Three-Dimensional Foot Position Estimation Based on Footprint Shadow Image Processing and Deep Learning for Smart Trampoline Fitness System.

In the wake of COVID-19, the digital fitness market combining health equipment and ICT technologies is experiencing unexpected high growth. A smart trampoline fitness system is a new representative home exercise equipment for muscle strengthening and rehabilitation exercises. Recognizing the motions of the user and evaluating user activity is critical for implementing its self-guided exercising system. This study aimed to estimate the three-dimensional positions of the user's foot using deep learning-based image processing algorithms for footprint shadow images acquired from the system. The proposed system comprises a jumping fitness trampoline; an upward-looking camera with a wide-angle and fish-eye lens; and an embedded board to process deep learning algorithms. Compared with our previous approach, which suffered from a geometric calibration process, a camera calibration method for highly distorted images, and algorithmic sensitivity to environmental changes such as illumination conditions, the proposed deep learning algorithm utilizes end-to-end learning without calibration. The network is configured with a modified Fast-RCNN based on ResNet-50, where the region proposal network is modified to process location regression different from box regression. To verify the effectiveness and accuracy of the proposed algorithm, a series of experiments are performed using a prototype system with a robotic manipulator to handle a foot mockup. The three root mean square errors corresponding to X, Y, and Z directions were revealed to be 8.32, 15.14, and 4.05 mm, respectively. Thus, the system can be utilized for motion recognition and performance evaluation of jumping exercises.

Understanding Customer Responses to Service Failures during the COVID-19 Pandemic for Sustained Restaurant Businesses: Focusing on Guanxi

Due to the COVID-19 pandemic, restaurants worldwide, including China, have been forced to protect public health by following food safety standards and adapting to the necessary social distancing practices. Accordingly, restaurant diners who are concerned about food safety and unsure of whether it is truly safe to dine out, put more importance on the entire stages of service consumption. Restaurants must make their best efforts to minimize service failures in their service provision process and outcomes. Given that customers from different cultures are reported to evaluate service quality differently, this study was designed to investigate what actions Chinese customers who encounter service failures would take under the influence of Guanxi. Guanxi represents Chinese attitudes towards long-term individual and business relationships and ultimately involves moral obligations and mutual favors. Analyzing our structural equation model using 439 responses obtained from Chinese diners, this study determined that Chinese consumers would react differently in the service process failures and outcome failures in terms of negative word-of-mouth, direct complaints, switching intention, and revisit intention. More importantly, this study confirmed the significant moderating effects of Guanxi within the proposed relationships. Based on the study’s findings, useful implications are provided for academics and practitioners regarding sustained restaurant businesses.