Monitoring and evaluating the nutritional status of vegetation under stress from exhausted coal mining sites by hyper-spectral remote sensing is important in future ecological restoration engineering. The Wangpingcun ...Monitoring and evaluating the nutritional status of vegetation under stress from exhausted coal mining sites by hyper-spectral remote sensing is important in future ecological restoration engineering. The Wangpingcun coal mine, located in the Mentougou district of Beijing, was chosen as a case study. The ecological damage was analyzed by 3S technology, field investigation and from chemical data. The derivative spectra of the diagnostic absorption bands are derived from the spectra measured in the field and used as characteristic spectral variables. A correlation analysis was conducted for the nitrogen content of the vegetation samples and the fast derivative spectrum and the estimation model of nitrogen content established by a multiple stepwise linear regression method. The spatial distribution of nitrogen content was extracted by a parameter mapping method from the Hyperion data which revealed the distribution of the nitrogen content. In addition, the estimation model was evaluated for two evaluation indicators which are important for the precision of the model. Experimental results indicate that by linear regression and parameter mapping, the estimation model precision was Very high. The coefficient of determination, R2, was 0.795 and the standard deviation of residual （SDR） 0.19. The nitrogen content of most samples was about 1.03% and the nitrogen content in the study site seems inversely proportional to the distance from the piles of coal waste. Therefore, we can conclude that inversely modeling nitrogen content by hyper-spectral remote sensing in exhausted coal mining sites is feasible and our study can be taken as reference in species selection and in subseauent management and maintenance in ecological restoration.展开更多
Particle size distribution of coarse aggregates through mechanical sieving gives results in terms of cumu- lative mass percent. But digital image processing generated size distribution of particles, while being fast a...Particle size distribution of coarse aggregates through mechanical sieving gives results in terms of cumu- lative mass percent. But digital image processing generated size distribution of particles, while being fast and accurate, is often expressed in terms of area function or number of particles. In this paper, a mass model is developed which converts the image obtained size distribution to mass-wise distribution, mak- ing it readily comparable to mechanical sieving data. The concept of weight/particle ratio is introduced for mass reconstruction from 2D images of particle aggregates. Using this mass model, the effects of several particle shape parameters （such as major axis, minor axis, and equivalent diameter） on sieve-size of the particles is studied. It is shown that the sieve-size of a particle strongly depend upon the shape param- eters, 91% of its variation being explained by major axis, minor axis, bounding box length and equivalent diameter. Furthermore, minor axis gives an overall accurate estimate of particle sieve-size, error in mean size （D-50） being just 0.4%. However, sieve-size of smaller particles （〈20 ram） strongly depends upon the length of the smaller arm of the bounding box enclosing them and sieve-sizes of larger particles （〉20 mm） are highly correlated to their equivalent diameters. Multiple linear regression analysis has been used to generate overall mass-wise particle size distribution, considering the influences of all these shape parameters on particle sieve-size. Multiple linear regression generated overall mass-wise particle size distribution shows a strong correlation with sieve generated data. The adjusted R-square value of the regression analysis is found to be 99 percent （w.r,t cumulative frequency）. The method proposed in this paper provides a time-efficient way of producing accurate （up to 99%） mass-wise PSD using digital image processing and it can be used effectively to renlace the mechanical sieving.展开更多
This paper uses regression analysis and econometric modeling foundations to track public expenditures in the Slovak Republic and the Czech Republic （Fejesova, 2011） and their influences on the development of the fol...This paper uses regression analysis and econometric modeling foundations to track public expenditures in the Slovak Republic and the Czech Republic （Fejesova, 2011） and their influences on the development of the following two targets of the Europe 2020 Strategy： to increase the employment of the selected population groups to a predetermined percentage level and to reduce the number of people at risk of poverty. In addition to the selection of monitored indicators, we included other indicators from the social sphere, which are funded by mandatory national public expenditure budgets and which are expected to have a positive development in terms of improving the demographic structure of the country--the unemployment rate and the number of live births.展开更多
