A kernel-based discriminant analysis method called kernel direct discriminant analysis is employed, which combines the merit of direct linear discriminant analysis with that of kernel trick. In order to demonstrate it...A kernel-based discriminant analysis method called kernel direct discriminant analysis is employed, which combines the merit of direct linear discriminant analysis with that of kernel trick. In order to demonstrate its better robustness to the complex and nonlinear variations of real face images, such as illumination, facial expression, scale and pose variations, experiments are carried out on the Olivetti Research Laboratory, Yale and self-built face databases. The results indicate that in contrast to kernel principal component analysis and kernel linear discriminant analysis, the method can achieve lower （7%） error rate using only a very small set of features. Furthermore, a new corrected kernel model is proposed to improve the recognition performance. Experimental results confirm its superiority （1% in terms of recognition rate） to other polynomial kernel models.展开更多
It is important to emphasize the value of research in safe mining technology of high-risk water outburst coal seams. We describe briefly current conditions abroad and in China. Based on an Ordovician limestone aquifer...It is important to emphasize the value of research in safe mining technology of high-risk water outburst coal seams. We describe briefly current conditions abroad and in China. Based on an Ordovician limestone aquifer with high-risk water outburst seams in the Feicheng coal field, we analyzed the water-resistant characteristics of a coal floor aquifuge and the behavior of water head intrusion of a confined aquifer and propose a safe criterion model and relevant technology of mining above aquifers. This has brought satisfactory results in engineering practice.展开更多
In this paper, an attempt to analyse landslide hazard and vulnerability in the municipality of Pahuatlfin, Puebla, Mexico, is presented. In order to estimate landslide hazard, the susceptibility, magnitude （area-velo...In this paper, an attempt to analyse landslide hazard and vulnerability in the municipality of Pahuatlfin, Puebla, Mexico, is presented. In order to estimate landslide hazard, the susceptibility, magnitude （area-velocity ratio） and landslide frequency of the area of interest were produced based on information derived from a geomorphological landslide inventory; the latter was generated by using very high resolution satellite stereo pairs along with information derived from other sources （Google Earth, aerial photographs and historical information）. Estimations of landslide susceptibility were determined by combining four statistical techniques： （i） logistic regression, （ii） quadratic discriminant analysis, （iii） linear discriminant analysis, and （iv） neuronal networks. A Digital Elevation Model （DEM） of lo m spatial resolution was used to extract the slope angle, aspect, curvature, elevation and relief. These factors, in addition to land cover, lithology anddistance to faults, were used as explanatory variables for the susceptibility models. Additionally, a Poisson model was used to estimate landslide temporal frequency, at the same time as landslide magnitude was obtained by using the relationship between landslide area and the velocity of movements. Then, due to the complexity of evaluating it, vulnerability of population was analysed by applying the Spatial Approach to Vulnerability Assessment （SAVE） model which considered levels of exposure, sensitivity and lack of resilience. Results were expressed on maps on which different spatial patterns of levels of landslide hazard and vulnerability were found for the inhabited areas. It is noteworthy that the lack of optimal methodologies to estimate and quantify vulnerability is more notorious than that of hazard assessments. Consequently, levels of uncertainty linked to landslide risk assessment remain a challenge to be addressed.展开更多
The Gaussian mixture model (GMM), k-nearest neighbor (k-NN), quadratic discriminant analysis (QDA), and linear discriminant analysis (LDA) were compared to classify wrist motions using surface electromyogram (EMG). Ef...The Gaussian mixture model (GMM), k-nearest neighbor (k-NN), quadratic discriminant analysis (QDA), and linear discriminant analysis (LDA) were compared to classify wrist motions using surface electromyogram (EMG). Effect of feature selection in EMG signal processing was also verified by comparing classification accuracy of each feature, and the enhancement of classification accuracy by normalization was confirmed. EMG signals were acquired from two electrodes placed on the forearm of twenty eight healthy subjects and used for recognition of wrist motion. Features were extracted from the obtained EMG signals in the time domain and were applied to classification methods. The difference absolute mean value (DAMV), difference absolute standard deviation value (DASDV), mean absolute value (MAV), root mean square (RMS) were used for composing 16 double features which were combined of two channels. In the classification methods, the highest accuracy of classification showed in the GMM. The most effective combination of classification method and double feature was (MAV, DAMV) of GMM and its classification accuracy was 96.85%. The results of normalization were better than those of non-normalization in GMM, k-NN, and LDA.展开更多
