April 2019 arXiv papers — page 90

The MSE Science Team, Carine Babusiaux, Maria Bergemann, Adam Burgasser

(Abridged) The Maunakea Spectroscopic Explorer (MSE) is an end-to-end science platform for the design, execution and scientific exploitation of spectroscopic surveys. It will unveil the composition and dynamics of the faint Universe and impact nearly every field of astrophysics across all spatial scales, from individual stars to the largest scale structures

K. Atapin, S. Fabrika, M. D. Caballero-Garcia

We analyzed the X-ray power density spectra of five ultraluminous X-ray sources (ULXs) NGC5408 X-1, NGC6946 X-1, M82 X-1, NGC1313 X-1 and IC342 X-1 that are the only ULXs which display both flat-topped noise (FTN) and quasi-periodic oscillations (QPO). We studied the QPO frequencies, fractional root-mean-square (rms) variability, X-ray luminosity and spectra

Miruna-Stefana Sorea

We give a new and constructive proof of the existence of a special class of univariate polynomials whose graphs have preassigned shapes. By definition, all the critical points of a Morse polynomial function are real and distinct and all its critical values are distinct. Thus we can associate to it an alternating permutation: the so-called Arnold snake, given

Bena Tshishiku

In this note, we remark on the range in Borel's theorem on the stable cohomology of the arithmetic groups Sp(2n,Z) and SO(n,n;Z). This improves the range stated in Borel's original papers, an improvement that was known to Borel. Our main task is a technical computation involving the Weyl group action on roots and weights. This note originally appeare

Lucía Santamaría, Amittai Axelrod

We present and apply two methods for addressing the problem of selecting relevant training data out of a general pool for use in tasks such as machine translation. Building on existing work on class-based language difference models, we first introduce a cluster-based method that uses Brown clusters to condense the vocabulary of the corpora. Secondly, we impl

Cleber F. Colle, Eduardo Garibaldi

Since techniques used to address the Nivat's conjecture usually relies on Morse-Hedlund Theorem, an improved version of this classical result may mean a new step towards a proof for the conjecture. In this paper, considering an alphabetical version of the Morse-Hedlund Theorem, we show that, for a configuration $η\in A^{\mathbb{Z}^2}$ that contains all l

Ruizhi Li, Gregory Sell, Hynek Hermansky

Measuring performance of an automatic speech recognition (ASR) system without ground-truth could be beneficial in many scenarios, especially with data from unseen domains, where performance can be highly inconsistent. In conventional ASR systems, several performance monitoring (PM) techniques have been well-developed to monitor performance by looking at tri-

Brian A. Powell

A method for detecting electronic data theft from computer networks is described, capable of recognizing patterns of remote exfiltration occurring over days to weeks. Normal traffic flow data, in the form of a host's ingress and egress bytes over time, is used to train an ensemble of one-class learners. The detection ensemble is modular, with individual

Yasutada Oohama

We study the determination problem of the channel capacity for the discrete memoryless channels in the finite blocklength regime. We derive explicit lower and upper bounds of the capacity. We shall demonstrate that the information spectrum approach is quite useful for investigating this problem.

David S. Aguado, Jonay I. González Hernández, Carlos Allende Prieto, Rafael Rebolo

We present an analysis of the UVES high-resolution spectroscopic observations at the 8.2m VLT of J0023+0307, a main-sequence extremely iron-poor dwarf star. We are unable to detect iron lines in the spectrum but derive [Fe/H]<-6.1 from the Ca II resonance lines assuming [Ca/Fe]>0.40. The chemical abundance pattern of J0023+0307, with very low [Fe/Mg] and [Ca

S. S. Kondov, C. -H. Lee, K. H. Leung, C. Liedl

Atomic lattice clocks have spurred numerous ideas for tests of fundamental physics, detection of general relativistic effects, and studies of interacting many-body systems. On the other hand, molecular structure and dynamics offer rich energy scales that are at the heart of new protocols in precision measurement and quantum information science. Here we demon

E. Mervinetsky, I. Alshanski, S. Lenfant, D. Guerin

We report how the electron transport through a solid-state metal/Gly-Gly-His tripeptide (GGH) monolayer/metal junction and the metal/GGH work function are modified by the GGH complexation with Cu2+ ions. Conducting AFM is used to measure the current-voltage histograms. The work function is characterized by combining macroscopic Kelvin probe and Kelvin probe

Alberto Lastra, Stéphane Malek

We study a family of partial differential equations in the complex domain, under the action of a complex perturbation parameter $ε$. We construct inner and outer solutions of the problem and relate them to asymptotic representations via Gevrey asymptotic expansions with respect to $ε$, in adequate domains. The construction of such analytic solutions is close

