论知识管理的涵义及起因

本文从知识自身的“增长与过时”、知识是生产要素与消费自身、知识经济时代的体系支撑、现代理性决策对知识的需求、知识的垄断与共享 (生产与消费 ) 5个方面论述了知识管理的起因 ,阐述了人类为什么现在提出知识管理问题。给出了知识管理的定义。分析了知识管理的自然属性和社会属性     

房地产价格评估方法前沿动态及其应用研究

房地产评估活动是市场主体决策与交易行为达成的重要环节,正确有效的评估活动基于并依赖于科学合理的评估方法的运用。在系统梳理了房地产评估中的各类方法后,在比较和剖析传统评估方法局限性的基础上,对人工神经网络法、特征价格法、空间分析法、模糊逻辑法及自回归单整移动平均法（ARIMA）等前沿评估方法及其原理进行介绍,并通过相关案例引用及实证分析揭示其应用性,力争为客观评价房地产价格提供有效评估工具和奠定坚实理论基础。     

从人的社会属性看雷锋精神的当代价值简

学习雷锋精神首先要回答的就是为什么要学习雷锋精神和雷锋精神有无当代价值,本文从人的社会属性层面来回答这个问题。雷锋精神实质上是共产主义新型社会关系在思想方面的体现,学习雷锋精神是构建和谐社会关系的内在要求,是抵制市场经济负面作用的必然选择,是提升公民的思想道德素质、培育社会主义核心价值的重要途径,因此具有重大的现实意义和当代价值。     

Nonparametric Identification and Estimation of Nonadditive Hedonic Models

This paper studies the identification and estimation of preferences and technologies in equilibrium hedonic models. In it, we identify nonparametric structural relationships with nonadditive heterogeneity. We determine what features of hedonic models can be identified from equilibrium observations in a single market under weak assumptions about the available information. We then consider use of additional information about structural functions and heterogeneity distributions. Separability conditions facilitate identification of consumer marginal utility and firm marginal product functions. We also consider how identification is facilitated using multimarket data.     

论我国节能服务合同的法律属性

节能服务合同是合同能源管理实施中的基础性合同,节能服务公司在合同期限届满时应当无偿向用能单位移交项目设备及其所有权,因而对节能服务合同的属性存有争议。为此,必须厘清合同能源管理实施中所涉及的交易关系,分析合同能源管理运营中设备所有权的归属,确定节能服务合同为技术合同的属性,在我国现有法律体系框架范围内,有效地调整合同能源管理以及节能服务合同关系。     

How to build nomogram for type 2 diabetes using a naïve Bayesian classifier technique

In this study, we introduced a method for building a Bayesian nomogram and proposed an appropriate nomogram for type 2 diabetes (T2D) using data from 13,474 subjects collected from the 2013–2015 Korean National Health and Nutrition Examination Survey (KNHANES) data. We identified risk factors related to T2D, proposed a visual nomogram for T2D from a naïve Bayesian classifier model, and predicted incidence rates. Additionally, we computed confidence intervals for the influence of risk factors (attributes) and verified the proposed Bayesian nomogram using a receiver operating characteristic curve. Finally, we compared logistic regression and the Bayesian nomogram for T2D. The results of the analysis of the T2D data showed that the most influential factor among all attributes in the Bayesian nomogram was age group, and the highest risk factor for T2D incidence was cardiovascular disease. Dyslipidemia and hypertension also had significant impacts on T2D incidence while the effects of sex, smoking status, and employment status were relatively small compared to those of other variables. Using the proposed Bayesian nomogram, we can easily predict the incidence rate of T2D in an individual, and treatment plans can be established based on this information.     

Estimation of a rare sensitive attribute for two-stage randomized response model in probability proportional to size sampling using Poisson probability distribution

This paper addresses the estimation of the mean number of individuals in the population who possess a rare sensitive attribute using Poisson distribution for the situations of (i) clustered population and (ii) stratified population with clusters are strata units. Properties of the proposed estimation procedures have been discussed when the proportion of a rare unrelated non-sensitive attribute is assumed to be known as well as unknown. Empirical studies are carried out to support the theoretical results which showed dominance over Lee et al. [Estimation of a rare sensitive attribute in probability proportional to size measures using Poisson distribution. Statistics (Ber). 2014;48(3):685–709] estimation procedures.     

A binomial CUSUM chart for detecting large shifts in fraction nonconforming

This article studies a unique feature of the binomial CUSUM chart in which the difference (d _t ?d ₀) is replaced by (d _t ?d ₀)² in the formulation of the cumulative sum C _t (where d _t and d ₀ are the actual and in-control numbers of nonconforming units, respectively, in a sample). Performance studies are reported and the results reveal that this new feature is able to increase the detection effectiveness when fraction nonconforming p becomes three to four times as large as the in-control value p ₀. The design of the new binomial CUSUM chart is presented along with the calculation of the in-control and out-of-control Average Run Lengths (ARL₀ and ARL₁).     

Analysis of bivariate dichotomous data from a stratified two-stage cluster sample

In the health and social sciences, researchers often encounter categorical data for which complexities come from a nested hierarchy and/or cross-classification for the sampling structure. A common feature of these studies is a non-standard data structure with repeated measurements which may have some degree of clustering. In this paper, methodology is presented for the joint estimation of quantities of interest in the context of a stratified two-stage sample with bivariate dichotomous data. These quantities are the mean value π of an observed dichotomous response for a certain condition or time-point and a set of correlation coefficients for intra-cluster association for each condition or time period and for inter-condition correlation within and among clusters. The methodology uses the cluster means and pairwise joint probability parameters from each cluster. They together provide appropriate information across clusters for the estimation of the correlation coefficients.     

Sample size requirements for rare or abundant attribute sampling

Two approximation procedures to determine required sample size for a Fixed width binomial confidence interval are given and compared to exact calculations as well as the normal and Poisson approximations. The approximation procedures are found to be quite simple but very accurate for estimating sample sizes for either rare or abundant attributes.