The Chinese financial sector, despite having been developed at a much later stage compared with other developed nations, has achieved substantial progresses over the past decades. By the end of 2014, a total of 16 commercial banks had been listed on the stock exchanges, exerting strong impact onto the market indices and contributing significantly to the country's sustained economic growth. This book reviews the evolution of the Chinese financial system, examining the effectiveness of reform strategies made by the government over the last ten years. The first chapter offers a comprehensive review of the development of the Chinese banking sector and the state-owned banks (SOBs). The second chapter focuses on the efficiency of the Chinese banking sector. Employing data envelopment analysis (DEA) and stochastic frontier analysis (SFA), the author tests the change of efficiency within the Chinese banking sector over the past decade. It also looks at the strategy adopted by the Chinese government as the final attempt in reforming its troublesome SOBs and the effectiveness of such a reform strategy. The next chapter examines the corporate governance practise of the Chinese commercial banks, and the author follows by investigating the effect of the 2007 US credit crunch on Chinese banks and the country's wider economy. Other chapters survey the influence of foreign entry to the Chinese domestic banking sector, and the development of shadow banking in China. The author concludes by discussing the role of the central bank, namely the People's Bank of China (PBOC), and its role in implementing effective policies to promote economic growth.

Muslim minorities in China and India form only a small fraction of their respective populations, yet as they principally live in troubled border states, they are of key strategic importance in the war on terror. In this global context, this book explores whether economics is more important than the suppression of rights in explaining social unrest.

This book delivers a course module for advanced undergraduates, postgraduates and researchers of electronics, computing science, medical imaging, or wherever the study of identification and classification of objects by electronics-driven image processing and pattern recognition is relevant. Object analysis first uses image processing to detect objects and extract their features, then identifies and classifies them by pattern recognition. Its manifold applications include recognition of objects in satellite images which enable discrimination between different objects, such as fishing boats, merchant ships or warships; machine spare parts e.g. screws, nuts etc. (engineering); detection of cancers, ulcers, tumours and so on (medicine); and recognition of soil particles of different types (agriculture or soil mechanics in civil engineering).
Outlines the identification and classification of objects by electronics-driven image processing and pattern recognitionDiscusses object detection, shape, roundness and sharpness analysis, orientation analysis and arrangement analysisDelivers a course module for advanced undergraduates, postgraduates and researchers of electronics, computing science and medical imaging