April 2019 arXiv papers — page 19

Jiayuan Mao, Chuang Gan, Pushmeet Kohli, Joshua B. Tenenbaum

We propose the Neuro-Symbolic Concept Learner (NS-CL), a model that learns visual concepts, words, and semantic parsing of sentences without explicit supervision on any of them; instead, our model learns by simply looking at images and reading paired questions and answers. Our model builds an object-based scene representation and translates sentences into ex

Chunfeng Song, Yan Huang, Wanli Ouyang, Liang Wang

Semantic segmentation has achieved huge progress via adopting deep Fully Convolutional Networks (FCN). However, the performance of FCN based models severely rely on the amounts of pixel-level annotations which are expensive and time-consuming. To address this problem, it is a good choice to learn to segment with weak supervision from bounding boxes. How to m

Srinivasan Aiyappan, Klas Pettersson

This paper deals with the homogenization of a mixed boundary value problem for the Laplace operator in a domain with locally periodic oscillating boundary. The Neumann condition is prescribed on the oscillating part of the boundary, and the Dirichlet condition on a separate part. It is shown that the homogenization result holds in the sense of weak $L^2$ con

Letian Wang, Matthew Eliceiri, Yang Deng, Yoonsoo Rho

Phase change material (PCM) features distinct optical or electronic properties between amorphous and crystalline states. Recently, it starts to play a key role in the emerging photonic applications like optoelectronic display, dynamic wavefront control, on-chip photonic memory and computation. However, current PCMs do not refract effectively at visible wavel

Fikret A. Aliev, N. A. Aliev, N. A. Safarova

In this paper the Mittag-Leffler function is given through the exponential functions for any rational derivatives of m/n order, where m<n, n>1 are natural irreducible numbers (if n=1 then m is also equal to unity). Unlike the previous papers the given formulas do not contain integrals.

M. T. Wei, A. W. Draelos, A. Seredinski, C. T. Ke

We study a two-terminal graphene Josephson junction with contacts shaped to form a narrow constriction, less than 100nm in length. The contacts are made from type II superconducting contacts and able to withstand magnetic fields high enough to reach the quantum Hall (QH) regime in graphene. In this regime, the device conductance is determined by edge states,

Ashish Upadhyay, Shashank Kotyan, Shrivishal Tripathi, Sandeep Yadav

Spectrum scarcity is one of the major challenges that the modern communication engineers are going through because of inefficient utilization of allocated frequency spectrum. The spectrum scarcity is a problem because there is not enough wavelengths/frequency to match the number of channels which are required to broadcast in a given bandwidth. Therefore, the

Dongjun Lee, Jaesik Yoon, Jongyun Song, Sanggil Lee

Most deep learning approaches for text-to-SQL generation are limited to the WikiSQL dataset, which only supports very simple queries. Recently, template-based and sequence-to-sequence approaches were proposed to support complex queries, which contain join queries, nested queries, and other types. However, Finegan-Dollak et al. (2018) demonstrated that both t

D. Karabali, S. Kurkcuoglu, V. P. Nair

The pair production rates for spin-zero and spin-$\frac{1}{2}$ particles are calculated on spaces of the form $M \times {\mathbb R}^{1,1}$ with $M$ corresponding to ${\mathbb R}^2$ (flat), $T^2$ (flat, compactified), $S^2$ (positive curvature) and $H^2$ (negative curvature), with and without a background magnetic field on $M$. The motivation is to elucidate

Khaled B. Letaief, Wei Chen, Yuanming Shi, Jun Zhang

The recent upsurge of diversified mobile applications, especially those supported by Artificial Intelligence (AI), is spurring heated discussions on the future evolution of wireless communications. While 5G is being deployed around the world, efforts from industry and academia have started to look beyond 5G and conceptualize 6G. We envision 6G to undergo an

Xiang Wang, Kai Wang, Shiguo Lian

The quality and size of training set have great impact on the results of deep learning-based face related tasks. However, collecting and labeling adequate samples with high quality and balanced distributions still remains a laborious and expensive work, and various data augmentation techniques have thus been widely used to enrich the training dataset. In thi

Fuying Cui, Yuchao Tang, Yang Yang

The three-operators splitting algorithm is a popular operator splitting method for finding the zeros of the sum of three maximally monotone operators, with one of which is cocoercive operator. In this paper, we propose a class of inertial three-operator splitting algorithm. The convergence of the proposed algorithm is proved by applying the inertial Krasnose

