CAI——信息时代的教育手段

计算机辅助教学是信息时代的教育手段之一。本文介绍了CAI系统及其应用,并探讨了目前CAI在学校应用中存在的问题、发展策略,说明CAI在学校教育中的重要性和作用。     

Retirement patterns in Hong Kong: a censored regression analysis

This paper provides an overview of retirement patterns in Hong Kong on the basis of limited data. A censored regression model is used to infer the retirement age from people‘s current retirement status and their current age. This model is equivalent to a restricted probit model, and the interpretation of parameters is straightforward. The results clearly show a negative income effect on the retirement decision. The retirement age seems to be positively related to lifetime earnings but negatively related to the rate of decline of earnings with age. JEL classification: C24, J14, J26 Received May 6, 1996 / Accepted February 5, 1997     

Modeling household fertility decisions with generalized Poisson regression

This paper models household fertility decisions by using a generalized Poisson regression model. Since the fertility data used in the paper exhibit under-dispersion, the generalized Poisson regression model has statistical advantages over both standard Poisson and negative binomial regression models, and is suitable for analysis of count data that exhibit either over-dispersion or under-dispersion. The model is estimated by the method of maximum likelihood. Approximate tests for the dispersion and goodness-of-fit measures for comparing alternative models are discussed. Based on observations from the Panel Study of Income Dynamics of 1989 interviewing year, the empirical results support the fertility hypothesis of Becker and Lewis (1973). Received January 7, 1997 /Accepted April 3, 1997     

基于ARTⅡ网络的煤炭资源资产分类研究

本文建立了用于煤炭资源资产分类的ARTⅡ神经网络模型,编制了相应的计算机和软件,并将ARTⅡ模型与模糊分类模型和基于BP网络的分类模型进行了对比分析,实例运行结果表明,用ARTⅡ网络进行分类具有分类稳定、结果可靠等特点。     

信息不完全确定的区域产品模糊区间聚类方法

区域产品分类与选择是区域经济发展中最重要和最基础的工作.在产品选择与分类时,需要确定指标权系数和分类阈值等参数,这在实际应用中是比较困难的.针对这种情况,提出了一种信息不完全确定的区域产品模糊区间聚类方法.该方法构建了指标权系数信息不完全确定的最优模糊区间聚类模型,利用遗传算法和改进的FCM算法联合求解所得优化模型,得到指标权系数、最优聚类中心和最优划分,进而确定各产品所属类别.最后将该方法应用于某区域的产品分类和主导产品的确定中,实例计算说明该方法的可行性和有效性.     

基于学习动机感知的学生主体分类及其影响因素探究——以江苏省普通高校为实证

以大样本问卷调查为基础,采用多种数理统计方法,进行基于学习动机主观感知为学生主体类型划分及影响因素的研究。发现学习动机表征因素不止于内在和外在,还会体现在近期和远期、物质和精神、自我和他者等其他复杂要素上,而且还会受到入校时间、学校类型、性别以及地缘背景等因素影响。构建与学生主体需求相匹配的教育资源供给梯次和分类指导对促进高校教育具有重要意义。     

论老年人犯罪从宽暨免死的年龄标准与立法模式——以《刑法修正案(八)》为视角

老年人犯罪从宽的年龄标准应当有别于老年人免死的年龄标准。当前,中国对老年人犯罪从宽的年龄宜规定为"年满70周岁",而对老年人犯罪免死的年龄则宜规定为"年满75周岁"。对老年人犯罪从宽应当与对未成年人犯罪从宽相一致,统一规定为"应当从轻或者减轻处罚",而没有必要区分故意和过失犯罪分别规定。考虑到老年人犯罪免死的根据、刑罚目的和国际上的普遍做法,中国应当免除所有老年人犯罪的死刑,而不应有例外。     

提高辅导员工作信息化实践探索

本文在分析辅导员信息素养基础上,对提高辅导员工作信息化进行实践探索。     

Extending social security coverage to the rural sector in China

In late 2009 China launched an innovative, voluntary programme that by 2011 had extended pension coverage to 326.4 million people in the rural sector, including contributors and beneficiaries. It requires one contribution per year and provides a flat‐rate benefit and a contributions‐related benefit through a contributory individual account, with a government guarantee that the benefit will continue for life. The programme encourages participation of persons who do not pay income taxes, and thus have no tax incentive to participate, by providing substantial government subsidies. As a further incentive, old‐age benefits are provided to older parents when all their adult children participate in the contributory programme.     

Model-based clustering of multivariate skew data with circular components and missing values

Motivated by classification issues that arise in marine studies, we propose a latent-class mixture model for the unsupervised classification of incomplete quadrivariate data with two linear and two circular components. The model integrates bivariate circular densities and bivariate skew normal densities to capture the association between toroidal clusters of bivariate circular observations and planar clusters of bivariate linear observations. Maximum-likelihood estimation of the model is facilitated by an expectation maximization (EM) algorithm that treats unknown class membership and missing values as different sources of incomplete information. The model is exploited on hourly observations of wind speed and direction and wave height and direction to identify a number of sea regimes, which represent specific distributional shapes that the data take under environmental latent conditions.