Presently developed two-phase turbulence models under-predict the gas turbulent fluctuation, because their turbulence modification models cannot fully reflect the effect of particles. In this paper, a two-time-scale d...Presently developed two-phase turbulence models under-predict the gas turbulent fluctuation, because their turbulence modification models cannot fully reflect the effect of particles. In this paper, a two-time-scale dis- sipation model of turbulence modification, developed for the two-phase velocity correlation and for the dissipation rate of gas turbulent kinetic energy, is proposed and used to simulate sudden-expansion and swirling gas-particle flows. The proposed two-time scale model gives better results than the single-time scale model. Besides, a gas tur- bulence augmentation model accounting for the finite-size particle wake effect in the gas Reynolds stress equation is proposed. The proposed turbulence modification models are used to simulate two-phase pipe flows. It can prop- erly predict both turbulence reduction and turbulence enhancement for a certain size of particles observed in ex- periments.展开更多
The Huolin River is one of the most important water sources for Xianghai wetland, Horqin wetland, and Chaganhu wetland in the western Songnen Plain of Northeast China. The annual runoff series of 46 years at Baiyunhus...The Huolin River is one of the most important water sources for Xianghai wetland, Horqin wetland, and Chaganhu wetland in the western Songnen Plain of Northeast China. The annual runoff series of 46 years at Baiyunhushuo Hydrologic Station, which is located in the middle reaches of the Huolin River, were analyzed by using wavelet analysis. Main objective was to discuss the periodic characteristics of the runoff, and examine the temporal patterns of the Huolin River recharging to the floodplain wetlands in the lower reaches of the river, and the corresponding effects of recharging variation on the environmental evolution of the wetlands. The results show that the annual runoff varied mainly at three time scales. The intensities of periodical signals at different time scales were strongly characterized by local distribution in its time frequency domain. The interdecadal variation at a scale of more than 30yr played a leading role in the temporal pattern ofrnnoffvariation, and at this scale, the runoffat Baiyunhushuo Hydrologic Station varied in turn of flood, draught and flood. Accordingly, the landscape of the floodplain wetlands presented periodic features, especially prominent before the 1990s. Compared with intense human activities, the runoff periodic pattern at middle （10-20yr） and small （1-10yr） scales, which has relatively low energy, exerted unobvious effects on the environmental evolution of the floodplain wetlands, especially after the 1990s.展开更多
Considering the complex coupling of multiple energies and the varying load forecasting errors for an integrated energy system(IES),this study proposes a dynamic time-scale scheduling strategy based on long short-term ...Considering the complex coupling of multiple energies and the varying load forecasting errors for an integrated energy system(IES),this study proposes a dynamic time-scale scheduling strategy based on long short-term memory(LSTM)and multiple load forecasting errors.This strategy dynamically selects a hybrid timescale which is suitable for a variety of energies for each month.This is obtained by combining the mean absolute percentage error(MAPE)curve of the load forecasting with the error restriction requirements of the dispatcher.Based on the day-ahead scheduling plan,the output of the partial equipment is selectively adjusted at each time-scale to realize multi-energy collaborative optimization and gives full play to the comprehensive advantages of the IES.This is achieved by considering the differences in the response speed for each piece of equipment within the intra-day scheduling.This study uses the IES as an example,and it dynamically determines the time scale of the energy monthly.In addition,this investigation presents a detailed analysis of the output plan of the key equipment to demonstrate the necessity and the advantages of the strategy.展开更多
When modeling the soil/atmosphere interaction,it is of paramount importance to determine the net radiation flux.There are two common calculation methods for this purpose.Method 1 relies on use of air temperature,while...When modeling the soil/atmosphere interaction,it is of paramount importance to determine the net radiation flux.There are two common calculation methods for this purpose.Method 1 relies on use of air temperature,while Method 2 relies on use of both air and soil temperatures.Nowadays,there has been no consensus on the application of these two methods.In this study,the half-hourly data of solar radiation recorded at an experimental embankment are used to calculate the net radiation and long-wave radiation at different time-scales(half-hourly,hourly,and daily) using the two methods.The results show that,compared with Method 2 which has been widely adopted in agronomical,geotechnical and geo-environmental applications.Method 1 is more feasible for its simplicity and accuracy at shorter time-scale.Moreover,in case of longer time-scale,daily for instance,less variations of net radiation and long-wave radiation are obtained,suggesting that no detailed soil temperature variations can be obtained.In other words,shorter time-scales are preferred in determining net radiation flux.展开更多
