Since the mid-1990s, as China has downsized and privatized its state-owned enterprises, severe unemployment has created a new class of urban poor and widespread social and psychological disorders. In Unknotting the Heart, Jie Yang examines this understudied group of workers and their experiences of being laid off, "counseled," and then reoriented to the market economy. Using fieldwork from reemployment programs, community psychosocial work, and psychotherapy training sessions in Beijing between 2002 and 2013, Yang highlights the role of psychology in state-led interventions to alleviate the effects of mass unemployment. She pays particular attention to those programs that train laid-off workers in basic psychology and then reemploy them as informal "counselors" in their capacity as housemaids and taxi drivers.
These laid-off workers are filling a niche market created by both economic restructuring and the shortage of professional counselors in China, helping the government to defuse intensified class tension and present itself as a nurturing and kindly power. In reality, Yang argues, this process creates both new political complicity and new conflicts, often along gender lines. Women are forced to use the moral virtues and work ethics valued under the former socialist system, as well as their experiences of overcoming depression and suffering, as resources for their new psychological care work. Yang focuses on how the emotions, potentials, and "hearts" of these women have become sites of regulation, market expansion, and political imagination.
Автор: Kang, Jie (the College Of New Jersey, Usa) Название: Nutrition and metabolism in sports, exercise and health ISBN: 1138687588 ISBN-13(EAN): 9781138687585 Издательство: Taylor&Francis Рейтинг: Цена: 8420.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This new edition offers a useful and concise introduction to nutrition and metabolism in sport, exercise and health settings. Informed by the latest research and using updated pedagogical features, this book includes new sections on topics such as, cellular structure and protein supplementation, alongside a revised and expanded companion website.
Автор: Liu Shaoshan, Li Liyun, Tang Jie Название: Creating Autonomous Vehicle Systems ISBN: 1681739356 ISBN-13(EAN): 9781681739359 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 10672.00 р. Наличие на складе: Нет в наличии.
Описание:
This book is one of the first technical overviews of autonomous vehicles written for a general computing and engineering audience. The authors share their practical experiences designing autonomous vehicle systems. These systems are complex, consisting of three major subsystems: (1) algorithms for localization, perception, and planning and control; (2) client systems, such as the robotics operating system and hardware platform; and (3) the cloud platform, which includes data storage, simulation, high-definition (HD) mapping, and deep learning model training. The algorithm subsystem extracts meaningful information from sensor raw data to understand its environment and make decisions as to its future actions. The client subsystem integrates these algorithms to meet real-time and reliability requirements. The cloud platform provides offline computing and storage capabilities for autonomous vehicles. Using the cloud platform, new algorithms can be tested so as to update the HD map--in addition to training better recognition, tracking, and decision models.
Since the first edition of this book was released, many universities have adopted it in their autonomous driving classes, and the authors received many helpful comments and feedback from readers. Based on this, the second edition was improved by extending and rewriting multiple chapters and adding two commercial test case studies. In addition, a new section entitled "Teaching and Learning from this Book" was added to help instructors better utilize this book in their classes. The second edition captures the latest advances in autonomous driving and that it also presents usable real-world case studies to help readers better understand how to utilize their lessons in commercial autonomous driving projects.
This book should be useful to students, researchers, and practitioners alike. Whether you are an undergraduate or a graduate student interested in autonomous driving, you will find herein a comprehensive overview of the whole autonomous vehicle technology stack. If you are an autonomous driving practitioner, the many practical techniques introduced in this book will be of interest to you. Researchers will also find extensive references for an effective, deeper exploration of the various technologies.
Описание: Varieties of Governance in China examines the origins of the varying institutional foundations of rural China`s decentralized governance, explains the performance and change of the formal and informal institutions that uphold rural China`s governance, and documents the effects of rural-urban migration on institutional change and local governance in Chinese villages.
Описание: In recent years, the control of Connected and Automated Vehicles (CAVs) has attracted strong attention for various automotive applications. One of the important features demanded of CAVs is collision avoidance, whether it is a stationary or a moving obstacle. Due to complex traffic conditions and various vehicle dynamics, the collision avoidance system should ensure that the vehicle can avoid collision with other vehicles or obstacles in longitudinal and lateral directions simultaneously. The longitudinal collision avoidance controller can avoid or mitigate vehicle collision accidents effectively via Forward Collision Warning (FCW), Brake Assist System (BAS), and Autonomous Emergency Braking (AEB), which has been commercially applied in many new vehicles launched by automobile enterprises. But in lateral motion direction, it is necessary to determine a flexible collision avoidance path in real time in case of detecting any obstacle. Then, a path-tracking algorithm is designed to assure that the vehicle will follow the predetermined path precisely, while guaranteeing certain comfort and vehicle stability over a wide range of velocities. In recent years, the rapid development of sensor, control, and communication technology has brought both possibilities and challenges to the improvement of vehicle collision avoidance capability, so collision avoidance system still needs to be further studied based on the emerging technologies.
