Xufeng Zhao – författare

This is the first book on the Which-Is-Better (WIB) Problem. These are questions that in daily life include such as “Which is larger, younger and stronger?". The main objective of this book is summarizing WIB Problems in maintenance and reliability theory. Optimal policies of replacement first, last and overtime are derived and compared theoretically and numerically, and WIB policies are determined. Furthermore, the reliability properties of parallel and standby systems are compared, and WIB system is determined. These WIB Problems are applied to shock and damage models and backup and checkpoint models of computer systems.

This is the first book on the Which-Is-Better (WIB) Problem. These are questions that in daily life include such as “Which is larger, younger and stronger?". The main objective of this book is summarizing WIB Problems in maintenance and reliability theory. Optimal policies of replacement first, last and overtime are derived and compared theoretically and numerically, and WIB policies are determined. Furthermore, the reliability properties of parallel and standby systems are compared, and WIB system is determined. These WIB Problems are applied to shock and damage models and backup and checkpoint models of computer systems.

This book is designed to provide a well-structured, comprehensive, and practical textbook on machine learning for undergraduate and graduate students in related fields. Through clear and accessible explanations, this book allows readers go master the concepts and techniques of machine learning, equipping them with the ability to solve real-world problems.A distinctive feature of this book is its emphasis on interpretability. In the world of machine learning, models need not only to be accurate but also to be understandable and explainable. For students, understanding the underlying principles and logic of algorithms is more important than simply using them as black boxes. Therefore, each chapter in this textbook not only introduces the mathematical background and implementation principles of the algorithms but also demonstrates them through detailed Python code, helping readers understand how each algorithm works and providing valuable insights.From the foundational concepts of linear regression and logistic regression to more complex techniques such as deep neural networks, convolutional neural networks, and recurrent neural networks, this book covers the full spectrum of classical algorithms and cutting-edge technologies in machine learning. We also provide in-depth discussions on ensemble learning, reinforcement learning, and Transformer models, addressing some of the most popular topics in the field. Through real-world case studies, we connect these algorithms with practical applications, helping readers better understand how they are used in various scenarios.While focusing on theoretical learning, we also emphasize the development of practical skills. The case studies in each chapter are based on real-world data and cover a variety of domains, including classification, regression, image processing, and natural language processing. Through these case studies, readers will not only grasp the ideas behind the algorithms but also experience how to apply these theories to solve actual problems.Finally, this book includes a special section on large language models, showcasing how machine learning has evolved into today's cutting-edge technology. It guides readers toward the frontier of artificial intelligence, highlighting breakthroughs in natural language understanding and generation. This marks not just an extension of machine learning techniques, but also their profound impact in the realm of language processing.This book is suitable not only for academic teaching but also for scholars and practitioners who wish to deepen their understanding of machine learning. We hope that it helps readers strengthen their theoretical foundation, enhance their practical skills, and pave the way for engaging with frontier research and innovation in this field.

This book introduces a new notion of replacement in maintenance and reliability theory. Replacement Overtime, where replacement is done at the first completion of a working cycle over a planned time, is a new research topic in maintenance theory and also serves to provide a fresh optimization technique in reliability engineering. In comparing replacement overtime with standard and random replacement techniques theoretically and numerically, 'Maintenance Overtime Policies in Reliability Theory' highlights the key improvements to be gained by adopting this new approach and shows how they can be applied to inspection policies, parallel systems and cumulative damage models. Utilizing the latest research in replacement overtime by internationally recognized experts, the reader will be introduced to new topics and methods, and learn how to apply this knowledge practically to actual reliability models. This book will serve as an essential guide to a new subject of study for graduate students and researchers and also provides a useful guide for reliability engineers and managers who have difficulties in maintenance of computer and production systems with random working cycles.

This book introduces a new notion of replacement in maintenance and reliability theory. Replacement Overtime, where replacement is done at the first completion of a working cycle over a planned time, is a new research topic in maintenance theory and also serves to provide a fresh optimization technique in reliability engineering. In comparing replacement overtime with standard and random replacement techniques theoretically and numerically, ''Maintenance Overtime Policies in Reliability Theory'' highlights the key improvements to be gained by adopting this new approach and shows how they can be applied to inspection policies, parallel systems and cumulative damage models. Utilizing the latest research in replacement overtime by internationally recognized experts, the reader will be introduced to new topics and methods, and learn how to apply this knowledge practically to actual reliability models. This book will serve as an essential guide to a new subject of study for graduate students and researchers and also provides a useful guide for reliability engineers and managers who have difficulties in maintenance of computer and production systems with random working cycles.

This book introduces a new notion of replacement in maintenance and reliability theory. Replacement Overtime, where replacement is done at the first completion of a working cycle over a planned time, is a new research topic in maintenance theory and also serves to provide a fresh optimization technique in reliability engineering. In comparing replacement overtime with standard and random replacement techniques theoretically and numerically, 'Maintenance Overtime Policies in Reliability Theory' highlights the key improvements to be gained by adopting this new approach and shows how they can be applied to inspection policies, parallel systems and cumulative damage models. Utilizing the latest research in replacement overtime by internationally recognized experts, the reader will be introduced to new topics and methods, and learn how to apply this knowledge practically to actual reliability models. This book will serve as an essential guide to a new subject of study for graduate students and researchers and also provides a useful guide for reliability engineers and managers who have difficulties in maintenance of computer and production systems with random working cycles.

This book surveys the recent development of maintenance theory, advanced maintenance techniques with shock and damage models, and their applications in computer systems dealing with efficiency problems. It also equips readers to handle multiple maintenance, informs maintenance policies, and explores comparative methods for several different kinds of maintenance. Further, it discusses shock and damage modelling as an important failure mechanism for reliability systems, and extensively explores the degradation processes, failure modes, and maintenance characteristics of modern, highly complex systems, especially for some key mechanical systems designed for specific tasks.

This book surveys the recent development of maintenance theory, advanced maintenance techniques with shock and damage models, and their applications in computer systems dealing with efficiency problems. It also equips readers to handle multiple maintenance, informs maintenance policies, and explores comparative methods for several different kinds of maintenance. Further, it discusses shock and damage modelling as an important failure mechanism for reliability systems, and extensively explores the degradation processes, failure modes, and maintenance characteristics of modern, highly complex systems, especially for some key mechanical systems designed for specific tasks.