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Human Performance Models for Computer-Aided Engineering
- 1st Edition - June 28, 2014
- Editors: Jerome I. Elkind, Stuart K. Card, Julian Hochberg
- Language: English
- Paperback ISBN:9 7 8 - 1 - 4 8 3 2 - 3 8 4 0 - 1
- eBook ISBN:9 7 8 - 1 - 4 8 3 2 - 7 2 3 9 - 9
Human Performance Models for Computer-Aided Engineering is a collection of papers that deals with the relationship between scientific theories of human performance and practical… Read more
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Request a sales quoteHuman Performance Models for Computer-Aided Engineering is a collection of papers that deals with the relationship between scientific theories of human performance and practical engineering. This collection describes the emergence of a scientific engineering paradigm that uses computational theories in computational design aids. This book also considers computational human factors such as human performance models and their application in computer-based engineering designs. This text then presents applications of these models to some helicopter flight problems. This book also explains the four requirements in programming a computer-based model of the sensory performance of a pilot as 1) prediction capability; 2) measurement capability; 3) provision of compatible computer algorithms; and 4) image driven. This collection also describes cognitive structures—aspects of the human information processing system. This text then discusses resource management and time-sharing issues that is related to competition of scarce resources, which can be predictive of the quality of information processing. This book also describes other modeling scenarios such as those predicting human errors, decision making, and shape modeling. This text can prove valuable for computer programmers, engineers, physicists, and research scientists dealing with psychophysics.
Foreword
Preface
Part I
1 Introduction
Helicopter Flight Problems and Applications of Human Performance Models
Detectability and Visibility
Surface and Motion Estimation
Object Recognition
Hetero-Ocular Vision
Workload and Pilot Performance
Decision Theory
Memory Overload
Skill Acquisition
Human Error
References
2 Preview of Models
Framework
Assessment of Models
3 Use and Integration of Models
Design Process
Toolbox Framework
Selecting Tools and Models
Engineering Analyses
Discussion
Afterword
References
Part II
4 Introduction to Vision Models
5 Models in Early Vision
Overview
Introduction
What is a Model?
Model Attributes
Spatial Vision
Temporal Sensitivity
Motion Processing
Summary
References
6 Models of Static Form Perception
Image Generation
Image Analysis
Potential Applications
References
7 Structure from Motion
Overview
Introduction
Models
Conclusion
Research Needs: Structure from Motion
References
8 Motion-Based State Estimation and Shape Modeling
Introduction and Summary
Framework for Motion-Based State Estimation and Shape Modeling
Review of Research in Motion-Based State Estimation and Shape Modeling
Model Applications and Limitations
Future Research
References
9 Real-Time Human Image Understanding in Pilot Performance Models
Theories of Object Recognition
Model-Based Matching: Lowe's SCERPO and UUman's Alignment Models
Perception of Multiobject Displays
References
10 Manipulation Of Visual Information
Summary
Introduction
Transformations on Information Presented in a Static Visual Display
Memory for Positions in a Sequence of Static Displays
Extrapolation of Perceptually Driven Spatial Transformations
Judgments of Object Structure from Partial Views
Future Research
References
11 Combining Views
Integration of Successive Views
Binocular Combination
References
12 Afterword
13 Introduction to Cognition Models
14 Cognitive Architectures
Symbolist Architectures
Connectionist Models
References
15 Resource Management and Time-Sharing
Overview
Serial Allocation
Parallel Allocation
Serial Competition
Parallel Competition
Synthesis of the Optimal Model
Conclusion
References
16 Models of Working Memory
Phenomena of Working Memory
Models of Working Memory
References
17 Training Models to Estimate Training Costs for New Systems
Overview
Skill Development
Models for Predicting Human Performance
Engineering Guidance without an All-inclusive Model
Use of Rapid Prototyping and Quick Empirical Evaluations
Needed Research
References
18 Modeling Scenarios for Action
Fixed Scenarios
Scenarios with Simple Contingencies
Modeling More Complex Scenarios
References
19 Modeling and Predicting Human Error
Introduction
Error Modeling
References
20 Modeling Decision Making for System Design
Why Decision Making Seems Easy to Model—Sometimes
Implication for Modeling Operator Performance
Modeling without Optimality
Making Behavior More Model-like
Testing the Limits of Decision Making
References
21 Knowledge Elicitation and Representation
Knowledge Elicitation
Knowledge Representation
Mental Models and Design Decisions
References
22 Afterword
Part IV
23 Findings and Recommendations
Desirable Attributes and Types of Models
Adequacy of Models for the A3I Design Facility
Validation
Need for Access to Human Factors Data Base
Broader Context of Computational Human Factors
Importance of the System Design Context for Research on Models
Focusing the A3I Program
Providing a Framework and a Box of Tools
- No. of pages: 344
- Language: English
- Edition: 1
- Published: June 28, 2014
- Imprint: Academic Press
- Paperback ISBN: 9781483238401
- eBook ISBN: 9781483272399
JH
Julian Hochberg
Julian Hochberg is the Centennial Professor Emeritus at Columbia University. Dr. Hochberg is a member of the National Academy of Sciences, American Academy of Arts and Sciences, and a recipient of the Distinguished Scientific Contribution Award of the American Psychological Association.
Affiliations and expertise
Columbia University, New York, U.S.A.Read Human Performance Models for Computer-Aided Engineering on ScienceDirect