Description |
1 online resource (435 p.) |
Contents |
Cover -- Half Title -- Title Page -- Copyright Page -- Table of Contents -- Preface -- Acknowledgements -- About the Authors -- 1 Introduction -- 1.1 Aviation Scenarios (Situation in Aviation) -- 1.1.1 Piggybacking Planes -- 1.1.2 The Crash Landing of Pan Am Flight 6 -- 1.1.3 Flight 143 of Air Canada, a Gimli Glider -- 1.1.4 US Airways Flight 1549-Miracle On the Hudson -- 1.2 Situation Awareness and Assessment for Pilots -- 1.2.1 Situation Awareness -- 1.2.2 Visual Scan Pattern Accuracy -- 1.2.3 Cognitive Load -- 1.2.4 SAW Measurement Categories -- 1.2.4.1 Freeze-Probe Techniques |
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1.2.4.2 Real-Time Probe Techniques -- 1.2.4.3 Post-Trial Self-Rating Techniques -- 1.2.4.4 Observer-Rating Techniques -- 1.2.4.5 Performance Measures -- 1.2.4.6 Process Indices -- 1.3 Analytical Decision Process -- 1.3.1 History of ADM -- 1.3.2 Risk Management -- 1.3.3 Crew Resource Management (CRM) -- 1.3.3.1 Single-Pilot Resource Management -- 1.3.3.2 Hazard and Risk -- 1.3.3.3 Hazardous Attitudes and Antidotes -- 1.3.3.4 Risk -- 1.3.3.5 Assessment of Risk -- 1.3.3.6 Likelihood of an Event -- 1.3.3.7 Severity of an Event -- 1.3.4 Mitigating Risk -- 1.4 Intuitive Decision Strategies |
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1.4.1 Managing External Pressures -- 1.4.2 Human Factors -- 1.4.3 Human Behaviour -- 1.4.4 The Decision-Making Process -- 1.4.5 Single-Pilot Resource Management (SRM) -- 1.4.6 The 5 Ps Check -- 1.4.6.1 The Plan -- 1.4.6.2 The Pilot -- 1.4.6.3 The Passenger -- 1.4.6.4 The Programming -- 1.4.6.5 Perceive, Process, Perform (3P) Model -- 1.5 Cognitive Continuum Theory -- 1.5.1 Key Terms and Definition -- 1.5.1.1 Analysis -- 1.5.1.2 Coherence -- 1.5.1.3 Correspondence -- 1.5.1.4 Functional Relation -- 1.5.1.5 Intuition -- 1.5.1.6 Modes of Inquiry -- 1.5.1.7 Oscillation -- 1.5.1.8 Pattern Recognition |
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1.5.1.9 Quasi-Rationality -- 1.6 Role of Bayesian Network -- 1.6.1 Understanding the Bayesian Network -- 1.6.2 What Is It Used For? -- 1.6.3 How Does It Work? -- 1.6.4 What Is an Influencer Diagram in a Bayesian Network? -- 1.6.5 Constraints of the Bayesian Network -- 1.6.6 How Are Bayesian Networks Developed? -- 1.7 Role of Fuzzy Logic -- References -- 2 Situation Awareness -- 2.1 Introduction -- 2.2 Definitions of SAW -- 2.3 Approaches Used to Define and Explain Situation Awareness -- 2.3.1 Information Processing Models -- 2.3.2 The Perception-Action Cycle |
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2.3.3 Situation Awareness Fused With Models of Decision-Making -- 2.3.4 Situation Awareness as a Description of an Event -- 2.3.5 Summary -- 2.4 Measures Used to Assess Situation Awareness -- 2.4.1 Explicit Measures -- 2.4.2 Implicit Measures -- 2.4.3 Subjective Measures -- 2.5 Situation Awareness and Surveillance -- 2.5.1 Components of SAW Related to Surveillance -- 2.5.2 Examining the Relevant Components of SAW -- 2.5.3 Examining Spatial Awareness -- 2.5.4 Examining Navigation Awareness -- Exercises -- References -- 3 Situation Assessment -- 3.1 Introduction |
Summary |
Situation Assessment in Aviation new aspects of soft computing technologies for evaluation and assessment of situations in aviation scenarios. It considers using technologies, emerging from: multisensory data fusion (MSDF), Bayesian networks (BN), and fuzzy logic (FL), to assist pilots in their decision making |
Notes |
Description based upon print version of record |
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3.2 Problems With Situation Assessment |
Genre/Form |
Electronic books
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Form |
Electronic book
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Author |
Kashyap, Sudesh K
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Shrinivasan, Lakshmi
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ISBN |
9781000998887 |
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1000998886 |
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