我国水-能源-粮食耦合关系及影响因素

为缓解我国水、能源和粮食资源紧张问题，促进资源可持续利用，构建水-能源-粮食系统，利用耦合协调度模型对我国的30个省（自治区、直辖市）进行测算,并利用空间杜宾模型分析主要影响因素。结果表明：2003—2017年，我国能源、粮食评价[JP]指数高于水资源评价指数，系统综合评价指数逐年递增；大部分省份耦合协调度处于初级协调水平且呈现逐年上升的态势，个别省份耦合协调度濒临失调；耦合协调度空间自相关性较强，虽有明显波动，但是呈现逐年加强的态势；影响耦合协调度的主要因素有从业人口数、固定资产投资额、人均生产总值、人口总数、[JP]文盲人口占比、工业污染排放、城镇化。     

空间统计在长江流域大米镉分布特征研究的应用

目的通过研究长江流域大米中镉含量的空间分布特征,为治理粮食作物镉污染提供科学依据。方法利用空间自相关对镉污染的聚集水平进行分析。结果湘江、岷江、涪江、沱江、青衣江、大度河支流流域的大米中镉含量高于长江流域的其他地区,2015年长江流域大米中镉含量的全局Moran's I指数值为0.596,在α=0.01水平上具有统计学意义。长江流域的大米样品中镉含量呈现中度的空间聚集性。湘江支流流域、岷江支流流域形成了2个"高-高"聚集区域,在鸭池河及其周边地区形成了一个典型的"低-低"聚集区域。结论长江流域整体上呈现中度的空间聚集性,局部地区呈现出空间异质性。     

CEEMD与KSVD字典训练相结合的去噪方法

本文提出一种完备总体经验模态分解（CEEMD）方法与K奇异值分解（KSVD）学习字典算法相结合的地震信号去噪方法。含噪信号通过CEEMD分解得到一系列不同尺度的固有模态函数（IMF）；按频率由高到低依次排列IMF各分量，并做自相关分析，去除噪声主导的IMF分量；将累加的过渡IMF分量叠加重构并做CEEMD二次分解，通过自相关分析再次去除噪声主导的IMF分量；分别叠加二次CEEMD分解剩余的IMF分量和一次剩余的IMF分量，得到两个新的含噪信号，并利用KSVD过完备字典分别稀疏表示该两个新的含噪信号，即由稀疏系数重构去噪后地震信号，进而重构最终去噪结果。实验结果证明：该算法的去噪效果明显优于F-X去噪、小波阈值去噪和KSVD字典稀疏去噪等传统方法。     

New sampling strategies to reduce the effect of autocorrelation on the synthetic T2 chart to monitor bivariate process

In this paper, synthetic T² chart is developed to monitor bivariate process with correlated variables and autocorrelated observations. The proposed chart is a combination of the Hotelling's T² chart and the conforming run length chart. The operation and design of the chart are described when observations are autocorrelated and cross correlated. The first‐order vector autoregressive process VAR (1) is used to model the bivariate data from an autocorrelated process of interest. Using an average run length as performance measure criterion in the VAR (1) model, it is observed that autocorrelation seriously impact the performance of the synthetic T² chart. To reduce the effect of autocorrelation on the performance of the synthetic T² chart, the skip and mixed sampling strategies are implemented to form rational subgroups in the construction of synthetic T² chart. The average run length performance of the synthetic T² chart implementing these strategies is compared with that of the standard strategy of formation of rational subgroups. It is observed that implementing skip and mixed sampling strategies within rational subgroup improves the performance of the synthetic T² chart.     

Examining spatially varying relationships between land use and water quality using geographically weighted regression I: model design and evaluation

Traditional regression techniques such as ordinary least squares (OLS) can hide important local variations in the model parameters, and are not able to deal with spatial autocorrelations existing in the variables. A recently developed technique, geographically weighted regression (GWR), is used to examine the relationships between land use and water quality in eastern Massachusetts, USA. GWR models make great improvements of model performance over OLS models, which is proved by F-test and comparisons of model R² and corrected Akaike Information Criterion (AIC_c) from both GWR and OLS. GWR models also improve the reliabilities of the relationships by reducing spatial autocorrelations. The application of GWR models finds that the relationships between land use and water quality are not constant over space but show great spatial non-stationarity. GWR models are able to reveal the information previously ignored by OLS models on the local causes of water pollution, and so improve the model ability to explain local situation of water quality. The results of this study suggest that GWR technique has the potential to serve as a useful tool for environmental research and management at watershed, regional, national and even global scales.     

