March 2020 arXiv papers — page 139

Ying-Qiu He, Dong Ding, Ting Gao, Fengli Yan

We consider six-photon entangled state emitted from a single third-order parametric down-conversion process. In the regime of weak nonlinearities, we present a symmetry detector which is capable of analyzing the twin-beam six-photon symmetric states. By cascading the symmetry detectors, as an application, it is shown that one can purify the desired six-photo

T. Ohmura, M. Machida, K. E. Nakamura, Y. Kudoh

We present the results of two-temperature magnetohydrodynamic simulations of the propagation of sub-relativistic jets of active galactic nuclei. The dependence of the electron and ion temperature distributions on the fraction of electron heating fe at the shock front is studied for fe=0, 0.05, and 0.2. Numerical results indicate that in sub-relativistic, rar

Leonardo Fernandez-Jambrina

In this paper we provide a characterisation of rational developable surfaces in terms of the blossoms of the bounding curves and three rational functions $Λ$, $M$, $ν$. Properties of developable surfaces are revised in this framework. In particular, a closed algebraic formula for the edge of regression of the surface is obtained in terms of the functions $Λ$

E. Ya. Paryev

We study the $J/ψ$ photoproduction from nuclei in the near-threshold beam energy region of $E_γ$=5--11 GeV within the nuclear spectral function approach by considering incoherent direct ($γN \to {J/ψ}N$) and two-step ($γp \to P^+_c(4312)$, $P^+_c(4312) \to {J/ψ}p$; $γp \to P^+_c(4440)$, $P^+_c(4440) \to {J/ψ}p$; $γp \to P^+_c(4457)$, $P^+_c(4457) \to {J/ψ}p$

V. Venkatesha, H. Aruna Kumara, Devaraja Mallesha Naik

The aim of this article is to study the Riemann soliton and gradient almost Riemann soliton on certain class of almost Kenmotsu manifolds. Also some suitable examples of Kenmotsu and $(κ,μ)'$-almost Kenmotsu manifolds are constructed to justify our results.

Cornelia Herbert, Jan Nachtsheim, Michael Munz

To improve the understanding of human gait and to facilitate novel developments in gait rehabilitation, the neural correlates of human gait as measured by means of non-invasive electroencephalography (EEG) have been investigated recently. Particularly, gait-related event-related brain potentials (gERPs) may provide information about the functional role of co

Wentang Kuo, Wei-Liang Sun

Let $p$ be a prime such that the multiplicative order $m$ of $2$ modulo $p$ is even. We prove that the integral group ring $\mathbb{Z}[Q_8 \times C_p]$ has the multiplicative Jordan decomposition property when $m$ is congruent to $2$ modulo $4$. There are infinitely many such primes and these primes include the case $p \equiv 3 \pmod{4}$. We also prove that

Eknath Ghate, Mihir Sheth

We use a Diamond diagram attached to a $2$-dimensional reducible split mod $p$ Galois representation of $\mathrm{Gal}(\overline{\mathbb{Q}_{p}}/\mathbb{Q}_{p^{2}})$ to construct a non-admissible smooth irreducible mod $p$ representation of $GL_{2}(\mathbb{Q}_{p^{2}})$ following the approach of Daniel Le.

Umit Kose, Andrzej Ruszczynski

We consider reinforcement learning with performance evaluated by a dynamic risk measure. We construct a projected risk-averse dynamic programming equation and study its properties. Then we propose risk-averse counterparts of the methods of temporal differences and we prove their convergence with probability one. We also perform an empirical study on a comple

Rakesh Kumar, Reena Koundal, K. Srivastava

In current work, non-familiar shifted Lucas polynomials are introduced. We have constructed a computational wavelet technique for solution of initial/boundary value second order differential equations. For this numerical scheme, we have developed weight function and Rodrigues' formula for Lucas polynomials. Further, Lucas polynomials and their properties

Justyna A. Niestrawska, Christoph M. Augustin, Gernot Plank

Cardiac growth and remodeling (G&R) refers to structural changes in myocardial tissue in response to chronic alterations in loading conditions. One such condition is pressure overload where elevated wall stresses stimulate the growth in cardiomyocyte thickness, associated with a phenotype of concentric hypertrophy at the organ scale, and promote fibrosis. Th

Andrea Simonetto

Convex regression (CR) is the problem of fitting a convex function to a finite number of noisy observations of an underlying convex function. CR is important in many domains and one of its workhorses is the non-parametric least square estimator (LSE). Currently, LSE delivers only non-smooth non-strongly convex function estimates. In this paper, leveraging re

