March 2020 arXiv papers — page 70

Charles Dawson, Andreas Hofmann, Brian Williams

To operate reactively in uncertain environments, robots need to be able to quickly estimate the risk that they will collide with their environment. This ability is important for both planning (to ensure that plans maintain acceptable levels of safety) and execution (to provide real-time warnings when risk exceeds some threshold). Existing methods for estimat

Bo Zhang, Pei-Hsun Tsai, An-Bang Wang, Stéphane Popinet

The short-term transient falling dynamics of a dripping water drop in quiescent air has been investigated through both simulation and experiment. The focus is on the short term behavior and the time range considered covers about eight dominant second-mode oscillations of the drop after it is formed. Due to the small fluid inertia the growth of the drop is qu

Pourya Shamsolmoali, Masoumeh Zareapoor, Ruili Wang, Huiyu Zhou

Sea-land segmentation is an important process for many key applications in remote sensing. Proper operative sea-land segmentation for remote sensing images remains a challenging issue due to complex and diverse transition between sea and lands. Although several Convolutional Neural Networks (CNNs) have been developed for sea-land segmentation, the performanc

Davide Lombardo, Elisa Lorenzo García, Christophe Ritzenthaler, Jeroen Sijsling

Let $ϕ:\,X\rightarrow Y$ be a (possibly ramified) cover between two algebraic curves of positive genus. We develop tools that may identify the Prym variety of $ϕ$, up to isogeny, as the Jacobian of a quotient curve $C$ in the Galois closure of the composition of $ϕ$ with a well-chosen map $Y\rightarrow \mathbb{P}^1$. This method allows us to recover all prev

Grzegorz Pastuszak, Adam Skowyrski, Andrzej Jamiołkowski

Assume that $Φ:\mathbb{M}_{n}(\mathbb{C})\rightarrow\mathbb{M}_{n}(\mathbb{C})$ is a superoperator which preserves hermiticity. We give an algorithm determining whether $Φ$ preserves semipositivity (we call $Φ$ positive in this case). Our approach to the problem has a model-theoretic nature, namely, we apply techniques of quantifier elimination theory for re

Laura Katharina Scarbath-Evers, René Hammer, Dorothea Golze, Martin Brehm

We investigate domain formation and local morphology of thin films of $α$-sexithiophene ($α$-6T) on Au(100) beyond monolayer coverage by combining high resolution scanning tunneling microscopy (STM) experiments with electronic structure theory calculations and computational structure search. We report a layerwise growth of highly-ordered enantiopure domains.

Marino Coppolaro, Giuseppe Castaldi, Vincenzo Galdi

It is common understanding that multilayered dielectric metamaterials, in the regime of deeply subwavelength layers, are accurately described by simple effective-medium models based on mixing formulas that do not depend on the spatial arrangement. In the wake of recent studies that have shown counterintuitive examples of periodic and aperiodic (orderly or ra

Lingyi Dong, Haocheng Zhang, Dimitrios Giannios

Relativistic jets are highly collimated plasma outflows emerging from accreting black holes. They are launched with a significant amount of magnetic energy, which can be dissipated to accelerate nonthermal particles and give rise to electromagnetic radiation at larger scales. Kink instabilities can be an efficient mechanism to trigger dissipation of jet magn

S. Mora

Stationary whirling of slender and homogeneous (continuous) elastic shafts rotating around their axis, with pin-pin boundary condition at the ends, is revisited by considering the complete deformations in the cross section of the shaft. The stability against a synchronous sinusoidal disturbance of any wave length is investigated and the analytic expression o

Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat

The availability of large-scale datasets has helped unleash the true potential of deep convolutional neural networks (CNNs). However, for the single-image denoising problem, capturing a real dataset is an unacceptably expensive and cumbersome procedure. Consequently, image denoising algorithms are mostly developed and evaluated on synthetic data that is usua

Tian-Yun Chang, Yueyang Chen, De-In Luo, Jia-Xin Li

Light-emitting diodes (LEDs) based on III-V/II-VI materials have delivered a compelling performance in the mid-infrared (mid-IR) region, which enabled wide-ranging applications, including environmental monitoring, defense and medical diagnostics. Continued efforts are underway to realize on-chip sensors via heterogeneous integration of mid-IR emitters on a s

Marc Stieffenhofer, Michael Wand, Tristan Bereau

A tight and consistent link between resolutions is crucial to further expand the impact of multiscale modeling for complex materials. We herein tackle the generation of condensed molecular structures as a refinement -- backmapping -- of a coarse-grained structure. Traditional schemes start from a rough coarse-to-fine mapping and perform further energy minimi

