some efforts by tourism travel to encourage public trust, which can help reduce poverty and increase community trust in tourism development in their region.

Increasing populations in cities have created challenges for the urban environment and also public health. Today, lacking sport participation opportunities in urban settings is a global concern. This study conceptualizes and develops a theoretical framework that identifies factors associated with effective urban built environments that help shape and reshape residents’ attitude toward sport activities and enhances their participation. Based on a comprehensive review of literature and by following the Stimulus-Organism-Response (SOR) theory and attitude change theory, a four-factor measurement model is proposed for studying urban built environment, including Availability, Accessibility, Design, and Safety. Further examinations are made on how these factors are channeled to transform residents’ attitudes and behavior associated with participating in sport activities, with Affordability as a moderator. Discussions are centered around the viability of the developed framework and its application for future research investigations.

This investigation derives formulas to predict the mixed convective surface conductance of a flat isotropic surface roughness having a convex perimeter in a Newtonian fluid with a steady forced flow in the plane of that roughness. Heat transfer measurements of a 30.5 cm square rough plate with forced air velocities between 0.1 m/s and 2.5 m/s were made by the present apparatus in two inclined and all five orthogonal orientations. The present work’s formulas are compared with 104 measurements in twelve data-sets. The twelve data-sets have root-mean-square relative error (RMSRE) values between 1.3% and 4% relative to the present theory. The present work’sformulas are also compared with 78 measurements in 28 data-sets on five vertical rough surfaces in horizontal flow from prior work. The five stucco data-sets have RMSRE values between 2.5% and 6.5%; the other data-sets have RMSRE values between 0.2% and 5%. 

Heat removal has become an increasingly crucial issue for microelectronic chips due to increasingly high speed and high performance. One solution is to increase the thermal conductivity of the corresponding dielectrics. However, traditional approach to adding solid heat conductive nanoparticles to polymer dielectrics led to a significant weight increase. Here we propose a dielectric polymer filled with heat conductive hollow nanoparticles to mitigate the weight gain. Our mesoscale simulation of heat conduction through this dielectric polymer composite microstructure using the phase-field spectral iterative perturbation method demonstrates the simultaneous achievement of enhanced effective thermal conductivity and the low density. It is shown that additional heat conductivity enhancement can be achieved by wrapping the hollow nanoparticles with graphene layers. The underlying mesoscale mechanism of such a microstructure design and the quantitative effect of interfacial thermal resistance will be discussed. This work is expected to stimulate future efforts to develop light-weight thermal conductive polymer nanocomposites.