Amidst growing environmental protection intensity by the Chinese government, this paper investigates the effects of environmental regulation on China＇s industrial pollution treatment productivity and environmental TF...Amidst growing environmental protection intensity by the Chinese government, this paper investigates the effects of environmental regulation on China＇s industrial pollution treatment productivity and environmental TFP. By estimating China＇s pollution treatment productivity between 2001 and 2008 and analyzing environmental regulation intensity and the effects of the relevant factors and pollution treatment productivity using panel data, this paper discovers that （1） pollution treatment productivity contributed a significant share of about 40% to industrial environmental TFP during the investigation period; （2） environmental regulation may not necessarily cause adverse impacts on pollution treatment efficiency and productivity but demonstrates a U-shaped relationship： when the share of pollution treatment cost in industrial value-added is above the range of 3.8%-5.1%, environmental regulation is likely to promote pollution treatment productivity and thus environmental TFP Judging by the estimation result, enhancing environmental protection and expediting the development of ecological civilization are conducive to China ＂s economic transition towards an intensive, efficient, circular, and sustainable development pattern. China＇s current industrial development has the capacity to tolerate a rather demanding level of pollution treatment and management and China needs to further rely on energy conservation and the environmental production industries to promote the progress of pollution treatment technologies.展开更多
In cloud computing,fairness is one of the most significant indicators to evaluate resource allocation algorithms,which reveals whether each user is allocated as much as that of all other users having the same bottlene...In cloud computing,fairness is one of the most significant indicators to evaluate resource allocation algorithms,which reveals whether each user is allocated as much as that of all other users having the same bottleneck.However,how fair an allocation algorithm is remains an urgent issue.In this paper,we propose Dynamic Evaluation Framework for Fairness(DEFF),a framework to evaluate the fairness of an resource allocation algorithm.In our framework,two sub-models,Dynamic Demand Model(DDM) and Dynamic Node Model(DNM),are proposed to describe the dynamic characteristics of resource demand and the computing node number under cloud computing environment.Combining Fairness on Dominant Shares and the two sub-models above,we finally obtain DEFF.In our experiment,we adopt several typical resource allocation algorithms to prove the effectiveness on fairness evaluation by using the DEFF framework.展开更多
The detection and identification of gross errors, especially measurement bias, plays a vital role in data reconciliation for nonlinear dynamic systems. Although parameter estimation method has been proved to be a pow-...The detection and identification of gross errors, especially measurement bias, plays a vital role in data reconciliation for nonlinear dynamic systems. Although parameter estimation method has been proved to be a pow-erful tool for bias identification, without a reliable and efficient bias detection strategy, the method is limited in ef-ficiency and cannot be applied widely. In this paper, a new bias detection strategy is constructed to detect the pres-ence of measurement bias and its occurrence time. With the help of this strategy, the number of parameters to be es-timated is greatly reduced, and sequential detections and iterations are also avoided. In addition, the number of de-cision variables of the optimization model is reduced, through which the influence of the parameters estimated is reduced. By incorporating the strategy into the parameter estimation model, a new methodology named IPEBD (Improved Parameter Estimation method with Bias Detection strategy) is constructed. Simulation studies on a con-tinuous stirred tank reactor (CSTR) and the Tennessee Eastman (TE) problem show that IPEBD is efficient for eliminating random errors, measurement biases and outliers contained in dynamic process data.展开更多
Units and components of the powerful power equipment are exposed to the big static and dynamic load. An example of such equipments is turbines hydraulic power plant and, especially, hydroelectric pumped storage power ...Units and components of the powerful power equipment are exposed to the big static and dynamic load. An example of such equipments is turbines hydraulic power plant and, especially, hydroelectric pumped storage power plant. Existing techniques of control of a vibrating condition do not consider： very wide frequency range of vibrating processes, difficult character of such processes in the form of the sum multiharmonic, random and close to shock processes. Such techniques usually do not consider intervals of start-up and stop, and also work on transitive modes when loadings on a construction are maximum. Available techniques of an estimation of admissible level of vibrating influence and tests for vibration durability are not harmonized enough among themselves. Various known interpretations of communication of vibrating characteristics and durability estimations on mechanical pressure at broadband vibrating influence yield ambiguous result. On the basis of the analysis of the published information, we attempt to formulate the requirement to system of vibrating monitoring of the hydraulic turbine and power motor pumps. System should provide data acquisition and the analysis of the data on a vibrating condition taking into account accumulation of vibrating influences and long term of operation on the basis of estimation methods as low-cycle, and high-cycle （gigacycle） fatigue is made.展开更多