Zhifeng Zhu, Kaiming Cai, Jiefang Deng, Venkata Pavan Kumar Miriyala

Terahertz (THz) signals, mainly generated by photonic or electronic approaches, are being sought for various applications, whereas the development of magnetic source might be a necessary step to harness the magnetic nature of electromagnetic radiation. We show that the relativistic effect on the current-driven domain-wall motion induces THz spin-wave emissio

Steve Hofmann, Olli Tapiola

We construct extensions of Varopolous type for functions $f \in \text{BMO}(E)$, for any uniformly rectifiable set $E$ of codimension one. More precisely, let $Ω\subset \mathbb{R}^{n+1}$ be an open set satisfying the corkscrew condition, with an $n$-dimensional uniformly rectifiable boundary $\partial Ω$, and let $σ:= \mathcal{H}^n\lfloor_{\partial Ω}$ denote

J. -R. Marquès, C. Briand, F. Amiranoff, S. Depierreux

A new experimental platform based on laser-plasma interaction is proposed to explore the fundamental processes of wave coupling at the origin of interplanetary radio emissions. It is applied to the study of electromagnetic (EM) emission at twice the plasma frequency ($2ω_p$) observed during solar bursts and thought to result from the coalescence of two Langm

Connor Basich, Justin Svegliato, Kyle Hollins Wray, Stefan Witwicki

Interest in semi-autonomous systems (SAS) is growing rapidly as a paradigm to deploy autonomous systems in domains that require occasional reliance on humans. This paradigm allows service robots or autonomous vehicles to operate at varying levels of autonomy and offer safety in situations that require human judgment. We propose an introspective model of auto

Fernando Albiac, Jose L. Ansorena, Przemyslaw Wojtaszczyk

We show how to construct nonlocally convex quasi-Banach spaces $X$ whose dual separates the points of a dense subspace of $X$ but does not separate the points of $X$. Our examples connect with a question raised by Pietsch [About the Banach envelope of $l_{1,\infty}$, Rev. Mat. Complut. 22 (2009), 209-226] and shed light into the unexplored class of quasi-Ban

Na Sai, JinYuan Liao, ChengKui Li, Ju Guan

The Galactic plane scanning survey is one of the main scientific objectives of the Hard X-ray Modulation Telescope (known as Insight-HXMT). During the two-year operation of Insight-HXMT, more than 1000 scanning observations have been performed and the whole Galactic plane ($\rm 0^{\circ}<l<360^{\circ}$, $\rm -10^{\circ}<b<10^{\circ}$) has been covered comple

Salvador Dominguez, Gaëtan Garcia, Arnaud Hamon, Vincent Frémont

Obtaining a realistic and accurate model of the longitudinal dynamics is key for a good speed control of a self-driving car. It is also useful to simulate the longitudinal behavior of the vehicle with high fidelity. In this paper, a straightforward and generic method for obtaining the friction, braking and propulsion forces as a function of speed, throttle i

Da-Hye Yoon, Nam-Gyu Cho, Seong-Whan Lee

Online temporal action localization from an untrimmed video stream is a challenging problem in computer vision. It is challenging because of i) in an untrimmed video stream, more than one action instance may appear, including background scenes, and ii) in online settings, only past and current information is available. Therefore, temporal priors, such as the

Mu-Tao Wang

An idealized observer of an astronomical event is situated at future null infinity, where light rays emitted from the source approach. Mathematically, null infinity corresponds to the portion of the spacetime boundary defined by equivalence classes of null geodesics. But what can we observe at future null infinity? In the note, we start by reviewing the desc

Carlo Maria Carbonaro, Alessia Zurru, Viviana Fanti, Matteo Tuveri

We present the results of an experience of teaching updating dispensed to Italian high-school physics teachers to promote the application of the Cooperative Problem Solving method as an useful strategy to improve physics learning at high-school level and to foster the development of problem solving skills. Beside analysing the method and discussing the ways

Salvador Dominguez, Gaëtan Garcia, Vincent Frémont, Arnaud Hamon

One of the hardest challenges to face in the development of a non GPS-based localization system for autonomous vehicles is the changes of the environment. LiDAR-based systems typically try to match the last measurements obtained with a previously recorded map of the area. If the existing map is not updated along time, there is a good chance that the measures

