February 2019 arXiv papers — page 85

Bruna D. Wundervald, Walmes M. Zeviani

Music genre can be hard to describe: many factors are involved, such as style, music technique, and historical context. Some genres even have overlapping characteristics. Looking for a better understanding of how music genres are related to musical harmonic structures, we gathered data about the music chords for thousands of popular Brazilian songs. Here, &#

Xi Hang Cao, Xiaojiang Du, E. Paul Ratazzi

Internet of Things (IoT) is ubiquitous because of its broad applications and the advance in communication technologies. The capabilities of IoT also enable its important role in homeland security and tactical missions, including Reconnaissance, Intelligence, Surveillance, and Target Acquisition (RISTA). IoT security becomes the most critical issue before its

Petr Vogel

I shall sketch the history of reactor neutrino physics over five decades since the Reines-Cowan proof of neutrino existence in the late 50s, till the advent of the present era of precision reactor neutrino oscillation experiments. There are three chapters of this story: i) Exploration of possibilities of the reactor neutrinos in the 60s and 70s; ii) Looking

Vojkan Jaksic, Vahagn Nersesyan, Claude-Alain Pillet, Armen Shirikyan

We study the motion of a particle in a random time-dependent vector field defined by the 2D Navier-Stokes system with a noise. Under suitable non-degeneracy hypotheses we prove that the empirical measures of the trajectories of the pair (velocity field, particle) satisfy the LDP with a good rate function. Moreover, we show that the law of a unique stationary

Manuel Cáceres, Gonzalo Navarro

Suffix trees are a fundamental data structure in stringology, but their space usage, though linear, is an important problem for its applications. We design and implement a new compressed suffix tree targeted to highly repetitive texts, such as large genomic collections of the same species. Our suffix tree tree builds on Block Trees, a recent Lempel-Ziv-bound

Ana Ozaki, Nicolas Troquard

We investigate the problem of learning description logic ontologies from entailments via queries, using epistemic reasoning. We introduce a new learning model consisting of epistemic membership and example queries and show that polynomial learnability in this model coincides with polynomial learnability in Angluin's exact learning model with membership a

Russell Jeter, Christopher Josef, Supreeth Shashikumar, Shamim Nemati

From 2017 to 2018 the number of scientific publications found via PubMed search using the keyword "Machine Learning" increased by 46% (4,317 to 6,307). The results of studies involving machine learning, artificial intelligence (AI), and big data have captured the attention of healthcare practitioners, healthcare managers, and the public at a time whe

Giacomo Di Gesù, Tony Lelièvre, Dorian Le Peutrec, Boris Nectoux

We consider the first exit point distribution from a bounded domain $Ω$ of the stochastic process $(X_t)_{t\ge 0}$ solution to the overdamped Langevin dynamics $$d X_t = -\nabla f(X_t) d t + \sqrt{h} \ d B_t$$ starting from the quasi-stationary distribution in $Ω$. In the small temperature regime ($h\to 0$) and under rather general assumptions on $f$ (in par

Arturo Avelino, Andrew S. Friedman, Kaisey S. Mandel, David O. Jones

We analyze a set of 89 Type Ia supernovae (SN Ia) that have both optical and near-infrared (NIR) photometry to derive distances and construct low redshift ($z < 0.04$) Hubble diagrams. We construct mean light curve (LC) templates using a hierarchical Bayesian model. We explore both Gaussian process (GP) and template methods for fitting the LCs and estimating

Wiley S. Morgan, John E. Christensen, Parker K. Hamilton, Jeremy J. Jorgensen

In the DFT community, it is common practice to use regular k-point grids (Monkhorst-Pack, MP) for Brillioun zone integration. Recently Wisesa et. al.\cite{wisesa2016efficient} and Morgan et. al.\cite{MORGAN2018424} demonstrated that generalized regular (GR) grids offer advantages over traditional MP grids. GR grids have not been widely adopted because one mu

Michael Schwarz, Samuel Weiser, Daniel Gruss

Modern CPU architectures offer strong isolation guarantees towards user applications in the form of enclaves. For instance, Intel&#39;s threat model for SGX assumes fully trusted enclaves, yet there is an ongoing debate on whether this threat model is realistic. In particular, it is unclear to what extent enclave malware could harm a system. In this work, we

Joseph D. Hart, Yuanzhao Zhang, Rajarshi Roy, Adilson E. Motter

Symmetries are ubiquitous in network systems and have profound impacts on the observable dynamics. At the most fundamental level, many synchronization patterns are induced by underlying network symmetry, and a high degree of symmetry is believed to enhance the stability of identical synchronization. Yet, here we show that the synchronizability of almost any

