arXiv subjects

Rui Chen

Publications and source records attributed to Rui Chen.

At least 451 records · Page 25Linked to original sources

arXiv2017

Stochastic Flow Models with Delays and Applications to Multi-Intersection Traffic Light Control

We extend Stochastic Flow Models (SFMs), used for a large class of discrete event and hybrid systems, by including the delays which typically arise in flow movement. We apply this framework to the multi-intersection traffic light control problem by including transit delays for vehicles moving from one intersection to the next. Using Infinitesimal Perturbation Analysis (IPA) for this SFM with delays, we derive new on-line gradient estimates of several congestion cost metrics with respect to the controllable green and red cycle lengths. The IPA estimators are used to iteratively adjust light cycle lengths to improve performance and, in conjunction with a standard gradient-based algorithm, to obtain optimal values which adapt to changing traffic conditions. We introduce two new cost metrics to better capture congestion and show that the inclusion of delays in our analysis leads to improved performance relative to models that ignore delays.

eess.SY↗

arXiv2017

Second Order, linear and unconditionally energy stable schemes for a hydrodynamic model of Smectic-A Liquid Crystals

In this paper, we consider the numerical approximations for a hydrodynamical model of smectic-A liquid crystals. The model, derived from the variational approach of the modified Oseen-Frank energy, is a highly nonlinear system that couples the incompressible Navier-Stokes equations and a constitutive equation for the layer variable. We develop two linear, second-order time-marching schemes based on the "Invariant Energy Quadratization" method for nonlinear terms in the constitutive equation, the projection method for the Navier-Stokes equations, and some subtle implicit-explicit treatments for the convective and stress terms. Moreover, we prove the well-posedness of the linear system and their unconditionally energy stabilities rigorously. Various numerical experiments are presented to demonstrate the stability and the accuracy of the numerical schemes in simulating the dynamics under shear flow and the magnetic field.

math.NA↗

arXiv2017

Possible strange hidden-charm pentaquarks from $Σ_c^{()}\bar{D}_s^$ and $Ξ^{(',)}_c\bar{D}^$ interactions

Using the one-boson-exchange model, we investigate the $Λ_c\bar{D}_s^*$, $Σ_c\bar{D}_s^*$, $Σ_c^*\bar{D}_s^*$, $Ξ_c\bar{D}^*$, $Ξ_c'\bar{D}^*$, and $Ξ_c^*\bar{D}^*$ interactions by considering the one-eta-exchange and/or one-pion-exchange contributions. We further predict the existence of hidden-charm molecular pentaquarks. Promising candidates for hidden-charm molecular pentaquarks include a $Ξ_c'\bar{D}^*$ state with $0(\frac{1}{2}^-)$ and the $Ξ_c^*\bar{D}^*$ states with $0(\frac{1}{2}^-)$ and $0(\frac{3}{2}^-)$. Experimental searches for these predicted hidden-charm molecular pentaquarks are an interesting future research topic for experiments like LHCb.

hep-ph↗

arXiv2017

Dynamic Semiparametric Models for Expected Shortfall (and Value-at-Risk)

Expected Shortfall (ES) is the average return on a risky asset conditional on the return being below some quantile of its distribution, namely its Value-at-Risk (VaR). The Basel III Accord, which will be implemented in the years leading up to 2019, places new attention on ES, but unlike VaR, there is little existing work on modeling ES. We use recent results from statistical decision theory to overcome the problem of "elicitability" for ES by jointly modelling ES and VaR, and propose new dynamic models for these risk measures. We provide estimation and inference methods for the proposed models, and confirm via simulation studies that the methods have good finite-sample properties. We apply these models to daily returns on four international equity indices, and find the proposed new ES-VaR models outperform forecasts based on GARCH or rolling window models.

econ.GN↗

arXiv2017

Topological Anderson insulator phase in a Dirac-semimetal thin film

The recently discovered topological Dirac semimetal represents a new exotic quantum state of matter. Topological Dirac semimetals can be viewed as three dimensional analogues of graphene, in which the Dirac nodes are protected by crystalline symmetry. It has been found that quantum confinement effect can gap out Dirac nodes and convert Dirac semimetal to a band insulator. The band insulator is either normal insulator or quantum spin Hall insulator depending on the thin film thickness. We present the study of disorder effects in thin film of Dirac semimetals. It is found that moderate Anderson disorder strength can drive a topological phase transition from normal band insulator to topological Anderson insulator in Dirac semimetal thin film. The numerical calculation based on the model parameters of Dirac semimetal Na$_{3}$Bi shows that in the topological Anderson insulator phase a quantized conductance plateau occurs in the bulk gap of band insulator, and the distributions of local currents further confirm that the quantized conductance plateau arises from the helical edge states induced by disorder. Finally, an effective medium theory based on Born approximation fits the numerical data.

