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Institution

Nanjing University of Science and Technology

EducationNanjing, China
About: Nanjing University of Science and Technology is a education organization based out in Nanjing, China. It is known for research contribution in the topics: Catalysis & Computer science. The organization has 31581 authors who have published 36390 publications receiving 525474 citations. The organization is also known as: Nánjīng Lǐgōng Dàxué & Nánlǐgōng.


Papers
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Journal ArticleDOI
TL;DR: A joint direction of departures (DODs) and direction of arrivals (DOAs) estimation for bistatic MIMO radar via both ESPRIT and SVD of cross-correlation matrix of the received data from two transmit subarrays is presented and the maximum number of targets can be identified by using this method.

118 citations

Journal ArticleDOI
TL;DR: In this article, a novel tannic acid assisted interfacial polymerization (TAIP) method was developed for preparing loose nanofiltration membranes (LNMs), which resulted in enlarged pores in the skin layer due to the longer monomers.

118 citations

Journal ArticleDOI
TL;DR: X-ray analysis and comparison with curcumin reveals that the presence of cyclohexanone in 3c, which remotely resembles the 6-membered ring in the enol tautomer inCurcumin, may play an important role in the bioactivity.

118 citations

Journal ArticleDOI
TL;DR: Experiments on six microarray data sets show that the fast algorithm can effectively reduce the computational time in comparison with the naive algorithm when facing high dimensional data sets, and it is shown that fast algorithm is useful in decreasing the computationalTime of finding both traditional reduct and attribute clustering based reduct.
Abstract: Dynamic updating of the rough approximations is a critical factor for the success of the rough set theory since data is growing at an unprecedented rate in the information-explosion era. Though many updating schemes have been proposed to study such problem, few of them were carried out in a multigranulation environment. To fill such gap, the updating of the multigranulation rough approximations is firstly explored in this paper. Both naive and fast algorithms are presented for updating the multigranulation rough approximations with the increasing of the granular structures. Different from the naive algorithm, the fast algorithm is designed based on the monotonic property of the multigranulation rough approximations. Experiments on six microarray data sets show us that the fast algorithm can effectively reduce the computational time in comparison with the naive algorithm when facing high dimensional data sets. Moreover, it is also shown that fast algorithm is useful in decreasing the computational time of finding both traditional reduct and attribute clustering based reduct.

118 citations


Authors

Showing all 31818 results

NameH-indexPapersCitations
Jian Yang1421818111166
Liming Dai14178182937
Hui Li1352982105903
Jian Zhou128300791402
Shuicheng Yan12381066192
Zidong Wang12291450717
Xin Wang121150364930
Xuan Zhang119153065398
Zhenyu Zhang118116764887
Xin Li114277871389
Zeshui Xu11375248543
Xiaoming Li113193272445
Chunhai Fan11270251735
H. Vincent Poor109211667723
Qian Wang108214865557
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023107
2022594
20214,309
20203,990
20193,920
20183,211