Let {Xn, n≥1} be a strictly stationary sequence of random variables, which are either associated or negatively associated, f(.) be their common density. In this paper, the author shows a central limit theorem for a k...Let {Xn, n≥1} be a strictly stationary sequence of random variables, which are either associated or negatively associated, f(.) be their common density. In this paper, the author shows a central limit theorem for a kernel estimate of f(.) under certain regular conditions.展开更多
Due to the frequency of occlusion, cluttering and lowcontrast edges, gray intensity based active contour models oftenfail to segment meaningful objects. Prior shape information is usuallyutilized to segment desirable ...Due to the frequency of occlusion, cluttering and lowcontrast edges, gray intensity based active contour models oftenfail to segment meaningful objects. Prior shape information is usuallyutilized to segment desirable objects. A parametric shape priormodel is proposed. Firstly, principal component analysis is employedto train object shape and transformation is added to shaperepresentation. Then the energy function is constructed througha combination of shape prior energy, gray intensity energy andshape constraint energy of the kernel density function. The objectboundary extraction process is converted into the parameters solvingprocess of object shape. Besides, two new shape prior energyfunctions are defined when desirable objects are occluded by otherobjects or some parts of them are missing. Finally, an alternatingdecent iteration solving scheme is proposed for numerical implementation.Experiments on synthetic and real images demonstratethe robustness and accuracy of the proposed method.展开更多
With the increase of total energy consumption,eco-environmental quality drops sharply,which has attracted concerns from all circles.It has become the top priority of construction of socialist ecological civilization t...With the increase of total energy consumption,eco-environmental quality drops sharply,which has attracted concerns from all circles.It has become the top priority of construction of socialist ecological civilization to clarify the influences of energy consumption on the level of eco-environmental pollution.Ecological environmental pollution control cannot be one size fits all.It can avoid resource depletion and environmental deterioration via adjusting measures to local conditions to coordinate ecological environmental pollution and energy consumption problems.In this essay,entropy method is adopted to measure the composite indexes of eco-environmental pollution of 30 provinces and cities in China,based on which kernel density function is used to analyze the dynamic law of eco-environmental pollution.And then,traditional fixed effect model and panel quantile regression model are adopted respectively to analyze the influences of energy consumption on eco-environmental pollution.The research finds that composite index of eco-environmental pollution shows N-shaped curve of“rising-dropping-rising”during the sample period,with the overall difference decreasing gradually and the polarization disappearing gradually;in areas with higher eco-environmental pollution,energy consumption has aggravated ecoenvironmental pollution,while in areas with lower eco-environmental pollution,energy consumption could alleviate eco-environmental pollution to some degree;foreign direct investment could relieve eco-environmental pollution.Therefore,corresponding measures should be taken to improve the quality of eco-environment based on the changes of energy consumption in areas with different levels of eco-environmental pollution.展开更多
Existing literature is characterized by certain deficiencies in measuring housing bubbles in China. By extending the analytical framework of Black et al. (2006) to a spatial panel VAR structure, this paper measures ...Existing literature is characterized by certain deficiencies in measuring housing bubbles in China. By extending the analytical framework of Black et al. (2006) to a spatial panel VAR structure, this paper measures housing bubbles in China's 35 major cities from 1999Q2 to 2012Q3 and analyzes the spatial-temporal changes of the housing bubbles in these cities. Results indicate that 1) changes to housing bubbles in most cities highly correspond with changes in the main real estate policies of the country and 2) housing bubbles in eastern developed cities such as Beijing, Shanghai, Shenzhen, Hangzhou, and Ningbo, have been relatively large in recent years although the average housing bubble is not very serious over the 35 major cities. Through the Kernel Density Function and local indicators of spatial autocorrelation analysis, this paper finds that housing bubbles are concentrated in several eastern developed cities. Based on empirical analysis, this paper proposes policy recommendations on inhibiting the expansion and diffusion of housing bubbles.展开更多
文摘Let {Xn, n≥1} be a strictly stationary sequence of random variables, which are either associated or negatively associated, f(.) be their common density. In this paper, the author shows a central limit theorem for a kernel estimate of f(.) under certain regular conditions.
基金supported by the National Natural Science Foundation of China(6137214261571005U1401252)
文摘Due to the frequency of occlusion, cluttering and lowcontrast edges, gray intensity based active contour models oftenfail to segment meaningful objects. Prior shape information is usuallyutilized to segment desirable objects. A parametric shape priormodel is proposed. Firstly, principal component analysis is employedto train object shape and transformation is added to shaperepresentation. Then the energy function is constructed througha combination of shape prior energy, gray intensity energy andshape constraint energy of the kernel density function. The objectboundary extraction process is converted into the parameters solvingprocess of object shape. Besides, two new shape prior energyfunctions are defined when desirable objects are occluded by otherobjects or some parts of them are missing. Finally, an alternatingdecent iteration solving scheme is proposed for numerical implementation.Experiments on synthetic and real images demonstratethe robustness and accuracy of the proposed method.
基金“Public Service Improvement Foundation in Industry and Information under Grant No.2019-00909-2-1”.
文摘With the increase of total energy consumption,eco-environmental quality drops sharply,which has attracted concerns from all circles.It has become the top priority of construction of socialist ecological civilization to clarify the influences of energy consumption on the level of eco-environmental pollution.Ecological environmental pollution control cannot be one size fits all.It can avoid resource depletion and environmental deterioration via adjusting measures to local conditions to coordinate ecological environmental pollution and energy consumption problems.In this essay,entropy method is adopted to measure the composite indexes of eco-environmental pollution of 30 provinces and cities in China,based on which kernel density function is used to analyze the dynamic law of eco-environmental pollution.And then,traditional fixed effect model and panel quantile regression model are adopted respectively to analyze the influences of energy consumption on eco-environmental pollution.The research finds that composite index of eco-environmental pollution shows N-shaped curve of“rising-dropping-rising”during the sample period,with the overall difference decreasing gradually and the polarization disappearing gradually;in areas with higher eco-environmental pollution,energy consumption has aggravated ecoenvironmental pollution,while in areas with lower eco-environmental pollution,energy consumption could alleviate eco-environmental pollution to some degree;foreign direct investment could relieve eco-environmental pollution.Therefore,corresponding measures should be taken to improve the quality of eco-environment based on the changes of energy consumption in areas with different levels of eco-environmental pollution.
文摘Existing literature is characterized by certain deficiencies in measuring housing bubbles in China. By extending the analytical framework of Black et al. (2006) to a spatial panel VAR structure, this paper measures housing bubbles in China's 35 major cities from 1999Q2 to 2012Q3 and analyzes the spatial-temporal changes of the housing bubbles in these cities. Results indicate that 1) changes to housing bubbles in most cities highly correspond with changes in the main real estate policies of the country and 2) housing bubbles in eastern developed cities such as Beijing, Shanghai, Shenzhen, Hangzhou, and Ningbo, have been relatively large in recent years although the average housing bubble is not very serious over the 35 major cities. Through the Kernel Density Function and local indicators of spatial autocorrelation analysis, this paper finds that housing bubbles are concentrated in several eastern developed cities. Based on empirical analysis, this paper proposes policy recommendations on inhibiting the expansion and diffusion of housing bubbles.