April 2019 arXiv papers — page 40

Lili Su, Chia-Jung Chang, Nancy Lynch

Winner-Take-All (WTA) refers to the neural operation that selects a (typically small) group of neurons from a large neuron pool. It is conjectured to underlie many of the brain's fundamental computational abilities. However, not much is known about the robustness of a spike-based WTA network to the inherent randomness of the input spike trains. In this w

A. S. Kuraptsev

On the basis of the general quantum microscopic theory we study the process of spontaneous decay of an excited atom in a dense and disordered ensemble of point-like impurity atoms embedded into transparent dielectric and located near a charged perfectly conducting surface. We have analyzed the simultaneous influence of the modified spatial structure of field

Hyenho Lho

We study the quasimap invariants of elliptic and K3 fibrations. Oberdieck and Pixton conjectured that the Gromov-Witten potentials of elliptic fibrations are quasi-modular forms. Analogously, we propose similar conjecture for the quasimap potentials of elliptic fibrations. We also conjecture some finite generation properties of quasimap potentials of K3 fibr

Ayan Banerjee, P. H. R. S. Moraes, R. A. C. Correa, G. Ribeiro

Braneworld models were firstly proposed as a great alternative for the hierarcy problem of particle physics, by allowing gravitons, differently from the other interacting bosons, to propagate through an extradimensional space named bulk. As time passed by the braneworld setup has also shown to be able to provide interesting results when applied to cosmology

Hemant Rathore, Sanjay K. Sahay, Palash Chaturvedi, Mohit Sewak

Android malware have been growing at an exponential pace and becomes a serious threat to mobile users. It appears that most of the anti-malware still relies on the signature-based detection system which is generally slow and often not able to detect advanced obfuscated malware. Hence time-to-time various authors have proposed different machine learning solut

Mariam Moussilli, Abdul Rahman El Falou, Raed Shubair

The last two decades have witnessed an exponential growth and tremendous developments in wireless technologies and systems, and their associated applications. In the recent years following 2006, there has been a great surge in interest in the newly emerging plasmonics nanotechnology because this new device technology provides tremendous synergy between elect

Kevin Karsch, Qing He, Ye Duan

Medical image segmentation has become an essential technique in clinical and research-oriented applications. Because manual segmentation methods are tedious, and fully automatic segmentation lacks the flexibility of human intervention or correction, semi-automatic methods have become the preferred type of medical image segmentation. We present a hybrid, semi

Kevin Karsch, Brian Grinstead, Qing He, Ye Duan

Brain volume calculations are crucial in modern medical research, especially in the study of neurodevelopmental disorders. In this paper, we present an algorithm for calculating two classifications of brain volume, total brain volume (TBV) and intracranial volume (ICV). Our algorithm takes MRI data as input, performs several preprocessing and intermediate st

Jia-Hong Ke, Elaina R. Reese, Emmanuelle A. Marquis, G. Robert Odette

Radiation-enhanced precipitation of Cr-rich α' in irradiated Fe-Cr alloys, which results in hardening and embrittlement, depends on the irradiating particle and the displacement per atom (dpa) rate. Here, we utilize a Cahn-Hilliard phase-field based approach, that includes simple models for nucleation, irradiating particle and rate dependent radiation-en

Hongji Huang, Song Guo, Guan Gui, Zhen Yang

The new demands for high-reliability and ultra-high capacity wireless communication have led to extensive research into 5G communications. However, the current communication systems, which were designed on the basis of conventional communication theories, signficantly restrict further performance improvements and lead to severe limitations. Recently, the eme

Tao Wu, Lichen Wang, Meiliang Gong, Yunjuan Lin

We report the design and development of a dual-functional magnetic nanoparticle platform for potential treatment of H. pylori infection. We show that an ultralow concentration of Mn0.3Fe2.7O4@SiO2 nanoparticles subjected to a moderate AC magnetic field, without bulk heating effect, can deposit heat locally and effectively inhibit H. pylori growth and virulen

Rami Al-Rfou, Dustin Zelle, Bryan Perozzi

Can neural networks learn to compare graphs without feature engineering? In this paper, we show that it is possible to learn representations for graph similarity with neither domain knowledge nor supervision (i.e.\ feature engineering or labeled graphs). We propose Deep Divergence Graph Kernels, an unsupervised method for learning representations over graphs

Sergey Dolgov, Alexander Litvinenko, Dishi Liu

Combination of low-tensor rank techniques and the Fast Fourier transform (FFT) based methods had turned out to be prominent in accelerating various statistical operations such as Kriging, computing conditional covariance, geostatistical optimal design, and others. However, the approximation of a full tensor by its low-rank format can be computationally formi

