By extending the concept of diffusion to the potential energy landscapes(PELs), we introduce the meansquared energy difference(MSED) as a novel quantity to investigate the intrinsic properties of supercooled liquids. ...By extending the concept of diffusion to the potential energy landscapes(PELs), we introduce the meansquared energy difference(MSED) as a novel quantity to investigate the intrinsic properties of supercooled liquids. MSED can provide a clear description of the “energy relaxation” process on a PEL. Through MSED analysis, we have obtained a characteristic time similar to that derived from structure analysis, namely τ_(α)^(*).Further, we establish a connection between MSED and the feature of PELs, providing a concise and quantitative description of PELs. The relaxation behavior of energy has been found to follow a stretched exponential form.As the temperature decreases, the roughness of the accessible PEL changes significantly around a characteristic temperature T_(x), which is 20% higher than the glass transition temperature T_(g) and is comparable to the critical temperature of the mode-coupling theory. More importantly, one of the PEL parameters is closely related to the Adam–Gibbs configurational entropy. The present research, which directly links the PEL to the relaxation process, provides avenues for further research of glasses.展开更多
Historical database of National Soil Survey Center containing 1424 geo-referenced soil profiles was used in this study for estimating the organic carbon （SOC） for the soils of Ohio, USA. Specific objective of the st...Historical database of National Soil Survey Center containing 1424 geo-referenced soil profiles was used in this study for estimating the organic carbon （SOC） for the soils of Ohio, USA. Specific objective of the study was to estimate the spatial distribution of SOC density （C stock per unit area） to 1.0-m depth for soils of Ohio using geographically weighted regression （GWR）, and compare the results with that obtained from multiple linear regression （MLR）. About 80% of the analytical data were used for calibration and 20% for validation. A total of 20 variables including terrain attributes, climate data, bedrock geology, and land use data were used for mapping the SOC density. Results showed that the GWR provided better estimations with the lowest （3.81 kg m-2） root mean square error （RMSE） than MLR approach Total estimated SOC pool for soils in Ohio ranged from 727 to 742 Tg. This study demon strates that, the local spatial statistical technique, the GWR can perform better in capturing the spatial distribution of SOC across the study region as compared to other global spatial statistical techniques such as MLR. Thus, GWR enhances the accuracy for mapping SOC density.展开更多
This paper is concerned with the robust stabilization problem of networked control systems with stochastic packet dropouts and uncertain parameters. Considering the stochastic packet dropout occuring in two channels b...This paper is concerned with the robust stabilization problem of networked control systems with stochastic packet dropouts and uncertain parameters. Considering the stochastic packet dropout occuring in two channels between the sensor and the controller, and between the controller and the actuator, networked control systems are modeled as the Markovian jump linear system with four operation modes. Based on this model, the necessary and sufficient conditions for the mean square stability of the deterministic networked control systems and uncertain networked control systems are given by using the theory of the Markovian jump linear system, and corresponding controller design procedures are proposed via the cone complementarity linearization method. Finally, the numerical example and simulations are given to illustrate the effectiveness of the proposed results.展开更多
