Maximum likelihood estimation of the parameters of a multiple step-stress model from the Birnbaum-Saunders distribution under time-constraint: A comparative study

The cumulative exposure model (CEM) is a commonly used statistical model utilized to analyze data from a step-stress accelerated life testing which is a special class of accelerated life testing (ALT). In practice, researchers conduct ALT to: (1) determine the effects of extreme levels of stress factors (e.g., temperature) on the life distribution, and (2) to gain information on the parameters of the life distribution more rapidly than under normal operating (or environmental) conditions. In literature, researchers assume that the CEM is from well-known distributions, such as the Weibull family. This study, on the other hand, considers a p-step-stress model with q stress factors from the two-parameter Birnbaum-Saunders distribution when there is a time constraint on the duration of the experiment. In this comparison paper, we consider different frameworks to numerically compute the point estimation for the unknown parameters of the CEM using the maximum likelihood theory. Each framework implements at least one optimization method; therefore, numerical examples and extensive Monte Carlo simulations are considered to compare and numerically examine the performance of the considered estimation frameworks.     

Pilot power optimization and coverage control in WCDMA mobile networks

In mobile networks using wideband code division multiple access (WCDMA), common pilot channel (CPICH) signals are used by mobile terminals for channel quality estimation, cell selection, and handover. The strength of the CPICH signal determines the coverage area of the cell, impacts the network capacity, and thereby the quality of service, and is therefore a crucial parameter in network planning and optimization. Pilot power is the most important parameter that allows us to control the strength of the CPICH signal. The more power is spent for pilot signals, the better coverage is obtained. On the other hand, a higher value of the pilot power level in a cell means higher pilot pollution in the network and less power available to serve user traffic in the cell. In this paper, we consider the problem of minimizing the total amount of pilot power subject to a coverage constraint. Our modeling and solution approaches are based on mathematical programming techniques. We present a basic model for pilot power optimization subject to a full coverage constraint as well as its extended version which allows us to study various coverage levels and to consider user traffic distribution over the network. We also propose an efficient algorithm that gives near-optimal solutions to the problem within a reasonable amount of time. We report our numerical experiments for three WCDMA networks of various sizes based on realistic planning scenarios and examine the effect of different levels of the required coverage degree on the total amount of pilot power.     

Coordinated Capacitated Lot‐Sizing Problem with Dynamic Demand: A Lagrangian Heuristic

Coordinated replenishment problems are common in manufacturing and distribution when a family of items shares a common production line, supplier, or a mode of transportation. In these situations the coordination of shared, and often limited, resources across items is economically attractive. This paper describes a mixed‐integer programming formulation and Lagrangian relaxation solution procedure for the single‐family coordinated capacitated lot‐sizing problem with dynamic demand. The problem extends both the multi‐item capacitated dynamic demand lot‐sizing problem and the uncapacitated coordinated dynamic demand lot‐sizing problem. We provide the results of computational experiments investigating the mathematical properties of the formulation and the performance of the Lagrangian procedures. The results indicate the superiority of the dual‐based heuristic over linear programming‐based approaches to the problem. The quality of the Lagrangian heuristic solution improved in most instances with increases in problem size. Heuristic solutions averaged 2.52% above optimal. The procedures were applied to an industry test problem yielding a 22.5% reduction in total costs.     

Generating Correlation Matrices With Specified Eigenvalues Using the Method of Alternating Projections

ABSTRACT

This article describes a new algorithm for generating correlation matrices with specified eigenvalues. The algorithm uses the method of alternating projections (MAP) that was first described by Neumann. The MAP algorithm for generating correlation matrices is both easy to understand and to program in higher-level computer languages, making this method accessible to applied researchers with no formal training in advanced mathematics. Simulations indicate that the new algorithm has excellent convergence properties. Correlation matrices with specified eigenvalues can be profitably used in Monte Carlo research in statistics, psychometrics, computer science, and related disciplines. To encourage such use, R code (R Core Team) for implementing the algorithm is provided in the supplementary material.     

“机械优化设计”课程教学改革

"机械优化设计"是一门研究生课程,结合研究生教学的特点,我们从教学大纲制定、教材编写、教学内容取舍着手,几年来不断补充更新教学内容及优化软件,改革教学手段、教学方法,注重多媒体及双语教学,注意提高研究生素质教学及创新能力培养,并在考试方法及提高学生实际操作能力等方面进行了教学改革实践探讨,取得了一定成果。     

Health economic modeling to support surgery management at a Swedish hospital

Elective surgery management typically deals with a queue of patients that have to be scheduled for surgery within a certain time frame, considering both medical and economic constraints. In order to prevent the patient queue and waiting times from growing, surgery management has to decide whether to temporarily increase patient throughput at the regional hospital or have some patients scheduled for surgery at another hospital. In Sweden, a newly passed law states that patients who decide to receive surgery should not have to wait more than 90 days before this surgery is carried out. Therefore, if a patient decides to apply the new law by requesting surgery within 90 days, the regional hospital is obliged to arrange and pay for either in-house surgery or surgery at another hospital. In this paper, we suggest an approach using simulation including optimization for modeling surgery management decisions. We study a case based on data from a General Surgery Department at a Swedish hospital and present our results as a health economic evaluation. The results indicate an increase in the mean waiting times for medium prioritized patients when the new law is applied.     

SEO算法在网站建设和优化方面的应用研究

通过对搜索引擎和SEO（Search Engine Optimization）算法的研究，分析搜索引擎的工作原理和SEO的具体实施过程。再用一实例阐述SEO算法在网站建设和优化方面的作用，即在不损害用户体验的情况下，提高搜索引擎排名，从而提高网站的访问量和营销效果，最终提升网站的传播能力和盈利能力。     

大弹涂鱼肝脏蛋白质双向电泳技术的建立及优化

通过对不同裂解液配方、等电聚焦程序和SDS-PAGE方式等的对比实验,建立和优化了大弹涂鱼肝脏蛋白质组双向电泳的相关技术体系。结果显示采用裂解液中添加Tris和TBP,聚焦时适当延长除盐时间,提高聚焦电压和功率(伏-小时),能显著提高双向电泳图谱的分辨率,MSOG程序进行双向电泳(Multi-strips on One Gel MSOG),提高了双向凝胶的匹配率及有效性,降低了人为修饰点的增加,匹配率高达90%。通过相关条件优化提高了大弹涂鱼肝脏蛋白双向电泳图谱的分辨率,为后续大弹涂鱼的毒理蛋白质组学研究提供技术保障。     

高负债与资本结构不合理的关系探析--兼论我国国有企业资本结构优化

资本结构是指权益资本与负债资本的比例关系,资本结构的核心问题就是负债问题.资本结构是一个动态的概念,考察资本结构合不合理不能仅从负债高低考虑,而应权衡各方面的因素综合分析.     

“费时低效”与语言习得——对优化大学英语教学方法的思考

不恰当的教学方法是造成大学英语教学“费时低效”现象的原因之一。在充分了解语言习得过程的基础上探索以该理论为指导原则的教学方法,“高效低耗”地培养学生实际运用语言能力,即尽量创造促进语言习得的教学环境,让第二语言的学得最大可能变为第一语言的习得,增加语言的输入量和输出量,使教学方法与教学目的达到最佳的匹配度,作到有的放矢,降低教学“成本”,增大教学的“有效”产出。