Aims Recent mechanistic explanations for community assembly focus on the debates surrounding niche-based deterministic and dispersalbased stochastic models.This body of work has emphasized the importance of both habit...Aims Recent mechanistic explanations for community assembly focus on the debates surrounding niche-based deterministic and dispersalbased stochastic models.This body of work has emphasized the importance of both habitat filtering and dispersal limitation,and many of these works have utilized the assumption of species spatial independence to simplify the complexity of the spatial modeling in natural communities when given dispersal limitation and/or habitat filtering.One potential drawback of this simplification is that it does not consider species interactions and how they may influence the spatial distribution of species,phylogenetic and functional diversity.Here,we assess the validity of the assumption of species spatial independence using data from a subtropical forest plot in southeastern China.Methods We use the four most commonly employed spatial statistical models—the homogeneous Poisson process representing pure random effect,the heterogeneous Poisson process for the effect of habitat heterogeneity,the homogenous Thomas process for sole dispersal limitation and the heterogeneous Thomas process for joint effect of habitat heterogeneity and dispersal limitation—to investigate the contribution of different mechanisms in shaping the species,phylogenetic and functional structures of communities.Important Findings Our evidence from species,phylogenetic and functional diversity demonstrates that the habitat filtering and/or dispersal-based models perform well and the assumption of species spatial independence is relatively valid at larger scales(50×50 m).Conversely,at local scales(10×10 and 20×20 m),the models often fail to predict the species,phylogenetic and functional diversity,suggesting that the assumption of species spatial independence is invalid and that biotic interactions are increasingly important at these spatial scales.展开更多
Several software reliability growth models （SRGM） have been developed to monitor the reliability growth during the testing phase of software development. In most of the existing research available in the literatures...Several software reliability growth models （SRGM） have been developed to monitor the reliability growth during the testing phase of software development. In most of the existing research available in the literatures, it is considered that a similar testing effort is required on each debugging effort. However, in practice, different types of faults may require different amounts of testing efforts for their detection and removal. Consequently, faults are classified into three categories on the basis of severity： simple, hard and complex. This categorization may be extended to r type of faults on the basis of severity. Although some existing research in the literatures has incorporated this concept that fault removal rate （FRR） is different for different types of faults, they assume that the FRR remains constant during the overall testing period. On the contrary, it has been observed that as testing progresses, FRR changes due to changing testing strategy, skill, environment and personnel resources. In this paper, a general discrete SRGM is proposed for errors of different severity in software systems using the change-point concept. Then, the models are formulated for two particular environments. The models were validated on two real-life data sets. The results show better fit and wider applicability of the proposed models as to different types of failure datasets.展开更多
Accurate classification and prediction of future traffic conditions are essential for developing effective strategies for congestion mitigation on the highway systems. Speed distribution is one of the traffic stream p...Accurate classification and prediction of future traffic conditions are essential for developing effective strategies for congestion mitigation on the highway systems. Speed distribution is one of the traffic stream parameters, which has been used to quantify the traffic conditions. Previous studies have shown that multi-modal probability distribution of speeds gives excellent results when simultaneously evaluating congested and free-flow traffic conditions. However, most of these previous analytical studies do not incorporate the influencing factors in characterizing these conditions. This study evaluates the impact of traffic occupancy on the multi-state speed distribution using the Bayesian Dirichlet Process Mixtures of Generalized Linear Models (DPM-GLM). Further, the study estimates the speed cut-point values of traffic states, which separate them into homogeneous groups using Bayesian change-point detection (BCD) technique. The study used 2015 archived one-year traffic data collected on Florida’s Interstate 295 freeway corridor. Information criteria results revealed three traffic states, which were identified as free-flow, transitional flow condition (congestion onset/offset), and the congested condition. The findings of the DPM-GLM indicated that in all estimated states, the traffic speed decreases when traffic occupancy increases. Comparison of the influence of traffic occupancy between traffic states showed that traffic occupancy has more impact on the free-flow and the congested state than on the transitional flow condition. With respect to estimating the threshold speed value, the results of the BCD model revealed promising findings in characterizing levels of traffic congestion.展开更多
