2016年5月18日,《地震研究快报》（Seismological Research Letters）在线发表了题为《德克萨斯州诱发地震历史回顾》（A historical review of induced earthquakes in Texas）的文章指出,自1925年以来,人类活动已经在德克萨斯州引发...2016年5月18日,《地震研究快报》（Seismological Research Letters）在线发表了题为《德克萨斯州诱发地震历史回顾》（A historical review of induced earthquakes in Texas）的文章指出,自1925年以来,人类活动已经在德克萨斯州引发多次地震,此后,人为诱发地震迅速遍布整个美国。展开更多
Support vector machines （SVMs） are combined with the artificial immune network （aiNet）, thus forming a new hybrid ai-SVM algorithm. The algorithm is used to reduce the number of samples and the training time of SV...Support vector machines （SVMs） are combined with the artificial immune network （aiNet）, thus forming a new hybrid ai-SVM algorithm. The algorithm is used to reduce the number of samples and the training time of SVM on large datasets, aiNet is an artificial immune system （AIS） inspired method to perform the automatic data compression, extract the relevant information and retain the topology of the original sample distribution. The output of aiNet is a set of antibodies for representing the input dataset in a simplified way. Then the SVM model is built in the compressed antibody network instead of the original input data. Experimental results show that the ai-SVM algorithm is effective to reduce the computing time and simplify the SVM model, and the accuracy is not decreased.展开更多
Liver transplantation and blood purification therapy,including plasmapheresis,hemodiafiltration,and bioartificial liver support,are the available treatments for patients with severe hepatic failure.Bioartificial liver...Liver transplantation and blood purification therapy,including plasmapheresis,hemodiafiltration,and bioartificial liver support,are the available treatments for patients with severe hepatic failure.Bioartificial liver support,in which living liver tissue is used to support hepatic function,has been anticipated as an effective treatment for hepatic failure.The two mainstream systems developed for bioartificial liver support are extracorporeal whole liver perfusion(ECLP)and bioreactor systems.Comparing various types of bioartificial liver in view of function,safety,and operability,we concluded that the best efficacy can be provided by the ECLP system.Moreover,in our subsequent experiments comparing ECLP and apheresis therapy,ECLP offers more ammonia metabolism than HD and HF.In addition,ECLP can compensate amino acid imbalance and can secret bile.A controversial point with ECLP is the procedure is labor intensive,resulting in high costs.However,ECLP has the potential to reduce elevated serum ammonia levels of hepatic coma patients in a short duration.When these problems are solved,bioartificial liver support,especially ECLP,can be adopted as an option in ordinary clinical therapy to treat patients with hepatic failure.展开更多
To automatically detecting whether a person is wearing mask properly,we propose a face mask detection algorithm based on hue-saturation-value(HSV)+histogram of oriented gradient(HOG)features and support vector machine...To automatically detecting whether a person is wearing mask properly,we propose a face mask detection algorithm based on hue-saturation-value(HSV)+histogram of oriented gradient(HOG)features and support vector machines(SVM).Firstly,human face and five feature points are detected with RetinaFace face detection algorithm.The feature points are used to locate to mouth and nose region,and HSV+HOG features of this region are extracted and input to SVM for training to realize detection of wearing masks or not.Secondly,RetinaFace is used to locate to nasal tip area of face,and YCrCb elliptical skin tone model is used to detect the exposure of skin in the nasal tip area,and the optimal classification threshold can be found to determine whether the wear is properly according to experimental results.Experiments show that the accuracy of detecting whether mask is worn can reach 97.9%,and the accuracy of detecting whether mask is worn correctly can reach 87.55%,which verifies the feasibility of the algorithm.展开更多
Although many works have been done to construct prediction models on yarn processing quality,the relation between spinning variables and yarn properties has not been established conclusively so far.Support vector mach...Although many works have been done to construct prediction models on yarn processing quality,the relation between spinning variables and yarn properties has not been established conclusively so far.Support vector machines(SVMs),based on statistical learning theory,are gaining applications in the areas of machine learning and pattern recognition because of the high accuracy and good generalization capability.This study briefly introduces the SVM regression algorithms,and presents the SVM based system architecture for predicting yarn properties.Model selection which amounts to search in hyper-parameter space is performed for study of suitable parameters with grid-research method.Experimental results have been compared with those of artificial neural network(ANN)models.The investigation indicates that in the small data sets and real-life production,SVM models are capable of remaining the stability of predictive accuracy,and more suitable for noisy and dynamic spinning process.展开更多
