关于有限群的可解性

利用极大子群的几乎正规的概念得到了有限群为可解群的若干充要条件．     

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.     

模糊语言的独特功能

本文对模糊语言的独特功能从日常生活、文学作品、科学医学三方面进行了探讨 ,从而阐明在自然语言中 ,模糊语言是绝对的、普遍的。语言的模糊性缘于客观事物本身的模糊性及人们对客观世界认识的不确定性。     

反Fuzzy子群的直积

1990年R.Biswas在[2]中提出了反Fuzzy子群的概念.在此基础上本文相应定义了反Fuzzy子群的直积.接着讨论了其包括正规、共轭情况下的若干性质.此外,还给出了直积μ_1×μ_2是G×G上的反Fuzzy子群的一个充要条件.     

一种改进的图像模糊增强法

基于医学图像对比度差以致正常组织和病态组织难以区分,本文在讨论了Pal.King模糊增强的基础上,对模糊算法进行了改进,改进后的模糊算法效果明显,能增强图像细微细节,提高图像的对比度,改善图像视觉效果,提高诊断的准确性。     

Diverging Paths? A Comparative Look at Childcare Policies in Japan,South Korea and Taiwan

This article compares state policies to support childcare in Japan, South Korea and Taiwan, using fuzzy set ideal type analysis to determine the nature of institutional arrangements with respect to labour, money and time provisions. We then note their implications for familialization and defamilialization in the three countries. Our analysis suggests a common pattern towards the increased use of financial support amongst the three countries over time; however, this commonality does not mean their childcare policies are converging, as the financial supports differ in focus, with Japan concentrating on familialization by valuing family care, and Korea exclusively employing policy to facilitate the use of market‐based care services. For its part, Taiwan has been strengthening familialization by increasing the leave compensation to value time off to provide care. The different labour, money and time dimensions vis‐à‐vis the familialization/defamilialization matrix suggest varying implications of institutional arrangements for gender.     

Construction of Fuzzy Control Charts Based on Weighted Possibilistic Mean

The problem of constructing control charts for fuzzy data has been considered in literature. The proposed transformation approaches and direct fuzzy approaches have their advantages and disadvantages. The representative values charts based on transformation methods are often recommended in practical application. For representing a fuzzy set by a crisp value, the weight of importance of the members assigned with some membership levels in a fuzzy set should be considered, and the possibility theory can be employed to deal with such problem. In this article, we propose to employ the weighted possibilistic mean (WPM), weighted interval valued possibilistic mean (WIVPM) of fuzzy number as a sort of representative values for the fuzzy attribute data, and establish new fuzzy control charts with WPM and WIVPM. The performance of the charts is compared to the existing fuzzy charts with a fuzzy c-chart example via newly defined average number of inspection for variation of control state.     

2阶子群均共轭置换的4p2及4pq阶群

子群H为G的共轭置换子群是指日满足对G中任意元素g均成立HgH=HHg，记为H〈c-pG．本文利用共轭置换来刻画2阶子群均共轭置换的有限群，得到具有该特性的4p2及4pg阶群的结构分类．     

Development of predictive signatures for treatment selection in precision medicine with survival outcomes

For survival endpoints in subgroup selection, a score conversion model is often used to convert the set of biomarkers for each patient into a univariate score and using the median of the univariate scores to divide the patients into biomarker‐positive and biomarker‐negative subgroups. However, this may lead to bias in patient subgroup identification regarding the 2 issues: (1) treatment is equally effective for all patients and/or there is no subgroup difference; (2) the median value of the univariate scores as a cutoff may be inappropriate if the sizes of the 2 subgroups are differ substantially. We utilize a univariate composite score method to convert the set of patient's candidate biomarkers to a univariate response score. We propose applying the likelihood ratio test (LRT) to assess homogeneity of the sampled patients to address the first issue. In the context of identification of the subgroup of responders in adaptive design to demonstrate improvement of treatment efficacy (adaptive power), we suggest that subgroup selection is carried out if the LRT is significant. For the second issue, we utilize a likelihood‐based change‐point algorithm to find an optimal cutoff. Our simulation study shows that type I error generally is controlled, while the overall adaptive power to detect treatment effects sacrifices approximately 4.5% for the simulation designs considered by performing the LRT; furthermore, the change‐point algorithm outperforms the median cutoff considerably when the subgroup sizes differ substantially.     

Model averaging for treatment effect estimation in subgroups

In many clinical trials, biological, pharmacological, or clinical information is used to define candidate subgroups of patients that might have a differential treatment effect. Once the trial results are available, interest will focus on subgroups with an increased treatment effect. Estimating a treatment effect for these groups, together with an adequate uncertainty statement is challenging, owing to the resulting “random high” / selection bias. In this paper, we will investigate Bayesian model averaging to address this problem. The general motivation for the use of model averaging is to realize that subgroup selection can be viewed as model selection, so that methods to deal with model selection uncertainty, such as model averaging, can be used also in this setting. Simulations are used to evaluate the performance of the proposed approach. We illustrate it on an example early‐phase clinical trial.