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Search Results: 1 - 10 of 81338 matches for " Chong Liu "
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Robust Semiparametric Optimal Testing Procedure for Multiple Normal Means
Peng Liu,Chong Wang
Journal of Probability and Statistics , 2012, DOI: 10.1155/2012/913560
Abstract: In high-dimensional gene expression experiments such as microarray and RNA-seq experiments, the number of measured variables is huge while the number of replicates is small. As a consequence, hypothesis testing is challenging because the power of tests can be very low after controlling multiple testing error. Optimal testing procedures with high average power while controlling false discovery rate are preferred. Many methods were constructed to achieve high power through borrowing information across genes. Some of these methods can be shown to achieve the optimal average power across genes, but only under a normal assumption of alternative means. However, the assumption of a normal distribution is likely violated in practice. In this paper, we propose a novel semiparametric optimal testing (SPOT) procedure for high-dimensional data with small sample size. Our procedure is more robust because it does not depend on any parametric assumption for the alternative means. We show that the proposed test achieves the maximum average power asymptotically as the number of tests goes to infinity. Both simulation study and the analysis of a real microarray data with spike-in probes show that the proposed SPOT procedure performs better when compared to other popularly applied procedures.
On the validity of the Navier-Stokes equations for nanoscale liquid flows: The role of channel size
Chong Liu,Zhigang Li
AIP Advances , 2011, DOI: 10.1063/1.3621858
Abstract: In this work, we investigate the validity of the Navier-Stokes (NS) equations for nanoscale liquid flows through molecular dynamics simulations. We focus on the role of channel size by considering the fluid-wall interaction. Liquid flows between two planar parallel walls driven by an external force with channel size ranging from 2 to 80 nm are studied. The volumetric flux is computed and the dependence of the volumetric flux on the channel size is explained both qualitatively and quantitatively. It is found that the flow is sensitive to the fluid-wall binding energy and the classical fluid mechanics falls apart in small nanochannels. However, the wall effects become insignificant and the NS equations are valid when the channel size is larger than about 150 molecular diameters (~ 50 nm).
Reversal-mechanism of in-plane current induced perpendicular switching in a single ferromagnetic layer
Chong Bi,Ming Liu
Physics , 2014,
Abstract: We propose a magnetization reversal model to explain the perpendicular switching of a single ferromagnetic layer induced by an in-plane current. Contrary to previously proposed reversal mechanisms that such magnetic switching is directly from the Rashba or spin Hall effects, we suggest that this type of switching arises from the current-induced chirality dependent domain wall motion. By measuring the field dependent switching behaviors, we show that such switching can also be achieved between any two multidomain states, and all of these switching behaviors can be well explained by this model. This model indicates that the spin Hall angle in such structures may be overestimated and also predicts similar switching behaviors in other ferromagnetic structures with chiral domain walls or skyrmions.
Homology of saddle point reduction and applications to resonant elliptic systems
Chong Li,Shibo Liu
Mathematics , 2012,
Abstract: In the setting of saddle point reduction, we prove that the critical groups of the original functional and the reduced functional are isomorphic. As application, we obtain two nontrivial solutions for elliptic gradient systems which may be resonant both at the origin and at infinity. The difficulty that the variational functional does not satisfy the Palais-Smale condition is overcame by taking advantage of saddle point reduction. Our abstract results on critical groups are crucial.
Brake subharmonic solutions of first order Hamiltonian systems
Chong Li,Chungen Liu
Mathematics , 2009, DOI: 10.1007/s11425-010-4105-5
Abstract: In this paper, we mainly use the Galerkin approximation method and the iteration inequalities of the $L$-Maslov type index theory to study the properties of brake subharmonic solutions for the first order non-autonomous Hamiltonian systems. We prove that when the positive integers $j$ and $k$ satisfies the certain conditions, there exists a $jT$-periodic nonconstant brake solution $z_{j}$ such that $z_{j}$ and $z_{kj}$ are distinct.
Adsorption of Quaternary Ammonium Compounds onto Activated Sludge  [PDF]
Rong Ren, Dongfang Liu, Kexun Li, Jie Sun, Chong Zhang
Journal of Water Resource and Protection (JWARP) , 2011, DOI: 10.4236/jwarp.2011.32012
Abstract: The performance of activated sludge in the removal of tetradecyl benzyl dimethyl ammonium chloride (C14BDMA) by adsorption from aqueous solution was investigated with different PH, contact time, ionic strength and temperature. Equilibrium was achieved within 2 h of contact time. The adsorption capacity increased largely with increasing solution pH and remained constant above pH 9. The ionic strength had a negative effect on C14BDMA removal. The adsorption isotherms were analyzed by Langmuir and Freundlich isotherm models, and equilibrium partitioning data was described well by both models. Kinetics data was best described by the pseudo second-order model. Experimental results indicated that the adsorption was favorable at lower temperatures. Thermodynamic parameters, including the Gibbs free energy (ΔG0), enthalpy (ΔH0), and entropy (ΔS0), were also calculated. These parameters indicated that adsorption of C14BDMA onto activated sludge was feasible, spontaneous and exothermic in the temperature range of 15-35℃. The activated sludge was shown to be an effective adsorbent for C14BDMA.
A novel four-dimensional autonomous hyperchaotic system