Arkaprava Das, Ashish Kumar, Vijay Soni, Soumen Kar

In the present investigation resistivity Vs temperature measurements have been performed for solgel prepared pure and Ni doped CdO (NDO) thin films. The semiconducting behavior i.e. negative temperature coefficient of resistivity (TCR) of pure CdO thin film through-out the whole temperature range can be attributed mainly due to concentration dependent therma

Yongqi Zhang, Quanming Yao, Wenyuan Dai, Lei Chen

Scoring functions (SFs), which measure the plausibility of triplets in knowledge graph (KG), have become the crux of KG embedding. Lots of SFs, which target at capturing different kinds of relations in KGs, have been designed by humans in recent years. However, as relations can exhibit complex patterns that are hard to infer before training, none of them can

Lijun Zhang, Tie-Yan Liu, Zhi-Hua Zhou

We investigate online convex optimization in changing environments, and choose the adaptive regret as the performance measure. The goal is to achieve a small regret over every interval so that the comparator is allowed to change over time. Different from previous works that only utilize the convexity condition, this paper further exploits smoothness to impro

Alexander A. Khajetoorians, Daniel Wegner, Alexander F. Otte, Ingmar Swart

With the advances in high resolution and spin-resolved scanning tunneling microscopy as well as atomic-scale manipulation, it has become possible to create and characterize quantum states of matter bottom-up, atom-by-atom. This is largely based on controlling the particle- or wave-like nature of electrons, as well as the interactions between spins, electrons

Xinyi Zhou, Atishay Jain, Vir V. Phoha, Reza Zafarani

Massive dissemination of fake news and its potential to erode democracy has increased the demand for accurate fake news detection. Recent advancements in this area have proposed novel techniques that aim to detect fake news by exploring how it propagates on social networks. Nevertheless, to detect fake news at an early stage, i.e., when it is published on a

Sumanta kumar das, R. S. Singh

Accurate predictions of electro-optical imager performance are important for defence decision-making. The predictions serve as a guide for system development and are used in war game, simulations that directly influence engagement tactics. In the present study, mathematical models have been developed which involves detection of different military targets usi

Naoya Uematsu, Shunji Umetani, Yoshinobu Kawahara

When approaching to problems in computer science, we often encounter situations where a subset of a finite set maximizing some utility function needs to be selected. Some of such utility functions are known to be approximately submodular. For the problem of maximizing an approximately submodular function (ASFM problem), a greedy algorithm quickly finds good

Yusuke Ujitoko, Yuki Ban, Koichi Hirota

Previous studies have aimed at creating a simple hardware implementation of surface friction display. In this study, we propose a new method for presenting static frictional sensation using the pseudo-haptic effect as a first attempt, which is the simplest implementation of presenting static friction sensation. We focus on the stick-slip phenomenon while use

Huanyin Chen, Marjan Sheibani Abdolyousefi

Let $R$ be an associative ring with an identity and suppose that $a,b,c,d \in R$ satisfy $bdb = bac,dbd = acd$. If $ac$ has generalized Drazin ( respectively, pseudo Drazin, Drazin) inverse, we prove that $bd$ has generalized Drazin (respectively, pseudo Drazin, Drazin) inverse. In particular, as applications, we obtain new common spectral properties of boun

Teagan E. Bate, Edward J. Jarvis, Megan E. Varney, Kun-Ta Wu

Self-organization of kinesin-driven, microtubule-based 3D active fluids relies on the collective dynamics of single microtubules. However, the connection between macroscopic fluid flows and microscopic motion of microtubules remains unclear. In this work, the motion of single microtubules was characterized by means of 2D gliding assays and compared with the

V. L. Oknyansky, V. I. Shenavrin, N. V. Metlova, C. M. Gaskell

We present results of a study of the correlation between the infrared (JHKL) and optical(B) fluxes of the nucleus of the Seyfert galaxy NGC 4151 for the years 2010 - 2015 using our own data (partially published) in combination with published data of Roberts and Rumstey (2012), Guo et al. (2014) and Schnulle et al. (2013, 2015).We find similar lags for each o

Shashank Kotyan, Danilo Vasconcellos Vargas, Venkanna U

Intrinsically, driving is a Markov Decision Process which suits well the reinforcement learning paradigm. In this paper, we propose a novel agent which learns to drive a vehicle without any human assistance. We use the concept of reinforcement learning and evolutionary strategies to train our agent in a 2D simulation environment. Our model's architecture goe

Kyrylo Snizhko, Reinhold Egger, Yuval Gefen

We provide a detailed theoretical analysis of the adiabatic evolution of degenerate open quantum systems, where the dynamics is induced by time-dependent fluctuating loop paths in control parameter space. For weak system-bath coupling, the fluctuations around a deterministic base path obey Gaussian statistics, where we assume that the quantum adiabatic theor