Alceu Bissoto, Fábio Perez, Eduardo Valle, Sandra Avila

Skin cancer is by far the most common type of cancer. Early detection is the key to increase the chances for successful treatment significantly. Currently, Deep Neural Networks are the state-of-the-art results on automated skin cancer classification. To push the results further, we need to address the lack of annotated data, which is expensive and require mu

Markus Rexroth, Christoph Schäfer, Gilles Fourestey, Jean-Paul Kneib

Strong gravitational lensing is a powerful probe of cosmology and the dark matter distribution. Efficient lensing software is already a necessity to fully use its potential and the performance demands will only increase with the upcoming generation of telescopes. In this paper, we study the possible impact of High Performance Computing techniques on a perfor

Mitchell Stern, William Chan, Jamie Kiros, Jakob Uszkoreit

We present the Insertion Transformer, an iterative, partially autoregressive model for sequence generation based on insertion operations. Unlike typical autoregressive models which rely on a fixed, often left-to-right ordering of the output, our approach accommodates arbitrary orderings by allowing for tokens to be inserted anywhere in the sequence during de

Hyewon Suh, Francesca Civano, Guenther Hasinger, Elisabeta Lusso

We investigate the multi-wavelength properties of host galaxies of 3701 X-ray-selected active galactic nuclei (AGNs) out to z~5 in the Chandra-COSMOS Legacy Survey. Thanks to the extensive multi-wavelength photometry available in the COSMOS field, we derive AGN luminosities, host stellar masses, and star formation rates (SFRs) via a multi-component SED fitti

Natsumi Makigusa, Kanta Naito

This paper is concerned with testing normality in a Hilbert space based on the maximum mean discrepancy. Specifically, we discuss the behavior of the test from two standpoints: asymptotics and practical aspects. Asymptotic normality of the test under a fixed alternative hypothesis is developed, which implies that the test has consistency. Asymptotic distribu

Geunyeong Byeon, Pascal Van Hentenryck

Recent changes in the fuel mix for electricity generation and, in particular, the increase in Gas-Fueled Power Plants (GFPP), have created significant interdependencies between the electrical power and natural gas transmission systems. However, despite their physical and economic couplings, these networks are still operated independently, with asynchronous m

Justin Tatch Moore

The purpose of this article is to give a presentation of the method of forcing aimed at someone with a minimal knowledge of set theory and logic. The emphasis will be on how the method can be used to prove theorems in ZFC.

Alexey Kokotov, Kelvin Lagota

Using Roelcke formula for the Green function, we explicitly construct a basis in the kernel of the adjoint Laplacian on a compact polyhedral surface $X$ and compute the $S$-matrix of $X$ at the zero value of the spectral parameter. We apply these results to study various self-adjoint extensions of a symmetric Laplacian on a compact polyhedral surface of genu

Krishna Pillutla, Vincent Roulet, Sham M. Kakade, Zaid Harchaoui

We present a framework to train a structured prediction model by performing smoothing on the inference algorithm it builds upon. Smoothing overcomes the non-smoothness inherent to the maximum margin structured prediction objective, and paves the way for the use of fast primal gradient-based optimization algorithms. We illustrate the proposed framework by dev

Sanjana Srivastava, Guy Ben-Yosef, Xavier Boix

The human ability to recognize objects is impaired when the object is not shown in full. &#34;Minimal images&#34; are the smallest regions of an image that remain recognizable for humans. Ullman et al. 2016 show that a slight modification of the location and size of the visible region of the minimal image produces a sharp drop in human recognition accuracy.

Farrukh Mukhamedov, Abdessatar Barhoumi, Abdessatar Souissi, Soueidy EL Gheteb

The main aim of the present paper is to establish the existence of a phase transition for the quantum Ising model with competing XY interactions within the quantum Markov chain (QMC) scheme. In this scheme, we employ the $C^*$-algebraic approach to the phase transition problem. Note that these kinde of models do not have one-dimensional analogues, i.e. the c

Jian-Pin Wu

We construct a higher derivative theory involving an axionic field and the Weyl tensor in four dimensional spacetime. Up to the first order of the coupling parameters, the charged black brane solution with momentum dissipation in a perturbative manner is constructed. Metal-insulator transitions are implemented when varying the system parameters at zero tempe