The performance of the conventional Kalman filter depends on process and measurement noise statistics given by the system model and measurements.The conventional Kalman filter is usually used for a linear system,but i...The performance of the conventional Kalman filter depends on process and measurement noise statistics given by the system model and measurements.The conventional Kalman filter is usually used for a linear system,but it should not be used for estimating the state of a nonlinear system such as a satellite motion because it is difficult to obtain the desired estimation results.The linearized Kalman filtering approach and the extended Kalman filtering approach have been proposed for a general nonlinear system.The equations of satellite motion are described.The satellite motion states are estimated,and the relevant estimation errors are calculated through the estimation algorithms of the both above mentioned approaches implemented in Matlab are estimated.The performances of the extended Kalman filter and the linearized Kalman filter are compared.The simulation results show that the extended Kalman filter is much better than the linearized Kalman filter at the aspect of estimation effect.展开更多
A sensor scheduling problem was considered for a class of hybrid systems named as the stochastic linear hybrid system （SLHS）. An algorithm was proposed to select one （or a group of） sensor at each time from a set ...A sensor scheduling problem was considered for a class of hybrid systems named as the stochastic linear hybrid system （SLHS）. An algorithm was proposed to select one （or a group of） sensor at each time from a set of sensors. Then, a hybrid estimation algorithm was designed to compute the estimates of the continuous and discrete states of the SLHS based on the observations from the selected sensors. As the sensor scheduling algorithm is designed such that the Bayesian decision risk is minimized, the true discrete state can be better identified. Moreover, the continuous state estimation performance of the proposed algorithm is better than that of hybrid estimation algorithms using only predetermined sensors. Finallyo the algorithms are validated through an illustrative target tracking example.展开更多
Under dynamic conditions, the signals of power system have time-varying magnitude and frequency, which might lead to considerable errors for synchrophasor measurement. The traditional discrete Fourier transform (DFT) ...Under dynamic conditions, the signals of power system have time-varying magnitude and frequency, which might lead to considerable errors for synchrophasor measurement. The traditional discrete Fourier transform (DFT) based algorithms used in Phasor Measurement Unit (PMU) are hard to meet the requirements of measurement accuracy because of the existence of spectral leakage. A dynamic phasor measurement algorithm is proposed in this paper in which the input sampled data are considered as non-stationary signals with amplitude modulation-frequency modulation (AM-FM) form, and the measurement is achieved by AM-FM demodulation. An angle-shifted energy operator (ASEO) is used to extract the instantaneous amplitude and low pass differential filter is introduced for frequency estimation. Simulation results indicate that the proposed algorithm can effectively improve the phasor measurement accuracy and has very short response time for PMU under dynamic conditions.展开更多
文摘Amidst growing environmental protection intensity by the Chinese government, this paper investigates the effects of environmental regulation on China＇s industrial pollution treatment productivity and environmental TFP. By estimating China＇s pollution treatment productivity between 2001 and 2008 and analyzing environmental regulation intensity and the effects of the relevant factors and pollution treatment productivity using panel data, this paper discovers that （1） pollution treatment productivity contributed a significant share of about 40% to industrial environmental TFP during the investigation period; （2） environmental regulation may not necessarily cause adverse impacts on pollution treatment efficiency and productivity but demonstrates a U-shaped relationship： when the share of pollution treatment cost in industrial value-added is above the range of 3.8%-5.1%, environmental regulation is likely to promote pollution treatment productivity and thus environmental TFP Judging by the estimation result, enhancing environmental protection and expediting the development of ecological civilization are conducive to China ＂s economic transition towards an intensive, efficient, circular, and sustainable development pattern. China＇s current industrial development has the capacity to tolerate a rather demanding level of pollution treatment and management and China needs to further rely on energy conservation and the environmental production industries to promote the progress of pollution treatment technologies.
基金supported in part by Program for Changjiang Scholars and Innovative Research Team in University No.IRT1078The Key Program of NSFC-Guangdong Union Foundation No.U1135002The Fundamental Research Funds for the Central Universities No.JY0900120301
文摘In cloud computing,fairness is one of the most significant indicators to evaluate resource allocation algorithms,which reveals whether each user is allocated as much as that of all other users having the same bottleneck.However,how fair an allocation algorithm is remains an urgent issue.In this paper,we propose Dynamic Evaluation Framework for Fairness(DEFF),a framework to evaluate the fairness of an resource allocation algorithm.In our framework,two sub-models,Dynamic Demand Model(DDM) and Dynamic Node Model(DNM),are proposed to describe the dynamic characteristics of resource demand and the computing node number under cloud computing environment.Combining Fairness on Dominant Shares and the two sub-models above,we finally obtain DEFF.In our experiment,we adopt several typical resource allocation algorithms to prove the effectiveness on fairness evaluation by using the DEFF framework.
