February 2019 arXiv papers — page 61

Danijela Damjanovic, Amie Wilkinson, Disheng Xu

We discover a rigidity phenomenon within the volume-preserving partially hyperbolic diffeomorphisms with $1$-dimensional center. In particular, for smooth, ergodic perturbations of certain algebraic systems -- including the discretized geodesic flows over hyperbolic manifolds and certain toral automorphisms with simple spectrum and exactly one eigenvalue on

Sharmila Karumuri, Rohit Tripathy, Ilias Bilionis, Jitesh Panchal

Stochastic partial differential equations (SPDEs) are ubiquitous in engineering and computational sciences. The stochasticity arises as a consequence of uncertainty in input parameters, constitutive relations, initial/boundary conditions, etc. Because of these functional uncertainties, the stochastic parameter space is often high-dimensional, requiring hundr

Shaowu Pan, Karthik Duraisamy

This work addresses fundamental issues related to the structure and conditioning of linear time-delayed models of non-linear dynamics on an attractor. While this approach has been well-studied in the asymptotic sense (e.g. for infinite number of delays), the non-asymptotic setting is not well-understood. First, we show that the minimal time-delays required f

Sobhan Moosavi, Mohammad Hossein Samavatian, Arnab Nandi, Srinivasan Parthasarathy

Pattern discovery in geo-spatiotemporal data (such as traffic and weather data) is about finding patterns of collocation, co-occurrence, cascading, or cause and effect between geospatial entities. Using simplistic definitions of spatiotemporal neighborhood (a common characteristic of the existing general-purpose frameworks) is not semantically representative

Jules Chouquet, Lionel Vaux Auclair

We examine some combinatorial properties of parallel cut elimination in multiplicative linear logic (MLL) proof nets. We show that, provided we impose a constraint on some paths, we can bound the size of all the nets satisfying this constraint and reducing to a fixed resultant net. This result gives a sufficient condition for an infinite weighted sum of nets

Kwokwai Chan, Cheol-Hyun Cho, Siu-Cheong Lau, Naichung Conan Leung

We compute orbi-disk invariants of compact Gorenstein semi-Fano toric orbifolds by extending the method used for toric Calabi-Yau orbifolds. As a consequence the orbi-disc potential is analytic over complex numbers.

Masaru Ikehata

We consider an inverse boundary value problem for the equation $\nabla\cdot(\sigma-i\omega\epsilon)\nabla u=0$ in a given bounded domain $\Omega$ at a fixed $\omega>0$. $\sigma$ and $\epsilon$ denote the conductivity and permittivity of the material forming $\Omega$, respectively. We give some formulae for extracting information about the location of the dis

Huanyao Wen

We consider the Dirichlet problem for a compressible two-fluid model in three dimensions, and obtain the global existence of weak solution with large initial data and independent adiabatic constants \Gamma,\gamma>=9/5. The pressure functions are of two components solving the continuity equations. Two typical cases for the pressure are considered, which are m

Maithra Raghu, Chiyuan Zhang, Jon Kleinberg, Samy Bengio

Transfer learning from natural image datasets, particularly ImageNet, using standard large models and corresponding pretrained weights has become a de-facto method for deep learning applications to medical imaging. However, there are fundamental differences in data sizes, features and task specifications between natural image classification and the target me

Shuang Qiu, David Gesbert, Da Chen, Tao Jiang

In this paper, a novel covariance-based channel feedback mechanism is investigated for frequency division duplexing (FDD) massive multi-input multi-output (MIMO) systems. The concept capitalizes on the notion of user statistical separability which was hinted in several prior works in the massive antenna regime but not fully exploited so far. We here propose

Vedhas Pandit, Björn Schuller

We derive the mapping between two of the most pervasive utility functions, the mean square error ($MSE$) and the concordance correlation coefficient (CCC, $\rho_c$). Despite its drawbacks, $MSE$ is one of the most popular performance metrics (and a loss function); along with lately $\rho_c$ in many of the sequence prediction challenges. Despite the ever-grow

Saeed Ranjbar Alvar, Ivan V. Bajić

A promising way to deploy Artificial Intelligence (AI)-based services on mobile devices is to run a part of the AI model (a deep neural network) on the mobile itself, and the rest in the cloud. This is sometimes referred to as collaborative intelligence. In this framework, intermediate features from the deep network need to be transmitted to the cloud for fu

