地震荷载作用下钢筋混凝土安全壳的可靠性分析

对秦山核电站的钢筋混凝土安全壳进行了地震可靠性分析．结构系统极限破坏的可靠度采用稳定构形法（ＳＣＡ）和三维有限元法的应力分析（ＦＥＭ）来估计．结构系统的破坏定义为所有可能的稳定构形破坏事件的交集．用２ＳＳＥ地震作为输入地震荷载．地面运动假设为具有田治见洪－金井清谱的零平均平稳高斯过程．基于在不同峰地面加速度下计算的条件破坏概率,给出了系统极限状态的破坏概率以及初始屈服时的年破坏概率．     

稳态光散射法测粒下限及其影响因素的讨论

在经典Ｍｉｅ散射理论基础上,讨论全方位稳态光散射法激光测粒仪测量粒径的下限及其影响因素,认为通过减小激光测粒仪的系统误差和增大探测的散射角范围,可降低测粒仪的测量下降。     

Interculturalism in Italian primary schools with a high concentration of immigrant students

The present article focuses on quantitative research carried out on a statistically representative sample of Italian primary schools with a high concentration of immigrant students. Research data show that schools with a higher number of immigrant students offer a greater number and a wider variety of intercultural initiatives. The presence of immigrant students serves as an effective stimulus in enhancing intercultural approaches. Furthermore, the opinions of head teachers about the proposal of ‘separate classes’ for immigrant students and the proposed ‘limit of 30% on the presence’ of immigrant students are negative. These judgements do not change in a statistically significant manner in relation to concentration of immigrant students: in particular, higher rates of immigrant students are not related to more positive opinions. Continuing education on intercultural issues is widely adopted, mainly on behalf of teachers and less often on behalf of head teachers and other school personnel. Finally, activities by ‘linguistic facilitators’ and ‘linguistic and cultural mediators’ are not significantly related to a decrease in perceived concern regarding problematic situations.     

Application of extreme value theory to the bec family of distributions

Arnold and Strauss (1988) derived a family of bivariate life distributions having the property that the conditional distributions are exponential. Asymptotic distributions for the marginal and bivariate extremes for this family of distributions are derived employing the asymptotic theory of extreme order statistics.     

Limit theorems for dependent Bernoulli variables with statistical inference

We consider a class of dependent Bernoulli variables where the conditional success probability is a linear combination of the last few trials and the original success probability. We obtain its limit theorems including the strong law of large numbers, weak invariance principle, and law of the iterated logarithm. We also derive some statistical inference results which make the model applicable. Simulation results are exhibited as well to show that with small sample size the convergence rate is satisfying and the proposed estimators behave well.     

A probabilistic approach to Wallis’ formula

We present an alternative proof of Wallis’ formula from the probabilistic point of view. Based on the classical central limit theorem, some discrete distributions with additive property, such as binomial, negative binomial, Poisson and multinomial distributions, are considered to derive π/2.     

A process capability index with reliable confidence intervals

A well-know process capability index is slightly modified in this article to provide a new measure of process capability which takes account of the process location and variability, and for which point estimator and confidence intervals do exist that are insensitive to departures from the assumption of normal variability. Two examples of applications based on real data are presented.     

Parameter Estimation for the Discrete Stable Family

The discrete stable family constitutes an interesting two-parameter model of distributions on the non-negative integers with a Paretian tail. The practical use of the discrete stable distribution is inhibited by the lack of an explicit expression for its probability function. Moreover, the distribution does not possess moments of any order. Therefore, the usual tools—such as the maximum-likelihood method or even the moment method—are not feasible for parameter estimation. However, the probability generating function of the discrete stable distribution is available in a simple form. Hence, we initially explore the application of some existing estimation procedures based on the empirical probability generating function. Subsequently, we propose a new estimation method by minimizing a suitable weighted L ²-distance between the empirical and the theoretical probability generating functions. In addition, we provide a goodness-of-fit statistic based on the same distance.     

Optimal hedging through limit orders

This article applies the methods of stochastic dynamic programming to a risk management problem, where an agent hedges her derivative position by submitting limit orders. Therefore, this model is the first, in the literature on optimal trading with limit orders, to handle a problem of hedging options or other derivatives. A hedging strategy is developed where both the size and the limit price of each order is optimally set.     

On LSE in regression model for long-range dependent random fields on spheres

We study the asymptotic behaviour of least squares estimators (LSE) in regression models for long-range dependent random fields observed on spheres. The LSE can be given as a weighted functional of long-range dependent random fields. It is known that in this scenario the limits can be non-Gaussian. We derive the limit distribution and the corresponding rate of convergence for the estimators. The results were obtained under rather general assumptions on the random fields. Simulation studies were conducted to support theoretical findings.