Abstract: An active edge caching method based on community discovery and weighted federated learning for selecting an optimal caching user and developing an optimal caching strategy; user grouping method based on community discovery is first provided, users are divided into different user groups according to users' mobility and social attributes, degrees of importance of different users are computed in each user group, and most important user is selected as a caching node to provide content distribution services; a content popularity prediction framework based on attention weighted federated learning is provided for combining attention weighted federated learning mechanism with deep learning algorithm to predict future user preferences for different content, so as to improve content popularity prediction accuracy and solve user privacy disclosure; finally, hot content is cached on selected caching users according to prediction results, to achieve goals of reducing network transmission latency and network operation cost

Abstract: A folding device is provided. The folding device includes a bearing and fixing mechanism (1) configured to bear and fix a main body portion (21) of a to-be-folded device (2); a folding mechanism (3) located on at least one side of the bearing and fixing mechanism (1), the folding mechanism (3) being rotatably connected to the bearing and fixing mechanism (1) and configured to bear and fix a to-be-folded portion (22) of the to-be-folded device (2); and a driving mechanism (4) connected to the folding mechanism (3), the driving mechanism (4) being configured to drive the folding mechanism (3) to turn relative to the bearing and fixing mechanism (1), so as to fold the to-be-folded portion (22) to a side in a thickness direction of the main body portion (21). The folding device can fold automatically, and manual folding is avoided.