Anqi Li, Mustafa Mukadam, Magnus Egerstedt, Byron Boots

In many applications, multi-robot systems are required to achieve multiple objectives. For these multi-objective tasks, it is oftentimes hard to design a single control policy that fulfills all the objectives simultaneously. In this paper, we focus on multi-objective tasks that can be decomposed into a set of simple subtasks. Controllers for these subtasks a

Behnoosh Parsa, Ekta U. Samani, Rose Hendrix, Cameron Devine

Automated real-time prediction of the ergonomic risks of manipulating objects is a key unsolved challenge in developing effective human-robot collaboration systems for logistics and manufacturing applications. We present a foundational paradigm to address this challenge by formulating the problem as one of action segmentation from RGB-D camera videos. Spatia

Davide Gaiotto, Tadashi Okazaki

We compute supersymmetric indices which count local operators at certain half-BPS interfaces and quarter-BPS junctions of interfaces in four-dimensional $\mathcal{N}=4$ Super Yang-Mills theory. We use the indices as very stringent tests of a variety of string theory-inspired conjectures about the action of S-duality on such defects.

Francois Delarue, Sergey Nadtochiy, Mykhaylo Shkolnikov

We consider the supercooled Stefan problem, which captures the freezing of a supercooled liquid, in one space dimension. A probabilistic reformulation of the problem allows to define global solutions, even in the presence of blow-ups of the freezing rate. We provide a complete description of such solutions, by relating the temperature distribution in the liq

Stephen C. Anco, Elena Recio

A wide class of nonlinear dispersive wave equations are shown to possess a novel type of peakon solution in which the amplitude and speed of the peakon are time-dependent. These novel dynamical peakons exhibit a wide variety of different behaviours for their amplitude, speed, and acceleration, including an oscillatory amplitude and constant speed which descr

Christine Betts, Joanna Power, Waleed Ammar

We introduce GrapAL (Graph database of Academic Literature), a versatile tool for exploring and investigating a knowledge base of scientific literature, that was semi-automatically constructed using NLP methods. GrapAL satisfies a variety of use cases and information needs requested by researchers. At the core of GrapAL is a Neo4j graph database with an intu

Takafumi Suzuki, Sei-ichiro Suga

We calculate the dynamical spin-structure factor of the $S=1$ Ising spin chain with negative single-ion anisotropy in magnetic fields using the infinite time-evolving-block-decimation algorithm. We show that when a transverse magnetic field is applied, both the $ΔS=2$ excitation continuum and one-magnon mode appear in the low-lying excitation. When a longitu

Sumin Choi, Viatcheslav N. Agafonov, Valery A. Davydov, Taras Plakhotnik

Nanoscale thermometry is paramount to study primary processes of heat transfer in solids and is a subject of hot debate in cell biology. Here we report ultrafast temperature sensing using all-optical thermometry exploiting synthetic nanodiamonds with silicon-vacancy (SiV) centres embedded at a high concentration. Using multi-parametric analysis of photolumin

Yifan Lu

We show how voltage glitching can cause timing violations in CMOS behavior. Then we attack a real, security hardened, consumer device to gain code execution and dump the secure boot ROM.

Balázs Dobi, András Zempléni

Control charts have traditionally been used in industrial statistics, but are constantly seeing new areas of application, especially in the age of Industry 4.0. This paper introduces a new method, which is suitable for applications in the healthcare sector, especially for monitoring a health-characteristic of a patient. We adapt a Markov chain-based approach

Ellen C Caniglia, Eleanor J Murray, Miguel A Hernan, Zach Shahn

Existing strategies for determining the optimal treatment or monitoring strategy typically assume unlimited access to resources. However, when a health system has resource constraints, such as limited funds, access to medication, or monitoring capabilities, medical decisions must balance impacts on both individual and population health outcomes. That is, dec

Xuan Liang, Yida Xu

Sequence transduction models have been widely explored in many natural language processing tasks. However, the target sequence usually consists of discrete tokens which represent word indices in a given vocabulary. We barely see the case where target sequence is composed of continuous vectors, where each vector is an element of a time series taken successive

Da-Cheng Juan, Chun-Ta Lu, Zhen Li, Futang Peng

Learning image representations to capture fine-grained semantics has been a challenging and important task enabling many applications such as image search and clustering. In this paper, we present Graph-Regularized Image Semantic Embedding (Graph-RISE), a large-scale neural graph learning framework that allows us to train embeddings to discriminate an unprec

Nurlan N. Tashatov, Alua S. Turginbayeva, Serik A. Altynbek

Statistical distribution of the primes in an arithmetic progression is considered. The estimation of prime numbers is given and combinatorial methods are used to calculate the twin primes on the available interval. The distribution and estimation of the number of primes on the twin primes rows are obtained. A new method of twin prime infinity is proposed.

