双能CT成像基材料分解法的理论误差分析

双能X射线计算机断层成像技术(DECT)能够准确地重建物质的有效原子序数和电子密度信息,是一种有效的物质辨别技术。基材料分解法是求解DECT重建问题的主要方法之一。但目前应用此方法得到的重建结果误差较大,并且对于金属伪影抑制能力也较差。本文分析了DECT基材料分解法重建结果的误差来源和形成机制,阐释了其对金属伪影抑制作用差的原因,并推导出了该方法的理论误差计算公式,为分析方便,本文使用了两个单能进行研究。最后,对基材料分解法重建的适用条件提出了建议,一般情况下,该方法对低Z材料误差较小,对高Z材料误差较大。     

Re-examining urban region and inferring regional function based on spatial–temporal interaction

Urban system is shaped by the interactions between different regions and regions planned by the government, then reshaped by human activities and residents’ needs. Understanding the changes of regional structure and dynamics of city function based on the residents’ movement demand are important to evaluate and adjust the planning and management of urban services and internal structures. This paper constructed a probabilistic factor model on the basis of probabilistic latent semantic analysis and tensor decomposition, for purpose of understanding the higher order interactive population mobility and its impact on urban structure changes. First, a four-dimensional tensor of time (T)?×?week (W)?×?origin (O)?×?destination (D) was constructed to identify the day-to-day activities in three time modes and weekly regularity of weekday/weekend pattern. Then we reclassified the urban regions based on the space clustering formed by the space factor matrix and core tensor. Finally, we further analysed the space–time interaction on different time scales to deduce the actual function and connection strength of each region. Our research shows that the application of individual-based spatial–temporal data in human mobility and space–time interaction study can help to analyse urban spatial structure and understand the actual regional function from a new perspective.     

Generating non-stationary random fields of auto-correlated,normally distributed CPT profile by matrix decomposition method

This paper emphasises the true realisation of Cone Penetration Test (CPT) profiles considering non-stationary nature of the data. Formulation of stationary random field theory has been modified and adapted to non-stationary state in order to take into account the mean and variance variability for soil properties. Multi-variance correlation matrix along with the Cholesky decomposition technique was employed to produce realisations of non-homogenous and non-stationary random fields of CPT profiles. A piecewise and segmental data realisation according to the lithology and site class specifications acquired directly from CPT data is adopted in this study so as to render an accurate data simulation. For validation of proposed method 8 CPT test profiles collected from Urmia Lake site have been introduced and simulated by the stationary and non-stationary algorithms. The mean correlation coefficient between the actual CPT data profiles and related realisations along with some other important statistical parameters and their coefficients of variation strongly demonstrate that non-stationary random field generation technique gives quite better accuracy, by comparison to the conventional stationary random field generation scheme.     

一种新的极化SAR图像非监督分类算法研究

提出了一种建立在Mean-shift过分割结果区域图上的极化SAR图像非监督分类算法。首先通过Mean-shift算法得到极化SAR图像的过分割结果区域图,并将过分割小块视为“超级像素”,然后在Freeman-Durden分解的基础上引入散射功率熵和各向异性量参数来进一步分析“超级像素”的混合散射机制问题,最后结合Wishart迭代聚类实现极化SAR图像的非监督分类。实验表明,该算法具有较为满意的分类效果。     

基于小波分解的西太平洋副热带高压模糊推理预测

基于NCEP/NCAR再分析资料,讨论了西太平洋副高脊线与其前期位置的相互关系,并在此基础上用小波分解和自适应模糊推理方法,对副高脊线进行集成建模和预测.基于小波分解重构的副高脊线短期活动集成预测结果表明,该方法可有效降低预报难度,明显改进和提高了副高脊线短期活动的预报准确率.     

Refugees in the IT Sector: Young Syrians’ Economic Subjectivities and Familial Lives in Jordan

This article explores refugee economic subjectivity in the context of restrictive asylum policies and disrupted transnational family lives. Drawing on fieldwork with young Syrian refugees pursuing IT training in Jordan, I focus on the “coding boot camp,” an emerging educational format in the field of refugee professional training. I thus explore how Syrian youths approach humanitarian policies in which, in the absence of full social and economic rights for refugees, the question of livelihoods is addressed through the paradigms of self‐reliance, creativity, and innovation. Reframing the refugee from a “protected” to a “productive” subject, and offering individual solutions to a structural economic impasse, these policies produce tensions between individual responsibilities and more‐than‐individual relations and identifications—with families, religious identities, and national communities—that remain unresolved. The findings contribute to geographical scholarship on economic subjectivity, familial relations, and the migrant and refugee condition, while shedding light on some of the effects of the encounter between technology‐centred, neoliberal approaches to humanitarianism and restrictive migration regimes in responses to the Syrian displacement.     