Ken Sakaushi

Kinetic isotope effect (KIE) is a common physicochemical effect to elucidate complicated microscopic reaction mechanism in biological, chemical and physical systems. Especially, the exchange of hydrogen to deuterium is a standard approach to investigate kinetics and pathways of a wide spectrum of key reactions involving proton transfer. However, KIE in elect

Bo-Hung Chen, Dah-Wei Chiou

With the inclusion of arbitrary long-range hopping and (pseudo)spin-orbit coupling amplitudes, we formulate a generic model that can describe any two-dimensional two-band bulk insulators, thus providing a simple framework to investigate arbitrary adiabatic deformations upon the systems of any arbitrary Chern numbers. Without appealing to advanced techniques

Ruta Kale, Krishna M. Shende, Viral Parekh

Diffuse radio sources associated with the intra-cluster medium are direct probes of the cosmic ray electrons and magnetic fields. We report the discovery of a diffuse radio source in the galaxy cluster RXCJ0232.2-4420 (SPT-CL J0232-4421, $z=0.2836$) using 606 MHz observations with the Giant Metrewave Radio Telescope. The diffuse radio source surrounds the Br

Yuta Fujihashi, Ryosuke Shimizu, Akihito Ishizaki

Light incident upon molecules trigger fundamental processes in diverse systems present in nature. However, under natural conditions, such as sunlight illumination, it is impossible to assign known times for photon arrival owing to continuous pumping, and therefore, the photo-induced processes cannot be easily investigated. In this work, we theoretically demo

Nazakat Ali, Jang-Eui Hong

Background/Objectives: Software engineering community has been studied extensively on large-sized software organizations and has provided suitable and interesting solutions. However, small software companies that make a large part of the software industry have been overlooked. Methods/Statistical analysis: The current requirement engineering practices are no

Arturo I. Merino, José A. Soto

We study the minimum weight basis problem on matroid when elements' weights are uncertain. For each element we only know a set of possible values (an uncertainty area) that contains its real weight. In some cases there exist bases that are uniformly optimal, that is, they are minimum weight bases for every possible weight function obeying the uncertainty are

Alvaro Alvarez-Parrilla, Jesús Muciño-Raymundo

We consider the family $\mathcal{E}(s,r,d)=\Big\{ X(z)=\frac{Q(z)}{P(z)}\ e^{E(z)} \frac{\partial}{\partial z} \Big\},$ with $Q, P, E$ polynomials, deg${Q}=s$, deg$(P)=r$ and deg$(E)=d$, of singular complex analytic vector fields $X$ on the Riemann sphere $\widehat{\mathbb{C}}$. For $d\geq1$, $X\in\mathcal{E}(s,r,d)$ has $s$ zeros and $r$ poles on the comple

Chaohan Cui, Reeshad Arian, Saikat Guha, N. Peyghambarian

Indistinguishable single photons are key ingredient for a plethora of quantum information processing applications ranging from quantum communications to photonic quantum computing. A mainstream platform to produce indistinguishable single photons over a wide spectral range is based on biphoton generation through spontaneous parametric down-conversion (SPDC)

Zhu L. -Y., Qian S. -B., Fernandez Lajus, E.

NSVS 14256825 is the second sdOB + dM eclipsing binary systems with an orbital period of 2.65 hours. The special binary was reported to contain circumbinary planets or brown dwarfs by using the timing method. However, different results were derived by different authors because of the insufficient coverage of eclipse timings. Since 2008, we have monitored thi

Hao Ge, Randall Berry

Many network resource allocation problems can be viewed as allocating a divisible resource, where the allocations are constrained to lie in a polymatroid. We consider market-based mechanisms for such problems. Though the Vickrey-Clarke-Groves (VCG) mechanism can provide the efficient allocation with strong incentive properties (namely dominant strategy incen

Sunkyu Yu, Xianji Piao, Namkyoo Park

Chirality is ubiquitous from microscopic to macroscopic phenomena in physics and biology, such as fermionic interactions and DNA duplication. In photonics, chirality has traditionally represented differentiated optical responses for right and left circular polarizations. This definition of optical chirality in the polarization domain includes handedness-depe

Shanyu Ji, Wanke Yin

We show the D'Angelo conjecture holds in the third gap interval. More precisely, we prove that the degree of any rational proper holomorphic map from $\mathbb{B}^n$ to $\mathbb{B}^{4n-6}$ with $n\geq 7$ is not more than $3$.

