高校素质教育探索

高等学校素质教育的核心问题,要为大众教育,学科本身要改革难的问题。学习怎样学习,在愉快中学习,学会学习就是学会生存。发展交叉学科,开展跨学科的课题研究,开辟新的研究领域,例如双语十数学的教学模式独具特色。重视培养学生创造性思维、设计、动手、人际交往四种能力,培养学生全面发展,培养学生艰苦奋斗,到西部创业的精神。     

Fuzzy K-means clustering models for triangular fuzzy time trajectories

We focus our attention on the classification of fuzzy time trajectories with triangular membership function, described by a given set of individuals. To this purpose, we adopt a fullyinformational approach, explicitly recognizing the informational nature shared by the ingredients of the classification procedure: the observed data (Empirical Information) and the classification model (Theoretical Information). In particular, by supposing that the informational paradigm has a fuzzy nature, we suggest three fuzzy clustering models allowing the classification of the triangular fuzzy time trajectories, based on the analysis of the cross sectional and/or longitudinal characteristics of their components (centers and spreads). Two applicative examples are illustrated.     

当代苏联小说叙述角度的新突破

当代苏联小说叙述角度的变化经历了一个复杂的过程.一个作家要想写好一部作品首先考虑确定叙述角度,这是选择和观察现实的立足点.随着苏联当代小说的丰富与发展,叙述角度也逐渐有了新的突破与创新,进而汇成了文学星空的万千气象.这种突破是对苏联当代小说的一大贡献.     

Validation of immigrants’ prior foreign learning as a framing practice

This paper explores the attempts by public officials and caseworkers to manage an overflow of immigrants in the labour market in Sweden. I draw on notions of framing and overflowing, inspired by Michel Callon's (1998) work on the organizing of market-based exchange relationships. I argue that validation is best understood as a framing practice, aimed at creating an understanding for the vastness of foreign experience – including skills and competence – of recent immigrants to Sweden, to make this experience measurable and manageable. Validation as a framing practice thereby exemplifies the widespread trust in framing as a way to normalise overflows – to turn overflows into normal flows. However, as the ethnography-inspired study reported here shows, repeated framing does not remove overflows; instead, it produces new and different types of overflows. In the conclusions, I emphasise the heavy investments required by validation in contrast with the fragility of the results it produces in the context of migration management.     

Validation of Nonparametric Two-sample Bootstrap in ROC Analysis on Large Datasets

The nonparametric two-sample bootstrap is applied to computing uncertainties of measures in receiver operating characteristic (ROC) analysis on large datasets in areas such as biometrics, speaker recognition, etc. when the analytical method cannot be used. Its validation was studied by computing the standard errors of the area under ROC curve using the well-established analytical Mann–Whitney statistic method and also using the bootstrap. The analytical result is unique. The bootstrap results are expressed as a probability distribution due to its stochastic nature. The comparisons were carried out using relative errors and hypothesis testing. These match very well. This validation provides a sound foundation for such computations.     

A class of weighted dependence measures for bivariate failure time data

This paper considers a class of summary measures of the dependence between a pair of failure time variables over a finite follow-up region. The class consists of measures that are weighted averages of local dependence measures, and includes the cross-ratio-measure and finite region version of Kendall's τ; recently proposed by the authors. Two new special cases are identified that can avoid the need to estimate the bivariate survivor function and that admit explicit variance estimators. Nonparametric estimators of such dependence measures are proposed and are shown to be consistent and asymptotically normal with variances that can be consistently estimated. Properties of selected estimators are evaluated in a simulation study, and the method is illustrated through an analysis of Australian Twin Study data.     

Toward an integrated Bayesian network approach to measurement error detection and correction

In this article, the quality of data produced by national statistical institutes and by governmental institutions is considered. In particular, the problem of measurement error is analyzed and an integrated Bayesian network decision support system based on non-parametric Bayesian networks is proposed for its detection and correction. Non-parametric Bayesian networks are graphical models expressing dependence structure via bivariate copulas associated to the edges of the graph. The network structure and the misreport probability are estimated using a validation sample. The Bayesian network model is proposed to decide: (i) which records have to be corrected; (ii) the kind and amount of correction to be adopted. The proposed correction procedure is applied to the Banca d’Italia Survey on Household Income and Wealth and, specifically, the bond amounts are analyzed. Finally, the sensitivity of the conditional distribution of the true value random variable given the observed one to different evidence configurations is studied.     

Validation of the Australian Midwifery Standards Assessment Tool (AMSAT): A tool to assess midwifery competence

Background

There is no current validated clinical assessment tool to measure the attainment of midwifery student competence in the midwifery practice setting. The lack of a valid assessment tool has led to a proliferation of tools and inconsistency in assessment of, and feedback on student learning.

Income inequality,poverty and crime across nations

We examine the relationship between income inequality, poverty, and different types of crime. Our results are consistent with recent research in showing that inequality is unrelated to homicide rates when poverty is controlled. In our multi‐level analyses of the International Crime Victimization Survey we find that inequality is unrelated to assault, robbery, burglary, and theft when poverty is controlled. We argue that there are also theoretical reasons to doubt that the level of income inequality of a country affects the likelihood of criminal behaviour.     

Mitigating the Impact of Functional Dominance in Cross‐Functional Process Improvement Teams

Manufacturing process improvement teams often draw upon cross‐functional expertise. However, teams dominated by a single or few functions often do not achieve the desired interdisciplinary learning and cooperation, which in turn could negatively affect the performance of that cross‐functional team. Through an empirical analysis of 149 manufacturing process improvement teams in six SIC industrial categories, we show that even after controlling for several factors such as team size, number of functions, gender diversity, ethnicity, number of management levels, and geographic dispersion of team members, psychological safety of work environment fully mediates the relationship between functional dominance and team performance. We also confirm that a team leader possessing high interpersonal justice mitigates the deficiency of dominated teams and improves team performance by fostering a psychologically safe work environment. Our recommendation therefore is that when a dominated team is unavoidable due to the needed skill sets or other organizational considerations, to ensure success it is imperative that the firm chooses a team leader who can promote psychological safety by being just, and who can effectively encourage input from all functional team members and give them objective feedback.