Human Action Recognition(HAR)in uncontrolled environments targets to recognition of different actions froma video.An effective HAR model can be employed for an application like human-computer interaction,health care,p...Human Action Recognition(HAR)in uncontrolled environments targets to recognition of different actions froma video.An effective HAR model can be employed for an application like human-computer interaction,health care,person tracking,and video surveillance.Machine Learning(ML)approaches,specifically,Convolutional Neural Network(CNN)models had beenwidely used and achieved impressive results through feature fusion.The accuracy and effectiveness of these models continue to be the biggest challenge in this field.In this article,a novel feature optimization algorithm,called improved Shark Smell Optimization(iSSO)is proposed to reduce the redundancy of extracted features.This proposed technique is inspired by the behavior ofwhite sharks,and howthey find the best prey in thewhole search space.The proposed iSSOalgorithmdivides the FeatureVector(FV)into subparts,where a search is conducted to find optimal local features fromeach subpart of FV.Once local optimal features are selected,a global search is conducted to further optimize these features.The proposed iSSO algorithm is employed on nine(9)selected CNN models.These CNN models are selected based on their top-1 and top-5 accuracy in ImageNet competition.To evaluate the model,two publicly available datasets UCF-Sports and Hollywood2 are selected.展开更多
[Objectives]This study was conducted to investigate the application of Sargassum fusiforme(Harv.)Setch.in cigarettes.[Methods]Tobacco-specific nitrosamines in the smoke of cigarettes added with ethanol extract of S.fu...[Objectives]This study was conducted to investigate the application of Sargassum fusiforme(Harv.)Setch.in cigarettes.[Methods]Tobacco-specific nitrosamines in the smoke of cigarettes added with ethanol extract of S.fusiforme were determined,and the compounds related to the aroma of S.fusiforme were identified by flavor-smelling experiment.[Results]With the addition of the ethanol extract of S.fusiforme,the decrease in the total amount of four tobacco-specific nitrosamines in mainstream cigarette smoke reached 16.42%.The results of the flavor-smelling experiment showed that the aroma of S.fusiforme might be related to(R)-5,6,7,7A-tetrahydro-4,4,7A-trimethyl-2(4H)-benzofuranone,glycerol,ethyl palmitate,methyl palmitate,ethyl linoleate,methyl(Z,Z,Z)-9,12,15-octadecatrienoate,ethyl(Z,Z,Z)-9,12,15-octadecatrienoate,phytol,and tetradecanoic acid.[Conclusions]The ethanol extract of S.fusiforme has the potential function of reducing the content of tobacco-specific nitrosamines in smoke and improving the taste of cigarettes.展开更多
基金supported by the Collabo R&D between Industry,Academy,and Research Institute(S3250534)funded by the Ministry of SMEs and Startups(MSS,Korea)the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(No.RS-2023-00218176)the Soonchunhyang University Research Fund.
文摘Human Action Recognition(HAR)in uncontrolled environments targets to recognition of different actions froma video.An effective HAR model can be employed for an application like human-computer interaction,health care,person tracking,and video surveillance.Machine Learning(ML)approaches,specifically,Convolutional Neural Network(CNN)models had beenwidely used and achieved impressive results through feature fusion.The accuracy and effectiveness of these models continue to be the biggest challenge in this field.In this article,a novel feature optimization algorithm,called improved Shark Smell Optimization(iSSO)is proposed to reduce the redundancy of extracted features.This proposed technique is inspired by the behavior ofwhite sharks,and howthey find the best prey in thewhole search space.The proposed iSSOalgorithmdivides the FeatureVector(FV)into subparts,where a search is conducted to find optimal local features fromeach subpart of FV.Once local optimal features are selected,a global search is conducted to further optimize these features.The proposed iSSO algorithm is employed on nine(9)selected CNN models.These CNN models are selected based on their top-1 and top-5 accuracy in ImageNet competition.To evaluate the model,two publicly available datasets UCF-Sports and Hollywood2 are selected.
文摘[Objectives]This study was conducted to investigate the application of Sargassum fusiforme(Harv.)Setch.in cigarettes.[Methods]Tobacco-specific nitrosamines in the smoke of cigarettes added with ethanol extract of S.fusiforme were determined,and the compounds related to the aroma of S.fusiforme were identified by flavor-smelling experiment.[Results]With the addition of the ethanol extract of S.fusiforme,the decrease in the total amount of four tobacco-specific nitrosamines in mainstream cigarette smoke reached 16.42%.The results of the flavor-smelling experiment showed that the aroma of S.fusiforme might be related to(R)-5,6,7,7A-tetrahydro-4,4,7A-trimethyl-2(4H)-benzofuranone,glycerol,ethyl palmitate,methyl palmitate,ethyl linoleate,methyl(Z,Z,Z)-9,12,15-octadecatrienoate,ethyl(Z,Z,Z)-9,12,15-octadecatrienoate,phytol,and tetradecanoic acid.[Conclusions]The ethanol extract of S.fusiforme has the potential function of reducing the content of tobacco-specific nitrosamines in smoke and improving the taste of cigarettes.