Chengjian Sun, Chenyang Yang

In this paper, we study how to solve resource allocation problems in ultra-reliable and low-latency communications by unsupervised deep learning, which often yield functional optimization problems with quality-of-service (QoS) constraints. We take a joint power and bandwidth allocation problem as an example, which minimizes the total bandwidth required to gu

David Dov, Shahar Ziv Kovalsky, Serge Assaad, Avani A. Pendse Jonathan Cohen

We consider machine-learning-based thyroid-malignancy prediction from cytopathology whole-slide images (WSI). Multiple instance learning (MIL) approaches, typically used for the analysis of WSIs, divide the image (bag) into patches (instances), which are used to predict a single bag-level label. These approaches perform poorly in cytopathology slides due to

Abdelrahman Mohamed, Dmytro Okhonko, Luke Zettlemoyer

The recent success of transformer networks for neural machine translation and other NLP tasks has led to a surge in research work trying to apply it for speech recognition. Recent efforts studied key research questions around ways of combining positional embedding with speech features, and stability of optimization for large scale learning of transformer net

Joachim Toft

We extend Paley-Wiener results in the Bargmann setting deduced earlier by the author together with E. Nabizadeh and C. Pfeuffer to larger class of power series expansions. At the same time we deduce characterisations of all Pilipovi{\'c} spaces and their distributions (and not only of low orders as in the earlier work).

Hanqing Nan, Yu Zheng, Shaohua Chen, Christopher Eddy

Collective cell migration in 3D extracellular matrix (ECM) is crucial to many physiological and pathological processes. Migrating cells can generate active pulling forces via actin filament contraction, which are transmitted to the ECM fibers and lead to a dynamically evolving force network in the system. Here, we elucidate the role of such force network in

STAR Collaboration

We report on the first measurements of J/$\psi$ production at very low transverse momentum ($p_{T} <$ 0.2 GeV/c) in hadronic Au+Au collisions at $\sqrt{s_{\rm{NN}}} =$ 200 GeV and U+U collisions at $\sqrt{s_{\rm{NN}}} =$ 193 GeV. Remarkably, the inferred nuclear modification factor of J/$\psi$ at mid-rapidity in Au+Au (U+U) collisions reaches about 24 (52) f

E. Acri, R. Lutowski, L. Vendramin

Using Bieberbach groups we study multipermutation involutive solutions to the Yang-Baxter equation. We use a linear representation of the structure group of an involutive solution to study the unique product property in such groups. An algorithm to find subgroups of a Bieberbach group isomorphic to the Promislow subgroup is introduced and then used in the ca

Chang-Rui Yi, Jin-Long Yu, Wei Sun, Xiao-Tian Xu

A dynamical Hopf insulator is experimentally synthesized with a quenched two-dimensional quantum anomalous Hall system on a square Raman lattice. The quench dynamics for the quasimomentum-time-dependent Bloch vectors defines a Hopf map from $(q_x,q_y,t)\in T^3$ to the Bloch sphere $S^2$. In this Hopf map, a dynamical Hopf number can be defined, and it exactl

Feng Ji, Wee Peng Tay

Graph signal processing (GSP) has become an important tool in many areas such as image processing, networking learning and analysis of social network data. In this paper, we propose a broader framework that not only encompasses traditional GSP as a special case, but also includes a hybrid framework of graph and classical signal processing over a continuous d

Liz Arcila-Osejo, Marcin Sawicki, Stephane Arnouts, Anneya Golob

We introduce the largest to date survey of massive quiescent galaxies at redshift z~1.6. With these data, which cover 27.6 deg^2, we can find significant numbers of very rare objects such as ultra-massive quiescent galaxies that populate the extreme massive end of the galaxy mass function, or dense environments that are likely to become present-day massive g

Hongzhi Wang, Jiabao Han, Bin Shao, Jianzhong Li

In many applications, it is necessary to retrieve pairs of vertices with the path between them satisfying certain constraints, since regular expression is a powerful tool to describe patterns of a sequence. To meet such requirements, in this paper, we define regular expression (RE) query on graphs to use regular expression to represent the constraints betwee

Bum Chul Kwon, Vibha Anand, Kristen A Severson, Soumya Ghosh

Clinical researchers use disease progression models to understand patient status and characterize progression patterns from longitudinal health records. One approach for disease progression modeling is to describe patient status using a small number of states that represent distinctive distributions over a set of observed measures. Hidden Markov models (HMMs