Thirupathi Guggulothu

Code smells are characteristics of the software that indicates a code or design problem which can make software hard to understand, evolve, and maintain. The code smell detection tools proposed in the literature produce different results, as smells are informally defined or are subjective in nature. To address the issue of tool subjectivity, machine learning

S. Blouin, P. Dufour, N. F. Allard, S. Salim

WD J2356$-$209 is a cool metal-polluted white dwarf whose visible spectrum is dominated by a strong and broad sodium feature. Although discovered nearly two decades ago, no detailed and realistic analysis of this star had yet been realized. In the absence of atmosphere models taking into account the nonideal high-density effects arising at the photosphere of

Ji Guan, Yuan Feng, Andrea Turrini, Mingsheng Ying

Model checking has been successfully applied to verification of computer hardware and software, communication systems and even biological systems. In this paper, we further push the boundary of its applications and show that it can be adapted for applications in quantum physics. More explicitly, we show how quantum statistical and many-body systems can be mo

Gaoxiang Zhou, Kai-Wen Liang, Natasa Miskov-Zivanov

The sensitivity analysis of biological system models can significantly contribute to identifying and explaining influences of internal or external changes on model and its elements. We propose here a comprehensive framework to study sensitivity of intra-cellular networks and to identify key intervention pathways, by performing both static and dynamic sensiti

V. V. Ryzhikov

An ergodic self-joining of an infinite rank-one transformation is a part of the weak limit of off-diagonal measures. A class of uncountaible cardinality of nonisomorphic transformations with polynomial weak closure is presented. Such actions have minimal self-joinings and some unusual spectral properties. For any set $M$ of positive integers there exists an

Prachi Telang, Kshiti Mishra, Giacomo Prando, A. K. Sood

We study the pyrochlore series (Eu$_{1-x}$Bi$_x$)$_2$Ir$_2$O$_7$ for $ 0 \leq x \leq 1$. We show that for small $x$, the lattice undergoes an anomalous contraction but the all-in/all-out and metal-to-insulator transitions remain robust, and the resistivity approaches a $1/T$ dependence at low-T, suggesting proximity to the Weyl semimetallic phase, as previou

J. L. M. van Mechelen, M. J. van Setten

To achieve room-temperature superconductivity, a mechanism is needed that provides heavy quasiparticles at room temperature. In heavy fermion systems such localization is prototypically present only at liquid helium temperatures. In these $f$-electron Kondo systems, conduction electrons magnetically couple to localized moments, enhancing their mass and scatt

Kim Ngan Le, William McLean, Kassem Mustapha

We present a new stability and convergence analysis for the spatial discretization of a time-fractional Fokker--Planck equation in a convex polyhedral domain, using continuous, piecewise-linear, finite elements. The forcing may depend on time as well as on the spatial variables, and the initial data may have low regularity. Our analysis uses a novel sequence

Pok Man Lo, Francesco Giacosa

Within the framework of the Lee model, we analyze in detail the difference between the energy derivative of the phase shift and the standard spectral function of the unstable state. The fact that the model is exactly solvable allows us to demonstrate the construction of these observables from various exact Green functions. The connection to a formula due to

Marc Raventós, Michael Tovar, Marisa Medarde, Tian Shang

This article presents a measurement technique and data analysis tool to perform 3D grain distribution mapping and indexing of oligocrystalline samples using neutrons: Laue three-dimensional neutron diffraction (Laue3DND). The approach builds on forward modelling used for correlation and multiple fitting of the measured diffraction spots relative to individua

Majdi Salman, Georgina M Klemencic, Soumen Mandal, Scott Manifold

Based on the superconducting quantum interference device (SQUID) equations described by the resistively- and capacitively-shunted junction model coupled to the equation of motion of a damped harmonic oscillator, we provide simulations to quantitatively describe the interaction between a dc SQUID and an integrated doubly clamped cantilever. We have chosen to

Kiana Mittelstaedt

We examine the aggregate behavior of one-dimensional random walks in a model known as (one-dimensional) Internal Diffusion Limited Aggregation. In this model, a sequence of $n$ particles perform random walks on the integers, beginning at the origin. Each particle walks until it reaches an unoccupied site, at which point it occupies that site and the next par

Guangzhi Sun, Chao Zhang, Phil Woodland

Speaker diarisation systems often cluster audio segments using speaker embeddings such as i-vectors and d-vectors. Since different types of embeddings are often complementary, this paper proposes a generic framework to improve performance by combining them into a single embedding, referred to as a c-vector. This combination uses a 2-dimensional (2D) self-att

