Offering important insights into the changing higher education policy context in an age increasingly defined by globalization, China's Rising Research Universities will appeal to higher education leaders and policymakers; students, faculty, and scientists who interact with Chinese counterparts; and scholars of international and comparative studies.
Offering important insights into the changing higher education policy context in an age increasingly defined by globalization, China's Rising Research Universities will appeal to higher education leaders and policymakers; students, faculty, and scientists who interact with Chinese counterparts; and scholars of international and comparative studies.
China’s residential real estate sector plays an important role in the economy and has been a key driver of growth. Since 2014 the sector has softened visibly, reflecting overbuilding across many cities. An orderly adjustment of the sector is welcome. The key questions are how severe the adjustment will be and how long it will last. This paper uses various datasets, an analytical framework to estimate demand and supply conditions, and develops a number of scenarios to determine the oversupply both at the national level and by city tiers. It highlights that the adjustment will be a multiyear process with adverse implications for investment and growth. Smaller cities, as well as those in the Northeast region, face more challenging demand-supply dynamics. The key will be to allow the adjustment to take place, while avoiding a too sharp of an economic slowdown.
Global Navigation Satellite Systems (GNSS), such as GPS, have become an efficient, reliable and standard tool for a wide range of applications. However, when processing GNSS data, the stochastic model characterising the precision of observations and the correlations between them is usually simplified and incomplete, leading to overly optimistic accuracy estimates. This work extends the stochastic model using signal-to-noise ratio (SNR) measurements and time series analysis of observation residuals. The proposed SNR-based observation weighting model significantly improves the results of GPS data analysis, while the temporal correlation of GPS observation noise can be efficiently described by means of autoregressive moving average (ARMA) processes. Furthermore, this work includes an up-to-date overview of the GNSS error effects and a comprehensive description of various mathematical methods.
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