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DTSTART:19700101T000000
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BEGIN:VEVENT
DTSTAMP:20241014T203108Z
LOCATION:FLW Salon B
DTSTART;TZID=America/Phoenix:20240910T094500
DTEND;TZID=America/Phoenix:20240910T104500
UID:HFESAM_ASPIRE - Presented by HFES_sess121@linklings.com
SUMMARY:HPM1: Human Performance Modeling
DESCRIPTION:Lecture\n\nHuman-Integrated System Simulation Analysis “in the
  Wild”\n\nSystems engineers often use model-based simulations to estimate 
 performance measures and compare designs before building expensive physica
 l prototypes. One common limitation, however, is that the simulation model
 s exclude human operators. Human factors practitioners have developed mode
 l-based approa...\n\n\nAndrew Abbate and Maia Cook (Pacific Science & Engi
 neering Group)\n---------------------\nApplying the SEEV Model to Assess W
 here People Will Look:  Practical Considerations\n\nFor safety-critical ta
 sks, such as landing an airplane and driving through an intersection, oper
 ators must find critical information quickly, which depends upon where the
 y are likely to look.  This can be determined using the SEEV computational
  model which includes 4 primary factors:  Salience, Effo...\n\n\nPaul Gree
 n (University of Michigan)\n---------------------\nVerification and Valida
 tion of Cognitive Workload Models for Adaptive Automation Tasks\n\nTechnol
 ogical advances that seek to address future operational challenges abound.
  While advanced capabilities are being developed, there is an important sp
 ace for human design considerations, including cognitive workload. One pro
 posed solution to improve cognitive workload management is adaptive aut...
 \n\n\nCharles Rowan (Naval Postgraduate School, United States Army)\n\nTra
 ck: Human Performance Modeling\n\nSession Chair: Na Du (University of Pitt
 sburgh)
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