arXiv subjects

Qi Wang

Publications and source records attributed to Qi Wang.

At least 613 records · Page 34Linked to original sources

arXiv2020

Periodically modulated thermal convection

Many natural and industrial turbulent flows are subjected to time-dependent boundary conditions. Despite being ubiquitous, the influence of temporal modulations (with frequency $f$) on global transport properties has hardly been studied. Here, we perform numerical simulations of Rayleigh-Bénard (RB) convection with time periodic modulation in the temperature boundary condition and report how this modulation can lead to a significant heat flux (Nusselt number $\rm{Nu}$) enhancement. Using the concept of Stokes thermal boundary layer, we can explain the onset frequency of the Nu enhancement and the optimal frequency at which Nu is maximal, and how they depend on the Rayleigh number Ra and Prandtl number $\rm{Pr}$. From this, we construct a phase diagram in the 3D parameter space ($f$, $\rm{Ra}$, $\rm{Pr}$) and identify: (i) a regime where the modulation is too fast to affect $\rm{Nu}$; (ii) a moderate modulation regime, where $\rm{Nu}$ increases with decreasing $f$ and (iii) slow modulation regime, where $\rm{Nu}$ decreases with further decreasing $f$. Our findings provide a framework to study other types of turbulent flows with time-dependent forcing.

physics.flu-dyn↗

arXiv2020

New Construction of Optimal Type-II Binary Z-Complementary Pairs

A pair of sequences is called a Z-complementary pair (ZCP) if it has zero aperiodic autocorrelation sums at each of the non-zero time-shifts within {a} certain region, called the zero correlation zone (ZCZ). ZCPs are categorised into two types{:} Type-I ZCPs and Type-II ZCPs. Type-I ZCPs have {the} ZCZ around the in-phase position and Type-II ZCPs have the ZCZ around the end-shift position. {Till now only a few} constructions of Type-II ZCPs are reported {in the literature}, and all {have} lengths of the form $2^m\pm1$ or $N+1$ where $N=2^a 10^b 26^c$ and $a,~b,~c$ are non-negative integers. In this paper, we {propose} a recursive construction of ZCPs based on concatenation of sequences. Inspired by Turyn's construction of Golay complementary pairs, we also propose a construction of Type-II ZCPs from known ones. The proposed constructions can generate optimal Type-II ZCPs with new flexible parameters and Z-optimal Type-II ZCPs with any odd length. In addition, we give upper bounds for the PMEPR of the proposed ZCPs. It turns out that our constructions lead to ZCPs with low PMEPR.

cs.IT↗

arXiv2020

A note on an OACF-preserving operation based on Parker's Transformation

Binary sequences with low odd-periodic correlation magnitudes have found important applications in communication systems. It is well known that the nega-cyclic shift and negation preserve the odd-periodic autocorrelation function (OACF) values in general. In this paper, we define a new operation based on Parker's transformation, which also preserves the OACF values of binary sequences. This enables us to classify Parker's 16 cases into 8 ones, and may possibly further allow to classify all constructions based on Parker's transformation.

cs.IT↗

arXiv2020

Pre-Lie analogues of Poisson-Nijenhuis structures and Maurer-Cartan equations

In this paper, we study pre-Lie analogues of Poisson-Nijenhuis structures and introduce ON-structures on bimodules over pre-Lie algebras. We show that an ON-structure gives rise to a hierarchy of pairwise compatible O-operators. We study solutions of the strong Maurer-Cartan equation on the twilled pre-Lie algebra associated to an O-operator, which gives rise to a pair of ON-structures which are naturally in duality. We show that KVN-structures and HN-structures on a pre-Lie algebra g are corresponding to ON-structures on the bimodule $(\mathfrak g^*;\mathrm{ad}^*,-R^*)$, and $KVΩ$-structures are corresponding to solutions of the strong Maurer-Cartan equation on a twilled pre-Lie algebra associated to an $s$-matrix.

math.QA↗

arXiv2020

SDFN: Segmentation-based Deep Fusion Network for Thoracic Disease Classification in Chest X-ray Images