Matteo Bonforte, Alessio Figalli

We investigate the homogeneous Dirichlet problem for the Fast Diffusion Equation $u_t=Δu^m$, posed in a smooth bounded domain $Ω\subset \mathbb{R}^N$, in the exponent range $m_s=(N-2)_+/(N+2)<m<1$. It is known that bounded positive solutions extinguish in a finite time $T>0$, and also that they approach a separate variable solution $u(t,x)\sim (T-t)^{1/(1-m)

Ehsan Hajiramezanali, Mahdi Imani, Ulisses Braga-Neto, Xiaoning Qian

Single-cell gene expression measurements offer opportunities in deriving mechanistic understanding of complex diseases, including cancer. However, due to the complex regulatory machinery of the cell, gene regulatory network (GRN) model inference based on such data still manifests significant uncertainty. The goal of this paper is to develop optimal classific

Michinari Kono, Jun Rekimoto

There has been a long history in electrical muscle stimulation (EMS), which has been used for medical and interaction purposes. Human-computer interaction (HCI) researchers are now working on various applications, including virtual reality (VR), notification, and learning. For the electric signals applied to the human body, various types of waveforms have be

Thomas Meier, Florian Trybel, Saiana Khandarkhaeva, Gerd Steinle-Neumann

Knowledge of the behavior of hydrogen in metal hydrides is the key for understanding their electronic properties. So far, no experimental methods exist to access these properties beyond 100 GPa, where high-Tc superconductivity emerges. Here, we present an 1H-NMR study of cubic FeH up to 200GPa. We observe a distinct deviation from the ideal metallic behavior

Leonard Vance, Jekan Thangavelautham, Erik Asphaug

There are more than 750,000 asteroids identified in the main belt. These asteroids are diverse in composition and size. Some of these asteroids can be traced back to the early solar system and can provide insight into the origins of the so-lar system, origins of Earth and origins of life. Apart from being important tar-gets for science exploration, asteroids

Zin Lin, Victor Liu, Raphaël Pestourie, Steven G. Johnson

We demonstrate optimization of optical metasurfaces over $10^5$--$10^6$ degrees of freedom in two and three dimensions, 100--1000+ wavelengths ($λ$) in diameter, with 100+ parameters per $λ^2$. In particular, we show how topology optimization, with one degree of freedom per high-resolution &#34;pixel,&#34; can be extended to large areas with the help of a lo

P. Berrutti, B. Giaccone, M. Martinello, A. Grassellino

Superconducting Radio Frequency (SRF) cavities performance preservation is crucial, from vertical test to accelerator operation. Field Emission (FE) is still one of the performance limiting factors to overcome and plasma cleaning has been proven successful by the Spallation Neutron Source (SNS), in cleaning field emitters and increasing the work function of

Zs. Bognár, Cs. Kalup, Á. Sódor

We present our results on the continuation of our survey searching for new ZZ Ceti stars, inspired by the recently launched TESS space mission. The seven targets were bright DA-type white dwarfs located close to the empirical ZZ Ceti instability strip. We successfully identified one new pulsator candidate, namely PM J22299+3024, derived detection limits for

Silas Alben

Snakes&#39; bodies are covered in scales that make it easier to slide in some directions than in others. This frictional anisotropy allows for sliding locomotion with an undulatory gait, one of the most common for snakes. Isotropic friction is a simpler situation (that arises with snake robots for example) but is less understood. In this work we regularize a

Uthman Baroudi, Abdulrahman Abu Elkhail, Hesham Alfares

A novel technique is proposed to optimize energy efficiency for wireless networks based on hierarchical mobile clustering. The new bi-level clustering technique minimizes mutual interference and energy consumption in large-scale tracking systems used in large public gatherings such as festivals and sports events. This technique tracks random movements of a l

Katarzyna Mazowiecka, Michał Miśkiewicz, Armin Schikorra

We extend the results of our recent preprint [arXiv: 1811.00515] into higher dimensions $n \geq 4$. For minimizing harmonic maps $u\in W^{1,2}(Ω,\mathbb{S}^2)$ from $n$-dimensional domains into the two dimensional sphere we prove: (1) An extension of Almgren and Lieb&#39;s linear law, namely \[\mathcal{H}^{n-3}(\textrm{sing} u) \le C \int_{\partial Ω} |\nabl

Hesham Alfares, Abdulrahman Abu Elkhail, Uthman Baroudi

A new technique is presented to design energy-efficient large-scale tracking systems based on mobile clustering. The new technique optimizes the formation of mobile clusters to minimize energy consumption in large-scale tracking systems. This technique can be used in large public gatherings with high crowd density and continuous mobility. Utilizing both Blue