According to the World Health Organization,about 50 million people worldwide suffer from epilepsy.The detection and treatment of epilepsy face great challenges.Electroencephalogram(EEG)is a significant research object...According to the World Health Organization,about 50 million people worldwide suffer from epilepsy.The detection and treatment of epilepsy face great challenges.Electroencephalogram(EEG)is a significant research object widely used in diagnosis and treatment of epilepsy.In this paper,an adaptive feature learning model for EEG signals is proposed,which combines Huber loss function with adaptive weight penalty term.Firstly,each EEG signal is decomposed by intrinsic time-scale decomposition.Secondly,the statistical index values are calculated from the instantaneous amplitude and frequency of every component and fed into the proposed model.Finally,the discriminative features learned by the proposed model are used to detect seizures.Our main innovation is to consider a highly flexible penalization based on Huber loss function,which can set different weights according to the influence of different features on epilepsy detection.Besides,the new model can be solved by proximal alternating direction multiplier method,which can effectively ensure the convergence of the algorithm.The performance of the proposed method is evaluated on three public EEG datasets provided by the Bonn University,Childrens Hospital Boston-Massachusetts Institute of Technology,and Neurological and Sleep Center at Hauz Khas,New Delhi(New Delhi Epilepsy data).The recognition accuracy on these two datasets is 98%and 99.05%,respectively,indicating the application value of the new model.展开更多
The variational calculus of time-scale non-shifted systems includes both the traditional continuous and traditional significant discrete variational calculus.Not only can the combination ofand∇derivatives be beneficia...The variational calculus of time-scale non-shifted systems includes both the traditional continuous and traditional significant discrete variational calculus.Not only can the combination ofand∇derivatives be beneficial to obtaining higher convergence order in numerical analysis,but also it prompts the timescale numerical computational scheme to have good properties,for instance,structure-preserving.In this letter,a structure-preserving algorithm for time-scale non-shifted Hamiltonian systems is proposed.By using the time-scale discrete variational method and calculus theory,and taking a discrete time scale in the variational principle of non-shifted Hamiltonian systems,the corresponding discrete Hamiltonian principle can be obtained.Furthermore,the time-scale discrete Hamilton difference equations,Noether theorem,and the symplectic scheme of discrete Hamiltonian systems are obtained.Finally,taking the Kepler problem and damped oscillator for time-scale non-shifted Hamiltonian systems as examples,they show that the time-scale discrete variational method is a structure-preserving algorithm.The new algorithm not only provides a numerical method for solving time-scale non-shifted dynamic equations but can be calculated with variable step sizes to improve the computational speed.展开更多
This paper investigates the controllability of two time-scale systems using both the time-scale separation model and the slow-fast order reduction model. This work considers the effect of a singular perturbation param...This paper investigates the controllability of two time-scale systems using both the time-scale separation model and the slow-fast order reduction model. This work considers the effect of a singular perturbation parameter on the model transformations to improve the criterion precision. The Maclaurin expansion method and homotopy arithmetic are introduced to obtain t-dependent controllability criteria. Examples indicate that the s-dependent controllability criteria are more accurate and that the controllability of two time-scale systems does not change during model transformations with these more accurate forms.展开更多
A new measurement-based admission control algorithm to support Quality of Service(QoS) demand is proposed for soft real-time applications. In the algorithm, admission test is performed across Multiple Time-Scales (MTS...A new measurement-based admission control algorithm to support Quality of Service(QoS) demand is proposed for soft real-time applications. In the algorithm, admission test is performed across Multiple Time-Scales (MTS) to accurately capture traffic fluctuation on various time-scales. By applying the QoS requirements directly to admission test, the MTS algorithm can properly meet the QoS target and maximize the bandwidth utilization.展开更多
