June 2020 arXiv papers — page 16

Akbar Rafiey, Yuichi Yoshida

The problem of maximizing nonnegative monotone submodular functions under a certain constraint has been intensively studied in the last decade, and a wide range of efficient approximation algorithms have been developed for this problem. Many machine learning problems, including data summarization and influence maximization, can be naturally modeled as the pr

G. Sampaio dos Santos, G. Gil da Silveira, M. V. T. Machado

Prompt photon production in hadronic collisions at the RHIC and the LHC energies is investigated within the QCD color dipole approach. Predictions for the nuclear modification factor in $pA$ collisions are evaluated based on parton saturation framework and the results are compared to the experimental measurements as a function of the photon transverse moment

Marco Aurelio Galvani Cunha, Mark O. Robbins

Structures formed by fused filament fabrication are often substantially weaker than those made with conventional techniques, and fail at the welds between successive layers. One factor that may influence strength is flow-induced alignment of deposited material. Recent work suggests that alignment reduces the entanglement density and thus should accelerate we

Minsu Cho, Ameya Joshi, Chinmay Hegde

Deep neural networks are often highly overparameterized, prohibiting their use in compute-limited systems. However, a line of recent works has shown that the size of deep networks can be considerably reduced by identifying a subset of neuron indicators (or mask) that correspond to significant weights prior to training. We demonstrate that an simple iterative

Ozgur Aydogmus, Ali Hakan Tor

To increase the predictive power of a model, one needs to estimate its unknown parameters. Almost all parameter estimation techniques in ordinary differential equation models suffer from either a small convergence region or enormous computational cost. The method of multiple shooting, on the other hand, takes its place in between these two extremes. The comp

Yan Min, Miles Bennett

The causal explanation of image misclassifications is an understudied niche, which can potentially provide valuable insights in model interpretability and increase prediction accuracy. This study trains CIFAR-10 on six modern CNN architectures, including VGG16, ResNet50, GoogLeNet, DenseNet161, MobileNet V2, and Inception V3, and explores the misclassificati

P-A. Maugis

Subgraph counts - in particular the number of occurrences of small shapes such as triangles - characterize properties of random networks, and as a result have seen wide use as network summary statistics. However, subgraphs are typically counted globally, and existing approaches fail to describe vertex-specific characteristics. On the other hand, rooted subgr

Benyamin Ghojogh, Fakhri Karray, Mark Crowley

Human action recognition is one of the important fields of computer vision and machine learning. Although various methods have been proposed for 3D action recognition, some of which are basic and some use deep learning, the need of basic methods based on generalized eigenvalue problem is sensed for action recognition. This need is especially sensed because o

Pavel Tokmakov, Martial Hebert, Cordelia Schmid

This paper addresses the task of unsupervised learning of representations for action recognition in videos. Previous works proposed to utilize future prediction, or other domain-specific objectives to train a network, but achieved only limited success. In contrast, in the relevant field of image representation learning, simpler, discrimination-based methods

Alexandr Kostochka, Mikhail Lavrov, Ruth Luo, Dara Zirlin

A hypergraph $\mathcal H$ is super-pancyclic if for each $A \subseteq V(\mathcal H)$ with $|A| \geq 3$, $\mathcal H$ contains a Berge cycle with base vertex set $A$. We present two natural necessary conditions for a hypergraph to be super-pancyclic, and show that in several classes of hypergraphs these necessary conditions are also sufficient for this. In pa

Stephen Zito

We apply the notion of a full convex subcategory to a wide range of algebras including tilted, quasi-tilted, shod, weakly shod, left and right glued, laura, simply connected, strongly simply connected, left supported, and cluster-tilted. In particular, given an algebra $Λ$ from one of the aforementioned classes, we investigate certain factor algebras $Λ/I$ w

Arpan Das, Hiranmaya Mishra, Ranjita K. Mohapatra

We estimate the axion properties i.e. its mass, topological susceptibility and the self-coupling within the framework of Polyakov loop enhanced Nambu-Jona-Lasinio (PNJL) model at finite temperature and quark chemical potential. PNJL model, where quarks couple simultaneously to the chiral condensate and to a background temporal quantum chromodynamics (QCD) ga

Abdullah Ali, Birhanu Eshete

An adversary who aims to steal a black-box model repeatedly queries the model via a prediction API to learn a function that approximates its decision boundary. Adversarial approximation is non-trivial because of the enormous combinations of model architectures, parameters, and features to explore. In this context, the adversary resorts to a best-effort strat