This study aims to automatically diagnose thoracic diseases depicted on the chest x-ray (CXR) images using deep convolutional neural networks. The existing methods generally used the entire CXR images for training purposes, but this strategy may suffer from two drawbacks. First, potential misalignment or the existence of irrelevant objects in the entire CXR images may cause unnecessary noise and thus limit the network performance. Second, the relatively low image resolution caused by the resizing operation, which is a common preprocessing procedure for training neural networks, may lead to the loss of image details, making it difficult to detect pathologies with small lesion regions. To address these issues, we present a novel method termed as segmentation-based deep fusion network (SDFN), which leverages the domain knowledge and the higherresolution information of local lung regions. Specifically, the local lung regions were identified and cropped by the Lung Region Generator (LRG). Two CNN-based classification models were then used as feature extractors to obtain the discriminative features of the entire CXR images and the cropped lung region images. Lastly, the obtained features were fused by the feature fusion module for disease classification. Evaluated by the NIH benchmark split on the Chest X-ray 14 Dataset, our experimental result demonstrated that the developed method achieved more accurate disease classification compared with the available approaches via the receiver operating characteristic (ROC) analyses. It was also found that the SDFN could localize the lesion regions more precisely as compared to the traditional method.

cs.CV↗

arXiv2020

Transparent Metamaterial Absorber with Broadband RCS Reduction for Solar Arrays

Solar arrays are the primary energy source of the satellite. In this paper, a metamaterial absorber for solar arrays with simultaneous high optical transparency and broadband microwave absorption is presented. By tailoring the reflection response of meta-atoms, 85% absorption performance from 6.8GHz to 18GHz is obtained. In the meantime, by employing transparent substrates, including indium tin oxide (ITO) film and anti-reflection glass, a maximum of 87% light transmittance is achieved. The absorptivity of the proposed metamaterial absorber is simulated and measured experimentally. Light transmittance and the effect of transparent metamaterial absorber on the conversion efficiency of the solar array have also been measured. These results fully demonstrate the reliability of our design for solar arrays, which also meet the requirements of structural strength, atomic oxygen erosion resistance, weight limitation, etc.

physics.app-ph↗

arXiv2020

CNN-based Density Estimation and Crowd Counting: A Survey

Accurately estimating the number of objects in a single image is a challenging yet meaningful task and has been applied in many applications such as urban planning and public safety. In the various object counting tasks, crowd counting is particularly prominent due to its specific significance to social security and development. Fortunately, the development of the techniques for crowd counting can be generalized to other related fields such as vehicle counting and environment survey, if without taking their characteristics into account. Therefore, many researchers are devoting to crowd counting, and many excellent works of literature and works have spurted out. In these works, they are must be helpful for the development of crowd counting. However, the question we should consider is why they are effective for this task. Limited by the cost of time and energy, we cannot analyze all the algorithms. In this paper, we have surveyed over 220 works to comprehensively and systematically study the crowd counting models, mainly CNN-based density map estimation methods. Finally, according to the evaluation metrics, we select the top three performers on their crowd counting datasets and analyze their merits and drawbacks. Through our analysis, we expect to make reasonable inference and prediction for the future development of crowd counting, and meanwhile, it can also provide feasible solutions for the problem of object counting in other fields. We provide the density maps and prediction results of some mainstream algorithm in the validation set of NWPU dataset for comparison and testing. Meanwhile, density map generation and evaluation tools are also provided. All the codes and evaluation results are made publicly available at https://github.com/gaoguangshuai/survey-for-crowd-counting.

cs.CV↗

arXiv2020

Where Does It Exist: Spatio-Temporal Video Grounding for Multi-Form Sentences

In this paper, we consider a novel task, Spatio-Temporal Video Grounding for Multi-Form Sentences (STVG). Given an untrimmed video and a declarative/interrogative sentence depicting an object, STVG aims to localize the spatio-temporal tube of the queried object. STVG has two challenging settings: (1) We need to localize spatio-temporal object tubes from untrimmed videos, where the object may only exist in a very small segment of the video; (2) We deal with multi-form sentences, including the declarative sentences with explicit objects and interrogative sentences with unknown objects. Existing methods cannot tackle the STVG task due to the ineffective tube pre-generation and the lack of object relationship modeling. Thus, we then propose a novel Spatio-Temporal Graph Reasoning Network (STGRN) for this task. First, we build a spatio-temporal region graph to capture the region relationships with temporal object dynamics, which involves the implicit and explicit spatial subgraphs in each frame and the temporal dynamic subgraph across frames. We then incorporate textual clues into the graph and develop the multi-step cross-modal graph reasoning. Next, we introduce a spatio-temporal localizer with a dynamic selection method to directly retrieve the spatio-temporal tubes without tube pre-generation. Moreover, we contribute a large-scale video grounding dataset VidSTG based on video relation dataset VidOR. The extensive experiments demonstrate the effectiveness of our method.

