• STI Policy Review
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• v.4 no.2
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• pp.74-95
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• 2013

Rapid changes in the economic, social and academic environments often provide opportunities to develop new and advanced technologies. In China, recent literature on the role of universities suggests that university-industry linkages (UILs) play a substantial role in the development of high-tech industries. Since 1979 when the country became more open and underwent economic reform, Chinese central authorities, local governments, and universities have continued to set up various science and technology (S&T) policies to stimulate UILs, contributing to China's technological progress and economic growth. This study examines the role of S&T policies on UILs such as transfer of technology, joint research, and spin-off creation with a particular focus on Nanjing University (NJU) in Jiangsu Province. Nanjing has over 53 universities, ranking it behind Beijing and Shanghai in terms of S&T and higher education opportunities. By adopting "institutional methodology," this study contends that UILs not only benefit universities and industry but also society in terms of job training, consulting activities, joint research, R&D results commercialization, patent licensing, new business creation, and other aspects. Finally, we suggest that the Chinese experience, though with some problems, might enhance our understanding of how to stimulate UILs through the arrangement of various S&T policies.

• STI Policy Review
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• v.7 no.2
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• pp.16-34
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• 2016

This study aims to identify the chronological trajectory of university science parks (USPs) in China and to discuss the roles of government-driven science and technology (S&T) policies in the development of USPs and the future directions of these entities. Our study shows that USPs in China have undergone two development waves: The first from the late 1980s to the late 1990s, when research universities expected to directly participate in economic activities, and the second from 2000 when the Ministry of Science and Technology (MOST) and the Ministry of Education (MOE) jointly enacted the Proposed Regulation of State-level USPs Management to guide and regulate the development of USPs. The development trajectory highlights that USPs are effective platforms that link scientific research, knowledge spillovers and industrial system. However, Chinese USPs still need to confront some conundrums which may influence the processes and outcomes of UILs. Finally, we also summarize the major issues inherent in the development of USPs to guide policymakers to enact more effective policies.

• Smart Structures and Systems
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• v.24 no.5
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• pp.617-630
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• 2019

Currently most of the vision-based structural identification research focus either on structural input (vehicle location) estimation or on structural output (structural displacement and strain responses) estimation. The structural condition assessment at global level just with the vision-based structural output cannot give a normalized response irrespective of the type and/or load configurations of the vehicles. Combining the vision-based structural input and the structural output from non-contact sensors overcomes the disadvantage given above, while reducing cost, time, labor force including cable wiring work. In conventional traffic monitoring, sometimes traffic closure is essential for bridge structures, which may cause other severe problems such as traffic jams and accidents. In this study, a completely non-contact structural identification system is proposed, and the system mainly targets the identification of bridge unit influence line (UIL) under operational traffic. Both the structural input (vehicle location information) and output (displacement responses) are obtained by only using cameras and computer vision techniques. Multiple cameras are synchronized by audio signal pattern recognition. The proposed system is verified with a laboratory experiment on a scaled bridge model under a small moving truck load and a field application on a footbridge on campus under a moving golf cart load. The UILs are successfully identified in both bridge cases. The pedestrian loads are also estimated with the extracted UIL and the predicted weights of pedestrians are observed to be in acceptable ranges.