H. P. M. Melo, J. Henriques, R. Carvalho, T. Verma

Without a vaccine, the fight against the spreading of the coronavirus has focused on maintaining physical distance. To study the impact of such measures on inter-municipality traffic, we analyze a mobile dataset with the daily flow of people in Portugal in March and April 2020. We find that the reduction in inter-municipality traffic depends strongly on its

Giuliano Giacalone, Bjoern Schenke, Chun Shen

We show that the correlation between the elliptic momentum anisotropy, $v_2$, and the average transverse momentum, $[p_T]$, at fixed multiplicity in small system nuclear collisions carries information on the origin of the observed momentum anisotropy. A calculation using a hybrid IP-Glasma+\textsc{Music}+UrQMD model that includes contributions from final sta

Steve Bryson, Jeffrey L. Coughlin, Michelle Kunimoto, Susan E. Mullally

The Kepler DR25 planet candidate catalog was produced using an automated method of planet candidate identification based on various tests. These tests were tuned to obtain a reasonable but arbitrary balance between catalog completeness and reliability. We produce new catalogs with differing balances of completeness and reliability by varying these tests, and

Andreas Schimpe, Frank Diermeyer

Autonomous driving is among the most promising of upcoming traffic safety technologies. Prototypes of autonomous vehicles are already being tested on public streets today. However, while current prototypes prove the feasibility of truly driverless cars, edge cases remain which necessitate falling back on human operators. Teleoperated driving is one solution

Öznur Kulak, A. Turan Gürkanlı

Let $G$ be a locally compact abelian metric group with Haar measure $λ$ and $\hat{G}$ its dual with Haar measure $μ,$ and $λ( G) $ is finite. Assume that$~1<p_{i}<\infty $, $p_{i}^{\prime }=\frac{ p_{i}}{p_{i}-1}$, $( i=1,2,3) $ and $θ\geq 0$. Let $ L^{(p_{i}^{\prime },θ}( G) ,$ $( i=1,2,3) $ be small Lebesgue spaces. A bounded measurable function $m( ξ,η) $

Kevin Kunzmann, Michael J. Grayling, Kim May Lee, David S. Robertson

Sample size derivation is a crucial element of the planning phase of any confirmatory trial. A sample size is typically derived based on constraints on the maximal acceptable type I error rate and a minimal desired power. Here, power depends on the unknown true effect size. In practice, power is typically calculated either for the smallest relevant effect si

Mariya Iv. Trukhanova, Gennady Shipov

Using the hydrodynamical formalism of quantum mechanics for a Schrodinger spinning particle, developed by T. Takabayashi, J. P. Vigier and followers, that involves vortical flows, we propose the new geometrical interpretation of the wave-pilot theory. The spinor wave in this interpretation represents an objectively real field and the evolution of a material

Xinglong Ju, Jay M. Rosenberger, Victoria C. P. Chen, Feng Liu

Multivariate adaptive regression splines (MARS) is a flexible statistical modeling method that has been popular for data mining applications. MARS has also been employed to approxmiate unknown relationships in optimzation for complex systems, including surrogate optimization, dynamic programming, and two-stage stochastic programming. Given the increasing des

H. Susanto, V. R. Tjahjono, A. Hasan, M. F. Kasim

This is a pedagogical paper on estimating the number of people that can be infected by one infectious person during an epidemic outbreak, known as the reproduction number. Knowing the number is crucial for developing policy responses. There are generally two types of such a number, i.e., basic and effective (or instantaneous). While basic reproduction number

Michael Björklund, Yair Hartman, Hanna Oppelmayer

Let $Γ$ be a countable discrete group, $H$ a lcsc totally disconnected group and $ρ: Γ\rightarrow H$ a homomorphism with dense image. We develop a general and explicit technique which provides, for every compact open subgroup $L < H$ and bi-$L$-invariant probability measure $θ$ on $H$, a Furstenberg discretization $τ$ of $θ$ such that the Poisson boundary of

Shen Li, Yanli Zhao, Rohan Varma, Omkar Salpekar

This paper presents the design, implementation, and evaluation of the PyTorch distributed data parallel module. PyTorch is a widely-adopted scientific computing package used in deep learning research and applications. Recent advances in deep learning argue for the value of large datasets and large models, which necessitates the ability to scale out model tra

Mustafa Muratov, Ben-Zion Rubshtein

In this paper we consider equimeasurable symmetric(rearrangement invariant) spaces $\mathbf{E}_1 = \mathbf{E}_1(Ω_1,\mathcal{F}_1,μ_1)$ and $\mathbf{E}_2 = \mathbf{E}_2(Ω_2,\mathcal{F}_2,μ_2)$ on a measure spaces $(Ω_1, \mathcal{F}_1,μ_1)$ and $(Ω_2,\mathcal{F}_2,μ_2)$ with finite or infinite $σ$-finite non-atomic measures $μ_1$ and $μ_2$. If $\mathbf{E}_1(Ω