Benjamin Moseley

This paper considers scheduling on identical machines. The scheduling objective considered in this paper generalizes most scheduling minimization problems. In the problem, there are $n$ jobs and each job $j$ is associated with a monotonically increasing function $g_j$. The goal is to design a schedule that minimizes $\sum_{j \in [n]} g_{j}(C_j)$ where $C_j$

S. Bezuglyi, O. Karpel

This paper is a survey devoted to the study of probability and infinite ergodic invariant measures for aperiodic homeomorphisms of a Cantor set. We focus mostly on the cases when a homeomorphism has either a unique ergodic invariant measure or finitely many such measures (finitely ergodic homeomorphisms). Since every Cantor dynamical system $(X,T)$ can be re

Matthew D. Blair, Yannick Sire, Christopher D. Sogge

We obtain quasimode, eigenfunction and spectral projection bounds for Schrödinger operators, $H_V=-Δ_g+V(x)$, on compact Riemannian manifolds $(M,g)$ of dimension $n\ge2$, which extend the results of the third author~\cite{sogge88} corresponding to the case where $V\equiv 0$. We are able to handle critically singular potentials and consequently assume that $

Ruth Gregory, Andrew Scoins

We introduce a new set of chemical variables for the accelerating black hole. We show how these expressions suggest that conical defects emerging from a black hole can be considered as true hair -- a new charge that the black hole can carry -- and discuss the impact of conical deficits on black hole thermodynamics from this `chemical' perspective. We con

Alessandro Dal Palu'

The paper presents a new model for single channel images low-level interpretation. The image is decomposed into a graph which captures a complete set of structural features. The description allows to accurately identify every edge location and its correct connectivity. The key features of the method are: vector description of the edges, subpixel precision, a

Robert S. Coulter, Stefaan De Winter, Alex Kodess, Felix Lazebnik

We present an example of a result in graph theory that is used to obtain a result in another branch of mathematics. More precisely, we show that the isomorphism of certain directed graphs implies that some trinomials over finite fields have the same number of roots.

Satyasaran Changdar, Snehangshu Bhattacharjee

This paper discusses a new method to solve definite integrals using artificial neural networks. The objective is to build a neural network that would be a novel alternative to pre-established numerical methods and with the help of a learning algorithm, be able to solve definite integrals, by minimising a well constructed error function. The proposed algorith

Jose Chauta, Ricardo Freire

We prove the existence of calibrated uniformly continuous subactions for coercive potentials with bounded variation defined on topologically transitive Markov shifts with countable alphabet through the construction of the Peierls barrier in this context. Also, we characterize the existence of bounded calibrated subactions in the same context.

Maruthi Rohit Ayyagari

Research has provided evidence that associative classification produces more accurate results compared to other classification models. The Classification Based on Association (CBA) is one of the famous Associative Classification algorithms that generates accurate classifiers. However, current association classification algorithms reside external to databases

Yijia Li, Yuanyuan Su, Christine Jones

NGC 4477 is a low-mass lenticular galaxy in the Virgo Cluster, residing at 100\,kpc to the north of M87. Using a total of 116\,ks {\sl Chandra} observations, we study the interplay between its hot ($\sim$0.3\,keV) gas halo and the central supermassive black hole. A possible cool core is indicated by the short cooling time of the gas at the galaxy centre. We

Ugo Dal Lago, Thomas Leventis

We generalise Ehrhard and Regnier's Taylor expansion from pure to probabilistic $λ$-terms through notions of probabilistic resource terms and explicit Taylor expansion. We prove that the Taylor expansion is adequate when seen as a way to give semantics to probabilistic $λ$-terms, and that there is a precise correspondence with probabilistic Böhm trees, a

Quanzhi Ye, Frank J. Masci, Hsing Wen Lin, Bryce Bolin

We describe ZStreak, a semi-real-time pipeline specialized in detecting small, fast-moving near-Earth asteroids (NEAs) that is currently operating on the data from the newly-commissioned Zwicky Transient Facility (ZTF) survey. Based on a prototype originally developed by Waszczak et al. (2017) for the Palomar Transient Factory (PTF), the predecessor of ZTF,

Indranil Mukherjee, Partha Guha

The non-holonomic deformations of non-local integrable systems belonging to the Nonlinear Schrodinger family are studied using the Bi-Hamiltonian formalism as well as the Lax pair method. The non-local equations are first obtained by symmetry reductions of the variables in the corresponding local systems. The bi-Hamiltonian structures of these equations are