Shuwei Zhou, Xiaoying Zhuang, Timon Rabczuk

This paper proposes a phase field model for fracture in poroelastic media. The porous medium is modeled based on the classical Biot poroelasticity theory and the fracture behavior is controlled by the phase field model. Moreover, the fracture propagation is driven by the elastic energy where the phase field is used as an interpolation function to transit flu

D. J. Arnold, Y. M. Stokes, J. E. F. Green

Particle-laden flows in helical channels are of interest for their applications in spiral particle separators used in the mining and mineral processing industries. In this paper, we extend the previous work of Lee, Stokes, Bertozzi (2013) by studying thin-film flows of mono-disperse particle-laden fluid in helically-wound channels of arbitrary centreline cur

Ritesh Kumar Dubey, Sabana Parvin

The main aim of this work is not to improve any existing non-linear weight but to give a generalized framework for the construction of non-linear weights to get non-oscillatory third order WENO schemes. It is done by imposing necessary conditions on weights to get non-oscillatory WENO reconstruction which give further insight on the structure of weights to e

Enrico Celeghini

The Paradigms introduced in philosophy of science one century ago are shown to be quite more satisfactory of that introduced by Galileo. This is particularly evident in the physics based on Hilbert Spaces and related mathematical structures that we apply in this paper to Quantum Mechanics and to Theory of Images. An exhaustive discussion, that include the al

Erick Schmidt, David Akopian, Daniel J. Pack

The ubiquitousness of location based services (LBS) has proven effective for many applications such as commercial, military, and emergency responders. Software-defined radio (SDR) has emerged as an adequate framework for development and testing of global navigational satellite systems (GNSS) such as the Global Position System (GPS). SDR receivers are constan

A. R. Mendez, W. Marques, R. M. Velasco

Our aim in this paper is to establish a theoretical fundamental diagram for a multi-class traffic flow from a gas-kinetic-like traffic model. We start with a multi-class generalization of the Prigogine-Herman-Boltzmann equation to construct the fundamental relation for this system. We show that there exists a critical density which depends on the relative co

Vaibhav Kumar, Barry Cardiff, Mark F. Flanagan

Non-orthogonal multiple access (NOMA) is widely recognized as a potential multiple access (MA) technology for efficient spectrum utilization in the fifth-generation (5G) wireless standard. In this paper, we present the achievable sum rate analysis of a cooperative relaying system (CRS) using NOMA with two different receive diversity schemes - selection combi

Pushkar Mishra, Marco Del Tredici, Helen Yannakoudakis, Ekaterina Shutova

The rapid growth of social media in recent years has fed into some highly undesirable phenomena such as proliferation of abusive and offensive language on the Internet. Previous research suggests that such hateful content tends to come from users who share a set of common stereotypes and form communities around them. The current state-of-the-art approaches t

Alberto Facchini, Carmelo Finocchiaro

We show that in the category of preordered sets, there is a natural notion of pretorsion theory, in which the partially ordered sets are the torsion-free objects and the sets endowed with an equivalence relation are the torsion objects. Correspondingly, it is possible to construct a stable category factoring out the objects that are both torsion and torsion-

W. Marques, A. R. Mendez, R. M. Velasco

Recent applications of a new methodology to measure fundamental traffic relations on freeways shows that many of the critical parameters of the flow-density and speed-spacing diagrams depend on vehicle length. In response to this fact, we present in this work a generalization of the Prigogine-Herman traffic equation for aggressive drivers which takes into ac

Shuwei Zhou, Xiaoying Zhuang, Hehua Zhu, Timon Rabczuk

We present a phase field model (PFM) for simulating complex crack patterns including crack propagation, branching and coalescence in rock. The phase field model is implemented in COMSOL and is based on the strain decomposition for the elastic energy, which drives the evolution of the phase field. Then, numerical simulations of notched semi-circular bend (NSC

Alejandro Alés, Juan M. López

We investigate Kardar-Parisi-Zhang (KPZ) surface growth in the presence of long-term correlated noise. By means of extensive numerical simulations of models in the KPZ universality class we find that, as the noise correlator range increases, the surface develops a pattern of macroscopic facets that completely dominate the dynamics and induce anomalous kineti