Michael Hammann, Maximilian Kraus, Sina Shafaei, Alois Knoll

Identity recognition in a car cabin is a critical task nowadays and offers a great field of applications ranging from personalizing intelligent cars to suit drivers physical and behavioral needs to increasing safety and security. However, the performance and applicability of published approaches are still not suitable for use in series cars and need to be im

Stefan Mijin, Abetharan Antony, Fulvio Militello, Robert J. Kingham

Here we present a new code for modelling electron kinetics in the tokamak Scrape-Off Layer (SOL). SOL-KiT (Scrape-Off Layer Kinetic Transport) is a fully implicit 1D code with kinetic (or fluid) electrons, fluid (or stationary) ions, and diffusive neutrals. The code is designed for fundamental exploration of non-local physics in the SOL and utilizes an arbit

Ringo Baumann

Given the large variety of existing logical formalisms it is of utmost importance to select the most adequate one for a specific purpose, e.g. for representing the knowledge relevant for a particular application or for using the formalism as a modeling tool for problem solving. Awareness of the nature of a logical formalism, in other words, of its fundamenta

Auguste Hébert

Recently, Iwahori-Hecke algebras were associated to Kac-Moody groups over non-Archimedean local fields. In a previous paper, we introduced principal series representations for these algebras and partially generalized Kato's irreducibility criterion. In this paper, we study how some of these representations decompose when they are reducible and deduce inf

M. Mace, N. Mueller, S. Schlichting, S. Sharma

Chirality transfer between fermions and gauge fields plays a crucial role for understanding the dynamics of anomalous transport phenomena such as the Chiral Magnetic Effect. In this proceeding we present a first principles study of these processes based on classical-statistical real-time lattice simulations of strongly coupled QED $(e^2N_f=64)$. Our simulati

Svend-Age Biehs, Achim Kittel, Philippe Ben-Abdallah

Following a recent report on experiments it has been claimed that a phonon heat transfer through a vacuum gap between two solids due to quantum fluctuations had been measured. Here we make a theoretical analyzis of this mechanism and demonstrate that the Casimir force driven heat flux is at least 15 orders of magnitude smaller than the near-field heat flux b

Anton Deitmar

In this note we show the equivalence of Benjamini-Schramm convergence and convergence of the zeta functions for compact hyperbolic surfaces.

Francesco P. Pinnola, Giorgio Zavarise, Antonio Del Prete, Rodolfo Franchi

Finding an accurate stress-strain relation, able to describe the mechanical behavior of metals during {forming} and machining processes, is an important challenge in several fields of mechanics, with significant repercussions in the technological field. Indeed, in order to predict the real mechanical behavior of materials, constitutive laws must be able to t

Shantanu Mishra, Doreen Beyer, Kristjan Eimre, Ricardo Ortiz

Triangular zigzag nanographenes, such as triangulene and its pi-extended homologues, have received widespread attention as organic nanomagnets for molecular spintronics, and may serve as building blocks for high-spin networks with long-range magnetic order - of immense fundamental and technological relevance. As a first step toward these lines, we present th

Xiaobing Deng, Xiaoyu Yu, Jianfeng Pei

Regulating the upstream of the cytokines production could be a promising strategy to the treatment of COVID-19. We suggest to pay more attention to the dysregulated IFN-I production in COVID-19 and to considerate cGAS, ALK and STING as potential therapeutic targets preventing cytokine storm. Approved drugs like suramin and ALK inhibitors are worthy of clinic

David Tuckey, Alessandra Russo, Krysia Broda

Explainability in AI is gaining attention in the computer science community in response to the increasing success of deep learning and the important need of justifying how such systems make predictions in life-critical applications. The focus of explainability in AI has predominantly been on trying to gain insights into how machine learning systems function

Mohammed S. G. Mohammed, Luciano Colazzo, Roberto Robles, Ruth Dorel

We report on the effect of sp3 hybridized carbon atoms in acene derivatives adsorbed on metal surfaces, namely decoupling the molecules from the supporting substrates. In particular, we have used a Ag(100) substrate and hydrogenated heptacene molecules, in which the longest conjugated segment determining its frontier molecular orbitals amounts to five consec

Carlo Guarnieri Calo\' Carducci, Gianluca Lipari, Nicola Giaquinto, Ferdinanda Ponci

