Significant spatial co-distribution pattern discovery

Given instances (spatial points) of different spatial features (categories), significant spatial co-distribution pattern discovery aims to find subsets of spatial features whose spatial distributions are statistically significantly similar to each other. Discovering significant spatial co-distribution patterns is important for many application domains such as identifying spatial associations between diseases and risk factors in spatial epidemiology. Previous methods mostly associated spatial features whose instances are frequently located together; however, this does not necessarily indicate a similarity in the spatial distributions between different features. Thus, this paper defines the significant spatial co-distribution pattern discovery problem and subsequently develops a novel method to solve it effectively. First, we propose a new measure, dissimilarity index, to quantify the difference between spatial distributions of different features under the spatial neighbor relation and then employ it in a distribution clustering method to detect candidate spatial co-distribution patterns. To further remove spurious patterns that occur accidentally, the validity of each candidate spatial co-distribution pattern is verified through a significance test under the null hypothesis that spatial distributions of different features are independent of each other. To model the null hypothesis, a distribution shift-correction method is presented by randomizing the relationships between different features and maintaining spatial structure of each feature (e.g., spatial auto-correlation). Comparisons with baseline methods using synthetic datasets demonstrate the effectiveness of the proposed method. A case study identifying co-morbidities in central Colorado is also presented to illustrate the real-world applicability of the proposed method.     

基于神经网络算法的井下裂缝诊断与堵漏技术

在钻井过程中，常常钻遇不同宽度的井下地层裂缝。钻遇裂缝时容易发生钻井液漏失现象，甚至发生钻井液失返现象，严重影响了安全、高效钻井。目前裂缝封堵的方法常存在封堵成功率不高、堵漏承压能力低的问题，其中一个重要的原因是对井下地层的裂缝宽度等特征认识不清。基于地层裂缝产生的岩石力学机理，确定影响裂缝宽度关键的6个力学和工程因素，并利用神经网络计算的非线性、大数据特点建立了井下地层裂缝宽度的分析模型，模型包含输入层、输出层和3个隐藏层。通过该模型诊断井下裂缝宽度，提高了计算精度，平均误差仅为2.09%，最大误差为5.88%，解决钻井现场仅凭经验判断裂缝误差较大和依靠成像测井成本较高的问题。同时根据神经网络模型诊断得到的裂缝宽度优化堵漏材料的粒径配比，提高了裂缝内的架桥封堵强度和架桥的稳定性，封堵层的承压能力达到12.8 MPa，反向承压能力达到4.5 MPa。现场堵漏试验最高憋压10 MPa，经过封堵作业后大排量循环不漏，达到了裂缝性地层高效堵漏的目的，堵漏一次成功。      

ECISER: Efficient Clip-art Image SEgmentation by Re-rasterization

Clip-art image segmentation is widely used as an essential step to solve many vision problems such as colorization and vectorization. Many of these applications not only demand accurate segmentation results, but also have little tolerance for time cost, which leads to the main challenge of this kind of segmentation. However, most existing segmentation techniques are found not sufficient for this purpose due to either their high computation cost or low accuracy. To address such issues, we propose a novel segmentation approach, ECISER, which is well-suited in this context. The basic idea of ECISER is to take advantage of the particular nature of cartoon images and connect image segmentation with aliased rasterization. Based on such relationship, a clip-art image can be quickly segmented into regions by re-rasterization of the original image and several other computationally efficient techniques developed in this paper. Experimental results show that our method achieves dramatic computational speedups over the current state-of-the-art approaches, while preserving almost the same quality of results.     

水文序列相依变异识别的RIC定阶准则——以自回归模型为例

水文过程相依性是水文变异的主要表现形式之一,应用自回归模型对其进行拟合时合理确定模型阶数是一个难点问题。本文在分析AIC和BIC准则的基础上,提出了一种以原序列与其相依成分的相关系数作为拟合度指标,同时借用信息熵形式的函数式,作为模型不确定性度量指标的自回归模型定阶准则(简称RIC准则)。以AR(1)、AR(2)、AR(3)和AR(4)模型为例进行统计试验,将不同序列长度下该准则的定阶准确率与其他定阶准则进行比较,试验结果表明,RIC准则对于上述模型均具有较好的适应性,且定阶准确率远高于AIC准则,其中对于前三阶模型RIC准则优于BIC准则,但四阶模型略低于BIC准则。RIC准则的优势是可以同时满足模型定阶、相依程度分级与模型检验的需求,将其应用于实测水文序列分析,结果显示,该准则能较准确地识别自回归模型的阶数,且符合提出的"相依有变异而残差无变异的最小阶数"的检验标准。     

大庆油混兑俄罗斯油对润滑油基础油生产及性质的影响

与大庆原油相比,大庆原油混兑8%俄罗斯原油后,对润滑油基础油的生产和质量均产生了较大影响。基础油HVI 150、350、650的粘度指数下降了1~4个单位,旋转氧弹上升了19~47 min,比色上升了0.5个单位。基础油综合收率提高了0.04%。大庆原油混兑8%俄罗斯原油后,通过调整润滑油生产装置的操作条件,可以生产符合Q/SHR 001-95标准的HVI 150、350、650基础油。     

石化装置蒸汽发生系统的仪表工程设计

主要探讨了某石化装置蒸汽发生系统的仪表工程设计，提出了复杂控制方案、联锁方案设计，同时也详述了影响系统设计的因素，如测量补偿和迁移等。     

建立速度模型的层析成像方法研究

针对目前叠前深度偏移速度模型建立中，全局反演的层析成像方法存在稳定性和走时拾取困难，以及局部反演的偏移速度分析大多存在假设条件过于苛刻等问题，通过分析，提出了利用地震同相辅的多种信息进行层析反演，并在反演中加入富有地质含义的倾角信息以增加反演过程的稳定性和收敛速度，利用类似于叠加速度谱的斜率速度谱来拾取地震同相轴的斜率，抛开了层位反演要求拾取同一同相轴这一实际应用难度很大的条件，使拾取方便，算法稳定。通过理论试算，证明了本方法的有效性。     

Host/guest complex of Me-β-CD/2,2-dimethoxy-2-phenyl acetophenone for initiation of aqueous photopolymerization: Kinetics and mechanism

Methylated-β-cyclodextrin (Me-β-CD) was used to complex the photoinitiator, 2,2-dimethoxy-2-phenyl acetophenone (DMPA), yielding a water-soluble host/guest complex. The comparative studies demonstrated that the Me-β-CD complexed DMPA exhibited a high photoreactivity identical to the uncomplexed DMPA, while the CD complex obviously influenced the products of primary photolysis of DMPA and the photopolymerization kinetics due to the steric effect of CD on the subsequent initiation reactions. The photopolymerization rate of acrylamide can be described by the equation: R_p=K[2a]^0.62[M]^1.37[I]^0.5[Me-β-CD]⁰. The mechanism of polymerization was also discussed.     

关于询价招标订购文件的名称

根据Requisition的词义和询价、招标、订购文件的意义，建议将不能准确表达意思的中文译词“请购”改成“询购”。