Kevin Mallery, Jiarong Hong

The key limitations of digital inline holography (DIH) for particle tracking applications are poor longitudinal resolution, particle concentration limits, and case-specific processing. We utilize an inverse problem method with fused lasso regularization to perform full volumetric reconstructions of particle fields. By exploiting data sparsity in the solution

Eunice Bezerra, Oswaldo D. Miranda

Mimetic gravity can be described as a formulation capable of mimicking different evolutionary scenarios regarding the universe dynamics. Notwithstanding its initial aim of producing a similar evolution to the one expected from the dark components of the standard cosmology, a recent association with loop quantum cosmology could also provide interesting result

Supreeth Narasimhaswamy, Zhengwei Wei, Yang Wang, Justin Zhang

We present Hand-CNN, a novel convolutional network architecture for detecting hand masks and predicting hand orientations in unconstrained images. Hand-CNN extends MaskRCNN with a novel attention mechanism to incorporate contextual cues in the detection process. This attention mechanism can be implemented as an efficient network module that captures non-loca

K. Suchomska, D. Graczyk, G. Pietrzyński, W. Gieren

Aim: Our aim is to obtain high-accuracy measurements of the physical and orbital parameters of two evolved eclipsing binary systems, and to use these measurements to study their evolutionary status. We also aim to derive distances to the systems by using a surface brightness - colour relation and compare these distances with the measurements provided by GAIA

L. Crespo Campo, R. B. Firestone, B. A. Brown, M. Guttormsen

The $γ$-ray strength function, or average reduced $γ$-ray transition probability, is a fundamental input in the calculation of $(n,γ)$ cross sections used to simulate the nucleosynthesis of elements heavier than Fe. Since 2004, an enhanced probability of $γ$-decay with $γ$-ray energies below $\approx2 - 4$ MeV has been measured in reaction data for numerous

Kelly Van Lancker, An Vandebosch, Stijn Vansteelandt

Conditional power calculations are frequently used to guide the decision whether or not to stop a trial for futility or to modify planned sample size. These ignore the information in short-term endpoints and baseline covariates, and thereby do not make fully efficient use of the information in the data. We therefore propose an interim decision procedure base

Luca V. Delacrétaz, Blaise Goutéraux, Sean A. Hartnoll, Anna Karlsson

Electron solid phases of matter are revealed by characteristic vibrational resonances. Sufficiently large magnetic fields can overcome the effects of disorder, leading to a weakly pinned collective mode called the magnetophonon. Consequently, in this regime it is possible to develop a tightly constrained hydrodynamic theory of pinned magnetophonons. The beha

Fil Simovic, Robert B. Mann

We examine the thermodynamic behaviour of charged, asymptotically de Sitter black holes embedded in a finite-radius isothermal cavity, with a Born-Infeld gauge field replacing the ordinary Maxwell field. We find that the non-linearities of Born-Infeld theory lead to the presence of reentrant phase transitions in the canonical ensemble, whose existence and ch

Douglas Rizzolo

Let $G_n$ be a simple graph on $V_n=\{v_1,\dots, v_n\}$. The Seidel matrix $S(G_n)$ of $G_n$ is the $n\times n$ matrix whose $(ij)$&#39;th entry, for $i\neq j$ is $-1$ if $v_i\sim v_j$ and $1$ otherwise, and whose diagonal entries are $0$. We show that the proportion of simple graphs $G_n$ such that $\det(S(G_n))\geq n-1$ tends to one as $n$ tends to infinit

Nina Bulanova, Maxim Buzdalov

The binary value function, or BinVal, has appeared in several studies in theory of evolutionary computation as one of the extreme examples of linear pseudo-Boolean functions. Its unbiased black-box complexity was previously shown to be at most $\lceil \log_2 n \rceil + 2$, where $n$ is the problem size. We augment it with an upper bound of $\log_2 n + 2.4214

Brendan Whitaker, Denis Newman-Griffis, Aparajita Haldar, Hakan Ferhatosmanoglu

Analysis of word embedding properties to inform their use in downstream NLP tasks has largely been studied by assessing nearest neighbors. However, geometric properties of the continuous feature space contribute directly to the use of embedding features in downstream models, and are largely unexplored. We consider four properties of word embedding geometry,

R. Gerrú, S. Mulas, U. Losada, F. Castejón

This study presents the investigation of the connection between radial electric field, gradient of Reynolds stress and Long Range Correlation (LRC), as a proxy for Zonal Flows (ZF), in different plasma scenarios in the TJ-II stellarator. Monte Carlo simulations were made showing that radial electric fields in the range of those experimentally measured have a

Djamel Meraghni, Louiza Soltane

We exploit the asymptotic normality of the extreme value theory (EVT) based estimators of the parameters of a symmetric Lévy-stable distribution, to construct confidence intervals. The accuracy of these intervals is evaluated through a simulation study.

