Search arXiv⌕ Search

arXiv subjects

Chao Wang

Publications and source records attributed to Chao Wang.

At least 757 records · Page 42Linked to original sources
arXiv2015

Shield Synthesis: Runtime Enforcement for Reactive Systems

Scalability issues may prevent users from verifying critical properties of a complex hardware design. In this situation, we propose to synthesize a "safety shield" that is attached to the design to enforce the properties at run time. Shield synthesis can succeed where model checking and reactive synthesis fail, because it only considers a small set of critical properties, as opposed to the complex design, or the complete specification in the case of reactive synthesis. The shield continuously monitors the input/output of the design and corrects its erroneous output only if necessary, and as little as possible, so other non-critical properties are likely to be retained. Although runtime enforcement has been studied in other domains such as action systems, reactive systems pose unique challenges where the shield must act without delay. We thus present the first shield synthesis solution for reactive hardware systems and report our experimental results. This is an extended version of [5], featuring an additional appendix.

cs.LO↗
arXiv2014

A Pilot Study on Coupling CT and MRI through Use of Semiconductor Nanoparticles

CT and MRI are the two most widely used imaging modalities in healthcare, each with its own merits and drawbacks. Combining these techniques in one machine could provide unprecedented resolution and sensitivity in a single scan, and serve as an ideal platform to explore physical coupling of x-ray excitation and magnetic resonance. Molecular probes such as functionalized nanophosphors present an opportunity to demonstrate a synergy between these modalities. However, a simultaneous CT-MRI scanner does not exist at this moment. As a pilot study, here we propose a mechanism in which water solutions containing LiGa5O8:Cr3+ nanophosphors can be excited with x-rays to store energy, and these excited particles may subsequently influence the T2 relaxation times of the solutions so that a difference in T2 can be measured by MRI before and after x-ray excitation. The trends seen in our study suggest that a measurable effect may exist from x-ray excitation of the nanophosphors. However, there are several experimental conditions that hinder the clarity of the results to be statistically significant up to a commonly accepted level (p=0.05), including insoluble nanoparticles and inter-scan variability. Nevertheless, the initial results from our experiments seem a consistent and inspiring story that x-rays modify MRI T2 values around nanophosphors. Upon availability of soluble nanophosphors, we will repeat our experiments to confirm these observations.

physics.med-ph↗
arXiv2014

Characterizing an Entangled-Photon Source with Classical Detectors and Measurements

Quantum state tomography (QST) is a universal tool for the design and optimization of entangled-photon sources. It typically requires single-photon detectors and coincidence measurements. Recently, it was suggested that the information provided by the QST of photon pairs generated by spontaneous parametric down-conversion could be obtained by exploiting the stimulated version of this process, namely difference frequency generation. In this protocol, so-called "stimulated-emission tomography" (SET), a seed field is injected along with the pump pulse, and the resulting stimulated emission is measured. Since the intensity of the stimulated field can be several orders of magnitude larger than the intensity of the corresponding spontaneous emission, measurements can be made with simple classical detectors. Here, we experimentally demonstrate SET and compare it with QST. We show that one can accurately reconstruct the polarization density matrix, and predict the purity and concurrence of the polarization state of photon pairs without performing any single-photon measurements.

quant-ph↗
arXiv2014

Encoding High Dimensional Local Features by Sparse Coding Based Fisher Vectors

Deriving from the gradient vector of a generative model of local features, Fisher vector coding (FVC) has been identified as an effective coding method for image classification. Most, if not all, % FVC implementations employ the Gaussian mixture model (GMM) to characterize the generation process of local features. This choice has shown to be sufficient for traditional low dimensional local features, e.g., SIFT; and typically, good performance can be achieved with only a few hundred Gaussian distributions. However, the same number of Gaussians is insufficient to model the feature space spanned by higher dimensional local features, which have become popular recently. In order to improve the modeling capacity for high dimensional features, it turns out to be inefficient and computationally impractical to simply increase the number of Gaussians. In this paper, we propose a model in which each local feature is drawn from a Gaussian distribution whose mean vector is sampled from a subspace. With certain approximation, this model can be converted to a sparse coding procedure and the learning/inference problems can be readily solved by standard sparse coding methods. By calculating the gradient vector of the proposed model, we derive a new fisher vector encoding strategy, termed Sparse Coding based Fisher Vector Coding (SCFVC). Moreover, we adopt the recently developed Deep Convolutional Neural Network (CNN) descriptor as a high dimensional local feature and implement image classification with the proposed SCFVC. Our experimental evaluations demonstrate that our method not only significantly outperforms the traditional GMM based Fisher vector encoding but also achieves the state-of-the-art performance in generic object recognition, indoor scene, and fine-grained image classification problems.