Younghun Hong, Chulkwang Kwak, Shohei Nakamura, Changhun Yang

A nonlinear Schrödinger equation (NLS) on a periodic box can be discretized as a discrete nonlinear Schrödinger equation (DNLS) on a periodic cubic lattice, which is a system of finitely many ordinary differential equations. We show that in two spatial dimensions, solutions to the DNLS converge strongly in $L^2$ to those of the NLS as the grid size $h>0$ app

Jialiang Xu, Yun-Bin Zhao

The sparse optimization problems arise in many areas of science and engineering, such as compressed sensing, image processing, statistical and machine learning. The $\ell_{0}$-minimization problem is one of such optimization problems, which is typically used to deal with signal recovery. The $\ell_{1}$-minimization method is one of the plausible approaches f

Ze Yang, Linjun Shou, Ming Gong, Wutao Lin

Deep pre-training and fine-tuning models (like BERT, OpenAI GPT) have demonstrated excellent results in question answering areas. However, due to the sheer amount of model parameters, the inference speed of these models is very slow. How to apply these complex models to real business scenarios becomes a challenging but practical problem. Previous works often

Yingjie Fei, Yudong Chen

We study the statistical performance of semidefinite programming (SDP) relaxations for clustering under random graph models. Under the $\mathbb{Z}_{2}$ Synchronization model, Censored Block Model and Stochastic Block Model, we show that SDP achieves an error rate of the form \[ \exp\Big[-\big(1-o(1)\big)\bar{n} I^* \Big]. \] Here $\bar{n}$ is an appropriate

Cheng Chang, Su Gao

We consider the homeomorphic classification of finite-dimensional continua as well as several related equivalence relations. We show that, when $n \geq 2$, the classification problem of $n$-dimensional continua is strictly more complex than the isomorphism problem of countable graphs. We also obtain results that compare the relative complexity of various equ

Devinder Kumar, Ibrahim Ben-Daya, Kanav Vats, Jeffery Feng

In this study, we propose the leveraging of interpretability for tasks beyond purely the purpose of explainability. In particular, this study puts forward a novel strategy for leveraging gradient-based interpretability in the realm of adversarial examples, where we use insights gained to aid adversarial learning. More specifically, we introduce the concept o

Jeremiah Zhe Liu

We introduce constrained Gaussian process (CGP), a Gaussian process model for random functions that allows easy placement of mathematical constrains (e.g., non-negativity, monotonicity, etc) on its sample functions. CGP comes with closed-form probability density function (PDF), and has the attractive feature that its posterior distributions for regression an

Niels Lörch, Yaxing Zhang, Christoph Bruder, M. I. Dykman

We investigate the quantum transition to a correlated state of coupled oscillators in the regime where they display period tripling in response to a drive at triple the eigenfrequency. Correlations are formed between the discrete oscillation phases of individual oscillators. The evolution toward the ordered state is accompanied by the transient breaking of t

David Polishook, Oded Aharonson

Asteroid pairs had a single progenitor that split due to rotational-fission of a weak, rubble-pile structured body. By constructing shape models of asteroid pairs from multiple-apparition observations and using a lightcurve inversion technique, we mapped the gravitational and rotational accelerations on the surfaces of these asteroids. This allows us to cons

Sungyeon Kim, Minkyo Seo, Ivan Laptev, Minsu Cho

Metric Learning for visual similarity has mostly adopted binary supervision indicating whether a pair of images are of the same class or not. Such a binary indicator covers only a limited subset of image relations, and is not sufficient to represent semantic similarity between images described by continuous and/or structured labels such as object poses, imag

Themis Mitsis, Christos Pelekis, Václav Vlasák

A \emph{chain} in the unit $n$-cube is a set $C\subset [0,1]^n$ such that for every $\mathbf{x}=(x_1,\ldots,x_n)$ and $\mathbf{y}=(y_1,\ldots,y_n)$ in $C$ we either have $x_i\le y_i$ for all $i\in [n]$, or $x_i\ge y_i$ for all $i\in [n]$. We show that the $1$-dimensional Hausdorff measure of a chain in the unit $n$-cube is at most $n$, and that the bound is

Ahmad Yaser Alhaddad, John-John Cabibihan, Ahmad Hayek, Andrea Bonarini

There is a growing interest in social robots to be considered in the therapy of children with autism due to their effectiveness in improving the outcomes. However, children on the spectrum exhibit challenging behaviors that need to be considered when designing robots for them. A child could involuntarily throw a small social robot during meltdown and that co