Fluctuations of the world oil prices affect economic performance. Outside the impact on the sector of energy production, the rising oil price has consequences on inflationary pressures and a deteriorating fiscal posit...Fluctuations of the world oil prices affect economic performance. Outside the impact on the sector of energy production, the rising oil price has consequences on inflationary pressures and a deteriorating fiscal position of Burkina Faso. In this context, studying the impact of rising oil prices on the economy, especially the cost of living of its population has a great interest because although many studies have attempted to link 〈〈oil prices〉~ and 〈〈cost of living~, very few have focused on the specific case of Burkina Faso. This allows us to make our contribution to this construction literature. This contribution will consist to highlight the relation between changes in oil prices and the cost of living in Burkina Faso. Also to be reached, we will find the best indicator to reflect the cost of living in Burkina Faso, identify the suitable econometric model for estimating the correlation and verify the existence of the relation between oil prices and the cost of living. For a better approach to this study, we used a VAR （Vector Auto-Regressive） model. Also, we will use documentary research that will make an assessment on the existing in terms of theoretical debates around the theme descriptive statistics that will help to introduce and describe the variables used in the study, and econometric analysis will analyze and estimate the parameters of our objective function using Eviews.展开更多
This paper studies the parameter estimation of one dimensional linear errors-in-variables(EV) models in the case that replicated observations are available in some experimental points.Asymptotic normality is establis...This paper studies the parameter estimation of one dimensional linear errors-in-variables(EV) models in the case that replicated observations are available in some experimental points.Asymptotic normality is established under mild conditions, and the parameters entering the asymptotic variance are consistently estimated to render the result useable in construction of large-sample confidence regions.展开更多
In social network analysis, logistic regression models have been widely used to establish the relationship between the response variable and covariates. However, such models often require the network relationships to ...In social network analysis, logistic regression models have been widely used to establish the relationship between the response variable and covariates. However, such models often require the network relationships to be mutually independent, after controlling for a set of covariates. To assess the validity of this assumption,we propose test statistics, under the logistic regression setting, for three important social network drivers. They are, respectively, reciprocity, centrality, and transitivity. The asymptotic distributions of those test statistics are obtained. Extensive simulation studies are also presented to demonstrate their finite sample performance and usefulness.展开更多
文摘Monitoring and evaluating the nutritional status of vegetation under stress from exhausted coal mining sites by hyper-spectral remote sensing is important in future ecological restoration engineering. The Wangpingcun coal mine, located in the Mentougou district of Beijing, was chosen as a case study. The ecological damage was analyzed by 3S technology, field investigation and from chemical data. The derivative spectra of the diagnostic absorption bands are derived from the spectra measured in the field and used as characteristic spectral variables. A correlation analysis was conducted for the nitrogen content of the vegetation samples and the fast derivative spectrum and the estimation model of nitrogen content established by a multiple stepwise linear regression method. The spatial distribution of nitrogen content was extracted by a parameter mapping method from the Hyperion data which revealed the distribution of the nitrogen content. In addition, the estimation model was evaluated for two evaluation indicators which are important for the precision of the model. Experimental results indicate that by linear regression and parameter mapping, the estimation model precision was Very high. The coefficient of determination, R2, was 0.795 and the standard deviation of residual （SDR） 0.19. The nitrogen content of most samples was about 1.03% and the nitrogen content in the study site seems inversely proportional to the distance from the piles of coal waste. Therefore, we can conclude that inversely modeling nitrogen content by hyper-spectral remote sensing in exhausted coal mining sites is feasible and our study can be taken as reference in species selection and in subseauent management and maintenance in ecological restoration.
