Based on systematized physical, chemical, and biological modules, a multi-species harmful algal bloom （HAB） model coupled with background ecological fields was established. This model schematically embod-ied that HA...Based on systematized physical, chemical, and biological modules, a multi-species harmful algal bloom （HAB） model coupled with background ecological fields was established. This model schematically embod-ied that HAB causative algal species and the background ecological system, quantified as total biomass, were significantly different in terms of the chemical and biological processes during a HAB while the inter-action between the two was present. The model also included a competition and interaction mechanism between the HAB algal species or populations. The Droop equation was optimized by considering tempera-ture, salinity, and suspended material impact factors in the parameterization of algal growth rate with the nutrient threshold. Two HAB processes in the springs of 2004 and 2005 were simulated using this model. Both simulation results showed consistent trends with corresponding HAB processes observed in the East China Sea, which indicated the rationality of the model. This study made certain progress in modeling HABs, which has great application potential for HAB diagnosis, prediction, and prevention.展开更多
A light source of multi-star simulator capable of background adjustment and magnitude control has been designed.Two integrating spheres are employed as the star-point light source and the background light source respe...A light source of multi-star simulator capable of background adjustment and magnitude control has been designed.Two integrating spheres are employed as the star-point light source and the background light source respectively.A beam splitter prism has been designed to serve as the beam combiner for the star-point and the background light sources,and a mathematical model has been constructed respectively to compute the light flux of the two integrating spheres.A magnitude testing system and a background testing system have been created using low-light illuminometer,luminance meter,and testing instruments to measure the star-point magnitude and the background luminance of the multi-star simulator.The test results suggest that the star-point magnitude is adjustable from0 to+5 m_v,with a simulation precision superior to ±0.026 m_v.The maximum background luminance is 3.8×10~5 cd·m^(-2),and the minimum background luminance is6.4×10^(-2)cd·m^(-2).The designed light source system can meet the requirements for simulating the stellar map with a sky background.展开更多
The large-scale and small-scale errors could affect background error covariances for a regional numerical model with the specified grid resolution.Based on the different background error covariances influenced by diff...The large-scale and small-scale errors could affect background error covariances for a regional numerical model with the specified grid resolution.Based on the different background error covariances influenced by different scale errors,this study tries to construct a so-called"optimal background error covariances"to consider the interactions among different scale errors.For this purpose,a linear combination of the forecast differences influenced by information of errors at different scales is used to construct the new forecast differences for estimating optimal background error covariances.By adjusting the relative weight of the forecast differences influenced by information of smaller-scale errors,the relative influence of different scale errors on optimal background error covariances can be changed.For a heavy rainfall case,the corresponding optimal background error covariances can be estimated through choosing proper weighting factor for forecast differences influenced by information of smaller-scale errors.The data assimilation and forecast with these optimal covariances show that,the corresponding analyses and forecasts can lead to superior quality,compared with those using covariances that just introduce influences of larger-or smallerscale errors.Due to the interactions among different scale errors included in optimal background error covariances,relevant analysis increments can properly describe weather systems(processes)at different scales,such as dynamic lifting,thermodynamic instability and advection of moisture at large scale,high-level and low-level jet at synoptic scale,and convective systems at mesoscale and small scale,as well as their interactions.As a result,the corresponding forecasts can be improved.展开更多
