DRTC＋＋：一个面向对象的分布式实时程序设计语言

提出了一个面向对象的分布式实时程序设计语言ＤＲＴＣ＋＋。它是在Ｃ＋＋语言的基础上进行了扩充，增加了分布功能和通信功能，引入了活跃对象、共享对象、活跃对象的时间封装机制、对象的访问权限等功能。ＤＲＴＣ＋＋语言有简洁的文法和清晰的语义。     

重塑大学生就业观

随着我国高等教育事业的发展 ,高校的不断扩招 ,就业形势越来越严峻。“先就业 ,后择业 ,再创业”的择业观为各高校所倡行 ,但这种择业观中隐含了不少弊病。从目前我国高校就业形势来看我们认为应当从社会要求、诚信教育、职业理想及规划等方面对学生进行引导和教育 ,在此基础上秉承“先择业 ,后就业 ,再择岗”的择业观 ,才比较符合现实。     

绿色带型工业城构想

我国城市空气污染与城市工业规划密切相关。因此，新建或改建中小城市的工业规划区域，决不能再走“工业污染城市”的老路，应以科学发展观和可持续发展的理念，在总结了有关城市工业污染教训的基础上，特别是吸取了天津开发区工业社会化服务中心建设的经验，按照新的规划要求，提出了工业与城市同步发展的无有害气体污染的新型绿色带型工业城的构想。     

基于VB的计算机考试系统的设计与实现

介绍了网络环境下的基于Visual Basic计算机考试系统的基本组成和功能结构,同时,就题库的建立和管理、随机成卷系统和评分系统等研制的难点进行了分析,并针对其中的关键技术,提出相应的解决方法。     

Performance measurement and classification data in DEA: Input-oriented model

This paper presents an improved efficiency measurement tool by modifying the existing data envelopment analysis methodology to permit the incorporation of expert knowledge. A previous paper examined the inclusion of such knowledge within the additive model. This information appeared in the form of a binary classification of a subset of the decision making units under study (e.g. good versus poor performers). In the current paper, we extend this logic to the input-oriented radial projection model. We demonstrate that the inclusion of this and other forms of expert judgment can improve the performance of the DEA tool in the sense that the efficiency scores are more in line with expert/management beliefs.     

Conditional Likelihood Estimators for Hidden Markov Models and Stochastic Volatility Models

ABSTRACT.  This paper develops a new contrast process for parametric inference of general hidden Markov models, when the hidden chain has a non-compact state space. This contrast is based on the conditional likelihood approach, often used for ARCH-type models. We prove the strong consistency of the conditional likelihood estimators under appropriate conditions. The method is applied to the Kalman filter (for which this contrast and the exact likelihood lead to asymptotically equivalent estimators) and to the discretely observed stochastic volatility models.     

Improved Monte Carlo inference for models with additive error

Some statistical models defined in terms of a generating stochastic mechanism have intractable distribution theory, which renders parameter estimation difficult. However, a Monte Carlo estimate of the log-likelihood surface for such a model can be obtained via computation of nonparametric density estimates from simulated realizations of the model. Unfortunately, the bias inherent in density estimation can cause bias in the resulting log-likelihood estimate that alters the location of its maximizer. In this paper a methodology for radically reducing this bias is developed for models with an additive error component. An illustrative example involving a stochastic model of molecular fragmentation and measurement is given.     

合作处理中的团队透明性

对合作处理中的一些基本概念给出了明确的定义，并提出了一个有用的合作团队的模型。模型中的团队代理是实现透明性的依托，在此对其特性、行为及其构造作了描述。把合作团队的透明性分解为环境透明和编程透明，并给出两种进明性在ＯＳＥｗａｒｅ中的实现方法。     

基于二阶段随机规划的城市医疗废弃物回收网络设计

城市医疗废弃物日益增加,且回收需求量受诸多因素的影响,难以准确预测,假定回收需求为确定值的医疗废弃物网络优化设计不能与实际需求相匹配。本文考虑了离散随机参数环境下,医疗回收网络设计中选址规划、分配计划及运输规划的协同优化问题,建立了以选址成本、运输成本最小为目标,设施与车辆能力限制为约束的二阶段随机规划模型。根据模型特点,设计了基于Benders decomposition的求解算法,同时,设计了一系列加速技术用于提高算法的求解效率。最后,以国内某城市医疗回收网络为背景设计算例,检验本文模型和求解策略的可行性和有效性。结果表明：相比确定性规划,随机规划的解能够节约总成本,结合一系列加速技术的Benders decomposition方法比CPLEX与纯的Benders decomposition更有优势。     

用线性互补及二次规划理论分析市场均衡问题

本文讨论了一类完全竞争条件下的市场均衡问题,供给方的生产特征用线性规划模型进行刻划,市场需求函数源于一般经济意义下的模型,它是一系列相互独立的价格变量的函数．我们将此问题归结为线性互补问题,并依此讨论了均衡点的存在性．本文还讨论了一种用二次规划进行刻划的经济问题,并指出此二次规划的K－K－T条件等价于所讨论的线性互补问题．