Prosanta Sarkar, Nilanjan De, Anita Pal

A topological index is a real number which is derived from a network or a graph by mathematically that characterizes the whole of its structural properties. Recently, there are various topological indices that have been introduced in mathematical chemistry to predict the properties of molecular topology. Among, the degree based topological indices such as Za

S. Ayik, B. Yilmaz, O. Yilmaz, A. S. Umar

Employing a quantal diffusion description based on the stochastic mean-field (SMF) approach, we analyze the mass distribution of the primary fragments in the collisions of ${}^{136} \text{Xe}+{}^{208} \text{Pb}$ system at the bombarding energy $E_\text{c.m.} =526$~MeV. This quantal approach provides a good description of the primary fragment distribution wit

Zhengnan Li, Shuai Dong, Jie Guan

Isolated oxygen impurities and fully oxidized structures of four stable two-dimensional (2D) SiS structures are investigated by {\em ab initio} density functional calculations. Binding energies of oxygen impurities for all the four 2D SiS structures are found larger than those for phosphorene, due to the lower electronegativity of Si atoms. The most stable c

Duotong Yang, Hung-Ming Chou, Kyle Thomas, Sergey Kynev

Static Synchronous Compensators (STATCOMs) are being employed by Dominion Energy to control voltage and enhance system stability. Due to the complexity of the control systems, operational modes, and nonlinearities, it is essential to evaluate STATCOMs' behavior to ensure their correct and proper response to dynamic events such as line faults, generator t

Qian Yang, Aaron Steinfeld, John Zimmerman

Clinical decision support tools (DST) promise improved healthcare outcomes by offering data-driven insights. While effective in lab settings, almost all DSTs have failed in practice. Empirical research diagnosed poor contextual fit as the cause. This paper describes the design and field evaluation of a radically new form of DST. It automatically generates sl

K. Abe, R. Akutsu, A. Ali, C. Andreopoulos

We report a measurement of the flux-integrated $ν_μ$ charged-current cross sections on water, hydrocarbon, and iron in the T2K on-axis neutrino beam with a mean neutrino energy of 1.5 GeV. The measured cross sections on water, hydrocarbon, and iron are $σ^{\rm{H_{2}O}}_{\rm{CC}}$ = (0.840$\pm 0.010$(stat.)$^{+0.10}_{-0.08}$(syst.))$\times$10$^{-38}$cm$^2$/nu

Nicholas S. Berry, Ranjan Maitra

The $K$-means algorithm is extended to allow for partitioning of skewed groups. Our algorithm is called TiK-Means and contributes a $K$-means type algorithm that assigns observations to groups while estimating their skewness-transformation parameters. The resulting groups and transformation reveal general-structured clusters that can be explained by invertin

Zoey S. Davidson, Hamed Shahsavan, Amirreza Aghakhani, Yubing Guo

Macroscale robotic systems have demonstrated great capabilities of high speed, precise, and agile functions. However, the ability of soft robots to perform complex tasks, especially in centimeter and millimeter scale, remains limited due to the unavailability of fast, energy-efficient soft actuators that can programmably change shape. Here, we combine desira

Mohammad K. Mardini, Haining Li, Vinicius M. Placco, Sofya Alexeeva

We report on the discovery of five carbon-enhanced metal-poor (CEMP) stars in the metallicity range of $-3.3<$ [Fe/H] $<-2.4$. These stars were selected from the LAMOST DR3 low-resolution (R$ \sim$ 2,000) spectroscopic database as metal-poor candidates and followed-up with high-resolution spectroscopy (R$ \sim$110,000) with the LICK/APF. Stellar parameters a

Sofia-Paraskevi Moschou, Jeremy J. Drake, Ofer Cohen, Julián D. Alvarado-Gómez

Solar CMEs and flares have a statistically well defined relation, with more energetic X-ray flares corresponding to faster and more massive CMEs. How this relation extends to more magnetically active stars is a subject of open research. Here, we study the most probable stellar CME candidates associated with flares captured in the literature to date, all of w

Aleksandar Tošić, Jernej Vičič, Michael Mrissa

Edge computing is a distributed computing paradigm that relies on computational resources of end devices in a network to bring benefits such as low bandwidth utilization, responsiveness, scalability and privacy preservation. Applications range from large scale sensor networks to IoT, and concern multiple domains (agriculture, supply chain, medicine. . . ). H

