打造长白山人口文化的意义与作用

吉林省打造长白山人口文化,是全面做好人口计生工作、统筹解决吉林人口问题的需要。打造长白山人口文化,是对吉林丰富的人口文化资源发掘和提炼的过程,是新型人口文化的构建过程,是现代人口计生工作文明形态的构建过程。它既是传统人口文化与现代文化的一次融合、碰撞与创新的过程,也是对以往文化"缺位"的人口计生工作模式的积极定位。因此,打造长白山人口文化具有重要的理论意义和现实意义。     

Pilot–pivotal trials for average bioequivalence

Before carrying out a full scale bioequivalence trial, it is desirable to conduct a pilot trial to decide if a generic drug product shows promise of bioequivalence. The purpose of a pilot trial is to screen test formulations, and hence small sample sizes can be used. Based on the outcome of the pilot trial, one can decide whether or not a full scale pivotal trial should be carried out to assess bioequivalence. This article deals with the design of a pivotal trial, based on the evidence from the pilot trial. A two-stage adaptive procedure is developed in order to determine the sample size and the decision rule for the pivotal trial, for testing average bioequivalence using the two one-sided test (TOST). Numerical implementation of the procedure is discussed in detail, and the required tables are provided. Numerical results indicate that the required sample sizes could be smaller than that recommended by the FDA for a single trial, especially when the pilot study provides strong evidence in favor of bioequivalence.     

对大数据统计设计的思考

本文认为大数据统计与三个问题有关：大数据发展趋向极限无穷,人类社会数据信息将发生什么变化？大数据发展会不会产生危害社会进步的数据垃圾？大数据即使是一场革命,那么作为数据科学的统计学脱胎换骨地继承与发展是什么？本文对此回答包括,提出大数据发展的统计设计观点,从理论和实践上做出了论证分析,并联系我国实际,探讨了我国大数据发展中的统计设计理论和内容要点。     

社会工作教学实验设计研究

社会工作实验课程的实验设计以学生操作能力的获得为目的,这样就与作为研究的实验设计迥异。教师进行实验设计的重点在于如何根据课堂内容,设计适当的课堂实验活动,将课堂体验与讲授有机结合,在讲授中巧妙地穿插体验活动。主要通过案例分析、情景模拟、角色扮演等方法,演练典型案例,提升社会工作实务技能,并借助单面镜、视频和音频采集处理系统等实验设备对演练过程进行观察、录制和回放,教师进行点评,角色扮演的双方同学反馈感受,同学之间互相讨论,使角色扮演者和观察者反思自己和他人的行动,关注自己的体验和选择,建构社会工作理论知识和实务操作能力,使学生从中获得专业成长。本文将参考了国外最新的实验室利用方法,从社会工作实验教学设计的角度出发,探索如何设计符合课堂内容,同时又能提高学生学习兴趣的实验,加强实验室的软实力建设,提高实验教学的效果。     

高校知识与技术创新中的知识产权信息管理系统建设

文章分析了高校知识与技术创新体系对知识产权信息管理的需求,并通过借鉴相关机构开发的知识产权信息管理系统,提出高校建立知识产权信息管理系统的设计思路.     

社会工作专业“实践教学系统”构想

社会工作是一门应用性的学科,是实务性、操作性取向的专业。社会工作专业人才除了具备一般社会科学和社会工作专业的理论和知识之外,还应树立社会工作的价值理念和掌握社会工作的方法、技能。这就要求必须强化社会工作实务教学,使之贯穿整个社会工作专业教学过程。本文分析和反思了目前影响社会工作专业实践教学实效的问题,从社会工作专业实务性特征入手探讨了＂角色—方式—目标＂相结合的社会工作实践教学系统的设计。该系统通过将＂实验型＂实习模式、＂项目化＂实习模式及＂分类分层化＂实习模式合理、有机地整合起来,为学生提供了适宜的实习条件。     

Revenue Management in Order‐Driven Production Systems

This article investigates the effectiveness of a tactical demand‐capacity management policy to guide operational decisions in order‐driven production systems. The policy is implemented via a heuristic that attempts to maximize revenue by selectively accepting or rejecting customer orders for multiple product classes when demand exceeds capacity constantly over the short term. The performance of the heuristic is evaluated in terms of its ability to generate a higher profit compared to a first‐come‐first‐served (FCFS) policy. The policies are compared over a wide range of conditions characterized by variations in both internal (firm) and external (market) factors. The heuristic, when used with a Whole Lot order‐processing approach, produces higher profit compared to FCFS when profit margins of products are substantially different from each other and demand exceeds capacity by a large amount. In other cases it is better to use the heuristic in conjunction with the Split Lot order‐processing approach.     

Fractional Factorial Designs for Model-Based Evaluation of Customer Preferences

In this article, we explore the connection between Conjoint Analysis (CA) and a recent theory for minimum size orthogonal fractional factorial design generation (Fontana, 2013 Fontana , R. ( 2013 ). Algebraic generation of minimum size orthogonal fractional factorial designs: an approach based on integer linear programming . Computat. Statist. 28 : 241 – 253 .[Crossref], [Web of Science ®] , [Google Scholar]).

We show how searching for a minimum size OFFD that satisfies a set of constraints, expressed in terms of orthogonality between simple and interaction effects, is equivalent to solving an integer linear programming problem. It is worth noting that the methodology puts no restriction either on the number of levels of each factor or on the orthogonality constraints and so it can be applied to a very wide range of designs, including mixed orthogonal arrays. An algorithm, that has been implemented in SAS/IML, is briefly described.

The use of this algorithm during the design stage of a generic CA is shown in two applications.     

Blocking in two-level non-regular fractional factorial designs

In this paper we consider screening experiments where a two-level fractional factorial design is to be used to identify significant factors in an experimental process and where the runs in the experiment are to occur in blocks of equal size. A simple method based on the foldover technique is given for constructing resolution IV orthogonal and non-orthogonal blocked designs and examples are given to illustrate the process.     

Improving predictive inference under covariate shift by weighting the log-likelihood function

A class of predictive densities is derived by weighting the observed samples in maximizing the log-likelihood function. This approach is effective in cases such as sample surveys or design of experiments, where the observed covariate follows a different distribution than that in the whole population. Under misspecification of the parametric model, the optimal choice of the weight function is asymptotically shown to be the ratio of the density function of the covariate in the population to that in the observations. This is the pseudo-maximum likelihood estimation of sample surveys. The optimality is defined by the expected Kullback–Leibler loss, and the optimal weight is obtained by considering the importance sampling identity. Under correct specification of the model, however, the ordinary maximum likelihood estimate (i.e. the uniform weight) is shown to be optimal asymptotically. For moderate sample size, the situation is in between the two extreme cases, and the weight function is selected by minimizing a variant of the information criterion derived as an estimate of the expected loss. The method is also applied to a weighted version of the Bayesian predictive density. Numerical examples as well as Monte-Carlo simulations are shown for polynomial regression. A connection with the robust parametric estimation is discussed.