The computational cost required by the Ensemble Kalman Filter （EnKF） is much larger than that of some simpler assimilation schemes, such as Optimal Interpolation （OI） or three-dimension variational as- similation ...The computational cost required by the Ensemble Kalman Filter （EnKF） is much larger than that of some simpler assimilation schemes, such as Optimal Interpolation （OI） or three-dimension variational as- similation （3DVAR）. Ensemble optimal interpolation （EnOI）, a crudely simplified implementation of EnKF, is sometimes used as a substitute in some oceanic applications and requires much less computational time than EnKF. In this paper, to compromise between computational cost and dynamic covariance, we use the idea of ＂dressing＂ a small size dynamical ensemble with a larger number of static ensembles in order to form an approximate dynamic covariance. The term ＂dressing＂ means that a dynamical ensemble seed from model runs is perturbed by adding the anomalies of some static ensembles. This dressing EnKF （DrEnKF for short） scheme is tested in assimilation of real altimetry data in the Pacific using the HYbrid Coordinate Ocean Model （HYCOM） over a four-year period. Ten dynamical ensemble seeds are each dressed by 10 static ensemble members selected from a 100-member static ensemble. Results are compared to two EnKF assimilation runs that use 10 and 100 dynamical ensemble members. Both temperature and salinity fields from the DrEnKF and the EnKF are compared to observations from Argo floats and an OI SST dataset. The results show that the DrEnKF and the 100-member EnKF yield similar root mean square errors （RMSE） at every model level. Error covariance matrices from the DrEnKF and the 100-member EnKF are also compared and show good agreement.展开更多
The forms of minimum wavepackets (MWPs) corresponding to the geueralized momentum space and coordinates spaca are derived by using the generalized Hermitian expression of the momentum operator in curvilinear coordinat...The forms of minimum wavepackets (MWPs) corresponding to the geueralized momentum space and coordinates spaca are derived by using the generalized Hermitian expression of the momentum operator in curvilinear coordinates. The several MWPs are discussed according to different upper and lower limits of the usual coordinate componets, and the relevant conclusions are drawn in this paper.展开更多
We investigate the problem of H_(∞) state estimation for discrete-time Markov jump neural networks. The transition probabilities of the Markov chain are assumed to be piecewise time-varying, and the persistent dwell-...We investigate the problem of H_(∞) state estimation for discrete-time Markov jump neural networks. The transition probabilities of the Markov chain are assumed to be piecewise time-varying, and the persistent dwell-time switching rule,as a more general switching rule, is adopted to describe this variation characteristic. Afterwards, based on the classical Lyapunov stability theory, a Lyapunov function is established, in which the information about the Markov jump feature of the system mode and the persistent dwell-time switching of the transition probabilities is considered simultaneously.Furthermore, via using the stochastic analysis method and some advanced matrix transformation techniques, some sufficient conditions are obtained such that the estimation error system is mean-square exponentially stable with an H_(∞) performance level, from which the specific form of the estimator can be obtained. Finally, the rationality and effectiveness of the obtained results are verified by a numerical example.展开更多
By analyzing the relationship between Basis Expansion Model (BEM) and Doppler spectrum, this letter proposed a quasi-MMSE-based BEM estimation scheme for doubly selective channels. Based on the assumption that the bas...By analyzing the relationship between Basis Expansion Model (BEM) and Doppler spectrum, this letter proposed a quasi-MMSE-based BEM estimation scheme for doubly selective channels. Based on the assumption that the basis coefficients are approximately independent and have the same variance for the same channel tap, the quasi-MMSE estimation shows approximately optimal performance and is robust to noise. Moreover, it can avoid a high Peak-to-Average Power Ratio (PAPR) by using continuous pilots. Performance of the proposed estimation scheme has been shown with computer simulations.展开更多
