Position-spoofing-based attacks seriously threaten the security of Vehicular Ad Hoc Network(VANET).An effective solution to detect position spoofing is location verification.However,since vehicles move fast and the to...Position-spoofing-based attacks seriously threaten the security of Vehicular Ad Hoc Network(VANET).An effective solution to detect position spoofing is location verification.However,since vehicles move fast and the topology changes quickly in VANET,the static location verification method in Wireless Sensor Network(WSN) is not suitable for VANET.Taking into account the dynamic changing topology of VANET and collusion,we propose a Time-Slice-based Location Verification scheme,named TSLV,to resist position spoofing in VANET.Specifically,TSLV transforms the dynamic topology into static topology by time slice and each time slice corresponds to a verification process.The verifier can implement location verification for the corresponding prover.During the verification process,the verifier first filters out vehicles which provide unreasonably claimed locations,and then uses the Mean Square Error(MSE)-based cluster approach to separate the consistent vehicles by time slice,and uses the consistent set for its verification.In addition,security analysis and simulation show that TSLV can defend against the collusion attack effectively.展开更多
Recently, canopy transpiration （Ec） has been often estimated by xylem sap-flow measurements. However, there is a significant time lag between sap flow measured at the base of the stem and canopy transpiration due to...Recently, canopy transpiration （Ec） has been often estimated by xylem sap-flow measurements. However, there is a significant time lag between sap flow measured at the base of the stem and canopy transpiration due to the capacitive exchange between the transpiration stream and stem water storage. Significant errors will be introduced in canopy conductance （gc） and canopy transpiration estimation if the time lag is neglected. In this study, a cross-correlation analysis was used to quantify the time lag, and the sap flowbased transpiration was measured to pararneterize Jarvistype models of gc and thus to simulate Ec of Populus cathayana using the Penman-Monteith equation. The results indicate that solar radiation （Rs） and vapor pressure deficit （VPD） are not fully coincident with sap flow and have an obvious lag effect; the sap flow lags behind Rs and precedes VPD, and there is a 1-h time shift between Eo and sap flow in the 30-min interval data set. A parameterized Jarvis-type gc model is suitable to predict P. cathayana transpiration and explains more than 80% of the variation observed in go, and the relative error was less than 25%, which shows a preferable simulation effect. The root mean square error （RMSEs） between the predicted and measured Ec were 1.91×10^-3 （with the time lag） and 3.12×10^-3cm h^-1 （without the time lag）. More importantly, Ec simulation precision that incorporates time lag is improved by 6% compared to the results without the time lag, with the mean relative error （MRE） of only 8.32% and the mean absolute error （MAE） of 1.48 × 10^-3 cm h^-1.展开更多
Recent advances in intelligent transportation system allow traffic safety studies to extend from historic data-based analyses to real-time applications. The study presents a new method to predict crash likelihood with...Recent advances in intelligent transportation system allow traffic safety studies to extend from historic data-based analyses to real-time applications. The study presents a new method to predict crash likelihood with traffic data collected by discrete loop detectors as well as the web-crawl weather data. Matched case-control method and support vector machines （SVMs） technique were employed to identify the risk status. The adaptive synthetic over-sampling technique was applied to solve the imbalanced dataset issues. Random forest technique was applied to select the contributing factors and avoid the over-fitting issues. The results indicate that the SVMs classifier could successfully classify 76.32% of the crashes on the test dataset and 87.52% of the crashes on the overall dataset, which were relatively satisfactory compared with the results of the previous studies. Compared with the SVMs classifier without the data, the SVMs classifier with the web-crawl weather data increased the crash prediction accuracy by 1.32% and decreased the false alarm rate by 1.72%, showing the potential value of the massive web weather data. Mean impact value method was employed to evaluate the variable effects, and the results are identical with the results of most of previous studies. The emerging technique based on the discrete traffic data and web weather data proves to be more applicable on real- time safety management on freeways.展开更多
