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Victor Finomore

Researcher at West Virginia University

Publications -  99
Citations -  1605

Victor Finomore is an academic researcher from West Virginia University. The author has contributed to research in topics: Vigilance (psychology) & Workload. The author has an hindex of 20, co-authored 95 publications receiving 1367 citations. Previous affiliations of Victor Finomore include United States Air Force Academy & University of West Virginia.

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Predicting vigilance: A fresh look at an old problem

TL;DR: Recent empirical studies using personality measures, ability tests and scales for stress and coping as predictors of vigilance suggest promising new constructs include trait scales linked to fatigue, abnormal personality and the stress state of task engagement.
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Google Glass: A Driver Distraction Cause or Cure?

TL;DR: Glass in not a panacea as some supporters claim, but it does point the way to design interventions that effect reduced load in multitasking, and discussions of these identified benefits are framed within the potential of new in-vehicle systems that bring both novel forms of distraction and tools for mitigation into the driver’s seat.
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Individual differences in vigilance: Personality, ability and states of stress

TL;DR: In this article, a multivariate approach based on attentional resource theory was adopted to predict the detection rate of visual vigilance in a high-workload visual vigilance task with 210 participants.
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Effects of sensory modality on cerebral blood flow velocity during vigilance

TL;DR: The results of Transcranial Doppler sonography are consistent with the view that a right hemispheric system is involved in the functional control of vigilance and that this system operates in a similar manner in the auditory and visual channels.
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Predicting battlefield vigilance: a multivariate approach to assessment of attentional resources

TL;DR: Investigation of the validity of a battery of measures of attentional resources in predicting vigilance on a military display monitoring task confirms that the multivariate approach substantially enhances prediction over existing approaches.