For a century or so, the Hong Kong Observatory （HKO） has been providing temperature forecast for the whole of Hong Kong with the HKO Headquarters as the reference location. In recent decades, due to spreading of pop...For a century or so, the Hong Kong Observatory （HKO） has been providing temperature forecast for the whole of Hong Kong with the HKO Headquarters as the reference location. In recent decades, due to spreading of population from the main urban center to satellite towns, there is an increasing demand for regional temperature forecasts. To support such provision, the HKO has developed a regression model to provide objective guidance to forecasters in formulating forecasts of maximum and minimum temperatures for the next day at various locations in Hong Kong. In this paper, the regression model is presented, together with the assessment of its performance. Based on the verification of one year of forecasts, it is found that the root mean square errors （RMSEs） of maximum （minimum） temperature forecasts are from about 1.3 to 2.1 （1.1 to 1.4） degrees, respectively. The regression model is shown to have generally out-performed the operational regional spectral model then operated by HKO. Regional temperature forecast methods of other meteorological or research centers are also surveyed. Equipped with the regression model, the HKO has launched an online regional temperature forecast service for the next day in Hong Kong since March 2008.展开更多
基金supported by the National Key Research and Development Program of China (Grant No. 2022YFA1404603)by the National Natural Science Foundation of China (Grant Nos. 12274127 and 12188101)。
文摘By extending the concept of diffusion to the potential energy landscapes(PELs), we introduce the meansquared energy difference(MSED) as a novel quantity to investigate the intrinsic properties of supercooled liquids. MSED can provide a clear description of the “energy relaxation” process on a PEL. Through MSED analysis, we have obtained a characteristic time similar to that derived from structure analysis, namely τ_(α)^(*).Further, we establish a connection between MSED and the feature of PELs, providing a concise and quantitative description of PELs. The relaxation behavior of energy has been found to follow a stretched exponential form.As the temperature decreases, the roughness of the accessible PEL changes significantly around a characteristic temperature T_(x), which is 20% higher than the glass transition temperature T_(g) and is comparable to the critical temperature of the mode-coupling theory. More importantly, one of the PEL parameters is closely related to the Adam–Gibbs configurational entropy. The present research, which directly links the PEL to the relaxation process, provides avenues for further research of glasses.
文摘Historical database of National Soil Survey Center containing 1424 geo-referenced soil profiles was used in this study for estimating the organic carbon （SOC） for the soils of Ohio, USA. Specific objective of the study was to estimate the spatial distribution of SOC density （C stock per unit area） to 1.0-m depth for soils of Ohio using geographically weighted regression （GWR）, and compare the results with that obtained from multiple linear regression （MLR）. About 80% of the analytical data were used for calibration and 20% for validation. A total of 20 variables including terrain attributes, climate data, bedrock geology, and land use data were used for mapping the SOC density. Results showed that the GWR provided better estimations with the lowest （3.81 kg m-2） root mean square error （RMSE） than MLR approach Total estimated SOC pool for soils in Ohio ranged from 727 to 742 Tg. This study demon strates that, the local spatial statistical technique, the GWR can perform better in capturing the spatial distribution of SOC across the study region as compared to other global spatial statistical techniques such as MLR. Thus, GWR enhances the accuracy for mapping SOC density.
基金supported by the National Natural Science Foundation of China (60574082,60804027)
文摘This paper is concerned with the robust stabilization problem of networked control systems with stochastic packet dropouts and uncertain parameters. Considering the stochastic packet dropout occuring in two channels between the sensor and the controller, and between the controller and the actuator, networked control systems are modeled as the Markovian jump linear system with four operation modes. Based on this model, the necessary and sufficient conditions for the mean square stability of the deterministic networked control systems and uncertain networked control systems are given by using the theory of the Markovian jump linear system, and corresponding controller design procedures are proposed via the cone complementarity linearization method. Finally, the numerical example and simulations are given to illustrate the effectiveness of the proposed results.
