Identification of micro-scale calorimetric devices II

The miniaturized calorimetric devices furnish a reduced working flat surface and permits measurements with extremely low-mass quantities. The experimental sensitivity shows relevant position dependence with x-y surface coordinates and with z-distance. The device identification is realized via a 2-D model based in Fourier general equation. Using the Marquardt method the experimental flat surface device can be identified and the fitted parameters used to simulate the behavior of the experimental system. From the model, the effects of several dissipation configurations can be evaluated. Also, via the RC-analogy, a way to 3-D experimental devices is roughly described. This revised version was published online in July 2006 with corrections to the Cover Date.     

关于奇ATm核1/2+[411]转动带的系统分析

壳模型计算表明,1/2⁺[411]出现于¹⁵⁷Tm核的基态可能是由非轴对称形变造成的.但是新近从¹⁵⁷Yb衰变纲图给出的¹⁵⁷Tm低激发谱中,指认了一个建立在1/2⁺[411]带头上的基态转动带,并认为该带的性质是轴对称的,提取了该带的惯性参数与脱耦合参数.通过对奇ATm核1/2⁺[411]转动带的系统分析,强调了在¹⁵⁷Tm核中非轴对称γ自由度效应的重要性.     

关于智能电度表的误差分析与修正

本文详细介绍了多功能智能电度表在研制过程中，分析与修正了由计算机采样与计算所引起的电量值误差的原因，并由此研制出一种多功能智能电度表，以及一种简单易行的误差修正的编程算法。     

析氢反应动力学的交流阻抗法研究

利用交流阻抗法测定析氢电化学动力学参数，得到与极化曲线法一致的结果，为确定复杂析氢过程速率的决定步骤提供了判据。     

抽样调查中最佳测量次数的确定

现场抽样调查中，由于测量误差的存在，使得所测变量实测值的方差增大，通过增加每个体的测量次数可以控制测量误差，但这样每个体调查费用增大。本文对测量信度Ｒ，每个体测量次数ｍ与相应所需的样本含量ｎｍ、调查费用Ｔｎ的关系进行了探讨，并介绍了如何根据Ｒ，及每个体测量费用占其总费用构成比Ｃ，确定最佳测量次数ｍ值，以达到最佳控制调查费用的目的，这对我们在大型现场调查中进行经济效益分析具有重大的理论指导意义。     

SDH中泊松分布下误块率与误码率的关系分析

本文较详细地介绍了ＳＤＨ中的ＢＩＰ误码校验方式，推导了泊松分布下，ＢＩＰ误块率与误码率的一般关系式，给出了ＳＤＨ中几种典型的误块率与误码率的关系曲线，并做了计算机模拟验证     

一种新的$1/f$过程小波模型

给出了一种新的二进小波1/f过程模型,从理论上证明了一类谱指数为H的近似1/f过程可通过一簇平稳随机过程产生.由于所提方法利用了1/f过程小波系数的相关性,因而有效地减少了合成1/f过程的谱误差.数值实验结果表明,新模型很好地改进了已有模型.     

Discrete duality finite volume schemes for Leray−Lions−type elliptic problems on general 2D meshes

Discrete duality finite volume schemes on general meshes, introduced by Hermeline and Domelevo and Omnès for the Laplace equation, are proposed for nonlinear diffusion problems in 2D with nonhomogeneous Dirichlet boundary condition. This approach allows the discretization of non linear fluxes in such a way that the discrete operator inherits the key properties of the continuous one. Furthermore, it is well adapted to very general meshes including the case of nonconformal locally refined meshes. We show that the approximate solution exists and is unique, which is not obvious since the scheme is nonlinear. We prove that, for general W^?1,p′(Ω) source term and W^1‐(1/p),p(?Ω) boundary data, the approximate solution and its discrete gradient converge strongly towards the exact solution and its gradient, respectively, in appropriate Lebesgue spaces. Finally, error estimates are given in the case where the solution is assumed to be in W^2,p(Ω). Numerical examples are given, including those on locally refined meshes. © 2006 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq, 2007     

An approximate solution to the integral radiative transfer equation in an optically thick slab

We consider the problem of solving the integral form of the radiative transfer equation in an atmosphere with optical thickness τ₀?1. We propose two methods transforming this problem to a finite set of the independent problems of the same type set in an atmosphere with optical thickness much less then τ₀. The error estimates are derived. Copyright © 2007 John Wiley & Sons, Ltd.     

Estimating tail probabilities of heavy tailed distributions with asymptotically zero relative error

Efficient estimation of tail probabilities involving heavy tailed random variables is amongst the most challenging problems in Monte-Carlo simulation. In the last few years, applied probabilists have achieved considerable success in developing efficient algorithms for some such simple but fundamental tail probabilities. Usually, unbiased importance sampling estimators of such tail probabilities are developed and it is proved that these estimators are asymptotically efficient or even possess the desirable bounded relative error property. In this paper, as an illustration, we consider a simple tail probability involving geometric sums of heavy tailed random variables. This is useful in estimating the probability of large delays in M/G/1 queues. In this setting we develop an unbiased estimator whose relative error decreases to zero asymptotically. The key idea is to decompose the probability of interest into a known dominant component and an unknown small component. Simulation then focuses on estimating the latter ‘residual’ probability. Here we show that the existing conditioning methods or importance sampling methods are not effective in estimating the residual probability while an appropriate combination of the two estimates it with bounded relative error. As a further illustration of the proposed ideas, we apply them to develop an estimator for the probability of large delays in stochastic activity networks that has an asymptotically zero relative error.