数值天气预报是天气预报业务和防灾减灾的核心科技。中国数值天气预报研究和业务应用一直受到高度重视,在基础理论研究、关键技术突破和业务系统研制方面取得了有广泛国际影响力的研究成果。在回顾中国数值天气预报技术及业务系统发展...数值天气预报是天气预报业务和防灾减灾的核心科技。中国数值天气预报研究和业务应用一直受到高度重视,在基础理论研究、关键技术突破和业务系统研制方面取得了有广泛国际影响力的研究成果。在回顾中国数值天气预报技术及业务系统发展基础上,重点综述中国自主发展的GRAPES(Global Regional Assimilation and PrEdiction System)和YHGSM(YinHe Global Spectral Model)两大业务预报系统的重要科技进展。GRAPES在模式动力框架、四维变分资料同化、卫星资料同化技术、雷达资料同化应用、集合预报和云物理过程等方面实现了技术突破,建立了无缝隙的、包含确定性预报和集合预报系统的中国气象局数值天气预报业务体系。YHGSM持续走谱模式发展路线,突破了干空气质量守恒全球大气谱模式、集合四维变分资料同化、海-陆-气耦合集合预报等技术,建立了以高分辨率全球中期和月延伸数值预报系统为核心的数值预报体系。军队和地方自主研发的数值天气预报系统是长期坚持既定科学技术方向、学术研究和业务研制紧密结合的结果。展开更多
Historical evidence indicates that dust storms of considerable ferocity often wreak havoc, posing a genuine threat to the climatic and societal equilibrium of a place. A systematic study, with emphasis on the modeling...Historical evidence indicates that dust storms of considerable ferocity often wreak havoc, posing a genuine threat to the climatic and societal equilibrium of a place. A systematic study, with emphasis on the modeling and forecasting aspects, thus, becomes imperative, so that efficient measures can be promptly undertaken to cushion the effect of such an unforeseen calamity. The present work intends to discover a suitable ARIMA model using dust storm data from northern China from March 1954 to April 2002, provided by Zhou and Zhang (2003), thereby extending the idea of empirical recurrence rate (ERR) developed by Ho (2008), to model the temporal trend of such sand dust storms. In particular we show that the ERR time series is endowed with the following characteristics: 1) it is a potent surrogate for a point process, 2) it is capable of taking advantage of the well developed and powerful time series modeling tools and 3) it can generate reliable forecasts, with which we can retrieve the corresponding mean number of strong sand dust storms. A simulation study is conducted prior to the actual fitting, to justify the applicability of the proposed technique.展开更多
无线信道建模对于理解、设计和优化无线通信系统具有重要意义,是无线通信领域中不可或缺的一部分。为了满足车联网(vehicle to everything,V2X)环境中的通信需求,研究空间中障碍物的分布对信道衰落特性的影响,本文提出了一种新的随机散...无线信道建模对于理解、设计和优化无线通信系统具有重要意义,是无线通信领域中不可或缺的一部分。为了满足车联网(vehicle to everything,V2X)环境中的通信需求,研究空间中障碍物的分布对信道衰落特性的影响,本文提出了一种新的随机散射簇生成算法,即通过把Matérn硬核点过程和泊松簇过程相结合来模拟真实V2X信道中的障碍物。在算法中,依据真实环境障碍物的方位设置散射簇的坐标位置,根据周围障碍物密度合理设置簇内散射点数量。利用传播图论进行仿真,考虑直射路径和单跳散射路径,基于信道冲激响应(channel impulse response,CIR)分别研究了功率延迟分布(power delay profile,PDP)和多普勒功率谱密度(Doppler power spectrum density,DPSD),并分析了不同移动轨迹下的均方根(root mean square,RMS)时延扩展的累计分布函数(cumulative distribution function,CDF),以及莱斯K因子的分布特性和角度功率谱(power angular spectrum,PAS)的分布。本文研究验证得到,所提出的模型有助于分析车辆-基础设施(vehicle to infrastructure,V2I)通信场景下的时域非平稳特性,为V2X通信系统的设计和优化提供了重要参考。展开更多
基金NSFC grant of National Natural Science Foundation of China(31170401)Dimensions of biodiversity grant of Natural Science Fundation(NSF 1046113)Natural Science Foundation of Zhejiang Province(Y5100361).
文摘Aims Recent mechanistic explanations for community assembly focus on the debates surrounding niche-based deterministic and dispersalbased stochastic models.This body of work has emphasized the importance of both habitat filtering and dispersal limitation,and many of these works have utilized the assumption of species spatial independence to simplify the complexity of the spatial modeling in natural communities when given dispersal limitation and/or habitat filtering.One potential drawback of this simplification is that it does not consider species interactions and how they may influence the spatial distribution of species,phylogenetic and functional diversity.Here,we assess the validity of the assumption of species spatial independence using data from a subtropical forest plot in southeastern China.Methods We use the four most commonly employed spatial statistical models—the homogeneous Poisson process representing pure random effect,the heterogeneous Poisson process for the effect of habitat heterogeneity,the homogenous Thomas process for sole dispersal limitation and the heterogeneous Thomas process for joint effect of habitat heterogeneity and dispersal limitation—to investigate the contribution of different mechanisms in shaping the species,phylogenetic and functional structures of communities.Important Findings Our evidence from species,phylogenetic and functional diversity demonstrates that the habitat filtering and/or dispersal-based models perform well and the assumption of species spatial independence is relatively valid at larger scales(50×50 m).Conversely,at local scales(10×10 and 20×20 m),the models often fail to predict the species,phylogenetic and functional diversity,suggesting that the assumption of species spatial independence is invalid and that biotic interactions are increasingly important at these spatial scales.