D. Cazau

In the Big Data era, the community of PAM faces strong challenges, including the need for more standardized processing tools accross its different applications in oceanography, and for more scalable and high-performance computing systems to process more efficiently the everly growing datasets. In this work we address conjointly both issues by first proposing

Xose Luis Dean-Ben, Ali Ozbek, Hernan Lopez-Schier, Daniel Razansky

Optoacoustic image formation is conventionally based upon ultrasound time-of-flight readings from multiple detection positions. Herein, we exploit acoustic scattering to physically encode the position of optical absorbers in the acquired signals, thus reduce the amount of data required to reconstruct an image from a single waveform. This concept is experimen

E. Sorouri, M. Eshaghi Gordji

In this paper, we present a model of Partnership Game with respect to the important role of partnership and cooperation in nowdays life. Since such interactions are repeated frequently, we study this model as a Stage Game in the structure of infinitely repeated games with a discount factor $δ$ and Trigger strategy. We calculate and compare the payoffs of coo

Matthew de Brecht, Arno Pauly, Matthias Schröder

We introduce and study the notion of overt choice for countably-based spaces and for CoPolish spaces. Overt choice is the task of producing a point in a closed set specified by what open sets intersect it. We show that the question of whether overt choice is continuous for a given space is related to topological completeness notions such as the Choquet-prope

Shuwei Zhou, Timon Rabczuk, Xiaoying Zhuang

The phase-field model (PFM) represents the crack geometry in a diffusive way without introducing sharp discontinuities. This feature enables PFM to effectively model crack propagation compared with numerical methods based on discrete crack model, especially for complex crack patterns. Due to the involvement of \phased field", phase-field method can be es

J. Huang, F. Sukochev

Let ${\mathcal M}$ be a semifinite von Neumann algebra with a faithful semifinite normal trace $τ$. We show that the symmetrically $Δ$-normed operator space $E({\mathcal M},τ)$ corresponding to an arbitrary symmetrically $Δ$-normed function space $E(0,\infty)$ is an interpolation space between $L_0({\mathcal M},τ)$ and ${\mathcal M}$, which is in contrast wi

Lei Gao, Yulong Cao, Hongqing Ran, Lingdi Kong

Optical control of graphene-based photonic devices and systems has been under extensive explorations, nevertheless, the requirement of high power pump laser due to incoherent modulation makes those schemes low efficient. Here, we demonstrate coherent manipulation of the operating states of partially mode-locked fiber laser based on coherent population oscill

Nahidsadat Majlesinasab, Farzad Yousefian, Mohammad Javad Feizollahi

The goal in this paper is to develop first-order methods equipped with convergence rates for multi-agent optimization problems on semidefinite matrix spaces. These problems include cooperative optimization problems and non-cooperative Nash games. Accordingly, first we consider a multi-agent system where the agents cooperatively minimize the summation of thei

Sahar Sadani, Kamel Abdollahnezhad, Mahdi Teimouri, Vahid Ranjbar

Weibull distribution has received a wide range of applications in engineering and science. The utility and usefulness of an estimator is highly subject to the field of practitioner's study. In practice users looking for their desired estimator under different setting of parameters and sample sizes. In this paper we focus on two topics. Firstly, we propos

J. Deteix, D. Yakoubi

The operator splitting approach applied to the Navier-Stokes equations, gave rise to various numerical methods for the simulations of the dynamics of fluids. The separate work of Chorin and Temam on this subject gave birth to the so-called projection methods. The basic projection schemes, either the incremental or non-incremental variant (see [1]) induces an

Zhaokai Li, Xiaomei Liu, Hefeng Wang, Sahel Ashhab

It is difficult to calculate the energy levels and eigenstates of a large physical system on a classical computer because of the exponentially growing size of the Hilbert space. In this work, we experimentally demonstrate a quantum algorithm which could solve this problem via simulated resonant transitions. Using a four-qubit quantum simulator in which two q

Manuel Blanco, M. T. Flores-Arias, Marija Vranic

Ion acceleration in the MeV range can be routinely achieved with table-top laser technology. One of the current challenges is to improve the energy coupling from the laser to the proton beam without increasing the laser peak power. Introducing nanostructures at the front target surface was shown to be beneficial for an efficient transfer of energy to the ele