Fernando A. Oliveira, Rogelma M. S. Ferreira, Luciano C. Lapas, Mendeli H. Vainstein

In this article we review classical and recent results in anomalous diffusion and provide mechanisms useful for the study of the fundamentals of certain processes, mainly in condensed matter physics, chemistry and biology. Emphasis will be given to some methods applied in the analysis and characterization of diffusive regimes through the memory function, the

Timo Nolle, Stefan Luettgen, Alexander Seeliger, Max Mühlhäuser

In this paper, we introduce BINet, a neural network architecture for real-time multi-perspective anomaly detection in business process event logs. BINet is designed to handle both the control flow and the data perspective of a business process. Additionally, we propose a set of heuristics for setting the threshold of an anomaly detection algorithm automatica

V. D. Ivashchuk

The regularization of propagators by means of a complex metric is considered. (The paper is an English translation of the first of two articles in Russian published by the author in 1987-88: V.D. Ivashchuk, Regularization by ε-metric. I, Izvestiya Akademii Nauk Moldavskoy SSR, Ser. Fiziko-tekhnicheskih i matematicheskih nauk, No 3, p. 8-17 (1987) [in Russian

Marc G. Bellemare, Nicolas Le Roux, Pablo Samuel Castro, Subhodeep Moitra

Despite many algorithmic advances, our theoretical understanding of practical distributional reinforcement learning methods remains limited. One exception is Rowland et al. (2018)&#39;s analysis of the C51 algorithm in terms of the Cramér distance, but their results only apply to the tabular setting and ignore C51&#39;s use of a softmax to produce normalized

Kaye Jiale Li, Kinwah Wu, Dinesh Singh

We investigate the spin dynamics of a millisecond pulsar (MSP) in a tightly bounded orbit around a massive black hole. These binaries are progenitors of the extreme-mass-ratio-inspirals (EMRIs) and intermediate-mass-ratio-inspirals (IMRIs) gravitational wave events. The Mathisson-Papapetrou-Dixon (MPD) formulation is used to determine the orbital motion and

Y. Ünal, Ulf-G. Meißner

Using baryon chiral perturbation theory including vector mesons, we analyse various continuum contributions to the isoscalar electromagnetic spectral functions of the nucleon induced by the leading order couplings.

Ethan C. Jackson, Mark Daley

Reinforcement learning (RL) problems often feature deceptive local optima, and learning methods that optimize purely for reward signal often fail to learn strategies for overcoming them. Deep neuroevolution and novelty search have been proposed as effective alternatives to gradient-based methods for learning RL policies directly from pixels. In this paper, w

Alessio Meneghetti, Armanda Ottaviano Quintavalle, Massimiliano Sala, Alessandro Tomasi

Digital notarization is one of the most promising services offered by modern blockchain-based solutions. We present a digital notary design with incremental security and cost reduced with respect to current solutions. A client of the service receives evidence in three steps. In the first step, evidence is received almost immediately, but a lot of trust is re

Gal Mishne, Adam S. Charles

Calcium imaging has become a fundamental neural imaging technique, aiming to recover the individual activity of hundreds of neurons in a cortical region. Current methods (mostly matrix factorization) are aimed at detecting neurons in the field-of-view and then inferring the corresponding time-traces. In this paper, we reverse the modeling and instead aim to

Yaé Ulrich Gaba

In this article, we present a new characterization of the completeness of a partial metric space--which we call \textit{orbital characterization}-- using fixed point results.

Hossein Yazdani

This paper introduces Bounded Fuzzy Possibilistic Method (BFPM) by addressing several issues that previous clustering/classification methods have not considered. In fuzzy clustering, object&#39;s membership values should sum to 1. Hence, any object may obtain full membership in at most one cluster. Possibilistic clustering methods remove this restriction. Ho

Daniela De Canditiis, Armando Guardasole

In this contribution we deal with the problem of learning an undirected graph which encodes the conditional dependence relationship between variables of a complex system, given a set of observations of this system. This is a very central problem of modern data analysis and it comes out every time we want to investigate a deeper relationship between random va

Silvia Bianchi, Graciela Nasini, Paola Tolomei, Luis Miguel Torres

Circulant contraction minors play a key role for characterizing ideal circular matrices in terms of minimally non ideal structures. In this article we prove necessary and sufficient conditions for a circular matrix $A$ to have circulant contraction minors in terms of circuits in a digraph associated with $A$. In the particular case when $A$ itself is a circu

Yaé Ulrich Gaba

In this short note, we obtain partial quasi-metric versions of Kannan&#39;s fixed point theorem for self-mappings. Moreover, we use these fixed points results to characterize a certain type of completeness in partial quasi-metric spaces. We have reported an example to support our result.

