Reliability Analysis and Modeling for Complex Systems
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Reliability Analysis and Modeling for Complex Systems: (Advances in Reliability Science)

Reliability Analysis and Modeling for Complex Systems: (Advances in Reliability Science)


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About the Book

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.

Table of Contents:
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

About the Author :
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. Dr. Shubham Mahajan, a distinguished member of prestigious organizations such as IEEE, ACM, and IAENG, boasts an impressive academic and professional background. He earned his B.Tech. degree from Baba Ghulam Shah Badshah University, his M.Tech. degree from Chandigarh University, and his Ph.D. degree from Shri Mata Vaishno Devi University (SMVDU) in Katra, India. Dr. Mahajan has a remarkable track record in the field of artificial intelligence and image processing, holding an impressive portfolio of eleven Indian patents, as well as one Australian and one German patent. His contributions to the field are further evidenced by his extensive publication record, which includes over 100+ articles published in peer-reviewed journals, conferences and 10+ books. His research interests span a wide array of topics, encompassing image processing, video compression, image segmentation, fuzzy entropy, nature-inspired computing methods, optimization, data mining, machine learning, robotics, and optical communication. Notably, his dedication and expertise have earned him the 'Best Research Paper Award' from ICRIC 2019, published by Springer in the LNEE series. In recognition of his exceptional achievements, Dr. Mahajan has received numerous accolades and honours throughout his career. These include the Best Student Award in 2019, the IEEE Region-10 Travel Grant Award in 2019, the 2nd runner-up prize in the IEEE RAS HACKATHON in 2019 (held in Bangladesh), the IEEE Student Early Researcher Conference Fund (SERCF) in 2020, the Emerging Scientist Award in 2021, and the IEEE Signal Processing Society Professional Development Grant in 2021. His commitment to excellence in research was further underscored by his receipt of the Excellence in Research Award in 2023. Dr. Mahajan's impact extends beyond the realm of academia. He has served as a Campus Ambassador for IEEE, representing esteemed institutions such as IIT Bombay, Kanpur, Varanasi, Delhi, as well as various multinational corporations. His active engagement in fostering international research collaborations reflects his enthusiasm for advancing the frontiers of knowledge and innovation on a global scale.


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Product Details
  • ISBN-13: 9780443336553
  • Publisher: Elsevier - Health Sciences Division
  • Publisher Imprint: Elsevier - Health Sciences Division
  • Height: 229 mm
  • No of Pages: 300
  • Width: 152 mm
  • ISBN-10: 0443336555
  • Publisher Date: 05 Oct 2025
  • Binding: Paperback
  • Language: English
  • Series Title: Advances in Reliability Science


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