Ji-You Huang, Hsiao-feng Francis Lu

A tradeoff between sum rate and fairness for MISO broadcast communication employing dirty paper coding or zero-forcing dirty paper coding at physical layer is investigated in this paper. The tradeoff is based on a new design objective termed "tri-stage" approach as well as a new L1-based fairness measure that is much more robust than the well-known J

Saül Vélez, Jakob Schaab, Martin S. Wörnle, Marvin Müller

Recent reports of current-induced switching of ferrimagnetic oxides coupled to a heavy metal layer have opened realistic prospects for implementing magnetic insulators into electrically addressable spintronic devices. However, key aspects such as the configuration and dynamics of magnetic domain walls driven by electrical currents in insulating oxides remain

Abhinav Mishra

Many distributed learning techniques have been motivated by the increasing size of datasets and their inability to fit into main memory on a single machine. We propose an algorithm that finds the nearest neighbor in a graph locally without the need of visiting the whole graph. Our algorithm is distributed which further encourage scalability. We prove the con

Abhijit Saha, A. Katherina Vivas, Edward W. Olszewski, Verne Smith

We have obtained repeated images of 6 fields towards the Galactic bulge in 5 passbands (u, g, r, i, z) with the DECam imager on the Blanco 4m telescope at CTIO. From over 1.6 billion individual photometric measurements in the field centered on Baade's window, we have detected 4877 putative variable stars. 474 of these have been confirmed as fundamental m

Abhinav Mishra

Performance of standard processes over large distributed networks typically scales with the size of the network. For example, in planar topologies where nodes communicate with their natural neighbors, the scaling factor is $O(n)$, where $n$ is the number of nodes. As the size of the network increases, this makes global convergence over the entire network les

Luke E. Heyfron, Earl Campbell

Prevailing proposals for the first generation of quantum computers make use of 2-level systems, or qubits, as the fundamental unit of quantum information. However, recent innovations in quantum error correction and magic state distillation protocols demonstrate that there are advantages of using d-level quantum systems, known as \emph{qudits}, over the qubit

Nathan Fulton, Andre Platzer

The desire to use reinforcement learning in safety-critical settings has inspired a recent interest in formal methods for learning algorithms. Existing formal methods for learning and optimization primarily consider the problem of constrained learning or constrained optimization. Given a single correct model and associated safety constraint, these approaches

Ryo Onishi, Daisuke Sugiyama, Keigo Matsuda

We propose a super-resolution (SR) simulation system that consists of a physics-based meteorological simulation and an SR method based on a deep convolutional neural network (CNN). The CNN is trained using pairs of high-resolution (HR) and low-resolution (LR) images created from meteorological simulation results for different resolutions so that it can map L

Jomara Sandbulte, Jessica Kropczynski, John M. Carroll

This paper examines the role of community animators in technology adoption. Community animators are individuals that actively build social networks and broker ties between nodes in those networks. The present study observes technology adoption patterns through data collected from a mobile application at a local arts festival. A social network was constructed

Rupak Majumdar, Nir Piterman, Anne-Kathrin Schmuck

Many problems in reactive synthesis are stated using two formulas ---an environment assumption and a system guarantee--- and ask for an implementation that satisfies the guarantee in environments that satisfy their assumption. Reactive synthesis tools often produce strategies that formally satisfy such specifications by actively preventing an environment ass

M. R. Tarbutt

Recently, laser cooling methods have been extended from atoms to molecules. The complex rotational and vibrational energy level structure of molecules makes laser cooling difficult, but these difficulties have been overcome and molecules have now been cooled to a few microkelvin and trapped for several seconds. This opens many possibilities for applications

Francisco Arana-Herrera

We show that the number of square-tiled surfaces of genus $g$, with $n$ marked points, with one or both of its horizontal and vertical foliations belonging to fixed mapping class group orbits, and having at most $L$ squares, is asymptotic to $L^{6g-6+2n}$ times a product of constants appearing in Mirzakhani's count of simple closed hyperbolic geodesics.