cs.CV↗
arXiv2014

Direct CP violation in $τ^\pm\rightarrow K^\pm ρ^0 (ω)ν_τ\rightarrow K^\pm π^+π^-ν_τ$

We study the direct CP violation in the $τ^\pm\rightarrow K^\pm ρ^0 (ω)ν_τ\rightarrow K^\pm π^+π^-ν_τ$ decay process in the Standard Model. An interesting mechanism involving the charge symmetry violating mixing between $ρ^0$ and $ω$ is applied to enlarge the CP asymmetry. With this mechanism, the maximum differential and localized integrated CP asymmetries can reach $-(5.6^{+2.9}_{-1.7})\times10^{-12}$ and $6.3^{+2.4}_{-3.3}\times 10^{-11}$, respectively, which still leave plenty room for CP-violating New Physics to be discovered through this process.

hep-ph↗
arXiv2014

iGPSe: A Visual Analytic System for Integrative Genomic Based Cancer Patient Stratification

Background: Cancers are highly heterogeneous with different subtypes. These subtypes often possess different genetic variants, present different pathological phenotypes, and most importantly, show various clinical outcomes such as varied prognosis and response to treatment and likelihood for recurrence and metastasis. Recently, integrative genomics (or panomics) approaches are often adopted with the goal of combining multiple types of omics data to identify integrative biomarkers for stratification of patients into groups with different clinical outcomes. Results: In this paper we present a visual analytic system called Interactive Genomics Patient Stratification explorer (iGPSe) which significantly reduces the computing burden for biomedical researchers in the process of exploring complicated integrative genomics data. Our system integrates unsupervised clustering with graph and parallel sets visualization and allows direct comparison of clinical outcomes via survival analysis. Using a breast cancer dataset obtained from the The Cancer Genome Atlas (TCGA) project, we are able to quickly explore different combinations of gene expression (mRNA) and microRNA features and identify potential combined markers for survival prediction. Conclusions: Visualization plays an important role in the process of stratifying given population patients. Visual tools allowed for the selection of possibly features across various datasets for the given patient population. We essentially made a case for visualization for a very important problem in translational informatics.

cs.GR↗
arXiv2014

Replica exchange molecular dynamics optimization of tensor network states for quantum many-body systems

The tensor network states (TNS) methods combined with Monte Carlo (MC) techniques have been proved a powerful algorithm for simulating quantum many-body systems. However, because the ground state energy is a highly non-linear function of the tensors, it is easy to get stuck in local minima when optimizing the TNS of the simulated physical systems. To overcome this difficulty, we introduce a replica-exchange molecular dynamics optimization algorithm to obtain the TNS ground state, based on the MC sampling techniques, by mapping the energy function of the TNS to that of a classical dynamical system. The method is expected to effectively avoid local minima. We make benchmark tests on a 1D Hubbard model based on matrix product states (MPS) and a Heisenberg $J_1$-$J_2$ model on square lattice based on string bond states (SBS). The results show that the optimization method is robust and efficient compared to the existing results.

cond-mat.str-el↗
arXiv2014

Collision free autonomous navigation and formation building for non-holonomic ground robots