This paper presents a new algorithm to predict locations and severities of damage in structures by changing modal parameters. An existing algorithm of damage detection is reviewed and the new algorithm is formulated t...This paper presents a new algorithm to predict locations and severities of damage in structures by changing modal parameters. An existing algorithm of damage detection is reviewed and the new algorithm is formulated to improve the accuracy of damage locating and severity estimation by eliminating the erratic assumptions and limits in the existing algorithm. The damage prediction accuracy is numerically assessed for each algorithm when applied to a two-dimensional frame structure for which pre-damage and post-damage modal parameters are available for only a few modes of vibration. The analysis results illustrate the improved accuracy of the new algorithm when compared to the existing algorithm.展开更多
The aim of this paper is to put forward the explanatory factors of the participation of women in the economic activity in the Cameroonian context characterized by an important and persistent gender gap in terms of par...The aim of this paper is to put forward the explanatory factors of the participation of women in the economic activity in the Cameroonian context characterized by an important and persistent gender gap in terms of participation in the economic activity （more men than women）. The authors carried out, on the basis of data resulting from the DHS-MICS 2011, an analysis using the binomial logistic model. It comes out from this analysis that the significant explanatory variables are the age （which plays at the same time the role of variable of control）, the religion, the ethnic group, the size of the household, the relationship with the head of household, the educational level （of the woman and the husband/partner）, the occupational status of the husband/partner, the household＇s standard of living, and the marital status. According to the results obtained, it would be important to set up policies intended to reinforce the professionalization of the young woman and to fight against the sexist sociocultural norms and practices advocating the ＂sexual division＂ of labor.展开更多
Existing seismic prediction methods struggle to effectively discriminate between fluids in tight gas reservoirs,such as those in the Sulige gas field in the Ordos Basin,where porosity and permeability are extremely lo...Existing seismic prediction methods struggle to effectively discriminate between fluids in tight gas reservoirs,such as those in the Sulige gas field in the Ordos Basin,where porosity and permeability are extremely low and the relationship between gas and water is complicated.In this paper,we have proposed a comprehensive seismic fluid identification method that combines ray-path elastic impedance(REI)inversion with fluid substitution for tight reservoirs.This approach is grounded in geophysical theory,forward modeling,and real data applications.We used geophysics experiments in tight gas reservoirs to determine that Brie's model is better suited to calculate the elastic parameters of mixed fluids than the conventional Wood’s model.This yielded a more reasonable and accurate fluid substitution model for tight gas reservoirs.We developed a forward model and carried out inversion of REI.which reduced the non-uniqueness problem that has plagued elastic impedance inversion in the angle domain.Our well logging forward model in the ray-path domain with different fluid saturations based on a fluid substitution model proved that REI identifies fluids more accurately when the ray parameters are large.The distribution of gas saturation can be distinguished from the crossplot of REI(p=0.10)and porosity.The inverted ray-path elastic impedance profile was further used to predict the porosity and gas saturation profile.Our new method achieved good results in the application of 2D seismic data in the western Sulige gas field.展开更多
This paper shows influence of gender equality on economy where it analyzed how gender equality in Europe has affected on the development of the frozen food industry and services related to childcare. The development o...This paper shows influence of gender equality on economy where it analyzed how gender equality in Europe has affected on the development of the frozen food industry and services related to childcare. The development of these industries has given a positive impulse to the development of the whole economy. In this analysis, it is used multiple regressions as one of the most important statistical methods. In the first part of this paper, it shows the connection among the growth of female employment, growth in frozen food expenditure and growth of GDP in United Kingdom. In the second part of paper, it shows the relationship among the growth of labor force participation of women, growth of number of kindergarten and growth of GDP in Hungary. To proof these relationships, it used a multiple regression model. This statistical model was tested by using the T schedule which showed that the model in both the analyses is correct. At the end of the paper, it presents that employment rate and GDP behaves in the same way in European Union. These analyses show that it is necessary to continue to strengthen gender equality if the policy makers want to achieve even greater economic growth. The issue of gender equality is a very important factor in creating employment policy, and statisticians should be more involved in process of employment policy and gender equality展开更多
