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Institution

Northeastern University (China)

EducationShenyang, China
About: Northeastern University (China) is a education organization based out in Shenyang, China. It is known for research contribution in the topics: Control theory & Microstructure. The organization has 36087 authors who have published 36125 publications receiving 426807 citations. The organization is also known as: Dōngběi Dàxué & Northeastern University (东北大学).


Papers
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Journal ArticleDOI
TL;DR: By designing suitable robust adaptive synchronization controllers that have strong robustness against the uncertainties in coupling matrices, the all nodes states of complex networks globally asymptotically synchronize to a desired synchronization state.
Abstract: In this article, the synchronization problem of uncertain complex networks with multiple coupled time-varying delays is studied. The synchronization criterion is deduced for complex dynamical networks with multiple different time-varying coupling delays and uncertainties, based on Lyapunov stability theory and robust adaptive principle. By designing suitable robust adaptive synchronization controllers that have strong robustness against the uncertainties in coupling matrices, the all nodes states of complex networks globally asymptotically synchronize to a desired synchronization state. The numerical simulations are given to show the feasibility and effectiveness of theoretical results. © 2014 Wiley Periodicals, Inc. Complexity 20: 62-73, 2015

101 citations

Journal ArticleDOI
TL;DR: Simulation results are given to demonstrate that the proposed approaches can reduce the communication delay comparing to D2D-unicast based RA scheme, especially in a multiplatoon scenario with a large number of vehicles.
Abstract: With the significant population growth in megacities everywhere, traffic congestion is becoming a severe impediment, leading to long travel delays and large economic loss on a global scale. Platooning is a promising intelligent transportation framework that can improve road capacity, on-road safety, and fuel efficiency. Furthermore, enabling inter-vehicle communications within a platoon and among platoons (in a multiplatoon) can potentially enhance platoon control by keeping constant inter-vehicle and inter-platoon distances. However, an efficient resource allocation (RA) approach is required for the timely and successful delivery of inter-vehicle information within multiplatoons. In this paper, subchannel allocation scheme and power control mechanism are proposed for LTE-based inter-vehicle communications in a multiplatooning scenario. We jointly consider the evolved multimedia broadcast multicast services and device-to-device (D2D) multicast communications to enable intra- and inter-platoon communications such that a desired tradeoff between the required cellular resources and the imposed communication delay can be achieved. Simulation results are given to demonstrate that the proposed approaches can reduce the communication delay comparing to D2D-unicast based RA scheme, especially in a multiplatoon scenario with a large number of vehicles.

100 citations

Journal ArticleDOI
TL;DR: In this paper, the authors test the models of vacuum energy interacting with cold dark matter and try to probe the possible deviation from the standard $\mathrm{\ensuremath{\Lambda}}\mathrm{CDM}$ model using current observations.
Abstract: We test the models of vacuum energy interacting with cold dark matter and try to probe the possible deviation from the $\mathrm{\ensuremath{\Lambda}}\mathrm{CDM}$ model using current observations. We focus on two specific models, $Q=3\ensuremath{\beta}H{\ensuremath{\rho}}_{\mathrm{\ensuremath{\Lambda}}}$ and $Q=3\ensuremath{\beta}H{\ensuremath{\rho}}_{c}$. The data combinations come from the Planck 2013 data, the baryon acoustic oscillations measurements, the type-Ia supernovae data, the Hubble constant measurement, the redshift space distortions data and the galaxy weak lensing data. For the $Q=3\ensuremath{\beta}H{\ensuremath{\rho}}_{c}$ model, we find that it can be tightly constrained by all the data combinations, while for the $Q=3\ensuremath{\beta}H{\ensuremath{\rho}}_{\mathrm{\ensuremath{\Lambda}}}$ model, there still exist significant degeneracies between parameters. The tightest constraints for the coupling constant are $\ensuremath{\beta}={\ensuremath{-}0.026}_{\ensuremath{-}0.053}^{+0.036}$ (for $Q=3\ensuremath{\beta}H{\ensuremath{\rho}}_{\mathrm{\ensuremath{\Lambda}}}$) and $\ensuremath{\beta}=\ensuremath{-}0.00045\ifmmode\pm\else\textpm\fi{}0.00069$ (for $Q=3\ensuremath{\beta}H{\ensuremath{\rho}}_{c}$) at the $1\ensuremath{\sigma}$ level. For all the fit results, we find that the null interaction $\ensuremath{\beta}=0$ is always consistent with data. Our work completes the discussion on the interacting dark energy model in the recent Planck 2015 papers. Considering this work together with the Planck 2015 results, it is believed that there is no evidence for the models beyond the standard $\mathrm{\ensuremath{\Lambda}}\mathrm{CDM}$ model from the point of view of possible interaction.

100 citations

Journal ArticleDOI
15 Feb 2015-Fuel
TL;DR: In this paper, the performance of different ABE blends with different component volumetric ratio (A:B:E of 6:3:1, 3:6:1; 0:10:0) was investigated under LTC conditions (ambient temperature of 800 K with varying ambient oxygen content) and high speed camera and flame lift-off lengths were acquired.

100 citations

Journal ArticleDOI
TL;DR: A hybrid sampling algorithm called RFMSE, which combines the Misclassification-oriented Synthetic Minority Over-sampling TEchnique and Edited Nearest Neighbor based on Random Forest, is proposed, which can improve F-value and MCC more effectively.

100 citations


Authors

Showing all 36436 results

NameH-indexPapersCitations
Rui Zhang1512625107917
Hui-Ming Cheng147880111921
Yonggang Huang13679769290
Yang Liu1292506122380
Tao Zhang123277283866
J. R. Dahn12083266025
Terence G. Langdon117115861603
Frank L. Lewis114104560497
Xin Li114277871389
Peng Wang108167254529
David J. Hill107136457746
Jian Zhang107306469715
Xuemin Shen106122144959
Yi Zhang102181753417
Tao Li102248360947
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023166
2022906
20214,689
20204,118
20193,653
20182,878