Reliability Analysis and Modeling for Complex Systems

Erscheinungsjahr 2025
ISBN: 978-0-443-33655-3
Verlag: Elsevier Science

Buch, Englisch, 384 Seiten, Format (B × H): 169 mm x 217 mm, Gewicht: 626 g

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.

Autoren/Hrsg.

Kadry, Seifedine

Mahajan, Shubham

Fachgebiete

• Technische Wissenschaften Maschinenbau | Werkstoffkunde Produktionstechnik Zuverlässigkeitstechnik
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Kybernetik, Systemtheorie, Komplexe Systeme
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion
• Mathematik | Informatik Mathematik Mathematik Interdisziplinär Systemtheorie

Inhaltsverzeichnis

1. The Rationale behind Reliability Analysis in Complex Systems: Issues, Challenges, and the Imperative of Addressing Human Factors
2. A Reliability Modelling and Exploratory Data Analysis Approach to Understanding Complex Human Well-Being Systems: Decoding the Interplay of Financial Prosperity and Life Satisfaction
3. Deep Learning augmented Human Detection and Reliable Assessment for Search and Rescue in Disasters
4. Exploratory Human Factors Analysis for Reliable Happiness Perception in Complex Social Media Systems
5. Human Factors and Reliability in Complex Systems
6. Human Factors design considerations for complex systems
7. Impact of Smart Healthcare Devices in daily life
8. LEVERAGING AI TO ENHANCE HUMAN FACTOR ANALYSIS IN COMPLEX SYSTEM RELIABILITY
9. Digitalization of Healthcare: The Rise of Digital Twin Trend Worldwide and Its Implementation in Healthcare
10. Reliability Analysis in Healthcare Systems Addressing Technical and Human Factors
11. Reliability in Healthcare Systems
12. Reliability in Healthcare Systems ensuring patient safety
13. The Role of Diet and Nutrition in Alzheimer's Disease: Exploring the Gut-Cognitive Health Connection
14. Optimizing Parkinson's Disease Detection Based on Machine Learning and Statistical Feature Selection Approach
15. Reliability Measures in Wireless Zigbee Network Communication Systems: Addressing Data Loss and Remote Signal Strength
16. Solar Power Prediction using Computer Vision and Machine Intelligence: Predicting and Optimizing Solar Energy Generation

Über Autor(innen)

Kadry, Seifedine
Seifedine Kadry is a Professor in the Department of Mathematics and Computer Science, at Norrof University College, in Norway. He has a Bachelor’s degree in 1999 from Lebanese University, MS degree in 2002 from Reims University (France) and EPFL (Lausanne), PhD in 2007 from Blaise Pascal University (France), HDR degree in 2017 from Rouen University. At present, his research focuses on data Science, education using technology, system prognostics, stochastic systems, and applied mathematics. He is an ABET program evaluator for computing, and ABET program evaluator for Engineering Tech. He is a Fellow of IET, Fellow of IETE, and Fellow of IACSIT. He is a distinguished speaker of IEEE Computer Society.

Mahajan, Shubham
Dr. Shubham Mahajan is an academic and researcher, member of IEEE, ACM, and IAENG. He earned a B.Tech from Baba Ghulam Shah Badshah University, an M.Tech from Chandigarh University, and a PhD from Shri Mata Vaishno Devi University. He is currently Assistant Professor at Amity University, Haryana. His research spans artificial intelligence and image processing, including video compression, image segmentation, fuzzy entropy, nature-inspired optimization, data mining, machine learning, robotics, and optical communications. He holds patents internationally and has published widely in high-impact venues; he has edited several Scopus-indexed books. He has received multiple awards for research excellence and travel support from IEEE, among others. He has served as IEEE Campus Ambassador at premier institutes and promotes international collaborations. He participates in technical program committees and editorial boards for conferences and journals, shaping discourse in AI and image processing.