Allison J. B. Chaney, Archit Verma, Young-suk Lee, Barbara E. Engelhardt

We describe nonparametric deconvolution models (NDMs), a family of Bayesian nonparametric models for collections of data in which each observation is the average over the features from heterogeneous particles. For example, these types of data are found in elections, where we observe precinct-level vote tallies (observations) of individual citizens&#39; votes

Zhaojian Wang, Wei Wei, Changhong Zhao, Zetian Zheng

In this paper, we investigate the continuous time partial primal-dual gradient dynamics (P-PDGD) for solving convex optimization problems with the form $ \min\limits_{x\in X,y\inΩ}\ f({x})+h(y),\ \textit{s.t.}\ A{x}+By=C $, where $ f({x}) $ is strongly convex and smooth, but $ h(y) $ is strongly convex and non-smooth. Affine equality and set constraints are

Mengyu Yao, Kaustuv Manna, Qun Yang, Alexander Fedorov

Non-symmorphic chiral topological crystals host exotic multifold fermions, and their associated Fermi arcs helically wrap around and expand throughout the Brillouin zone between the high-symmetry center and surface-corner momenta. However, Fermi-arc splitting and realization of the theoretically proposed maximal Chern number rely heavily on the spin-orbit co

Marco Forte, François Pitié

Cutting out an object and estimating its opacity mask, known as image matting, is a key task in many image editing applications. Deep learning approaches have made significant progress by adapting the encoder-decoder architecture of segmentation networks. However, most of the existing networks only predict the alpha matte and post-processing methods must the

Jing Zhang, Xin Yu, Aixuan Li, Peipei Song

Compared with laborious pixel-wise dense labeling, it is much easier to label data by scribbles, which only costs 1$\sim$2 seconds to label one image. However, using scribble labels to learn salient object detection has not been explored. In this paper, we propose a weakly-supervised salient object detection model to learn saliency from such annotations. In

O. J. D. Farley, J. Osborn, T. Morris, T. Fusco

The performance of tomographic adaptive optics systems is intrinsically linked to the vertical profile of optical turbulence. Firstly, a sufficient number of discrete turbulent layers must be reconstructed to model the true continuous turbulence profile. Secondly over the course of an observation, the profile as seen by the telescope changes and the tomograp

Sophie Hermann, Matthias Schmidt

We prove three exact sum rules that relate the polarization of active Brownian particles to their one-body current: (i) The total polarization vanishes, provided that there is no net flux through the boundaries, (ii) at any planar wall the polarization is determined by the magnitude of the bulk current, and (iii) the total interface polarization between phas

Eun-jin Kim, Rainer Hollerbach

We report a first study of time-dependent Probability Density Functions (PDFs) in the Low-to- High confinement mode (L-H) transition by extending the previous prey-predator-type model (Kim & Diamond, Phys. Rev. Lett. 91, 185006, 2003) to a stochastic model. We highlight the limited utility of mean value and variance in understanding the L-H transition by sho

Akshay Subramanian, Utkarsh Saha, Tejasvini Sharma, Naveen K. Tailor

Singlet fission has emerged as one of the most exciting phenomena known to improve the efficiencies of different types of solar cells and has found uses in diverse optoelectronic applications. The range of available singlet fission molecules is, however, limited as to undergo singlet fission, molecules have to satisfy certain energy conditions. Recent advanc

A. Dmytriiev, H. Sol, A. Zech

We present a new time-dependent leptonic code that we developed to model the varying multi-wavelength (MWL) emission during blazar flares. In our modeling, we assume that the blazar emission originates from a plasma blob located in the jet, and that relativistic electrons are injected into the blob and may undergo stochastic (Fermi II) or shock (Fermi I) acc

Hagai Netzer

New reverberation mapping (RM) measurements, combined with accurate luminosities and line ratios, provide strong constraints on the location of the line emitting gas in the broad line region (BLR) of active galactic nuclei (AGN). In this paper I present new calculations of radiation pressure and magnetic pressure confined clouds and apply them to a ``generic

Riccardo La Placa, Luigi Stella, Alessando Papitto, Pavel Bakala

We present a new method to measure the radius-to-mass ratio (R/M) of weakly magnetic, disc-accreting neutron stars by exploiting the occultation of parts of the inner disc by the star itself. This occultation imprints characteristic features on the X-ray line profile that are unique and are expected to be present in low mass X-ray binary systems seen under i

Alex Brodersen, Ick Hoon Jin, Ying Cheng, Minjeong Jeon

This study discusses an alternative tool for modeling student assessment data. The model constructs networks from a matrix item responses and attempts to represent these data in low dimensional Euclidean space. This procedure has advantages over common methods used for modeling student assessment data such as Item Response Theory because it relaxes the highl

Vladimir A. Petrov

This is an improved and extended exposition of the modified formulas for accounting for Coulomb-nuclear interference in hadron scattering which is intended to dispel recently claimed doubts.