Mojan Javaheripi, Bita Darvish Rouhani, Farinaz Koushanfar

Training large and highly accurate deep learning (DL) models is computationally costly. This cost is in great part due to the excessive number of trained parameters, which are well-known to be redundant and compressible for the execution phase. This paper proposes a novel transformation which changes the topology of the DL architecture such that it reaches a

Jeremy E. J. Cohen, Todd Huster, Ra Cohen

Adversarial attacks against machine learning models are a rather hefty obstacle to our increasing reliance on these models. Due to this, provably robust (certified) machine learning models are a major topic of interest. Lipschitz continuous models present a promising approach to solving this problem. By leveraging the expressive power of a variant of neural

Joshua Brakensiek, Venkatesan Guruswami

Under the Strong Exponential Time Hypothesis, an integer linear program with $n$ Boolean-valued variables and $m$ equations cannot be solved in $c^n$ time for any constant $c < 2$. If the domain of the variables is relaxed to $[0,1]$, the associated linear program can of course be solved in polynomial time. In this work, we give a natural algorithmic bridgin

Sebastian Opper

We study triangulated categories which can be modeled by an oriented marked surface $\mathcal{S}$ and a line field $η$ on $\mathcal{S}$. This includes bounded derived categories of gentle algebras and -- conjecturally -- all partially wrapped Fukaya categories introduced by Haiden-Katzarkov-Kontsevich. We show that triangle equivalences between such categori

Joao Campos, Joao R. Cardoso, Pedro Miraldo

Pose estimation is one of the most important problems in computer vision. It can be divided in two different categories -- absolute and relative -- and may involve two different types of camera models: central and non-central. State-of-the-art methods have been designed to solve separately these problems. This paper presents a unified framework that is able

John Carr, Mark Greer

We study P-groupoids that arise from certain decompositions of complete graphs. We show that left distributive P-groupoids are distributive, quasigroups. We characterize P-groupoids when the corresponding decomposition is a Hamiltonian decomposition for complete graphs of odd, prime order. We also study a specific example of a P-quasigroup constructed from c

A. Bartlett, R. Belanger, M. Amman, D. Venus

An alternate method of measuring anisotropy fields in thin film ferromagnets is demonstrated. The method relies on the magnetic susceptibility in a small a.c. magnetic field, measured \txtit{in situ} using the magneto-optic Kerr effect (MOKE), and will be useful in situations where more specialized apparatus are not available, or constraints discourage the u

Sergey Zakharov, Wadim Kehl, Benjamin Planche, Andreas Hutter

In this paper, we address the problem of 3D object instance recognition and pose estimation of localized objects in cluttered environments using convolutional neural networks. Inspired by the descriptor learning approach of Wohlhart et al., we propose a method that introduces the dynamic margin in the manifold learning triplet loss function. Such a loss func

Jake Langham, Tom S. Eaves, Rich R. Kerswell

We examine how known unstable equilibria of the Navier-Stokes equations in plane Couette flow adapt to the presence of an imposed stable density difference between the two boundaries for varying values of the Prandtl number $Pr$, the ratio of viscosity to density diffusivity, and fixed moderate Reynolds number, $Re=400$. In the two asymptotic limits $Pr \to

Bruno Sicardy, Stefan Renner, Rodrigo Leiva, Françoise Roques

Since 2013, dense and narrow rings are known around the small Centaur object Chariklo and the dwarf planet Haumea. Dense material has also been detected around the Centaur Chiron, although its nature is debated. This is the first time ever that rings are observed elsewhere than around the giant planets, suggesting that those features are more common than pre

Yonatan Svirsky, Andrei Sharf

In this work we introduce a differential rendering module which allows neural networks to efficiently process cluttered data. The module is composed of continuous piecewise differentiable functions defined as a sensor array of cells embedded in 3D space. Our module is learnable and can be easily integrated into neural networks allowing to optimize data rende

P. Sánchez-Sáez, P. Lira, R. Cartier, N. Miranda

We used data from the QUEST-La Silla Active Galactic Nuclei (AGN) variability survey to construct light curves for 208,583 sources over $\sim 70$ deg$^2$, with a a limiting magnitude $r \sim 21$. Each light curve has at least 40 epochs and a length of $\geq 200$ days. We implemented a Random Forest algorithm to classify our objects as either AGN or non-AGN a

