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Human Mental Workload: Models and Applications

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Cover of 'Human Mental Workload: Models and Applications'

Table of Contents

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    Book Overview
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    Chapter 1 Whither Workload? Mapping a Path for Its Future Development
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    Chapter 2 Mental Workload: Assessment, Prediction and Consequences
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    Chapter 3 Assessment of Mental Workload: A Comparison of Machine Learning Methods and Subjective Assessment Techniques
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    Chapter 4 Elasticity and Rigidity Constructs and Ratings of Subjective Workload for Individuals and Groups
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    Chapter 5 Observations and Issues in the Application of Cognitive Workload Modelling for Decision Making in Complex Time-Critical Environments
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    Chapter 6 The Impact of Workload and Fatigue on Performance
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    Chapter 7 Estimation of Train Driver Workload: Extracting Taskload Measures from On-Train-Data-Recorders
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    Chapter 8 The Relationship Between Workload and Performance in Air Traffic Control: Exploring the Influence of Levels of Automation and Variation in Task Demand
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    Chapter 9 The WASCAL-Tool: Prediction of Staffing for Train Dispatching as Part of the Design Process of Track Yards
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    Chapter 10 Adaptive Automation and the Third Pilot: Managing Teamwork and Workload in an Airline Cockpit
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    Chapter 11 Quantification of Rail Signaller Demand Through Simulation
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    Chapter 12 Mental Workload as an Outcome in Medical Education
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    Chapter 13 Effect of Control-Display Compatibility on the Mental Workload of Submarine Helmsmen
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    Chapter 14 Neuroergonomics Method for Measuring the Influence of Mental Workload Modulation on Cognitive State of Manual Assembly Worker
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    Chapter 15 The Benefits of Task and Cognitive Workload Support for Operators in Ground Handling
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    Chapter 16 Workload Differences Between On-road and Off-road Manoeuvres for Motorcyclists
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    Chapter 17 Workload, Fatigue and Performance in the Rail Industry
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Title
Human Mental Workload: Models and Applications
Published by
Springer, Cham, January 2017
DOI 10.1007/978-3-319-61061-0
ISBNs
978-3-31-961060-3, 978-3-31-961061-0
Editors

Luca Longo, M. Chiara Leva

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X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 49 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 6 12%
Student > Ph. D. Student 5 10%
Student > Doctoral Student 3 6%
Researcher 3 6%
Lecturer 1 2%
Other 1 2%
Unknown 30 61%
Readers by discipline Count As %
Engineering 8 16%
Business, Management and Accounting 3 6%
Psychology 3 6%
Environmental Science 2 4%
Computer Science 1 2%
Other 2 4%
Unknown 30 61%