Micro- and Nano-Bionic Surfaces: Biomimetics, Interface Energy Field Effects, and Applications synthesizes the latest research in bio-inspired surfaces and devices for tactile and flow field perception. The book provides solutions to common problems related to flow field/tactile perception, intelligent MEMS sensors, smart materials, material removal methods, cell/particle control methods, and micro-nano robot technology. With a heavy emphasis on applications throughout, the book starts by providing insights into biomimetic device design, outlining strategies readers can adopt for various engineering applications. From there, it introduces the controlling methods of smart materials, controlling methods from external energy input, and more. Sections demonstrate how to solve problems of high efficiency, high quality, and low damage material removal for metals, composites, soft tissues, and other materials by applying bionic wave-motion surface characteristics. The latest theoretical and technical developments in field control methods applied to biological interfaces are also discussed, and the book concludes with a chapter on fabrication strategies to synthesize micro/nano functional particles based on bio-templates.

Community structure is a salient structural characteristic of many real-world networks. Communities are generally hierarchical, overlapping, multi-scale and coexist with other types of structural regularities of networks. This poses major challenges for conventional methods of community detection. This book will comprehensively introduce the latest advances in community detection, especially the detection of overlapping and hierarchical community structures, the detection of multi-scale communities in heterogeneous networks, and the exploration of multiple types of structural regularities. These advances have been successfully applied to analyze large-scale online social networks, such as Facebook and Twitter. This book provides readers a convenient way to grasp the cutting edge of community detection in complex networks.
The thesis on which this book is based was honored with the Top 100 Excellent Doctoral Dissertations Award from the Chinese Academy of Sciences and was nominated as the Outstanding Doctoral Dissertation by the Chinese Computer Federation.

This book constitutes the thoroughly refereed proceedings of the 6th National Conference of Social Media Processing, SMP 2017, held in Beijing, China, in September 2017. The 28 revised full papers presented were carefully reviewed and selected from 140 submissions. The papers address issues such as: knowledge discovery for data; natural language processing; text mining and sentiment analysis; social network analysis and social computing.

Community structure is a salient structural characteristic of many real-world networks. Communities are generally hierarchical, overlapping, multi-scale and coexist with other types of structural regularities of networks. This poses major challenges for conventional methods of community detection. This book will comprehensively introduce the latest advances in community detection, especially the detection of overlapping and hierarchical community structures, the detection of multi-scale communities in heterogeneous networks, and the exploration of multiple types of structural regularities. These advances have been successfully applied to analyze large-scale online social networks, such as Facebook and Twitter. This book provides readers a convenient way to grasp the cutting edge of community detection in complex networks. The thesis on which this book is based was honored with the "Top 100 Excellent Doctoral Dissertations Award" from the Chinese Academy of Sciences and was nominated as the "Outstanding Doctoral Dissertation" by the Chinese Computer Federation.

This book constitutes the refereed proceedings of the 4th International Conference on Computational Social Networks, CSoNet 2015, held in Beijing, China, in August 2015. The 23 revised full papers and 3 short papers presented together with 2 extended abstracts were carefully reviewed and selected from 101 submissions and cover topics on social information diffusion; network clustering and community structure; social link prediction and recommendation; and social network structure analysis.

This modern introduction to seismic data processing in both exploration and global geophysics demonstrates practical applications through real data and tutorial examples. The underlying physics and mathematics of the various seismic analysis methods are presented, giving students an appreciation of their limitations and potential for creating models of the sub-surface. Designed for a one-semester course, this textbook discusses key techniques within the context of the world's ever increasing need for petroleum and mineral resources - equipping upper undergraduate and graduate students with the tools they need for a career in industry. Examples presented throughout the text allow students to compare different methods and can be demonstrated using the instructor's software of choice. Exercises at the end of sections enable students to check their understanding and put the theory into practice and are complemented by solutions for instructors and additional case study examples online to complete the learning package.