Yu-Zhong Wu, Wei Zhang, Yong-Heng Zhao

We present a sample of 86,111 star-forming galaxies (SFGs) selected from the catalogue of the MPA-JHU emission-line measurements for SDSS DR7 to investigate the evolution of mass-metallicity (MZ) relation. We find that: under the $\rm log(L_{H \alpha})>41.0$ threshold, the $0.04<z\leqslant0.06$ SFGs with $9.2<$ log($M_{\star}/M_{\sun})<9.5$ have always highe

Wonyoung Cho, Kanghoon Lee

We discuss the generalization of the Kerr-Schild (KS) formalism for general relativity and double field theory (DFT) to the heterotic DFT and supergravity. We first introduce a heterotic KS ansatz by introducing a pair of null O(d,d+G) generalized tangent vectors. The pair of null vectors are represented by a pair of d-dimensional vector fields, and one of t

Maosen Li, Siheng Chen, Xu Chen, Ya Zhang

Action recognition with skeleton data has recently attracted much attention in computer vision. Previous studies are mostly based on fixed skeleton graphs, only capturing local physical dependencies among joints, which may miss implicit joint correlations. To capture richer dependencies, we introduce an encoder-decoder structure, called A-link inference modu

Alexandre Reeberg Mello, Jonathan de Matos, Marcelo R. Stemmer, Alceu de Souza Britto

In this paper, we propose the use of a black-box optimization method called deterministic Mesh Adaptive Direct Search (MADS) algorithm with orthogonal directions (Ortho-MADS) for the selection of hyperparameters of Support Vector Machines with a Gaussian kernel. Different from most of the methods in the literature that exploit the properties of the data or a

Chong Ma, Wenxuan Deng, Shuangge Ma, Ray Liu

The identification of predictive biomarkers from a large scale of covariates for subgroup analysis has attracted fundamental attention in medical research. In this article, we propose a generalized penalized regression method with a novel penalty function, for enforcing the hierarchy structure between the prognostic and predictive effects, such that a nonzer

Pei-Lun Tseng

We consider the infinitesimal freeness in the operator-valued framework, and we show that the operator-valued infinitesimal (OVI) free independence is equivalent to the operator-valued free independence over an algebra of $2\times 2$ upper triangular matrices. We introduce the notion of OVI cumulants and investigate its properties, and we then deduce that th

Sergio Grillo, Leandro Salomone, Marcela Zuccalli

In the Hamiltonian formalism, and in the presence of a symmetry Lie group, a variational reduction procedure has already been developed for Hamiltonian systems without constraints. In this paper we present a procedure of the same kind, but for the entire class of the higher order constrained systems (HOCS), described in the Hamiltonian formalism. Last system

Indrani Banerjee, Ayan Bhattacharjee, Anuvab Banerjee, Dipak Debnath

The galactic black hole candidate Cygnus X-1, one of the brightest sources in the sky, is the first ever black hole candidate to be discovered. Despite being a very well-studied object due to its persistent brightness in X-rays, there has been much difficulty in determining its mass since its discovery. In spite of continuous efforts since the early nineteen

Toan Tran, Thanh-Toan Do, Ian Reid, Gustavo Carneiro

Deep learning models have demonstrated outstanding performance in several problems, but their training process tends to require immense amounts of computational and human resources for training and labeling, constraining the types of problems that can be tackled. Therefore, the design of effective training methods that require small labeled training sets is

Xiao-Tian Xu, Zong-Yao Wang, Rui-Heng Jiao, Chang-Rui Yi

Ultra-low noise magnetic field is essential for many branches of scientific research. Examplesinclude experiments conducted on ultra-cold atoms, quantum simulations, as well as precisionmeasurements. In ultra-cold atom experiments specifically, a bias magnetic field will be oftenserved as a quantization axis and be applied for Zeeman splitting. As atomic sta

Mohammed Senoussaoui, Patrick Cardinal, Najim Dehak, Alessandro Lameiras Koerich

Automatic measuring of speaker sincerity degree is a novel research problem in computational paralinguistics. This paper proposes covariance-based feature vectors to model speech and ensembles of support vector regressors to estimate the degree of sincerity of a speaker. The elements of each covariance vector are pairwise statistics between the short-term fe

Erich Poppitz, Thomas A. Ryttov

We discuss an exotic phase that adjoint QCD possibly exhibits in the deep infrared (IR). It is a confining phase, with a light spectrum consisting of massless composite fermions. The discrete chiral symmetry is broken, with unbroken continuous chiral symmetry. We argue that it may give a description of the IR of adjoint QCD with three massless Weyl flavors a

