Institution
Beihang University
Education•Beijing, China•
About: Beihang University is a education organization based out in Beijing, China. It is known for research contribution in the topics: Control theory & Microstructure. The organization has 67002 authors who have published 73507 publications receiving 975691 citations. The organization is also known as: Beijing University of Aeronautics and Astronautics.
Topics: Control theory, Microstructure, Nonlinear system, Artificial neural network, Feature extraction
Papers published on a yearly basis
Papers
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TL;DR: A novel eigenvector based on time–frequency-wavelet joint features is proposed to effectively represent bearing degradation process and a deep autoencoder based joint features compression and computing method is presented to retain effective information without increasing the scale of DNN.
250 citations
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TL;DR: In this article, small size molybdenum disulfide (MoS2) quantum dots with desired optical properties were controllably synthesized by using tetrabutylammonium-assisted ultrasonication of multilayered MoS2 powder via OH-mediated chain-like MoS bond cleavage mode.
Abstract: Small size molybdenum disulfide (MoS2) quantum dots (QDs) with desired optical properties were controllably synthesized by using tetrabutylammonium-assisted ultrasonication of multilayered MoS2 powder via OH-mediated chain-like Mo–S bond cleavage mode. The tunable up-bottom approach of precise fabrication of MoS2 QDs finally enables detailed experimental investigations of their optical properties. The synthesized MoS2 QDs present good down-conversion photoluminescence behaviors and exhibit remarkable up-conversion photoluminescence for bioimaging. The mechanism of the emerging photoluminescence was investigated. Furthermore, superior 1O2 production ability of MoS2 QDs to commercial photosensitizer PpIX was demonstrated, which has great potential application for photodynamic therapy. These early affording results of tunable synthesis of MoS2 QDs with desired photo properties can lead to application in fields of biomedical and optoelectronics.
250 citations
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TL;DR: Electrochemical investigations show that stripping and plating of Li and Na and the robust and flexible passivation film formed in situ suppress dendrite and buffer alloy anode volume expansion and thus prevent cracking, avoiding electrolyte consumption and ensuring high electron transport efficiency and continued electrochemical reactions.
Abstract: Rechargeable aprotic alkali metal (Li or Na)-O2 batteries are the subject of great interest because of their high theoretical specific energy. However, the growth of dendrites and cracks at the Li or Na anode, as well as their corrosive oxidation lead to poor cycling stability and safety issues. Understanding the mechanism and improving Li/Na-ion plating and stripping electrochemistry are therefore essential to realizing their technological potential. Here, we report how the use of a Li-Na alloy anode and an electrolyte additive realizes an aprotic bimetal Li-Na alloy-O2 battery with improved cycling stability. Electrochemical investigations show that stripping and plating of Li and Na and the robust and flexible passivation film formed in situ (by 1,3-dioxolane additive reacting with the Li-Na alloy) suppress dendrite and buffer alloy anode volume expansion and thus prevent cracking, avoiding electrolyte consumption and ensuring high electron transport efficiency and continued electrochemical reactions.
250 citations
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28 Jun 2009TL;DR: An organized study of 16 external validation measures for K-means clustering by introducing the importance of measure normalization in the evaluation of the clustering performance on data with imbalanced class distributions and revealing the interrelationships among these external measures.
Abstract: Clustering validation is a long standing challenge in the clustering literature. While many validation measures have been developed for evaluating the performance of clustering algorithms, these measures often provide inconsistent information about the clustering performance and the best suitable measures to use in practice remain unknown. This paper thus fills this crucial void by giving an organized study of 16 external validation measures for K-means clustering. Specifically, we first introduce the importance of measure normalization in the evaluation of the clustering performance on data with imbalanced class distributions. We also provide normalization solutions for several measures. In addition, we summarize the major properties of these external measures. These properties can serve as the guidance for the selection of validation measures in different application scenarios. Finally, we reveal the interrelationships among these external measures. By mathematical transformation, we show that some validation measures are equivalent. Also, some measures have consistent validation performances. Most importantly, we provide a guide line to select the most suitable validation measures for K-means clustering.
250 citations
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TL;DR: In this article, a measurement of the H→ττ signal strength is performed using events recorded in proton-proton collisions by the CMS experiment at the LHC in 2016 at a center-of-mass energy of 13TeV.
250 citations
Authors
Showing all 67500 results
Name | H-index | Papers | Citations |
---|---|---|---|
Yi Chen | 217 | 4342 | 293080 |
H. S. Chen | 179 | 2401 | 178529 |
Alan J. Heeger | 171 | 913 | 147492 |
Lei Jiang | 170 | 2244 | 135205 |
Wei Li | 158 | 1855 | 124748 |
Shu-Hong Yu | 144 | 799 | 70853 |
Jian Zhou | 128 | 3007 | 91402 |
Chao Zhang | 127 | 3119 | 84711 |
Igor Katkov | 125 | 972 | 71845 |
Tao Zhang | 123 | 2772 | 83866 |
Nicholas A. Kotov | 123 | 574 | 55210 |
Shi Xue Dou | 122 | 2028 | 74031 |
Li Yuan | 121 | 948 | 67074 |
Robert O. Ritchie | 120 | 659 | 54692 |
Haiyan Wang | 119 | 1674 | 86091 |