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Xin Chen

Publications and source records attributed to Xin Chen.

At least 649 records · Page 36Linked to original sources
arXiv2017

ChineseFoodNet: A large-scale Image Dataset for Chinese Food Recognition

In this paper, we introduce a new and challenging large-scale food image dataset called "ChineseFoodNet", which aims to automatically recognizing pictured Chinese dishes. Most of the existing food image datasets collected food images either from recipe pictures or selfie. In our dataset, images of each food category of our dataset consists of not only web recipe and menu pictures but photos taken from real dishes, recipe and menu as well. ChineseFoodNet contains over 180,000 food photos of 208 categories, with each category covering a large variations in presentations of same Chinese food. We present our efforts to build this large-scale image dataset, including food category selection, data collection, and data clean and label, in particular how to use machine learning methods to reduce manual labeling work that is an expensive process. We share a detailed benchmark of several state-of-the-art deep convolutional neural networks (CNNs) on ChineseFoodNet. We further propose a novel two-step data fusion approach referred as "TastyNet", which combines prediction results from different CNNs with voting method. Our proposed approach achieves top-1 accuracies of 81.43% on the validation set and 81.55% on the test set, respectively. The latest dataset is public available for research and can be achieved at https://sites.google.com/view/chinesefoodnet.

cs.CV↗
arXiv2017

Data hiding in Fingerprint Minutiae Template for Privacy Protection

In this paper, we propose a novel scheme for data hiding in the fingerprint minutiae template, which is the most popular in fingerprint recognition systems. Various strategies are proposed in data embedding in order to maintain the accuracy of fingerprint recognition as well as the undetectability of data hiding. In bits replacement based data embedding, we replace the last few bits of each element of the original minutiae template with the data to be hidden. This strategy can be further improved using an optimized bits replacement based data embedding, which is able to minimize the impact of data hiding on the performance of fingerprint recognition. The third strategy is an order preserving mechanism which is proposed to reduce the detectability of data hiding. By using such a mechanism, it would be difficult for the attacker to differentiate the minutiae template with hidden data from the original minutiae templates. The experimental results show that the proposed data hiding scheme achieves sufficient capacity for hiding common personal data, where the accuracy of fingerprint recognition is acceptable after the data hiding.

cs.CR↗
arXiv2017

Robust Capacity Assessment of Distributed Generation in Unbalanced Distribution Networks Incorporating ANM Techniques

To settle a large-scale integration of renewable distributed generations (DGs), it requires to assess the maximal DG hosting capacity of active distribution networks (ADNs). For fully exploiting the ability of ADNs to accommodate DG, this paper proposes a robust comprehensive DG capacity assessment method considering three-phase power flow modelling and active network management (ANM) techniques. The two-stage adjustable robust optimization is employed to tackle the uncertainties of load demands and DG outputs. With our method, system planners can obtain the maximum penetration level of DGs with their optimal sizing and sitting decisions. Meanwhile, the robust optimal ANM schemes can be generated for each operation time period, including network reconfiguration, on-load-tap-changers regulation, and reactive power compensation. In addition, a three-step optimization algorithm is proposed to enhance the accuracy of DG capacity assessment results. The optimality and robustness of our method are validated via numerical tests on an unbalanced IEEE 33-bus distribution system.

eess.SY↗
arXiv2017

Detecting Small Signs from Large Images

In the past decade, Convolutional Neural Networks (CNNs) have been demonstrated successful for object detections. However, the size of network input is limited by the amount of memory available on GPUs. Moreover, performance degrades when detecting small objects. To alleviate the memory usage and improve the performance of detecting small traffic signs, we proposed an approach for detecting small traffic signs from large images under real world conditions. In particular, large images are broken into small patches as input to a Small-Object-Sensitive-CNN (SOS-CNN) modified from a Single Shot Multibox Detector (SSD) framework with a VGG-16 network as the base network to produce patch-level object detection results. Scale invariance is achieved by applying the SOS-CNN on an image pyramid. Then, image-level object detection is obtained by projecting all the patch-level detection results to the image at the original scale. Experimental results on a real-world conditioned traffic sign dataset have demonstrated the effectiveness of the proposed method in terms of detection accuracy and recall, especially for those with small sizes.