C. J. Díaz Baso, M. J. Martínez González, A. Asensio Ramos

The determination of the magnetic filed vector in solar filaments is possible by interpreting the Hanle and Zeeman effects in suitable chromospheric spectral lines like those of the He I multiplet at 10830 A. We study the vector magnetic field of an active region filament (NOAA 12087). Spectropolarimetric data of this active region was acquired with the GRIS

Linda S. L. Tan, Aishwarya Bhaskaran, David J. Nott

We develop flexible methods of deriving variational inference for models with complex latent variable structure. By splitting the variables in these models into &#34;global&#34; parameters and &#34;local&#34; latent variables, we define a class of variational approximations that exploit this partitioning and go beyond Gaussian variational approximation. This

Jurgen Mifsud, Carsten van de Bruck

A rigorous constraint analysis on cosmic inflation entails several probes which collectively survey an extensive range of energy scales. We complement the cosmic microwave background data with an updated compilation of the cosmic abundance limits of primordial black holes, with which we infer stringent constraints on the runnings of the scalar spectral index

François-Xavier Coudert, Marie Jeffroy, Alain H. Fuchs, Anne Boutin

We provide a general thermodynamic framework for the understanding of guest-induced structural transitions in hybrid organic-inorganic materials. The method is based on the analysis of experimental adsorption isotherms. It allows the determination of the free energy differences between host structures involved in guest-induced transitions, especially hard to

Yongnan Jia, Tamas Vicsek

We present a general framework for modeling a wide selection of flocking scenarios under free boundary conditions. Several variants have been considered - including examples for the widely observed behavior of hierarchically interacting units. The models we have simulated correspond to classes of various realistic situations. Our primary goal was to investig

Elsa Perrin, Martin Schoen, François-Xavier Coudert, Anne Boutin

Whereas it is experimentally known that the inclusion of nanoparticles in hydrogels can lead to a mechanical reinforcement, a detailed molecular understanding of the adhesion mechanism is still lacking. Here we use coarse-grained molecular dynamics simulations to investigate the nature of the interface between silica surfaces and solvated polymers. We show h

Rolf Güsten, Helmut Wiesemeyer, David Neufeld, Karl M. Menten

During the dawn of chemistry when the temperature of the young Universe had fallen below $\sim$4000 K, the ions of the light elements produced in Big Bang nucleosynthesis recombined in reverse order of their ionization potential. With its higher ionization potentials, He$^{++}$ (54.5 eV) and He$^+$ (24.6 eV) combined first with free electrons to form the fir

Sota Arakawa, Taishi Nakamoto

Shock-wave heating within the solar nebula is one of the leading candidates for the source of chondrule-forming events. Here, we examine the possibility of compound chondrule formation via optically thin shock waves. Several features of compound chondrules indicate that compound chondrules are formed via the collisions of supercooled precursors. We evaluate

Artem Koval, Yao Chen, Takuya Tsugawa, Yuichi Otsuka

The solar radiation focusing effect is related to the specific phenomenon of propagation of the Sun-emitted HF and VHF waves through terrestrial ionosphere. This natural effect is observed with ground-based radio instruments running within 10-200 MHz range, as distinctive patterns - the Spectral Caustics (SCs) - on the solar dynamic spectra. It has been sugg

Weichao Guo, Yongming Wen, Huoxiong Wu, Dongyong Yang

In this paper, we first establish the weighted compactness result for oscillation and variation associated with the truncated commutator of singular integral operators. Moreover, we establish a new $CMO(\mathbb{R}^n)$ characterization via the compactness of oscillation and variation of commutators on weighted Lebesgue spaces.

Wayne Wu, Kaidi Cao, Cheng Li, Chen Qian

Unsupervised image-to-image translation aims at learning a mapping between two visual domains. However, learning a translation across large geometry variations always ends up with failure. In this work, we present a novel disentangle-and-translate framework to tackle the complex objects image-to-image translation task. Instead of learning the mapping on the

Bin-Bin Mao, Maoxin Liu, Wei Wu, Liangsheng Li

An analytical variational method for the ground state of the biased quantum Rabi model in the ultra-strong coupling regime is presented. This analytical variational method can be obtained by a unitary transformation or alternatively by assuming the form of ground state wave function. The key point of the method is to introduce a variational parameter $λ$, wh

Jiang-Jiang Liu, Qibin Hou, Ming-Ming Cheng, Jiashi Feng

We solve the problem of salient object detection by investigating how to expand the role of pooling in convolutional neural networks. Based on the U-shape architecture, we first build a global guidance module (GGM) upon the bottom-up pathway, aiming at providing layers at different feature levels the location information of potential salient objects. We furt