基金Indian Institute of Technology,Kharagpur in India for supporting this work
文摘Particle size distribution of coarse aggregates through mechanical sieving gives results in terms of cumu- lative mass percent. But digital image processing generated size distribution of particles, while being fast and accurate, is often expressed in terms of area function or number of particles. In this paper, a mass model is developed which converts the image obtained size distribution to mass-wise distribution, mak- ing it readily comparable to mechanical sieving data. The concept of weight/particle ratio is introduced for mass reconstruction from 2D images of particle aggregates. Using this mass model, the effects of several particle shape parameters （such as major axis, minor axis, and equivalent diameter） on sieve-size of the particles is studied. It is shown that the sieve-size of a particle strongly depend upon the shape param- eters, 91% of its variation being explained by major axis, minor axis, bounding box length and equivalent diameter. Furthermore, minor axis gives an overall accurate estimate of particle sieve-size, error in mean size （D-50） being just 0.4%. However, sieve-size of smaller particles （〈20 ram） strongly depends upon the length of the smaller arm of the bounding box enclosing them and sieve-sizes of larger particles （〉20 mm） are highly correlated to their equivalent diameters. Multiple linear regression analysis has been used to generate overall mass-wise particle size distribution, considering the influences of all these shape parameters on particle sieve-size. Multiple linear regression generated overall mass-wise particle size distribution shows a strong correlation with sieve generated data. The adjusted R-square value of the regression analysis is found to be 99 percent （w.r,t cumulative frequency）. The method proposed in this paper provides a time-efficient way of producing accurate （up to 99%） mass-wise PSD using digital image processing and it can be used effectively to renlace the mechanical sieving.
文摘This paper uses regression analysis and econometric modeling foundations to track public expenditures in the Slovak Republic and the Czech Republic （Fejesova, 2011） and their influences on the development of the following two targets of the Europe 2020 Strategy： to increase the employment of the selected population groups to a predetermined percentage level and to reduce the number of people at risk of poverty. In addition to the selection of monitored indicators, we included other indicators from the social sphere, which are funded by mandatory national public expenditure budgets and which are expected to have a positive development in terms of improving the demographic structure of the country--the unemployment rate and the number of live births.
文摘Fluctuations of the world oil prices affect economic performance. Outside the impact on the sector of energy production, the rising oil price has consequences on inflationary pressures and a deteriorating fiscal position of Burkina Faso. In this context, studying the impact of rising oil prices on the economy, especially the cost of living of its population has a great interest because although many studies have attempted to link 〈〈oil prices〉~ and 〈〈cost of living~, very few have focused on the specific case of Burkina Faso. This allows us to make our contribution to this construction literature. This contribution will consist to highlight the relation between changes in oil prices and the cost of living in Burkina Faso. Also to be reached, we will find the best indicator to reflect the cost of living in Burkina Faso, identify the suitable econometric model for estimating the correlation and verify the existence of the relation between oil prices and the cost of living. For a better approach to this study, we used a VAR （Vector Auto-Regressive） model. Also, we will use documentary research that will make an assessment on the existing in terms of theoretical debates around the theme descriptive statistics that will help to introduce and describe the variables used in the study, and econometric analysis will analyze and estimate the parameters of our objective function using Eviews.
基金Project supported by the National Natural Science Foundation of China (No. 19631040).
文摘This paper studies the parameter estimation of one dimensional linear errors-in-variables(EV) models in the case that replicated observations are available in some experimental points.Asymptotic normality is established under mild conditions, and the parameters entering the asymptotic variance are consistently estimated to render the result useable in construction of large-sample confidence regions.
文摘In social network analysis, logistic regression models have been widely used to establish the relationship between the response variable and covariates. However, such models often require the network relationships to be mutually independent, after controlling for a set of covariates. To assess the validity of this assumption,we propose test statistics, under the logistic regression setting, for three important social network drivers. They are, respectively, reciprocity, centrality, and transitivity. The asymptotic distributions of those test statistics are obtained. Extensive simulation studies are also presented to demonstrate their finite sample performance and usefulness.