J. H. Adler, T. Benson, E. C. Cyr, P. E. Farrell

The magnetohydrodynamics (MHD) equations model a wide range of plasma physics applications and are characterized by a nonlinear system of partial differential equations that strongly couples a charged fluid with the evolution of electromagnetic fields. After discretization and linearization, the resulting system of equations is generally difficult to solve d

Kevin Eckenhoff, Patrick Geneva, Guoquan Huang

As cameras and inertial sensors are becoming ubiquitous in mobile devices and robots, it holds great potential to design visual-inertial navigation systems (VINS) for efficient versatile 3D motion tracking which utilize any (multiple) available cameras and inertial measurement units (IMUs) and are resilient to sensor failures or measurement depletion. To thi

Nadine Gächter, Fabian Könemann, Masiar Sistani, Maximilian G. Bartmann

The thermoelectric properties of a nanoscale germanium segment connected by aluminium nanowires are studied using scanning thermal microscopy. The germanium segment of 168\,nm length features atomically sharp interfaces to the aluminium wires and is surrounded by an Al$_2$O$_3$ shell. The temperature distribution along the self-heated nanowire is measured as

Dr Ing Hongguang Yang, Dr ret nat Weidong Yang

This paper gives an extended model of the atomic nucleus - we call it the YY model, which allows a new description for strong forces from the well-known Standard Model. The forces that hold the nucleus together (protons and neutrons) can be expressed in a new way. Based on the YY model, more structural description details for an atomic nucleus will be possib

Fernando Pérez-García, Roman Rodionov, Ali Alim-Marvasti, Rachel Sparks

Resective surgery may be curative for drug-resistant focal epilepsy, but only 40% to 70% of patients achieve seizure freedom after surgery. Retrospective quantitative analysis could elucidate patterns in resected structures and patient outcomes to improve resective surgery. However, the resection cavity must first be segmented on the postoperative MR image.

Dov Fields, Abdelali Sajia, János A. Bergou

Quantum retrodiction is a time-symmetric approach to quantum mechanics with applications in a number of important problems. One of the major challenges to its more widespread applicability is the restriction of its symmetric formalism to unbiased sources. The main result of this paper is to develop a general theory yielding a symmetric formalism for arbitrar

Ibrahim El Shar, Daniel R. Jiang

We introduce the lookahead-bounded Q-learning (LBQL) algorithm, a new, provably convergent variant of Q-learning that seeks to improve the performance of standard Q-learning in stochastic environments through the use of ``lookahead&#39;&#39; upper and lower bounds. To do this, LBQL employs previously collected experience and each iteration&#39;s state-action

Yuanlu Bai, Zhiyuan Huang, Henry Lam

We study a methodology to tackle the NASA Langley Uncertainty Quantification Challenge problem, based on an integration of robust optimization, more specifically a recent line of research known as distributionally robust optimization, and importance sampling in Monte Carlo simulation. The main computation machinery in this integrated methodology boils down t

Rumit Kumar, Mahathi Bhargavapuri, Aditya M. Deshpande, Siddharth Sridhar

In this paper, we present an autonomous flight controller for a quadcopter with thrust vectoring capabilities. This UAV falls in the category of multirotors with tilt-motion enabled rotors. Since the vehicle considered is over-actuated in nature, the dynamics and control allocation have to be analysed carefully. Moreover, the possibility of hovering at large

Nader Sadegh, Hassan Almubarak

The paper develops an optimal regulator for a general class of multi-input affine nonlinear systems minimizing a nonlinear cost functional with infinite horizon. The cost functional is general enough to enforce saturation limits on the control input if desired. An efficient algorithm utilizing tensor algebra is employed to compute the tensor coefficients of

Lawrence Reeves, Peter Scott, Gadde A. Swarup

We prove the analogue of Johannson&#39;s Deformation Theorem for PD3 pairs.

