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Application of edge computing and cloud service data system for doctors' psychological reconstruction after the epidemic
Wireless Networks ( IF 2.1 ) Pub Date : 2021-07-19 , DOI: 10.1007/s11276-021-02696-x
Xiujun Zhai 1
Affiliation  

In response to the problems that the new crown pneumonia epidemic may bring to doctors in schools of Chinese medicine, such as information overload, traumatic stress, changes in mentality, crisis of trust, safety when going abroad, and employment choices, explain from the perspective of medical teachers in Chinese medicine schools. The understanding of the epidemic and the major events during the epidemic, combined with the experience of the psychological impact of the past epidemic on the doctors in the school, to highlight the outstanding contributions of medical staff in the fight against the epidemic, and to emphasize the strong leadership of the party and the unity of the people during the fight against the epidemic. The huge role played by Chinese medicine in the fight against the epidemic is the principle. In recent years, cloud computing technology has been continuously developed and improved. Traditional infrastructure as a service has been unable to meet users' needs for cloud computing delivery capabilities. They hope that more and more traditional IT software will be delivered in the form of cloud services. This paper mainly studies the utility optimization and stable matching strategy of UDRN based on EH and limited character input, divides the nodes into multiple clusters, and implements the utility optimization strategy within the clusters. Model users and relays as energy buyers and energy sellers. First, when users choose relays as their candidates, the golden section method is used to obtain the best relay power to maximize user utility. Secondly, based on the principle of maximizing the utility of matching, a mutual preference matrix between users and relays is established. Finally, based on the mutual preference matrix, an improved UDRN stable matching algorithm is proposed through the less complex GS algorithm. This algorithm will play a great role in the psychological reconstruction of doctors after the epidemic.



中文翻译:

边缘计算和云服务数据系统在医生疫后心理重建中的应用

针对新冠肺炎疫情可能给中医药院校医生带来的信息过载、创伤性压力、心态转变、信任危机、出国安全、就业选择等问题,多角度解读中医学院的医学教师。对疫情及疫情期间重大事件的认识,结合以往疫情对学校医生心理影响的经验,突出医务人员在抗击疫情中的突出贡献,强调在抗击疫情的过程中,党的坚强领导和人民的团结一致。中医药在抗击疫情中的巨大作用是原则。最近几年,云计算技术不断发展和完善。传统的基础设施即服务已经无法满足用户对云计算交付能力的需求。他们希望越来越多的传统 IT 软件以云服务的形式交付。本文主要研究基于EH和有限字符输入的UDRN效用优化和稳定匹配策略,将节点划分为多个簇,在簇内实现效用优化策略。将用户和中继建模为能源买家和能源卖家。首先,当用户选择中继作为他们的候选时,使用黄金分割法来获得最佳中继功率以最大化用户效用。其次,基于匹配效用最大化的原则,建立用户和中继之间的互偏好矩阵。最后,基于互偏好矩阵,通过不太复杂的GS算法,提出了一种改进的UDRN稳定匹配算法。该算法将对医生在疫情后的心理重建起到很大的作用。

更新日期:2021-07-19
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