Key findings of the 2016 symposium on the frontiers of chemical science and engineering: Environment and sustainable development

doi:10.1007/s11705-017-1666-7

Front. Chem. Sci. Eng.

2017, Vol. 11

Issue (3) : 305-307 https://doi.org/10.1007/s11705-017-1666-7

VIEWS & COMMENTS

Key findings of the 2016 symposium on the frontiers of chemical science and engineering: Environment and sustainable development

Zhongming Lu¹, Duo Li², John C. Crittenden³(

)

¹. School of Environment, Beijing Normal University, Beijing 100875, China
². Crittenden and Associates, Beijing 100102, China
³. Brook Byers Institute for Sustainable Systems, School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0355, USA

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Corresponding Author(s): John C. Crittenden

Online First Date: 28 July 2017 Issue Date: 23 August 2017

Cite this article:

Zhongming Lu,Duo Li,John C. Crittenden. Key findings of the 2016 symposium on the frontiers of chemical science and engineering: Environment and sustainable development[J]. Front. Chem. Sci. Eng., 2017, 11(3): 305-307.

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https://academic.hep.com.cn/fcse/EN/10.1007/s11705-017-1666-7
https://academic.hep.com.cn/fcse/EN/Y2017/V11/I3/305

Fig.1 Keywords and the interpretation of the six topics in this symposium

Fig.2 Sharing of topics (i.e., the percentage of the contents related to each topic) in abstracts: the title of each abstract is not complete due to space limit but it provides a basic idea of the content for each abstract

1	Symposium on Frontiers of Chemical Science and Engineering: Environment and Sustainable Development. 2017,
2	Kuang D, Park H. Fast rank-2 nonnegative matrix factorization for hierarchical document clustering. In: Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Chicago: ACM Press, 2013, 739–747
3	Xu W, Liu X, Gong Y. Document clustering based on non-negative matrix factorization. In: Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. Chicago: ACM Press, 2003, 267–273

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