cs.CV↗
arXiv2017

Intrinsic Ultracontractivity of Non-local Dirichlet forms on Unbounded Open Sets

In this paper we consider a large class of symmetric Markov processes $X=(X_t)_{t\ge0}$ on $\R^d$ generated by non-local Dirichlet forms, which include jump processes with small jumps of $α$-stable-like type and with large jumps of super-exponential decay. Let $D\subset \R^d$ be an open (not necessarily bounded and connected) set, and $X^D=(X_t^D)_{t\ge0}$ be the killed process of $X$ on exiting $D$. We obtain explicit criterion for the compactness and the intrinsic ultracontractivity of the Dirichlet Markov semigroup $(P^{D}_t)_{t\ge0}$ of $X^D$. When $D$ is a horn-shaped region, we further obtain two-sided estimates of ground state in terms of jumping kernel of $X$ and the reference function of the horn-shaped region $D$.

math.PR↗
arXiv2017

Thermodynamics of supra-arcade downflows in solar flares

Context. Supra-arcade downflows (SADs) have been frequently observed during the gradual phase of solar flares near the limb. In coronal emission lines sensitive to flaring plasmas, they appear as tadpole-like dark voids against the diffuse fan-shaped "haze" above, flowing toward the well-defined flare arcade. Aims. We aim to investigate the evolution of SADs' thermal properties, and to shed light on the formation mechanism and physical processes of SADs. Methods. We carefully studied several selected SADs from two flare events and calculated their differential emission measures (DEMs) as well as DEM-weighted temperatures using data obtained by the Atmospheric Imaging Assembly (AIA) onboard the Solar Dynamic Observatory. Results. Our analysis shows that SADs are associated with a substantial decrease in DEM above 4 MK, which is 1-3 orders of magnitude smaller than the surrounding haze as well as the region before or after the passage of SADs, but comparable to the quiet corona. There is no evidence for the presence of the SAD-associated hot plasma (> 20 MK) in the AIA data, and this decrease in DEM does not cause any significant change in the DEM distribution as well as the DEM-weighted temperature, which supports this idea that SADs are density depletion. This depression in DEM rapidly recovers in the wake of the SADs studied, generally within a few minutes, suggesting that they are discrete features. In addition, we found that SADs in one event are spatio-temporally associated with the successive formation of post-flare loops along the flare arcade.

astro-ph.SR↗
arXiv2017

Competition between Chaotic and Non-Chaotic Phases in a Quadratically Coupled Sachdev-Ye-Kitaev Model

The Sachdev-Ye-Kitaev (SYK) model is a concrete solvable model to study non-Fermi liquid properties, holographic duality and maximally chaotic behavior. In this work, we consider a generalization of the SYK model that contains two SYK models with different number of Majorana modes coupled by quadratic terms. This model is also solvable, and the solution shows a zero-temperature quantum phase transition between two non-Fermi liquid chaotic phases. This phase transition is driven by tuning the ratio of two mode numbers, and a Fermi liquid non-chaotic phase sits at the critical point with equal mode number. At finite temperature, the Fermi liquid phase expands to a finite regime. More intriguingly, a different non-Fermi liquid phase emerges at finite temperature. We characterize the phase diagram in term of the spectral function, the Lyapunov exponent and the entropy. Our results illustrate a concrete example of quantum phase transition and critical regime between two non-Fermi liquid phases.

cond-mat.str-el↗
arXiv2017

Motion Saliency Based Automatic Delineation of Glottis Contour in High-speed Digital Images

In recent years, high-speed videoendoscopy (HSV) has significantly aided the diagnosis of voice pathologies and furthered the understanding the voice production in recent years. As the first step of these studies, automatic segmentation of glottal images till presents a major challenge for this technique. In this paper, we propose an improved Saliency Network that automatically delineates the contour of the glottis from HSV image sequences. Our proposed additional saliency measure, Motion Saliency (MS), improves upon the original Saliency Network by using the velocities of defined edges. In our results and analysis, we demonstrate the effectiveness of our approach and discuss its potential applications for computer-aided assessment of voice pathologies and understanding voice production.