Jon Lasa-Alonso, Diego R. Abujetas, Alvaro Nodar, Jennifer A. Dionne

Increasing the sensitivity of chiral spectroscopic techniques such as circular dichroism (CD) spectroscopy is a current aspiration in the research field of nanophotonics. Enhancing CD spectroscopy depends upon of two complementary requirements: the enhancement of the electromagnetic fields perceived by the molecules under study and the conservation of the he

Martin Dzúrik

In this article we study graphs with ordering of vertices, we define a generalization called a pseudoordering, and for a graph $H$ we define the $H$-Hamiltonian number of a graph $G$. We will show that this concept is a generalization of both the Hamiltonian number and the traceable number. We will prove equivalent characteristics of an isomorphism of graphs

Zhengzheng Tu, Chun Lin, Chenglong Li, Jin Tang

Classifying the confusing samples in the course of RGBT tracking is a quite challenging problem, which hasn&#39;t got satisfied solution. Existing methods only focus on enlarging the boundary between positive and negative samples, however, the structured information of samples might be harmed, e.g., confusing positive samples are closer to the anchor than no

Wolfgang Erb

For semi-supervised learning on graphs, we study how initial kernels in a supervised learning regime can be augmented with additional information from known priors or from unsupervised learning outputs. These augmented kernels are constructed in a simple update scheme based on the Schur-Hadamard product of the kernel with additional feature kernels. As gener

Vlas Sokolov, Jaime E. Pineda, Johannes Buchner, Paola Caselli

Resolved kinematical information, such as from molecular gas in star forming regions, is obtained from spectral line observations. However, these observations often contain multiple line-of-sight components, making estimates harder to obtain and interpret. We present a fully automatic method that determines the number of components along the line of sight, o

K. E. Harborne, C. Power, A. S. G. Robotham

We present SimSpin, a new, public, software framework for generating integral field spectroscopy (IFS) data cubes from N-body/hydrodynamical simulations of galaxies, which can be compared directly with observational datasets. SimSpin provides a consistent method for studying a galaxy&#39;s stellar component. It can be used to explore how observationally infe

Lin Wang, Tae-Kyun Kim, Kuk-Jin Yoon

Event cameras sense intensity changes and have many advantages over conventional cameras. To take advantage of event cameras, some methods have been proposed to reconstruct intensity images from event streams. However, the outputs are still in low resolution (LR), noisy, and unrealistic. The low-quality outputs stem broader applications of event cameras, whe

R. Riaz, D. R. G. Schleicher, S. Vanaverbeke, Ralf S. Klessen

While the stellar Initial Mass Function (IMF) appears to be close to universal within the Milky Way galaxy, it is strongly suspected to be different in the primordial Universe, where molecular hydrogen cooling is less efficient and the gas temperature can be higher by a factor of 30. In between these extreme cases, the gas temperature varies depending on the

Dario Guidotti, Francesco Leofante, Luca Pulina, Armando Tacchella

Verification of deep neural networks has witnessed a recent surge of interest, fueled by success stories in diverse domains and by abreast concerns about safety and security in envisaged applications. Complexity and sheer size of such networks are challenging for automated formal verification techniques which, on the other hand, could ease the adoption of de

P G Romeo, Riya Jose

For a category with subobjects and factorization, here we describe a new category which we call category of chain bundles and it is shown that this new category is also a category with subobjects and admits factorization under certain restriction. Further we provide several examples of bundle categories and discuss some interesting properties of these catego

Ivan Sekulić, Michael Strube

Mental health poses a significant challenge for an individual&#39;s well-being. Text analysis of rich resources, like social media, can contribute to deeper understanding of illnesses and provide means for their early detection. We tackle a challenge of detecting social media users&#39; mental status through deep learning-based models, moving away from tradi

Clément Cancès, Daniel Matthes

We prove the existence of weak solutions to a system of two diffusion equations that are coupled by a pointwise volume constraint. The time evolution is given by gradient dynamics for a free energy functional. Our primary example is a model for the demixing of polymers, the corresponding energy is the one of Flory, Huggins and deGennes. Due to the non-locali

Daniel Schlör, Markus Ring, Andreas Hotho

Neural networks have to capture mathematical relationships in order to learn various tasks. They approximate these relations implicitly and therefore often do not generalize well. The recently proposed Neural Arithmetic Logic Unit (NALU) is a novel neural architecture which is able to explicitly represent the mathematical relationships by the units of the ne