Growing literature has demonstrated that exercise may be an effective prevention and treatment option for drug addiction. In the past few years, many studies have suggested that there were sex differences in all phase...Growing literature has demonstrated that exercise may be an effective prevention and treatment option for drug addiction. In the past few years, many studies have suggested that there were sex differences in all phases of drug addiction. However, very limited research has investigated sex differences in the effectiveness of exercise intervention in drug addiction and rehabilitation. In this mini review, we summarize the effect of sex on the results of using exercise to prevent and treat drug addiction. The studies we consider span various animal models and use multiple types of exercise to examine the effectiveness of exercise on the neurobiological mechanism of exercise rehabilitation. We believe that exercise as an adjuvant intervention strategy can be applied better in drug addiction prevention and recovery. Copyright 2014, Shanghai University of Sport. Production and hosting by Elsevier B.V. All rights reserved.展开更多
System identification is a method for using measured data to create or improve a mathematical model of the object being tested. From the measured data however, noise is noticed at the beginning of the response. One so...System identification is a method for using measured data to create or improve a mathematical model of the object being tested. From the measured data however, noise is noticed at the beginning of the response. One solution to avoid this noise problem is to skip the noisy data and then use the initial conditions as active parameters, to be found by using the system identification process. This paper describes the development of the equations for setting up the initial conditions as active parameters. The simulated data and response data from actual shear buildings were used to prove the accuracy of both the algorithm and the computer program, which include the initial conditions as active parameters. The numerical and experimental model analysis showed that the value of mass, stiffness and frequency were very reasonable and that the computed acceleration and measured acceleration matched very well.展开更多
To improve maneuverability and stability of articulated vehicles, we design an active steering controller, including tractor and trailer controllers, based on linear quadratic regulator(LQR) theory. First, a three-deg...To improve maneuverability and stability of articulated vehicles, we design an active steering controller, including tractor and trailer controllers, based on linear quadratic regulator(LQR) theory. First, a three-degree-of-freedom(3-DOF) model of the tractor-trailer with steered trailer axles is built. The simulated annealing particle swarm optimization(SAPSO) algorithm is applied to identify the key parameters of the model under specified vehicle speed and steering wheel angle. Thus, the key parameters of the simplified model can be obtained according to the vehicle conditions using an online look-up table and interpolation. Simulation results show that vehicle parameter outputs of the simplified model and Truck Sim agree well, thus providing the ideal reference yaw rate for the controller. Then the active steering controller of the tractor and trailer based on LQR is designed to follow the desired yaw rate and minimize their side-slip angle of the center of gravity(CG) at the same time. Finally, simulation tests at both low speed and high speed are conducted based on the Truck Sim-Simulink program. The results show significant effects on the active steering controller on improving maneuverability at low speed and lateral stability at high speed for the articulated vehicle. The control strategy is applicable for steering not only along gentle curves but also along sharp curves.展开更多
This work is concerned with identification of systems that are subject to not only measurement noises, but also structural uncertainties such as unmodeled dynamics, sensor nonlinear mismatch, and observation bins. Ide...This work is concerned with identification of systems that are subject to not only measurement noises, but also structural uncertainties such as unmodeled dynamics, sensor nonlinear mismatch, and observation bins. Identification errors are analyzed for their dependence on these structural uncertainties. Asymptotic distributions of scaled sequences of estimation errors are derived.展开更多
文摘A kernel-based discriminant analysis method called kernel direct discriminant analysis is employed, which combines the merit of direct linear discriminant analysis with that of kernel trick. In order to demonstrate its better robustness to the complex and nonlinear variations of real face images, such as illumination, facial expression, scale and pose variations, experiments are carried out on the Olivetti Research Laboratory, Yale and self-built face databases. The results indicate that in contrast to kernel principal component analysis and kernel linear discriminant analysis, the method can achieve lower （7%） error rate using only a very small set of features. Furthermore, a new corrected kernel model is proposed to improve the recognition performance. Experimental results confirm its superiority （1% in terms of recognition rate） to other polynomial kernel models.
基金support for this work, provided by the National Natural Science Foundation of China (No50834005)the National Basic Research Program of China (No2007CB209402)
文摘It is important to emphasize the value of research in safe mining technology of high-risk water outburst coal seams. We describe briefly current conditions abroad and in China. Based on an Ordovician limestone aquifer with high-risk water outburst seams in the Feicheng coal field, we analyzed the water-resistant characteristics of a coal floor aquifuge and the behavior of water head intrusion of a confined aquifer and propose a safe criterion model and relevant technology of mining above aquifers. This has brought satisfactory results in engineering practice.