文摘2016年5月18日,《地震研究快报》（Seismological Research Letters）在线发表了题为《德克萨斯州诱发地震历史回顾》（A historical review of induced earthquakes in Texas）的文章指出,自1925年以来,人类活动已经在德克萨斯州引发多次地震,此后,人为诱发地震迅速遍布整个美国。
文摘Support vector machines （SVMs） are combined with the artificial immune network （aiNet）, thus forming a new hybrid ai-SVM algorithm. The algorithm is used to reduce the number of samples and the training time of SVM on large datasets, aiNet is an artificial immune system （AIS） inspired method to perform the automatic data compression, extract the relevant information and retain the topology of the original sample distribution. The output of aiNet is a set of antibodies for representing the input dataset in a simplified way. Then the SVM model is built in the compressed antibody network instead of the original input data. Experimental results show that the ai-SVM algorithm is effective to reduce the computing time and simplify the SVM model, and the accuracy is not decreased.
文摘Liver transplantation and blood purification therapy,including plasmapheresis,hemodiafiltration,and bioartificial liver support,are the available treatments for patients with severe hepatic failure.Bioartificial liver support,in which living liver tissue is used to support hepatic function,has been anticipated as an effective treatment for hepatic failure.The two mainstream systems developed for bioartificial liver support are extracorporeal whole liver perfusion(ECLP)and bioreactor systems.Comparing various types of bioartificial liver in view of function,safety,and operability,we concluded that the best efficacy can be provided by the ECLP system.Moreover,in our subsequent experiments comparing ECLP and apheresis therapy,ECLP offers more ammonia metabolism than HD and HF.In addition,ECLP can compensate amino acid imbalance and can secret bile.A controversial point with ECLP is the procedure is labor intensive,resulting in high costs.However,ECLP has the potential to reduce elevated serum ammonia levels of hepatic coma patients in a short duration.When these problems are solved,bioartificial liver support,especially ECLP,can be adopted as an option in ordinary clinical therapy to treat patients with hepatic failure.
基金National Natural Science Foundation of China(No.519705449)。
文摘To automatically detecting whether a person is wearing mask properly,we propose a face mask detection algorithm based on hue-saturation-value(HSV)+histogram of oriented gradient(HOG)features and support vector machines(SVM).Firstly,human face and five feature points are detected with RetinaFace face detection algorithm.The feature points are used to locate to mouth and nose region,and HSV+HOG features of this region are extracted and input to SVM for training to realize detection of wearing masks or not.Secondly,RetinaFace is used to locate to nasal tip area of face,and YCrCb elliptical skin tone model is used to detect the exposure of skin in the nasal tip area,and the optimal classification threshold can be found to determine whether the wear is properly according to experimental results.Experiments show that the accuracy of detecting whether mask is worn can reach 97.9%,and the accuracy of detecting whether mask is worn correctly can reach 87.55%,which verifies the feasibility of the algorithm.
基金National Science Foundation and Technology Innovation Fund of P.R.China(No.70371040and02LJ-14-05-01)
文摘Although many works have been done to construct prediction models on yarn processing quality,the relation between spinning variables and yarn properties has not been established conclusively so far.Support vector machines(SVMs),based on statistical learning theory,are gaining applications in the areas of machine learning and pattern recognition because of the high accuracy and good generalization capability.This study briefly introduces the SVM regression algorithms,and presents the SVM based system architecture for predicting yarn properties.Model selection which amounts to search in hyper-parameter space is performed for study of suitable parameters with grid-research method.Experimental results have been compared with those of artificial neural network(ANN)models.The investigation indicates that in the small data sets and real-life production,SVM models are capable of remaining the stability of predictive accuracy,and more suitable for noisy and dynamic spinning process.