Neda Azarmehr, Xujiong Ye, Faraz Janan, James P Howard

Following the successful application of the U-Net to medical images, there have been different encoder-decoder models proposed as an improvement to the original U-Net for segmenting echocardiographic images. This study aims to examine the performance of the state-of-the-art proposed models as well as the original U-Net model by applying them to segment the e

Michael R. Wilczynska, John K. Webb, Matthew Bainbridge, Sarah E. I. Bosman

Observations of the redshift z=7.085 quasar J1120+0641 have been used to search for variations of the fine structure constant, alpha, over the redshift range 5.5 to 7.1. Observations at z=7.1 probe the physics of the universe when it was only 0.8 billion years old. These are the most distant direct measurements of alpha to date and the first measurements mad

Babich P. V., Levenshtam V. B

The paper is devoted to the development of the theory of inverse problems for evolution equations with terms rapidly oscillating in time. A new approach to setting such problems is developed for the case in which additional constraints are imposed only on several first terms of the asymptotics of the solution rather that on the whole solution. This approach

Giulia Slavic, Damian Campo, Mohamad Baydoun, Pablo Marin

This paper proposes a method for detecting anomalies in video data. A Variational Autoencoder (VAE) is used for reducing the dimensionality of video frames, generating latent space information that is comparable to low-dimensional sensory data (e.g., positioning, steering angle), making feasible the development of a consistent multi-modal architecture for au

Stephan Wiefling, Luigi Lo Iacono, Markus Dürmuth

Risk-based authentication (RBA) is an adaptive security measure to strengthen password-based authentication. RBA monitors additional implicit features during password entry such as device or geolocation information, and requests additional authentication factors if a certain risk level is detected. RBA is recommended by the NIST digital identity guidelines,

Laura Boeschoten, Erik-Jan van Kesteren, Ayoub Bagheri, Daniel L. Oberski

Fair inference in supervised learning is an important and active area of research, yielding a range of useful methods to assess and account for fairness criteria when predicting ground truth targets. As shown in recent work, however, when target labels are error-prone, potential prediction unfairness can arise from measurement error. In this paper, we show t

Benjamin F. Cooke, Don Pollacco, Monika Lendl, Thibault Kuntzer

We set out to look at the overlap between CHEOPS sky coverage and TESS primary mission monotransits to determine what fraction of TESS monotransits may be observed by CHEOPS. We carry out a simulation of TESS transits based on the stellar population in TICv8 in the primary TESS mission. We then select the monotransiting candidates and determine their CHEOPS

M. Migliorati, E. Métral, M. Zobov

In this paper a review of some important impedance-induced instabilities are briefly described for both the longitudinal and transverse planes. The main tools used nowadays to predict these instabilities and some considerations about possible mitigation techniques are also presented.

Soojung Yang, Kyung Hoon Lee, Seongok Ryu

Prediction models based on deep neural networks are increasingly gaining attention for fast and accurate virtual screening systems. For decision makings in virtual screening, researchers find it useful to interpret an output of classification system as probability, since such interpretation allows them to filter out more desirable compounds. However, probabi

Sibei Yang, Dachun Yang, Wen Yuan

Let $n\ge2$ and $Ω$ be a bounded Lipschitz domain in $\mathbb{R}^n$. In this article, the authors investigate global (weighted) estimates for the gradient of solutions to Robin boundary value problems of second order elliptic equations of divergence form with real-valued, bounded, measurable coefficients in $Ω$. More precisely, let $p\in(n/(n-1),\infty)$. Us

Davide Rossini, Ettore Vicari

We study the quantum dynamics of many-body systems, in the presence of dissipation due to the interaction with the environment, under Kibble-Zurek (KZ) protocols in which one Hamiltonian parameter is slowly, and linearly in time, driven across the critical value of a zero-temperature quantum transition. In particular we address whether, and under which condi

D. V. Zyabkin, H. P. Gunnlaugsson, J. N. Goncalves, K. Bharuth-Ram

In this study we report on the results from emission $^{57}$Fe M${ö}$ssbauer Spectroscopy experiments, using dilute $^{57}$Mn implantation into pristine (TiO$_2$) and hydrogenated anatase held at temperatures between 300-700 K. Results of the electronic structure and local environment are complemented with ab-initio calculations. Upon implantation both Fe$^{

