This document outlines the advancements in AI- accelerated frame generation utilizing Neural Processing Units (NPU) in mobile devices. The integration of NPU technology enhances the processing efficiency of mobile graphics, enabling real-time frame generation that significantly improves video and image quality. By leveraging specialized hardware designed for AI computations, the system reduces latency and optimizes power consumption, making it ideal for demanding applications such as gaming and augmented reality. This paper discusses the underlying architecture of NPUs, their role in accelerating frame generation, and the potential impacts on user experience in mobile environments. The findings illustrate how NPU-driven solutions can transform mobile graphics, offering a more immersive and responsive experience while efficiently managing resources.

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.

This study looked at how adding augmented reality (AR) to Jordanian fast-food apps during the pandemic impacts brand identity, consumer views, and interactions. It wanted to see if AR strengthens brand connections or leads to brand dilution concerns in the industry. The research utilized a qualitative approach, employing semi-structured interviews with 52 marketing managers from diverse fast-food establishments across Jordan. The study highlighted how mobile apps, especially AR, changed brand interactions in Jordan’s fast-food market. They boosted convenience and engagement but raised worries about food quality and brand dilution due to heavy app use. It stressed the need to balance tech innovation, preserve brand identity, offer personalized experiences, understand user behavior, and tackle app development challenges for better brand loyalty. The research offers practical implications for stakeholders, recommending strategic AR integration, a user-centric approach, cultural sensitivity in tech adoption, and the preservation of emotional connections. It emphasizes the significance of maintaining a delicate balance between leveraging technological advancements and safeguarding the distinctiveness of individual brand identities within an increasingly app-centric landscape. This study uncovers AR’s influence in Jordan’s fast-food scene, highlighting its transformative power and possible drawbacks. It offers practical advice for industry players, guiding them on how to navigate the digital shift without compromising brand integrity or customer connections.

Hazards are the primary cause of occupational accidents, as well as occupational safety and health issues. Therefore, identifying potential hazards is critical to reducing the consequences of accidents. Risk assessment is a widely employed hazard analysis method that mitigates and monitors potential hazards in our everyday lives and occupational environments. Risk assessment and hazard analysis are observing, collecting data, and generating a written report. During this process, safety engineers manually and periodically control, identify, and assess potential hazards and risks. Utilizing a mobile application as a tool might significantly decrease the time and paperwork involved in this process. This paper explains the sequential processes involved in developing a mobile application designed for hazard analysis for safety engineers. This study comprehensively discusses creating and integrating mobile application features for hazard analysis, adhering to the Unified Modeling Language (UML) approach. The mobile application was developed by implementing a 10-step approach. Safety engineers from the region were interviewed to extract the knowledge and opinions of experts regarding the application’s effectiveness, requirements, and features. These interview results are used during the requirement gathering phase of the mobile application design and development. Data collection was facilitated by utilizing voice notes, photos, and videos, enabling users to engage in a more convenient alternative to manual note-taking with this mobile application. The mobile application will automatically generate a report once the safety engineer completes the risk assessment.

The mobile health market is expected to continue to grow that will make it harder for mobile application developer to compete. One of the most popular types of mobile health application is health and fitness applications. This application aims to modify user behavior; therefore, it requires user to use the system continuously in relatively longer period of time to effectively change user behavior. Thus, user satisfaction is essential and must be maintained to reach this goal. This study aims to define the mobile health application qualities that would influence user satisfaction level. Developer can priorities the most influential qualities when building their application. Quality dimensions would be explored by literature review and Google Play Store review and categorised using DeLone McLean IS Success Model. We identified 12 quality dimension that will furthered analysed using Kano Model. The data collecting was conducted with online form with 12 pairs of Kano two-dimensional questionnaires (n = 115). The results show that the important qualities of mobile health application are Privacy, Availability, Reliability, Ease of Use, Accuracy and Responsiveness, lack of these qualities would cause dissatisfaction from user. The developer might also consider to improve user interface and usefulness of the application to increase user satisfaction even though these qualities would not cause much of dissatisfaction