Symposium: Neuroergonomics, technology, and cognition

This symposium describes collaborative research on neuroergonomics, technology, and cognition being conducted at George Mason University and the US Air Force Research Laboratory (AFRL) as part of the Center of Excellence in Neuroergonomics, Technology, and Cognition (CENTEC). Six presentations describe the latest developments in neuroergonomics research conducted by CENTEC scientists. The individual papers cover studies of: (1) adaptive learning systems; (2) neurobehavioral synchronicity during team performance; (3) genetics and individual differences in decision making; (4) vigilance and mindlessness; (5) interruptions and multi-tasking; and (6) development of a simulation capability that integrates measures across these domains and levels of analysis.     

An extension of the Freund's bivariate distribution to model cascading failures

The notion of cascading failures is a common phenomenon we observe around us. Here the initial failure alters the structure function of the system, which leads to subsequent failures within a short period of time referred to as threshold time. The concept of cascading failures within the framework of reliability theory and the Freund bivariate exponential distribution to model cascading failures has been studied by few authors. The Freund bivariate exponential distribution allows modelling a parallel redundant system with two components. In this system, the lifetimes of the two components behave as if they are independent, until one of the components fail, after which the remaining component suffers an increased/decreased stress. In this article, we further generalize this model to accommodate cascading failures. Various properties of the model are investigated and statistical inference procedures are developed using L-moments and method of moments. A practical application of this model is illustrated using data from www.espncricinfo.com. Also well analysed Diabetic Retinopathy Study (DRS) data is further analysed using this model and our findings are presented.     

Minimal circular strongly balanced repeated measurements designs in periods of three different sizes

Repeated measurements designs (RMD) are widely used in medicine, pharmacology, animal sciences, and psychology. If there is a restriction on the total number of treatments, some experimental units can receive on the total length of time while some experimental units can remain in the trial, then RMD in periods of unequal sizes should be used. In this article, some infinite series are developed to generate the minimal circular strongly balanced RMD in periods of three different sizes p₁, p₂, and p₃, where 2 ≤ p₃ < p₂ ≤ 10.     

The historical trajectory and diaspora of Hong Kong immigrants in Africa

Using Diaspora as a theoretical framework, this article investigates the historical trajectory of Hong Kong immigrant access to Africa, the evolution of their diaspora as well as living strategies. Based on data collected from 10 Hong Kong immigrants during 2018-2019 in Africa, and assessment of some historical materials such as Sino-Africa political relationships, its change trajectory, trade record, and personnel exchanges, the results demonstrate that the different Hong Kong political system might lead to the entrepreneurial resource obtains and the evolution trends of the diaspora of Hong Kong immigrants. Since the 1980s, the increase of re-export trade volume between Mainland China and Hong Kong had strengthened the trade volume between Hong Kong and Africa with the development of the Sino-Africa relationship. It illustrates that the trade relations between Hong Kong and Africa have been increasingly influenced by the re-export trade between Hong Kong and mainland China. Meanwhile, the Hong Kong immigrants in Africa have gradually been showing a trend of integration with new Chinese immigrants in Africa, which navigated their identities constantly i.e., Hong Kong diaspora, Chinese ethnic group and British citizenship (overseas), while their daily life was inclined towards cosmopolitan trends.     

Joint distribution of simultaneous exposures to several carcinogens in a case–control study: sample size determination

Consider a population of individuals who are free of a disease under study, and who are exposed simultaneously at random exposure levels, say X,Y,Z,… to several risk factors which are suspected to cause the disease in the populationm. At any specified levels X=x, Y=y, Z=z, …, the incidence rate of the disease in the population ot risk is given by the exposure–response relationship r(x,y,z,…) = P(disease|x,y,z,…). The present paper examines the relationship between the joint distribution of the exposure variables X,Y,Z, … in the population at risk and the joint distribution of the exposure variables U,V,W,… among cases under the linear and the exponential risk models. It is proven that under the exponential risk model, these two joint distributions belong to the same family of multivariate probability distributions, possibly with different parameters values. For example, if the exposure variables in the population at risk have jointly a multivariate normal distribution, so do the exposure variables among cases; if the former variables have jointly a multinomial distribution, so do the latter. More generally, it is demonstrated that if the joint distribution of the exposure variables in the population at risk belongs to the exponential family of multivariate probability distributions, so does the joint distribution of exposure variables among cases. If the epidemiologist can specify the differnce among the mean exposure levels in the case and control groups which are considered to be clinically or etiologically important in the study, the results of the present paper may be used to make sample size determinations for the case–control study, corresponding to specified protection levels, i.e., size α and 1–β of a statistical test. The multivariate normal, the multinomial, the negative multinomial and Fisher's multivariate logarithmic series exposure distributions are used to illustrate our results.     

