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Racket sports such as tennis are amongst the most popular recreational sports activities. Optimizing tennis teaching methods and improving teaching modes can effectively improve the teaching quality of tennis. In this study, a video and image action recognition system based on image processing techniques and Internet of things is developed to overcome the shortcomings of the traditional tennis teaching methods. To validate its performance, the students of tennis courses are divided into experimental group and control group, respectively. The control group is taught by using the traditional tennis teaching method whereas the experimental group is taught by using the IoT video and image recognition teaching system. Three factors of students including service throwing height, arm elbow angle, and knee bending angles of both groups are measured and compared with those of world elite tennis players. The results show that the students’ serving abilities in the experimental group are significantly improved using the video and image recognition system based on IoT, and they are better than those of the students in the control group. The proposed video and image processing technique can be applied in students’ physical education and can be employed to provide the basis for the innovation of tennis teaching strategies in physical education.

Rail operators in many countries discount group tickets to improve revenue by increasing price-driven demand. For individual passengers, dynamic pricing is beneficial for maximizing revenue based on the price discrimination principle. Usually, group fares are cheaper than individual fares. If too many group tickets are sold, there will not be enough tickets available to meet high-priced individual demand; by contrast, if not enough group tickets are sold and there is insufficient individual demand, the unsold seats will not have value once the train departs. Therefore, for railway operators, it is worth looking for a balance between group discounts and dynamic pricing to maximize benefits. Essentially, rail operators need to find the symmetry point of the expected revenue between accepting group bookings and reserving tickets for individuals when making decisions. In this study, we formulated a joint decision model of group ticket booking control and dynamic pricing and investigated the effect of the joint decision. The results of numerical experiments showed that incorporating group discounts into dynamic pricing can improve expected revenue when passenger demand is weak, and compared to setting fixed quantities for group tickets, dynamically controlling the limit of group bookings can effectively increase expected revenue. Further analysis of the impacts of time, number of tickets sold, and group demand was helpful to implement the proposed joint policy.

Metastable 1T′-phase transition metal dichalcogenides (TMDs) attract increasing interests owing to their fascinating physicochemical properties in superconductors, optical materials, and energy storage. However, spontaneous 1T′ to 2H phase transition severely hinders practical application of 1T′ TMD. In this study, through systematic investigation and theoretical simulation of phase change of 1T′ WS2, we demonstrate ultrathin 1T′ WS2 has significantly higher intrinsic thermal and antioxidant stabilities than the bulk counterparts. 1T′ to 2H phase transition temperature increases from 120°C to 350°C and durability increases from 2 days to more than 5 months in the air as thickness of 1T′ WS2 is lessened from bulk to monolayer. The higher stability of thinner 1T′ WS2 is attributed to stiffened intralayer bonds and enhanced thermal conductivity, originated from weakened interlayer Coulombic interactions. The high intrinsic phase stabilities of ultrathin 1T′ TMDs can pave the way for their wide tempting practical applications.

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