In this book, we provide a comprehensive overview of the current collision avoidance strategies for traditional vehicles and CAVs. First, the book introduces some emergency path planning methods that can be applied in global route design and local path generation situations which are the most common scenarios in driving. A comparison is made in the path-planning problem in both timing and performance between the conventional algorithms and emergency methods. In addition, this book introduces and designs an up-to-date path-planning method based on artificial potential field methods for collision avoidance, and verifies the effectiveness of this method in complex road environment. Next, in order to accurately track the predetermined path for collision avoidance, traditional control methods, humanlike control strategies, and intelligent approaches are discussed to solve the path-tracking problem and ensure the vehicle successfully avoids the collisions. In addition, this book designs and applies robust control to solve the path-tracking problem and verify its tracking effect in different scenarios. Finally, this book introduces the basic principles and test methods of AEB system for collision avoidance of a single vehicle. Meanwhile, by taking advantage of data sharing between vehicles based on V2X (vehicle-to-vehicle or vehicle-to-infrastructure) communication, pile-up accidents in longitudinal direction are effectively avoided through cooperative motion control of multiple vehicles.
Автор: Li, Jie Jack Название: Name reactions ISBN: 3030508641 ISBN-13(EAN): 9783030508647 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Поставка под заказ.
Описание: In this sixth edition of Jack Jie Li`s seminal "Name Reactions", the author has added three or more synthetic applications of name reactions to reflect the recent advances in organic chemistry.
Автор: Xiao, Jie Название: Integral & functional analysis ISBN: 1600217842 ISBN-13(EAN): 9781600217845 Издательство: Nova Science Рейтинг: Цена: 9344.00 р. Наличие на складе: Невозможна поставка.
Описание: Based on Integration and Metric Spaces and Functional Analysis, this book is useful for undergraduate students. This book assumes that the students have some familiarity with Introductory Calculus and Linear Algebra as well as the basic (direct, indirect) proof methods.
Автор: Liu Shaoshan, Li Liyun, Tang Jie Название: Creating Autonomous Vehicle Systems ISBN: 1681739372 ISBN-13(EAN): 9781681739373 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 13583.00 р. Наличие на складе: Нет в наличии.
Описание:
This book is one of the first technical overviews of autonomous vehicles written for a general computing and engineering audience. The authors share their practical experiences designing autonomous vehicle systems. These systems are complex, consisting of three major subsystems: (1) algorithms for localization, perception, and planning and control; (2) client systems, such as the robotics operating system and hardware platform; and (3) the cloud platform, which includes data storage, simulation, high-definition (HD) mapping, and deep learning model training. The algorithm subsystem extracts meaningful information from sensor raw data to understand its environment and make decisions as to its future actions. The client subsystem integrates these algorithms to meet real-time and reliability requirements. The cloud platform provides offline computing and storage capabilities for autonomous vehicles. Using the cloud platform, new algorithms can be tested so as to update the HD map--in addition to training better recognition, tracking, and decision models.
Since the first edition of this book was released, many universities have adopted it in their autonomous driving classes, and the authors received many helpful comments and feedback from readers. Based on this, the second edition was improved by extending and rewriting multiple chapters and adding two commercial test case studies. In addition, a new section entitled "Teaching and Learning from this Book" was added to help instructors better utilize this book in their classes. The second edition captures the latest advances in autonomous driving and that it also presents usable real-world case studies to help readers better understand how to utilize their lessons in commercial autonomous driving projects.
This book should be useful to students, researchers, and practitioners alike. Whether you are an undergraduate or a graduate student interested in autonomous driving, you will find herein a comprehensive overview of the whole autonomous vehicle technology stack. If you are an autonomous driving practitioner, the many practical techniques introduced in this book will be of interest to you. Researchers will also find extensive references for an effective, deeper exploration of the various technologies.
Описание: The book focuses on symplectic pseudospectral methods for nonlinear optimal control problems and their applications. Symplectic pseudospectral methods for nonlinear optimal control problems with complicated factors (i.e., inequality constraints, state-delay, unspecific terminal time, etc.) are solved under the framework of indirect methods.
Автор: Liu Zhiyuan, Zhou Jie Название: Introduction to Graph Neural Networks ISBN: 1681737671 ISBN-13(EAN): 9781681737676 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 9286.00 р. Наличие на складе: Нет в наличии.
Описание: Graphs are useful data structures in complex real-life applications such as modeling physical systems, learning molecular fingerprints, controlling traffic networks, and recommending friends in social networks.
However, these tasks require dealing with non-Euclidean graph data that contains rich relational information between elements and cannot be well handled by traditional deep learning models (e.g., convolutional neural networks (CNNs) or recurrent neural networks (RNNs)). Nodes in graphs usually contain useful feature information that cannot be well addressed in most unsupervised representation learning methods (e.g., network embedding methods). Graph neural networks (GNNs) are proposed to combine the feature information and the graph structure to learn better representations on graphs via feature propagation and aggregation. Due to its convincing performance and high interpretability, GNN has recently become a widely applied graph analysis tool.
This book provides a comprehensive introduction to the basic concepts, models, and applications of graph neural networks. It starts with the introduction of the vanilla GNN model. Then several variants of the vanilla model are introduced such as graph convolutional networks, graph recurrent networks, graph attention networks, graph residual networks, and several general frameworks. Variants for different graph types and advanced training methods are also included. As for the applications of GNNs, the book categorizes them into structural, non-structural, and other scenarios, and then it introduces several typical models on solving these tasks. Finally, the closing chapters provide GNN open resources and the outlook of several future directions.
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