Chao Li, Balaji Palanisamy

In the age of Big Data, releasing protected sensitive data at a future point in time is critical for various applications. Such self-emerging data release requires the data to be protected until a prescribed data release time and be automatically released to the recipient at the release time, even if the data sender goes offline. While straight-forward centr

Vesselin Drensky, Şehmus Fındık

Let $K[X_d]=K[x_1,\ldots,x_d]$ be the polynomial algebra in $d$ variables over a field $K$ of characteristic 0. The classical theorem of Weitzenböck from 1932 states that for linear locally nilpotent derivations $δ$ (known as Weitzenböck derivations) the algebra of constants $K[X_{d}]^δ$ is finitely generated. When the Weitzenböck derivation $δ$ acts on the

M. H. Montgomery, J. J. Hermes, D. E. Winget

The standard theory of pulsations deals with the frequencies and growth rates of infinitesimal perturbations in a stellar model. Modes which are calculated to be linearly driven should increase their amplitudes exponentially with time; the fact that nearly constant amplitudes are usually observed is evidence that nonlinear mechanisms inhibit the growth of fi

László Jenkovszky, Rainer Schicker, István Szanyi

We review elastic and diffractive scattering of protons (called also "forward physics") with emphasis on the LHC data, especially those deviating from the expectations based on extrapolations from earlier measurements at the ISR, Fermilab and thus triggering searches for new ideas, models and theories. We list these new data and provide a brief intro

Chao Li, Balaji Palanisamy

In the age of Big Data, enabling task scheduling while protecting users' privacy is critical for various decentralized applications in blockchain-based smart contract platforms. Such a privacy-preserving task scheduler requires the task input data to be secretly maintained until a prescribed task execution time and be automatically recorded into the bloc

Fabian Donat Natterer

We present here the straightforward implementation of pump-probe methods into existing scanning tunneling microscopy (STM) systems. Our method uses the waveform-sequencing abilities of a standard arbitrary waveform generator (AWG) and a simple mechanical relay switch that either connects the regular STM control electronics or the AWG to the STM system. Our u

Deepjyoti Deka, Sidhant Misra

The optimal power flow is an optimization problem used in power systems operational planning to maximize economic efficiency while satisfying demand and maintaining safety margins. Due to uncertainty and variability in renewable energy generation and demand, the optimal solution needs to be updated in response to observed uncertainty realizations or near rea

Josh Ziegler, Sean Echols, Matthew J. Moelter, Karl Saunders

This analysis of the electroclinic effect in ferroelectric liquid crystals with a first order Smectic-$A^*$--Smectic-$C^*$ (Sm-$A^*$--Sm-$C^*$) transition, shows they can be either Type I or Type II. In temperature--field parameter space Type I systems exhibit a macroscopically achiral (in which the Sm-$C^*$ helical superstructure is expelled) low-tilt (LT)

Utkarsh Gupta, Preey Shah, S. Akshay, Piotr Hofman

Unordered data Petri nets (UDPN) are an extension of classical Petri nets with tokens that carry data from an infinite domain and where transitions may check equality and disequality of tokens. UDPN are well-structured, so the coverability and termination problems are decidable, but with higher complexity than for Petri nets. On the other hand, the problem o

Nate Harman

We discuss certain effective improvements on superrigidity for $SL_n(\mathbb{Z})$ for finite $n>2$. Using these ideas we then use superrigidity to prove a representation stability theorem about pointwise finite dimensional $VIC(\mathbb{Z})$-modules, which itself can be viewed as a superrigidity theorem for $VIC(\mathbb{Z})$ and $GL_\infty(\mathbb{Z})$

Sebastian Ament, John Gregoire, Carla Gomes

We propose a novel exponentially-modified Gaussian (EMG) mixture residual model. The EMG mixture is well suited to model residuals that are contaminated by a distribution with positive support. This is in contrast to commonly used robust residual models, like the Huber loss or $\ell_1$, which assume a symmetric contaminating distribution and are otherwise as

Andrzej P. Kisielewicz, Krzysztof Przesławski

A combinatorial theorem on families of disjoint sub-boxes of a discrete cube, which implies that there at most $2^{d+1}-2$ neighbourly simplices in $\mathbb R^d$, is presented.

Aleksandar S. Dimovski, Axel Legay, Andrzej Wasowski

Variability models allow effective building of many custom model variants for various configurations. Lifted model checking for a variability model is capable of verifying all its variants simultaneously in a single run by exploiting the similarities between the variants. The computational cost of lifted model checking still greatly depends on the number of

Cody Burkard, Brent Lagesse

Convolutional Neural Networks and Deep Learning classification systems in general have been shown to be vulnerable to attack by specially crafted data samples that appear to belong to one class but are instead classified as another, commonly known as adversarial examples. A variety of attack strategies have been proposed to craft these samples; however, ther

