Coherence region of the Priority-AND gate : analytical and numerical examples

In recent years, the need for a more accurate dependability modelling (encompassing reliability, availability, maintenance, and safety) has favoured the emergence of novel dynamic dependability techniques able to account for temporal and stochastic dependencies of a system. One of the most successful and widely used method is Dynamic Fault Tree that, with the introduction of the dynamic gates, enables the analysis of dynamic failure logic systems such as fault-tolerant or reconfigurable systems. Among the dynamic gates, Priority-AND (PAND) is one of the most frequently used gate for the specification and analysis of event sequences. Despite the numerous modelling contributions addressing the resolution of the PAND gate, its failure logic and the consequences for the coherence behaviour of the system need to be examined to understand its effects for engineering decision-making scenarios including design optimization and sensitivity analysis. Accordingly, the aim of this short communication is to analyse the coherence region of the PAND gate so as to determine the coherence bounds and improve the efficacy of the dynamic dependability modelling process

The emergence of modern statistics in agricultural science : Analysis of variance, experimental design and the reshaping of research at Rothamsted Experimental Station, 1919–1933

During the twentieth century statistical methods have transformed research in the experimental and social sciences. Qualitative evidence has largely been replaced by quantitative results and the tools of statistical inference have helped foster a new ideal of objectivity in scientific knowledge. The paper will investigate this transformation by considering the genesis of analysis of variance and experimental design, statistical methods nowadays taught in every elementary course of statistics for the experimental and social sciences. These methods were developed by the mathematician and geneticist R. A. Fisher during the 1920s, while he was working at Rothamsted Experimental Station, where agricultural research was in turn reshaped by Fisher’s methods. Analysis of variance and experimental design required new practices and instruments in field and laboratory research, and imposed a redistribution of expertise among statisticians, experimental scientists and the farm staff. On the other hand the use of statistical methods in agricultural science called for a systematization of information management and made computing an activity integral to the experimental research done at Rothamsted, permanently integrating the statisticians’ tools and expertise into the station research programme. Fisher’s statistical methods did not remain confined within agricultural research and by the end of the 1950s they had come to stay in psychology, sociology, education, chemistry, medicine, engineering, economics, quality control, just to mention a few of the disciplines which adopted them

Learning from Team and Group Diversity: Nurturing and Benefiting from our Heterogeneity

By 2019, diversity is an established fact in most workplaces, teams, and work-groups, presenting both old and new challenges to CSCW in terms of team structure and technological supports for increasingly diverse teams. The research literature on diversity and teams has examined many definitions and attributes of diversity, and has described different types of teams, tasks, and measures, with contrasting and even contradictory results. Diversity becomes a strength in some studies, and a burden in others. The literature is similarly complex regarding individual and organizational approaches to realize those strengths, or to mitigate those burdens. In this workshop, we collectively take stock of these complex findings; we consider the several theoretical and methodological efforts to organize these findings; and we propose new research directions to address the “diversity of diversity studies.”Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/150491/1/Muller et al. 2019.pd

Risk Importance Measures

ISBN 978-0-85729-469-