This paper improves and presents an advanced method of the voice conversion system based on Gaussian Mixture Models(GMM) models by changing the time-scale of speech.The Speech Transformation and Representation using A...This paper improves and presents an advanced method of the voice conversion system based on Gaussian Mixture Models(GMM) models by changing the time-scale of speech.The Speech Transformation and Representation using Adaptive Interpolation of weiGHTed spectrum(STRAIGHT) model is adopted to extract the spectrum features,and the GMM models are trained to generate the conversion function.The spectrum features of a source speech will be converted by the conversion function.The time-scale of speech is changed by extracting the converted features and adding to the spectrum.The conversion voice was evaluated by subjective and objective measurements.The results confirm that the transformed speech not only approximates the characteristics of the target speaker,but also more natural and more intelligible.展开更多
S-ALOHA （Slotted ALOHA） random access protocol is a widely used protocol mainly for the transmission of short packets in wireless networks. Most papers consider either an infinite population model where the impact o...S-ALOHA （Slotted ALOHA） random access protocol is a widely used protocol mainly for the transmission of short packets in wireless networks. Most papers consider either an infinite population model where the impact of the backoff protocol cannot be adequately evaluated or a finite population model where the number of nodes is fixed. In this letter, a combination of both models is proposed using the time-scale decomposition technique. This methodology allows to study the system under more realistic conditions where the dynamics of users enter and leaving the system are reflected on the performance of the system as well as the impact of the backoff protocol. Also, it allows studying the system in non-saturation conditions. The proposed methodology divides the analysis in two parts： packet-level and connection-level. This analysis renders suitable results when the time scale of the packet level and connection level statistics is different. On the other hand, when these scales are similar, the proposed methodology is no longer suited.展开更多
基金State Key Development Program for Basic Research of China (No.2006CB200305), the National Natural Sci-ence Foundation of China (No.50376004), and Ph.D. Program Foundation of Ministry of Education of China (No.20030007028).
文摘Presently developed two-phase turbulence models under-predict the gas turbulent fluctuation, because their turbulence modification models cannot fully reflect the effect of particles. In this paper, a two-time-scale dis- sipation model of turbulence modification, developed for the two-phase velocity correlation and for the dissipation rate of gas turbulent kinetic energy, is proposed and used to simulate sudden-expansion and swirling gas-particle flows. The proposed two-time scale model gives better results than the single-time scale model. Besides, a gas tur- bulence augmentation model accounting for the finite-size particle wake effect in the gas Reynolds stress equation is proposed. The proposed turbulence modification models are used to simulate two-phase pipe flows. It can prop- erly predict both turbulence reduction and turbulence enhancement for a certain size of particles observed in ex- periments.
基金Under the auspices of Knowledge Innovation Program of Chinese Academy of Sciences (No. KZCX3-SW-332-01)
文摘The Huolin River is one of the most important water sources for Xianghai wetland, Horqin wetland, and Chaganhu wetland in the western Songnen Plain of Northeast China. The annual runoff series of 46 years at Baiyunhushuo Hydrologic Station, which is located in the middle reaches of the Huolin River, were analyzed by using wavelet analysis. Main objective was to discuss the periodic characteristics of the runoff, and examine the temporal patterns of the Huolin River recharging to the floodplain wetlands in the lower reaches of the river, and the corresponding effects of recharging variation on the environmental evolution of the wetlands. The results show that the annual runoff varied mainly at three time scales. The intensities of periodical signals at different time scales were strongly characterized by local distribution in its time frequency domain. The interdecadal variation at a scale of more than 30yr played a leading role in the temporal pattern ofrnnoffvariation, and at this scale, the runoffat Baiyunhushuo Hydrologic Station varied in turn of flood, draught and flood. Accordingly, the landscape of the floodplain wetlands presented periodic features, especially prominent before the 1990s. Compared with intense human activities, the runoff periodic pattern at middle （10-20yr） and small （1-10yr） scales, which has relatively low energy, exerted unobvious effects on the environmental evolution of the floodplain wetlands, especially after the 1990s.
