China has become an innovation powerhouse in high-tech industries, but the widely held view assumes the Chinese model is built on technological borrowing and state capitalism. This book debunks the myths surrounding the Chinese model with a fresh take on China's strategies for technological innovation. The central argument is that indigenous innovation plays a critical role in transforming the Chinese high-tech industry. Like any successfully industrialized nation in history, indigenous innovation in China allows industrial enterprises to assimilate knowledge developed elsewhere, utilize science and technology resources and human capabilities accumulated in the country, and eventually approach the technological frontier. The question is, how do Chinese businesses and governments engage in indigenous innovation? Employing the "social conditions of innovative enterprise" framework developed by William Lazonick and colleagues, this book analyzes how the interaction of strategy, organization, and finance in leading Chinese high-tech firms underpinned by national institutions enables indigenous innovation with Chinese characteristics. It features detailed case studies of two critical high-tech industries-the telecom-equipment industry and the semiconductor industry-and within them, the business histories of leading Chinese innovators. The in-depth look into China's experience in indigenous innovation provides valuable lessons for advanced and emerging economies.

This book constitutes the refereed post-conference proceedings of the 15th EAI International Conference on Tools for Design, Implementation and Verification of Emerging Information Technologies, TridentCom 2020. Due to COVID 19 pandemic the conference was held virtually. The 12 full papers were selected from 32 submissions and deal the emerging technologies of big data, cyber-physical systems and computer communications. The papers are grouped in thematical sessions on computer network and testbed application as well as analytics for big data of images and test.

Image-based rendering (IBR) is unique in that it requires computer graphics, computer vision, and image processing to join forces to solve a common goal, namely photorealistic rendering through the use of images. IBR as an area of research has been around for about ten years, and substantial progress has been achieved in effectively capturing, representing, and rendering scenes. Image-Based Rendering surveys the various techniques used in the area. It shows that representations and rendering techniques can differ radically, depending on design decisions related to ease of capture, use of geometry, accuracy of geometry (if used), number and distribution of source images, degrees of freedom for virtual navigation, and expected scene complexity.It is an invaluable resource for anyone planning or conducting research in this particular area, or computer graphics or vision generally. The essentials of the topic are presented in an accessible manner and an extensive bibliography guides towards further reading.