Xiaoli Xu, Yong Zeng

In this paper, we propose a new three dimensional (3D) networking architecture with integrated aerial and ground base stations (BSs) for swift post-disaster communication recovery. By exploiting their respective advantages in terms of response time, coverage area, and operational duration, the proposed network is highly heterogeneous, consisting of sustained

Tomas Teijeiro, Paulo Felix

This paper presents a software implementation of a general framework for time series interpretation based on abductive reasoning. The software provides a data model and a set of algorithms to make inference to the best explanation of a time series, resulting in a description in multiple abstraction levels of the processes underlying the time series. As a pro

Lena Clever, Dennis Assenmacher, Kilian Müller, Moritz Vinzent Seiler

Nowadays fake news are heavily discussed in public and political debates. Even though the phenomenon of intended false information is rather old, misinformation reaches a new level with the rise of the internet and participatory platforms. Due to Facebook and Co., purposeful false information - often called fake news - can be easily spread by everyone. Becau

Ridvan Karagoz, Kim Batselier

This article introduces the Tensor Network B-spline model for the regularized identification of nonlinear systems using a nonlinear autoregressive exogenous (NARX) approach. Tensor network theory is used to alleviate the curse of dimensionality of multivariate B-splines by representing the high-dimensional weight tensor as a low-rank approximation. An iterat

Oleg Elshin, Andrew A. Tronin

Terra Seismic can predict most major earthquakes (M6.2 or greater) at least 2 - 5 months before they will strike. Global earthquake prediction is based on determinations of the stressed areas that will start to behave abnormally before major earthquakes. The size of the observed stressed areas roughly corresponds to estimates calculated from Dobrovolskys for

Claudiu Albulescu

This paper investigates the effect of the novel coronavirus and crude oil prices on the United States (US) economic policy uncertainty (EPU). Using daily data for the period January 21-March 13, 2020, our Autoregressive Distributed Lag (ARDL) model shows that the new infection cases reported at global level, and the death ratio, have no significant effect on

Ran Duan, Haoqing He, Tianyi Zhang

We study the maximum weight perfect $f$-factor problem on any general simple graph $G=(V,E,w)$ with positive integral edge weights $w$, and $n=|V|$, $m=|E|$. When we have a function $f:V\rightarrow \mathbb{N}_+$ on vertices, a perfect $f$-factor is a generalized matching so that every vertex $u$ is matched to $f(u)$ different edges. The previous best algorit

Chuanyang Jiang, Yanying Zhu, Kaixuan Guo, Qing Li

Bioelastomers have demonstrated tremendous value and potential in the field of tissue repair due to increasing health demands. Improved non-invasive methods are required for monitoring tissue development assisted by bioelastomers. In this paper, we present a novel theory of fluid-solid coupling in a porous medium for application to the ultrasonic evaluation

Tomonori Okuno, Masahiro Manago, Shunsaku Kitagawa, Kenji Ishida

We conducted$^{195}$Pt-nuclear magnetic resonance measurements on various-diameter Pt nanoparticles coated with polyvinylpyrrolidone in order to detect the quantum size effect and the discrete energy levels in the electron density of states, both of which were predicted by Kubo more than 50 years ago. We succeeded in separating the signals arising from the s

Wei Quan, Yuxuan Pan, Bin Xiang, Lin Zhang

With the merit of containing full panoramic content in one camera, Virtual Reality (VR) and 360-degree videos have attracted more and more attention in the field of industrial cloud manufacturing and training. Industrial Internet of Things (IoT), where many VR terminals needed to be online at the same time, can hardly guarantee VR&#39;s bandwidth requirement

Umar Iqbal, Pavlo Molchanov, Jan Kautz

One major challenge for monocular 3D human pose estimation in-the-wild is the acquisition of training data that contains unconstrained images annotated with accurate 3D poses. In this paper, we address this challenge by proposing a weakly-supervised approach that does not require 3D annotations and learns to estimate 3D poses from unlabeled multi-view data,

R. Iaria, S. M. Mazzola, T. Di Salvo, A. Marino

GX 9+9 (4U 1728-16) is a low mass X-ray binary (LMXB) source harboring a neutron star. Although it belongs to the subclass of the bright Atoll sources together with GX 9+1, GX 3+1, and GX 13+1, its broadband spectrum is poorly studied and apparently does not show reflection features in the spectrum. To constrain the continuum well and verify whether a relati

Tingting Yu, Guoxian Yu, Jun Wang, Maozu Guo

Partial multi-label learning (PML) models the scenario where each training instance is annotated with a set of candidate labels, and only some of the labels are relevant. The PML problem is practical in real-world scenarios, as it is difficult and even impossible to obtain precisely labeled samples. Several PML solutions have been proposed to combat with the

