Bøger af Qi Wang

Memory, Subjectivity and Independent Chinese Cinema provides a historically informed examination of independent moving image works made between 1990 and 2010 in China. Showcasing an evolving personal mode of narrating memory, documenting reality, and inscribing subjectivity in over sixteen selected works that range from narrative film and documentary to experimental video and digital media (even including a multimedia avant-garde play), this book presents a provocative portrait of the independent filmmakers as a peculiarly pained yet active group of historical subjects of the transitional, post-socialist era. Through a connected investigation of cultural and cinematic concepts including historical consciousness, personal memory, narrative, performance, subjectivity, spatiality, and the body, Wang weaves a critical narrative of the formation of a unique post-socialist cultural consciousness that enables independent cinema and media to become a highly significant and effective conduit for historical thinking in contemporary China. Covering directors such as Zhang Yimou, Chen Kaige, Jia Zhangke, Jiang Wen, Lou Ye, Meng Jinghui, Wang Bing, Wang Guangli, Duan Jinchuan, Cui Zi'en, Shi Tou, and Tang Danhong, this book is essential reading for all students and scholars in Chinese film.

This book examines the field of surrounding rock control mechanisms and support technologies in underground engineering, and proposes a high-strength support system to address the complex conditions in underground engineering, such as high stress, extremely soft rocks, fault fracture zone and strong mining activity.

The book shows how various gender inequality issues are approached and analysed in the location of China by Chinese gender/social science scholars and how studies of gender inequality constitutes an astute critique of the neo-liberal capitalist development in China.

With the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field.