A case-deletion diagnostic for penalized calibration estimators and BLUP under linear mixed models in survey sampling

The penalized calibration technique in survey sampling combines usual calibration and soft calibration by introducing a penalty term. Certain relevant estimates in survey sampling can be considered as penalized calibration estimates obtained as particular cases from an optimization problem with a common basic structure. In this framework, a case deletion diagnostic is proposed for a class of penalized calibration estimators including both design-based and model-based estimators. The diagnostic compares finite population parameter estimates and can be calculated from quantities related to the full data set. The resulting diagnostic is a function of the residual and leverage, as other diagnostics in regression models, and of the calibration weight, a singular feature in survey sampling. Moreover, a particular case, which includes the basic unit level model for small area estimation, is considered. Both a real and an artificial example are included to illustrate the diagnostic proposed. The results obtained clearly show that the proposed diagnostic depends on the calibration and soft-calibration variables, on the penalization term, as well as on the parameter to estimate.     

GOS+MU:一种查询对象选择新方法

在分析单一MU(Most Uncertainty)采样缺陷的基础上,提出一种"全局最优搜寻"方法 GOS(Global Optimal Search),并结合MU共同完成查询选择。GOS+MU方法中,GOS着眼全局寻找目标,在应用环境能提供的训练样本数量有限、分类器受训不充分时,该方法选择的对象学习价值高,能快速推进分类器学习进程;MU则能够在GOS采样失效情形下,利用分类器当前训练成果,选择查询不确定性最强的样本补充训练集。通过对网络商品的用户评论进行分类仿真,并比较其他采样学习方法的效果,证明了GOS+MU方法在压缩学习成本、提高训练效率方面的有效性。     

Occurrence and diversity of Listeria spp. in seafood processing plant environments

Listeria contamination in processing plant environments is a major issue for the seafood industry worldwide; faster and more reliable results are therefore desired for early detection and monitoring of environmental Listeria spp. This study aimed to gain a better understanding of the prevalence and diversity of Listeria spp., and to evaluate a rapid detection method, the 3M Molecular Detection Assay (MDA) Listeria, for its ability to detect Listeria spp. in environmental samples from seafood processing plants. Duplicate environmental sponge samples (n = 444) were collected from 152 different sites within three seafood processing plants, and analyzed for Listeria spp. by the MDA method (after 26 and 48 h of enrichment) and the U.S. Food and Drug Administration Bacteriological Analytical Manual method. Overall, detection of Listeria spp. by the two methods did not differ significantly (p > 0.05); 11 (4.9%) and 13 (5.9%) samples were positive for Listeria spp. by the MDA and FDA-BAM method, respectively. The sensitivity of the MDS was 87.0% (95% CI: 77.4–96.6%), specificity was 97.6% (95% CI: 95.5–99.7%), accuracy was 95.3%, and the positive predictive value was 89.4% (95% CI: 80.5–98.2%). Classification of 19 Listeria isolates by partial SigB sequencing analysis identified three allelic types. Twelve of these isolates were ATs 58 and 60 which were classified as Listeria monocytogenes lineage I and serotypes 1/2b, 3b, 4b, 4d, 4e, by multiplex-PCR serotyping. Six Listeria isolates were classified as Listeria innocua (AT31). Our data show that the 3M Molecular Detection Assay Listeria provides rapid and reliable results for detection and monitoring of Listeria spp., which are important for seafood processing plants. Effective Listeria monitoring programs will allow for improved development of Listeria control measures in order to minimize cross-contamination in finished products.     

马钢二烧结配料计算机控制系统

阐明了马钢二烧结配科计算机控制系统的目的、控制形式、控制原理；根据烧结配料控制对象的特点对信号采样和控制算法进行了探讨；提供了系统的主要硬件结构，软件功能和程序框图。     

传感器管理及其在相控阵雷达中的应用

传感器管理是数据融合的一部分。介绍了传感器管理的概念和框架 ,概述了国内外传感器管理算法的研究现状。主要工作是针对相控阵雷达这一传感器 ,通过对其不同工作模式以及不同参数的管理 ,来说明传感器管理的原理。提出了一种新的自适应采样周期算法 ,仿真结果表明该算法的优越性     

带通采样在数据采集中的应用研究

在数据采集中采用带通采样，可大大降低采样率，但系统中的抗混叠滤波器会造成相位的非线性。采用对滤波后的信号进行带通采样，然后再用FRR滤波器校正相位的非线性，从而不失真地还原原信号，最后在Matlab中进行仿真，验证了该方法的有效性。     

利用框架理论对信号进行重建

在Hilbert空间中讨论了框架的一些重要的性质,定义了一个框架算子,并讨论了该算子的性质。根据实际问题构造了一框架,使信号在此框架下的投影正好为非均匀采样值。给出了一种框架界的估计方法和重建原信号的迭代算法,最后,用仿真验证了此算法的有效性。     

准噶尔盆地侏罗系储集层的基本特征及其主控因素分析

从描述储集层基本特征、分析储集层性质的主控因素、建立储集层成因模式和评价、预测储集层性质这 4个层次 ,研究准噶尔盆地重点勘探目标区的侏罗系储集层。系统总结侏罗系储集层岩石学特征 ,认为成岩压实作用强弱是控制储集层性质的关键因素 ;指出相对优质储集层均为剩余原生粒间孔隙型储集层 ,溶蚀作用对渗透率贡献小 ;非煤系储集层的孔隙保存条件明显比煤系储集层好 ,这是三工河组、头屯河组和吐谷鲁群的物性普遍优于八道湾组和西山窑组的原因。在确定储集层性质的控制因素和控制机理基础上 ,建立了煤系和非煤系两大类储集层的成因 演化模型。在上述研究的基础上 ,分地区、分层位评价了储集层 ,并预测了不同渗透率储集层的深度界线及相对优质储集层的平面分布。图 6参 10     

Poly(butylene terephthalate)–clay nanocomposites prepared by melt intercalation: morphology and thermomechanical properties

Nanocomposites based on poly(butylene terephthalate) (PBT) and an organoclay (Cloisite 30B) were prepared by melt blending using a twin‐screw extruder. Two kinds of PBTs, ie PBT‐A and PBT‐B, with different inherent viscosities (η_inh), were used for this study (η_inh of PBT‐A and PBT‐B were 0.74 and 1.48, respectively). Dispersion of the clay layers in the PBT nanocomposites was characterized by using X‐ray diffraction (XRD) and transmission electron microscopy (TEM). Tensile and dynamic mechanical properties and non‐isothermal crystallization temperatures of the nanocomposites were also examined. Nanocomposites based on the higher‐viscosity PBT (PBT‐B) showed a higher degree of exfoliation of the clay and a higher reinforcing effect when compared to the composites based on the lower‐viscosity PBT (PBT‐A). The clay nanolayers dispersed in PBT matrices lead to increases in the non‐isothermal crystallization temperatures of the PBTs, with such increases being more significant for the PBT‐B nanocomposites than for the PBT‐A nanoocomposites. Copyright © 2004 Society of Chemical Industry