David Dubois, Nathalie Carrasco, Jérémy Bourgalais, Ludovic Vettier

The Cassini Plasma Spectrometer (CAPS) Electron Spectrometer (ELS) instrument onboard Cassini revealed an unexpected abundance of negative ions above 950 km in Titan's ionosphere. \textit{In situ} measurements indicated the presence of negatively charged particles with mass-over-charge ratios up to 13,800 \textit{u/q}. At present, only a handful of anion

Marius V. Ionescu, Kasso A. Okoudjou, Luke G. Rogers

We prove a strong maximum principle for Schrödinger operators defined on a class of fractal sets and their blowups without boundary. Our primary interest is in weaker regularity conditions than have previously appeared in the literature; in particular we permit both the fractal Laplacian and the potential to be Radon measures on the fractal. As a consequence

Stewart Mallory, Angelo Cacciuto

Here, we describe a method for the enhanced self-assembly of triblock Janus colloids targeted to form a kagome lattice. Using computer simulations, we demonstrate that the formation of this elusive structure can be significantly improved by self-propelling or activating the colloids along the axis connecting their hydrophobic hemispheres. The process by whic

Hongxu Yang, Caifeng Shan, Alexander F. Kolen, Peter H. N. de With

Fast and accurate catheter detection in cardiac catheterization using harmless 3D ultrasound (US) can improve the efficiency and outcome of the intervention. However, the low image quality of US requires extra training for sonographers to localize the catheter. In this paper, we propose a catheter detection method based on a pre-trained VGG network, which ex

Wenju Xu, Shawn Keshmiri, Guanghui Wang

Regularized autoencoders learn the latent codes, a structure with the regularization under the distribution, which enables them the capability to infer the latent codes given observations and generate new samples given the codes. However, they are sometimes ambiguous as they tend to produce reconstructions that are not necessarily faithful reproduction of th

Vladimir Vargas-Calderón, Herbert Vinck-Posada

The effects caused by phonon-assisted tunnelling (PhAT) in a double quantum dot (QD) molecule immersed in a cavity were studied under the quantum Markovian master equation formalism in order to account for dissipation phenomena. We explain how for higher PhAT rates, a stronger interaction between a QD and the cavity at off-resonance takes place through the r

Raúl V. Casaña-Eslava, Paulo J. G. Lisboa, Sandra Ortega-Martorell, Ian H. Jarman

Quantum Clustering is a powerful method to detect clusters in data with mixed density. However, it is very sensitive to a length parameter that is inherent to the Schrödinger equation. In addition, linking data points into clusters requires local estimates of covariance that are also controlled by length parameters. This raises the question of how to adjust

Dominik J. Winterauer, Daniel Funes-Hernando, Jean-Luc Duvail, Saïd Moussaoui

Raman microscopy is a valuable tool for detecting physical and chemical properties of a sample material. When probing nanomaterials or nanocomposites the spatial resolution of Raman microscopy is not always adequate as it is limited by the optical diffraction limit. Numerical post-processing with super-resolution algorithms provides a means to enhance resolu

Jacob Anderson

In this work I propose a new way of using fully convolutional networks for classification while allowing for input of any size. I additionally propose two modifications on the idea of attention and the benefits and detriments of using the modifications. Finally, I show suboptimal results on the ITAmoji 2018 tweet to emoji task and provide a discussion about

Ben K. D. Pearce, Paul W. Ayers, Ralph E. Pudritz

HCN is a key ingredient for synthesizing biomolecules such as nucleobases and amino acids. We calculate 42 reaction rate coefficients directly involved with or in competition with the production of HCN in the early Earth or Titan atmospheres. These reactions are driven by methane and nitrogen radicals produced via UV photodissociation or lightning. For every

Valentina Candiani, Antti Hannukainen, Nuutti Hyvönen

This work introduces a computational framework for applying absolute electrical impedance tomography to head imaging without accurate information on the head shape or the electrode positions. A library of fifty heads is employed to build a principal component model for the typical variations in the shape of the human head, which leads to a relatively accurat

M. Burgay, B. Stappers, M. Bailes, E. D. Barr

We report on the latest six pulsars discovered through our standard pipeline in the intermediate-latitude region (|b| < 15 deg) of the Parkes High Time Resolution Universe Survey (HTRU). We also present timing solutions for the new discoveries and for 19 further pulsars for which only discovery parameters were previously published. Highlights of the presente