基金supported by the Fundamental Research Funds for the Central Universities(No.2017MS093)
文摘Considering the complex coupling of multiple energies and the varying load forecasting errors for an integrated energy system(IES),this study proposes a dynamic time-scale scheduling strategy based on long short-term memory(LSTM)and multiple load forecasting errors.This strategy dynamically selects a hybrid timescale which is suitable for a variety of energies for each month.This is obtained by combining the mean absolute percentage error(MAPE)curve of the load forecasting with the error restriction requirements of the dispatcher.Based on the day-ahead scheduling plan,the output of the partial equipment is selectively adjusted at each time-scale to realize multi-energy collaborative optimization and gives full play to the comprehensive advantages of the IES.This is achieved by considering the differences in the response speed for each piece of equipment within the intra-day scheduling.This study uses the IES as an example,and it dynamically determines the time scale of the energy monthly.In addition,this investigation presents a detailed analysis of the output plan of the key equipment to demonstrate the necessity and the advantages of the strategy.
基金support of the European Commission by the Marie Curie IRSES Project GREAT-Geotechnical and Geological Responses to Climate Change:Exchanging Approaches and Technologies on a World-wide Scale(FP7-PEOPLE2013-IRSES-612665)the China Scholarship Council(CSC)Ecole des Ponts Paris Tech for their financial supports
文摘When modeling the soil/atmosphere interaction,it is of paramount importance to determine the net radiation flux.There are two common calculation methods for this purpose.Method 1 relies on use of air temperature,while Method 2 relies on use of both air and soil temperatures.Nowadays,there has been no consensus on the application of these two methods.In this study,the half-hourly data of solar radiation recorded at an experimental embankment are used to calculate the net radiation and long-wave radiation at different time-scales(half-hourly,hourly,and daily) using the two methods.The results show that,compared with Method 2 which has been widely adopted in agronomical,geotechnical and geo-environmental applications.Method 1 is more feasible for its simplicity and accuracy at shorter time-scale.Moreover,in case of longer time-scale,daily for instance,less variations of net radiation and long-wave radiation are obtained,suggesting that no detailed soil temperature variations can be obtained.In other words,shorter time-scales are preferred in determining net radiation flux.
基金Supported by National Natural Science Foundation of China(Grant Nos.11701144,11971149)Henan Province Key and Promotion Special(Science and Technology)Project(Grant No.212102310305).
文摘According to the World Health Organization,about 50 million people worldwide suffer from epilepsy.The detection and treatment of epilepsy face great challenges.Electroencephalogram(EEG)is a significant research object widely used in diagnosis and treatment of epilepsy.In this paper,an adaptive feature learning model for EEG signals is proposed,which combines Huber loss function with adaptive weight penalty term.Firstly,each EEG signal is decomposed by intrinsic time-scale decomposition.Secondly,the statistical index values are calculated from the instantaneous amplitude and frequency of every component and fed into the proposed model.Finally,the discriminative features learned by the proposed model are used to detect seizures.Our main innovation is to consider a highly flexible penalization based on Huber loss function,which can set different weights according to the influence of different features on epilepsy detection.Besides,the new model can be solved by proximal alternating direction multiplier method,which can effectively ensure the convergence of the algorithm.The performance of the proposed method is evaluated on three public EEG datasets provided by the Bonn University,Childrens Hospital Boston-Massachusetts Institute of Technology,and Neurological and Sleep Center at Hauz Khas,New Delhi(New Delhi Epilepsy data).The recognition accuracy on these two datasets is 98%and 99.05%,respectively,indicating the application value of the new model.