Sub-micrometer particulate air pollution and cardiovascular mortality in Beijing, China

Background

While the link between particulate matter and cardiovascular mortality is well established, it is not fully investigated and understood which properties of the aerosol might be responsible for the health effects, especially in polluted mega-city areas.

Objectives

Our goal was to explore the association between daily cardiovascular mortality and different particle metrics in the sub-micrometer range in Beijing, China.

Methods

We obtained daily counts of cause-specific cardiovascular deaths in the Beijing urban area for the period March 2004 to August 2005. Concurrently, continuous measurements of particle number size distributions were performed. Particle number concentrations (NC) between 0.003 μm and 0.8 μm were converted to particle mass and surface area concentrations assuming spherical particles. Semi-parametric Poisson regression models adjusting for trend, seasonality, day of the week, and meteorology were used to estimate immediate, delayed and cumulative particle effects. Additionally, effect modification by air mass origin was investigated.

Results

We observed associations between daily cardiovascular mortality and particle NC for a 2-days delay. Moreover, nearly all particle metrics showed 2-days delayed associations with ischemic heart disease mortality. The strongest association was found for particle NC in the size range 0.03-0.1 μm (7.1% increase in daily mortality with a 95%-confidence interval of 2.9%-11.5%, per an increase of 6250 particles/cm³). Results for surface and mass concentrations with a lag of two days indicated effect modification by air mass origin, whereas effects of particle NC were not modified.

Conclusions

Results show an elevated risk of cardiovascular mortality in Beijing from short-term exposure to particulate air pollution in the sub-micrometer range. Results also indicate that locally produced smaller particles and regionally transported particles may exhibit different effects in Beijing.     

基于虚拟仪器的频率测量研究

阐述了一种基于虚拟仪器的正弦信号频率测量设计方案.结合相关原理和求导原理,提出了一种新的频率测量算法,该设计方案已成功应用于某型导弹的自动测试系统.实践证明,这项技术能提高测量精度,同时也能降低费用.     

基于EMD-小波包的随钻测量信号去噪方法

为了降低随钻测量过程中噪声对信号的影响,针对经验模态分解(EMD)去噪方法粗糙和小波包去噪方法缺乏自适应的问题,提出了一种基于EMD-小波包的随钻测量信号去噪方法。利用EMD分解自适应的特点将随钻测量信号分解成几个IMF分量;根据信号自相关函数的特性找出主要含噪的IMF分量,再利用小波包阈值去噪方法将含噪IMF分量中的噪声去除;将去噪后的IMF分量和剩余的分量重构,得到去噪后的随钻测量信号。为验证方法的有效性,进行了随钻测量实验并用该方法对采集的信号进行处理。结果表明该方法能够很好地去除随钻测量信号中噪声的干扰,提高信号的信噪比。     

昆明市住宅地价空间自相关分析

以昆明市五个城区为研究区,收集了2012~2016年的住宅用地地价交易数据,利用Arcgis10.0软件对其进行空间自相关分析和半变异函数分析,测算其Moran’s I指数、Local Moran’s I指数和块金系数来分析其全局自相关性、局部自相关性和空间异质性。结果表明:昆明市住宅地价具有全局空间正相关性;住宅地价高值与高值聚类,低值与低值聚类,具有局部空间集聚性;空间异质性主要由随机性因素引起,在一定范围内空间异质性随着样点间距增大而增大。     

Six Sigma experience as a stochastic process

This study empirically investigates the states of Six Sigma from a stochastic point of view. By the means of an advanced survey, 97 respondents are asked to rate the effect of Six Sigma on different performance categories, the cost of implementing Six Sigma, the level of enthusiasm and expectations from Six Sigma over 20 years. The autocorrelation and cross-correlation functions of these processes are analyzed to investigate the stages of Six Sigma. Consequently, new concepts namely steady state of Six Sigma and Six Sigma experience functions are introduced which shed light on the life cycle of Six Sigma within the companies.