Quiescent consistency is a notion of correctness for a concurrent object that gives meaning to the objects behaviours in quiescent states, i.e., states in which none of the objects operations are being executed. Correctness of an implementation object is defined in terms of a corresponding abstract specification. This gives rise to two important verification questions: membership (checking whet...

Misunderstandings about the Concept of Limit among High School Seniors E. Reyhaani, Ph.D. Z. Sharifi M. Soltaani The concept of limit is one of the basic concepts in mathematics. As such, clear understanding of it is pre-requisite for learning many other concepts. However, many of high school students suffer from misunderstanding this basic concept. To identify and remedy these ...

BACKGROUND There is a growing body of evidence linking health and well-being to key business issues. Despite this, corporate uptake of workplace health promotion programmes has been slow outside the USA. One possible reason for this is the lack of a generally available health risk measure that is quick and easy to administer and produces data that is rich enough to inform and direct subsequent ...

This study contrasts consistent partial identification with learning in the limit. Here partial identification means that the learner outputs an infinite sequence of conjectures in which one correct hypothesis occurs infinitely often and all other hypotheses occur only finitely often. Consistency means that every conjecture is correct on all the data seen so far. Learning in the limit means tha...

We prove several equivalences and relative consistency results involving notions of generic absoluteness beyond Woodin’s (Σ ̃ 1)λ generic absoluteness for a limit of Woodin cardinals λ. In particular, we prove that two-step ∃R(Π ̃ 1)λ generic absoluteness below a measurable cardinal that is a limit of Woodin cardinals has high consistency strength, and that it is equivalent with the existence of ...

An important issue in survival analysis is the investigation and the modeling of hazard rates. Within a Bayesian nonparametric framework, a natural and popular approach is to model hazard rates as kernel mixtures with respect to a completely random measure. In this paper we provide a comprehensive analysis of the asymptotic behavior of such models. We investigate consistency of the posterior di...

Hierarchical clustering is a popular method for analyzing data which associates a tree to a dataset. Hartigan consistency has been used extensively as a framework to analyze such clustering algorithms from a statistical point of view. Still, as we show in the paper, a tree which is Hartigan consistent with a given density can look very different than the correct limit tree. Specifically, Hartig...