cs.CV↗

arXiv2020

Unveiling the secrets of the mid-infrared Moon

The Moon's optical characteristics in visible and long-wavelength infrared (LWIR) have long been observed with our eyes or with instruments. What the mid-infrared (MIR) Moon looks like is still a mystery. For the first time we present detailed appearance of the MIR Moon observed by a high-resolution geostationary satellite and reveal the essence behind its appearance. The appearance of the MIR Moon is opposite to its normal visible appearance. In addition the MIR Moon shows limb darkening. Both the absolute and the relative brightness distribution of the MIR lunar disk changes with the solar incidence angle. The signatures of the MIR Moon are controlled by both the reflection and emission of the lunar surface. We also show first-ever brightness temperature maps of the lunar disk without needing a mosaic, which better show the temperature variation across the lunar disk. They reveal that the relationship between brightness temperature and solar incidence angle i is cos1/bi, and the power parameter is smaller than the Lambertian temperature model of cos1/4i observed for lunar orbit-based measurements. The slower decrease of the brightness temperature when moving away from the sub-solar point than the Lambertian model is due to topographic effects. The brightness temperature is dominated by albedo and the solar incidence angle and influenced by the topography. Our results indicate that the Moon in the MIR exhibits many interesting phenomena which were previously unknown, and contains abundant information about lunar reflection and thermal emission for future study.

astro-ph.EP↗

arXiv2020

Overview of the CCKS 2019 Knowledge Graph Evaluation Track: Entity, Relation, Event and QA

Knowledge graph models world knowledge as concepts, entities, and the relationships between them, which has been widely used in many real-world tasks. CCKS 2019 held an evaluation track with 6 tasks and attracted more than 1,600 teams. In this paper, we give an overview of the knowledge graph evaluation tract at CCKS 2019. By reviewing the task definition, successful methods, useful resources, good strategies and research challenges associated with each task in CCKS 2019, this paper can provide a helpful reference for developing knowledge graph applications and conducting future knowledge graph researches.

cs.AI↗

arXiv2020

Intelligent Radome Design Using Multilayer Metamaterial Structures to Realize Energy Isolation and Asymmetric Propagation of Electromagnetic Wave

An intelligent radome utilizing composite metamaterial structures is presented and investigated in this article, which can realize energy isolation and asymmetric propagation of electromagnetic (EM) wave self-adaptively by controlling states of PIN diodes. The whole structure mainly consists of a broadband polarization-sensitive polarization converter (PC) and an active frequency selective rasorber (AFSR) switching between a transmission mode and absorption mode which is used as an energy-selective surface (ESS). Among them, the function of the PC is to make the EM waves transmit asymmetrically, and the purpose of AFSR is to make the high-power waves be reflected or absorbed, which depends on the polarization type of the wave. Thus, the radome can realize both asymmetric propagations of EM wave and electromagnetic shielding. The equivalent circuit models (ECM) and parametric studies are considered to explain the physical operating mechanism of PC and AFSR. The fabricated structure with 7*7 unit cells is experimentally demonstrated and the measured results agree with simulated results well. Considering the distinctive characteristic of self-actuation, the presented concept has the potential application in electromagnetic stealth and HPEMWs shielding to protect communication devices.

physics.app-ph↗

arXiv2020

Koszul-Vinberg structures and compatible structures on left-symmetric algebroids

In this paper, we introduce the notion of Koszul-Vinberg-Nijenhuis structures on a left-symmetric algebroid as analogues of Poisson-Nijenhuis structures on a Lie algebroid, and show that a Koszul-Vinberg-Nijenhuis structure gives rise to a hierarchy of Koszul-Vinberg structures. We introduce the notions of ${\rm KVΩ}$-structures, pseudo-Hessian-Nijenhuis structures and complementary symmetric $2$-tensors for Koszul-Vinberg structures on left-symmetric algebroids, which are analogues of ${\rm PΩ}$-structures, symplectic-Nijenhuis structures and complementary $2$-forms for Poisson structures. We also study the relationships between these various structures.

math.RA↗

arXiv2020

Spin-orbit quantum impurity in a topological kagome magnet

Quantum states induced by single-atomic-impurities are the current frontier of material and information science. Recently the spin-orbit coupled correlated kagome magnets are emerging as a new class of topological quantum materials, although the effect of single-atomic impurities remains unexplored. Here we use state-of-the-art scanning tunneling microscopy/spectroscopy (STM/S) to study the atomic indium impurity in a topological kagome magnet Co3Sn2S2, which is designed to support the spin-orbit quantum state. We find each impurity features a strongly localized bound state. Our systematic magnetization-polarized tunneling probe reveals its spin-down polarized nature with an unusual moment of -5uB, indicative of additional orbital magnetization. As the separation between two impurities progressively shrinks, their respective bound states interact and form quantized molecular orbital states. The molecular orbital of three neighboring impurities further exhibits an intriguing splitting owing to the combination of geometry, magnetism, and spin-orbit coupling, analogous to the splitting of the topological Weyl fermion line12,19. Our work demonstrates the quantum-level interplay between magnetism and spin-orbit coupling at an individual atomic impurity, which provides insights into the emergent impurity behavior in a topological kagome magnet and the potential of spin-orbit quantum impurities for information science.