The original temporal clustering analysis (OTCA) is an effective technique for obtaining brain activation maps when the timing and location of the activation are completely unknown, but its deficiency of sensitivity i...The original temporal clustering analysis (OTCA) is an effective technique for obtaining brain activation maps when the timing and location of the activation are completely unknown, but its deficiency of sensitivity is exposed in processing brain activation signal which is relatively weak. The time slice analysis method based on OTCA is proposed considering the weakness of the functional magnetic resonance imaging (fMRI) signal of the rat model. By dividing the stimulation period into several time slices and analyzing each slice to detect the activated pixels respectively after the background removal, the sensitivity is significantly improved. The inhibitory response in the hypothalamus after glucose loading is detected successfully with this method in the experiment on rat. Combined with the OTCA method, the time slice analysis method based on OTCA is effective on detecting when, where and which type of response will happen after stimulation, even if the fMRI signal is weak.展开更多
在低空智联网中,无人机作为空中通信基站、数据传输中继节点和移动网络终端的重要组成部分,凭借其卓越的机动性和适应性,广泛应用于扩展网络覆盖和支持多种业务服务。然而,由于低空智联网面临着网络拓扑动态变化、空域资源稀缺以及多样...在低空智联网中,无人机作为空中通信基站、数据传输中继节点和移动网络终端的重要组成部分,凭借其卓越的机动性和适应性,广泛应用于扩展网络覆盖和支持多种业务服务。然而,由于低空智联网面临着网络拓扑动态变化、空域资源稀缺以及多样化业务需求等挑战,实现有限资源的高效编排和管理仍然是一项艰巨任务。为解决这一问题,通过对无人机网络进行端到端切片,构建满足特定需求的逻辑无人机网络架构。首先,设计了一种分群轨迹预测模型,用于确定分群接入节点的位置,为网络切片的资源预留与优化提供支持。基于此,提出了一种双时间尺度的资源管理框架:在大时间尺度上,采用非线性规划方法将切片重配置问题转化为约束优化问题,优化整体切片效益并合理预留资源;在小时间尺度上,通过针对切片内业务需求的资源调度策略,满足具体业务的传输服务质量(quality of service,QoS)需求。仿真结果表明,该方法增强了低空无人机智联网络在动态环境中的适应性与服务质量,为低空智联网复杂场景下的资源管理和业务保障提供了有效支持。展开更多
Forest losses or gains have long been recognized as critical processes modulating the carbon flux between the biosphere and the atmosphere. Timely, accurate and spatially explicit information on forest disturbance and...Forest losses or gains have long been recognized as critical processes modulating the carbon flux between the biosphere and the atmosphere. Timely, accurate and spatially explicit information on forest disturbance and recovery history is required for assessing the effectiveness of existing forest management. The major objectives of our research focused on testing the mapping efficacy of the vegetation change tracker （VCT） model over a forested area in China. We used a new version of VCT algorithm built upon the Landsat time series stacks （LTSS）. The LTSS consisted of yearly image acquisitions to map forest disturbance history from 1987 to 2011 over the Ning-Zhen Mountains, Jiangsu Province of east China. The LTSS consisted of TM and ETM＋ scenes with different projec- tions due to distinct data sources （Beijing remote sensing ground station and the USGS EROS Center）. The valida- tion results of the disturbance year maps showed that most spatial agreement measures ranged from 70 to 86 %, comparable with the VCT accuracies reported for many places in USA. Very low accuracies were identified in 1995 （38.3 %） and 1992 （56.2 %） in the current analysis. These resulted from the insensitivity of the VCT algorithm to detect low intensity disturbances and also from the mis- registration errors of the image pairs. Major forest distur- bance types existing in our study area were identified as agricultural expansion （39.8 %）, urbanization （24.9 %）, forest management practice （19.3 %）, and mining （12.8 %）. In general, there was a gradual decreasing trend in forest cover throughout this region, caused principally by China＇s economic, demographic, environmental and political policies and decisions, as well as some weather events. While VCT has largely been used to assess long term changes and trends in the USA, it has great potential for assessing landscape level change elsewhere throughout the world.展开更多
March is a right party time for friends to get together to enjoy the smell of early spring. Moreover, people would like to take off the thick winter coat to showcase their colorful attitude towards the warm spring sun...March is a right party time for friends to get together to enjoy the smell of early spring. Moreover, people would like to take off the thick winter coat to showcase their colorful attitude towards the warm spring sunshine. Here, an annual fashion feast in Beijing not only could provide you a visual inspiration of trend, but also would tell you what’s the most "in" factors in the coming season.展开更多
基金supported by National Natural Science Foundation of China under Grant No.60972036
文摘Position-spoofing-based attacks seriously threaten the security of Vehicular Ad Hoc Network(VANET).An effective solution to detect position spoofing is location verification.However,since vehicles move fast and the topology changes quickly in VANET,the static location verification method in Wireless Sensor Network(WSN) is not suitable for VANET.Taking into account the dynamic changing topology of VANET and collusion,we propose a Time-Slice-based Location Verification scheme,named TSLV,to resist position spoofing in VANET.Specifically,TSLV transforms the dynamic topology into static topology by time slice and each time slice corresponds to a verification process.The verifier can implement location verification for the corresponding prover.During the verification process,the verifier first filters out vehicles which provide unreasonably claimed locations,and then uses the Mean Square Error(MSE)-based cluster approach to separate the consistent vehicles by time slice,and uses the consistent set for its verification.In addition,security analysis and simulation show that TSLV can defend against the collusion attack effectively.