cond-mat.mes-hall↗

arXiv2017

Bayer Demosaicking Using Optimized Mean Curvature over RGB channels

Color artifacts of demosaicked images are often found at contours due to interpolation across edges and cross-channel aliasing. To tackle this problem, we propose a novel demosaicking method to reliably reconstruct color channels of a Bayer image based on two different optimized mean-curvature (MC) models. The missing pixel values in green (G) channel are first estimated by minimizing a variational MC model. The curvatures of restored G-image surface are approximated as a linear MC model which guides the initial reconstruction of red (R) and blue (B) channels. Then a refinement process is performed to interpolate accurate full-resolution R and B images. Experiments on benchmark images have testified to the superiority of the proposed method in terms of both the objective and subjective quality.

cs.CV↗

arXiv2017

Learning a collaborative multiscale dictionary based on robust empirical mode decomposition

Dictionary learning is a challenge topic in many image processing areas. The basic goal is to learn a sparse representation from an overcomplete basis set. Due to combining the advantages of generic multiscale representations with learning based adaptivity, multiscale dictionary representation approaches have the power in capturing structural characteristics of natural images. However, existing multiscale learning approaches still suffer from three main weaknesses: inadaptability to diverse scales of image data, sensitivity to noise and outliers, difficulty to determine optimal dictionary structure. In this paper, we present a novel multiscale dictionary learning paradigm for sparse image representations based on an improved empirical mode decomposition. This powerful data-driven analysis tool for multi-dimensional signal can fully adaptively decompose the image into multiscale oscillating components according to intrinsic modes of data self. This treatment can obtain a robust and effective sparse representation, and meanwhile generates a raw base dictionary at multiple geometric scales and spatial frequency bands. This dictionary is refined by selecting optimal oscillating atoms based on frequency clustering. In order to further enhance sparsity and generalization, a tolerance dictionary is learned using a coherence regularized model. A fast proximal scheme is developed to optimize this model. The multiscale dictionary is considered as the product of oscillating dictionary and tolerance dictionary. Experimental results demonstrate that the proposed learning approach has the superior performance in sparse image representations as compared with several competing methods. We also show the promising results in image denoising application.

cs.CV↗

arXiv2017

Decoupled, Energy Stable Scheme for Hydrodynamic Allen-Cahn Phase Field Moving Contact Line Model

In this paper, we present an efficient energy stable scheme to solve a phase field model incorporating contact line condition. Instead of the usually used Cahn-Hilliard type phase equation, we adopt the Allen-Cahn type phase field model with the static contact line boundary condition that coupled with incompressible Navier-Stokes equations with Navier boundary condition. The projection method is used to deal with the Navier-Stokes equa- tions and an auxiliary function is introduced for the non-convex Ginzburg-Landau bulk potential. We show that the scheme is linear, decoupled and energy stable. Moreover, we prove that fully discrete scheme is also energy stable. An efficient finite element spatial discretization method is implemented to verify the accuracy and efficiency of proposed schemes. Numerical results show that the proposed scheme is very efficient and accurate

math.NA↗

arXiv2017

Social learning in a simple task allocation game

We investigate the effects of social interactions in task al- location using Evolutionary Game Theory (EGT). We propose a simple task-allocation game and study how different learning mechanisms can give rise to specialised and non- specialised colonies under different ecological conditions. By combining agent-based simulations and adaptive dynamics we show that social learning can result in colonies of generalists or specialists, depending on ecological parameters. Agent-based simulations further show that learning dynamics play a crucial role in task allocation. In particular, introspective individual learning readily favours the emergence of specialists, while a process resembling task recruitment favours the emergence of generalists.

q-bio.PE↗

arXiv2017

A Scalable Algorithm for Structure Identification of Complex Gene Regulatory Network from Temporal Expression Data