Rachel Akeson, Lee Armus, Etienne Bachelet, Vanessa Bailey

The Wide Field Infrared Survey Telescope (WFIRST) is a 2.4m space telescope with a 0.281 deg^2 field of view for near-IR imaging and slitless spectroscopy and a coronagraph designed for > 10^8 starlight suppresion. As background information for Astro2020 white papers, this article summarizes the current design and anticipated performance of WFIRST. While WFI

Philippe Poulin, Daniel Jörgens, Pierre-Marc Jodoin, Maxime Descoteaux

Supervised machine learning (ML) algorithms have recently been proposed as an alternative to traditional tractography methods in order to address some of their weaknesses. They can be path-based and local-model-free, and easily incorporate anatomical priors to make contextual and non-local decisions that should help the tracking process. ML-based techniques

Douglas L. Compton, Timothy R. Bedding, Dennis Stello

Asteroseismology is a powerful way of determining stellar parameters and properties of stars like the Sun. However, main-sequence F-type stars exhibit short mode lifetimes relative to their oscillation frequency, resulting in overlapping radial and quadrupole modes. The goal of this paper is to use the blended modes for asteroseismology in place of the indiv

S. Saracino, E. Dalessandro, F. R. Ferraro, B. Lanzoni

We used high-resolution optical HST/WFC3 and multi-conjugate adaptive optics assisted GEMINI GeMS/GSAOI observations in the near-infrared to investigate the physical properties of the globular cluster NGC 6569 in the Galactic bulge. We have obtained the deepest purely NIR color-magnitude diagram published so far for this cluster using ground-based observatio

Kathryn V. Lester, Douglas R. Gies, Gail H. Schaefer, Christopher D. Farrington

We present the visual orbit of the double-lined spectroscopic binary HD 224355 from interferometric observations with the CHARA Array, as well as an updated spectroscopic analysis using echelle spectra from the Apache Point Observatory 3.5m telescope. By combining the visual and spectroscopic orbital solutions, we find the binary components to have masses of

Gang Chen, Yiming Peng

We propose a new policy iteration theory as an important extension of soft policy iteration and Soft Actor-Critic (SAC), one of the most efficient model free algorithms for deep reinforcement learning. Supported by the new theory, arbitrary entropy measures that generalize Shannon entropy, such as Tsallis entropy and Renyi entropy, can be utilized to properl

F. Kamali, C. Henkel, S. Koyama, C. Y. Kuo

An essential part of the paradigm describing active galactic nuclei is the alignment between the radio jet and the associated rotation axis of the sub-pc sized accretion disks. Because of the small linear and angular scales involved, this alignment has not yet been checked in a sufficient number of Low Luminosity Active Galactic Nuclei (LLAGNs). The project

Susanna Bisogni, Elisabeta Lusso, Alessandro Marconi, Guido Risaliti

We recently proposed the equivalent width (EW) of the narrow [OIII]5007Å emission line as an orientation indicator for active galactic nuclei. We tested this method on about $12,300$ optically selected broad line quasars from the SDSS 7th Data Release at redshift $z < 0.8$ and with full width at half-maximum values of broad emission lines (H$α$, H$β$, and Mg

Tianhe Yu, Gleb Shevchuk, Dorsa Sadigh, Chelsea Finn

While reinforcement learning (RL) has the potential to enable robots to autonomously acquire a wide range of skills, in practice, RL usually requires manual, per-task engineering of reward functions, especially in real world settings where aspects of the environment needed to compute progress are not directly accessible. To enable robots to autonomously lear

Alexander U. Nielsen, Bruno Garbin, Stéphane Coen, Stuart G. Murdoch

We report on experimental observations of coexistence and interactions between nonlinear states with different polarizations in a passive Kerr resonator driven at a single carrier frequency. Using a fiber ring resonator with adjustable birefringence, we partially overlap nonlinear resonances of two orthogonal polarization modes, achieving coexistence between

Arnaud Carayol, Stefan Göller

A pattern is encountered in a word if some infix of the word is the image of the pattern under some non-erasing morphism. A pattern $p$ is unavoidable if, over every finite alphabet, every sufficiently long word encounters $p$. A theorem by Zimin and independently by Bean, Ehrenfeucht and McNulty states that a pattern over $n$ distinct variables is unavoidab

Mario Gleirscher, Stefan Kugele

The specification, design, and assurance of safety encompasses various concepts and best practices, subject of reuse in form of patterns. This work summarizes applied research on such concepts and practices with a focus on the last two decades and on the state-of-the-art of patterns in safety-critical system design and assurance argumentation. We investigate