Macro and micromixing time represent two extreme mixing time scales,which governs the whole hydrodynamics characteristics of the surface aeration systems.With the help of experimental and numerical analysis,simulation...Macro and micromixing time represent two extreme mixing time scales,which governs the whole hydrodynamics characteristics of the surface aeration systems.With the help of experimental and numerical analysis,simulation equation governing those times scale has been presented in the present work.展开更多
Electromagnetic emission(EME) is a kind of physical phenomenon accompanying the process of deformation and fracture of loaded coal and rock and it is of importance in quantitatively analyzing its characteristics.This ...Electromagnetic emission(EME) is a kind of physical phenomenon accompanying the process of deformation and fracture of loaded coal and rock and it is of importance in quantitatively analyzing its characteristics.This will reveal the process of deformation and fracture of coal and predicting dynamic disasters in coal mines.In this study,the G-P(Grassberger and Procaccia) algorithm,calculation steps of the(if only 1 dimension) correlation dimension of time series and the identification standards of chaotic signals are introduced.Furthermore,the correlation dimensions of EME and the acoustic emission(AE) signals of time series during deformation and fracture of coal bodies are calculated and analyzed.The results show that the time series of pulses number of EME and the time series of AE count rate are chaotic and that the saturation embedding dimensions of a K3 coal sample are,respectively,5 and 6.The results can be used to provide basic parameters for predicting of EME and AE time series.展开更多
Linear Discriminant Analysis （LDA） is one of the principal techniques used in face recognition systems. LDA is well-known scheme for feature extraction and dimension reduction. It provides improved performance over ...Linear Discriminant Analysis （LDA） is one of the principal techniques used in face recognition systems. LDA is well-known scheme for feature extraction and dimension reduction. It provides improved performance over the standard Principal Component Analysis （PCA） method of face recognition by introducing the concept of classes and distance between classes. This paper provides an overview of PCA, the various variants of LDA and their basic drawbacks. The paper also has proposed a development over classical LDA, i.e., LDA using wavelets transform approach that enhances performance as regards accuracy and time complexity. Experiments on ORL face database clearly demonstrate this and the graphical comparison of the algorithms clearly showcases the improved recognition rate in case of the proposed algorithm.展开更多
基金Supported by the Department of Science and Technology,Government of India (DSTO717)
文摘Macro and micromixing time represent two extreme mixing time scales,which governs the whole hydrodynamics characteristics of the surface aeration systems.With the help of experimental and numerical analysis,simulation equation governing those times scale has been presented in the present work.
基金Projects 50427401 supported by the National Natural Science Foundation of China2006BAK03B06 by the National Eleventh Five-Year Key Science & Technology Project of China+2 种基金the New Century Excellent Talent Program from the Ministry of Education (No.NCET-07-0799)the Fok Ying-Tong Education Foundation for Young Teachers in Higher Education Institutions of China (No.111053)the Beijing Science and Technology New Star Plan (No.2006A081)
文摘Electromagnetic emission(EME) is a kind of physical phenomenon accompanying the process of deformation and fracture of loaded coal and rock and it is of importance in quantitatively analyzing its characteristics.This will reveal the process of deformation and fracture of coal and predicting dynamic disasters in coal mines.In this study,the G-P(Grassberger and Procaccia) algorithm,calculation steps of the(if only 1 dimension) correlation dimension of time series and the identification standards of chaotic signals are introduced.Furthermore,the correlation dimensions of EME and the acoustic emission(AE) signals of time series during deformation and fracture of coal bodies are calculated and analyzed.The results show that the time series of pulses number of EME and the time series of AE count rate are chaotic and that the saturation embedding dimensions of a K3 coal sample are,respectively,5 and 6.The results can be used to provide basic parameters for predicting of EME and AE time series.
文摘Linear Discriminant Analysis （LDA） is one of the principal techniques used in face recognition systems. LDA is well-known scheme for feature extraction and dimension reduction. It provides improved performance over the standard Principal Component Analysis （PCA） method of face recognition by introducing the concept of classes and distance between classes. This paper provides an overview of PCA, the various variants of LDA and their basic drawbacks. The paper also has proposed a development over classical LDA, i.e., LDA using wavelets transform approach that enhances performance as regards accuracy and time complexity. Experiments on ORL face database clearly demonstrate this and the graphical comparison of the algorithms clearly showcases the improved recognition rate in case of the proposed algorithm.
