关于列表曲线插补问题的探讨

本文介绍了根据列表曲线的离散点计算各程序段初值的一般方法.     

LTCC小型化Balun设计

介绍了一种基于LTCC(低温共烧陶瓷)技术的小型化balun的设计。设计的Balun采用Marchand balun结构,使用LTCC技术实现多层结构、上下耦合的方式减小balun的体积并拓展带宽。该balun工作在1.7～2.2GHz,体积为2.8mm×3mm×1mm,并且平衡端口输出具有良好的幅值平衡和180°相位差。     

Estimating the Upper Support Point in Deconvolution

Abstract.  We consider estimation of the upper boundary point F ⁻¹ (1) of a distribution function F with finite upper boundary or 'frontier' in deconvolution problems, primarily focusing on deconvolution models where the noise density is decreasing on the positive halfline. Our estimates are based on the (non-parametric) maximum likelihood estimator (MLE) of F . We show that (1) is asymptotically never too small. If the convolution kernel has bounded support the estimator (1) can generally be expected to be consistent. In this case, we establish a relation between the extreme value index of F and the rate of convergence of (1) to the upper support point for the 'boxcar' deconvolution model. If the convolution density has unbounded support, (1) can be expected to overestimate the upper support point. We define consistent estimators , for appropriately chosen vanishing sequences ( β _n ) and study these in a particular case.     

健美操课实施过程中应注意的几个问题

健美操课已经成为学校体育教学的重要组成部分,提高健美操课的质量,在实施中就应该掌握健美操课的特点,把握健美操课的结构和注意事项。     

熵权基点决策法在绿色施工评价中的应用

绿色施工是实现建造方式由劳动力密集型向技术密集型、由粗放型向集约型转变的组织方式。保证绿色施工的有效推进,一方面要创新绿色施工技术,另一方面要采取科学的评价方法。在已有文献的基础上,构建了一套科学的绿色施工评价指标体系,并运用熵理论和基点的决策分析方法建立综合评价模型,在一定程度上克服了以往绿色施工评价中的指标主观、测量效果不准确的问题。通过对某工程施工实例分析证明,该方法实用性强,可以应用于工程项目的前期招标方案评价和施工中、后期的施工质量评价。     

白云山风景区林地小气候与环境

本文通过实测的气象资料，应用统计方法，分析了林地的气候环境，它具有降漫画、增湿的效应。并用温湿指数（THI）说明它对人体的舒适程度，林地建设对维持城市生态平衡有重要作用。     

助燃剂为CO2+O2的燃烧方式实验研究

对用CO2＋O2作为助燃剂的燃料燃烧方式进行了实验研究，介绍了实验装置，实验的测点的布置及测量方法，根据实验数据分析了不同煤气流量，助燃剂的构成对燃烧室内部温度及出口温度，NO及CO分布的影响。     

大体积混凝土掺矿粉的试验与应用

矿渣微粉可以改善砼的性能,提高砼密实度,改善砼的和易性,并且可以降低砼水化热,增进后期强度、提高抗腐能力,尤其是磨细矿物掺合料对碱一集料反应的抑制作用。作用辅助胶凝材料的矿粉得到了广泛的认可。     

蒸汽在水下有限空间内喷注时喷注噪声的声源分析

在实验研究的基础上，用计算流体力学软件(CFD)对与喷注噪声密切相关的压力场与温度场进行数值计算，定量分析了在不同温度时所对应的压力场与喷注噪声的关系。     

A new financial stress index model based on support vector regression and control chart

Financial stress index (FSI) is considered to be an important risk management tool to quantify financial vulnerabilities. This paper proposes a new framework based on a hybrid classifier model that integrates rough set theory (RST), FSI, support vector regression (SVR) and a control chart to identify stressed periods. First, the RST method is applied to select variables. The outputs are used as input data for FSI–SVR computation. Empirical analysis is conducted based on monthly FSI of the Federal Reserve Bank of Saint Louis from January 1992 to June 2011. A comparison study is performed between FSI based on the principal component analysis and FSI–SVR. A control chart based on FSI–SVR and extreme value theory is proposed to identify the extremely stressed periods. Our approach identified different stressed periods including internet bubble, subprime crisis and actual financial stress episodes, along with the calmest periods, agreeing with those given by Federal Reserve System reports.