A novel diversity-sampling based nonparametric multi-modal background model is proposed. Using the samples having more popular and various intensity values in the training sequence, a nonparametric model is built for ...A novel diversity-sampling based nonparametric multi-modal background model is proposed. Using the samples having more popular and various intensity values in the training sequence, a nonparametric model is built for background subtraction. According to the related intensifies, different weights are given to the distinct samples in kernel density estimation. This avoids repeated computation using all samples, and makes computation more efficient in the evaluation phase. Experimental results show the validity of the diversity- sampling scheme and robustness of the proposed model in moving objects segmentation. The proposed algorithm can be used in outdoor surveillance systems.展开更多
人群分布不均、遮挡和背景干扰等问题使得人群计数成为了一项复杂且具有挑战性的任务。针对这些问题,提出了一种多尺度特征融合的位置关注网络(Position-Aware Network based on Multi-Scale Feature Fusion,MSFPANet)。首先,设计了一...人群分布不均、遮挡和背景干扰等问题使得人群计数成为了一项复杂且具有挑战性的任务。针对这些问题,提出了一种多尺度特征融合的位置关注网络(Position-Aware Network based on Multi-Scale Feature Fusion,MSFPANet)。首先,设计了一种多尺度特征融合模块,以在不同感受野下提取并融合人群密度图的多尺度特征,同时提取出前景信息,来应对人群计数中的遮挡和背景干扰问题;然后,通过位置注意力分配网络提高模型对人群区域的关注度,有效地应对人群分布不均的问题;最后,为了辅助模型训练,减小背景噪声带来的干扰,引入了一种结构交叉损失用于强化模型对人群结构的学习。实验结果表明:MSF-PANet在Shanghai Tech Part A、Shanghai Tech Part B、UCF-QNRF和UCF_CC_50上平均绝对误差分别为59.5、7.8、103、182.7,均方误差分别为96.7、13.6、177、237.7,验证了所提模块在提高人群计数准确率上的有效性。展开更多
以黄河中下游山地丘陵区的巩义市为研究区,采用典型样地法对灌草丛、人工林和农田边缘3种不同干扰背景下的自然、半自然生境内的植物进行调查。基于景观生态学原理,在地理信息系统技术支持下,借助于Fragstatta3.3软件,以调查样地为中心...以黄河中下游山地丘陵区的巩义市为研究区,采用典型样地法对灌草丛、人工林和农田边缘3种不同干扰背景下的自然、半自然生境内的植物进行调查。基于景观生态学原理,在地理信息系统技术支持下,借助于Fragstatta3.3软件,以调查样地为中心,计算了150、250、500、750、1000、1250、1500m不同半径缓冲区内表征景观形状(Edge and patch shape)、边缘对照(Edge contrast)、相似度和邻近度(Proximity and similarity)、景观多样性(Diversity)、基质(Texture)、斑块大小和密度(Patch size and patch density)共6类52个指数,运用冗余分析(RDA)筛选出不同尺度下对该区农业景观中植物多样性有显著影响的景观指数。结果表明:不同尺度,景观指数对物种多样性的影响变化显著。灌草丛生境,在500—750m范围内,SHAPE_AM指数和PARA_AM指数能够很好的解释物种多样性,解释量为33.6%;人工林生境,SHAPE_AM指数、AREA_CV指数、SIMI指数和PAFRAC指数在1000—1250m范围内对物种多样性的解释量达到48.1%;农田边缘生境,GYRATE_CV指数、ENN_CV指数、PARA_MN指数和FRAC_AM指数在750—1250m范围内对物种多样性影响显著,解释量为32%。其中,辛普森多样性指数(SIDI)与灌草丛物种多样性在750—1250m范围内作用显著,ENN_CV指数仅对农田边缘物种多样性影响较大。景观指数对物种多样性的影响具有尺度依赖性,未来应全面综合探讨这些指数的尺度效应及在景观生态学中的应用。展开更多
基金The National Natural Basic Research Program of China(973 Program) under contract No.2010CB428704
文摘Based on systematized physical, chemical, and biological modules, a multi-species harmful algal bloom （HAB） model coupled with background ecological fields was established. This model schematically embod-ied that HAB causative algal species and the background ecological system, quantified as total biomass, were significantly different in terms of the chemical and biological processes during a HAB while the inter-action between the two was present. The model also included a competition and interaction mechanism between the HAB algal species or populations. The Droop equation was optimized by considering tempera-ture, salinity, and suspended material impact factors in the parameterization of algal growth rate with the nutrient threshold. Two HAB processes in the springs of 2004 and 2005 were simulated using this model. Both simulation results showed consistent trends with corresponding HAB processes observed in the East China Sea, which indicated the rationality of the model. This study made certain progress in modeling HABs, which has great application potential for HAB diagnosis, prediction, and prevention.
基金Supported by Jilin Province Key Scientific and Technological Projects(20160204008GX)National Key Laboratory Fund Project(61420020210162002)Changchun University of Science and Technology Innovation Fund(XJJLG-2016-15)
文摘A light source of multi-star simulator capable of background adjustment and magnitude control has been designed.Two integrating spheres are employed as the star-point light source and the background light source respectively.A beam splitter prism has been designed to serve as the beam combiner for the star-point and the background light sources,and a mathematical model has been constructed respectively to compute the light flux of the two integrating spheres.A magnitude testing system and a background testing system have been created using low-light illuminometer,luminance meter,and testing instruments to measure the star-point magnitude and the background luminance of the multi-star simulator.The test results suggest that the star-point magnitude is adjustable from0 to+5 m_v,with a simulation precision superior to ±0.026 m_v.The maximum background luminance is 3.8×10~5 cd·m^(-2),and the minimum background luminance is6.4×10^(-2)cd·m^(-2).The designed light source system can meet the requirements for simulating the stellar map with a sky background.