H. E. A. Campbell, David L. Wehlau

We begin by considering faithful matrix representations of elementary abelian groups in prime characteristic. The representations considered are seen to be determined up to change of bases by a single number. Studying this number leads to a new family of polynomials which exhibit a number of special properties. These polynomials satisfy a three term recursio

Jeffrey Svajlenko, Chanchal K. Roy

There are a great many clone detection tools proposed in the literature. In this paper, we investigate the state of clone detection tool evaluation. We begin by surveying the clone detection benchmarks, and performing a multi-faceted evaluation and comparison of their features and capabilities. We then survey the existing clone detection tool and technique p

Pietro Barbiero, Giovanni Squillero, Alberto Tonda

As machine learning becomes more and more available to the general public, theoretical questions are turning into pressing practical issues. Possibly, one of the most relevant concerns is the assessment of our confidence in trusting machine learning predictions. In many real-world cases, it is of utmost importance to estimate the capabilities of a machine le

Beomjun Choi, Jianhui Gao, Robert Haslhofer, Daniel Sigal

We establish effective existence and uniqueness for the heat flow on time-dependent Riemannian manifolds, under minimal assumptions tailored towards the study of Ricci flow through singularities. The main point is that our estimates only depend on an upper bound for the logarithmic derivative of the volume measure. In particular, our estimates hold for any R

Wanqing Cheng John Ryan

The $Π$-operator, also known as Ahlfors-Beurling transform, plays an important role in solving the existence of locally quasiconformal solutions of Beltrami equations. In this paper, we first construct the $Π$-operator on a general Clifford-Hilbert module. This $Π$-operator is also an $L^2$ isometry. Further, it can also be used for solving certain Beltrami

Andreia Chapouto

We study the well-posedness of the complex-valued modified Korteweg-de Vries equation (mKdV) on the circle at low regularity. In our previous work (2019), we introduced the second renormalized mKdV equation, based on the conservation of momentum, which we proposed as the correct model to study the complex-valued mKdV outside of $H^\frac12(\mathbb{T})$. Here,

Jared Coleman, Evangelos Kranakis, Oscar Morales-Ponce, Jaroslav Opatrny

In the pattern formation problem, robots in a system must self-coordinate to form a given pattern, regardless of translation, rotation, uniform-scaling, and/or reflection. In other words, a valid final configuration of the system is a formation that is \textit{similar} to the desired pattern. While there has been no shortage of research in the pattern format

Anna Kostianko, Xinhua Li, Chunyou Sun, Sergey Zelik

The paper gives a comprehensive study of inertial manifolds for semilinear parabolic equations and their smoothness using the spatial averaging method suggested by G. Sell and J. Mallet-Paret. We present a universal approach which covers the most part of known results obtained via this method as well as gives a number of new ones. Among our applications are

Tim Hoheisel, Blanca Pablos, Aram-Alexandre Pooladian, Alexandra Schwartz

Mathematical programs with vanishing constraints (MPVCs) are a class of nonlinear optimization problems with applications to various engineering problems such as truss topology design and robot motion planning. MPVCs are difficult problems from both a theoretical and numerical perspective: the combinatorial nature of the vanishing constraints often prevents

Chantal David, Alexandra Florea, Matilde Lalin

We prove that there is a positive proportion of $L$-functions associated to cubic characters over $\mathbb{F}_q[T]$ that do not vanish at the critical point $s=1/2$. This is achieved by computing the first mollified moment using techniques previously developed by the authors in their work on the first moment of cubic $L$-functions, and by obtaining a sharp u

F. Millour, E. Lagadec, M. Montargès, P. Kervella

$η$~Car is one of the most massive stars in the Galaxy. It underwent a massive eruption in the 19th century, which produced the impressive bipolar Homunculus nebula now surrounding it. The central star is an eccentric binary with a period of 5.54\,years. Although the companion has not been detected directly, it causes time-variable ionization and colliding-w

Keyvan Safaei Baghbaderani, Mohammadreza Nematollahi, Parisa Bayatimalayeri, Hediyeh Dabbaghi

Two unique behaviors of superelasticity and shape memory effect have made shape memory alloy such as NiTi, an interesting alloy for different applications. Recently, additive manufacturing (AM) as a powerful tool for fabricating NiTi has become of interest to make complex geometries. Selective laser melting (SLM) is an AM method that not only provides flexib

Ariel Norambuena, Andrés Franco, Raúl Coto

Magnetic systems can be described by the classical Landau-Lifshitz (LL) equation or the fully quantum open Heisenberg model. Using the Lindblad master equation and the mean-field approximation, we demonstrate that the open Heisenberg model is reduced to a generalized LL equation. The open dynamic is modeled using spin-boson interactions with a common bosonic

Pavel A. Andreev

If we study the quantum effects in plasmas in terms of traditional hydrodynamics via the continuity and Euler equations we find the quantum Bohm potential and the force of spin-spin interaction. However, if we extend the set hydrodynamic equations beyond the 13-moments approximation, and include the third rank tensor evolution equation along with the pressur

