This book employs a qualitative analysis of China's publicly financed construction sector, taking the system design as its point of departure and applying comprehensive evaluation techniques to create an index system for this type of construction - which in turn serves as a basis for quantitatively evaluating China's publicly financed construction sector. Given the fact that China's publicly financed construction sector is a very complex field of systems engineering involving multiple subsystems, as an important indicator of China's fiscal innovations since its reform and opening, publicly financed construction is now shifting from theory to practice, demonstrating that China has entered an era of fully publicly financed construction.

The book starts with an introduction on silicon isotopes and related analytical methods, and explains the mechanisms of silicon isotope fractionation. Silicon isotope distributions in lithosphere, hydrosphere and biosphere are shown based on results from field studies, and silicon isotope relevance for applications are presented.

This book employs a qualitative analysis of China's publicly financed construction sector, taking the system design as its point of departure and applying comprehensive evaluation techniques to create an index system for this type of construction - which in turn serves as a basis for quantitatively evaluating China's publicly financed construction sector. Given the fact that China's publicly financed construction sector is a very complex field of systems engineering involving multiple subsystems, as an important indicator of China's fiscal innovations since its reform and opening, publicly financed construction is now shifting from theory to practice, demonstrating that China has entered an era of fully publicly financed construction.

This book constitutes the refereed proceedings of the 17 International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2016, held in Yangzhou, China, in October 2016. The 68 full papers presented were carefully reviewed and selected from 115 submissions. They provide a valuable and timely sample of latest research outcomes in data engineering and automated learning ranging from methodologies, frameworks, and techniques to applications including various topics such as evolutionary algorithms; deep learning; neural networks; probabilistic modeling; particle swarm intelligence; big data analysis; applications in regression, classification, clustering, medical and biological modeling and predication; text processing and image analysis.