cs.CV↗
arXiv2017

Prospects for Higgs CP property measurements at the LHC - Talk presented at the International Workshop on Future Linear Colliders (LCWS2016), Morioka, Japan, 5-9 December 2016. C16-12-05.4

This document is prepared for the LCWS2016 conference proceedings. It reviews the current results on the Higgs CP property measurements from both ATLAS and CMS experiments in the Higgs to diboson decays, and in the Vector Boson Fusion production of Higgs via the ditau decay channel. The projected sensitivity of the ditau signal in HL-LHC is briefly discussed. Finally, it gives the prospects for the CP measurement in the Higgs to ditau decay with the tau substructure developments at both collaborations.

hep-ex↗
arXiv2017

Resonant Energy Transfer Under the Influence of the Evanescent Field from the Metal

We present a quantum framework based on a density matrix of a dimer system to investigate the quantum dynamics of excitation energy transfer (EET) in the presence of the evanescent field from the metal and the phonon bath. Due to the spatial correlation of the electric field in the vicinity of the metal, the spectral density of the evanescent field is similar to that of a shared phonon bath. However, the EET dynamics under the influence of the evanescent field is an open and a new problem. Here we use a thin metallic film to investigate the effect of the evanescent field on the excitation energy transfer in a dimer system based on a density matrix approach. Our results indicate that a thin metallic film enhances the energy transfer rate at the expense of absorbing energy during the process. Since the spectral density of the evanescent field is affected by the geometry of the medium and the distance of a dimer system from the medium, our results demonstrate the possibility to tune EET based on material geometry and distances. Our model also serves as an expansion to quantum heat engine model and provides a framework to investigate the EET in light harvesting molecular networks under the influence of the evanescent field.

quant-ph↗
arXiv2016

Carbon-Rich Carbon Nitride Monolayers with Dirac Cones: Dumbbell C4N

Two-dimensional (2D) carbon nitride materials play an important role in energy-harvesting, energy-storage and environmental applications. Recently, a new carbon nitride, 2D polyaniline (C3N) was proposed [PNAS 113 (2016) 7414-7419]. Based on the structure model of this C3N monolayer, we propose two new carbon nitride monolayers, named dumbbell (DB) C4N-I and C4N-II. Using first-principles calculations, we systematically study the structure, stability, and band structure of these two materials. In contrast to other carbon nitride monolayers, the orbital hybridization of the C/N atoms in the DB C4N monolayers is sp3. Remarkably, the band structures of the two DB C4N monolayers have a Dirac cone at the K point and their Fermi velocities are comparable to that of graphene. This makes them promising materials for applications in high-speed electronic devices. Using a tight-binding model, we explain the origin of the Dirac cone.

cond-mat.mtrl-sci↗
arXiv2016

Measuring Topological Number of a Chern-Insulator from Quench Dynamics

In this letter we show how the topological number of a static Hamiltonian can be measured from a dynamical quench process. We focus on a two-band Chern insulator in two-dimension, for instance, the Haldane model, whose dynamical process can be described by a mapping from the $[k_x,k_y,t]$ space to the Bloch sphere, characterized by the Hopf invariant. Such a mapping has been constructed experimentally by measurements in cold atom systems. We show that, taking any two constant vectors on the Bloch sphere, their inverse images of this mapping are two trajectories in the $[k_x,k_y,t]$ space, and the linking number of these two trajectories exactly equals to the Chern number of the static Hamiltonian. Applying this result to a recent experiment from the Hamburg group, we show that the linking number of the trajectories of the phase vortices determines the phase boundary of the static Hamiltonian.

cond-mat.quant-gas↗
arXiv2016

Gallium Bismuth Halides GaBi-X2 (X= I, Br, Cl) Monolayers with Distorted Hexagonal Framework: Novel Room-Temperature Quantum Spin Hall Insulators