基金CONACyT for financial support for the research project 156242for providing a post-graduate scholarship
文摘In this paper, an attempt to analyse landslide hazard and vulnerability in the municipality of Pahuatlfin, Puebla, Mexico, is presented. In order to estimate landslide hazard, the susceptibility, magnitude （area-velocity ratio） and landslide frequency of the area of interest were produced based on information derived from a geomorphological landslide inventory; the latter was generated by using very high resolution satellite stereo pairs along with information derived from other sources （Google Earth, aerial photographs and historical information）. Estimations of landslide susceptibility were determined by combining four statistical techniques： （i） logistic regression, （ii） quadratic discriminant analysis, （iii） linear discriminant analysis, and （iv） neuronal networks. A Digital Elevation Model （DEM） of lo m spatial resolution was used to extract the slope angle, aspect, curvature, elevation and relief. These factors, in addition to land cover, lithology anddistance to faults, were used as explanatory variables for the susceptibility models. Additionally, a Poisson model was used to estimate landslide temporal frequency, at the same time as landslide magnitude was obtained by using the relationship between landslide area and the velocity of movements. Then, due to the complexity of evaluating it, vulnerability of population was analysed by applying the Spatial Approach to Vulnerability Assessment （SAVE） model which considered levels of exposure, sensitivity and lack of resilience. Results were expressed on maps on which different spatial patterns of levels of landslide hazard and vulnerability were found for the inhabited areas. It is noteworthy that the lack of optimal methodologies to estimate and quantify vulnerability is more notorious than that of hazard assessments. Consequently, levels of uncertainty linked to landslide risk assessment remain a challenge to be addressed.
基金Project(NIPA-2012-H0401-12-1007) supported by the MKE(The Ministry of Knowledge Economy), Korea, supervised by the NIPAProject(2010-0020163) supported by Key Research Institute Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology, Korea
文摘The Gaussian mixture model (GMM), k-nearest neighbor (k-NN), quadratic discriminant analysis (QDA), and linear discriminant analysis (LDA) were compared to classify wrist motions using surface electromyogram (EMG). Effect of feature selection in EMG signal processing was also verified by comparing classification accuracy of each feature, and the enhancement of classification accuracy by normalization was confirmed. EMG signals were acquired from two electrodes placed on the forearm of twenty eight healthy subjects and used for recognition of wrist motion. Features were extracted from the obtained EMG signals in the time domain and were applied to classification methods. The difference absolute mean value (DAMV), difference absolute standard deviation value (DASDV), mean absolute value (MAV), root mean square (RMS) were used for composing 16 double features which were combined of two channels. In the classification methods, the highest accuracy of classification showed in the GMM. The most effective combination of classification method and double feature was (MAV, DAMV) of GMM and its classification accuracy was 96.85%. The results of normalization were better than those of non-normalization in GMM, k-NN, and LDA.
基金The project was financially supported by the National Natural Science Foundation of China （No. 50479027）.
文摘This paper presents a new algorithm to predict locations and severities of damage in structures by changing modal parameters. An existing algorithm of damage detection is reviewed and the new algorithm is formulated to improve the accuracy of damage locating and severity estimation by eliminating the erratic assumptions and limits in the existing algorithm. The damage prediction accuracy is numerically assessed for each algorithm when applied to a two-dimensional frame structure for which pre-damage and post-damage modal parameters are available for only a few modes of vibration. The analysis results illustrate the improved accuracy of the new algorithm when compared to the existing algorithm.
文摘The aim of this paper is to put forward the explanatory factors of the participation of women in the economic activity in the Cameroonian context characterized by an important and persistent gender gap in terms of participation in the economic activity （more men than women）. The authors carried out, on the basis of data resulting from the DHS-MICS 2011, an analysis using the binomial logistic model. It comes out from this analysis that the significant explanatory variables are the age （which plays at the same time the role of variable of control）, the religion, the ethnic group, the size of the household, the relationship with the head of household, the educational level （of the woman and the husband/partner）, the occupational status of the husband/partner, the household＇s standard of living, and the marital status. According to the results obtained, it would be important to set up policies intended to reinforce the professionalization of the young woman and to fight against the sexist sociocultural norms and practices advocating the ＂sexual division＂ of labor.
基金supported by the National Science and Technology Major Project(No.2016ZX05050 and 2017ZX05069)CNPC Major Technology Special Project(No.2016E-0503)
文摘Existing seismic prediction methods struggle to effectively discriminate between fluids in tight gas reservoirs,such as those in the Sulige gas field in the Ordos Basin,where porosity and permeability are extremely low and the relationship between gas and water is complicated.In this paper,we have proposed a comprehensive seismic fluid identification method that combines ray-path elastic impedance(REI)inversion with fluid substitution for tight reservoirs.This approach is grounded in geophysical theory,forward modeling,and real data applications.We used geophysics experiments in tight gas reservoirs to determine that Brie's model is better suited to calculate the elastic parameters of mixed fluids than the conventional Wood’s model.This yielded a more reasonable and accurate fluid substitution model for tight gas reservoirs.We developed a forward model and carried out inversion of REI.which reduced the non-uniqueness problem that has plagued elastic impedance inversion in the angle domain.Our well logging forward model in the ray-path domain with different fluid saturations based on a fluid substitution model proved that REI identifies fluids more accurately when the ray parameters are large.The distribution of gas saturation can be distinguished from the crossplot of REI(p=0.10)and porosity.The inverted ray-path elastic impedance profile was further used to predict the porosity and gas saturation profile.Our new method achieved good results in the application of 2D seismic data in the western Sulige gas field.