Motivation: Gene regulatory interactions are of fundamental importance to various biological functions and processes. However, only a few previous computational studies have claimed success in revealing genome-wide regulatory landscapes from temporal gene expression data, especially for complex eukaryotes like human. Moreover, recent work suggests that these methods still suffer from the curse of dimensionality if network size increases to 100 or higher. Result: We present a novel scalable algorithm for identifying genome-wide regulatory network structures. The highlight of our method is that its superior performance does not degenerate even for a network size on the order of $10^4$, and is thus readily applicable to large-scale complex networks. Such a breakthrough is achieved by considering both prior biological knowledge and multiple topological properties (i.e., sparsity and hub gene structure) of complex networks in the regularized formulation. We also illustrate the application of our algorithm in practice using the time-course expression data from an influenza infection study in respiratory epithelial cells. Availability and Implementation: The algorithm described in this article is implemented in MATLAB$^\circledR$. The source code is freely available from https://github.com/Hongyu-Miao/DMI.git. Contact: jliu@cs.rochester.edu; hongyu.miao@uth.tmc.edu Supplementary information: Supplementary data are available online.

q-bio.MN↗

arXiv2016

Correlation Preserving Sparse Coding Over Multi-level Dictionaries for Image Denoising

In this letter, we propose a novel image denoising method based on correlation preserving sparse coding. Because the instable and unreliable correlations among basis set can limit the performance of the dictionary-driven denoising methods, two effective regularized strategies are employed in the coding process. Specifically, a graph-based regularizer is built for preserving the global similarity correlations, which can adaptively capture both the geometrical structures and discriminative features of textured patches. In particular, edge weights in the graph are obtained by seeking a nonnegative low-rank construction. Besides, a robust locality-constrained coding can automatically preserve not only spatial neighborhood information but also internal consistency present in noisy patches while learning overcomplete dictionary. Experimental results demonstrate that our proposed method achieves state-of-the-art denoising performance in terms of both PSNR and subjective visual quality.

cs.CV↗

arXiv2016

Blind restoration for non-uniform aerial images using non-local Retinex model and shearlet-based higher-order regularization

Aerial images are often degraded by space-varying motion blur and simultaneous uneven illumination. To recover high-quality aerial image from its non-uniform version, we propose a novel patch-wise restoration approach based on a key observation that the degree of blurring is inevitably affected by the illuminated conditions. A non-local Retinex model is developed to accurately estimate the reflectance component from the degraded aerial image. Thereafter the uneven illumination is corrected well. And then non-uniform coupled blurring in the enhanced reflectance image is alleviated and transformed towards uniform distribution, which will facilitate the subsequent deblurring. For constructing the multi-scale sparsified regularizer, the discrete shearlet transform is improved to better represent anisotropic image features in term of directional sensitivity and selectivity. In addition, a new adaptive variant of total generalized variation is proposed for the structure-preserving regularizer. These complementary regularizers are elegantly integrated into an objective function. The final deblurred image with uniform illumination can be extracted by applying the fast alternating direction scheme to solve the derived function. The experimental results demonstrate that our algorithm can not only remove both the space-varying illumination and motion blur in the aerial image effectively but also recover the abundant details of aerial scenes with top-level objective and subjective quality, and outperforms other state-of-the-art restoration methods.

cs.CV↗

arXiv2016

Magnetic moments of the hidden-charm pentaquark states

The magnetic moment of a baryon state is an equally important dynamical observable as its mass, which encodes crucial information of its underlying structure. According to the different color-flavor structure, we have calculated the magnetic moments of the hidden-charm pentaquark states with $J^P={\frac{1}{2}}^{\pm}$, ${\frac{3}{2}}^{\pm}$, ${\frac{5}{2}}^{\pm}$ and ${\frac{7}{2}}^{+}$ in the molecular model, the diquark-triquark model and the diquark-diquark-antiquark model respectively. Although a good description for the pentaquark mass spectrum and decay patterns has been obtained in all the three models, different color-flavor structures lead to different magnetic moments, which can be used to pin down their inner structures and distinguish various models.

hep-ph↗

arXiv2016

Is the newly reported $X(5568)$ a $B\bar{K}$ molecular state?

