Nanjing Audit University

About: Nanjing Audit University is a education organization based out in Nanjing, China. It is known for research contribution in the topics: Data envelopment analysis & China. The organization has 1316 authors who have published 1781 publications receiving 15752 citations.

The sixth visual object tracking VOT2018 challenge results

Abstract: The Visual Object Tracking challenge VOT2018 is the sixth annual tracker benchmarking activity organized by the VOT initiative. Results of over eighty trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The evaluation included the standard VOT and other popular methodologies for short-term tracking analysis and a “real-time” experiment simulating a situation where a tracker processes images as if provided by a continuously running sensor. A long-term tracking subchallenge has been introduced to the set of standard VOT sub-challenges. The new subchallenge focuses on long-term tracking properties, namely coping with target disappearance and reappearance. A new dataset has been compiled and a performance evaluation methodology that focuses on long-term tracking capabilities has been adopted. The VOT toolkit has been updated to support both standard short-term and the new long-term tracking subchallenges. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The dataset, the evaluation kit and the results are publicly available at the challenge website (http://votchallenge.net).

Variability in the analysis of a single neuroimaging dataset by many teams

Abstract: Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses1. The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset2-5. Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed.

Exploring an Inverted U-Shape Relationship between Entrepreneurial Orientation and Performance in Chinese Ventures

Abstract: The critical role of entrepreneurial orientation (EO) in firm performance has been widely studied in the U.S. context. However, the examination of this key construct in emerging regions such as Chi...

Green innovation and firm performance: Evidence from listed companies in China

Abstract: This paper focuses on how green patenting influences a firm’s subsequent performance. By investigating listed manufacturing firms in China for the 2000–2010 period, we find a positive and significant relationship between green patenting and firm performance. Moreover, our research reveals that green growth is mainly driven by green utility-model patents and that this positive relationship only exists among state-owned enterprises (SOEs), which are more capable of leveraging green innovation through their close relationship with the government. Furthermore, the positive relationship is found to exist primarily after 2006, when the government began to provide formal legislative support to green industry.