Failures are normal rather than exceptional in the cloud computing environments. To improve system avai- lability, replicating the popular data to multiple suitable locations is an advisable choice, as users can acces...Failures are normal rather than exceptional in the cloud computing environments. To improve system avai- lability, replicating the popular data to multiple suitable locations is an advisable choice, as users can access the data from a nearby site. This is, however, not the case for replicas which must have a fixed number of copies on several locations. How to decide a reasonable number and right locations for replicas has become a challenge in the cloud computing. In this paper, a dynamic data replication strategy is put forward with a brief survey of replication strategy suitable for distributed computing environments. It includes： 1） analyzing and modeling the relationship between system availability and the number of replicas; 2） evaluating and identifying the popular data and triggering a replication operation when the popularity data passes a dynamic threshold; 3） calculating a suitable number of copies to meet a reasonable system byte effective rate requirement and placing replicas among data nodes in a balanced way; 4） designing the dynamic data replication algorithm in a cloud. Experimental results demonstrate the efficiency and effectiveness of the improved system brought by the proposed strategy in a cloud.展开更多
Soil water is strongly affected by land use/cover in the Loess Plateau in China. Water stored in thick loessal soils is one of the most important resources regulating vegetation growth. However, soil water in the deep...Soil water is strongly affected by land use/cover in the Loess Plateau in China. Water stored in thick loessal soils is one of the most important resources regulating vegetation growth. However, soil water in the deep loess proifle, which is critical for maintaining the function of the“soil water pool”is rarely studied because deep proifle soil samples are dififcult to collect. In this study, four experimental plots were established in 2005 to represent different farming systems on the Changwu Tableland：fallow land, fertilized cropland, unfertilized cropland, and continuous alfalfa. The soil water content in the 15-m-deep loess proifles was monitored continuously from 2007 to 2012 with the neutron probe technique. The results showed that temporal variations in soil water proifles differed among the four farming systems. Under fallow land, the soil water content increased gradually over time, ifrst in the surface layers and later in the deep soil layers. In contrast, the soil water content decreased gradually under continuous alfalfa. The distributions of soil water in deep soil layers under both fertilized and unfertilized cropland were relatively stable over time. Thus farming system signiifcantly affected soil water content. Seven years after the start of the experiment, the soil water contents in the 15-m-deep proifles averaged 23.4%under fallow land, 20.3%under fertilized cropland, 21.6%under unfertilized cropland, and 16.0%under continuous alfalfa. Compared to measurements at the start of the experiment, both fallow land and unfertilized cropland increased soil water storage in the 15-m loess proifles. In contrast, continuous alfalfa reduced soil water storage. Fertilized cropland has no signiifcant effect on soil water storage. These results suggest that deep soil water can be replenished under the fallow and unfertilized farming systems. Dry soil layers （i.e., those which have soil water content less than the stable ifeld water capacity） in the subsoil of the Changwu Tableland region can be class展开更多
In the past decade,dramatic progress has been made in the field of machine learning.This paper explores the possibility of applying deep learning in power system state estimation.Traditionally,physics-based models are...In the past decade,dramatic progress has been made in the field of machine learning.This paper explores the possibility of applying deep learning in power system state estimation.Traditionally,physics-based models are used including weighted least square(WLS)or weighted least absolute value(WLAV).These models typically consider a single snapshot of the system without capturing temporal correlations of system states.In this paper,a physics-guided deep learning(PGDL)method is proposed.Specifically,inspired by autoencoders,deep neural networks(DNNs)are used to learn the temporal correlations.The estimated system states from DNNs are then checked against physics laws by running through a set of power flow equations.Hence,the proposed PGDL is both data-driven and physics-guided.The accuracy and robustness of the proposed PGDL method are compared with traditional methods in standard IEEE cases.Simulations show promising results and the applicability is further discussed.展开更多