Rambod Mojgani, Maciej Balajewicz

We design a physics-aware auto-encoder to specifically reduce the dimensionality of solutions arising from convection-dominated nonlinear physical systems. Although existing nonlinear manifold learning methods seem to be compelling tools to reduce the dimensionality of data characterized by a large Kolmogorov n-width, they typically lack a straightforward ma

Zhu-Xiong Ye, Li-Yang Xie, Zhen Guo, Xiao-Bin Ma

We report on the attainment of a degenerate Fermi gas of $\rm^{6}Li$ in contact with a Bose-Einstein condensate (BEC) of $^{84}$Sr. A degeneracy of $T/T_F=0.33(3)$ is observed with $1.6\times10^5$ $^{6}$Li atoms in the two lowest energy hyperfine states together with an almost pure BEC of $3.1\times10^5$ $^{84}$Sr atoms. The elastic s-wave scattering length

Pavlo Gavrylenko, Andrei Marshakov, Artem Stoyan

We study the relation of irregular conformal blocks with the Painlevé III$_3$ equation. The functional representation for the quasiclassical irregular block is shown to be consistent with the BPZ equations of conformal field theory and the Hamilton-Jacobi approach to Painlevé III$_3$. It leads immediately to a limiting case of the blow-up equations for dual

Alejandro Flores-Velazco

The nearest-neighbor rule is a well-known classification technique that, given a training set P of labeled points, classifies any unlabeled query point with the label of its closest point in P. The nearest-neighbor condensation problem aims to reduce the training set without harming the accuracy of the nearest-neighbor rule. FCNN is the most popular algorith

Erik A. Petigura

Recently, several groups have resolved a gap that bifurcates planets between the size of Earth and Neptune into two populations. The location and depth of this feature is an important signature of the physical processes that form and sculpt planets. In particular, planets residing in the radius gap are valuable probes of these processes as they may be underg

Hrishav Bakul Barua, Chayan Sarkar, Achanna Anil Kumar, Arpan Pal

Telepresence robots are used in various forms in various use-cases that helps to avoid physical human presence at the scene of action. In this work, we focus on a telepresence robot that can be used to attend a meeting remotely with a group of people. Unlike a one-to-one meeting, participants in a group meeting can be located at a different part of the room,

Saurav Roy, Arkka Bhattacharyya, Sriram Krishnamoorthy

This work presents the electrostatic analysis of a novel Ga$_2$O$_3$ vertical Schottky diode with three different guard ring configurations to reduce the peak electric field at the metal edges. Highly doped p-type GaN, p-type nonpolar AlGaN and polarization doped graded p-AlGaN are simulated and analyzed as the guard ring material, which forms a heterojuncti

Siyan Liu, Nikolay Borodinov, Lukas Vlcek, Dan Lu

Atomic-scale materials synthesis via layer deposition techniques present a unique opportunity to control material structures and yield systems that display unique functional properties that cannot be stabilized using traditional bulk synthetic routes. However, the deposition process itself presents a large, multidimensional space that is traditionally optimi

Daniel J. Tait, Theodoros Damoulas

Specifying a governing physical model in the presence of missing physics and recovering its parameters are two intertwined and fundamental problems in science. Modern machine learning allows one to circumvent these, via emulators and surrogates, but in doing so disregards prior knowledge and physical laws that are especially important for small data regimes,

Timothy D. Eales, Igor P. Marko, Alfred R. Adams, Jerry R. Meyer

From a systematic study of the threshold current density as a function of temperature and hydrostatic pressure, in conjunction with theoretical analysis of the gain and threshold carrier density, we have determined the wavelength dependence of the Auger recombination coefficients in InGaAsSb/GaSb quantum well lasers emitting in the 1.7-3.2 $μ$m wavelength ra

Richard C. Brower, George T. Fleming, Andrew D. Gasbarro, Dean Howarth

The quantum extension of classical finite elements, referred to as quantum finite elements ({\bf QFE})~\cite{Brower:2018szu,Brower:2016vsl}, is applied to the radial quantization of 3d $ϕ^4$ theory on a simplicial lattice for the $\mathbb R \times \mathbb S^2$ manifold. Explicit counter terms to cancel the one- and two-loop ultraviolet defects are implemente

Muhammad Emzir, Sari Lasanen, Zenith Purisha, Lassi Roininen

In this article, we study Bayesian inverse problems with multi-layered Gaussian priors. We first describe the conditionally Gaussian layers in terms of a system of stochastic partial differential equations. We build the computational inference method using a finite-dimensional Galerkin method. We show that the proposed approximation has a convergence-in-prob