Bin-Bin Mao, Liangsheng Li, Yimin Wang, Wen-Long You

We present an analytical method for the two-qubit quantum Rabi model. While still operating in the frame of the generalized rotating-wave approximation (GRWA), our method further embraces the idea of introducing variational parameters. The optimal value of the variational parameter is determined by minimizing the energy function of the ground state. Comparin

Daesung Kim

The isoperimetric inequalities for the expected lifetime of Brownian motion state that the $L^p$-norms of the expected lifetime in a bounded domain for $1\leq p\leq \infty$ are maximized when the region is a ball with the same volume. In this paper, we prove quantitative improvements of the inequalities. Since the isoperimetric properties hold for a wide cla

Michele Pagani, Sandra Alves

This volume contains a final and revised selection of papers presented at Twelfth Workshop on Developments in Computational Models (DCM 2018) and the Ninth Workshop on Intersection Types and Related Systems (ITRS 2018), held on July 8, 2018 in Oxford, in affiliation with FLOC 2018.

Francesco Messina, Reetika Dudi, Alessandro Nagar, Sebastiano Bernuzzi

We derive a point-mass (nonspinning) frequency-domain TaylorF2 phasing approximant at quasi-5.5 post-Newtonian (PN) accuracy for the gravitational wave from coalescing compact binaries. The new approximant is obtained by Taylor-expanding the effective-one-body (EOB) resummed energy and and angular momentum flux along circular orbits with all the known test-p

Min Li, Hui Xie, Wei Cao, Siqiang Luo

Laser-induced electron tunneling underlies numerous emerging spectroscopic techniques to probe attosecond electron dynamics in atoms and molecules. The improvement of those techniques requires an accurate knowledge of the exit momentum for the tunneling wave packet. Here we demonstrate a photoelectron interferometric scheme to probe the electron momentum lon

Yawen Zhang, Runsheng Wang, Xinyue Zhang, Zherui Zhang

Stochastic computing (SC) presents high error tolerance and low hardware cost, and has great potential in applications such as neural networks and image processing. However, the bitstream generator, which converts a binary number to bitstreams, occupies a large area and energy consumption, thus weakening the superiority of SC. In this paper, we propose a nov

Jathushan Rajasegaran, Vinoj Jayasundara, Sandaru Jayasekara, Hirunima Jayasekara

Capsule Network is a promising concept in deep learning, yet its true potential is not fully realized thus far, providing sub-par performance on several key benchmark datasets with complex data. Drawing intuition from the success achieved by Convolutional Neural Networks (CNNs) by going deeper, we introduce DeepCaps1, a deep capsule network architecture whic

Aihong Yuan, Xuelong Li, Xiaoqiang Lu

It is a big challenge of computer vision to make machine automatically describe the content of an image with a natural language sentence. Previous works have made great progress on this task, but they only use the global or local image feature, which may lose some important subtle or global information of an image. In this paper, we propose a model with 3-ga

Kaushlendra K. Pandey, Abhishek K. Gupta

Ecosystem of a forest suffers from many adverse events such as wild-fire which can occur randomly anywhere in the forest and grows in size with time. This paper aims to analyze performance of a network of randomly deployed wireless sensors for the early detection of these time-critical and time-evolving events in a forest. We consider that the forest lies in

Hiroto Masuda

We construct $G$-corks for any extension $G$ of $\mathbb Z^m$ by any finite subgroup of $\mathrm{SO}(4)$ and weakly equivariant $G$-corks for any extension $G$ of $\mathbb Z^m$ by any finite solvable group. In particular, this is the first example of $G$-corks for an infinite nonabelian group $G$ and answers a question by Tange. The construction is a combina

Zihao Fu, Yankai Lin, Zhiyuan Liu, Wai Lam

During the past few decades, knowledge bases (KBs) have experienced rapid growth. Nevertheless, most KBs still suffer from serious incompletion. Researchers proposed many tasks such as knowledge base completion and relation prediction to help build the representation of KBs. However, there are some issues unsettled towards enriching the KBs. Knowledge base c

Mehdi Rahmati, Roberto Petroccia, Dario Pompili

Achieving high throughput and reliability in underwater acoustic networks for transmitting distributed and large volume of data is a challenging task due to the bandwidth-limited and unpredictable nature of the acoustic channel. In a multi-node network, such as in the Internet of Underwater Things (IoUT), communication link efficiency varies dynamically: if