Glacier area changes in the Qangtang Plateau are analyzed during 1970-2000 using air photos,relevant photogrammetric maps and satellite images based on the multi-temporal grid method.The results indicate that the melt...Glacier area changes in the Qangtang Plateau are analyzed during 1970-2000 using air photos,relevant photogrammetric maps and satellite images based on the multi-temporal grid method.The results indicate that the melting of glaciers accelerated,only a few of glaciers in an advancing state during 1970-2000 in the whole Qangtang Plateau.However,the glaciers seemed still more stable in the study area than in most areas of western China.We estimate that glacier retreat was likely due to air temperature warming during 1970-2000 in the Qangtang Plateau.Furthermore,the functional model of glacier system is applied to study climate sensitivity of glacier area changes,which indicates that glacier lifespan mainly depends on the heating rate,secondly the precipitation,and precipitation increasing can slow down glacier retreat and make glacier lifespan prolonged.展开更多
Compared to 3D object detection using a single camera,multiple cameras can overcome some limitations on field-of-view,occlusion,and low detection confidence.This study employs multiple surveillance cameras and develop...Compared to 3D object detection using a single camera,multiple cameras can overcome some limitations on field-of-view,occlusion,and low detection confidence.This study employs multiple surveillance cameras and develops a cooperative 3D object detection and tracking framework by incorporating temporal and spatial information.The framework consists of a 3D vehicle detection model,cooperatively spatial-temporal relation scheme,and heuristic camera constellation method.Specifically,the proposed cross-camera association scheme combines the geometric relationship between multiple cameras and objects in corresponding detections.The spatial-temporal method is designed to associate vehicles between different points of view at a single timestamp and fulfill vehicle tracking in the time aspect.The proposed framework is evaluated based on a synthetic cooperative dataset and shows high reliability,where the cooperative perception can recall more than 66%of the trajectory instead of 11%for single-point sensing.This could contribute to full-range surveillance for intelligent transportation systems.展开更多
时间模式是一组正交的波包模式,可用来表征时域多模量子光场,为量子系统的描述提供一个可选择的理论框架.基于输入种子光诱导的受激拉曼散射(stimulated Raman scattering,SRS)系统,将输出的斯托克斯(Stokes)光场作为下一过程的输入种...时间模式是一组正交的波包模式,可用来表征时域多模量子光场,为量子系统的描述提供一个可选择的理论框架.基于输入种子光诱导的受激拉曼散射(stimulated Raman scattering,SRS)系统,将输出的斯托克斯(Stokes)光场作为下一过程的输入种子光场,进而实现连续迭代受激拉曼散射的过程;固定泵浦光场为高斯波形和超高斯波形,分别研究了在多种不同结构的高斯波形种子光输入的情形下,输出斯托克斯光场的时域波形演化特性,得到了不同波形种子光注入通过迭代会得到相同的稳定波形输出,而输出光场波形的时间半高全宽(full-width at the half of the maximum,FWHM)依赖于泵浦光场;运用施密特(Schmidt)模式分解,数值研究了最终稳定输出的斯托克斯光场时间模式特性,得到了稳定输出的斯托克斯光场本征值都集中在基模.该光场时间模式特性的研究,为进一步开发和利用时间模式这一量子资源提供了理论指导与实验参考.展开更多
基金Supported by the National Natural Science Foundation of China under Grant Nos. 61070162, 71071028 and 70931001the Specialized Research Fund for the Doctoral Program of Higher Education of China under Grant Nos. 20110042110024 and 20100042110025the Fundamental Research Funds for the Central Universities of China under Grant Nos. N100604012, N090504003 and N090504006
文摘Failures are normal rather than exceptional in the cloud computing environments. To improve system avai- lability, replicating the popular data to multiple suitable locations is an advisable choice, as users can access the data from a nearby site. This is, however, not the case for replicas which must have a fixed number of copies on several locations. How to decide a reasonable number and right locations for replicas has become a challenge in the cloud computing. In this paper, a dynamic data replication strategy is put forward with a brief survey of replication strategy suitable for distributed computing environments. It includes： 1） analyzing and modeling the relationship between system availability and the number of replicas; 2） evaluating and identifying the popular data and triggering a replication operation when the popularity data passes a dynamic threshold; 3） calculating a suitable number of copies to meet a reasonable system byte effective rate requirement and placing replicas among data nodes in a balanced way; 4） designing the dynamic data replication algorithm in a cloud. Experimental results demonstrate the efficiency and effectiveness of the improved system brought by the proposed strategy in a cloud.
