Reliability Analysis and Modeling for Complex Systems is a crucial resource for engineers and technologists grappling with modern challenges. As technology advances and safety concerns mount, the complexity of systems like autonomous vehicles and critical infrastructure demands innovative reliability assessment methods. This book bridges theory and practice, offering practical solutions for professionals navigating the intricate world of reliability engineering. Through real-world case studies and interdisciplinary insights, it equips readers to address the multifaceted challenges of ensuring dependability in today's interconnected technological landscape.
1. Cover image - p. c 2. Title page - p. i 3. Copyright - p. iv 4. Contents - p. v 5. Contributors - p. xi 6. Chapter 1 The rationale behind reliability analysis in complex systems: Issues, challenges, and the imperative of addressing human factors - p. 1 7. Chapter 2 A reliability modeling and exploratory data analysis approach to understanding complex human well-being systems: Decoding the interplay of financial prosperity and life satisfaction - p. 35 8. Chapter 3 Deep learning augmented human detection and reliable assessment for search and rescue in disasters - p. 53 9. Chapter 4 Exploratory human factors analysis for reliable happiness perception in complex social media systems - p. 93 10. Chapter 5 Reliability in healthcare systems - p. 119 11. Chapter 6 Human factors design considerations for complex systems - p. 133 12. Chapter 7 Impact of smart healthcare devices in daily life - p. 155 13. Chapter 8 Enhancing complex system reliability through artificial intelligence-driven human factor analysis - p. 167 14. Chapter 9 Digitalization of healthcare: The rise of digital twin trend worldwide and its implementation in healthcare - p. 193 15. Chapter 10 Reliability analysis in healthcare systems addressing technical and human factors - p. 219 16. Chapter 11 Reliability in healthcare systems - p. 239 17. Chapter 12 Reliability in healthcare systems ensuring patient safety - p. 263 18. Chapter 13 The role of diet and nutrition in Alzheimer's disease: Exploring the gut-cognitive health connection - p. 293 19. Chapter 14 Optimizing Parkinson's disease detection based on machine learning and statistical feature selection approach - p. 309 20. Chapter 15 Reliability measures in wireless Zigbee network communication systems: Addressing data loss and remote signal strength - p. 329 21. Chapter 16 Solar power prediction using computer vision and machine intelligence: Predicting and optimizing solar energy generation - p. 339 22. Index - p. 365
Reliability Analysis and Modeling for Complex Systems is a crucial resource for engineers and technologists grappling with modern challenges. As technology advances and safety concerns mount, the complexity of systems like autonomous vehicles and critical infrastructure demands innovative reliability assessment methods. This book bridges theory and practice, offering practical solutions for professionals navigating the intricate world of reliability engineering. Through real-world case studies and interdisciplinary insights, it equips readers to address the multifaceted challenges of ensuring dependability in today's interconnected technological landscape.
1. Cover image - p. c 2. Title page - p. i 3. Copyright - p. iv 4. Contents - p. v 5. Contributors - p. xi 6. Chapter 1 The rationale behind reliability analysis in complex systems: Issues, challenges, and the imperative of addressing human factors - p. 1 7. Chapter 2 A reliability modeling and exploratory data analysis approach to understanding complex human well-being systems: Decoding the interplay of financial prosperity and life satisfaction - p. 35 8. Chapter 3 Deep learning augmented human detection and reliable assessment for search and rescue in disasters - p. 53 9. Chapter 4 Exploratory human factors analysis for reliable happiness perception in complex social media systems - p. 93 10. Chapter 5 Reliability in healthcare systems - p. 119 11. Chapter 6 Human factors design considerations for complex systems - p. 133 12. Chapter 7 Impact of smart healthcare devices in daily life - p. 155 13. Chapter 8 Enhancing complex system reliability through artificial intelligence-driven human factor analysis - p. 167 14. Chapter 9 Digitalization of healthcare: The rise of digital twin trend worldwide and its implementation in healthcare - p. 193 15. Chapter 10 Reliability analysis in healthcare systems addressing technical and human factors - p. 219 16. Chapter 11 Reliability in healthcare systems - p. 239 17. Chapter 12 Reliability in healthcare systems ensuring patient safety - p. 263 18. Chapter 13 The role of diet and nutrition in Alzheimer's disease: Exploring the gut-cognitive health connection - p. 293 19. Chapter 14 Optimizing Parkinson's disease detection based on machine learning and statistical feature selection approach - p. 309 20. Chapter 15 Reliability measures in wireless Zigbee network communication systems: Addressing data loss and remote signal strength - p. 329 21. Chapter 16 Solar power prediction using computer vision and machine intelligence: Predicting and optimizing solar energy generation - p. 339 22. Index - p. 365
