膨胀剂对约束条件下UHPC早期抗裂性能影响的试验研究

超高性能混凝土(UHPC)在钢桥面铺装结构中由于铺装材料受到钢板、栓钉等的约束,加上材料本身水胶比小,更易收缩,早期容易承受拉应力导致开裂。通过在拌和过程中添加膨胀剂可以起到减小收缩的作用,但该方法对于约束条件下的UHPC铺装的早期抗裂性能提升是否有促进作用,仍需通过更多试验进行合理评估和深入研究。通过圆环法对3组不同配方的UHPC在均匀约束条件下的早期抗裂性能进行定量测试,并将试验数据进行回归分析和计算,得到了各组的平均应力发展速率,进而评估了各组的开裂风险等级。试验结果表明,通过在UHPC中加入适量膨胀剂,可使其最终收缩应力减小,并可降低其收缩应力发展速率,进一步降低其在约束条件下的开裂风险。     

基于投影寻踪的径向基函数网络在参考腾发量预测中的应用

径向基函数网络(RBFN)已广泛应用于参考腾发量预测等领域，但常用的K均值聚类和自组织特征映射等方法在求取径向基函数网络隐层节点中心时存在较大不足。针对这一问题，本文引入投影寻踪方法，在投影降维的基础上实现对大量高维数据的聚类，建立了基于投影寻踪的径向基函数网络模型，并将该模型应用于山西潇河灌区参考腾发量的预测，研究了不同气象因子输入对参考腾发量预测精度的影响。结果表明，基于投影寻踪的径向基函数网络具有较强的适用性，只需使用最高温度、最低温度、日照时数和旬序数作为输入因子，就能以较高的精度预测参考腾发量。     

Effects of modeling means on properties of monitoring models of spot welding quality

Analyzing and modeling the relation between monitoring information during welding and quality information of the joints is the foundation of monitoring resistance spot welding quality. According to the means of modeling, the known models can be divided into three large categories: single linear regression models, multiple linear regression models and multiple non-linear models. By modeling the relations between dynamic resistance information and welding quality parameters with different means, this paper analyzes effects of modeling means on performances of monitoring models of resistance spot welding quality. From the test results, the following conclusions can be drawn: By comparison with two other kinds of models, artificial neural network (ANN) model can describe non-linear and high coupling relationship between monitoring information and quality information more reasonably, improve performance of monitoring model remarkably, and make the estimated values of welding quality parameters more accurate and reliable.     

Semiparametric Estimation in Time‐Series Regression with Long‐Range Dependence

Abstract. We consider semiparametric estimation in time‐series regression in the presence of long‐range dependence in both the errors and the stochastic regressors. A central limit theorem is established for a class of semiparametric frequency domain‐weighted least squares estimates, which includes both narrow‐band ordinary least squares and narrow‐band generalized least squares as special cases. The estimates are semiparametric in the sense that focus is on the neighbourhood of the origin, and only periodogram ordinates in a degenerating band around the origin are used. This setting differs from earlier studies on time‐series regression with long‐range dependence, where a fully parametric approach has been employed. The generalized least squares estimate is infeasible when the degree of long‐range dependence is unknown and must be estimated in an initial step. In that case, we show that a feasible estimate which has the same asymptotic properties as the infeasible estimate, exists. By Monte Carlo simulation, we evaluate the finite‐sample performance of the generalized least squares estimate and the feasible estimate.     

Simultaneous Spectrophotometric Determination of Three Components Including Deoxyschizandrin by Partial Least Squares Regression

1IntroductionWuweizi is a traditional Chinese herb,usually usedto cure cough,asthma,neurasthenic,hepatitisetc.Theactive ingredients in wuweizi are5%-22%lignan,themain components of which include deoxyschizandrin,schizandrin andγ-Schizandrin.Forthe purpos…     

均匀设计法分析制备过程对钴钼硫化物催化剂机械强度的影响

建立了CoMoP/Al2O3加氢精制催化剂机械强度及其可靠性在制备过程中的数学模型,采用均匀设计考察了浸渍、干燥、煅烧、硫化4个制备过程中,浸渍时间、干燥温度、干燥时间、煅烧温度、煅烧时间、硫化温度和硫化升温速率7个实验因子对催化剂强度均值、Weibull模量的影响,同时考察了这些因素对颗粒密度的影响。方差分析表明所有模型都是充足的。实验结果表明,硫化过程是影响催化剂强度均值的主要过程。在实验范围内提高硫化温度、降低硫化时的升温速率有利于提高催化剂的强度。影响催化剂Weibull模量的因素主要为各个制备过程的交互效应。要提高催化剂强度的可靠性就必须全面考虑催化剂制备的各个过程,特别是各个制备过程的交互效应。     

Logistic Regression Analysis of Customer Satisfaction Data

Variation exists in all processes. Significant work has been done to identify and remove sources of variation in manufacturing processes resulting in large returns for companies. However, business process optimization is an area that has a large potential return for a company. Business processes can be difficult to optimize due to the nature of the output variables associated with them. Business processes tend to have output variables that are binary, nominal or ordinal. Examples of these types of output include whether a particular event occurred, a customer's color preference for a new product and survey questions that assess the extent of the survey respondent's agreement with a particular statement. Output variables that are binary, nominal or ordinal cannot be modeled using ordinary least‐squares regression. Logistic regression is a method used to model data where the output is binary, nominal or ordinal. This article provides a review of logistic regression and demonstrates its use in modeling data from a business process involving customer feedback. Copyright © 2006 John Wiley & Sons, Ltd.     

Moral value transfer from regulatory fit: What feels right is right and what feels wrong is wrong.

People experience regulatory fit (E. T. Higgins, 2000) when the strategic manner of their goal pursuit suits their regulatory orientation, and this regulatory fit feels right. Fit violation feels wrong. Four studies tested the proposal that experiences of fit can transfer to moral evaluations. The authors examined transfer of feeling wrong from fit violation by having participants in a promotion or prevention focus recall transgressions of commission or omission (Studies 1 and 2). Both studies found that when the type of transgression was a fit violation, participants expressed more guilt. Studies 3 and 4 examined transfer of feeling right from regulatory fit. Participants evaluated conflict resolutions (Study 3) and public policies (Study 4) as more right when the means pursued had fit. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

迭代回归法计算T型电位滴定中试液含量

本文将迭代回归法计算Ｔ型电位滴定中，叙述了其原理及数学推导，并运算了一批实验数据，结果表明，该法准确度较高，且不需空白溶液校正。     

预测井眼稳定性的力学化学耦合方法

在井眼力学稳定性评价的基础上，将硬脆性页岩水化后岩石强度等参数的变化规律用于页岩水化前后坍塌压力变化的对比分析，结果表明，地层坍塌压力当量密度随页岩水化程度的增加逐渐升高。给出了预测井眼稳定性的力学化学耦合方法，并将该方法应用于现场生产中，取得了较好的预测效果