Phasor Measurement Units (PMUs) are measurement devices long used in transmission systems and today even more essential for a proper monitoring of distribution grids. The expected massive penetration of distributed energy resources (DERs) is slowly taking place, carrying along a new set of challenges that put to test traditional instruments and requiring mor

Simone Ciani, Vincenzo Vespri

We shall establish the interior Hölder continuity for locally bounded weak solutions to a class of parabolic singular equations whose prototypes are \begin{equation} u_t= \nabla \cdot \bigg( |\nabla u|^{p-2} \nabla u \bigg), \quad \text{ for } \quad 1<p<2, \end{equation} and \begin{equation} u_{t}- \nabla \cdot ( u^{m-1} | \nabla u |^{p-2} \nabla u ) =0 , \q

Jose Villa, Jussi Taipalmaa, Mikhail Gerasimenko, Alexander Pyattaev

The aim of this work is to offer an overview of the research questions, solutions, and challenges faced by the project aColor (&#34;Autonomous and Collaborative Offshore Robotics&#34;). This initiative incorporates three different research areas, namely, mechatronics, machine learning, and communications. It is implemented in an autonomous offshore multicomp

C. Lazzoni, R. Gratton, J. M. Alcalà, S. Desidera

Very recently, a second companion on wider orbit has been discovered around GQ Lup. This is a low-mass accreting star partially obscured by a disk seen at high inclination. If detected, this disk may be compared to the known disk around the primary. We detected this disk on archive HST and WISE data. The extended spectral energy distribution provided by thes

Ivan Marin

In this technical note, we complete the PhD work of A. Esterle about determining the image of any Artin group of finite Coxeter type inside the associated Hecke algebra over a finite field, when the latter is semisimple. The only remaining case was the 48-dimensional irreducible representation in type $H_4$, for which the image is proven here to be $Ω_{48}^+

Rafael Hirschburger, Anke Weidlich

The increasing gap between electricity prices and feed-in tariffs for photovoltaic (PV) electricity in many countries, along with the recent strong cost degression of batteries, led to a rise in installed combined PV and battery systems worldwide. The load profile of a property greatly affects the self-consumption rate and, thus, the profitability of the sys

Werner M. Seiler, Matthias Seiss, Thomas Sturm

We discuss the effective computation of geometric singularities of implicit ordinary differential equations over the real numbers using methods from logic. Via the Vessiot theory of differential equations, geometric singularities can be characterised as points where the behaviour of a certain linear system of equations changes. These points can be discovered

Liang Jiang, Zujie Wen, Zhongping Liang, Yafang Wang

In the past decade, there has been substantial progress at training increasingly deep neural networks. Recent advances within the teacher--student training paradigm have established that information about past training updates show promise as a source of guidance during subsequent training steps. Based on this notion, in this paper, we propose Long Short-Ter

Yuka Hashimoto, Isao Ishikawa, Masahiro Ikeda, Fuyuta Komura

Kernel methods have been among the most popular techniques in machine learning, where learning tasks are solved using the property of reproducing kernel Hilbert space (RKHS). In this paper, we propose a novel data analysis framework with reproducing kernel Hilbert $C^*$-module (RKHM), which is another generalization of RKHS than vector-valued RKHS (vv-RKHS).

Adrian-S. Ungureanu, Saqib Salahuddin, Peter Corcoran

As a biometric palmprints have been largely under-utilized, but they offer some advantages over fingerprints and facial biometrics. Recent improvements in imaging capabilities on handheld and wearable consumer devices have re-awakened interest in the use fo palmprints. The aim of this paper is to provide a comprehensive review of state-of-the-art methods for

Manuel Penschuck, Ulrik Brandes, Michael Hamann, Sebastian Lamm

Random graph models are frequently used as a controllable and versatile data source for experimental campaigns in various research fields. Generating such data-sets at scale is a non-trivial task as it requires design decisions typically spanning multiple areas of expertise. Challenges begin with the identification of relevant domain-specific network feature

Yang Yu, Wen Chen, Jun Li, Xiao Ma

The equivalent binary parity check matrices for the binary images of the cycle-free non-binary LDPC codes have numerous bit-level cycles. In this paper, we show how to transform these binary parity check matrices into their cycle-free forms. It is shown that the proposed methodology can be adopted not only for the binary images of non-binary LDPC codes but a

Hans-Joachim Grafe, Piotr Lepucki, Markus Witschel, Adam P. Dioguardi

We present $^{75}$As Nuclear Magnetic and Quadrupole Resonance results (NMR, NQR) on a new set of LaFeAsO$_{1-x}$F$_x$ polycrystalline samples. Improved synthesis conditions led to more homogenized samples with better control of the fluorine content. The structural$\equiv$nematic, magnetic, and superconducting transition temperatures have been determined by

