The characteristics of coal seam development,and the prospects of a favorable coal-forming area,were evaluated for the Liaohe Basin located in China.The Number 3 and Number 9 coal seam thickness series from 60 nearly ...The characteristics of coal seam development,and the prospects of a favorable coal-forming area,were evaluated for the Liaohe Basin located in China.The Number 3 and Number 9 coal seam thickness series from 60 nearly equally spaced bores in the Eastern depression of the Liaohe Basin were examined by a rescaled range analysis.The results indicate that the Hurst exponents of the Number 3 and Number 9 coal seam thickness series are 0.69 and 0.68,respectively.This suggests the presence of persistence.As the bore spacing increases the Hurst exponent of the Number 3 series gradually decreases（H changes from 0.69 to 0.52） and shifts from persistence to randomness.The Hurst exponent of the Number 9 thickness data gradually increases（H changes from 0.68 to 0.91） and always shows the characteristic of persistence.A combination of geological characteristics and the series data allow the conclusion that it is more suitable for the Number 9 coal seam to form in the Northeastern part of the Eastern depression than the Number 3 coal seam.展开更多
Fingerprint authentication system is used to verify users' identification according to the characteristics of their fingerprints.However,this system has some security and privacy problems.For example,some artifici...Fingerprint authentication system is used to verify users' identification according to the characteristics of their fingerprints.However,this system has some security and privacy problems.For example,some artificial fingerprints can trick the fingerprint authentication system and access information using real users' identification.Therefore,a fingerprint liveness detection algorithm needs to be designed to prevent illegal users from accessing privacy information.In this paper,a new software-based liveness detection approach using multi-scale local phase quantity(LPQ) and principal component analysis(PCA) is proposed.The feature vectors of a fingerprint are constructed through multi-scale LPQ.PCA technology is also introduced to reduce the dimensionality of the feature vectors and gain more effective features.Finally,a training model is gained using support vector machine classifier,and the liveness of a fingerprint is detected on the basis of the training model.Experimental results demonstrate that our proposed method can detect the liveness of users' fingerprints and achieve high recognition accuracy.This study also confirms that multi-resolution analysis is a useful method for texture feature extraction during fingerprint liveness detection.展开更多
Coal occupies a dominant position in China＇s national economy and is an essential energy source for future industrial development. To inform the efficient and sustainable development of the coal industry, this paper ...Coal occupies a dominant position in China＇s national economy and is an essential energy source for future industrial development. To inform the efficient and sustainable development of the coal industry, this paper analyzes the sources of strategic risk for coal science and technology enterprises using 3 first-class indicators, 10 second-level indicators, and 37 observation points established through the existing research literature and experience. Moreover, in accordance to the obtained initial index data, the selected indicators have been tested and screened using reliability and membership degree analyses to remove redundant variables, avoid juxtaposition of risk factors at different levels, and reduce the influ- ence of some tiny risk factors for enterprise strategic risk. Then, factor analysis of external environment factor sub-scale was carried out. Factors are extracted according to a standard characteristic value greater than 1. Variables with high coefficients are classified into one factor category; and finally, 3 first-class indicators. 8 second-level indicators, and 37 observation noints are reconstructed.展开更多
基金supported by National Basic Research Program of China(No.2007CB209503)
文摘The characteristics of coal seam development,and the prospects of a favorable coal-forming area,were evaluated for the Liaohe Basin located in China.The Number 3 and Number 9 coal seam thickness series from 60 nearly equally spaced bores in the Eastern depression of the Liaohe Basin were examined by a rescaled range analysis.The results indicate that the Hurst exponents of the Number 3 and Number 9 coal seam thickness series are 0.69 and 0.68,respectively.This suggests the presence of persistence.As the bore spacing increases the Hurst exponent of the Number 3 series gradually decreases（H changes from 0.69 to 0.52） and shifts from persistence to randomness.The Hurst exponent of the Number 9 thickness data gradually increases（H changes from 0.68 to 0.91） and always shows the characteristic of persistence.A combination of geological characteristics and the series data allow the conclusion that it is more suitable for the Number 9 coal seam to form in the Northeastern part of the Eastern depression than the Number 3 coal seam.
基金supported by the NSFC (U1536206,61232016,U1405254,61373133, 61502242)BK20150925the PAPD fund
文摘Fingerprint authentication system is used to verify users' identification according to the characteristics of their fingerprints.However,this system has some security and privacy problems.For example,some artificial fingerprints can trick the fingerprint authentication system and access information using real users' identification.Therefore,a fingerprint liveness detection algorithm needs to be designed to prevent illegal users from accessing privacy information.In this paper,a new software-based liveness detection approach using multi-scale local phase quantity(LPQ) and principal component analysis(PCA) is proposed.The feature vectors of a fingerprint are constructed through multi-scale LPQ.PCA technology is also introduced to reduce the dimensionality of the feature vectors and gain more effective features.Finally,a training model is gained using support vector machine classifier,and the liveness of a fingerprint is detected on the basis of the training model.Experimental results demonstrate that our proposed method can detect the liveness of users' fingerprints and achieve high recognition accuracy.This study also confirms that multi-resolution analysis is a useful method for texture feature extraction during fingerprint liveness detection.
文摘Coal occupies a dominant position in China＇s national economy and is an essential energy source for future industrial development. To inform the efficient and sustainable development of the coal industry, this paper analyzes the sources of strategic risk for coal science and technology enterprises using 3 first-class indicators, 10 second-level indicators, and 37 observation points established through the existing research literature and experience. Moreover, in accordance to the obtained initial index data, the selected indicators have been tested and screened using reliability and membership degree analyses to remove redundant variables, avoid juxtaposition of risk factors at different levels, and reduce the influ- ence of some tiny risk factors for enterprise strategic risk. Then, factor analysis of external environment factor sub-scale was carried out. Factors are extracted according to a standard characteristic value greater than 1. Variables with high coefficients are classified into one factor category; and finally, 3 first-class indicators. 8 second-level indicators, and 37 observation noints are reconstructed.
