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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: Microstructure & Control theory. 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: In the proposed method, the feedback signals and the NN weights are aperiodically updated only when the event-triggered condition is violated, and the number of transmissions can be significantly reduced.
Abstract: This paper is concerned with the adaptive event-triggered control problem of nonlinear continuous-time systems in strict-feedback form. By using the event-sampled neural network (NN) to approximate the unknown nonlinear function, an adaptive model and an associated event-triggered controller are designed by exploiting the backstepping method. In the proposed method, the feedback signals and the NN weights are aperiodically updated only when the event-triggered condition is violated. A positive lower bound on the minimum intersample time is guaranteed to avoid accumulation point. The closed-loop stability of the resulting nonlinear impulsive dynamical system is rigorously proved via Lyapunov analysis under an adaptive event sampling condition. In comparing with the traditional adaptive backstepping design with a fixed sample period, the event-triggered method samples the state and updates the NN weights only when it is necessary. Therefore, the number of transmissions can be significantly reduced. Finally, two simulation examples are presented to show the effectiveness of the proposed control method.

211 citations

Journal ArticleDOI
TL;DR: Ionic liquid 1-butyl-3-methylimidazolium hexafluorophosphate (BmimPF6), as a green solvent, was successfully used for the direct extraction of dsDNA and a procedure for DNA quantification in ionic liquid was developed based on this observation.
Abstract: Ionic liquid 1-butyl-3-methylimidazolium hexafluorophosphate (BmimPF6), as a green solvent, was successfully used for the direct extraction of dsDNA The extraction efficiency and the distribution coefficient values indicated that trace amounts of DNA at the levels of <5 ng μL-1 facilitate quantitative fast extraction, while proteins and metal species do not interfere A total of 30% of the DNA in ionic liquid at ∼20 ng μL-1 was back extracted into aqueous phase in phosphate−citrate buffer with a single−stage extraction The extraction is demonstrated to be endothermic with an enthalpy of 343 kJ moL-1 The extraction mechanisms were proposed and verified by 31P NMR and FT-IR spectra Interactions between cationic 1-butyl-3-methylimidazolium (Bmim+) and P−O bonds of phosphate groups in the DNA strands take place both in the dissolved BmimPF6 in aqueous phase and at the interface of the two phases This interaction consequently led to the transformation of DNA conformations, along with a reduction of ethid

211 citations

Journal ArticleDOI
TL;DR: It was concluded that the Cu content affects the Cu existence and the Cu ion release behavior, which in turn influences the antibacterial property.

210 citations

Journal ArticleDOI
TL;DR: In this paper, the cosmological constraints on the holographic Ricci dark energy model were derived from the latest observational data including the Union sample of 307 type Ia supernovae, the shift parameter of the cosmic microwave background given by the five-year Wilkinson Microwave Anisotropy Probe observations, and the baryon acoustic oscillation measurement from the Sloan Digital Sky Survey.
Abstract: In this work, we consider the cosmological constraints on the holographic Ricci dark energy proposed by Gao et al [Phys Rev D 79, 043511 (2009)], by using the observational data currently available The main characteristic of holographic Ricci dark energy is governed by a positive numerical parameter $\ensuremath{\alpha}$ in the model When $\ensuremath{\alpha}l1/2$, the holographic Ricci dark energy will exhibit a quintomlike behavior; ie, its equation of state will evolve across the cosmological-constant boundary $w=\ensuremath{-}1$ The parameter $\ensuremath{\alpha}$ can be determined only by observations Thus, in order to characterize the evolving feature of dark energy and to predict the fate of the Universe, it is of extraordinary importance to constrain the parameter $\ensuremath{\alpha}$ by using the observational data In this paper, we derive constraints on the holographic Ricci dark energy model from the latest observational data including the Union sample of 307 type Ia supernovae, the shift parameter of the cosmic microwave background given by the five-year Wilkinson Microwave Anisotropy Probe observations, and the baryon acoustic oscillation measurement from the Sloan Digital Sky Survey The joint analysis gives the best-fit results (with $1\ensuremath{\sigma}$ uncertainty): $\ensuremath{\alpha}={0359}_{\ensuremath{-}0025}^{+0024}$ and ${\ensuremath{\Omega}}_{\mathrm{m}0}={0318}_{\ensuremath{-}0024}^{+0026}$ That is to say, according to the observations, the holographic Ricci dark energy takes on the quintom feature Finally, in light of the results of the cosmological constraints, we discuss the issue of the scalar-field dark energy reconstruction, based on the scenario of the holographic Ricci vacuum energy

208 citations

Journal ArticleDOI
01 Mar 2011
TL;DR: Computational experiments with a set of large-scale instances show that the NGHS can be an efficient alternative for solving 0-1 knapsack problems.
Abstract: This paper proposes a novel global harmony search algorithm (NGHS) to solve 0-1 knapsack problems. The proposed algorithm includes two important operations: position updating and genetic mutation with a small probability. The former enables the worst harmony of harmony memory to move to the global best harmony rapidly in each iteration, and the latter can effectively prevent the NGHS from trapping into the local optimum. Computational experiments with a set of large-scale instances show that the NGHS can be an efficient alternative for solving 0-1 knapsack problems.

206 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
20214,691
20204,118
20193,653
20182,878