Abhishek Pandey, A. K. Singh, Shovan Dan, K. Ghosh

We report investigations of the structural, magnetic, electrical transport and thermal properties of five compositions of the metallic perovskite GdRh$_3$C$_{1-x}$B$_x$ ($0.00 \le x \le 1.00$). Our results show that all the five compositions undergo magnetic ordering at low temperatures, but the nature of the ordered state is significantly different in the c

Bruno P. Zimmermann

We consider finite group-actions on closed, orientable and nonorientable 3-manifolds M which preserve the two handlebodies of a Heegaard splitting of M of some genus g > 1 (maybe interchanging the two handlebodies). The maximal possible order of a finite group-action on a handlebody of genus g>1 is 12(g-1) in the orientation-preserving case and 24(g-1) in ge

O. Linder, E. Fable, F. Jenko, G. Papp

We present the first successful simulation of a induced disruption in ASDEX Upgrade from massive material injection (MMI) up to established runaway electron (RE) beam, thus covering pre-thermal quench, thermal quench and current quench (CQ) of the discharge. For future high-current fusion devices such as ITER, the successful suppression of REs through MMI is

Abdulsamet Caglan, Adem Cicek, Enver Cavus, Ebrahim Bedeer

Reduced complexity faster-than-Nyquist (FTN) signaling systems are gaining increased attention as they provide improved bandwidth utilization for an acceptable level of detection complexity. In order to have a better understanding of the tradeoff between performance and complexity of the reduced complexity FTN detection techniques, it is necessary to study t

Junfeng Wen, Bo Dai, Lihong Li, Dale Schuurmans

We consider the problem of approximating the stationary distribution of an ergodic Markov chain given a set of sampled transitions. Classical simulation-based approaches assume access to the underlying process so that trajectories of sufficient length can be gathered to approximate stationary sampling. Instead, we consider an alternative setting where a fixe

Peter Camps, Maarten Baes

The open source SKIRT Monte Carlo radiative transfer code has been used for more than 15 years to model the interaction between radiation and dust in various astrophysical systems. In this work, we present version 9 of the code, which has been substantially redesigned to support long-term objectives. We invite interested readers to participate in the develop

Alessandro Monguzzi, Marco M. Peloso

In this paper we discuss some recent results concerning the regularity and irregularity of the Bergman and Szegő projections on some weakly pseudoconvex domains that have the common feature to possess a nontrivial Nebenhülle.

Klaus Kirch, Philipp Schmidt-Wellenburg

Searches for permanent electric dipole moments of fundamental particles and systems with spin are the experiments most sensitive to new CP violating physics and a top priority of a growing international community. We briefly review the current status of the field emphasizing on the charged leptons and lightest baryons.

Yang Yu, Wen Chen

By presenting an approximated performance-complexity tradeoff (PCT) algorithm,a low-complexity non-binary low density parity check (LDPC) code over q-ary-input symmetric-output channel is designed in this manuscript which converges faster than the threshold-optimized non-binary LDPC codes in the low error rate regime. We examine our algorithm by both hard an

Abolfazl Lavaei, Fabio Somenzi, Sadegh Soudjani, Ashutosh Trivedi

A novel reinforcement learning scheme to synthesize policies for continuous-space Markov decision processes (MDPs) is proposed. This scheme enables one to apply model-free, off-the-shelf reinforcement learning algorithms for finite MDPs to compute optimal strategies for the corresponding continuous-space MDPs without explicitly constructing the finite-state

Sizhang Dai, Weibing Huang

We propose a learning-based network for depth map estimation from multi-view stereo (MVS) images. Our proposed network consists of three sub-networks: 1) a base network for initial depth map estimation from an unstructured stereo image pair, 2) a novel refinement network that leverages both photometric and geometric information, and 3) an attentional multi-v

Suhyun Shin, Myungshin Im, Yongjung Kim, Minhee Hyun

The intergalactic medium (IGM) at $z\sim$ 5 to 6 is largely ionized, and yet the main source for the IGM ionization in the early universe is uncertain. Of the possible contributors are faint quasars with $-26 \lesssim M_{\rm 1450} \lesssim -23$, but their number density is poorly constrained at $z\sim5$. In this paper, we present our survey of faint quasars

