Remote Sensing Data Processing Process Scheduling Based on Reinforcement Learning in Cloud Environment

Task scheduling plays a crucial role in cloud computing and is a key factor determining cloud computing performance.To solve the task scheduling problem for remote sensing data processing in cloud computing,this paper proposes a workflow task scheduling algorithm—Workflow Task Scheduling Algorithm based on Deep Reinforcement Learning(WDRL).The remote sensing data process modeling is transformed into a directed acyclic graph scheduling problem.Then,the algorithm is designed by establishing a Markov decision model and adopting a fitness calculation method.Finally,combine the advantages of reinforcement learning and deep neural networks to minimize make-time for remote sensing data processes from experience.The experiment is based on the development of CloudSim and Python and compares the change of completion time in the process of remote sensing data.The results showthat compared with several traditionalmeta-heuristic scheduling algorithms,WDRL can effectively achieve the goal of optimizing task scheduling efficiency.

Volunteering and Depression among Older Adults: An Empirical Analysis Based on CLASS 2018

Introduction:Older adults are prone to high levels of depression due to their deteriorating physical functions and shrinking social networks after retirement.Volunteering as an important social activity is essential for alleviating depression by building social network.This paper aims to examine the effect of volunteering on depression among older adults by using China Longitudinal Aging Social Survey(CLASS 2018)data.Methods:This study uses descriptive analysis and chi-square tests to show differences in demographic factors of older adults’volun-teerism participation,followed by bivariate correlation analysis to examine the correlation between the vital vari-ables.Afterward,stratified linear regression analysis is used to research the significant level and impact between volunteering and degree of expertise,frequency,and variety of participation.Results:8,459 older adults are included in study.The research reveals that older adults who are younger,live in urban areas,are married,or have a higher degree of education tend to have fewer depressive symptoms.Meanwhile,participation in volun-teering(OR=0.90,95%CI:0.8,1.1,p<0.001),as well as that demands specialized skills(OR=0.51,95%CI:0.30,0.2,p<0.001),more frequency of participation(OR=1.85,95%CI:1.53,2.18,p<0.001),and a wider variety of activities(OR=0.21,95%CI:0.12,0.29,p<0.001),all have a positive influence on depression levels.Discussion/Conclusion:Older adults who participate in voluntary services have lower depression symptoms and should be encouraged to use their professional skills and increase participation frequency and variety in this process.This article suggests that governments should help older adults participate in voluntary services by time bank which will further strengthen social ties,rebuild social networks and alleviate depression symptoms of older adults.