Xian Gao

We investigate the ghostfree scalar-tensor theory with a timelike scalar field, with derivatives of the scalar field up to the third order and with the Riemann tensor up to the quadratic order. We build two types of linear spaces. One is the set of linearly independent generally covariant scalar-tensor monomials, the other is the set of linearly independent

Yunfei Song, Tian Liu, Tongquan Wei, Xiangfeng Wang

Along with the proliferation of Artificial Intelligence (AI) and Internet of Things (IoT) techniques, various kinds of adversarial attacks are increasingly emerging to fool Deep Neural Networks (DNNs) used by Industrial IoT (IIoT) applications. Due to biased training data or vulnerable underlying models, imperceptible modifications on inputs made by adversar

Jialin Wu, Liyan Chen, Raymond J. Mooney

Most recent state-of-the-art Visual Question Answering (VQA) systems are opaque black boxes that are only trained to fit the answer distribution given the question and visual content. As a result, these systems frequently take shortcuts, focusing on simple visual concepts or question priors. This phenomenon becomes more problematic as the questions become co

Dipen Sahu, Sheng-Yuan Liu, Ankan Das, Prasanta Gorai

Methyl carbamate CH$_3$OC(O)NH$_2$ is an isomer of glycine. Quantum chemical analyses show that methyl carbamate is more stable isomer than glycine. Because of this, there could be a higher chance for methyl carbamte to exist in the interstellar medium as compared to glycine. Despite immense searches, till now glycine has not been detected in the ISM, theref

Daniel J. Tait

Near-term prediction of the structured spatio-temporal processes driving our climate is of profound importance to the safety and well-being of millions, but the prounced nonlinear convection of these processes make a complete mechanistic description even of the short-term dynamics challenging. However, convective transport provides not only a principled phys

Bjorn Johansson

The effect of masking the general population on a COVID-19 epidemic is estimated by computer simulation using two separate state-of-the-art web-based softwares, one of them calibrated for the SARS-CoV-2 virus. The questions addressed are these: 1. Can mask use by the general population limit the spread of SARS-CoV-2 in a country? 2. What types of masks exist

T. F. M. Sirqueira, M. A. Miguel, H. L. O. Dalpra, M. A. P. Araujo

The experimental evaluation of the methods and concepts covered in software engineering has been increasingly valued. This value indicates the constant search for new forms of assessment and validation of the results obtained in Software Engineering research. Results are validated in studies through evaluations, which in turn become increasingly stringent. A

A. A. Makarov, V. I. Yudson

We suggest a regular method of achieving an extremely long lifetime of a collective singly excited state in a generic small-size ensemble of N identical atoms. The decay rate Γ_N of such a `superdark&#39; state can be as small as Γ_N \propto Γ(r/λ)^{2(N-1)} (Γis the radiative decay rate of an individual atom, r and λare the system size and the wavelength of

Stefan Aeby, Geoffroy J. Aubry, Nicolas Muller, Frank Scheffold

Photonic crystals with a sufficiently high refractive index contrast display partial or full band gaps. However, imperfections in the metamaterial cause light scattering and extinction of the interfering propagating waves. Positive as well as negative defect volumes may contribute to this kind of optical perturbation. In this study, we fabricate and characte

Brian Liu, Xianchao Xu, Yu Zhang

Deep learning based methods have been dominating the text recognition tasks in different and multilingual scenarios. The offline handwritten Chinese text recognition (HCTR) is one of the most challenging tasks because it involves thousands of characters, variant writing styles and complex data collection process. Recently, the recurrent-free architectures fo

Rui Gong, Dengxin Dai, Yuhua Chen, Wen Li

Image-to-image translation is to map images from a given \emph{style} to another given \emph{style}. While exceptionally successful, current methods assume the availability of training images in both source and target domains, which does not always hold in practice. Inspired by humans&#39; reasoning capability of analogy, we propose analogical image translat

Zhihao Liu, Hui Yin, Yang Mi, Mengyang Pu

Shadow removal can significantly improve the image visual quality and has many applications in computer vision. Deep learning methods based on CNNs have become the most effective approach for shadow removal by training on either paired data, where both the shadow and underlying shadow-free versions of an image are known, or unpaired data, where shadow and sh

Rongxing Xu, Xuding Zhu

A graph $G$ is called $3$-choice critical if $G$ is not $2$-choosable but any proper subgraph is $2$-choosable. A characterization of $3$-choice critical graphs was given by Voigt in [On list Colourings and Choosability of Graphs, Habilitationsschrift, Tu Ilmenau(1998)]. Voigt conjectured that if $G$ is a bipartite $3$-choice critical graph, then $G$ is $(4m

Shai Haran

For a commutative ring $A$, we have the category of (bounded-below) chain complexes of $A$-modules $Ch_{+}(A\mymod)$, a closed symmetric monoidal category with a compatible stable Quillen model structure. The associated homotopy category is the derived category $\mathbbm{D}(A\mymod)$, where one inverts all the quasi-isomorphisms, and it has the good descript

Yanki Lekili, David Treumann

This paper discusses homological mirror symmetry for the Fargues-Fontaine curve of equal characteristic.

