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Titlebook: Advances in Human Factors in Cybersecurity; AHFE 2020 Virtual Co Isabella Corradini,Enrico Nardelli,Tareq Ahram Conference proceedings 2020

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Thomas Chan,Noel Tracy,Zhu Wenhui2% in the identification of faked identities has been reached, even if errors were excluded from predictors and normalized features were included. The classification model performs similarly to those previously proposed, with a slightly lower accuracy (−3%) but overcoming their important practical limitations.
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,Macro-performance of China’s Export Sector,man limitations are outlined, in both an individual and social context. The difference between current systems and principles of interface and interaction design are highlighted. Finally, a possible ameliorating step is suggested. Specifically, a movement from reliance on human cognition and decision making to a reliance on habit formation.
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https://doi.org/10.1057/9780230114364endencies will trust more in AS when compared to high risk seeking participants. Moreover, other individual differences like age, gender, and education led to interesting results. Thus, our study provides valuable information about the human factors that mediate human and autonomous systems interact
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,Development of China’s Electronic Exports,edy Stepwise algorithm, for attribute selection. Next, a Genetic Algorithm with a Neural Network model was trained to the set of sessions . to generate a unique behavior profile for each user. In this way, the anomalous or intrusive behaviors of each user were identified in a more approximate and ef
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Front Matterc propagation to estimate the achievable risetime. The third uses an equivalent circuit of a single channel spark gap to calculate the maximum achievable rate of voltage rise. The first two estimates indicate that risetimes on the order of 1–10 ps are achievable. The last treatment, however, illustr
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