基金supported by the Knowledge Innovation Program of Chinese Academy of Sciences (Grant No. KZCX1-YW-12-03)National Basic Research Program of China (2006CB403600)+3 种基金Project of Young Scientists Fund by National Natural Sciences Foundation of China (Grant No. 40606008)National Science and Technology Infrastructure Program(2006BAC03B04)supported by National Natural Sciences Foundation of China (Grant No.40531006)supported by a private donation from Trond Mohn c/o Frank Mohn AS, Bergenand the MERSEA project from the European Commission (Grant No. SIP3-CT-2003-502885)
文摘The computational cost required by the Ensemble Kalman Filter （EnKF） is much larger than that of some simpler assimilation schemes, such as Optimal Interpolation （OI） or three-dimension variational as- similation （3DVAR）. Ensemble optimal interpolation （EnOI）, a crudely simplified implementation of EnKF, is sometimes used as a substitute in some oceanic applications and requires much less computational time than EnKF. In this paper, to compromise between computational cost and dynamic covariance, we use the idea of ＂dressing＂ a small size dynamical ensemble with a larger number of static ensembles in order to form an approximate dynamic covariance. The term ＂dressing＂ means that a dynamical ensemble seed from model runs is perturbed by adding the anomalies of some static ensembles. This dressing EnKF （DrEnKF for short） scheme is tested in assimilation of real altimetry data in the Pacific using the HYbrid Coordinate Ocean Model （HYCOM） over a four-year period. Ten dynamical ensemble seeds are each dressed by 10 static ensemble members selected from a 100-member static ensemble. Results are compared to two EnKF assimilation runs that use 10 and 100 dynamical ensemble members. Both temperature and salinity fields from the DrEnKF and the EnKF are compared to observations from Argo floats and an OI SST dataset. The results show that the DrEnKF and the 100-member EnKF yield similar root mean square errors （RMSE） at every model level. Error covariance matrices from the DrEnKF and the 100-member EnKF are also compared and show good agreement.
文摘The forms of minimum wavepackets (MWPs) corresponding to the geueralized momentum space and coordinates spaca are derived by using the generalized Hermitian expression of the momentum operator in curvilinear coordinates. The several MWPs are discussed according to different upper and lower limits of the usual coordinate componets, and the relevant conclusions are drawn in this paper.
基金supported by the National Natural Science Foundation of China (Grant Nos. 61873002, 61703004, 61973199, 61573008, and 61973200)。
文摘We investigate the problem of H_(∞) state estimation for discrete-time Markov jump neural networks. The transition probabilities of the Markov chain are assumed to be piecewise time-varying, and the persistent dwell-time switching rule,as a more general switching rule, is adopted to describe this variation characteristic. Afterwards, based on the classical Lyapunov stability theory, a Lyapunov function is established, in which the information about the Markov jump feature of the system mode and the persistent dwell-time switching of the transition probabilities is considered simultaneously.Furthermore, via using the stochastic analysis method and some advanced matrix transformation techniques, some sufficient conditions are obtained such that the estimation error system is mean-square exponentially stable with an H_(∞) performance level, from which the specific form of the estimator can be obtained. Finally, the rationality and effectiveness of the obtained results are verified by a numerical example.
基金Supported by the National Natural Science Foundation of China (No.60462002).
文摘By analyzing the relationship between Basis Expansion Model (BEM) and Doppler spectrum, this letter proposed a quasi-MMSE-based BEM estimation scheme for doubly selective channels. Based on the assumption that the basis coefficients are approximately independent and have the same variance for the same channel tap, the quasi-MMSE estimation shows approximately optimal performance and is robust to noise. Moreover, it can avoid a high Peak-to-Average Power Ratio (PAPR) by using continuous pilots. Performance of the proposed estimation scheme has been shown with computer simulations.
文摘For a century or so, the Hong Kong Observatory （HKO） has been providing temperature forecast for the whole of Hong Kong with the HKO Headquarters as the reference location. In recent decades, due to spreading of population from the main urban center to satellite towns, there is an increasing demand for regional temperature forecasts. To support such provision, the HKO has developed a regression model to provide objective guidance to forecasters in formulating forecasts of maximum and minimum temperatures for the next day at various locations in Hong Kong. In this paper, the regression model is presented, together with the assessment of its performance. Based on the verification of one year of forecasts, it is found that the root mean square errors （RMSEs） of maximum （minimum） temperature forecasts are from about 1.3 to 2.1 （1.1 to 1.4） degrees, respectively. The regression model is shown to have generally out-performed the operational regional spectral model then operated by HKO. Regional temperature forecast methods of other meteorological or research centers are also surveyed. Equipped with the regression model, the HKO has launched an online regional temperature forecast service for the next day in Hong Kong since March 2008.