Aldo Batta, Enrico Ramirez-Ruiz

Most common formation channels of stellar mass black hole (BH) binaries like the ones observed by LIGO, often assume they are assembled from the direct collapse of massive pre-supernova stars. However, it is still unclear whether the final mass and spin of the newly formed BH arises from the collapse of the entire stellar progenitor or just a fraction of it,

David V. Martin

Almost a dozen circumbinary planets have been found transiting eclipsing binaries. For the first time the observational bias of this sample is calculated with respect to the mass ratio of the host binaries. It is shown that the mass ratio affects transit detection in multiple, sometimes subtle ways, through stability and dynamics of orbits, dilution of trans

T . J . Taiwo

In order to establish a correspondence between the reformulation of quantum mechanics without potential function and the conventional quantum mechanics; we obtained the potential function of the New Wilson - Racah quantum system in [3] using any of the proposed formulas in [4]. To achieve this, we used the matrix elements of the potential function and the ba

Kasper Green Larsen, Tal Malkin, Omri Weinstein, Kevin Yeo

We prove an $Ω(d \lg n/ (\lg\lg n)^2)$ lower bound on the dynamic cell-probe complexity of statistically $\mathit{oblivious}$ approximate-near-neighbor search ($\mathsf{ANN}$) over the $d$-dimensional Hamming cube. For the natural setting of $d = Θ(\log n)$, our result implies an $\tildeΩ(\lg^2 n)$ lower bound, which is a quadratic improvement over the highe

Arnesh Sen, Jayoti Das

This paper depicts the actual variation of gate induced drain leakage current with impurity doping concentration by complete qualitative and quantitative approach. De Casteljaus algorithm is applied to describe the band to band tunneling in a thin gate oxide nMOSFET and the results are remarkably matched. Moreover for the very first time, the dependency of t

Kate Pattle, Laura Fissel

Observations of star-forming regions by the current and upcoming generation of submillimeter polarimeters will shed new light on the evolution of magnetic fields over the cloud-to-core size scales involved in the early stages of the star formation process. Recent wide-area and high-sensitivity polarization observations have drawn attention to the challenges

Lai Wang, Meilin Yu

We conduct a comparative study of the Jacobian-free linearly implicit Rosenbrock-Wanner (ROW) methods, the explicit first stage, singly diagonally implicit Runge-Kutta (ESDIRK) methods, and the second-order backward differentiation formula (BDF2) for unsteady flow simulation using spatially high-order flux reconstruction/correction procedure via reconstructi

J. Matthias Kahk, Johannes Lischner

Core-electron x-ray photoelectron spectroscopy is a powerful technique for studying the electronic structure and chemical composition of molecules, solids and surfaces. However, the interpretation of measured spectra and the assignment of peaks to atoms in specific chemical environments is often challenging. Here, we address this problem and introduce a para

Achilleas Lazarides, Sthitadhi Roy, Francesco Piazza, Roderich Moessner

We investigate the conditions under which periodically driven quantum systems subject to dissipation exhibit a stable subharmonic response. Noting that coupling to a bath introduces not only cooling but also noise, we point out that a system subject to the latter for the entire cycle tends to lose coherence of the subharmonic oscillations, and thereby the lo

Logan Courtney, Ramavarapu Sreenivas

This paper explores the use of convolution LSTMs to simultaneously learn spatial- and temporal-information in videos. A deep network of convolutional LSTMs allows the model to access the entire range of temporal information at all spatial scales of the data. We describe our experiments involving convolution LSTMs for lipreading that demonstrate the model is

Mattias Ångqvist, J. Magnus Rahm, Leili Gharaee, Paul Erhart

Phase diagrams for multi-component systems represent crucial information for understanding and designing materials but are very time consuming to assess experimentally. Computational modeling plays an increasingly important role in this regard but has been largely focused on systems with matching lattice structures and/or stable boundary phases. Here, using

Ching-Hang Chen, Ambrish Tyagi, Amit Agrawal, Dylan Drover

We present an unsupervised learning approach to recover 3D human pose from 2D skeletal joints extracted from a single image. Our method does not require any multi-view image data, 3D skeletons, correspondences between 2D-3D points, or use previously learned 3D priors during training. A lifting network accepts 2D landmarks as inputs and generates a correspond

