Biometric recognition is a widely used technology for user authentication.In the application of this technology,biometric security and recognition accuracy are two important issues that should be considered.In terms o...Biometric recognition is a widely used technology for user authentication.In the application of this technology,biometric security and recognition accuracy are two important issues that should be considered.In terms of biometric security,cancellable biometrics is an effective technique for protecting biometric data.Regarding recognition accuracy,feature representation plays a significant role in the performance and reliability of cancellable biometric systems.How to design good feature representations for cancellable biometrics is a challenging topic that has attracted a great deal of attention from the computer vision community,especially from researchers of cancellable biometrics.Feature extraction and learning in cancellable biometrics is to find suitable feature representations with a view to achieving satisfactory recognition performance,while the privacy of biometric data is protected.This survey informs the progress,trend and challenges of feature extraction and learning for cancellable biometrics,thus shedding light on the latest developments and future research of this area.展开更多
Regulable loading of Ni(OH)_(2) crystals by using three dimensionally ordered mesoporous carbon(3DOMC)as a support is achieved through a confined growth strategy accompanied by steam-assisted crystallization.Dual form...Regulable loading of Ni(OH)_(2) crystals by using three dimensionally ordered mesoporous carbon(3DOMC)as a support is achieved through a confined growth strategy accompanied by steam-assisted crystallization.Dual forms of high-crystalline nanosheet-like Ni(OH)_(2) severally distribute within mesopores or over the outer surface of 3DOMC particles depending on the loading amount(3%^(−1)5%)of Ni(OH)_(2).Benefitted from the highly hybrid combination and efficient electrolyte diffusion,the obtained Ni(OH)_(2)/carbon nanocomposites exhibit an excellent electrochemical performance,and the optimal sample of 6%_Ni(OH)_(2)/3DOMC with confined extrasmall Ni(OH)_(2) nanosheets as dominant shows the highest specific capacitance of 552.5F.g^(−1) at 1.0A⋅g^(−1),which is 330%higher than the contrast sample by using actived carbon as the support.Furthermore,the assembled hybrid supercapacitor by using 6%_Ni(OH)_(2)/3DOMC and 3DOMC as positive and negative electrodes displays an energy density of 11.7 Wh.kg^(−1) at 288.1 W.kg^(−1) and a superior charge/discharge stability.It is expected that the flexible component,well-defined structure,and superior electrochemical performance could promote a great application potential of Ni(OH)_(2)/3DOMC nanocomposites as supercapacitor electrodes and in other energy storage devices.展开更多
基金Australian Research Council,Grant/Award Numbers:DP190103660,DP200103207,LP180100663UniSQ Capacity Building Grants,Grant/Award Number:1008313。
文摘Biometric recognition is a widely used technology for user authentication.In the application of this technology,biometric security and recognition accuracy are two important issues that should be considered.In terms of biometric security,cancellable biometrics is an effective technique for protecting biometric data.Regarding recognition accuracy,feature representation plays a significant role in the performance and reliability of cancellable biometric systems.How to design good feature representations for cancellable biometrics is a challenging topic that has attracted a great deal of attention from the computer vision community,especially from researchers of cancellable biometrics.Feature extraction and learning in cancellable biometrics is to find suitable feature representations with a view to achieving satisfactory recognition performance,while the privacy of biometric data is protected.This survey informs the progress,trend and challenges of feature extraction and learning for cancellable biometrics,thus shedding light on the latest developments and future research of this area.
基金the National Natural Science Foundation of China(Nos.21978238,21878248,and 21978055)Natural Science Foundation of Shaanxi Provincial Department of Education(No.21JY041).
文摘Regulable loading of Ni(OH)_(2) crystals by using three dimensionally ordered mesoporous carbon(3DOMC)as a support is achieved through a confined growth strategy accompanied by steam-assisted crystallization.Dual forms of high-crystalline nanosheet-like Ni(OH)_(2) severally distribute within mesopores or over the outer surface of 3DOMC particles depending on the loading amount(3%^(−1)5%)of Ni(OH)_(2).Benefitted from the highly hybrid combination and efficient electrolyte diffusion,the obtained Ni(OH)_(2)/carbon nanocomposites exhibit an excellent electrochemical performance,and the optimal sample of 6%_Ni(OH)_(2)/3DOMC with confined extrasmall Ni(OH)_(2) nanosheets as dominant shows the highest specific capacitance of 552.5F.g^(−1) at 1.0A⋅g^(−1),which is 330%higher than the contrast sample by using actived carbon as the support.Furthermore,the assembled hybrid supercapacitor by using 6%_Ni(OH)_(2)/3DOMC and 3DOMC as positive and negative electrodes displays an energy density of 11.7 Wh.kg^(−1) at 288.1 W.kg^(−1) and a superior charge/discharge stability.It is expected that the flexible component,well-defined structure,and superior electrochemical performance could promote a great application potential of Ni(OH)_(2)/3DOMC nanocomposites as supercapacitor electrodes and in other energy storage devices.
