In the field of vocational education, no studies have examined the use of augmented reality (AR) learning technologies in the teaching of cosmetology. However, this study proposed the “Makeup AR” learning approach and conducted a quasi-experiment to examine the interaction effect between said approach and students with active and reflective learning styles. The research participants were 70 students from a vocational senior high school. The experimental group comprised 36 participants who were taught using Makeup AR, and the control group comprised 34 participants who were taught using an e-book. The results revealed that the use of Makeup AR improved students’ learning effectiveness. The proposed approach also effectively enhanced students’ self-efficacy and reduced their cognitive load. The students with a reflective learning style had a higher cognitive load than those with an active learning style when using the e-book learning approach. No difference in learning motivation was noted between the experimental and control groups. Overall, Makeup AR is suitable for makeup design certification courses in vocational senior high schools and can enhance learning effectiveness, improve students’ self-efficacy, and reduce cognitive load. This study suggests that the implementation of AR technology in certification courses can be beneficial to learning outcomes.

This study explored the technology learning model of the elderly in a senior learning center under the impact of the COVID-19 pandemic. Many senior learning centers were closed during the pandemic, and many of them adopted the mode of online education. However, problems such as decreased motivation and a lack of peer interaction still exist. To solve these problems, this study used the easy-to-implement calligraphy AR approach and E-book approach to conduct a quasi-experiment on the elderly of a calligraphy course offered by a senior learning center. The results show a higher learning motivation among the elderly who use calligraphy AR. The learning effectiveness and technology acceptance of the elderly in the E-book learning group were higher than those in the calligraphy AR group. The elderly mentioned that the E-book learning approach is more user-friendly. In general, in the face of the COVID-19 pandemic affecting the suspension of classes in senior centers, education through the development of technology has stimulated the growth of education in advanced learning centers. Through this kind of scientific and technological learning method, it will bring a whole new experience to the elderly. It can improve the stress relief methods, mental health, and quality of life of the elderly during the COVID-19 emergency shutdown, and provide a novel calligraphy technique learning experience for the elderly. Therefore, we believe that the calligraphy AR learning approach and the calligraphy E-book learning approach are practical and may promote quality of life and mental health of the elderly during the emergency closures due to COVID-19, providing elderly attendees with a novel calligraphy technology learning experience.

We study the problem of static index pruning in a renowned divergence minimization framework, using a range of divergence measures such as f-divergence and Rényi divergence as the objective. We show that many well-known divergence measures are convex in pruning decisions, and therefore can be exactly minimized using an efficient algorithm. Our approach allows postings be prioritized according to the amount of information they contribute to the index, and through specifying a different divergence measure the contribution is modeled on a different returns curve. In our experiment on GOV2 data, Rényi divergence of order infinity appears the most effective. This divergence measure significantly outperforms many standard methods and achieves identical retrieval effectiveness as full data using only 50% of the postings. When top-k precision is of the only concern, 10% of the data is sufficient to achieve the accuracy that one would usually expect from a full index.

Throughput of wireless packet transfer generally depends on the signal strength of wireless communication. The architecture of Wireless Distribution System (WDS) in an IEEE 802.11-based environment can avoid the decline of wireless signals and keep the data packet throughput by delivering packets among access points. This paper focuses on WDS and proposes an algorithm of Maximum Independent Set (MIS) to determine the subset of access points and reduce its computation time for wireless data packet transmission and achieving throughput improvement.