Ernst Paunzen, Gerald Handler, Przemyslaw Walczak, Stefan Huemmerich

The magnetic chemically peculiar (Ap/CP2) star 21 Com has been extensively studied in the past, albeit with widely differing and sometimes contradictory results, in particular concerning the occurrence of short term variability between about 5 to 90 minutes. We have performed a new investigation of 21 Com using MOST satellite and high-cadence ground-based ph

Binita Mondal, Shovan Dan, Sudipta Mondal, R. N. Bhowmik

The binary compounds GdIr3, TbIr3 and HoIr3 are synthesized successfully and found to form in macroscopic co-existence of two polymorphic phases: C15b and AuCu3-type. The dc magnetization and heat capacity studies confirm that C15b phase orders ferromagnetically, whereas the AuCu3 phase remains paramagnetic down to 2 K. The frequency dependent ac-susceptibil

Silvia Tozza, Maurizio Falcone

Astronomical images are of crucial importance for astronomers since they contain a lot of information about celestial bodies that can not be directly accessible. Most of the information available for the analysis of these objects starts with sky explorations via telescopes and satellites. Unfortunately, the quality of astronomical images is usually very low

James M. Taylor, Edouard Lesne, Anastasios Markou, Fasil Kidane Dejene

Non-collinear antiferromagnets, with either an L1$_{2}$ cubic crystal lattice (e.g. Mn$_{3}$Ir and Mn$_{3}$Pt) or a D0$_{19}$ hexagonal structure (e.g. Mn$_{3}$Sn and Mn$_{3}$Ge), exhibit a number of novel phenomena of interest to topological spintronics. Amongst the cubic systems, for example, tetragonally distorted Mn$_{3}$Pt exhibits an intrinsic anomalou

Felix Voigtlaender, Philipp Petersen

We discuss the expressive power of neural networks which use the non-smooth ReLU activation function $\varrho(x) = \max\{0,x\}$ by analyzing the approximation theoretic properties of such networks. The existing results mainly fall into two categories: approximation using ReLU networks with a fixed depth, or using ReLU networks whose depth increases with the

Doost Ali Mojdeh, Zhila Mansouri

An independent double Roman dominating function (IDRDF) on a graph $G=(V,E)$ is a function $f:V(G)\rightarrow \{0,1,2,3\}$ having the property that if $f(v)=0$, then the vertex $v$ has at least two neighbors assigned $2$ under $f$ or one neighbor $w$ with assigned $3$ under $f$, and if $f(v)=1$, then there exists $w\in N(v)$ with $f(w)\geq2$ such that the po

G. Lanzuisi, R. Gilli, M. Cappi, M. Dadina

X-ray emission from AGN is believed to be produced via Comptonization of optical/UV seed photons emitted by the accretion disk, up-scattered by hot electrons in a corona surrounding the black hole. A critical compactness vs. temperature threshold is predicted above which any increase in the source luminosity, for a fixed size, would then generate positron-el

Sergei Masis, Nir Alfasi, Roei Levi, Oleg Shtempluck

Dense ensembles of nitrogen vacancy (NV) centers in diamond are of interest for various applications including magnetometry, masers, hyperpolarization and quantum memory. All of the applications above may benefit from a non-linear response of the ensemble, and hence multiphoton processes are of importance. We study an enhancement of the NV ensemble multiphot

A. Guskov

The SPD experiment at the future NICA collider at JINR (Dubna, Russia) aims to investigate the nucleon spin structure and polarization phenomena in collisions of longitudinally and transversely polarized protons and deuterons at $\sqrt{s}$ up to 27 GeV and luminosity up to 10$^{32}$ cm$^{-2}$ s$^{-1}$. Measurement of asymmetries in the Drell-Yan pairs, charm

Valentin Lychagin, Mikhail Roop

In this paper we study a 3-dimensional filtration of real gases described by Redlich-Kwong equations of state. Thermodynamical states are considered as Legendrian (Lagrangian) submanifolds in contact (symplectic) space. Connection between singularities of their projection on the space of intensive variables and phase transitions is shown. Explicit formulae f

Luís H. S. Kadowaki, Elisabete M. de Gouveia Dal Pino, Tania E. Medina-Torrejón

Fast magnetic reconnection events can play an important role in accretion disk systems. A potential model to explain the non-thermal very-high-energy (VHE) emission (from GeV to TeV) observed in black-hole binaries (BHBs) and Active Galatic Nuclei (AGNs) can be attributed to fast magnetic reconnection induced in the turbulent corona of accretion disks and/or

Haohan Guo, Frank K. Soong, Lei He, Lei Xie

End-to-end, autoregressive model-based TTS has shown significant performance improvements over the conventional one. However, the autoregressive module training is affected by the exposure bias, or the mismatch between the different distributions of real and predicted data. While real data is available in training, but in testing, only predicted data is avai