基金National Natural Science Foundation of China(41130964)National Special Funding Project for Meteorology(GYHY-201006004)
文摘The large-scale and small-scale errors could affect background error covariances for a regional numerical model with the specified grid resolution.Based on the different background error covariances influenced by different scale errors,this study tries to construct a so-called"optimal background error covariances"to consider the interactions among different scale errors.For this purpose,a linear combination of the forecast differences influenced by information of errors at different scales is used to construct the new forecast differences for estimating optimal background error covariances.By adjusting the relative weight of the forecast differences influenced by information of smaller-scale errors,the relative influence of different scale errors on optimal background error covariances can be changed.For a heavy rainfall case,the corresponding optimal background error covariances can be estimated through choosing proper weighting factor for forecast differences influenced by information of smaller-scale errors.The data assimilation and forecast with these optimal covariances show that,the corresponding analyses and forecasts can lead to superior quality,compared with those using covariances that just introduce influences of larger-or smallerscale errors.Due to the interactions among different scale errors included in optimal background error covariances,relevant analysis increments can properly describe weather systems(processes)at different scales,such as dynamic lifting,thermodynamic instability and advection of moisture at large scale,high-level and low-level jet at synoptic scale,and convective systems at mesoscale and small scale,as well as their interactions.As a result,the corresponding forecasts can be improved.
基金Project supported by National Basic Research Program of Chinaon Urban Traffic Monitoring and Management System(Grant No .TG1998030408)
文摘A novel diversity-sampling based nonparametric multi-modal background model is proposed. Using the samples having more popular and various intensity values in the training sequence, a nonparametric model is built for background subtraction. According to the related intensifies, different weights are given to the distinct samples in kernel density estimation. This avoids repeated computation using all samples, and makes computation more efficient in the evaluation phase. Experimental results show the validity of the diversity- sampling scheme and robustness of the proposed model in moving objects segmentation. The proposed algorithm can be used in outdoor surveillance systems.
文摘人群分布不均、遮挡和背景干扰等问题使得人群计数成为了一项复杂且具有挑战性的任务。针对这些问题,提出了一种多尺度特征融合的位置关注网络(Position-Aware Network based on Multi-Scale Feature Fusion,MSFPANet)。首先,设计了一种多尺度特征融合模块,以在不同感受野下提取并融合人群密度图的多尺度特征,同时提取出前景信息,来应对人群计数中的遮挡和背景干扰问题;然后,通过位置注意力分配网络提高模型对人群区域的关注度,有效地应对人群分布不均的问题;最后,为了辅助模型训练,减小背景噪声带来的干扰,引入了一种结构交叉损失用于强化模型对人群结构的学习。实验结果表明:MSF-PANet在Shanghai Tech Part A、Shanghai Tech Part B、UCF-QNRF和UCF_CC_50上平均绝对误差分别为59.5、7.8、103、182.7,均方误差分别为96.7、13.6、177、237.7,验证了所提模块在提高人群计数准确率上的有效性。
文摘以黄河中下游山地丘陵区的巩义市为研究区,采用典型样地法对灌草丛、人工林和农田边缘3种不同干扰背景下的自然、半自然生境内的植物进行调查。基于景观生态学原理,在地理信息系统技术支持下,借助于Fragstatta3.3软件,以调查样地为中心,计算了150、250、500、750、1000、1250、1500m不同半径缓冲区内表征景观形状(Edge and patch shape)、边缘对照(Edge contrast)、相似度和邻近度(Proximity and similarity)、景观多样性(Diversity)、基质(Texture)、斑块大小和密度(Patch size and patch density)共6类52个指数,运用冗余分析(RDA)筛选出不同尺度下对该区农业景观中植物多样性有显著影响的景观指数。结果表明:不同尺度,景观指数对物种多样性的影响变化显著。灌草丛生境,在500—750m范围内,SHAPE_AM指数和PARA_AM指数能够很好的解释物种多样性,解释量为33.6%;人工林生境,SHAPE_AM指数、AREA_CV指数、SIMI指数和PAFRAC指数在1000—1250m范围内对物种多样性的解释量达到48.1%;农田边缘生境,GYRATE_CV指数、ENN_CV指数、PARA_MN指数和FRAC_AM指数在750—1250m范围内对物种多样性影响显著,解释量为32%。其中,辛普森多样性指数(SIDI)与灌草丛物种多样性在750—1250m范围内作用显著,ENN_CV指数仅对农田边缘物种多样性影响较大。景观指数对物种多样性的影响具有尺度依赖性,未来应全面综合探讨这些指数的尺度效应及在景观生态学中的应用。