Gaurav Verma, Vishwa Vinay, Sahil Bansal, Shashank Oberoi

Interactive search sessions often contain multiple queries, where the user submits a reformulated version of the previous query in response to the original results. We aim to enhance the query recommendation experience for a commercial image search engine. Our proposed methodology incorporates current state-of-the-art practices from relevant literature -- th

Puneet Kohli, Saravana Gunaseelan, Jason Orozco, Yiwen Hua

An estimated 60% of smartphones sold in 2018 were equipped with multiple rear cameras, enabling a wide variety of 3D-enabled applications such as 3D Photos. The success of 3D Photo platforms (Facebook 3D Photo, Holopix, etc) depend on a steady influx of user generated content. These platforms must provide simple image manipulation tools to facilitate content

Jianglei Han, Jing Li, Aixin Sun

Corporations today face increasing demands for the timely and effective delivery of customer service. This creates the need for a robust and accurate automated solution to what is formally known as the ticket routing problem. This task is to match each unresolved service incident, or &#34;ticket&#34;, to the right group of service experts. Existing studies d

Jan Bouwe van den Berg, Wouter Hetebrij, Bob Rink

In a previous paper we generalized the parameterization method of Cabré, Fontich and De la Llave to center manifolds of discrete dynamical systems. In this paper, we extend this result to several different settings. The natural setting in which center manifolds occur is at bifurcations in dynamical systems with parameters. Our first results will show that we

Hao Chen, Weiwei Wan, Keisuke Koyama, Kensuke Harada

This paper presents a planner that can automatically find an optimal assembly sequence for a dual-arm robot to assemble the soma blocks. The planner uses the mesh model of objects and the final state of the assembly to generate all possible assembly sequence and evaluate the optimal assembly sequence by considering the stability, graspability, assemblability

Diana Thongjaomayum, Sergej Flach, Alexei Andreanov

We consider the quasiperiodic Aubry-André chain in the insulating regime with localised single-particle states. Adding local interaction leads to the emergence of extended correlated two-particle bound states. We analyse the nature of these states including their multifractality properties. We use a projected Green function method to compute numerically part

Eshagh Kargar, Ville Kyrki

Driving in the dynamic, multi-agent, and complex urban environment is a difficult task requiring a complex decision policy. The learning of such a policy requires a state representation that can encode the entire environment. Mid-level representations that encode a vehicle&#39;s environment as images have become a popular choice, but they are quite high-dime

Huizhang Yang, Chengzhi Chen, Shengyao Chen, Feng Xi

To avoid decorrelation, conventional synthetic aperture radar interferometry (InSAR) requires that interferometric images should have a common spectral band and the same resolution after proper preprocessing. For a high-resolution (HR) image and a low-resolution (LR) one, the interferogram quality is limited by the LR one since the non-common band (NCB) betw

Luigi C. Berselli, Dominic Breit

In this paper we consider the steady Baldwin-Lomax model, which is a rotational model proposed to describe turbulent flows at statistical equilibrium. The Baldwin-Lomax model is specifically designed to address the problem of a turbulent motion taking place in a bounded domain, with Dirichlet boundary conditions at solid boundaries. The main features of this

Rupam Acharyya, Shouman Das, Ankani Chattoraj, Oishani Sengupta

Unbiased data collection is essential to guaranteeing fairness in artificial intelligence models. Implicit bias, a form of behavioral conditioning that leads us to attribute predetermined characteristics to members of certain groups and informs the data collection process. This paper quantifies implicit bias in viewer ratings of TEDTalks, a diverse social pl

Xubo Wang, Lu Qin, Lijun Chang, Ying Zhang

Graph is a ubiquitous structure in many domains. The rapidly increasing data volume calls for efficient and scalable graph data processing. In recent years, designing distributed graph processing systems has been an increasingly important area to fulfil the demands of processing big graphs in a distributed environment. Though a variety of distributed graph p

Ikkei Shimizu

We prove that the solutions to the initial-value problem for 2-dimensional Schrödinger maps are unique in $C_tL_x^{\infty} \cap L_t^{\infty} (\dot{H}^1_x\cap \dot{H}^2_x)$. For the proof, we follow McGahagan&#39;s argument with improving its technical part, combining Yudovich&#39;s argument.