Vivek Deulkar, Jayakrishnan Nair, Ankur A. Kulkarni

The inherent intermittency of wind and solar generation presents a significant challenge as we seek to increase the penetration of renewable generation in the power grid. Increasingly, energy storage is being deployed alongside renewable generation to counter this intermittency. However, a formal characterization of the reliability of renewable generators bu

Georgios Sakellaris

We construct Green&#39;s functions for elliptic operators of the form $\mathcal{L}u=-\text{div}(A\nabla u+bu)+c\nabla u+du$ in domains $Ω\subseteq\mathbb R^n$, under the assumption $d\geq\text{div}b$, or $d\geq\text{div}c$. We show that, in the setting of Lorentz spaces, the assumption $b-c\in L^{n,1}(Ω)$ is both necessary and optimal to obtain pointwise bou

Fritz Colonius, Alexandre J. Santana, João A. N. Cossich

This paper provides an upper for the invariance pressure of control sets with nonempty interior and a lower bound for sets with finite volume. In the special case of the control set of a hyperbolic linear control system in R^{d} this yields an explicit formula. Further applications to linear control systems on Lie groups and to inner control sets are discuss

Maxwell Henderson, Samriddhi Shakya, Shashindra Pradhan, Tristan Cook

Convolutional neural networks (CNNs) have rapidly risen in popularity for many machine learning applications, particularly in the field of image recognition. Much of the benefit generated from these networks comes from their ability to extract features from the data in a hierarchical manner. These features are extracted using various transformational layers,

Haohan Guo, Frank K. Soong, Lei He, Lei Xie

The end-to-end TTS, which can predict speech directly from a given sequence of graphemes or phonemes, has shown improved performance over the conventional TTS. However, its predicting capability is still limited by the acoustic/phonetic coverage of the training data, usually constrained by the training set size. To further improve the TTS quality in pronunci

Snežana Č. Živković-Zlatanović, Bhagwati P. Duggal

A bounded linear operator $T$ on a Banach space $X$ is said to be generalized Drazin-meromorphic invertible if there exists a bounded linear operator $S$ acting on $X$ such that $TS=ST$, $STS=S$, $ TST-T$ is meromorphic. We shall say that $T$ admits a generalized Kato-meromorphic decomposition if there exists a pair of $T$-invariant closed subspaces $(M,N)$

Marco Rehmeier

Let the coefficients $a_{ij}$ and $b_i$, $i,j \leq d$, of the linear Fokker-Planck-Kolmogorov equation (FPK-eq.) $$\partial_tμ_t = \partial_i\partial_j(a_{ij}μ_t)-\partial_i(b_iμ_t)$$ be Borel measurable, bounded and continuous in space. Assume that for every $s \in [0,T]$ and every Borel probability measure $ν$ on $\mathbb{R}^d$ there is at least one soluti

Enrique Fernandez-Blanco, Daniel Rivero, Marcos Gestal, Carlos Fernandez-Lozano

Data mining and data classification over biomedical data are two of the most important research fields in computer science. Among the great diversity of techniques that can be used for this purpose, Artifical Neural Networks (ANNs) is one of the most suited. One of the main problems in the development of this technique is the slow performance of the full pro

Smiju Kodamthuruthil Joy, Lakshmi Natarajan

An index code for a broadcast channel with receiver side information is &#39;locally decodable&#39; if every receiver can decode its demand using only a subset of the codeword symbols transmitted by the sender instead of observing the entire codeword. Local decodability in index coding improves the error performance when used in wireless broadcast channels,

Rafael Rodrigues, Antonio M. G. Pinheiro

Segmentation of skeletal muscles in Magnetic Resonance Images (MRI) is essential for the study of muscle physiology and diagnosis of muscular pathologies. However, manual segmentation of large MRI volumes is a time-consuming task. The state-of-the-art on algorithms for muscle segmentation in MRI is still not very extensive and is somewhat database-dependent.