cond-mat.mtrl-sci↗

arXiv2020

Focus on Semantic Consistency for Cross-domain Crowd Understanding

For pixel-level crowd understanding, it is time-consuming and laborious in data collection and annotation. Some domain adaptation algorithms try to liberate it by training models with synthetic data, and the results in some recent works have proved the feasibility. However, we found that a mass of estimation errors in the background areas impede the performance of the existing methods. In this paper, we propose a domain adaptation method to eliminate it. According to the semantic consistency, a similar distribution in deep layer's features of the synthetic and real-world crowd area, we first introduce a semantic extractor to effectively distinguish crowd and background in high-level semantic information. Besides, to further enhance the adapted model, we adopt adversarial learning to align features in the semantic space. Experiments on three representative real datasets show that the proposed domain adaptation scheme achieves the state-of-the-art for cross-domain counting problems.

cs.CV↗

arXiv2020

Propagation of spin-waves packets in individual nano-sized yttrium iron garnet magnonic conduits

Modern-days CMOS-based computation technology is reaching its fundamental limitations. The emerging field of magnonics, which utilizes spin waves for data transport and processing, proposes a promising path to overcome these limitations. Different devices have been demonstrated recently on the macro- and microscale, but the feasibility of the magnonics approach essentially relies on the scalability of the structure feature size down to an extent of a few 10 nm, which are typical sizes for the established CMOS technology. Here, we present a study of propagating spin-wave packets in individual yttrium iron garnet (YIG) conduits with lateral dimensions down to 50 nm. Space and time resolved micro-focused Brillouin-Light-Scattering (BLS) spectroscopy is used to characterize the YIG nanostructures and measure the spin-wave decay length and group velocity directly. The revealed magnon transport at the scale comparable to the scale of CMOS proves the general feasibility of a magnon-based data processing.

physics.app-ph↗

arXiv2020

Temperature dependence of spin pinning and spin-wave dispersion in nanoscopic ferromagnetic waveguides

The field of magnonics attracts significant attention due to the possibility of utilizing information coded into the spin-wave phase or amplitude to perform computation operations on the nanoscale. Recently, spin waves were investigated in Yttrium Iron Garnet (YIG) waveguides with widths ranging down to 50 nm and aspect ratios thickness over width approaching unity. A critical width was found, below which the exchange interaction suppresses the dipolar pinning phenomenon and the system becomes unpinned. Here we continue these investigations and analyse the pinning phenomenon and spin-wave dispersions as a function of temperature, thickness and material of choice. Higher order modes, the influence of a finite wavevector along the waveguide and the impact of the pinning phenomenon on the spin-wave lifetime are discussed as well as the influence of a trapezoidal cross section and edge roughness of the waveguides. The presented results are of particular interest for potential applications in magnonic devices and the incipient field of quantum magnonics at cryogenic temperatures.

physics.app-ph↗

arXiv2020

An energy-based discontinuous Galerkin method for semilinear wave equations

We generalize the energy-based discontinuous Galerkin method proposed in [SIAM J. Num. Anal., 53(6):2705-2726, 2015.] to second-order semilinear wave equations. A stability and convergence analysis is presented along with numerical experiments demonstrating optimal convergence for certain choices of the interelement fluxes. Applications to the sine-Gordon equation include simulations of breathers, kink, and anti-kink solitons.

math.NA↗

arXiv2020

Propagating magnetic droplet solitons as moveable nanoscale spin-wave sources with tunable direction of emission

Magnetic droplets are strongly nonlinear and localized spin-wave solitons that can be formed in current-driven nanocontacts. Here, we propose a simple way to launch droplets in an inhomogeneous nanoscopic waveguide. We use the drift motion of a droplet and show that in a system with broken translational symmetry, the droplet acquires a linear momentum and propagates. We find that the droplet velocity can be tuned via the strength of the break in symmetry and the size of the nanocontact. In addition, we demonstrate that the launched droplet can propagate up to several micrometers in a realistic system with reasonable damping. Finally, we demonstrate how an annihilating droplet delivers its momentum to a highly nonreciprocal spin-wave burst with a tunable wave vector with nanometer wavelengths. Such a propagating droplet can be used as a moveable spin-wave source in nanoscale magnonic networks. The presented method enables full control of the spin-wave emission direction, which can largely extend the freedom to design integrated magnonic circuits with a single spin-wave source.

cond-mat.mes-hall↗