Yuhang Li, Wei Wang, Haoli Bai, Ruihao Gong

Network quantization has rapidly become one of the most widely used methods to compress and accelerate deep neural networks. Recent efforts propose to quantize weights and activations from different layers with different precision to improve the overall performance. However, it is challenging to find the optimal bitwidth (i.e., precision) for weights and act

Hiromasa Suzuki, Aya Bamba, Rei Enokiya, Hiroya Yamaguchi

We report on the results of our detailed analyses on the peculiar recombining plasma of the supernova remnant (SNR) G359.1$-$0.5, and the interacting CO clouds. Combining {\it Chandra} and {\it Suzaku} data, we estimated the ionization state of the plasma with a careful treatment of the background spectrum. The average spectrum showed a remarkably large devi

Yong Zeng, Xiaoli Xu, Shi Jin, Rui Zhang

Cellular-connected unmanned aerial vehicle (UAV) is a promising technology to unlock the full potential of UAVs in the future. However, how to achieve ubiquitous three-dimensional (3D) communication coverage for the UAVs in the sky is a new challenge. In this paper, we tackle this challenge by a new coverage-aware navigation approach, which exploits the UAV&

Haya Brama, Tal Grinshpoun

The growing incorporation of artificial neural networks (NNs) into many fields, and especially into life-critical systems, is restrained by their vulnerability to adversarial examples (AEs). Some existing defense methods can increase NNs&#39; robustness, but they often require special architecture or training procedures and are irrelevant to already trained

M. Tedesco, H. V. M. Hamelers, P. M. Biesheuvel

The effect of the thickness of ion exchange membranes has been investigated for electrodialysis (ED) and reverse electrodialysis (RED), both experimentally and through theoretical modeling. By developing a two-dimensional model based on Nernst-Planck theory, we theoretically find that reducing the membrane thickness benefits process performance only until a

Akihiro Inoue, Ken Ohsuga, Tomohisa Kawashima

We calculate the pulsed fraction (PF) of the super-critical column accretion flows onto magnetized neutron stars (NSs), of which the magnetic axis is misaligned with the rotation axis, based on the simulation results by Kawashima et al.(2016, PASJ, 68, 83). Here, we solve the geodesic equation for light in the Schwarzschild spacetime in order to take into ac

Viktor Yu. Kovalskii

Silanol nests can play the role of places into which positively charged groups, such as, [FeO]2+, can invade. In the framework of this work, the influence of such structures on the activity of the [FeO]2+ group in the reaction of detachment of a hydrogen atom from methane was considered. Two ways of the reaction of hydrogen atom transfer (HAT) from methane w

Hao Yang, Dan Yan, Li Zhang, Dong Li

Skeleton-based action recognition has attracted considerable attention in computer vision since skeleton data is more robust to the dynamic circumstance and complicated background than other modalities. Recently, many researchers have used the Graph Convolutional Network (GCN) to model spatial-temporal features of skeleton sequences by an end-to-end optimiza

Yiren Li, Zheng Huang, Junchi Yan, Yi Zhou

Tabular data is a crucial form of information expression, which can organize data in a standard structure for easy information retrieval and comparison. However, in financial industry and many other fields tables are often disclosed in unstructured digital files, e.g. Portable Document Format (PDF) and images, which are difficult to be extracted directly. In

Yu Liu, Guanglu Song, Yuhang Zang, Yan Gao

This article introduces the solutions of the two champion teams, `MMfruit&#39; for the detection track and `MMfruitSeg&#39; for the segmentation track, in OpenImage Challenge 2019. It is commonly known that for an object detector, the shared feature at the end of the backbone is not appropriate for both classification and regression, which greatly limits the

Vera L. J. Somers, Ian R. Manchester

In this letter we propose a method for sparse allocation of resources to control spreading processes -- such as epidemics and wildfires -- using convex optimization, in particular exponential cone programming. Sparsity of allocation has advantages in situations where resources cannot easily be distributed over a large area. In addition, we introduce a model

Masaki Honda

Matrix models are proposed as nonperturbative formulations of superstring theory. We study a concrete correspondence of the analytical result between the matrix model and the field theory. In this paper, we focus on a fuzzy sphere and a complex projective space. We show a wave functions/states correspondence of the zero modes of the Dirac operators under the

