Publications by authors named "Claire Genevieve La Fleur"

Human interpersonal communications drive political, technological, and economic systems, placing importance on network link prediction as a fundamental problem of the sciences. These systems are often described at the network-level by degree counts -the number of communication links associated with individuals in the network-that often follow approximate Pareto distributions, a divergence from Poisson-distributed counts associated with random chance. A defining challenge is to understand the inter-personal dynamics that give rise to such heavy-tailed degree distributions at the network-level; primarily, these distributions are explained by preferential attachment, which, under certain conditions, can create power law distributions; preferential attachment's prediction of these distributions breaks down, however, in conditions with no network growth.

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A critical requirement for developing a cyber capable workforce is to understand how to challenge, assess, and rapidly develop human cyber skill-sets in realistic cyber operational environments. Fortunately, cyber team competitions make use of simulated operational environments with scoring criteria of task performance that objectively define overall team effectiveness, thus providing the means and context for observation and analysis of cyber teaming. Such competitions allow researchers to address the key determinants that make a cyber defense team more or less effective in responding to and mitigating cyber attacks.

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One of the central concepts within the literature on cognitive aging is the notion of dedifferentiation-the idea that increasing age is associated with an increase in the interrelatedness of different cognitive abilities. Despite the centrality of this dedifferentiation hypothesis, there is a great deal of evidence that both supports and does not support dedifferentiation. We hypothesized that these inconsistent findings were due to (a) the use of different cognitive abilities (i.

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