The primary objective of a safe navigation algorithm is to guide the object from its current position to the target position while avoiding any collision with the en-route obstacles, and the appropriate obstacle avoidance strategies are the key factors to ensure safe navigation tasks in dynamic environments. In this report, three different obstacle avoidance strategies for safe navigation in dynamic environments have been presented. The biologically-inspired navigation algorithm (BINA) is efficient in terms of avoidance time. The equidistant based navigation algorithm (ENA) is able to achieve navigation task with in uncertain dynamic environments. The navigation algorithm algorithm based on an integrated environment representation (NAIER) allows the object to seek a safe path through obstacles in unknown dynamic environment in a human-like fashion. The performances and features of the proposed navigation algorithms are confirmed by extensive simulation results and experiments with a real non-holonomic mobile robot. The algorithms have been implemented on two real control systems: intelligent wheelchair and robotic hospital bed. The performance of the proposed algorithms with SAM and Flexbed demonstrate their capabilities to achieve navigation tasks in complicated real time scenarios. The proposed algorithms are easy to be implemented in real time and costly efficient. An extra study on networked multi-robots formation building algorithm is presented in this paper. A constructive and easy-to-implement decentralised control is proposed for a formation building of a group of random positioned objects. Furthermore, the problem of formation building with anonymous objects is addressed. This randomised decentralised navigation algorithm achieves the convergence to a desired configuration with probability 1.

cs.RO↗
arXiv2014

Optimizing weights of protein energy function to improve ab initio protein structure prediction

Predicting protein 3D structure from amino acid sequence remains as a challenge in the field of computational biology. If protein structure homologues are not found, one has to construct 3D structural conformations from the very beginning by the so-called ab initio approach, using some empirical energy functions. A successful algorithm in this category, Rosetta, creates an ensemble of decoy conformations by assembling selected best short fragments of known protein structures and then recognizes the native state as the highly populated one with a very low energy. Typically, an energy function is a combination of a variety of terms characterizing different structural features, say hydrophobic interactions, van der Waals force, hydrogen bonding, etc. It is critical for an energy function to be capable to distinguish native-like conformations from non-native ones and to drive most initial conformations assembled from fragments to a native-like one in a conformation search process. In this paper we propose a linear programming algorithm to optimize weighting of a total of 14 energy terms used in Rosetta. We reverse the Monte Carlo process of Rosetta to approach native-like conformations to a process generating from the native state an ensemble of initial conformations most relevant to the native state. Intuitively, an ideal weighting scheme would result in a large "basin of attraction" of the native structure, which leads to an objective function for the linear programming. We have examined the proposal on several benchmark proteins, and the experimental results suggest that the optimized weights enlarge the attraction basin of the native state and improve the quality of the predicted native states as well. In addition, a comparison of optimal weighting schema for proteins of different classes indicates that in different protein classes energy terms may have different effects.

physics.bio-ph↗
arXiv2013

Exchange Bias Effect in Au-Fe3O4 Nanocomposites

We report exchange bias (EB) effect in the Au-Fe3O4 composite nanoparticle system, where one or more Fe3O4 nanoparticles are attached to an Au seed particle forming dimer and cluster morphologies, with the clusters showing much stronger EB in comparison with the dimers. The EB effect develops due to the presence of stress in the Au-Fe3O4 interface which leads to the generation of highly disordered, anisotropic surface spins in the Fe3O4 particle. The EB effect is lost with the removal of the interfacial stress. Our atomistic Monte-Carlo studies are in excellent agreement with the experimental results. These results show a new path towards tuning EB in nanostructures, namely controllably creating interfacial stress, and open up the possibility of tuning the anisotropic properties of biocompatible nanoparticles via a controllable exchange coupling mechanism.

cond-mat.mtrl-sci↗
arXiv2013

Micro-modulated luminescence tomography

Imaging depth of optical microscopy has been fundamentally limited to millimeter or sub-millimeter due to light scattering. X-ray microscopy can resolve spatial details of few microns deeply inside a sample but the contrast resolution is still inadequate to depict heterogeneous features at cellular or sub-cellular levels. To enhance and enrich biological contrast at large imaging depth, various nanoparticles are introduced and become essential to basic research and molecular medicine. Nanoparticles can be functionalized as imaging probes, similar to fluorescent and bioluminescent proteins. LiGa5O8:Cr3+ nanoparticles were recently synthesized to facilitate luminescence energy storage with x-ray pre-excitation and the subsequently stimulated luminescence emission by visible/near-infrared (NIR) light. In this paper, we suggest a micro-modulated luminescence tomography (MLT) approach to quantify a nanophosphor distribution in a thick biological sample with high resolution. Our numerical simulation studies demonstrate the feasibility of the proposed approach.