Linwei Ye, Mrigank Rochan, Zhi Liu, Yang Wang

We consider the problem of referring image segmentation. Given an input image and a natural language expression, the goal is to segment the object referred by the language expression in the image. Existing works in this area treat the language expression and the input image separately in their representations. They do not sufficiently capture long-range corr

Mahdyar Ravanbakhsh

Novelty detection is a process for distinguishing the observations that differ in some respect from the observations that the model is trained on. Novelty detection is one of the fundamental requirements of a good classification or identification system since sometimes the test data contains observations that were not known at the training time. In other wor

Qi Gao, Chiun-Chang Lee, Tai-Chia Lin

Recently, a rich variety of the micro-phenomena of the superfluid passing an obstacle has been observed in the binary mixture of rotating Bose--Einstein condensates (BECs). Among such phenomena, the interaction of dark--bright solitons is one of the most important issues. In this work we investigate the semi-classical limit for a coupled system of Gross--Pit

Iker Gallardo, Andres Arnau, Fernando Delgado, Romana Baltic

We combine x-ray absorption spectroscopy (XAS), x-ray magnetic circular dichroism (XMCD) and x-ray magnetic linear dichroism (XMLD) data with first principles density functional theory (DFT) calculations and a multiorbital many body Hamiltonian approach to understand the electronic and magnetic properties of Co atoms adsorbed on h-BN/Ru(0001) and h-BN/Ir(111

Bunjamin Memishi, Raja Appuswamy, Marcus Paradies

The abundance of available sensor and derived data from large scientific experiments, such as earth observation programs, radio astronomy sky surveys, and high-energy physics already exceeds the storage hardware globally fabricated per year. To that end, cold storage data archives are the---often overlooked---spearheads of modern big data analytics in scient

Maximilian Alber

Deep neural networks successfully pervaded many applications domains and are increasingly used in critical decision processes. Understanding their workings is desirable or even required to further foster their potential as well as to access sensitive domains like medical applications or autonomous driving. One key to this broader usage of explaining framewor

Daniel Russo

This note gives a short, self-contained, proof of a sharp connection between Gittins indices and Bayesian upper confidence bound algorithms. I consider a Gaussian multi-armed bandit problem with discount factor $γ$. The Gittins index of an arm is shown to equal the $γ$-quantile of the posterior distribution of the arm&#39;s mean plus an error term that vanis

A. Evans, Ya. V. Pavlenko, D. P. K. Banerjee, U. Munari

We report the discovery of the diatomic molecule SiO in the gas phase in the environment of the recurrent nova T Coronae Borealis. While some of the SiO is photospheric, a substantial portion must arise in the wind from the red giant component of T CrB. A simple fit to the SiO feature, assuming local thermodynamic equilibrium, suggests a SiO column density o

Panyue Zhou

Let C be a triangulated category with a Serre functor S and X a non-zero contravariantly finite rigid subcategory of C. Then X is cluster tilting if and only if the quotient category C/X is abelian and S(X)=X[2]. As an application, this result generalizes work by Beligiannis.

Samuel Brem, Jonas Zipfel, Malte Selig, Archana Raja

The reduced dielectric screening in atomically thin transition metal dichalcogenides allows to study the hydrogen-like series of higher exciton states in optical spectra even at room temperature. The width of excitonic peaks provides information about the radiative decay and phonon-assisted scattering channels limiting the lifetime of these quasi-particles.

Son T. Le, Joseph A. Hagmann, Nikolai Klimov, David Newell

We present the results of an experimental study of the interaction of quantized Landau level (LL) edge-states at the physical edge of graphene by using a graphene pn junction device with a ring-shaped geometry for the channel. The unique device geometry allows the interactions between edge-states to be probed at both electrostatic edges defined by pn junctio

Roy O. Davies, A. J. Ostaszewski

A classical inventory problem is studied from the perspective of embedded options, reducing inventory-management to the design of optimal contracts for forward delivery of stock (commodity). Financial option techniques à la Black-Scholes are invoked to value the additional `option to expand stock&#39;. A simplified approach which ignores distant time effects

Mohammad Keshavarzi, Michael Wu, Michael N. Chin, Robert N. Chin

Virtual and augmented reality communication platforms are seen as promising modalities for next-generation remote face-to-face interactions. Our study attempts to explore non-verbal communication features in relation to their conversation context for virtual and augmented reality mediated communication settings. We perform a series of user experiments, trigg

A. J. Ostaszewski

This paper, on subdominant eigenvalue location of a bordered diagonal matrix, is the mathematical sequel to an accounting paper by Gao, Ohlson, Ostaszewski \cite{GaoOO}. We explore the following characterization of dividend-policy irrelevance (DPI) to equity valuation in a multi-dimensional linear dynamics framework $L$: DPI occurs under $L$ when discounting

Sepehr Assadi, Yu Chen, Sanjeev Khanna

We present new lower bounds that show that a polynomial number of passes are necessary for solving some fundamental graph problems in the streaming model of computation. For instance, we show that any streaming algorithm that finds a weighted minimum $s$-$t$ cut in an $n$-vertex undirected graph requires $n^{2-o(1)}$ space unless it makes $n^{Ω(1)}$ passes o