Liu Chong-Xin,Liu Ling,

中国物理 B , 2009,
Abstract: A novel four-dimensional autonomous hyperchaotic system is reported in this paper. Some basic dynamical properties of the new hyperchaotic system are investigated in detail by means of a continuous spectrum, Lyapunov exponents, fractional dimensions, a strange attractor and Poincaré mapping. The dynamical behaviours of the new hyperchaotic system are proved by not only performing numerical simulation and brief theoretical analysis but also by conducting an electronic circuit experiment.
Circuit implementation of a new hyperchaos in fractional-order system

Liu Chong-Xin,Liu Ling,

中国物理 B , 2008,
Abstract: This paper introduces a new four-dimensional (4D) hyperchaotic system, which has only two quadratic nonlinearity parameters but with a complex topological structure. Some complicated dynamical properties are then investigated in detail by using bifurcations, Poincar\'{e} mapping, LE spectra. Furthermore, a simple fourth-order electronic circuit is designed for hardware implementation of the 4D hyperchaotic attractors. In particular, a remarkable fractional-order circuit diagram is designed for physically verifying the hyperchaotic attractors existing not only in the integer-order system but also in the fractional-order system with an order as low as 3.6.
Polarization Jitters Caused by Fiber Nonlinearity in PM Optical Communication System  [PDF]
Lan-Lan Liu, Chong-Qing Wu, Wei Yang, Jian Wang, Guo-Dong Liu
Optics and Photonics Journal (OPJ) , 2013, DOI: 10.4236/opj.2013.32B048

The phenomenon of polarization jitters caused by fiber nonlinearity is investigated. A general formula about the polarization jitter is concluded in polarization multiplexing (PM) system based on two orthogonal linear polarization states when the best polarization correction is used. A 100 Gb/s PM system based on NRZ code is investigated by simulation, and the Stocks parameter about polarization jitter and Poincare sphere diagrams are got for different power and phase difference of two orthogonal polarized light. The results show that the polarization jitters will be suppressed when the combined PM signal is the linear or circular polarization state.

Application of Chaos and Neural Network in Power Load Forecasting
Li Li,Liu Chong-xin
Discrete Dynamics in Nature and Society , 2011, DOI: 10.1155/2011/597634
Abstract: This paper employs chaos theory into power load forecasting. Lyapunov exponents on chaos theory are calculated to judge whether it is a chaotic system. Delay time and embedding dimension are calculated to reconstruct the phase space and determine the structure of artificial neural network (ANN). Improved back propagation (BP) algorithm based on genetic algorithm (GA) is used to train and forecast. Finally, this paper uses the load data of Shaanxi province power grid of China to complete the short-term load forecasting. The results show that the model in this paper is more effective than classical standard BP neural network model. 1. Introduction Chaos theory is the important component of the nonlinear science [1]. It is the random phenomena which appeared in the deterministic nonlinear dynamic system. Chaos is not a disorder but has a delicate inner structure. It reveals the order and regularity hidden behind the disordered and complex phenomena. Since the 90s, chaos theory has been well developed. Many subjects are infiltrated and promoted [2] under this tendency. So the research on chaos gets an access to a breakthrough. At the meanwhile the application about chaos theory gets a widely growing. Short-term power load forecasting is a multidimensional nonlinear system. It is easy to get the load time series in power system. But these data are nonlinear and difficult to establish a matched mathematical model to forecast the next-hour load. Recently, more and more nonlinear time series forecasting models based on chaos theory [3, 4] are applied to power short-term load forecasting. And they have achieved good prediction results. So chaos theory is employed to analyze the characters of the load time series and applied into the power system forecasting in this paper. There are many models to be adopted into power system load forecasting. They can generally be summarized as follows: time series model, regression model, expert system model, grey theory model, and fuzzy logic model. But according to chaotic characters of the load time series, ANN [5–9] is established and applied into the power system well. In view of neural network parallel processing and powerful nonlinear mapping ability, chaotic time series can be learned for unknown dynamic system and then predicted and controlled. As chaotic time series have an inner deterministic regularity which stems from nonlinearity, it represents the relevance of the time series on time delay state space. The feature makes the system have some kind of memory capacity. However it is difficult to express the
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