文摘This paper shows influence of gender equality on economy where it analyzed how gender equality in Europe has affected on the development of the frozen food industry and services related to childcare. The development of these industries has given a positive impulse to the development of the whole economy. In this analysis, it is used multiple regressions as one of the most important statistical methods. In the first part of this paper, it shows the connection among the growth of female employment, growth in frozen food expenditure and growth of GDP in United Kingdom. In the second part of paper, it shows the relationship among the growth of labor force participation of women, growth of number of kindergarten and growth of GDP in Hungary. To proof these relationships, it used a multiple regression model. This statistical model was tested by using the T schedule which showed that the model in both the analyses is correct. At the end of the paper, it presents that employment rate and GDP behaves in the same way in European Union. These analyses show that it is necessary to continue to strengthen gender equality if the policy makers want to achieve even greater economic growth. The issue of gender equality is a very important factor in creating employment policy, and statisticians should be more involved in process of employment policy and gender equality
基金supported by grants from the Shanghai Science and Technology Commission(NO.13490503600)National Natural Science Foundation of China (NO.31171004)
文摘Growing literature has demonstrated that exercise may be an effective prevention and treatment option for drug addiction. In the past few years, many studies have suggested that there were sex differences in all phases of drug addiction. However, very limited research has investigated sex differences in the effectiveness of exercise intervention in drug addiction and rehabilitation. In this mini review, we summarize the effect of sex on the results of using exercise to prevent and treat drug addiction. The studies we consider span various animal models and use multiple types of exercise to examine the effectiveness of exercise on the neurobiological mechanism of exercise rehabilitation. We believe that exercise as an adjuvant intervention strategy can be applied better in drug addiction prevention and recovery. Copyright 2014, Shanghai University of Sport. Production and hosting by Elsevier B.V. All rights reserved.
文摘System identification is a method for using measured data to create or improve a mathematical model of the object being tested. From the measured data however, noise is noticed at the beginning of the response. One solution to avoid this noise problem is to skip the noisy data and then use the initial conditions as active parameters, to be found by using the system identification process. This paper describes the development of the equations for setting up the initial conditions as active parameters. The simulated data and response data from actual shear buildings were used to prove the accuracy of both the algorithm and the computer program, which include the initial conditions as active parameters. The numerical and experimental model analysis showed that the value of mass, stiffness and frequency were very reasonable and that the computed acceleration and measured acceleration matched very well.
基金supported by the Program for Changjiang ScholarsInnovative Research Team in University,China(No.IRT0626)
文摘To improve maneuverability and stability of articulated vehicles, we design an active steering controller, including tractor and trailer controllers, based on linear quadratic regulator(LQR) theory. First, a three-degree-of-freedom(3-DOF) model of the tractor-trailer with steered trailer axles is built. The simulated annealing particle swarm optimization(SAPSO) algorithm is applied to identify the key parameters of the model under specified vehicle speed and steering wheel angle. Thus, the key parameters of the simplified model can be obtained according to the vehicle conditions using an online look-up table and interpolation. Simulation results show that vehicle parameter outputs of the simplified model and Truck Sim agree well, thus providing the ideal reference yaw rate for the controller. Then the active steering controller of the tractor and trailer based on LQR is designed to follow the desired yaw rate and minimize their side-slip angle of the center of gravity(CG) at the same time. Finally, simulation tests at both low speed and high speed are conducted based on the Truck Sim-Simulink program. The results show significant effects on the active steering controller on improving maneuverability at low speed and lateral stability at high speed for the articulated vehicle. The control strategy is applicable for steering not only along gentle curves but also along sharp curves.
文摘This work is concerned with identification of systems that are subject to not only measurement noises, but also structural uncertainties such as unmodeled dynamics, sensor nonlinear mismatch, and observation bins. Identification errors are analyzed for their dependence on these structural uncertainties. Asymptotic distributions of scaled sequences of estimation errors are derived.
