This book covers the full spectrum of water and environment conservation, offering management lessons, identifying the barriers to transformative change, and then presenting agendas and initiatives for sustainable global water and environment management. Water is a unique resource and is vital to human beings and ecosystems. At the same time, it is a driver of growth and development. However, in a changing world factors such as rapid population growth and urbanization are having an increasing impact on water and the environment, and managing critical water resources sustainably represents an unprecedented and urgent challenge. As such, the book describes innovative approaches that can be used to support the operationalization and delivery of sustainable water and environment management. ICSDWE 2019 is dedicated to sustainable water and environment, with a focus on the water resources management, wastewater treatment and environmental protection. Sharing current knowledge and recent developments, experiences and lessons learned, it stimulates discussion and reflection, to promote a paradigm shift toward sustainable water and environment management.

This book covers the full spectrum of water and environment conservation, offering management lessons, identifying the barriers to transformative change, and then presenting agendas and initiatives for sustainable global water and environment management. Water is a unique resource and is vital to human beings and ecosystems. At the same time, it is a driver of growth and development. However, in a changing world factors such as rapid population growth and urbanization are having an increasing impact on water and the environment, and managing critical water resources sustainably represents an unprecedented and urgent challenge. As such, the book describes innovative approaches that can be used to support the operationalization and delivery of sustainable water and environment management. ICSDWE 2019 is dedicated to sustainable water and environment, with a focus on the water resources management, wastewater treatment and environmental protection. Sharing current knowledge and recent developments, experiences and lessons learned, it stimulates discussion and reflection, to promote a paradigm shift toward sustainable water and environment management.

By incorporating the latest advancement in complex system modeling and simulation into the service system research, this book makes a valuable contribution to this field that will lead service innovation and service management toward the digital twin and metaverse. It covers important topics such as computational experiments and parallel execution of a parallel service system, the modeling of artificial service systems, semi-parallel service systems, parallel service, and digital twin/metaverse. It also provides a unified framework for realizing a parallel service system that demonstrates the capabilities or potentials of adopting digital twin and metaverse. In addition, the book contains numerous solutions to real-world problems, through which both academic readers and practitioners will gain new perspectives on service systems, and learn how to model a parallel service system or how to use the model to analyze and understand the behaviors of the system. For academic readers, it sheds light on a new research direction within the service science/engineering domain made possible by the latest technologies. For practitioners, with the help of methods such as Agent-based Modeling and Simulation, the book will enable them to enhance their skills in designing or analyzing a service system.

Computer vision systems require large amounts of manually annotated data to properly learn challenging visual concepts. Crowdsourcing platforms offer an inexpensive method to capture human knowledge and understanding, for a vast number of visual perception tasks. Crowdsourcing in Computer Vision describes the types of annotations computer vision researchers have collected using crowdsourcing, and how they have ensured that this data is of high quality while annotation effort is minimized. It begins by discussing data collection on both classic vision tasks, such as object recognition, and recent vision tasks, such as visual story-telling. It then summarizes key design decisions for creating effective data collection interfaces and workflows, and presents strategies for intelligently selecting the most important data instances to annotate. It concludes with some thoughts on the future of crowdsourcing in computer vision. Crowdsourcing in Computer Vision provides an overview of how crowdsourcing has been used in computer vision, enabling a computer vision researcher who has previously not collected non-expert data to devise a data collection strategy. It will also be of help to researchers who focus broadly on crowdsourcing to examine how the latter has been applied in computer vision, and to improve the methods that can be employed to ensure the quality and expedience of data collection.