Minghan Chen, Yilong Sun, Xueqing Cai, Boyi Liu

The agricultural irrigation system is closely related to agricultural production. There are some problems in nowadays agricultural irrigation system, such as poor mobility, imprecision and high price. To address these issues, an intelligent irrigation robot is designed and implemented in this work. The robot achieves precise irrigation by the irrigation path

Vladislav Kibalov, Oleg Shipitko

In order for autonomous vehicles to become a part of the Intelligent Transportation Ecosystem, they are required to guarantee a particular level of safety. For that to happen a safe vehicle control algorithms need to be developed, which include assessing the probability of a collision while driving along a given trajectory and selecting control signals that

Kuo-Hao Zeng, Mohammad Shoeybi, Ming-Yu Liu

We introduce a language generative model framework for generating a styled paragraph based on a context sentence and a style reference example. The framework consists of a style encoder and a texts decoder. The style encoder extracts a style code from the reference example, and the text decoder generates texts based on the style code and the context. We prop

Valentino Tosatti

We survey some recent developments on the problem of understanding degenerations of Calabi-Yau manifolds equipped with their Ricci-flat Kahler metrics, with an emphasis on the case when the metrics are volume collapsing.

Dejiao Hu, Hao Li, Yupeng Zhu, Yuqiu Lei

Two-dimensional (2D) transition metal dichalcogenides (TMDs) with tantalizing layer-dependent electronic and optical properties have emerged as a new paradigm for integrated flat opto-electronic devices. However, daunting challenges remain in deterministic fabrication of TMD layers with demanded shapes and thicknesses as well as light field manipulation in s

Marvin Chancán, Michael Milford

Autonomous navigation emerges from both motion and local visual perception in real-world environments. However, most successful robotic motion estimation methods (e.g. VO, SLAM, SfM) and vision systems (e.g. CNN, visual place recognition-VPR) are often separately used for mapping and localization tasks. Conversely, recent reinforcement learning (RL) based me

Zehua Zhao, Jiqiang Zheng

In this article, we study long time dynamics for defocusing cubic NLS on three dimensional product space. First, we apply the decoupling method in Bourgain-Demeter \cite{BD} to establish a bilinear Strichartz estimate. Moreover, we prove global well-posedness for defocusing, cubic NLS on three dimensional product space with rough initial data ($H^s$, $s>\fra

Alice Fialowski, Kenji Iohara

In this lecutre note, we consider infinite dimensional Lie algebras of generalized Jacobi matrices $\mathfrak{g}J(k)$ and $\mathfrak{gl}_\infty(k)$, which are important in soliton theory, and their orthogonal and symplectic subalgebras. In particular, we construct the homology ring of the Lie algebra $\mathfrak{g}J(k)$ and of the orthogonal and symplectic su

Shinsuke Koyama, Shigeru Shinomoto

Event occurrence is not only subject to the environmental changes, but is also facilitated by the events that have occurred in a system. Here, we develop a method for estimating such extrinsic and intrinsic factors from a single series of event-occurrence times. The analysis is performed using a model that combines the inhomogeneous Poisson process and the H

Xusheng Luo, Yan Zhang, Michael M. Zavlanos

In this paper, we consider the problem of designing collision-free, dynamically feasible, and socially-aware trajectories for robots operating in environments populated by humans. We define trajectories to be social-aware if they do not interfere with humans in any way that causes discomfort. In this paper, discomfort is defined broadly and, depending on spe

Eunji Jun, Ahmad Wisnu Mulyadi, Jaehun Choi, Heung-Il Suk

Electronic health records (EHR) are characterized as non-stationary, heterogeneous, noisy, and sparse data; therefore, it is challenging to learn the regularities or patterns inherent within them. In particular, sparseness caused mostly by many missing values has attracted the attention of researchers, who have attempted to find a better use of all available

Zuyao Chen, Qianqian Xu, Runmin Cong, Qingming Huang

Deep convolutional neural networks have achieved competitive performance in salient object detection, in which how to learn effective and comprehensive features plays a critical role. Most of the previous works mainly adopted multiple level feature integration yet ignored the gap between different features. Besides, there also exists a dilution process of hi

Larry R. Nittler, Elizabeth A. Frank, Shoshana Z. Weider, Ellen Crapster-Pregont

The X-Ray Spectrometer (XRS) on the MESSENGER spacecraft provided measurements of major-element ratios across Mercury&#39;s surface. We present global maps of Mg/Si, Al/Si, S/Si, Ca/Si, and Fe/Si derived from XRS data collected throughout MESSENGER&#39;s orbital mission. We describe the procedures we used to select and filter data and to combine them to make

Hsien-Chih Chang, Arnaud de Mesmay

We prove the first polynomial bound on the number of monotonic homotopy moves required to tighten a collection of closed curves on any compact orientable surface, where the number of crossings in the curve is not allowed to increase at any time during the process. The best known upper bound before was exponential, which can be obtained by combining the algor