Erik Sollesnes, Ole Martin Brokstad, Rolf Klæboe, Bendik Vågen

This paper presents preliminary results towards the development of an autonomous ocean observing system using Miniature Underwater Gliders (MUGs) that can operate with the support of Unmanned Aerial Vehicles (UAVs) and Unmanned Surface Vessels (USVs) for deployment, recovery, battery charging, and communication relay. The system reduces human intervention to

Yaé Ulrich Gaba, Collins Amburo Agyingi, Domini Jocema Leko

In this paper, we give and prove two Chatterjea type fixed point theorems on partial $b$-metric space. We propose an extension to the Banach contraction principle on partial $b$-metric space which was already presented by Shukla and also study some related results on the completion of a partial metric type space. In particular, we prove a joint Chatterjea-Ka

Bartolomé Coll, Joan Josep Ferrando, Juan Antonio Sáez

The necessary and sufficient condition for a conservative perfect fluid energy tensor to be the energetic evolution of a classical ideal gas is obtained. This condition forces the square of the speed of sound to have the form $c_s^2 = \frac{γp}{ρ+p}$ in terms of the hydrodynamic quantities, energy density $ρ$ and pressure $p$, $γ$ being the (constant) adiaba

Nikolaj Tatti, Michael Mampaey

Assessing the quality of discovered results is an important open problem in data mining. Such assessment is particularly vital when mining itemsets, since commonly many of the discovered patterns can be easily explained by background knowledge. The simplest approach to screen uninteresting patterns is to compare the observed frequency against the independenc

Daniela De Canditiis, Italia De Feis

A new technique for nonparametric regression of multichannel signals is presented. The technique is based on the use of the Rational-Dilation Wavelet Transform (RADWT), equipped with a tunable Q-factor able to provide sparse representations of functions with different oscillations persistence. In particular, two different frames are obtained by two RADWT wit

Chaitanya Kaul, Suresh Manandhar, Nick Pears

We propose a novel technique to incorporate attention within convolutional neural networks using feature maps generated by a separate convolutional autoencoder. Our attention architecture is well suited for incorporation with deep convolutional networks. We evaluate our model on benchmark segmentation datasets in skin cancer segmentation and lung lesion segm

Alessandra Candian, Marina Gomes Rachid, Heather MacIsaac, Viktor N. Staroverov

We report a computational study of the stability and infrared (IR) vibrational spectra of neutral and singly ionised fullerene cages containing between 44 and 70 carbon atoms. The stability is characterised in terms of the standard enthalpy of formation per CC bond, the HOMO-LUMO gap, and the energy required to eliminate a C$_2$ fragment. We compare the simu

Hasan Asyari Arief, Ulf Geir Indahl, Geir-Harald Strand, Håvard Tveite

Advances in techniques for automated classification of pointcloud data introduce great opportunities for many new and existing applications. However, with a limited number of labeled points, automated classification by a machine learning model is prone to overfitting and poor generalization. The present paper addresses this problem by inducing controlled noi

Carlos Esteve

We consider the diffusive Hamilton-Jacobi equation $u_t - Δu = |\nabla u|^p$ in a bounded planar domain with zero Dirichlet boundary condition. It is known that, for $p>2$, the solutions to this problem can exhibit gradient blow-up (GBU) at the boundary. In this paper we study the possibility of the GBU set being reduced to a single point. In a previous work

Siguo Bi, Zhaoxi Fang, Xiaojun Yuan, Xin Wang

In cellular heterogeneous networks (HetNets), a number of distributed base stations cooperatively provide services to multiple mobile users. This paper addresses joint base-station activation and coordinated beamforming design for downlink transmission in HetNets. To this end, a mixed integer program is formulated to optimize the total power consumption of a

Stefano Bianchi, Matteo Guainazzi, Ari Laor, Jonathan Stern

The observed spatial and kinematic overlap between soft X-ray emission and the Narrow Line Region (NLR) in obscured Active Galactic Nuclei (AGN) yields compelling evidence that relatively low-density gas co-exists with higher density gas on scales as large as 100s of pc. This is commonly interpreted as evidence for a constant gas pressure multiphase medium,

