Assembly-Line Health Check up in Digitalized Hospital

The health check up flow of digital hospital can be consulted with the assem bly line of industry factory.Because they have the following same features:highly specialized workstation, closeness and continuance,rhythm,balanced production,continuous production.The essential prerequisites are as the follows:The inspecting item s and methods should be stable;advanced product mix and stable production design;standardized raw m aterial,consumption,procedure, inspection method;there are lots of request for health inspection;the customers move at the least unit;the space arrangement should be reasonable;the time arrangement should be proportion. With the com puter net,the digital inspection can achieves the raw material controlling accurately. The basis of check up line concerns about equipm ent,net and software,data collection,and per- sonnel.The group technology is used in the health inspection flow design of the digital hospital in the field of items custom ers and zone redivided.The digital assembly linem ic health inspect has the following stages:m ember registering,notice,check in,arrange order,tim e control,report,feed- back and analysis. The assem bly linemic has following advantages:increasing the productivity, the space utility,satisfaction of customer,fund returning,lowering the cost and ensuring the quality.

Research and applications of artificial neural network in pavement engineering:A state-of-the-art review

Given the great advancements in soft computing and data science,artificial neural network(ANN)has been explored and applied to handle complicated problems in the field of pavement engineering.This study conducted a state-of-the-art review for surveying the recent progress of ANN application at different stages of pavement engineering,including pavement design,construction,inspection and monitoring,and maintenance.This study focused on the papers published over the last three decades,especially the studies conducted since 2013.Through literature retrieval,a total of 683 papers in this field were identified,among which 143 papers were selected for an in-depth review.The ANN architectures used in these studies mainly included multi-layer perceptron neural network(MLPNN),convolutional neural network(CNN)and recurrent neural network(RNN)for processing one-dimensional data,two-dimensional data and time-series data.CNN-based pavement health inspection and monitoring attracted the largest research interest due to its potential to replace human labor.While ANN has been proved to be an effective tool for pavement material design,cost analysis,defect detection and maintenance planning,it is facing huge challenges in terms of data collection,parameter optimization,model transferability and low-cost data annotation.More attention should be paid to bring multidisciplinary techniques into pavement engineering to tackle existing challenges and widen future opportunities.