“过”引申用法的认知分析

运用认知语言学的理论对汉语“过”的基本语义结构进行形象的图示 ,对其基本引申用法做出统一的解释 ,并着重阐明、辨析表完结的体助词“过1 ”和表经历的体助词“过2 ”的意义和用法 ,指出对二者进行区分的必要性。     

播出服务器磁盘I/O与缓存性能分析

针对电视台专业播出服务器在播出质量和播出性能上的高要求,提出了(s,S)策略下读数据缓存和复用缓存与节目数量、节目数据速率、磁盘性能、ASI卡缓存大小的关系。在此基础上进行的实验结果表明:分配给节目播出的读数据和复用缓存并不是越大越好,而是有一个较优的范围。据此可对服务器的资源分配进行优化。     

具有正确收敛性的EM算法在电子政务中的应用

将具有正确收敛性的EM算法应用到电子政务系统中,可最大限度地找到与丢失数据相似的数值,进而保证有效地进行数据挖掘.     

双权值最短路径问题的一种解决算法

物流配送方案中,费用、时间是客户最关心的两个问题。物流企业需要基于这两个客户所关心的问题,提出一套低成本的物流配送方案。本文探求使用费用、时间双权值有向图最短路径问题,解决这种配送方案,并进行算法的时间复杂度分析。     

Multivariate Life Testing in Variably Scaled Environments

This paper examines modeling and inference questions for experiments in which different subsets of a set of k possibly dependent components are tested in r different environments. In each environment, the failure times of the set of components on test is assumed to be governed by a particular type of multivariate exponential (MVE) distribution. For any given component tested in several environments, it is assumed that its marginal failure rate varies from one environment to another via a change of scale between the environments, resulting in a joint MVE model which links in a natural way the applicable MVE distributions describing component behavior in each fixed environment. This study thus extends the work of Proschan and Sullo (1976) to multiple environments and the work of Kvam and Samaniego (1993) to dependent data. The problem of estimating model parameters via the method of maximum likelihood is examined in detail. First, necessary and sufficient conditions for the identifiability of model parameters are established. We then treat the derivation of the MLE via a numerically-augmented application of the EM algorithm. The feasibility of the estimation method is demonstrated in an example in which the likelihood ratio test of the hypothesis of equal component failure rates within any given environment is carried out.     

Quantitative Risk Assessment for Bovine Spongiform Encephalopathy in Low- or Zero-Prevalence Countries: The Example of Norway

A predictive case-cohort model is applied to Norwegian data to analyze the interaction between challenge and stability factors for bovine spongiform encephalopathy (BSE) during the period 1980-2010. For each year, the BSE risk in cattle is estimated as the expected number of cases. The age distribution of expected cases as well as the relative impact of different challenges is estimated. The model consists of a simple, transparent, and practical deterministic spreadsheet calculation model, in which the following country-specific inputs are entered: (i) annual imports of live cattle and meat and bone meal, (ii) age distribution of native cattle, and (iii) estimated annual basic reproduction ratio (R(0)) for BSE. Results for Norway indicate that the highest risk of BSE cases was in 1989, when a total BSE risk of 0.13 cases per year was expected. After that date, the year-to-year decrease in risk ranged between 3% and 47%, except for a secondary peak in 1994 at 0.06 cases per year. The primary peak was almost entirely (99%) attributable to the importation of 11 cattle from the United Kingdom between 1982 and 1986. The secondary peak, in 1994, originated mainly from the recycling of the U.K. imported cattle (92%). In 2006, the remaining risk was 0.0003 cases per year, or 0.001 per million cows per year, with a maximal age-specific incidence of 0.03 cases per million per year in 10-year-old cattle. Only 15% of the cases were expected in imported cattle. The probability of having zero cases in Norway in 2006 was estimated to be 99.97%. The model and results are compared to previous risk assessments of Norway by the EU.     

TiNi和TiNiCu记忆合金薄膜的温度记忆效应研究

在形状记忆合金的相变过程中,如果温度升至TS后停止升温,并降温至马氏体相变结束温度Mf以下,则在下一次完全相变循环中出现动力学停顿,而这一动力学停止温度点与上次的停止温度密切相关,这一现象被称为温度记忆效应。该文通过示差扫描量热法对TiNi和TiNiCu合金薄膜进行一次或连续几次不完全相变,系统地研究了温度记忆效应。结果表明,不仅温度记忆效应是形状记忆合金固有现象,而且温度记忆效应与马氏体变体间的弹性能及母相和马氏体相之间的共格应变密切相关。     

Simulation of right and left truncated gamma distributions by mixtures

We study the properties of truncated gamma distributions and we derive simulation algorithms which dominate the standard algorithms for these distributions. For the right truncated gamma distribution, an optimal accept–reject algorithm is based on the fact that its density can be expressed as an infinite mixture of beta distribution. For integer values of the parameters, the density of the left truncated distributions can be rewritten as a mixture which can be easily generated. We give an optimal accept–reject algorithm for the other values of the parameter. We compare the efficiency of our algorithm with the previous method and show the improvement in terms of minimum acceptance probability. The algorithm proposed here has an acceptance probability which is superior to e/4.     

集配货一体化VRP问题的具记忆功能的模拟退火算法研究

针对集配货一体化车辆路径问题的特性,建立了考虑配送车辆出行固定成本、车辆出发满载系数等因素的更加符合实际的数学模型;并设计了一种带记忆功能的模拟退火算法求解模型,确保输出结果是每次寻优的最优解;最后通过算例计算,结果表明,算法求解更优,稳定性更好,计算效率也较高。     

Bayesian inference for pairwise interacting point processes

Pairwise interacting point processes are commonly used to model spatial point patterns. To perform inference, the established frequentist methods can produce good point estimates when the interaction in the data is moderate, but some methods may produce severely biased estimates when the interaction in strong. Furthermore, because the sampling distributions of the estimates are unclear, interval estimates are typically obtained by parametric bootstrap methods. In the current setting however, the behavior of such estimates is not well understood. In this article we propose Bayesian methods for obtaining inferences in pairwise interacting point processes. The requisite application of Markov chain Monte Carlo (MCMC) techniques is complicated by an intractable function of the parameters in the likelihood. The acceptance probability in a Metropolis-Hastings algorithm involves the ratio of two likelihoods evaluated at differing parameter values. The intractable functions do not cancel, and hence an intractable ratio r must be estimated within each iteration of a Metropolis-Hastings sampler. We propose the use of importance sampling techniques within MCMC to address this problem. While r may be estimated by other methods, these, in general, are not readily applied in a Bayesian setting. We demonstrate the validity of our importance sampling approach with a small simulation study. Finally, we analyze the Swedish pine sapling dataset (Strand 1972) and contrast the results with those in the literature.