J. Liang, G. E. Simion, Y. B. Lyanda-Geller

Search for parafermions and Fibonacci anyons, which are excitations obeying non-Abelian statistics, is driven both by the quest for deeper understanding of nature and prospects for universal topological quantum computation. However, physical systems that can host these exotic excitations are rare and hard to realize in experiments. Here we study the domain w

Cătălin I. Cârstea, Jenn-Nan Wang

In this paper we derive a propagation of smallness result for a scalar second elliptic equation in divergence form whose leading order coefficients are Lipschitz continuous on two sides of a $C^2$ hypersurface that crosses the domain, but may have jumps across this hypersurface. Our propagation of smallness result is in the most general form regarding the lo

Ahmet Iscen, Giorgos Tolias, Yannis Avrithis, Ondrej Chum

Semi-supervised learning is becoming increasingly important because it can combine data carefully labeled by humans with abundant unlabeled data to train deep neural networks. Classic methods on semi-supervised learning that have focused on transductive learning have not been fully exploited in the inductive framework followed by modern deep learning. The sa

Zhijie Qu, Joel N. Bregman, Edmund J. Hodges-Kluck

The metallicity of galactic gaseous halos provides insights into accretion and feedback of galaxies. The nearby edge-on galaxy NGC 891 has a multi-component gaseous halo and a background AGN (LQAC 035+042 003) projected 5 kpc above the disk near the minor axis. Against the UV continuum of this AGN, we detect lines from 13 ions associated with NGC 891 in new

Jingming Li, Nianping Li, Jinqing Peng, Zhibin Wu

The proportion of Energy consumption in the building industry is great, as well as the amount of cooling and heating system. Scholars have been working on energy conservation of Heating, ventilation, and air-conditioning and other systems in buildings. The application of occupant behavior data for building energy optimization has started gaining attention fr

Michael Neunteufel, Joachim Schöberl

In this paper we derive a new finite element method for nonlinear shells. The Hellan-Herrmann-Johnson (HHJ) method is a mixed finite element method for fourth order Kirchhoff plates. It uses convenient Lagrangian finite elements for the vertical deflection, and introduces sophisticated finite elements for the moment tensor. In this work we present a generali

Vegard B. Sørdal, Joakim Bergli

Machine learning techniques based on artificial neural networks have been successfully applied to solve many problems in science. One of the most interesting domains of machine learning, reinforcement learning, has natural applicability for optimization problems in physics. In this work we use deep reinforcement learning and Chopped Random Basis optimization

Samuel Brem, August Ekman, Dominik Christiansen, Florian Katsch

The photoluminescence (PL) spectrum of transition metal dichalcogenides (TMDs) shows a multitude of emission peaks below the bright exciton line and not all of them have been explained yet. Here, we study the emission traces of phonon-assisted recombinations of momentum-dark excitons. To this end, we develop a microscopic theory describing simultaneous excit

Thi Ai Thao Nguyen, Tran Khanh Dang, Quynh Chi Truong, Dinh Thanh Nguyen

In this paper, we have proposed a multi factor biometric-based remote authentication protocol. Our proposal overcomes the vulnerabilities of some previous works. At the same time, the protocol also obtains a low false accept rate (FAR) and false reject rate (FRR).

Wade Hindes

We show that the dynamical degree of an (i.i.d) random sequence of dominant, rational self-maps on projective space is almost surely constant. We then apply this result to height growth and height counting problems in random orbits.

Alberto Baccini, Giuseppe De Nicolao, Eugenio Petrovich

It is several years since national research evaluation systems around the globe started making use of quantitative indicators to measure the performance of researchers. Nevertheless, the effects on these systems on the behavior of the evaluated researchers are still largely unknown. We attempt to shed light on this topic by investigating how Italian research

Fabio C. Zegarra, Dirar Homouz, Andrei G. Gasic, Lucas Babel

Here, we show by solution nuclear magnetic resonance measurements that the urea-unfolded protein apoazurin becomes elongated when the synthetic crowding agent dextran 20 is present, in contrast to the prediction from the macromolecular crowding effect based on the argument of volume exclusion. To explore the complex interactions beyond volume exclusion, we e

Jeong-Hyuck Park

Upon treating the whole closed-string massless NS-NS sector as stringy graviton fields, Double Field Theory may evolve into `Stringy Gravity&#39;. In terms of an $\mathbf{O}(D,D)$ covariant differential geometry beyond Riemann, we present the definitions of the off-shell conserved stringy Einstein curvature tensor and the on-shell conserved stringy Energy-Mo