Integrating Operational and Organizational Aspects in Interdependent Infrastructure Network Recovery

Managing risk in infrastructure systems implies dealing with interdependent physical networks and their relationships with the natural and societal contexts. Computational tools are often used to support operational decisions aimed at improving resilience, whereas economics‐related tools tend to be used to address broader societal and policy issues in infrastructure management. We propose an optimization‐based framework for infrastructure resilience analysis that incorporates organizational and socioeconomic aspects into operational problems, allowing to understand relationships between decisions at the policy level (e.g., regulation) and the technical level (e.g., optimal infrastructure restoration). We focus on three issues that arise when integrating such levels. First, optimal restoration strategies driven by financial and operational factors evolve differently compared to those driven by socioeconomic and humanitarian factors. Second, regulatory aspects have a significant impact on recovery dynamics (e.g., effective recovery is most challenging in societies with weak institutions and regulation, where individual interests may compromise societal well‐being). And third, the decision space (i.e., available actions) in postdisaster phases is strongly determined by predisaster decisions (e.g., resource allocation). The proposed optimization framework addresses these issues by using: (1) parametric analyses to test the influence of operational and socioeconomic factors on optimization outcomes, (2) regulatory constraints to model and assess the cost and benefit (for a variety of actors) of enforcing specific policy‐related conditions for the recovery process, and (3) sensitivity analyses to capture the effect of predisaster decisions on recovery. We illustrate our methodology with an example regarding the recovery of interdependent water, power, and gas networks in Shelby County, TN (USA), with exposure to natural hazards.     

On the Convergence of the Monte Carlo Maximum Likelihood Method for Latent Variable Models

While much used in practice, latent variable models raise challenging estimation problems due to the intractability of their likelihood. Monte Carlo maximum likelihood (MCML), as proposed by Geyer & Thompson (1992 ), is a simulation-based approach to maximum likelihood approximation applicable to general latent variable models. MCML can be described as an importance sampling method in which the likelihood ratio is approximated by Monte Carlo averages of importance ratios simulated from the complete data model corresponding to an arbitrary value of the unknown parameter. This paper studies the asymptotic (in the number of observations) performance of the MCML method in the case of latent variable models with independent observations. This is in contrast with previous works on the same topic which only considered conditional convergence to the maximum likelihood estimator, for a fixed set of observations. A first important result is that when is fixed, the MCML method can only be consistent if the number of simulations grows exponentially fast with the number of observations. If on the other hand, is obtained from a consistent sequence of estimates of the unknown parameter, then the requirements on the number of simulations are shown to be much weaker.     

一类带有分布参数系统的最佳控制

本文给出一类非均匀弦的横向振动的最佳控制，推广了P C Park的结果。这一结果同样适用于同类型振动问题。     

无抵触理论与我国公共英语教学

将无抵触理论应用于公共英语教学，可以对外语学习活动进行设计，使学习者水平与任务的难度相当、培养语言学习兴趣、加强师生交流、确保学习者获得学习主动权等，使其在学习过程中体验到巨大乐趣，进入以注意力高度集中和全身心投入为特征的无抵触心理状态，提高学习效率。     

约束优化问题的异步并行拟牛顿方法

提出了一种求解等式约束优化问题的异步并行拟牛顿方法 .若假设目标函数 f和约束函数h至少三次连续可微 ,且△h(x)对任意x∈Rn 均为满秩矩阵 ,证明了所提出的异步并行算法是 q—超线性收敛的 .     

网络工期成本优化技术

本文提出利用列表和在表上逐步进行修改,最终得到工期成本优化问题的最优解的方法。该方法的特点是直观、易于操作。     

A study of simulated annealing and a revised cascade algorithm for image reconstruction

We describe an image reconstruction problem and the computational difficulties arising in determining the maximum a posteriori (MAP) estimate. Two algorithms for tackling the problem, iterated conditional modes (ICM) and simulated annealing, are usually applied pixel by pixel. The performance of this strategy can be poor, particularly for heavily degraded images, and as a potential improvement Jubb and Jennison (1991) suggest the cascade algorithm in which ICM is initially applied to coarser images formed by blocking squares of pixels. In this paper we attempt to resolve certain criticisms of cascade and present a version of the algorithm extended in definition and implementation. As an illustration we apply our new method to a synthetic aperture radar (SAR) image. We also carry out a study of simulated annealing, with and without cascade, applied to a more tractable minimization problem from which we gain insight into the properties of cascade algorithms.     

山西常家兴衰与人力资源优化

“常家”兴衰与人力资源的演变有着密切关系 ,常家在优化人力资源方面的一些主要措施 ,揭示出人力资源与经济发展是密不可分的。面对现代经济发展中遇到的种种挑战 ,更让我们认识到重视人力资源优化的重要性。以史为鉴 ,给现代人以很多启示。     

Web数据库性能调优(英文)

提出了一种基于Web数据库系统设计、实现和性能调优的新方法,该方法包括由RDBMS配置优化、应用模式设计优化和编程优化。通过内存、分段、磁盘参数和时间相关参数的优化可以设置一个好的RDBMS运行环境。在编程时,通过减少与后台连接和断开操作、建立和使用索引、多用存储过程和优化SQL语句可以优化系统性能。在应用设计时,通过优化应用逻辑和降低规范化可以大大地改善系统性能。     

论我国农业信贷资金的市场化效用

从农业生产主体的比较利益与经营风险分析入手，对农业市场化过程中信贷资金效用进行了深入研究，并针对我国农业经济发展的现状，提出了有关我国农业信贷资金体系建设以及农业生产资源配置等项工作的若干意见和建议。