安徽省产业结构变化和技术进步对用水效率影响测度与分析——基于完全分解模型

水资源短缺为掣肘安徽省经济社会可持续发展约束因素之一,提高水资源利用效率是破解其关键。运用完全分解模型,就技术进步、结构变动因素对安徽省单位GDP水耗贡献份额进行了测度,结果表明:(1)2001~2014年,技术进步导致安徽省单位GDP用水年均下降31.91m3,是提高水资源利用效率关键因素,贡献率高达88.69%,三次产业技术进步贡献率分别为45.19%、38.59%、4.91%;(2)产业结构调整对安徽省单位GDP用水强度下降贡献率为11.31%,三次产业变动贡献率分别为-4.98%、0.62%、15.66%。提高安徽省水资源利用效率核心在于:依靠科技创新,促进一、二产业技术水平提升,调整、优化产业结构,大力提高第三产业比重。研究结果,可为安徽省制定水资源利用效率的政策提供决策参考。     

EMD-Wavelet-ICA耦合模型及其在GPS坐标序列降噪中的应用

在分析比较经验模态分解(EMD)、小波变换(Wavelet)和独立分量分析(ICA)优缺点的基础上,提出一种新的EMD-Wavelet-ICA耦合模型。该模型充分利用了EMD的自适应性,对原始信号进行分解获得不同频率的模态函数(IMF),采用标准化模量的累计均值对IMF进行尺度划分;进而分别采用Wavelet和ICA对高频和低频IMF进行降噪,将降噪后的IMF进行多尺度重构,获得降噪后的信号;采用信噪比、标准差、偏差和相关系数等指标对降噪效果进行评价。仿真数据和GPS坐标序列的处理结果表明:与EMD模型和EMD-ICA模型相比,新模型的标准差、偏差均有不同程度的减小;信噪比和相关系数有一定程度的增大,可以获得更好的降噪效果。     

基于优化经验模态分解和聚类分析的滑坡位移智能预测研究

针对三峡库区"阶跃式"滑坡的变形特征,提出了一种新的滑坡位移预测方法。以白水河滑坡ZG118和XD-01监测点位移数据为例,采用基于软筛分停止准则的经验模态分解(SSSC-EMD)将累计位移-时间曲线和影响因子时间序列自适应地分解为多个固有模态函数(IMF),并采用K均值(K-Means)聚类法对其进行聚类累加,得到有物理含义的位移分量(趋势性位移、周期性位移以及随机性位移)和影响因子分量(高频影响因子和低频影响因子)。使用最小二乘法对趋势性位移进行拟合预测;采用果蝇优化-最小二乘支持向量机(FOA-LSSVM)模型对周期性位移和随机性位移进行预测。将各位移分量预测值进行叠加处理,实现滑坡累计位移的预测。研究结果表明,所提出的(SSSC-EMD)-K-Means-(FOA-LSSVM)模型能够预测"阶跃式"滑坡的位移变化规律,且预测精度高于传统的支持向量机回归(SVR)、最小二乘支持向量机(LSSVM)模型;并通过改变训练集长度,进行单因素分析,发现其与预测精度之间呈正相关关系。     

Geochemistry and pollution of shallow aquifers in the Mafraq area, North Jordan

 Chemical data are used to clarify the hydrogeological regime in the Mafraq area in northern Jordan, as well as to determine the status of water quality in the area. Groundwater from the shallow aquifer in the Mafraq area can be divided into two major groups according to geographical locations and chemical compositions. Water in the basaltic eastern part of the study area is characterized by the dominance of chloride, sulfate, sodium, and potassium, whereas waters in the limestone aquifers in the west are dominated by the same cations but have higher concentrations of bicarbonate. Stable isotopes show that the shallow aquifers contain a single water type which originated in a distinct climatic regime. This water type deviates from the Global Meteoric Water Line (MWL), as well as from the eastern Mediterranean meteoric water line. The waters are poor in tritium, and thus can be considered generally older than 50 years. Chemical mass balance models suggest that water is moving from the west towards the north of the study area. This suggests that waters from the different basins are separated from each other. Degradation of water quality can be attributed to agricultural fertilizers in most cases, although the waste-water treatment plant at Khirbet es Samra is a contributor to pollution in the southwestern part of the study area. Received: 20 August 1997 · Accepted: 3 February 1998