Design optimization using ANOVA

This paper describes the design optimization of a robot sensor used for locating 3-D objects employing the Taguchi method in a computer simulation scenario. The location information from the sensor is to be utilized to control the movements of an industrial robot in a 'pick-and-place' or assembly operation. The Taguchi method, which is based on the Analysis-of-Variance (ANOVA) approach, is utilized to improve the performance of the sensor over a wider operating range. A review of the Taguchi method is presented along with step-by-step implementation details to identify and optimize the design parameters of the sensor. The method allows us to gauge the impact of various interactions present in the sensor system exclusively and permits us to single out those factors that have a dominant influence on the overall performance of the sensor. The investigation suggests that the Taguchi method is a more structured and efficient approach for achieving a robust design compared with the classical full factorial design approach.     

A note on inverse estimation in non-linear models

The problem of estimating the value of an x variable for a given proportion of an observed value of the y variable is consdered for a non-linear model. Asymptotic confidence limits are obtained and an application of the method is illustrated witreal data.     

维吾尔族大学生的民族刻板印象

本研究采用问卷调查法,对维吾尔族大学生的民族刻板印象进行了调查。被试对汉族人和泉古族人形成的刻板印象以正面与中性的印象为主。被试认为,汉族人最主要的10项特征是爱吃菜、勤劳、团结、小气、自私、爱国、朴实、节俭、爱喝酒和追求享受;蒙古族人最主要的10项特征是勇敢、凝聚力强、游牧、爱喝酒、野蛮、高大强壮、擅长摔跤、好客、好斗和能歌善舞。     

Job Insecurity: Differential Effects of Subjective and Objective Measures on Life Satisfaction Trajectories of Workers Aged 27–30 in Germany

Job insecurity has become increasingly evident in European countries in recent years. In Germany, legislation has increased insecurity through erosion of the standard employment relationship. Fixed-term contracts are central to definitions of insecurity based on atypical or precarious work but there is still limited understanding of what creates insecurity and how it affects workers. Drawing on Bourdieu’s thesis that “insecurity is everywhere”, the relationships between subjective and objective measures of insecurity are examined for their impact on the 5-year trajectories of life satisfaction of men and women in the age group 27–30. Latent growth curve analysis of data from the German Socio-Economic Panel for 2010–2014 highlights the adverse and lasting effects of subjective concerns about job insecurity on life satisfaction trajectories. This association cuts across educational groups, with far reaching implications as subjective concerns about job security permeate young worker’s lives well beyond the objective condition of being employed on a fixed-term contract.     

Application of the characterization theory to the mixture model

This paper indicates the potential application of the characterization theory to the mixture model. It discusses a particular example of a mixture model and concludes that successful application of this theory can be made in order to choose the appropriate mixture model and the mixing parameter.     

Analysis of variance for circular data

Over the last 25 years, increasing attention has been given to the problem of analysing data arising from circular distributions. The most important circular distribution was introduced by Von Mises (1918) which takes the form:

[Formulas]

where Io(k) is a modified Bessel function, u0 is the mean direction and k is the concentration parameter of the distribution. Watson & Williams (1956) laid the foundation of analysis of variance type techniques for the two-dimensional case of circular data using the Von Mises distribution. Stephens (1962a,b; 1969, 1972). Upton (1974) and Stephens (1982) made further improvements to Watson & Williams’ work. In this paper the authors will discuss the pitfalls of the methods adopted by Stephens (1982) and present a unified analysis of variance type approach for circular data.     

Median rankit control chart by the quantile approach

It is desirable that the data for a statistical control chart be normally distributed. However, if the data are not normal, then a transformation can be used, e.g. Box-Cox transformations, to produce a suitable control chart. In this paper we will discuss a quantile approach to produce a control chart and to estimate median rankit for various non-normal distributions. We will also provide examples of logistic data to indicate how a quantile approach could be used to construct a control chart for a non-normal distribution using a median rankit.