Fourth-order kernel method for simple linear degradation model

Degradation analysis is a useful technique when life tests result in few or even no failures. The degradation measurements are recorded over time and the estimation of time-to-failure distribution plays a vital role in degradation analysis. The parametric method to estimate the time-to-failure distribution assumed a specific parametric model with known shape for the random effects parameter. To avoid any assumption about the model shape, a nonparametric method can be used. In this paper, we suggest to use the nonparametric fourth-order kernel method to estimate the time-to-failure distribution and its percentiles for the simple linear degradation model. The performances of the proposed method are investigated and compared with the classical kernel; maximum likelihood and ordinary least squares methods via simulation technique. The numerical results show the good performance of the fourth-order kernel method and demonstrate its superiority over the parametric method when there is no information about the shape of the random effect parameter distribution.     

A Potts‐mixture spatiotemporal joint model for combined magnetoencephalography and electroencephalography data

We develop a new methodology for determining the location and dynamics of brain activity from combined magnetoencephalography (MEG) and electroencephalography (EEG) data. The resulting inverse problem is ill‐posed and is one of the most difficult problems in neuroimaging data analysis. In our development we propose a solution that combines the data from three different modalities, magnetic resonance imaging (MRI), MEG and EEG, together. We propose a new Bayesian spatial finite mixture model that builds on the mesostate‐space model developed by Daunizeau & Friston [Daunizeau and Friston, NeuroImage 2007; 38, 67–81]. Our new model incorporates two major extensions: (i) We combine EEG and MEG data together and formulate a joint model for dealing with the two modalities simultaneously; (ii) we incorporate the Potts model to represent the spatial dependence in an allocation process that partitions the cortical surface into a small number of latent states termed mesostates. The cortical surface is obtained from MRI. We formulate the new spatiotemporal model and derive an efficient procedure for simultaneous point estimation and model selection based on the iterated conditional modes algorithm combined with local polynomial smoothing. The proposed method results in a novel estimator for the number of mixture components and is able to select active brain regions, which correspond to active variables in a high‐dimensional dynamic linear model. The methodology is investigated using synthetic data and simulation studies and then demonstrated on an application examining the neural response to the perception of scrambled faces. R software implementing the methodology along with several sample datasets are available at the following GitHub repository https://github.com/v2south/PottsMix . The Canadian Journal of Statistics 47: 688–711; 2019 © 2019 Statistical Society of Canada     

Estimation of reliability in multicomponent stress–strength based on two parameter exponentiated Weibull Distribution

In this research article, we estimate the multicomponent stress–strength reliability of a system when strength and stress variates are drawn from an exponentiated Weibull distribution with different shape parameters α?and?β, and common shape and scale parameters γ and λ, respectively. We estimate the parameters by using maximum likelihood estimation (MLE) and hence the estimate of reliability obtained applying the MLE method of estimation when samples are drawn from stress and strength distributions. The small sample comparison of the reliability estimates is made through Monte Carlo simulation.     

Human Resource Development in Asia – Thriving on dynamism & change: Reflections from 2006 Asian HRD conference

This article discusses the experiences of the conference management team and the host (Universiti Putra Malaysia -UPM) of the Fifth Asian Conference of the Academy of Human Resource Development, held in Putrajaya, Malaysia from 2 to 5 December 2006. In reviewing the conference, the following sub-topics are used for organizing the contents of the article: HRD in Malaysia; conference theme & overview; participations/country representations and paper streams; keynote addresses; conference assessment; and conclusions. At the end, brief perspectives of the next Asian HRD conference to be held in China are also provided.     

A sequential discrimination procedure for two almost identically shaped wrapped distributions

The way of investigating a distribution knowing its interesting properties might be often inadequate when the shapes of two distributions are almost similar. In each of these circumstances, the accurate decision about the genesis of a random sample from any of the two parent distributions will be very much ambiguous even with the availability of the existing testing procedure of the circular data. A sequential discrimination procedure has been suggested which is also invariant to the sample size. The performance of the proposed discrimination procedure has been evaluated by checking its capability of detecting the genesis of the known samples from the two identically shaped wrapped distributions.     

Intersectional oppression: A reflexive dialogue between Muslim academics and their experiences of Islamophobia and exclusion in UK Higher Education

Islamophobia has seen a disturbing rise in British and international contexts; however, we see limited attention being afforded to this in the context of Higher Education (HE), particularly the impacts of this through the lens of staff members. HE continues to frame itself as a post-racial, secular, progressive, and inclusive space, yet is perpetually opposed due to its surreptitious and violent incidences of racism, classism, sexism and ableism. We discuss here, using liberatory-based and autoethnographic methodologies, Muslim staff members' experiences and insights of Islamophobia in UK HE institutions (HEIs)—a severely underrepresented group and largely invisible issue in the academy. We highlight the need to expose, challenge, question, and destabilise the continuous victimisation of Muslims within these spaces and beyond. We unpick issues related to intersectionality and different levels of exclusion by exploring the sense of belonging felt by Muslim staff; specific challenges and episodes of Islamophobia faced; and ways the sector can dismantle Islamophobia and begin developing practices to genuinely support anti-Muslim, anti-racist inclusion and social justice.