Andrew S. Friedman, Roman Gerasimov, Fabian Kislat, David Leon

In the framework of the Standard Model Extension (SME), we present improved constraints on anisotropic Lorentz invariance and Charge-Parity-Time (CPT) violation by searching for astrophysical signals of cosmic vacuum birefringence with broadband optical polarimetry of high redshift astronomical sources, including Active Galactic Nuclei and Gamma-Ray Burst af

Noptanit Chotisarn, Leonel Merino, Xu Zheng, Supaporn Lonapalawong

We report on the state-of-the-art of software visualization. To ensure reproducibility, we adopted the Systematic Literature Review methodology. That is, we analyzed 1440 entries from IEEE Xplore and ACM Digital Library databases. We selected 105 relevant full papers published in 2013-2019, which we classified based on the aspect of the software system that

Hiroki Kawai, Jiawei Chen, Prakash Ishwar, Janusz Konrad

We present a novel variational generative adversarial network (VGAN) based on Wasserstein loss to learn a latent representation from a face image that is invariant to identity but preserves head-pose information. This facilitates synthesis of a realistic face image with the same head pose as a given input image, but with a different identity. One application

Chenhao Niu, Yang Song, Jiaming Song, Shengjia Zhao

Learning generative models for graph-structured data is challenging because graphs are discrete, combinatorial, and the underlying data distribution is invariant to the ordering of nodes. However, most of the existing generative models for graphs are not invariant to the chosen ordering, which might lead to an undesirable bias in the learned distribution. To

Fang Xu, Shijie Lin, Wen Yang, Lei Yu

The event camera has appealing properties: high dynamic range, low latency, low power consumption and low memory usage, and thus provides complementariness to conventional frame-based cameras. It only captures the dynamics of a scene and is able to capture almost &#34;continuous&#34; motion. However, different from frame-based camera that reflects the whole

Hesham Mostafa, Marcel Nassar

Graph convolutional networks (GCNs) update a node&#39;s feature vector by aggregating features from its neighbors in the graph. This ignores potentially useful contributions from distant nodes. Identifying such useful distant contributions is challenging due to scalability issues (too many nodes can potentially contribute) and oversmoothing (aggregating feat

Stuart J. Robbins, Michelle R. Kirchoff, Rachael H. Hoover

The Mars Reconnaissance Orbiter (MRO) spacecraft has been in orbit around Mars since March 2006. The Context Camera (CTX) on MRO has returned over 100,000 images of the planet at approximately 5-6 meters per pixel, providing nearly global coverage. During that time, Mars has gone through nearly 7 of its own years, changing solar distance from 1.38 to 1.67 AU

Thu Dinh, Bao Wang, Andrea L. Bertozzi, Stanley J. Osher

Deep neural nets (DNNs) compression is crucial for adaptation to mobile devices. Though many successful algorithms exist to compress naturally trained DNNs, developing efficient and stable compression algorithms for robustly trained DNNs remains widely open. In this paper, we focus on a co-design of efficient DNN compression algorithms and sparse neural arch

Chenghao Deng, Jing Yang, Changyong Pan

In this paper, we consider a status updating system where the transmitter sends status updates of the signal it monitors to the destination through a rate-limited link. We consider the scenario where the status of the monitored signal only changes at discrete time points. The objective is to let the destination be synchronized with the source in a timely man

Zoltán Füredi, Tao Jiang, Alexandr Kostochka, Dhruv Mubayi

In this paper we present a novel approach in extremal set theory which may be viewed as an asymmetric version of Katona&#39;s permutation method. We use it to find more Turán numbers of hypergraphs in the Erdős--Ko--Rado range. An $(a,b)$-path $P$ of length $2k-1$ consists of $2k-1$ sets of size $r=a+b$ as follows. Take $k$ pairwise disjoint $a$-element sets

Kevin Schultz, Marisel Villafane-Delgado

In the field of graph signal processing (GSP), directed graphs present a particular challenge for the &#34;standard approaches&#34; of GSP to due to their asymmetric nature. The presence of negative- or complex-weight directed edges, a graphical structure used in fields such as neuroscience, critical infrastructure, and robot coordination, further complicate

Shota Ono

The low temperature electron-phonon (e-ph) relaxation near the surface of noble metals, Cu and Ag, is studied by using the density-functional theory approach. The appearance of the surface phonon mode can give rise to a strong enhancement of the Eliashberg function at low frequency $ω$. Assuming the Eliashberg function proportional to the square of $ω$ in th

