Both functional magnetic resonance imaging （fMRI） and diffusion tensor imaging （DTI） can provide different information of the human brain, so using the wavelet transform method can achieve a fusion of these two ty...Both functional magnetic resonance imaging （fMRI） and diffusion tensor imaging （DTI） can provide different information of the human brain, so using the wavelet transform method can achieve a fusion of these two types of image data and can effectively improve the depression recognition accuracy. Multi-resolution wavelet decomposition is used to transform each type of images to the frequency domain in order to obtain the frequency components of the images. To each subject, decomposition components of two images are then added up separately according to their frequencies. The inverse discrete wavelet transform is used to reconstruct the fused images. After that, principal component analysis （PCA） is applied to reduce the dimension and obtain the features of the fusion data before classification. Based on the features of the fused images, an accuracy rate of 80. 95 % for depression recognition is achieved using a leave-one-out cross-validation test. It can be concluded that this wavelet fusion scheme has the ability to improve the current diagnosis of depression.展开更多
For understanding acoustic emission （AE） activity and accumulation of micro-damage inside rock under pure tensile state, the AE signals has been monitored on the test of directly tension on two kinds of marble speci...For understanding acoustic emission （AE） activity and accumulation of micro-damage inside rock under pure tensile state, the AE signals has been monitored on the test of directly tension on two kinds of marble specimens. A tensile constitutive model was proposed with the damage factor calculated by AE energy rate. The tensile strength of marble was discrete obviously and was sensitive to the inside microdefects and grain composition. With increasing of loading, the tensile stress-strain curve obviously showed nonlinear with the tensile tangent modulus decreasing. In repeated loading cycle, the tensile elastic modulus was less than that in the previous loading cycle because of the generation of micro damage during the prior loading. It means the linear weakening occurring in the specimens. The AE activity was corresponding with occurrence of nonlinear deformation. In the initial loading stage which only elastic deformation happened on the specimens, there were few AE events occurred; while when the nonlinear deformation happened with increasing of loading, lots of AE events were generated. The quantity and energy of AE events were proportionally related to the variation of tensile tangent modulus. The Kaiser effect of AE activity could be clearly observed in tensile cycle loading. Based on the theory of damage mechanics, the damage factor was defined by AE energy rate and the tensile damage constitutive model was proposed which only needed two property constants. The theoretical stress-strain curve was well fitted with the curve plotted with tested datum and the two property constants were easily gotten by the laboratory testing.展开更多
基金The National Natural Science Foundation of China(No.30900356,81071135)
文摘Both functional magnetic resonance imaging （fMRI） and diffusion tensor imaging （DTI） can provide different information of the human brain, so using the wavelet transform method can achieve a fusion of these two types of image data and can effectively improve the depression recognition accuracy. Multi-resolution wavelet decomposition is used to transform each type of images to the frequency domain in order to obtain the frequency components of the images. To each subject, decomposition components of two images are then added up separately according to their frequencies. The inverse discrete wavelet transform is used to reconstruct the fused images. After that, principal component analysis （PCA） is applied to reduce the dimension and obtain the features of the fusion data before classification. Based on the features of the fused images, an accuracy rate of 80. 95 % for depression recognition is achieved using a leave-one-out cross-validation test. It can be concluded that this wavelet fusion scheme has the ability to improve the current diagnosis of depression.
文摘For understanding acoustic emission （AE） activity and accumulation of micro-damage inside rock under pure tensile state, the AE signals has been monitored on the test of directly tension on two kinds of marble specimens. A tensile constitutive model was proposed with the damage factor calculated by AE energy rate. The tensile strength of marble was discrete obviously and was sensitive to the inside microdefects and grain composition. With increasing of loading, the tensile stress-strain curve obviously showed nonlinear with the tensile tangent modulus decreasing. In repeated loading cycle, the tensile elastic modulus was less than that in the previous loading cycle because of the generation of micro damage during the prior loading. It means the linear weakening occurring in the specimens. The AE activity was corresponding with occurrence of nonlinear deformation. In the initial loading stage which only elastic deformation happened on the specimens, there were few AE events occurred; while when the nonlinear deformation happened with increasing of loading, lots of AE events were generated. The quantity and energy of AE events were proportionally related to the variation of tensile tangent modulus. The Kaiser effect of AE activity could be clearly observed in tensile cycle loading. Based on the theory of damage mechanics, the damage factor was defined by AE energy rate and the tensile damage constitutive model was proposed which only needed two property constants. The theoretical stress-strain curve was well fitted with the curve plotted with tested datum and the two property constants were easily gotten by the laboratory testing.