Rolf Hennicker, Alexandre Madeira, Alexander Knapp

We propose $\mathcal{E}^{\downarrow}$-logic as a formal foundation for the specification and development of event-based systems with local data states. The logic is intended to cover a broad range of abstraction levels from abstract requirements specifications up to constructive specifications. Our logic uses diamond and box modalities over structured action

Cristian Pisano, Umberto D&#39;Alesio, Carlo Flore, Francesco Murgia

Within the color gauge invariant generalized parton model (CGI-GPM), which includes initial and final state interactions in a transverse momentum dependent formalism, we present the complete results, at leading order in perturbative QCD, for transverse single-spin asymmetries in the inclusive hadroproduction of $J/ψ$ and $D$ mesons, pions and direct photons.

Wen-Hao Xu, Xi-Le Zhao, Michael Ng

Recently, there has been a lot of research into tensor singular value decomposition (t-SVD) by using discrete Fourier transform (DFT) matrix. The main aims of this paper are to propose and study tensor singular value decomposition based on the discrete cosine transform (DCT) matrix. The advantages of using DCT are that (i) the complex arithmetic is not invol

Dong-Su Kim, Yong Whan Choi, Yun-Jin Jeong, Jongsung Park

We propose a novel cantilever device integrated with a polydimethylsiloxane (PDMS)-encapsulated crack sensor that directly measures the cardiac contractility. The crack sensor was chemically bonded to a PDMS thin layer to form a sandwiched structure which allows to be operated very stably in culture media. The reliability of the proposed crack sensor has imp

Amin Farajzadeh, Ozgur Ercetin, Halim Yanikomeroglu

The recent evolution of ambient backscattering technology has the potential to provide long-range and low-power wireless communications. In this work, we study the unmanned aerial vehicle (UAV)-assisted backscatter networks where the UAV acts both as a mobile power transmitter and as an information collector. We aim to maximize the number of successfully dec

Xiang Yang, Qian Zhu, Chang Liu, Wei Wang

In many natural and artificial devices diffusive transport takes place in confined geometries with corrugated boundaries. Such boundaries cause both entropic and hydrodynamic effects, which have been studied only for the case of spherical particles. Here we experimentally investigate diffusion of particles of elongated shape confined into a corrugated quasi-

Z. Luo, L. Qi, Ph. L. Toint

A generalization of the Bernstein matrix concentration inequality to random tensors of general order is proposed. This generalization is based on the use of Einstein products between tensors, from which a strong link can be established between matrices and tensors, in turn allowing exploitation of existing results for the former.

William N. Havard, Jean-Pierre Chevrot, Laurent Besacier

We investigate the behaviour of attention in neural models of visually grounded speech trained on two languages: English and Japanese. Experimental results show that attention focuses on nouns and this behaviour holds true for two very typologically different languages. We also draw parallels between artificial neural attention and human attention and show t

Zizhao Zhang, Adriana Romero, Matthew J. Muckley, Pascal Vincent

The goal of MRI reconstruction is to restore a high fidelity image from partially observed measurements. This partial view naturally induces reconstruction uncertainty that can only be reduced by acquiring additional measurements. In this paper, we present a novel method for MRI reconstruction that, at inference time, dynamically selects the measurements to

Michael Anton Hoefnagel

We introduce the notion of a majority category --- the categorical counterpart of varieties of universal algebras admitting a majority term. This notion can be thought to capture properties of the category of lattices, in a way that parallels how Mal&#39;tsev categories capture properties of the category of groups. Among algebraic majority categories are the

Leonardo Martini, Zongping Chen, Neeraj Mishra, Gabriela Borin Barin

Graphene nanoribbons (GNRs) are a novel and intriguing class of materials in the field of nanoelectronics, since their properties, solely defined by their width and edge type, are controllable with high precision directly from synthesis. Here we study the correlation between the GNR structure and the corresponding device electrical properties. We investigate

Lei Feng, Bo An, Shuo He

It is well-known that exploiting label correlations is crucially important to multi-label learning. Most of the existing approaches take label correlations as prior knowledge, which may not correctly characterize the real relationships among labels. Besides, label correlations are normally used to regularize the hypothesis space, while the final predictions

Lei Feng, Bo An

Partial label learning deals with the problem where each training instance is assigned a set of candidate labels, only one of which is correct. This paper provides the first attempt to leverage the idea of self-training for dealing with partially labeled examples. Specifically, we propose a unified formulation with proper constraints to train the desired mod