Haitian Sun, Tania Bedrax-Weiss, William W. Cohen

We consider open-domain queston answering (QA) where answers are drawn from either a corpus, a knowledge base (KB), or a combination of both of these. We focus on a setting in which a corpus is supplemented with a large but incomplete KB, and on questions that require non-trivial (e.g., ``multi-hop&#39;&#39;) reasoning. We describe PullNet, an integrated fra

Ning Jiang, Hui Liu, Yi-Long Luo

In this paper, we first prove the local-in-time existence of the evolutionary model for magnetoelasticity with finite initial energy by employing the nonlinear iterative approach given in \cite{Jiang-Luo-2019-SIAM} to deal with the geometric constraint $M \in \mathbb{S}^{d-1}$ in the Landau-Lifshitz-Gilbert (LLG) equation. Inspired by \cite{Lin-Liu-Zhang-CPA

Kevin Karsch, John C. Hart

While many algorithms exist for tracing various contours for illustrating a meshed object, few algorithms organize these contours into region-bounding closed loops. Tracing closed-loop boundaries on a mesh can be problematic due to switchbacks caused by subtle surface variation, and the organization of these regions into a planar map can lead to many small r

Mark A. Livingston, Zhuming Ai, Kevin Karsch, Gregory O. Gibson

Designing a user interface for military situation awareness presents challenges for managing information in a useful and usable manner. We present an integrated set of functions for the presentation of and interaction with information for a mobile augmented reality application for military applications. Our research has concentrated on four areas. We filter

Jiajun Tong

Inspired by the numerical immersed boundary method, we introduce regularized Stokes immersed boundary problems in two dimensions to describe regularized motion of a 1-D closed elastic string in a 2-D Stokes flow, in which a regularized $δ$-function is used to mollify the flow field and singular forcing. We establish global well-posedness of the regularized p

Harrish Thasarathan, Kamyar Nazeri, Mehran Ebrahimi

Greyscale image colorization for applications in image restoration has seen significant improvements in recent years. Many of these techniques that use learning-based methods struggle to effectively colorize sparse inputs. With the consistent growth of the anime industry, the ability to colorize sparse input such as line art can reduce significant cost and r

Marc Niethammer, Roland Kwitt, Francois-Xavier Vialard

Image registration is a key technique in medical image analysis to estimate deformations between image pairs. A good deformation model is important for high-quality estimates. However, most existing approaches use ad-hoc deformation models chosen for mathematical convenience rather than to capture observed data variation. Recent deep learning approaches lear

Yantao Yang, Roberto Verzicco, Detlef Lohse

We report here some intriguing properties of fingering double diffusive convection turbulence, i.e. convection flow driven simultaneously by an unstable salinity gradient and a stable temperature gradient. Multiple equilibria can be established in such flow for the same control parameters, either by setting different initial scalar distribution or different

Alexandru Ioan Badulescu

This is a survey of the proof of the global Jacquet-Langlands correspondence between GL_n and general inner forms, in characteristic zero. The proof is given after a long introduction recalling in some detail the objects and results involved. The paper is based on the notes of the lectures I gave at the doctoral school in CIRM 2016 (Jean-Morlet Chair) organi

Assyr Abdulle, Grigorios A. Pavliotis, Gilles Vilmart

In this paper we propose a new approach for sampling from probability measures in, possibly, high dimensional spaces. By perturbing the standard overdamped Langevin dynamics by a suitable Stratonovich perturbation that preserves the invariant measure of the original system, we show that accelerated convergence to equilibrium and reduced asymptotic variance c

Eduard Feireisl, Maria Lukacova-Medvidova, Hana Mizerova, Bangwei She

We study convergence of a finite volume scheme for the compressible (barotropic) Navier--Stokes system. First we prove the energy stability and consistency of the scheme and show that the numerical solutions generate a dissipative measure-valued solution of the system. Then by the dissipative measure-valued-strong uniqueness principle, we conclude the conver

Pintu Debnath, Sayan Goswami

Furstenberg and Glasner proved that for an arbitrary k in N, any piecewise syndetic set contains k length arithmetic progression and such collection is also piecewise syndetic in Z: They used algebraic structure of beta N. The above result was extended for arbitrary semigroups by Bergelson and Hindman, again using the structure of Stone-Cech compactification

Mohammad S. Alkousa

This paper is devoted to a new modification of a recently proposed adaptive stochastic mirror descent algorithm for constrained convex optimization problems in the case of several convex functional constraints. Algorithms, standard and its proposed modification, are considered for the type of problems with non-smooth Lipschitz-continuous convex objective fun

