Digital media are a key part of everyday social life for international migrants. However, we don’t know enough about how these migrants critically understand and cope with the cultures and infrastructures of ubiquitous connectivity while on the move. Social Media in the Lives of Young Connected Migrants explores and theorises what it means for young migrants to live in a digital age. Presenting a richly detailed analysis of Chinese international students’ everyday social media practices, the book unravels the meanings of digital connectivity in general and how contemporary mobile young generations respond to such changes. Drawing on ethnographic and interview data, this book highlights the enabling aspects of connective media in migration journeys and shows how and why young Chinese migrants manage or even resist being connected. With close attention to diasporic, intercultural, family, and professional migrant identities and relationships, the author provides a nuanced account of living with digital media in everyday settings. Focusing on the boundary practices associated with social media, the book offers a unique analytical framework through which to capture the complex intersections of digital communication technologies and migrant social life. This volume will appeal to students and scholars interested in researching Chinese diasporas, digital migration, and youth cultures.
Sleep is a cyclic physiological phenomenon, an important aspect of human life activity, which, like sport and diet, is a nutritional element that ensures the growth and development of the organism. Under the influence of various factors such as work and study stress and metabolic disorders, more and more people suffer from various types of sleep disorders. Sleep has become an important research topic in recent years. Sleep stage analysis plays an important role in the early detection and treatment of sleep disorders. However, different age groups show different symptoms of sleep disorders, and different sleep disorders show variability in their different sleep stages. The prevalence of sleep disorders is much higher in children than in adults. Although the classification of sleep stages in adults has been well studied, children show markedly different characteristics of sleep stages. Therefore, there is an urgent need for sleep stage classification in children. With the rapid development of intelligent computing technology, artificial intelligence has found wide application in medical research and health sciences in recent years. In the field of sleep medicine, deep learning approaches can efficiently and automatically learn abstracted relevant sleep features from collected sleep data to accurately interpret children's sleep stages accordingly. Compared to traditional sleep data analysis, this saves many manual and time resources for data annotation and helps sleep experts reduce the risk of misdiagnosing sleep disorders based on their prior knowledge. In this context, this book presents several advanced deep learning-based approaches for sleep stage classification in children using time series polysomnography recordings acquired from clinical sensor devices. Significantly improved performance in classifying sleep stages in children suffering from sleep disorders demonstrates the great potential of joint research and development between artificial intelligence and the field of sleep medicine.
Surveillance systems have become increasingly popular. Full involvement of human operators has led to shortcomings, e.g. high labor cost, limited capability for multiple screens, inconsistency in long-duration, etc. Intelligent surveillance systems (ISSs) can supplement or even replace traditional ones. In ISSs, computer vision, pattern recognition, and artificial intelligence technologies are used to identify abnormal behaviours in videos. They present the development of real-time behaviour-based intelligent surveillance systems. The book focuses on the detection of individual abnormal behaviour based on learning and the analysis of dangerous crowd behaviour based on texture and optical flow. Practical systems include a real-time face classification and counting system, a surveillance robot system that utilizes video and audio information for intelligent interaction, and a robust person counting system for crowded environments.
This book first presents a systematic theoretical study of wireless localization techniques. Then, guided by the theoretical results, the authors provide design approaches for improving the performance of localization systems and making the deployment of the systems more convenient. The book aims to address the following issues: how reliable the wireless localization system can be; how the system can scale up with the number of users to be served; how to make key design decisions in implementing the system; and how to mitigate human efforts in deploying the wireless localization system. The book is relevant for researchers, academics, and students interested in wireless localization technology.
This book investigates in detail production scheduling technology in different kinds of shop environment to achieve sustainability manufacturing. Studies on shop scheduling have attracted engineers and scientists from various disciplines, such as electrical, mechanical, automation, computer, and industrial engineering. Pursuing a holistic approach, the book establishes a fundamental framework for this topic, while emphasizing the importance of intelligent optimization and the significant influence of production scheduling in the manufacturing systems. The book is intended for undergraduate and graduate students who are interested in intelligent optimization technology, shop scheduling, and green manufacturing systems or other scheduling applications.
This book explores language teacher beliefs in English as a Foreign Language (EFL) reading instruction in the context of Chinese university English instructors. Since the 1990s, there has been a renewed interest on teacher beliefs in the domain of language teacher cognition. However, most studies in this area aim at investigating the relationship between particular aspects of teacher beliefs and classroom practices, largely ignoring the complexity of teacher beliefs. This study explores the issue from an alternative perspective by conceptualizing teacher beliefs as a complex, dynamic and multi-faceted system. By adopting five rounds of interview and four classroom observations, the year-long study reveals seven key features of the belief system shared among six participants. It calls for the holistic, complex and insider view to examine teacher beliefs in relation to the sociocultural and historical contexts where the teachers work and live.
This book covers some of the most popular methods in design space sampling, ensembling surrogate models, multi-fidelity surrogate model construction, surrogate model selection and validation, surrogate-based robust design optimization, and surrogate-based evolutionary optimization. Surrogate or metamodels are now frequently used in complex engineering product design to replace expensive simulations or physical experiments. They are constructed from available input parameter values and the corresponding output performance or quantities of interest (QOIs) to provide predictions based on the fitted or interpolated mathematical relationships. The book highlights a range of methods for ensembling surrogate and multi-fidelity models, which offer a good balance between surrogate modeling accuracy and building cost. A number of real-world engineering design problems, such as three-dimensional aircraft design, are also provided to illustrate the ability of surrogates for supporting complex engineering design. Lastly, illustrative examples are included throughout to help explain the approaches in a more “hands-on” manner.
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