Correlation between the numbers of two types of children in a family with the mpsd for the family size

The family size (sibship size) N is regarded as an integer-valued random variable having a Modified Power Series distribution (MPSD) of Gupta (1974). The family produces two types of children, with probabilities p and q (p+q =1) . It is proved that the correlation between the numbers B and C of these children is positive or negative according as the function log f(θ) is convex or concave with respect to the function g(θ), (see Section 2). This condition is a simple and a natural extension of the one given by Rao et al (1973). Several examples are discussed to illustrate the result.     

On length and area-biased Maxwell distributions

This article addresses the various properties and different methods of estimation of the unknown parameter of length and area-biased Maxwell distributions. Although, our main focus is on estimation from both frequentist and Bayesian point of view, yet, various mathematical and statistical properties of length and area-biased Maxwell distributions (such as moments, moment-generating function (mgf), hazard rate function, mean residual lifetime function, residual lifetime function, reversed residual life function, conditional moments and conditional mgf, stochastic ordering, and measures of uncertainty) are derived. We briefly describe different frequentist approaches, namely, maximum likelihood estimator, moments estimator, least-square and weighted least-square estimators, maximum product of spacings estimator and compare them using extensive numerical simulations. Next we consider Bayes estimation under different types of loss function (symmetric and asymmetric loss functions) using inverted gamma prior for the scale parameter. Furthermore, Bayes estimators and their respective posterior risks are computed and compared using Markov chain Monte Carlo (MCMC) algorithm. Also, bootstrap confidence intervals using frequentist approaches are provided to compare with Bayes credible intervals. Finally, a real dataset has been analyzed for illustrative purposes.     

Progressive Variance Control Charts for Monitoring Process Dispersion

In a process, the deviation from location or scale parameters affects the quality of the process and waste resources. So it is essential to monitor such processes for possible changes due to any assignable causes. Control charts are the most famous tool used to meet this intention. It is useless to monitor process location until the assurance that process dispersion is in-control. This study proposes some new two-sided memory control charts named as progressive variance (PV) control charts which are based on sample variance to monitor changes in process dispersion assuming normality of quality characteristic to be monitored. Simulation studies are made, and an example is discussed to evaluate the performance of the proposed charts. The comparison of the proposed chart is made with exponentially weighted moving average- and cumulative sum-type charts for process dispersion. The study shows that performance of the proposed charts are uniformly better than its competitors for detecting positive shifts while for detecting negative shift in the variance their performance is better for small shifts and reasonably good for moderated shifts.     

Seemingly unrelated reduced-rank regression model

Reduced-rank regression models proposed by Anderson [1951. Estimating linear restrictions on regression coefficients for multivariate normal distributions. Ann. Math. Statist. 22, 327–351] have been used in various applications in social and natural sciences. In this paper we combine the features of these models with another popular, seemingly unrelated regression model proposed by Zellner [1962. An efficient method of estimating seemingly unrelated regressions and tests for aggregation bias. J. Amer. Statist. Assoc. 57, 348–368]. In addition to estimation and inference aspects of the new model, we also discuss an application in the area of marketing.     

Multidimensional Wellbeing: An Index of Quality of Life in a Developing Economy

Human wellbeing indices can shed light on a society’s quality of life. This study ranks human wellbeing by employing objective and subjective indicators of quality of life for hundred districts of Pakistan. Households level data used for the analysis includes ‘The Pakistan Social and Living Standards Measurement Survey’ for the year 2006–2007. The human wellbeing is examined in four domains: education, health, living conditions and economic situation. Principal component analysis is employed for indexing human wellbeing, rated in five quintiles are generated. The paper demonstrates the importance of education, health and living condition domains in determining the human wellbeing. Objective indicators of education i.e., adult literacy rate, net primary enrolment and gender equality in education are important variables in ranking of districts. Economic status of the households and communities are important variables in subjective perception of wellbeing. The results indicate substantial variation in human wellbeing among districts of Pakistan It may be considered that disparity in objective condition and in subjective perceptions are adequately depicting wellbeing differences. Finally, it is argued that objective indicators and subjective wellbeing measures are needed in unison to understand human quality of life and to make informed policy decisions.