Zhidong Ding, Mackenzie Ridley, Jeroen Deijkers, Naiming Liu

Hafnium orthosilicate (HfSiO4: hafnon) has been proposed as an environmental barrier coating (EBC) material to protect silicon coated, silicon-based ceramic materials at high temperatures and as a candidate dielectric material in microelectronic devices. It can naturally form at the interface between silicon dioxide (SiO2) and hafnia (HfO2). When used in the

Cunhang Fan, Jianhua Tao, Bin Liu, Jiangyan Yi

In this paper, we propose an end-to-end post-filter method with deep attention fusion features for monaural speaker-independent speech separation. At first, a time-frequency domain speech separation method is applied as the pre-separation stage. The aim of pre-separation stage is to separate the mixture preliminarily. Although this stage can separate the mix

Guanglu Song, Yu Liu, Yuhang Zang, Xiaogang Wang

The small receptive field and capacity of minimal neural networks limit their performance when using them to be the backbone of detectors. In this work, we find that the appearance feature of a generic face is discriminative enough for a tiny and shallow neural network to verify from the background. And the essential barriers behind us are 1) the vague defin

N. Michel, J. G. Li, F. R. Xu, W. Zuo

We apply the Gamow shell model to study $^{25-31}$F isotopes. As both inter-nucleon correlations and continuum coupling are properly treated therein, the structure shape of $^{31}$F at large distance can be analyzed precisely. For this, one-nucleon densities, root-mean square radii and correlation densities are calculated in neutron-rich fluorine isotopes. I

Tian-Ying Xie, Long-Tu Yuan

For a fixed graph $F$, the $\textit{anti-Ramsey number}$, $AR(n,F)$, is the maximum number of colors in an edge-coloring of $K_n$ which does not contain a rainbow copy of $F$. In this paper, we determine the exact value of anti-Ramsey numbers of linear forests for sufficiently large $n$, and show the extremal edge-colored graphs. This answers a question of F

Guanglu Song, Yu Liu, Xiaogang Wang

The ``shared head for classification and localization&#39;&#39; (sibling head), firstly denominated in Fast RCNN~\cite{girshick2015fast}, has been leading the fashion of the object detection community in the past five years. This paper provides the observation that the spatial misalignment between the two object functions in the sibling head can considerably

Ming Ding, Shi Liu, Hanwen Luo, Wen Chen

We propose a greedy minimum mean squared error (MMSE)-based antenna selection algorithm for amplify-and-forward (AF) multiple-input multiple-output (MIMO) relay systems. Assuming equal-power allocation across the multi-stream data, we derive a closed form expression for the mean squared error (MSE) resulted from adding each additional antenna pair. Based on

Ming Ding, Meng Zhang, Hanwen Luo, Wen Chen

In this paper, we investigate the robust beamforming schemes for a multi-user multiple-input-single-output (MU-MISO) system with per-antenna power constraints and quantized channel direction information (CDI) feedback. Our design objective is to maximize the expectation of the weighted sum-rate performance by means of controlling the interference leakage and

Ming Ding, Jun Zou, Zeng Yang, Hanwen Luo

In this paper, we propose a sequential and incremental precoder design for downlink joint transmission (JT) network MIMO systems with imperfect backhaul links. The objective of our design is to minimize the maximum of the sub-stream mean square errors (MSE), which dominates the average bit error rate (BER) performance of the system. In the proposed scheme,we

Rameshwar L. Kumawat, Biswarup Pathak

In the last decade, solid state nanopores nanogaps have attracted significant interest in the rapid detection of DNA nucleotides. However, reducing the noise through the controlled translocating of the DNA nucleobases is a central issue for the developing nanogap nanopore based DNA sequencing to achieve single nucleobase resolution. Furthermore, the high rea

Yansheng Wu, Yoonjin Lee

Due to some practical applications, linear complementary dual (LCD) codes and self-orthogonal codes have attracted wide attention in recent years. In this paper, we use simplicial complexes for construction of an infinite family of binary LCD codes and two infinite families of binary self-orthogonal codes. Moreover, we explicitly determine the weight distrib

K. Ohnishi, S. Komori, G. Yang, K. -R. Jeon

Spin-transport in superconductors is a subject of fundamental and technical importance with the potential for applications in superconducting-based cryogenic memory and logic. Research in this area is rapidly intensifying with recent discoveries establishing the field of superconducting spintronics. In this perspective we provide an overview of the experimen

Ashish Verma

In this paper, we obtain recursion formulas for the Kampé de Feŕiet hypergeometric matrix function. We also give finite and infinite summation formulas for the Kampé de Feŕiet hypergeometric matrix function.