论奥斯古德对昆明高峣社区的人类学研究

1938年夏天,美国年轻学者科尼利尔斯·奥斯古德为了履行与燕京大学的合作计划,不远万里来到滇池西岸一个名不见经传的小村庄调查.1961年,他开启尘封的笔记本,整理旧资料,补充新文献,完成了<旧中国的农村生活:对云南高峣的社区研究>.70年过去,重温科尼利尔斯·奥斯古德的研究历程,我们仍会从中获得许多有益的启示.     

马克思与后现代主义"颠覆主体性"之比较

马克思与后现代主义都对传统主体概念进行了颠覆。在马克思那里 ,主体不再指自我意识或自我 ,而是渗透了历史性原则 ,是创造和规定人及产物的历史过程 ;其客观上表现为一定的社会关系和社会形态 ,主观上表现为人的社会历史存在。而后现代主义则反对主客二分 ,反对人类中心主义 ,反对寻求同一性 ,反对普遍主义 ,把以认识主体为核心的反映论作为批判的目标。这是两种不同的颠覆方式 ,但都宣判了传统主体概念的死亡。     

A simulation study of a discrete-time multiserver retrial queue with finite population

In this paper, we deal with a discrete-time multiserver retrial queue with finite population. Firstly, we study the Markov chain at the epochs immediately after slot boundaries making emphasis on the computation of its steady-state distribution. Then, the main performance measures are investigated. Besides, we simulate the waiting time of a customer in the retrial group under three different queueing policies. Some numerical examples are given to illustrate the analysis.     

A probablistic analysis for an optimal screening problem

Summary We consider a lotL formed byN apparently similar unitsW ₁,…,W _N, where each of theW _i may come from one of two different populationsP ₁ andP ₂;T ₁,…,T _N denote the corresponding lifetimes. The units fromP _i undergo a failure of kindi and their survival function isS _i (t). We assume that the failure rate function are known and that the units fromP ₁ are ?substandard?: λ ₁ (t)≥λ ₂ (t), ∀t≥0. We want to putW ₁,…,W _N under a pre-operational test (burn-in test) in order to eliminate at least a great part of the substandard units and we face the problem of obtaining a rule for stopping the test under the assumption that, with the failure of a unit, it is possible to recognize the population from which the unit comes. Such a problem will be formalized as an optimal stopping problem for a suitably defined Markov process. Our study shall evidentiate some fundamental aspects of the problem and the role of the prior distribution of the (random) numberM ₀ of those units inL coming fromP ₁ (substandard). The latter distribution has a great influence on the form of the solution. This research was supported by the C.N.R. Project ?Statistica Bayesiana e Simulazione in Affidalità e Modellistica Biologica?.     

The impact of P.L. 93-641, the National Health Planning and Resources Development Act, upon health and mental health programming

Federal legislation regarding health care in the U.S. has increased rapidly in the past few years. A major law with potential far-reaching effects was enacted as a result of increasing legislation and rising health care costs. This law,The National Health Planning and Resources Development Act,has created a network of over 200 local, mostly nongovernment units, called health systems agencies. These agencies are responsible for areawide health planning, plan implementation, review and approval of federal health care expenditures for local programs, and facilities review. They will affect health and mental health programs at the local level. The article is directed to local health and mental health care providers who will, of necessity, deal directly with the local HSA's.     

K3中BOM的编制技巧

准确的基础资料是系统运行的前提.在ERP系统的使用中,基础资料一定要保证正确性、完整性和唯一性.BOM是系统最重要的基础资料之一,它的准确与否将直接影响MRP计划、生产投料、生产领料、成本计算等业务的正确性.为准确录入BOM的基础数据,在长期工作实践中,本人摸索出一些技巧,不敢私自独用,便拿出来与大家分享.     

A modified LGB method for detecting significant effects based on a half-normal probability plot

In analyzing data from unreplicated factorial designs, the half-normal probability plot is commonly used to screen for the ‘vital few’ effects. Recently, many formal methods have been proposed to overcome the subjectivity of this plot. Lawson (1998) (hereafter denoted as LGB) suggested a hybrid method based on the half-normal probability plot, which is a blend of Lenth (1989) and Loh (1992) method. The method consists of fitting a simple least squares line to the inliers, which are determined by the Lenth method. The effects exceeding the prediction limits based on the fitted line are candidates for the vital few effects. To improve the accuracy of partitioning the effects into inliers and outliers, we propose a modified LGB method (hereafter denoted as the Mod_LGB method), in which more outliers can be classified by using both the Carling’s modification of the box plot (Carling, 2000) and Lenth method. If no outlier exists or there is a wide range in the inliers as determined by the Lenth method, more outliers can be found by the Carling method. A simulation study is conducted in unreplicated $2^4$ designs with the number of active effects ranging from 1 to 6 to compare the efficiency of the Lenth method, original LGB methods, and the proposed modified version of the LGB method.     

Business reform outcomes: Why so different?

Post-crisis policy making increasingly focuses on doing business reforms. We argue that the effects of those reforms will be different across countries. To understand the reasons for the reform outcome divergence, we advance a novel firm-size distribution (FSDs) argument. At the center of the argument is the fact that FSDs are different across countries and stable over time. Then, if a given doing business reform induces firms of different size to grow differently, this will produce a variety of reform outcomes across countries. To advance the argument, we set up a tractable general equilibrium (GE) model and study how firms of different size grow after a doing business reform. The model predicts that larger firms will grow faster than smaller firms after the reform. The model predictions are tested on the Enterprise Surveys (ES) data, merged with the Doing Business indicators. We confirm that firms of different size grow differently after a Doing Business reform. Thus, based on the notable differences of firm size distributions across countries, identical reforms to start, operate and close a business will produce a variety of reform outcomes across countries.     

Missing value imputation method for disaster decision-making using K nearest neighbor

Due to destructiveness of natural disasters, restriction of disaster scenarios and some human causes, missing data usually occur in disaster decision-making problems. In order to estimate missing values of alternatives, this paper focuses on imputing heterogeneous attribute values of disaster based on an improved K nearest neighbor imputation (KNNI) method. Firstly, some definitions of trapezoidal fuzzy numbers (TFNs) are introduced and three types of attributes (i.e. linguistic term sets, intervals and real numbers) are converted to TFNs. Then the correlated degree model is utilized to extract related attributes to form instances that will be used in K nearest neighbor algorithm, and a novel KNNI method merging with correlated degree model is presented. Finally, an illustrative example is given to verify the proposed method and to demonstrate its feasibility and effectiveness.