基金supported by the Qinghai province natural science foundation project(2015-ZJ-902)the Qinghai province science and technology plan program(2014-NK-A4-4)
文摘Recently, canopy transpiration （Ec） has been often estimated by xylem sap-flow measurements. However, there is a significant time lag between sap flow measured at the base of the stem and canopy transpiration due to the capacitive exchange between the transpiration stream and stem water storage. Significant errors will be introduced in canopy conductance （gc） and canopy transpiration estimation if the time lag is neglected. In this study, a cross-correlation analysis was used to quantify the time lag, and the sap flowbased transpiration was measured to pararneterize Jarvistype models of gc and thus to simulate Ec of Populus cathayana using the Penman-Monteith equation. The results indicate that solar radiation （Rs） and vapor pressure deficit （VPD） are not fully coincident with sap flow and have an obvious lag effect; the sap flow lags behind Rs and precedes VPD, and there is a 1-h time shift between Eo and sap flow in the 30-min interval data set. A parameterized Jarvis-type gc model is suitable to predict P. cathayana transpiration and explains more than 80% of the variation observed in go, and the relative error was less than 25%, which shows a preferable simulation effect. The root mean square error （RMSEs） between the predicted and measured Ec were 1.91×10^-3 （with the time lag） and 3.12×10^-3cm h^-1 （without the time lag）. More importantly, Ec simulation precision that incorporates time lag is improved by 6% compared to the results without the time lag, with the mean relative error （MRE） of only 8.32% and the mean absolute error （MAE） of 1.48 × 10^-3 cm h^-1.
基金supported by the National Natural Science Foundation (71301119)the Shanghai Natural Science Foundation (12ZR1434100)
文摘Recent advances in intelligent transportation system allow traffic safety studies to extend from historic data-based analyses to real-time applications. The study presents a new method to predict crash likelihood with traffic data collected by discrete loop detectors as well as the web-crawl weather data. Matched case-control method and support vector machines （SVMs） technique were employed to identify the risk status. The adaptive synthetic over-sampling technique was applied to solve the imbalanced dataset issues. Random forest technique was applied to select the contributing factors and avoid the over-fitting issues. The results indicate that the SVMs classifier could successfully classify 76.32% of the crashes on the test dataset and 87.52% of the crashes on the overall dataset, which were relatively satisfactory compared with the results of the previous studies. Compared with the SVMs classifier without the data, the SVMs classifier with the web-crawl weather data increased the crash prediction accuracy by 1.32% and decreased the false alarm rate by 1.72%, showing the potential value of the massive web weather data. Mean impact value method was employed to evaluate the variable effects, and the results are identical with the results of most of previous studies. The emerging technique based on the discrete traffic data and web weather data proves to be more applicable on real- time safety management on freeways.