In this work, we perform a dynamical study of the $B^{(*)}$ and $\bar K$ interaction and show that the newly reported $X(5568)$ or $X(5616)$ cannot be assigned to be an isovector $B\bar{K}$ or $B^*\bar{K}$ molecular state. We continue to investigate the isoscalar $B^{(*)}\bar{K}$ systems, and the $B^{(*)}\bar{K}$ systems with isospin $I=0,1$, and predict the existence of several isoscalar $B^{(*)}\bar K^{(*)}$ molecular states. A new task of exploring open-bottom molecular states will be created for future experiments.

hep-ph↗

arXiv2016

Predictions of the hidden-charm molecular states with four-quark component

In this work, we study the $T\bar{T}$-type molecular systems systematically via one pion exchange model, where $T$ denotes the narrow $J^P=1^+$ $D_1$ meson or $2^+$ $D_2^*$ meson and $\bar{T}$ is its antiparticle. With the effective potentials, we try to find the bound state solutions of the corresponding systems, which provide crucial information of whether there exist the $T\bar{T}$-type molecular states. According to our analysis, we predict some $T\bar{T}$-type molecular states which may be accessible at future experiments like LHCb and forthcoming BelleII.

hep-ph↗

arXiv2016

Hidden-charm molecular pentaquarks and their charm-strange partners

In the framework of one-pion-exchange (OPE) model, we study the hidden-charm and charm-strange molecular pentaquark systems composed of a heavy baryon $(Σ_c, Σ_c^*)$ and a vector meson $(\bar{K}^*, \bar{D}^*)$, where the S-D mixing effect is considered in our calculation. Our result shows that the $Σ_c\bar{D}^*$ molecular state with $(I=1/2,J^P=3/2^-)$ and the $Σ_c^*\bar{D}^*$ molecular state with $(I=1/2,J^P=5/2^-)$ exist in the mass range of the observed $P_c(4380)$ and $P_c(4450)$, respectively. Moreover, we predict two other hidden-charm molecular pentaquarks with configurations $Σ_c\bar{D}^*$ $(I=3/2, J^P=1/2^-)$ and $Σ_c^*\bar{D}^*$ $(I=3/2, J^P=1/2^-)$ and two charm-strange molecular pentaquarks $P_{cs}(3340)$ and $P_{cs}(3400)$ corresponding to the $Σ_c\bar{K}^*$ configuration with $(I=1/2, J^P=3/2^-)$ and the $Σ_c^*\bar{K}^*$ configuration with $(I=1/2, J^P=5/2^-)$, respectively. Additionally, we also predict some hidden-bottom $Σ_b^{(*)}B^*$ and $B_c$-like $Σ_c^{(*)}B^*/Σ_b^{(*)}\bar{D}^*$ pentaquarks.

hep-ph↗

arXiv2016

A systematic search for the spectra with features of crystalline silicates in the Spitzer IRS Enhanced Products

The crystalline silicates features are mainly reflected in infrared bands. The Spitzer Infrared Spectrograph (IRS) collected numerous spectra of various objects and provided a big database to investigate crystalline silicates in a wide range of astronomical environments. We apply the manifold ranking algorithm to perform a systematic search for the spectra with crystalline silicates features in the Spitzer IRS Enhanced Products available. In total, 868 spectra of 790 sources are found to show the features of crystalline silicate. These objects are cross-matched with the SIMBAD database as well as with the Large Sky Area Multi-Object Fibre Spectroscopic Telescope (LAMOST)/DR2. The average spectrum of young stellar objects show a variety of features dominated either by forsterite or enstatite or neither, while the average spectrum of evolved objects consistently present dominant features of forsterite in AGB, OH/IR, post-AGB and planetary nebulae. They are identified optically as early-type stars, evolved stars, galaxies and so on. In addition, the strength of spectral features in typical silicate complexes is calculated. The results are available through CDS for the astronomical community to further study crystalline silicate.

astro-ph.GA↗

arXiv2015

Correction to Solution of Dirac Equation

Using the China unitary principle to test the Dirac theoryfor the hydrogen atomic spectrum shows that the standard Dirac function withthe Dirac energy levels is only one the formal solutions of theDirac-Coulomb equation, which conceals some pivotal mathematicalcontradictions. The theorem of existence of solution of the Dirac equationrequires an important modification to the Dirac angular momentum constantthat was defined by Dirac's algebra. It derives the modified radial Diracequation which has the consistency solution involving the quantum neutronradius and the neutron binding energy. The inevitable solution for otheratomic energy states is only equivalent to the Bohr solution. It concludesthat the Dirac equation is more suitable to describe the structure ofneutron. How to treat the difference between the unitary energy levels andthe result of the experimental observation of the atomic spectrums for thehydrogen atom needs to be solved urgently.

physics.gen-ph↗