Osamu Fujino

John Lesieutre constructed an example satisfying $\kappa_\sigma\ne \kappa_\nu$. This says that the proof of the inequalities in Theorems 1.3, 1.9, and Remark 3.8 in [O. Fujino, On subadditivity of the logarithmic Kodaira dimension, J. Math. Soc. Japan 69 (2017), no. 4, 1565--1581] is insufficient. We claim that some weaker inequalities still hold true and th

J. -Y. Guan, L. -Y. Kong, L. -Q. Zhou, Y. -G. Zhong

Connate topological superconductor (TSC) combines topological surface states with nodeless superconductivity in a single material, achieving effective $p$-wave pairing without interface complication. By combining angle-resolved photoemission spectroscopy and $in$-$situ$ molecular beam epitaxy, we studied the momentum-resolved superconductivity in $\beta$-$\r

Dimitris Bertsimas, Christopher McCord

In this paper, we introduce a framework for solving finite-horizon multistage optimization problems under uncertainty in the presence of auxiliary data. We assume the joint distribution of the uncertain quantities is unknown, but noisy observations, along with observations of auxiliary covariates, are available. We utilize effective predictive methods from m

S. Takizawa, H. Katsuragi

Although a large number of astronomical craters are actually produced by the oblique impacts onto inclined surfaces, most of the laboratory experiments mimicking the impact cratering have been performed by the vertical impact onto a horizontal target surface. In previous studies on the effects of oblique impact and inclined terrain, only one of the impact an

Hideyuki Koie

Let $A$ be a truncated quiver algebra over an algebraically closed field such that any oriented cycle in the ordinary quiver of $A$ is zero in $A$. We give the number of the indecomposable direct summands of the middle term of an almost split sequence for a class of Hochschild extension algebras of $A$ by the standard duality module $D(A)$.

Saeideh Roshanfekr, Shahriar Esmaeili, Hassan Ataeian, Ali Amiri

We propose a method of using a Weighted second-order cone programming twin support vector machine (WSOCP-TWSVM) for imbalanced data classification. This method constructs a graph based under-sampling method which is utilized to remove outliers and reduce the dispensable majority samples. Then, appropriate weights are set in order to decrease the impact of sa

Magalí Giaroli, Rick Rischter, Mercedes Pérez Millán, Alicia Dickenstein

The distributive sequential n-site phosphorylation/dephosphorylation system is an important building block in networks of chemical reactions arising in molecular biology, which has been intensively studied. In the nice paper of Wang and Sontag (2008) it is shown that for certain choices of the reaction rate constants and total conservation constants, the sys

Anshuka Rangi, Massimo Franceschetti

In an effort to develop the foundations for a non-stochastic theory of information, the notion of $\delta$-mutual information between uncertain variables is introduced as a generalization of Nair's non-stochastic information functional. Several properties of this new quantity are illustrated, and used to prove a channel coding theorem in a non-stochastic set

Rebecca G. Martin, Stephen H. Lubow

Martin & Lubow (2017) found that an initially sufficiently misaligned low mass protoplanetary disc around an eccentric binary undergoes damped nodal oscillations of tilt angle and longitude of ascending node. Dissipation causes evolution towards a stationary state of polar alignment in which the disc lies perpendicular to the binary orbital plane with angula

Abbas Ganji, Negin Alimohammadi, Scott Miles

The importance of community resilience has become increasingly recognized in emergency management and post-disaster community well-being. To this end, three seismic resilience planning initiatives have been conducted in the U.S. in the last decade to envision the current state of community resilience. Experts who participated in these initiatives confronted

R. Hussain, F. Cugini, S. Baldini, G. Porcari

We report on a study on a representative set of Fe$_{2}$P-based MnFePSi samples by means of $^{55}$Mn NMR in both zero and applied magnetic field. The first-order nature of the magnetic transition is demonstrated by truncated order parameter curves with a large value of the local ordered moment at the Curie point, even at compositions where the transition ap

Abhay Shastry, Yiheng Xu, Charles A. Stafford

We consider open quantum systems consisting of a finite system of independent fermions with arbitrary Hamiltonian coupled to one or more equilibrium fermion reservoirs (which need not be in equilibrium with each other). A strong form of the third law of thermodynamics, $S(T) \rightarrow 0$ as $T\rightarrow 0$, is proven for fully open quantum systems in ther

K. Egawa, H. Katsuragi

When a solid projectile is dropped onto a dense non-Brownian-particle suspension, the action of an extremely large resistance force on the projectile results in its drastic deceleration, followed by a rebound. In this study, we perform a set of simple experiments of dropping a solid-projectile impact onto a dense potato-starch suspension. From the kinematic