基金the National Natural Science Foundation of China (30370432)
文摘The original temporal clustering analysis (OTCA) is an effective technique for obtaining brain activation maps when the timing and location of the activation are completely unknown, but its deficiency of sensitivity is exposed in processing brain activation signal which is relatively weak. The time slice analysis method based on OTCA is proposed considering the weakness of the functional magnetic resonance imaging (fMRI) signal of the rat model. By dividing the stimulation period into several time slices and analyzing each slice to detect the activated pixels respectively after the background removal, the sensitivity is significantly improved. The inhibitory response in the hypothalamus after glucose loading is detected successfully with this method in the experiment on rat. Combined with the OTCA method, the time slice analysis method based on OTCA is effective on detecting when, where and which type of response will happen after stimulation, even if the fMRI signal is weak.
文摘在低空智联网中,无人机作为空中通信基站、数据传输中继节点和移动网络终端的重要组成部分,凭借其卓越的机动性和适应性,广泛应用于扩展网络覆盖和支持多种业务服务。然而,由于低空智联网面临着网络拓扑动态变化、空域资源稀缺以及多样化业务需求等挑战,实现有限资源的高效编排和管理仍然是一项艰巨任务。为解决这一问题,通过对无人机网络进行端到端切片,构建满足特定需求的逻辑无人机网络架构。首先,设计了一种分群轨迹预测模型,用于确定分群接入节点的位置,为网络切片的资源预留与优化提供支持。基于此,提出了一种双时间尺度的资源管理框架:在大时间尺度上,采用非线性规划方法将切片重配置问题转化为约束优化问题,优化整体切片效益并合理预留资源;在小时间尺度上,通过针对切片内业务需求的资源调度策略,满足具体业务的传输服务质量(quality of service,QoS)需求。仿真结果表明,该方法增强了低空无人机智联网络在动态环境中的适应性与服务质量,为低空智联网复杂场景下的资源管理和业务保障提供了有效支持。
基金funded by the following grants:the Forestry Public Welfare Project(201304208)the‘‘948’’Project sponsored by the State Forestry Administration(SFA)of China(2014-4-25)+4 种基金the National Natural Science Foundation of China(31270587,31100414)the PAPD(Priority Academic Program Development)of Jiangsu provincial universitiesperformed while the lead author held a scholarship sponsored the CSC(China Scholarship Council)(201208320553)at the department of Geographical Sciences,University of Marylandawardee of the 2012 Youth Backbone Teachers Support Plan of Jiangsu Provincethe 2012 Youth Talents Support Plan of Nanjing Forestry University
文摘Forest losses or gains have long been recognized as critical processes modulating the carbon flux between the biosphere and the atmosphere. Timely, accurate and spatially explicit information on forest disturbance and recovery history is required for assessing the effectiveness of existing forest management. The major objectives of our research focused on testing the mapping efficacy of the vegetation change tracker （VCT） model over a forested area in China. We used a new version of VCT algorithm built upon the Landsat time series stacks （LTSS）. The LTSS consisted of yearly image acquisitions to map forest disturbance history from 1987 to 2011 over the Ning-Zhen Mountains, Jiangsu Province of east China. The LTSS consisted of TM and ETM＋ scenes with different projec- tions due to distinct data sources （Beijing remote sensing ground station and the USGS EROS Center）. The valida- tion results of the disturbance year maps showed that most spatial agreement measures ranged from 70 to 86 %, comparable with the VCT accuracies reported for many places in USA. Very low accuracies were identified in 1995 （38.3 %） and 1992 （56.2 %） in the current analysis. These resulted from the insensitivity of the VCT algorithm to detect low intensity disturbances and also from the mis- registration errors of the image pairs. Major forest distur- bance types existing in our study area were identified as agricultural expansion （39.8 %）, urbanization （24.9 %）, forest management practice （19.3 %）, and mining （12.8 %）. In general, there was a gradual decreasing trend in forest cover throughout this region, caused principally by China＇s economic, demographic, environmental and political policies and decisions, as well as some weather events. While VCT has largely been used to assess long term changes and trends in the USA, it has great potential for assessing landscape level change elsewhere throughout the world.
文摘March is a right party time for friends to get together to enjoy the smell of early spring. Moreover, people would like to take off the thick winter coat to showcase their colorful attitude towards the warm spring sunshine. Here, an annual fashion feast in Beijing not only could provide you a visual inspiration of trend, but also would tell you what’s the most "in" factors in the coming season.
