遗传算法中交叉操作的两种改进方法

通过分析交叉算子，提出了分别与模拟退火算法以及神经网络相结合的改进型遗传算法，改进型遗传算法的收敛性能远远优于标准遗传算法。     

一种改进的多目标微遗传算法

本文在回顾多目标进化算法发展的基础上,首次引进一种新的交叉算子(多个体交叉)对已有的微遗传算法进行改进,提出了一种多亲微遗传算法(MPMGA).通过理论分析和实验测试中度量距阵值的比较两方面说明,多亲微遗传算法在一定程度上提高了MGA的效率,增加了解群的多样性,使解在Pareto目标域上的分布更加均匀,解的精度也有所提高.     

Crossover of distress due to work and family demands in dual-earner couples: A dyadic analysis

Abstract

Distress resulting from work and family overload is likely to be interdependent between partners, as both men and women increasingly participate in work and family tasks. We attempted to explain distress of both partners by looking at their work and family demands and the resulting time and energy deficits experienced by each partner. Furthermore, we investigated how time deficit, energy deficit and distress due to such demands crossover between partners. The study, which used a precise measurement of family demands, was based on a sample of both partners from 828 dual-earner couples in The Netherlands. The results showed that for both partners work and family demands increase time deficit and energy deficit. Energy deficit due to heavy demands resulted in more feelings of distress, whereas time deficit did not contribute significantly to distress. We found different patterns of crossover between male and female partners. Feelings of time deficit and energy deficit crossed over from the man to the woman, whereas feelings of distress crossed over from the woman to the man. These results indicate that the demands on each partner contribute to their own distress, as well as to their partner's distress, either through the crossover of energy deficit or through the crossover of distress     

The Far-Reaching Consequences of Job Insecurity: A Review on Family-Related Outcomes

Job insecurity (JI) appears a fairly stable job stressor in working life today and likely to impair employee well-being. This review article presents the key findings of studies examining the effects of perceived JI on family well-being (e.g., marital/parental role quality, work–family conflict). The results, based on 25 published peer-reviewed studies, suggest an association between JI and impaired family well-being. Thus, JI spills over into family life as proposed in the spillover theory of work–family interface. Furthermore, studies have found some evidence of crossover effects of JI from parents to children: parents’ JI relates to negative outcomes in children. These results support the view that JI is very likely a severe stressor not only for employees’ well-being and health but also for their families’ well-being. Limitations, future directions, and implications are also discussed.     

CONSTRUCTION OF CROSSOVER DESIGNS WITH CORRELATED ERRORS

Crossover experiments are widely used, particularly where a sequence of treatments is given to subjects. Correlations between observations on the same subject are therefore likely and should be considered in both the design and analysis of crossover experiments. This paper presents an algorithm for the generation of efficient crossover designs with autoregressive and linear variance structures. The algorithm has been implemented as a module in the experimental design generation package CycDesigN (Release 3.0; CycSoftware, Hamilton, New Zealand). Output from the algorithm is compared with earlier work. Some results are given from the analysis of a crossover experiment assuming correlated errors.     

Carryover negligibility and relevance in bioequivalence studies

The carryover effect is a recurring issue in the pharmaceutical field. It may strongly influence the final outcome of an average bioequivalence study. Testing a null hypothesis of zero carryover is useless: not rejecting it does not guarantee the non‐existence of carryover, and rejecting it is not informative of the true degree of carryover and its influence on the validity of the final outcome of the bioequivalence study. We propose a more consistent approach: even if some carryover is present, is it enough to seriously distort the study conclusions or is it negligible? This is the central aim of this paper, which focuses on average bioequivalence studies based on 2 × 2 crossover designs and on the main problem associated with carryover: type I error inflation. We propose an equivalence testing approach to these questions and suggest reasonable negligibility or relevance limits for carryover. Finally, we illustrate this approach on some real datasets. Copyright © 2015 John Wiley & Sons, Ltd.     

A generalization of the Grizzle model to the estimation of treatment effects in crossover trials with non-compliance

Compliance with one specified dosing strategy of assigned treatments is a common problem in randomized drug clinical trials. Recently, there has been much interest in methods used for analysing treatment effects in randomized clinical trials that are subject to non-compliance. In this paper, we estimate and compare treatment effects based on the Grizzle model (GM) (ignorable non-compliance) as the custom model and the generalized Grizzle model (GGM) (non-ignorable non-compliance) as the new model. A real data set based on the treatment of knee osteoarthritis is used to compare these models. The results based on the likelihood ratio statistics and simulation study show the advantage of the proposed model (GGM) over the custom model (GGM).     

Sample size determination for testing equality in Poisson frequency data under an AB/BA crossover trial

Assuming that the frequency of occurrence follows the Poisson distribution, we develop sample size calculation procedures for testing equality based on an exact test procedure and an asymptotic test procedure under an AB/BA crossover design. We employ Monte Carlo simulation to demonstrate the use of these sample size formulae and evaluate the accuracy of sample size calculation formula derived from the asymptotic test procedure with respect to power in a variety of situations. We note that when both the relative treatment effect of interest and the underlying intraclass correlation between frequencies within patients are large, the sample size calculation based on the asymptotic test procedure can lose accuracy. In this case, the sample size calculation procedure based on the exact test is recommended. On the other hand, if the relative treatment effect of interest is small, the minimum required number of patients per group will be large, and the asymptotic test procedure will be valid for use. In this case, we may consider use of the sample size calculation formula derived from the asymptotic test procedure to reduce the number of patients needed for the exact test procedure. We include an example regarding a double‐blind randomized crossover trial comparing salmeterol with a placebo in exacerbations of asthma to illustrate the practical use of these sample size formulae. Copyright © 2013 John Wiley & Sons, Ltd.     

Adjusting overall survival for treatment switches: commonly used methods and practical application

In parallel group trials, long‐term efficacy endpoints may be affected if some patients switch or cross over to the alternative treatment arm prior to the event. In oncology trials, switch to the experimental treatment can occur in the control arm following disease progression and potentially impact overall survival. It may be a clinically relevant question to estimate the efficacy that would have been observed if no patients had switched, for example, to estimate ‘real‐life’ clinical effectiveness for a health technology assessment. Several commonly used statistical methods are available that try to adjust time‐to‐event data to account for treatment switching, ranging from naive exclusion and censoring approaches to more complex inverse probability of censoring weighting and rank‐preserving structural failure time models. These are described, along with their key assumptions, strengths, and limitations. Best practice guidance is provided for both trial design and analysis when switching is anticipated. Available statistical software is summarized, and examples are provided of the application of these methods in health technology assessments of oncology trials. Key considerations include having a clearly articulated rationale and research question and a well‐designed trial with sufficient good quality data collection to enable robust statistical analysis. No analysis method is universally suitable in all situations, and each makes strong untestable assumptions. There is a need for further research into new or improved techniques. This information should aid statisticians and their colleagues to improve the design and analysis of clinical trials where treatment switch is anticipated. Copyright © 2013 John Wiley & Sons, Ltd.     

从“声乐跨界”现象看我国声乐艺术的发展趋势

从语义学角度对“跨界”进行了词源分析,揭示了“跨界”的内涵与本质,进而引向“声乐跨界”这一话题。通过对我国声乐跨界历史脉络的梳理,找到当代语境下声乐跨界的理论根基及其在当代的表象。依据我国当前的文化发展态势和艺术发展规律,洞见我国声乐的发展趋势,以利于理解声乐审美观念和声乐艺术行为。