The book examines the relationship between imperial examinations and literature from the perspective of restoring the cultural ecology of imperial examinations in Ming China, breaking through the paradigm of pure literature research. This book presents an important practice in adjusting the pattern of literary research. The contents of this book include five mutually independent but supportive parts:  1) the living conditions and careers of the literary attendants; 2) the educational background and school’s consciousness of the Ming literati; 3) top candidates and Ming literature; 4) genres of imperial examination and the Ming society; 5) exam cheating cases from the perspective of politics and literature. This book will appeal to readers interested in Chinese literature and culture and the imperial examination system in ancient China.

Sustainable Buildings and Structures collects the contributions presented at the 1st International Conference on Sustainable Buildings and Structures (Suzhou, China, 29 October-1 November 2016). The book aims to share thoughts and ideas on sustainable approaches to urban planning, engineering design and construction. The topics discussed include: - Civil engineering - Structural approaches, including new materials - New technologies and new techniques - Green building and carbon neutral approaches to design and construction - Sustainability, urban planning and development. Sustainable Buildings and Structures will be of interest to academics, professionals, industry representatives and local government officials involved in structural engineering, urban planning, engineering design, and other related fields.

Lifelong Machine Learning, Second Edition is an introduction to an advanced machine learning paradigm that continuously learns by accumulating past knowledge that it then uses in future learning and problem solving. In contrast, the current dominant machine learning paradigm learns in isolation: given a training dataset, it runs a machine learning algorithm on the dataset to produce a model that is then used in its intended application. It makes no attempt to retain the learned knowledge and use it in subsequent learning. Unlike this isolated system, humans learn effectively with only a few examples precisely because our learning is very knowledge-driven: the knowledge learned in the past helps us learn new things with little data or effort. Lifelong learning aims to emulate this capability, because without it, an AI system cannot be considered truly intelligent. Research in lifelong learning has developed significantly in the relatively short time since the first edition of this book was published. The purpose of this second edition is to expand the definition of lifelong learning, update the content of several chapters, and add a new chapter about continual learning in deep neural networks-which has been actively researched over the past two or three years. A few chapters have also been reorganized to make each of them more coherent for the reader. Moreover, the authors want to propose a unified framework for the research area. Currently, there are several research topics in machine learning that are closely related to lifelong learning-most notably, multi-task learning, transfer learning, and meta-learning-because they also employ the idea of knowledge sharing and transfer. This book brings all these topics under one roof and discusses their similarities and differences. Its goal is to introduce this emerging machine learning paradigm and present a comprehensive survey and review of the important research results and latest ideas in the area. This book is thus suitable for students, researchers, and practitioners who are interested in machine learning, data mining, natural language processing, or pattern recognition. Lecturers can readily use the book for courses in any of these related fields.

Predictive Filtering for Microsatellite Control Systems introduces technological design, modeling, stability analysis, predictive filtering, state estimation problem and real-time operation of spacecraft control systems in aerospace engineering. The book gives a systematically and almost self-contained description of the many facets of envisaging, designing, implementing or experimentally exploring predictive filtering for spacecraft control systems, along with the adequate designs of integrated modeling, dynamics, state estimation, and signal processing of spacecrafts and nonlinear systems.