Michael T. Schaub, Santiago Segarra, Hoi-To Wai

We discuss a variant of `blind&#39; community detection, in which we aim to partition an unobserved network from the observation of a (dynamical) graph signal defined on the network. We consider a scenario where our observed graph signals are obtained by filtering white noise input, and the underlying network is different for every observation. In this fashi

Varun Jain, Yi Zhang, Joël Fisser, Artur Palha

We present a hybrid mimetic spectral element formulation for Darcy flow. The discrete representations for 1) conservation of mass, and 2) inter-element continuity, are topological relations that lead to sparse matrix systems. These constraints are independent of the element size and shape, and thus invariant under mesh transformations. The resultant algebrai

Peter Benner, Pawan Goyal

In this work, we investigate a model order reduction scheme for polynomial parametric systems. We begin with defining the generalized multivariate transfer functions for the system. Based on this, we aim at constructing a reduced-order system, interpolating the defined generalized transfer functions at a given set of interpolation points. Furthermore, we pro

Ramachandran Anantharaman, Virendra Sule

This paper develops methods for analyzing periodic orbits of states of linear feedback shift registers with periodic coefficients and estimating their lengths. These shift registers are among the simplest nonlinear feedback shift registers (FSRs) whose orbit lengths can be determined by feasible computation. In general such a problem for nonlinear FSRs invol

Ziyuan Gu, Sajjad Shafiei, Zhiyuan Liu, Meead Saberi

Given the efficiency and equity concerns of a cordon toll, this paper proposes a few alternative distance-dependent area-based pricing models for a large-scale dynamic traffic network. We use the Network Fundamental Diagram (NFD) to monitor the network traffic state over time and consider different trip lengths in the toll calculation. The first model is a d

Ziyuan Gu, S. Travis Waller, Meead Saberi

Toll optimization in a large-scale dynamic traffic network is typically characterized by an expensive-to-evaluate objective function. In this paper, we propose two toll level problems (TLPs) integrated with a large-scale simulation-based dynamic traffic assignment (DTA) model of Melbourne, Australia. The first TLP aims to control the pricing zone (PZ) throug

Fanhai Zeng, Ian Turner, Kevin Burrage, Stephen J. Wright

In this paper, we develop regularized discrete least squares collocation and finite volume methods for solving two-dimensional nonlinear time-dependent partial differential equations on irregular domains. The solution is approximated using tensor product cubic spline basis functions defined on a background rectangular (interpolation) mesh, which leads to hig

Innocent Niyonzima, Yang Jiao, Jacob Fish

Shape memory materials have gained considerable attention thanks to their ability to change physical properties when subjected to external stimuli such as temperature, pH, humidity, electromagnetic fields, etc. These materials are increasingly used for a large number of biomedical applications. For applications inside the human body, contactless control can

Martin W. Hess, Annalisa Quaini, Gianluigi Rozza

We consider the Navier-Stokes equations in a channel with a narrowing of varying height. The model is discretized with high-order spectral element ansatz functions, resulting in 6372 degrees of freedom. The steady-state snapshot solutions define a reduced order space through a standard POD procedure. The reduced order space allows to accurately and efficient

Natalie Beams, Adrianna Gillman, Russell J. Hewett

The recently developed Hierarchical Poincaré-Steklov (HPS) method is a high-order discretization technique that comes with a direct solver. Results from previous papers demonstrate the method&#39;s ability to solve Helmholtz problems to high accuracy without the so-called pollution effect. While the asymptotic scaling of the direct solver&#39;s computational

Hashim A. Hashim, Lyndon J. Brown, Kenneth McIsaac

This paper formulates the pose estimation problem as nonlinear stochastic filter kinematics evolved directly on the Special Euclidean Group SE(3). Proposed filter guarantees that the errors present in position and Rodriguez vector estimates are semi-globally uniformly ultimately bounded (SGUUB) in mean square, and that they converge to small neighborhood of

Francesco Patrizi, Tor Dokken

The focus on locally refined spline spaces has grown rapidly in recent years due to the need in Isogeoemtric analysis (IgA) of spline spaces with local adaptivity: a property not offered by the strict regular structure of tensor product B-spline spaces. However, this flexibility sometimes results in collections of B-splines spanning the space that are not li

Mark Giesbrecht, Joseph Haraldson, Erich Kaltofen

Differential (Ore) type polynomials with &#34;approximate&#34; polynomial coefficients are introduced. These provide an effective notion of approximate differential operators, with a strong algebraic structure. We introduce the approximate Greatest Common Right Divisor Problem (GCRD) of differential polynomials, as a non-commutative generalization of the wel