Askar Ali, Khalid Saifullah

We consider a model where massive static spherically symmetric black hole, in the presence of power-Yang-Mills source, is surrounded by a dark fluid with non-linear equation of state. In this set up we construct a new class of magnetized Lovelock black hole solutions of the gravitational field equations. In particular, we work out the metric functions in bot

Joel Merker, Pawel Nurowski

We study invariant properties of $5$-dimensional para-CR structures whose Levi form is degenerate in precisely one direction and which are $2$-nondegenerate. We realize that two, out of three, primary (basic) para-CR invariants of such structures are the classical differential invariants known to Monge (1810) and to Wuenschmann (1905) \[ M(G) := 40G_{ppp}^3-

Mohamed Hebiri, Johannes Lederer

Sparsity has become popular in machine learning, because it can save computational resources, facilitate interpretations, and prevent overfitting. In this paper, we discuss sparsity in the framework of neural networks. In particular, we formulate a new notion of sparsity that concerns the networks&#39; layers and, therefore, aligns particularly well with the

Yu Ge, Hyowon Kim, Fuxi Wen, Lennart Svensson

5G millimeter wave (mmWave) signals can be used to jointly localize the receiver and map the propagation environment in vehicular networks, which is a typical simultaneous localization and mapping (SLAM) problem. Mapping the environment is challenging, due to measurements comprising both specular and diffuse multipath components, and diffuse multipath is usu

Vanessa Braglia, Alena Kopaničáková, Rolf Krause

We propose a novel training method based on nonlinear multilevel minimization techniques, commonly used for solving discretized large scale partial differential equations. Our multilevel training method constructs a multilevel hierarchy by reducing the number of samples. The training of the original model is then enhanced by internally training surrogate mod

Zoubir Hemame, Mokhtar Falek, Mustafa Moumni

We study the effects of Snyder-de Sitter commutation relations on relativistic bosons by solving analytically in the momentum space representation the Klein-Gordon oscillator in arbitrary dimensions. The exact bound states spectrum and the corresponding momentum space wave functions are obtained using Gegenbauer polynomials in one dimension space and Jacobi

Daniel Dörfler, Andreas Löhne, Christopher Schneider, Benjamin Weißing

We present an algorithm for approximately solving bounded convex vector optimization problems. The algorithm provides both an outer and an inner polyhedral approximation of the upper image. It is a modification of the primal algorithm presented by Löhne, Rudloff, and Ulus in 2014. There, vertices of an already known outer approximation are successively cut o

Wenxuan Zhang, Yang Deng, Wai Lam

Many E-commerce sites now offer product-specific question answering platforms for users to communicate with each other by posting and answering questions during online shopping. However, the multiple answers provided by ordinary users usually vary diversely in their qualities and thus need to be appropriately ranked for each question to improve user satisfac

A. Nezih Kasim

For the next wireless communication systems, the major challenges are to provide ubiquitous wireless access abilities and maintain the quality of service and seamless mobility management for mobile communication devices in heterogeneous networks. Due to the rapid growth of mobile users, this demand becomes more challenging where the users always require seam

Mourad Baazouzi, Mustafa Moumni, Mokhtar Falek

We study analytically a system made up of a quantum ring with a dipolar impurity and under the effect of an Aharonov-Bohm field. We calculate the exact values of the energies and we also get the exact expressions of the wave functions.