Quantum Spin Hall (QSH) insulators with a large topologically nontrivial bulk gap are crucial for future applications of the QSH effect. Among these, group III-V monolayers and their halides with chair structure (regular hexagonal framework, RHF) were widely studied. Using first-principles calculations, we propose a new structure model for the functionalized group III-V monolayers, which consist of rectangular GaBi-X2 (X=I, Br, Cl) monolayers with a distorted hexagonal framework (DHF). These structures have a much lower energy than the GaBi-X2 monolayers with chair structure. Remarkably, the DHF GaBi-X2 monolayers are all QSH insulators, which exhibit sizeable nontrivial band gaps ranging from 0.17 eV to 0.39 eV. Those band gaps can be widely tuned by applying different spin-orbit coupling (SOC) strengths, resulting in a distorted Dirac cone.

cond-mat.mtrl-sci↗
arXiv2016

Search for Flavor Changing Neutral Currents in $t\to H c, H\to ττ$ Decay at the LHC

The prospects of searching for the flavor changing neutral current effect in the decay of $t\to H c, H\to ττ$ are investigated with the simulated $p-p$ collision data for the ATLAS detector at the LHC, where the Higgs mass is assumed to be 125~GeV. A fit based on the constraints from the Higgs mass and the tau decay kinematics is performed for each event, which improves significantly the Higgs and top mass reconstruction and helps the signal-background separation. Boosted Decision Trees discriminants are developed to achieve an optimal sensitivity of searching for the FCNC signal. An expected upper limit of the branching ratio $\mathcal{B}(t\to H c)$ at $95\%$ confidence level of 0.25\% is obtained with a data set of 100~fb$^{-1}$ at $\sqrt{s}=13$ TeV during the LHC Run-2 period.

hep-ph↗
arXiv2016

Enhancement of Resonant Energy Transfer Due to Evanescent-wave from the Metal

The high density of evanescent modes in the vicinity of a metal leads to enhancement of the near-field Förster resonant energy transfer (FRET) rate. We present a classical approach to calculate the FRET rate based on the dyadic Green's function of an arbitrary dielectric environment, and consider non-local limit of material permittivity in case of metallic halfspace and thin film. In a dimer system, we find that the FRET rate is enhanced due to shared evanescent photon modes bridging a donor and an acceptor. Furthermore, a general expression for the FRET rate for multimer systems is derived. The presence of a dielectric environment and the path interference effect enhance the transfer rate, depending on the combination of distance and geometry.

cond-mat.mes-hall↗
arXiv2015

Intrinsic Ultracontractivity for General Lévy processes on Bounded Open Sets

We prove that a general (not necessarily symmetric) Lévy process killed on exiting a bounded open set (without regular condition on the boundary) is intrinsically ultracontractive, provided that $B(0,R_0)\subseteq \rm{supp}(ν)$ for some constant $R_0>0$, where $\rm{supp}(ν)$ denotes the support of the associated Lévy measure $ν$. For a symmetric Lévy process killed on exiting a bounded Hölder domain of order $0$, we also obtain the intrinsic ultracontractivity under much weaker assumption on the associated Lévy measure.

math.PR↗
arXiv2015

Dumbbell Stanane: A large-gap quantum spin Hall insulator

Quantum spin Hall (QSH) effect is quite promising for applications in spintronics and quantum computations, but presently can only be achieved at ultralow temperature. Searching for large-gap QSH insulators is the key to increase the operating temperature. Using first-principles calculations, we demonstrate that the stable hydrogenated stanene with a dumbbell-like structure (DB stanane) has large topological nontrivial band gaps of 312 meV (gamma point) and 160 meV for bulk characterized by a topological invariant of Z2=1, due to the s-pxy band inversion. Helical gapless edge states appear in the nanoribbon structures with high Fermi velocity comparable to that of graphene. The nontrivial topological states are robust against the substrate effects. The realization of this material is a feasible solution for applications of QSH effect at room temperature and beneficial to the fabrication of high-speed spintronics devices.

cond-mat.mtrl-sci↗