physics.bio-ph↗
arXiv2013

Uniqueness for the 2-D Euler equations on domains with corners

For a large class of non smooth bounded domains, existence of a global weak solution of the 2D Euler equations, with bounded vorticity, was established by Gérard-Varet and Lacave. In the case of sharp domains, the question of uniqueness for such weak solutions is more involved due to the bad behavior of $Δ^{-1}$ close to the boundary. In the present work, we show uniqueness for any bounded and simply connected domain with a finite number of corners of angles smaller than $π/2$. Our strategy relies on a log-Lipschitz type regularity for the velocity field.

math.AP↗
arXiv2013

Stored Luminescence Computed Tomography

The phosphor nanoparticles made of doped semiconductors, pre-excited by well-collimated X-ray radiation, were recently reported for their light emission upon NIR light stimulation. The characteristics of X-ray energy storage and NIR stimulated emission is highly desirable to design targeting probes and improve molecular and cellular imaging. Here we propose stored luminescence computed tomography (SLCT), perform realistic numerical simulation, and demonstrate a much-improved spatial resolution in a preclinical research context. The future opportunities are also discussed along this direction.

physics.bio-ph↗
arXiv2013

Self-excited Threshold Poisson Autoregression

This paper studies theory and inference of an observation-driven model for time series of counts. It is assumed that the observations follow a Poisson distribution conditioned on an accompanying intensity process, which is equipped with a two-regime structure according to the magnitude of the lagged observations. The model remedies one of the drawbacks of the Poisson autoregression model by allowing possibly negative correlation in the observations. Classical Markov chain theory and Lyapunov's method are utilized to derive the conditions under which the process has a unique invariant probability measure and to show a strong law of large numbers of the intensity process. Moreover the asymptotic theory of the maximum likelihood estimates of the parameters is established. A simulation study and a real data application are considered, where the model is applied to the number of major earthquakes in the world.

stat.ME↗
arXiv2013

Proofs of the Technical Results Justifying an Algorithm for Collision Avoidance in Dynamic Environments with Moving and Deforming Obstacles

This text presents the proofs of the technical facts underlying theoretical justification of the convergence and performance of the novel algorithm for reactive navigation of differential drive wheeled robots in dynamic uncertain environments. The algorithm restricts neither the natures nor the motions of the obstacles, they need not be rigid but conversely may deform. It does not consume data about the velocities, shapes, sizes, or orientations of the obstacles, and does not need a map of the environment or recognition of individual obstacles. The only information about the scene is the current distance to the nearest obstacle.

math.OC↗
arXiv2013

Break-down criterion for the water-wave equation

We study the break-down mechanism of smooth solution for the gravity water-wave equation of infinite depth. It is proved that if the mean curvature $κ$ of the free surface $Σ_t$, the trace $(V,B)$ of the velocity at the free surface, and the outer normal derivative $\frac {\pa P} {\pa \textbf{n}}$ of the pressure $P$ satisfy \beno &&\displaystyle\sup_{t\in [0,T]}\|κ(t)\|_{L^p\cap L^2}+\int_0^T\|(\na V, \na B)(t)\|_{L^\infty}^6dt<+\infty, &\displaystyle\inf_{(t,x,y)\in [0,T]\times Σ_t}-\frac {\pa P} {\pa \textbf{n}}(t,x,y)\ge c_0, \eeno for some $p>2d$ and $c_0>0$, then the solution can be extended after $t=T$.

math.AP↗
arXiv2013

The influence of boundary conditions on the contact problem in a 3D Navier-Stokes Flow

We consider the free fall of a sphere above a wall in a viscous incompressible fluid. We investigate the influence of boundary conditions on the finite-time occurrence of contact between the sphere and the wall. We prove that slip boundary conditions enable to circumvent the "no-collision" paradox associated with no-slip boundary conditions. We also examine the case of mixed boundary conditions.

math.AP↗