Petr Jizba, Lesław Rachwał, Stefano G. Giaccari, Jaroslav Kňap

With the help of a functional renormalization group, we study the dynamical breakdown of scale invariance in quantum Weyl gravity by starting from the UV fixed point that we assume to be Gaussian. To this end, we resort to two classes of Bach-flat backgrounds, namely maximally symmetric spacetimes and Ricci-flat backgrounds in the improved one-loop scheme. W

Karim Sonbol, Öznur Özkasap, Ibrahim Al-Oqily, Moayad Aloqaily

Edge computing moves the computation closer to the data and the data closer to the user to overcome the high latency communication of cloud computing. Storage at the edge allows data access with high speeds that enable latency-sensitive applications in areas such as autonomous driving and smart grid. However, several distributed services are typically design

Dan Shafir, David A. Kessler

We study Saffman-Taylor flow in the presence of intermediate noise numerically by using both a boundary-integral approach as well as the Kadanoff-Liang modified Diffusion-Limited Aggregation model that incorporates surface tension and reduced noise. For little to no noise, both models result reproduce the well-known Saffman-Taylor finger. We compare both mod

Anna Talgat, Mustafa A. Kishk, Mohamed-Slim Alouini

This letter studies the performance of a low-earth orbit (LEO) satellite communication system where the locations of the LEO satellites are modeled as a binomial point process (BPP) on a spherical surface. In particular, we study the user coverage probability for a scenario where satellite gateways (GWs) are deployed on the ground to act as a relay between t

Xiaoguang Li, Peng Fu, Hongxia Yin, ZhenChang Wang

Computed Tomography (CT) of the temporal bone has become an important method for diagnosing ear diseases. Due to the different posture of the subject and the settings of CT scanners, the CT image of the human temporal bone should be geometrically calibrated to ensure the symmetry of the bilateral anatomical structure. Manual calibration is a time-consuming t

F Riedel, J Golda, J Held, H Davies

Atmospheric pressure plasmas have been ground-breaking for plasma science and technologies, due to their significant application potential in many fields, including medicinal, biological, and environmental applications. This is predominantly due to their efficient production and delivery of chemically reactive species under ambient conditions. One of the cha

Sevinj Yolchuyeva, Géza Németh, Bálint Gyires-Tóth

Self-attention networks (SAN) have shown promising performance in various Natural Language Processing (NLP) scenarios, especially in machine translation. One of the main points of SANs is the strength of capturing long-range and multi-scale dependencies from the data. In this paper, we present a novel intent detection system which is based on a self-attentio

Eduard Eiben, William Lochet

The line graph of a graph $G$ is the graph $L(G)$ whose vertex set is the edge set of $G$ and there is an edge between $e,f\in E(G)$ if $e$ and $f$ share an endpoint in $G$. A graph is called line graph if it is a line graph of some graph. We study the Line-Graph-Edge Deletion problem, which asks whether we can delete at most $k$ edges from the input graph $

A. Mazzolari, M. Romagnoni, E. Bagli, L. Bandiera

Experimental results and simulation models show that crystals might play a relevant role for the development of new generations of high-energy and high-intensity particle accelerators and might disclose innovative possibilities at existing ones. In this paper we describe the most advanced manufacturing techniques of crystals suitable for operations at ultra-

Mark Pankov, Krzysztof Petelczyc, Mariusz Zynel

Two distinct projections of finite rank $m$ are adjacent if their difference is an operator of rank two or, equivalently, the intersection of their images is $(m-1)$-dimensional. We extend this adjacency relation on other conjugacy classes of finite-rank self-adjoint operators which leads to a natural generalization of Grassmann graphs. Let ${\mathcal C}$ be

Md Firoz Ali, Vasudevarao Allu, Hiroshi Yanagihara

For $0<λ\le 1$, let $\mathcal{U}(λ)$ be the class analytic functions $f(z)= z+\sum_{n=2}^{\infty}a_n z^n$ in the unit disk $\mathbb{D}$ satisfying $|f&#39;(z)(z/f(z))^2-1|<λ$ and $\mathcal{U}:=\mathcal{U}(1)$. In the present article, we prove that the class $\mathcal{U}$ is contained in the closed convex hull of the class of starlike functions and using this

Md Firoz Ali, Vasudevarao Allu, Hiroshi Yanagihara

We continue our study on variability regions in \cite{Ali-Vasudevarao-Yanagihara-2018}, where the authors determined the region of variability $V_Ω^j (z_0, c ) = \{ \int_0^{z_0} z^{j}(g(z)-g(0))\, d z : g({\mathbb D}) \subset Ω, \; (P^{-1} \circ g) (z) = c_0 +c_1z + \cdots + c_n z^n + \cdots \}$ for each fixed $z_0 \in {\mathbb D}$, $j=-1,0,1,2, \ldots$ and

D. I. Novikov, S. V. Pilipenko, M. de Petris, G. Luzzi

We consider the Stokes parameters&#39; frequency spectral distortions arising due to Compton scattering of the anisotropic cosmic microwave background (CMB) radiation, the Sunyaev-Zel&#39; dovich effect (SZ), towards clusters of galaxies. We single out a very special type of such distortions and find simple analytical formulas for them. We show that this kin