William Detmold, Robert G. Edwards, Jozef J. Dudek, Michael Engelhardt

This document is one of a series of whitepapers from the USQCD collaboration. Here, we discuss opportunities for lattice QCD calculations related to the structure and spectroscopy of hadrons and nuclei. An overview of recent lattice calculations of the structure of the proton and other hadrons is presented along with prospects for future extensions. Progress

Ying Hong Tham

Given a tensor category C, one constructs its Drinfeld center Z(C) which is a braided tensor category, having as objects pairs (X, lambda), where X in Obj(C) and lambda is a half-braiding. For a premodular category C, we construct a new category Zel(C) which we call the Elliptic Drinfeld Center, which has objects (X, lambda1, lambda2), where the lambda i's a

Yasha Gindikin, Vitalina Vigdorchik, Vladimir A. Sablikov

We explore the bound electron pairs (BEPs) arising due to the pair spin-orbit interaction (PSOI) in two-dimensional structures with a gate that can allow the BEPs to be manipulated. The gate breaks the in-plane reflection symmetry of the pair Coulomb field and creates a one-particle Rashba spin-orbit interaction. We find that the normal component of the elec

Ali Övgün, İzzet Sakallı, Halil Mutuk

In this paper, we show how the quasinormal modes (QNMs) arise from the perturbations of massive scalar fields propagating in the curved background by using the artificial neural networks. To this end, we architect a special algorithm for the feedforward neural network method (FNNM) to compute the QNMs complying with the certain types of boundary conditions.

Javad Amirian, Jean-Bernard Hayet, Julien Pettre

This paper proposes a novel approach for predicting the motion of pedestrians interacting with others. It uses a Generative Adversarial Network (GAN) to sample plausible predictions for any agent in the scene. As GANs are very susceptible to mode collapsing and dropping, we show that the recently proposed Info-GAN allows dramatic improvements in multi-modal

Masoud Habibidavijani, Barry C. Sanders

Our aim is to formulate continuous-variable quantum secret sharing as a continuous-variable ramp quantum secret sharing protocol, provide a certification procedure for it and explain the criteria for the certification. Here we introduce a technique for certifying continuous-variable ramp quantum secret-sharing schemes in the framework of quantum interactive-

Jianyu Chen, Bodi Yuan, Masayoshi Tomizuka

Urban autonomous driving decision making is challenging due to complex road geometry and multi-agent interactions. Current decision making methods are mostly manually designing the driving policy, which might result in sub-optimal solutions and is expensive to develop, generalize and maintain at scale. On the other hand, with reinforcement learning (RL), a p

Olivia Saa, Julio Michael Stern

Randomization is an integral part of well-designed statistical trials, and is also a required procedure in legal systems, see Marcondes et al. (2019) This paper presents an easy to implement randomization protocol that assures, in a formal mathematical setting, a statistically sound, computationally efficient, cryptographically secure, traceable and auditabl

Jean-Christophe Pain

Analytical expressions of the total number of $J$ levels for three and four fermions in a nuclear $j^n$ shell are provided. The formulas were derived using a combination of sum rules for coefficients of fractional parentage, and "unusual" identities, i.e. which do not contain the weighting factor $(2J + 1)$ involving $6j$ and $9j$ symbols.

DaeJin Kim, Hyegyeong Park, Junkyun Choi

Recently, coding has been a useful technique to mitigate the effect of stragglers in distributed computing. However, coding in this context has been mainly explored under the assumption of homogeneous workers, although the real-world computing clusters can be often composed of heterogeneous workers that have different computing capabilities. The uniform load

Aleksandr Yu. Romanov

This work is devoted to the study of communication subsystem of networks-onchip (NoCs) development with an emphasis on their topologies. The main characteristics of NoC topologies and the routing problem in NoCs with various topologies are considered. It is proposed to use two-dimensional circulant topologies for NoC design, since they have significantly bet

Priyotosh Bandyopadhyay, Eung Jin Chun, Rusa Mandal

Type-X two Higgs doublet model is known to explain the muon $g-2$ anomaly with a relatively light charged Higgs boson at large $\tanβ$. The light charged Higgs boson has been searched in the main $τν$ mode at the colliders. Invoking a scenario of inverse seesaw as the origin of neutrino masses and mixing, the charged Higgs boson can decay additionally to rig

Guokan Shang, Antoine Jean-Pierre Tixier, Michalis Vazirgiannis, Jean-Pierre Lorré

Abstractive community detection is an important spoken language understanding task, whose goal is to group utterances in a conversation according to whether they can be jointly summarized by a common abstractive sentence. This paper provides a novel approach to this task. We first introduce a neural contextual utterance encoder featuring three types of self-