85,329 research outputs found

    amei: An R Package for the Adaptive Management of Epidemiological Interventions

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    The amei package for R is a tool that provides a flexible statistical framework for generating optimal epidemiological interventions that are designed to minimize the total expected cost of an emerging epidemic. Uncertainty regarding the underlying disease parameters is propagated through to the decision process via Bayesian posterior inference. The strategies produced through this framework are adaptive: vaccination schedules are iteratively adjusted to reflect the anticipated trajectory of the epidemic given the current population state and updated parameter estimates. This document briefly covers the background and methodology underpinning the implementation provided by the package and contains extensive examples showing the functions and methods in action.

    Optimisation of patch distribution strategies for AMR applications

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    As core counts increase in the world's most powerful supercomputers, applications are becoming limited not only by computational power, but also by data availability. In the race to exascale, efficient and effective communication policies are key to achieving optimal application performance. Applications using adaptive mesh refinement (AMR) trade off communication for computational load balancing, to enable the focused computation of specific areas of interest. This class of application is particularly susceptible to the communication performance of the underlying architectures, and are inherently difficult to scale efficiently. In this paper we present a study of the effect of patch distribution strategies on the scalability of an AMR code. We demonstrate the significance of patch placement on communication overheads, and by balancing the computation and communication costs of patches, we develop a scheme to optimise performance of a specific, industry-strength, benchmark application

    Does interactivity require multimedia? The case of SAKI

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    SAKI is a self‐adaptive touch‐typing tutor with a pedigree dating back to the mid‐1950s. Even in its most recent form it eschews the temptation to present itself with the trimmings now commonly associated with microcomputer products. This paper argues that while the absence of such features may be a limiting factor in the commercial success of the program, SAKI is nevertheless a prime example of the way in which a computer can successfully react to and interact with a user, and indeed one which would actually lose educational value if it were to undergo an interface‐lift
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