基金funded by the National Natural Science Foundation of China (41171033,51179161 and 41101025)
文摘Soil water is strongly affected by land use/cover in the Loess Plateau in China. Water stored in thick loessal soils is one of the most important resources regulating vegetation growth. However, soil water in the deep loess proifle, which is critical for maintaining the function of the“soil water pool”is rarely studied because deep proifle soil samples are dififcult to collect. In this study, four experimental plots were established in 2005 to represent different farming systems on the Changwu Tableland：fallow land, fertilized cropland, unfertilized cropland, and continuous alfalfa. The soil water content in the 15-m-deep loess proifles was monitored continuously from 2007 to 2012 with the neutron probe technique. The results showed that temporal variations in soil water proifles differed among the four farming systems. Under fallow land, the soil water content increased gradually over time, ifrst in the surface layers and later in the deep soil layers. In contrast, the soil water content decreased gradually under continuous alfalfa. The distributions of soil water in deep soil layers under both fertilized and unfertilized cropland were relatively stable over time. Thus farming system signiifcantly affected soil water content. Seven years after the start of the experiment, the soil water contents in the 15-m-deep proifles averaged 23.4%under fallow land, 20.3%under fertilized cropland, 21.6%under unfertilized cropland, and 16.0%under continuous alfalfa. Compared to measurements at the start of the experiment, both fallow land and unfertilized cropland increased soil water storage in the 15-m loess proifles. In contrast, continuous alfalfa reduced soil water storage. Fertilized cropland has no signiifcant effect on soil water storage. These results suggest that deep soil water can be replenished under the fallow and unfertilized farming systems. Dry soil layers （i.e., those which have soil water content less than the stable ifeld water capacity） in the subsoil of the Changwu Tableland region can be class
文摘In the past decade,dramatic progress has been made in the field of machine learning.This paper explores the possibility of applying deep learning in power system state estimation.Traditionally,physics-based models are used including weighted least square(WLS)or weighted least absolute value(WLAV).These models typically consider a single snapshot of the system without capturing temporal correlations of system states.In this paper,a physics-guided deep learning(PGDL)method is proposed.Specifically,inspired by autoencoders,deep neural networks(DNNs)are used to learn the temporal correlations.The estimated system states from DNNs are then checked against physics laws by running through a set of power flow equations.Hence,the proposed PGDL is both data-driven and physics-guided.The accuracy and robustness of the proposed PGDL method are compared with traditional methods in standard IEEE cases.Simulations show promising results and the applicability is further discussed.
基金supported by the National Natural Science Foundation of China (Nos.40871043,40801025)the Project of National Scientific Basic Special Fund on the Ministry of Science and Technology of China (No.2006FY110200)the Key Construction Disciplines of Hunan Province (No.40652001)
文摘Glacier area changes in the Qangtang Plateau are analyzed during 1970-2000 using air photos,relevant photogrammetric maps and satellite images based on the multi-temporal grid method.The results indicate that the melting of glaciers accelerated,only a few of glaciers in an advancing state during 1970-2000 in the whole Qangtang Plateau.However,the glaciers seemed still more stable in the study area than in most areas of western China.We estimate that glacier retreat was likely due to air temperature warming during 1970-2000 in the Qangtang Plateau.Furthermore,the functional model of glacier system is applied to study climate sensitivity of glacier area changes,which indicates that glacier lifespan mainly depends on the heating rate,secondly the precipitation,and precipitation increasing can slow down glacier retreat and make glacier lifespan prolonged.
基金the National Natural Science Foundation of China(No.61873167)the Automotive Industry Science and Technology Development Foundation of Shanghai(No.1904)。
文摘Compared to 3D object detection using a single camera,multiple cameras can overcome some limitations on field-of-view,occlusion,and low detection confidence.This study employs multiple surveillance cameras and develops a cooperative 3D object detection and tracking framework by incorporating temporal and spatial information.The framework consists of a 3D vehicle detection model,cooperatively spatial-temporal relation scheme,and heuristic camera constellation method.Specifically,the proposed cross-camera association scheme combines the geometric relationship between multiple cameras and objects in corresponding detections.The spatial-temporal method is designed to associate vehicles between different points of view at a single timestamp and fulfill vehicle tracking in the time aspect.The proposed framework is evaluated based on a synthetic cooperative dataset and shows high reliability,where the cooperative perception can recall more than 66%of the trajectory instead of 11%for single-point sensing.This could contribute to full-range surveillance for intelligent transportation systems.
文摘时间模式是一组正交的波包模式,可用来表征时域多模量子光场,为量子系统的描述提供一个可选择的理论框架.基于输入种子光诱导的受激拉曼散射(stimulated Raman scattering,SRS)系统,将输出的斯托克斯(Stokes)光场作为下一过程的输入种子光场,进而实现连续迭代受激拉曼散射的过程;固定泵浦光场为高斯波形和超高斯波形,分别研究了在多种不同结构的高斯波形种子光输入的情形下,输出斯托克斯光场的时域波形演化特性,得到了不同波形种子光注入通过迭代会得到相同的稳定波形输出,而输出光场波形的时间半高全宽(full-width at the half of the maximum,FWHM)依赖于泵浦光场;运用施密特(Schmidt)模式分解,数值研究了最终稳定输出的斯托克斯光场时间模式特性,得到了稳定输出的斯托克斯光场本征值都集中在基模.该光场时间模式特性的研究,为进一步开发和利用时间模式这一量子资源提供了理论指导与实验参考.