基金This work was supported by the National Natural Science Foundation of China(Nos.11972241,11572212)the Natural Science Foundation of Jiangsu Province(No.BK20191454)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.KYCX20_0251).
文摘The variational calculus of time-scale non-shifted systems includes both the traditional continuous and traditional significant discrete variational calculus.Not only can the combination ofand∇derivatives be beneficial to obtaining higher convergence order in numerical analysis,but also it prompts the timescale numerical computational scheme to have good properties,for instance,structure-preserving.In this letter,a structure-preserving algorithm for time-scale non-shifted Hamiltonian systems is proposed.By using the time-scale discrete variational method and calculus theory,and taking a discrete time scale in the variational principle of non-shifted Hamiltonian systems,the corresponding discrete Hamiltonian principle can be obtained.Furthermore,the time-scale discrete Hamilton difference equations,Noether theorem,and the symplectic scheme of discrete Hamiltonian systems are obtained.Finally,taking the Kepler problem and damped oscillator for time-scale non-shifted Hamiltonian systems as examples,they show that the time-scale discrete variational method is a structure-preserving algorithm.The new algorithm not only provides a numerical method for solving time-scale non-shifted dynamic equations but can be calculated with variable step sizes to improve the computational speed.
基金Supported by the National Science Fund for Distinguished Young Scholars(No.60625304)the National Natural Science Foundation of China(No.90716021)the Specialized Research Fund for the Doctoral Program of Higher Education of MOE,China(No.20050003049)
文摘This paper investigates the controllability of two time-scale systems using both the time-scale separation model and the slow-fast order reduction model. This work considers the effect of a singular perturbation parameter on the model transformations to improve the criterion precision. The Maclaurin expansion method and homotopy arithmetic are introduced to obtain t-dependent controllability criteria. Examples indicate that the s-dependent controllability criteria are more accurate and that the controllability of two time-scale systems does not change during model transformations with these more accurate forms.
文摘A new measurement-based admission control algorithm to support Quality of Service(QoS) demand is proposed for soft real-time applications. In the algorithm, admission test is performed across Multiple Time-Scales (MTS) to accurately capture traffic fluctuation on various time-scales. By applying the QoS requirements directly to admission test, the MTS algorithm can properly meet the QoS target and maximize the bandwidth utilization.
基金Supported by the National Natural Science Foundation of China (No. 60872105)the Program for Science & Technology Innovative Research Team of Qing Lan Project in Higher Educational Institutions of Jiangsuthe Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD)
文摘This paper improves and presents an advanced method of the voice conversion system based on Gaussian Mixture Models(GMM) models by changing the time-scale of speech.The Speech Transformation and Representation using Adaptive Interpolation of weiGHTed spectrum(STRAIGHT) model is adopted to extract the spectrum features,and the GMM models are trained to generate the conversion function.The spectrum features of a source speech will be converted by the conversion function.The time-scale of speech is changed by extracting the converted features and adding to the spectrum.The conversion voice was evaluated by subjective and objective measurements.The results confirm that the transformed speech not only approximates the characteristics of the target speaker,but also more natural and more intelligible.
文摘S-ALOHA （Slotted ALOHA） random access protocol is a widely used protocol mainly for the transmission of short packets in wireless networks. Most papers consider either an infinite population model where the impact of the backoff protocol cannot be adequately evaluated or a finite population model where the number of nodes is fixed. In this letter, a combination of both models is proposed using the time-scale decomposition technique. This methodology allows to study the system under more realistic conditions where the dynamics of users enter and leaving the system are reflected on the performance of the system as well as the impact of the backoff protocol. Also, it allows studying the system in non-saturation conditions. The proposed methodology divides the analysis in two parts： packet-level and connection-level. This analysis renders suitable results when the time scale of the packet level and connection level statistics is different. On the other hand, when these scales are similar, the proposed methodology is no longer suited.
