A Fast Tongue Detection and Location Algorithm in Natural Environment

The collection and extraction of tongue images has always been an important part of intelligent tongue diagnosis.At present,the collection of tongue images generally needs to be completed in a sealed,stable light environment,which is not conducive to the promotion of extensive tongue image and intelligent tongue diagnosis.In response to the problem,a newalgorithm named GCYTD(GELU-CA-YOLO Tongue Detection)is proposed to quickly detect and locate the tongue in a natural environment,which can greatly reduce the restriction of the tongue image collection environment.The algorithm is based on the YOLO(You Only Look Once)V4-tiny network model to detect the tongue.Firstly,the GELU(Gaussian Error Liner Units)activation function is integrated into the model to improve the training speed and reduce the number of model parameters;then,the CA(Coordinate Attention)mechanism is integrated into the model to enhance the detection precision and improve the failure tolerance of the model.Compared with the other classical algorithms,Experimental results show thatGCYTD algorithm has a better performance on the tongue images of all types in terms of training speed,tongue detection speed and detection precision,etc.The lighter model can contribute on deploying the tongue detection model on small mobile terminals.

Correlation-Aware Replica Prefetching Strategy to Decrease Access Latency in Edge Cloud

With the number of connected devices increasing rapidly,the access latency issue increases drastically in the edge cloud environment.Massive low time-constrained and data-intensive mobile applications require efficient replication strategies to decrease retrieval time.However,the determination of replicas is not reasonable in many previous works,which incurs high response delay.To this end,a correlation-aware replica prefetching(CRP)strategy based on the file correlation principle is proposed,which can prefetch the files with high access probability.The key is to determine and obtain the implicit high-value files effectively,which has a significant impact on the performance of CRP.To achieve the goal of accelerating the acquisition of implicit highvalue files,an access rule management method based on consistent hashing is proposed,and then the storage and query mechanisms for access rules based on adjacency list storage structure are further presented.The theoretical analysis and simulation results corroborate that CRP shortens average response time over 4.8%,improves average hit ratio over 4.2%,reduces transmitting data amount over 8.3%,and maintains replication frequency at a reasonable level when compared to other schemes.