Peng Jia, Xuebo Wu, Yi Huang, Bojun Cai

Ground based optical telescopes are seriously affected by atmospheric turbulence induced aberrations. Understanding properties of these aberrations is important both for instruments design and image restoration methods development. Because the point spread function can reflect performance of the whole optic system, it is appropriate to use the point spread f

Yan Ge, Philipp Rosendahl, Claudio Durán, Nicole Töpfner

Despite fluorescent cell-labelling being widely employed in biomedical studies, some of its drawbacks are inevitable, with unsuitable fluorescent probes or probes inducing a functional change being the main limitations. Consequently, the demand for and development of label-free methodologies to classify cells is strong and its impact on precision medicine is

Cyril Grunspan, Ricardo Pérez-Marco

We survey recent results on the mathematical stability of Bitcoin protocol. Profitability and probability of a double spend are estimated in closed form with classical special functions. The stability of Bitcoin mining rules is analyzed and several theorems are proved using martingale and combinatorics techniques. In particular, the empirical observation of

Mengshuo Jia, Chen Shen, Zhaojian Wang

Due to the uncertainty of distributed wind generations (DWGs), a better understanding of the probability distributions (PD) of their wind power forecast errors (WPFEs) can help market participants (MPs) who own DWGs perform better during trading. Under the premise of an accurate PD model, considering the correlation among DWGs and absorbing the new informati

Krishna Chaitanya Kosaraju, Michele Cucuzzella, Jacquelien M. A. Scherpen, Ramkrishna Pasumarthy

This paper deals with a class of Resistive-Inductive-Capacitive (RLC) circuits and switched RLC (s-RLC) circuits modeled in Brayton Moser framework. For this class of systems, new passivity properties using a Krasovskii&#39;s type Lyapunov function as storage function are presented. Consequently, the supply-rate is a function of the system states, inputs and

Mahmoud Assran, Michael Rabbat

We consider a multi-agent framework for distributed optimization where each agent has access to a local smooth strongly convex function, and the collective goal is to achieve consensus on the parameters that minimize the sum of the agents&#39; local functions. We propose an algorithm wherein each agent operates asynchronously and independently of the other a

Alexander Novikov, Pavel Izmailov, Valentin Khrulkov, Michael Figurnov

Tensor Train decomposition is used across many branches of machine learning. We present T3F -- a library for Tensor Train decomposition based on TensorFlow. T3F supports GPU execution, batch processing, automatic differentiation, and versatile functionality for the Riemannian optimization framework, which takes into account the underlying manifold structure

Hua Wei, Dongkuan Xu, Junjie Liang, Zhenhui Li

Modeling how human moves in the space is useful for policy-making in transportation, public safety, and public health. Human movements can be viewed as a dynamic process that human transits between states (\eg, locations) over time. In the human world where intelligent agents like humans or vehicles with human drivers play an important role, the states of ag

Omid Zandi, Renske M. van der Veen

We present a theoretical approach to study the dynamics of spherical, cylindrical and ellipsoidal charge distributions under their self-Coulomb field and a stochastic force due to collisions and random motions of charged particles. The approach is based on finding the current density of the charge distribution from the charge-current continuity equation and

Laia Amorós, Syed Mahbub Hafiz, Keewoo Lee, M. Caner Tol

We propose a HE-based protocol for trading ML models and describe possible improvements to the protocol to make the overall transaction more efficient and secure.

Henrique Ferrolho, Wolfgang Merkt, Vladimir Ivan, Wouter Wolfslag

This paper focuses on robustness to disturbance forces and uncertain payloads. We present a novel formulation to optimize the robustness of dynamic trajectories. A straightforward transcription of this formulation into a nonlinear programming problem is not tractable for state-of-the-art solvers, but it is possible to overcome this complication by exploiting

Dongrui Wu

To effectively train Takagi-Sugeno-Kang (TSK) fuzzy systems for regression problems, a Mini-Batch Gradient Descent with Regularization, DropRule, and AdaBound (MBGD-RDA) algorithm was recently proposed. It has demonstrated superior performances; however, there are also some limitations, e.g., it does not allow the user to specify the number of rules directly

Bang-Hai Wang

Quantum states are the key mathematical objects in quantum mechanics, and entanglement lies at the heart of the nascent fields of quantum information processing and computation. However, there has not been a general, necessary and sufficient, and operational separability condition to determine whether an arbitrary quantum state is entangled or separable. In