Hafiene Yosra, Jalal Fadili, Abderrahim Elmoataz

In this paper we study numerical approximations of the evolution problem for the nonlocal $p$-Laplacian with homogeneous Neumann boundary conditions. First, we derive a bound on the distance between two continuous-in-time trajectories defined by two different evolution systems (i.e. with different kernels and initial data). We then provide a similar bound fo

Oleh Dmytrenko, Dmitry Lande, Oleh Andriichuk

In this paper, we consider the problem of choosing the optimal scenario of the impact between nodes based on of the introduced criteria for the optimality of the impact. Two criteria for the optimality of the impact, which are called the force of impact and the speed of implementation of the scenario, are considered. To obtain a unique solution of the proble

Henry Lam, Fengpei Li

We consider optimization problems with uncertain constraints that need to be satisfied probabilistically. When data are available, a common method to obtain feasible solutions for such problems is to impose sampled constraints, following the so-called scenario optimization approach. However, when the data size is small, the sampled constraints may not statis

Clint Y. H. Wong, Philippe H. Trinh, S. Jonathan Chapman

We consider the instabilities of flows through a submerged canopy, and show how the full governing equations of the fluid-structure interactions can be reduced to a compact framework that captures many key features of vegetative flow. By modelling the canopy as a collection of homogeneous elastic beams, we predict the steady configuration of the plants in re

Michael Damron, Arnab Sen

In zero-temperature Glauber dynamics, vertices of a graph are given i.i.d.~initial spins $\sigma_x(0)$ from $\{-1,+1\}$ with $\mathbb{P}_p(\sigma_x(0) = +1)=p$, and they update their spins at the arrival times of i.i.d. Poisson processes to agree with a majority of their neighbors. We study this process on the 3-regular tree $\mathbb{T}_3$, where it is known

Martin Gerlach, Eduardo G. Altmann

The availability of large datasets requires an improved view on statistical laws in complex systems, such as Zipf's law of word frequencies, the Gutenberg-Richter law of earthquake magnitudes, or scale-free degree distribution in networks. In this paper we discuss how the statistical analysis of these laws are affected by correlations present in the observat

Cathryn M. Trott, Shih Ching Fu, Steven Murray, Christopher Jordan

We explore methods for robust estimation of the 21 cm signal from the Epoch of Reionisation (EoR). A Kernel Density Estimator (KDE) is introduced for measuring the spatial temperature fluctuation power spectrum from the EoR. The KDE estimates the underlying probability distribution function of fluctuations as a function of spatial scale, and contains differe

Vincent S. Chen, Paroma Varma, Ranjay Krishna, Michael Bernstein

Visual knowledge bases such as Visual Genome power numerous applications in computer vision, including visual question answering and captioning, but suffer from sparse, incomplete relationships. All scene graph models to date are limited to training on a small set of visual relationships that have thousands of training labels each. Hiring human annotators is

Amlan Kar, Aayush Prakash, Ming-Yu Liu, Eric Cameracci

Training models to high-end performance requires availability of large labeled datasets, which are expensive to get. The goal of our work is to automatically synthesize labeled datasets that are relevant for a downstream task. We propose Meta-Sim, which learns a generative model of synthetic scenes, and obtain images as well as its corresponding ground-truth

Kyongsik Yun, Kevin Yu, Joseph Osborne, Sarah Eldin

Infrared (IR) images are essential to improve the visibility of dark or camouflaged objects. Object recognition and segmentation based on a neural network using IR images provide more accuracy and insight than color visible images. But the bottleneck is the amount of relevant IR images for training. It is difficult to collect real-world IR images for special

Kyongsik Yun, Luan Nguyen, Tuan Nguyen, Doyoung Kim

It is important to find the target as soon as possible for search and rescue operations. Surveillance camera systems and unmanned aerial vehicles (UAVs) are used to support search and rescue. Automatic object detection is important because a person cannot monitor multiple surveillance screens simultaneously for 24 hours. Also, the object is often too small t

Shifan Zuo, Xuelei Chen

We present a simple and fast method for incoherent dedispersion and fast radio burst (FRB) detection based on the Hough transform, which is widely used for feature extraction in image analysis. The Hough transform maps a point in the time-frequency data to a straight line in the parameter space, and points on the same dispersed $f^{-2}$ curve to a bundle of

Ming Li, Chunyang Ye, Wei Li

Photorealistic style transfer aims to transfer the style of one image to another, but preserves the original structure and detail outline of the content image, which makes the content image still look like a real shot after the style transfer. Although some realistic image styling methods have been proposed, these methods are vulnerable to lose the details o