Christophe Minetti, Vassanti Audemar, Thomas Podgorski, Gwennou Coupier

An exhaustive description of the dynamics under shear flow of a large number of red blood cells in dilute regime is proposed, which highlights and takes into account the dispersion in cell properties within a given blood sample. Physiological suspending fluid viscosity is considered, a configuration surprisingly seldom considered in experimental studies, as

Oliver Kley, Claudia Klüppelberg, Sandra Paterlini

We introduce a statistical model for operational losses based on heavy-tailed distributions and bipartite graphs, which captures the event type and business line structure of operational risk data. The model explicitly takes into account the Pareto tails of losses and the heterogeneous dependence structures between them. We then derive estimators for individ

Yang Su, Yansong Gao, Omid Kavehei, Damith C. Ranasinghe

Recently, we have witnessed the emergence of intermittently powered computational devices, an early example is the Intel WISP (Wireless Identification and Sensing Platform). How we engineer basic security services to realize mutual authentication, confidentiality and preserve privacy of information collected, stored and transmitted by, and establish the vera

Gamal Sallam, Uthman Baroudi

In many applications, robots autonomous deployment is preferable and sometimes it is the only affordable solution. To address this issue, virtual force (VF) is one of the prominent approaches to performing multirobot deployment autonomously. However, most of the existing VF-based approaches consider only a uniform deployment to maximize the covered area whil

Diana Barseghyan, Pavel Exner

We investigate spectral properties of the operator describing a quantum particle confined to a planar domain $Ω$ rotating around a fixed point with an angular velocity $ω$ and demonstrate several properties of its principal eigenvalue $λ_1^ω$. We show that as a function of rotating center position it attains a unique maximum and has no other extrema provided

William Alston

Accreting compact objects show variations in source flux over a broad range of timescales and in all wavebands. The light curves typically show a lognormal distribution of flux and a linear relation between flux and rms. It has been demonstrated that an exponential transform of an underlying (and unobserved) Gaussian stochastic process provides a very good d

Wojciech Kotłowski, Gergely Neu

We consider a partial-feedback variant of the well-studied online PCA problem where a learner attempts to predict a sequence of $d$-dimensional vectors in terms of a quadratic loss, while only having limited feedback about the environment&#39;s choices. We focus on a natural notion of bandit feedback where the learner only observes the loss associated with i

Urtzi Buijs, José M. Moreno-Fernández

We provide two criteria for discarding the formality of a differential graded Lie algebra in terms of higher Whitehead brackets, which are the Lie analogue of the Massey products of a differential graded associative algebra. We also show that formality of a differential graded Lie algebra is not equivalent to the collapse of the Quillen spectral sequence. Fi

Eliandro Rodrigues Cirilo, Alessandra Negrini Dalla Barba, Neyva Maria Lopes Romeiro, Paulo Laerte Natti

In this paper we developed a numerical methodology to study some incompressible fluid flows without free surface, using the curvilinear coordinate system and whose edge geometry is constructed via parametrized spline. First, we discussed the representation of the Navier-Stokes and continuity equations on the curvilinear coordinate system, along with the auxi

Yansong Gao, Yang Su, Wei Yang, Shiping Chen

A securely maintained key is the premise upon which data stored and transmitted by ubiquitously deployed resource limited devices, such as those in the Internet of Things (IoT), are protected. However, many of these devices lack a secure non-volatile memory (NVM) for storing keys because of cost constraints. Silicon physical unclonable functions (PUFs) offer

A. B. Higgins, A. J. van der Horst, R. L. C. Starling, G. Anderson

We investigate the afterglow of GRB 140713A, a gamma-ray burst (GRB) that was detected and relatively well-sampled at X-ray and radio wavelengths, but was not present at optical and near-infrared wavelengths, despite searches to deep limits. We present the emission spectrum of the likely host galaxy at $z = 0.935$ ruling out a high-redshift explanation for t

Wojciech Nawalaniec

The main goal of this paper is to present the application of structural sums, mathematical objects originating from the computational materials science, in construction of a feature space vector of 2D random composites simulated by distributions of non-overlapping disks on the plane. Construction of the feature vector enables the immediate application of mac

Tobias Vogl, Ruvi Lecamwasam, Ben C. Buchler, Yuerui Lu

Sources of pure and indistinguishable single-photons are critical for near-future optical quantum technologies. Recently, color centers hosted by two-dimensional hexagonal boron nitride (hBN) have emerged as a promising platform for high luminosity room temperature single-photon sources. Despite the brightness of the emitters, the spectrum is rather broad an