文摘Several software reliability growth models （SRGM） have been developed to monitor the reliability growth during the testing phase of software development. In most of the existing research available in the literatures, it is considered that a similar testing effort is required on each debugging effort. However, in practice, different types of faults may require different amounts of testing efforts for their detection and removal. Consequently, faults are classified into three categories on the basis of severity： simple, hard and complex. This categorization may be extended to r type of faults on the basis of severity. Although some existing research in the literatures has incorporated this concept that fault removal rate （FRR） is different for different types of faults, they assume that the FRR remains constant during the overall testing period. On the contrary, it has been observed that as testing progresses, FRR changes due to changing testing strategy, skill, environment and personnel resources. In this paper, a general discrete SRGM is proposed for errors of different severity in software systems using the change-point concept. Then, the models are formulated for two particular environments. The models were validated on two real-life data sets. The results show better fit and wider applicability of the proposed models as to different types of failure datasets.
文摘Accurate classification and prediction of future traffic conditions are essential for developing effective strategies for congestion mitigation on the highway systems. Speed distribution is one of the traffic stream parameters, which has been used to quantify the traffic conditions. Previous studies have shown that multi-modal probability distribution of speeds gives excellent results when simultaneously evaluating congested and free-flow traffic conditions. However, most of these previous analytical studies do not incorporate the influencing factors in characterizing these conditions. This study evaluates the impact of traffic occupancy on the multi-state speed distribution using the Bayesian Dirichlet Process Mixtures of Generalized Linear Models (DPM-GLM). Further, the study estimates the speed cut-point values of traffic states, which separate them into homogeneous groups using Bayesian change-point detection (BCD) technique. The study used 2015 archived one-year traffic data collected on Florida’s Interstate 295 freeway corridor. Information criteria results revealed three traffic states, which were identified as free-flow, transitional flow condition (congestion onset/offset), and the congested condition. The findings of the DPM-GLM indicated that in all estimated states, the traffic speed decreases when traffic occupancy increases. Comparison of the influence of traffic occupancy between traffic states showed that traffic occupancy has more impact on the free-flow and the congested state than on the transitional flow condition. With respect to estimating the threshold speed value, the results of the BCD model revealed promising findings in characterizing levels of traffic congestion.
文摘数值天气预报是天气预报业务和防灾减灾的核心科技。中国数值天气预报研究和业务应用一直受到高度重视,在基础理论研究、关键技术突破和业务系统研制方面取得了有广泛国际影响力的研究成果。在回顾中国数值天气预报技术及业务系统发展基础上,重点综述中国自主发展的GRAPES(Global Regional Assimilation and PrEdiction System)和YHGSM(YinHe Global Spectral Model)两大业务预报系统的重要科技进展。GRAPES在模式动力框架、四维变分资料同化、卫星资料同化技术、雷达资料同化应用、集合预报和云物理过程等方面实现了技术突破,建立了无缝隙的、包含确定性预报和集合预报系统的中国气象局数值天气预报业务体系。YHGSM持续走谱模式发展路线,突破了干空气质量守恒全球大气谱模式、集合四维变分资料同化、海-陆-气耦合集合预报等技术,建立了以高分辨率全球中期和月延伸数值预报系统为核心的数值预报体系。军队和地方自主研发的数值天气预报系统是长期坚持既定科学技术方向、学术研究和业务研制紧密结合的结果。
文摘Historical evidence indicates that dust storms of considerable ferocity often wreak havoc, posing a genuine threat to the climatic and societal equilibrium of a place. A systematic study, with emphasis on the modeling and forecasting aspects, thus, becomes imperative, so that efficient measures can be promptly undertaken to cushion the effect of such an unforeseen calamity. The present work intends to discover a suitable ARIMA model using dust storm data from northern China from March 1954 to April 2002, provided by Zhou and Zhang (2003), thereby extending the idea of empirical recurrence rate (ERR) developed by Ho (2008), to model the temporal trend of such sand dust storms. In particular we show that the ERR time series is endowed with the following characteristics: 1) it is a potent surrogate for a point process, 2) it is capable of taking advantage of the well developed and powerful time series modeling tools and 3) it can generate reliable forecasts, with which we can retrieve the corresponding mean number of strong sand dust storms. A simulation study is conducted prior to the actual fitting, to justify the applicability of the proposed technique.
文摘无线信道建模对于理解、设计和优化无线通信系统具有重要意义,是无线通信领域中不可或缺的一部分。为了满足车联网(vehicle to everything,V2X)环境中的通信需求,研究空间中障碍物的分布对信道衰落特性的影响,本文提出了一种新的随机散射簇生成算法,即通过把Matérn硬核点过程和泊松簇过程相结合来模拟真实V2X信道中的障碍物。在算法中,依据真实环境障碍物的方位设置散射簇的坐标位置,根据周围障碍物密度合理设置簇内散射点数量。利用传播图论进行仿真,考虑直射路径和单跳散射路径,基于信道冲激响应(channel impulse response,CIR)分别研究了功率延迟分布(power delay profile,PDP)和多普勒功率谱密度(Doppler power spectrum density,DPSD),并分析了不同移动轨迹下的均方根(root mean square,RMS)时延扩展的累计分布函数(cumulative distribution function,CDF),以及莱斯K因子的分布特性和角度功率谱(power angular spectrum,PAS)的分布。本文研究验证得到,所提出的模型有助于分析车辆-基础设施(vehicle to infrastructure,V2I)通信场景下的时域非平稳特性,为V2X通信系统的设计和优化提供了重要参考。
