For anyone who has ever felt like they don't belong, Sigh, Gone shares an irreverent, funny, and moving tale of displacement and assimilation woven together with poignant themes from beloved works of classic literature. In 1975, during the fall of Saigon, Phuc Tran immigrates to America along with his family. By sheer chance they land in Carlisle, Pennsylvania, a small town where the Trans struggle to assimilate into their new life. In this coming-of-age memoir told through the themes of great books such as The Metamorphosis, The Scarlet Letter, The Iliad, and more, Tran navigates the push and pull of finding and accepting himself despite the challenges of immigration, feelings of isolation, and teenage rebellion, all while attempting to meet the rigid expectations set by his immigrant parents. Appealing to fans of coming-of-age memoirs such as Fresh Off the Boat, Running with Scissors, or tales of assimilation like Viet Thanh Nguyen's The Displaced and The Refugees, Sigh, Gone explores one man's bewildering experiences of abuse, racism, and tragedy and reveals redemption and connection in books and punk rock. Against the hairspray-and-synthesizer backdrop of the '80s, he finds solace and kinship in the wisdom of classic literature, and in the subculture of punk rock, he finds affirmation and echoes of his disaffection. In his journey for self-discovery Tran ultimately finds refuge and inspiration in the art that shapes--and ultimately saves--him.

This book provides readers with a comprehensive overview of the latest developments in the field of smart manufacturing, exploring theoretical research, technological advancements, and practical applications of AI approaches. With Industry 4.0 paving the way for intelligent systems and innovative technologies to enhance productivity and quality, the transition to Industry 5.0 has introduced a new concept known as augmented intelligence (AuI), combining artificial intelligence (AI) with human intelligence (HI). As the demand for smart manufacturing continues to grow, this book serves as a valuable resource for professionals and practitioners looking to stay up-to-date with the latest advancements in Industry 5.0. Covering a range of important topics such as product design, predictive maintenance, quality control, digital twin, wearable technology, quantum, and machine learning, the book also features insightful case studies that demonstrate the practical application of these tools in real-world scenarios. Overall, this book provides a comprehensive and up-to-date account of the latest advancements in smart manufacturing, offering readers a valuable resource for navigating the challenges and opportunities presented by Industry 5.0.

- Introduce Decision Support Systems (DSS) with artificial intelligence for the Industry 4.0 Environments - Provide the essentials of recent applications of Machine Learning and Probabilistic Graphical Models for DSS - Consider the process uncertainty when developing the DSS helps these studies closer to reality - Provide general concepts for extracting knowledge from big data effectively and interpret decisions for DSS - Introduce real-world case studies in various fields like Engineering, Management, Healthcare with guidance and recommendations for the practical applications of these studies

This book introduces the latest research on advanced control charts and new machine learning approaches to detect abnormalities in the smart manufacturing process. By approaching anomaly detection using both statistics and machine learning, the book promotes interdisciplinary cooperation between the research communities, to jointly develop new anomaly detection approaches that are more suitable for the 4.0 Industrial Revolution. The book provides ready-to-use algorithms and parameter sheets, enabling readers to design advanced control charts and machine learning-based approaches for anomaly detection in manufacturing. Case studies are introduced in each chapter to help practitioners easily apply these tools to real-world manufacturing processes. The book is of interest to researchers, industrial experts, and postgraduate students in the fields of industrial engineering, automation, statistical learning, and manufacturing industries.

From the #1 New York Times bestselling illustrator of the Food Group series, Pete Oswald, and debut picture book author Phuc Tran, this is a hilarious picture book about big trucks, big feelings, and even bigger friendships! It's the last day at the construction site and Cranky the crane truck is feeling, well, cranky. And he doesn't want to talk about it. His friends Zippy, Wheezy, and Dump Chuck try to cheer him up. But you know what doesn't help when you're feeling cranky? A lot of talking. But what will help?  With Phuc Tran’s hilarious text and Pete Oswald’s bold expressive illustrations, this tale that’s Grumpy Monkey meets The Little Blue Truck shows young readers how kind friends and honesty are the perfect tools for navigating strong emotions. 

This book introduces the latest research on advanced control charts and new machine learning approaches to detect abnormalities in the smart manufacturing process. By approaching anomaly detection using both statistics and machine learning, the book promotes interdisciplinary cooperation between the research communities, to jointly develop new anomaly detection approaches that are more suitable for the 4.0 Industrial Revolution. The book provides ready-to-use algorithms and parameter sheets, enabling readers to design advanced control charts and machine learning-based approaches for anomaly detection in manufacturing. Case studies are introduced in each chapter to help practitioners easily apply these tools to real-world manufacturing processes. The book is of interest to researchers, industrial experts, and postgraduate students in the fields of industrial engineering, automation, statistical learning, and manufacturing industries.