基金Supported by the National High Technology Research and Development Program of China (2006AA04Z176)
文摘The detection and identification of gross errors, especially measurement bias, plays a vital role in data reconciliation for nonlinear dynamic systems. Although parameter estimation method has been proved to be a pow-erful tool for bias identification, without a reliable and efficient bias detection strategy, the method is limited in ef-ficiency and cannot be applied widely. In this paper, a new bias detection strategy is constructed to detect the pres-ence of measurement bias and its occurrence time. With the help of this strategy, the number of parameters to be es-timated is greatly reduced, and sequential detections and iterations are also avoided. In addition, the number of de-cision variables of the optimization model is reduced, through which the influence of the parameters estimated is reduced. By incorporating the strategy into the parameter estimation model, a new methodology named IPEBD (Improved Parameter Estimation method with Bias Detection strategy) is constructed. Simulation studies on a con-tinuous stirred tank reactor (CSTR) and the Tennessee Eastman (TE) problem show that IPEBD is efficient for eliminating random errors, measurement biases and outliers contained in dynamic process data.
文摘Units and components of the powerful power equipment are exposed to the big static and dynamic load. An example of such equipments is turbines hydraulic power plant and, especially, hydroelectric pumped storage power plant. Existing techniques of control of a vibrating condition do not consider： very wide frequency range of vibrating processes, difficult character of such processes in the form of the sum multiharmonic, random and close to shock processes. Such techniques usually do not consider intervals of start-up and stop, and also work on transitive modes when loadings on a construction are maximum. Available techniques of an estimation of admissible level of vibrating influence and tests for vibration durability are not harmonized enough among themselves. Various known interpretations of communication of vibrating characteristics and durability estimations on mechanical pressure at broadband vibrating influence yield ambiguous result. On the basis of the analysis of the published information, we attempt to formulate the requirement to system of vibrating monitoring of the hydraulic turbine and power motor pumps. System should provide data acquisition and the analysis of the data on a vibrating condition taking into account accumulation of vibrating influences and long term of operation on the basis of estimation methods as low-cycle, and high-cycle （gigacycle） fatigue is made.
文摘The performance of the conventional Kalman filter depends on process and measurement noise statistics given by the system model and measurements.The conventional Kalman filter is usually used for a linear system,but it should not be used for estimating the state of a nonlinear system such as a satellite motion because it is difficult to obtain the desired estimation results.The linearized Kalman filtering approach and the extended Kalman filtering approach have been proposed for a general nonlinear system.The equations of satellite motion are described.The satellite motion states are estimated,and the relevant estimation errors are calculated through the estimation algorithms of the both above mentioned approaches implemented in Matlab are estimated.The performances of the extended Kalman filter and the linearized Kalman filter are compared.The simulation results show that the extended Kalman filter is much better than the linearized Kalman filter at the aspect of estimation effect.
基金Foundation item： Project（2012AA051603） supported by the National High Technology Research and Development Program 863 Plan of China
文摘A sensor scheduling problem was considered for a class of hybrid systems named as the stochastic linear hybrid system （SLHS）. An algorithm was proposed to select one （or a group of） sensor at each time from a set of sensors. Then, a hybrid estimation algorithm was designed to compute the estimates of the continuous and discrete states of the SLHS based on the observations from the selected sensors. As the sensor scheduling algorithm is designed such that the Bayesian decision risk is minimized, the true discrete state can be better identified. Moreover, the continuous state estimation performance of the proposed algorithm is better than that of hybrid estimation algorithms using only predetermined sensors. Finallyo the algorithms are validated through an illustrative target tracking example.
基金supported by the Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No.20090002110040)
文摘Under dynamic conditions, the signals of power system have time-varying magnitude and frequency, which might lead to considerable errors for synchrophasor measurement. The traditional discrete Fourier transform (DFT) based algorithms used in Phasor Measurement Unit (PMU) are hard to meet the requirements of measurement accuracy because of the existence of spectral leakage. A dynamic phasor measurement algorithm is proposed in this paper in which the input sampled data are considered as non-stationary signals with amplitude modulation-frequency modulation (AM-FM) form, and the measurement is achieved by AM-FM demodulation. An angle-shifted energy operator (ASEO) is used to extract the instantaneous amplitude and low pass differential filter is introduced for frequency estimation. Simulation results indicate that the proposed algorithm can effectively improve the phasor measurement accuracy and has very short response time for PMU under dynamic conditions.
