November 2018 arXiv papers — page 59

Eric Aristidi, Yan Fantei-Caujolle, Julien Chabé, Catherine Renaud

We present some statistics of turbulence monitoring at the Plateau de Calern (France), with the Generalised Differential Image Motion Monitor (GDIMM). This instrument allows to measure integrated parameters of the atmospheric turbulence, i.e. seeing, isoplanatic angle, coherence time and outer scale, with 2 minutes time resolution. It is running routinely si

Peter Panov, Alexei Savvateev

The geometric median of a domain is the point that minimises the average distance from itself to the points of the domain. We will give a gradient system of equations that defines the geometric median of a triangular domain and will prove a simple geometric property of the median. This property states that all three average distances from the median to the s

Eric Aristidi

This paper gives an introduction to the theory of orthogonal projection of functions or signals. Several kinds of decomposition are explored: Fourier, Fourier-Legendre, Fourier-Bessel series for 1D signals, and Spherical Harmonic series for 2D signals. We show how physical conditions and/or geometry can guide the choice of the base of functions for the decom

Yize Stephanie Li, John Nguyen

The development of Si-compatible active photonic devices is a high priority in computer and modern electronics industry. Ge is compatible with Si and is a promising light emission material. Nearly all Ge-on-Si materials reported so far were grown using toxic precursor gases. Here we demonstrate the creation of Ge films on Si substrates through physical vapor

Sanjoy K. Mahatha, Arlette S. Ngankeu, Nicki Frank Hinsche, Ingrid Mertig

The electron-phonon coupling strength in the spin-split valence band maximum of single-layer MoS$_2$ is studied using angle-resolved photoemission spectroscopy and density functional theory-based calculations. Values of the electron-phonon coupling parameter $λ$ are obtained by measuring the linewidth of the spin-split bands as a function of temperature and

Fabio Antonelli, Alessandro Ramponi, Sergio Scarlatti

We consider the problem of computing the Credit Value Adjustment ({CVA}) of a European option in presence of the Wrong Way Risk ({WWR}) in a default intensity setting. Namely we model the asset price evolution as solution to a linear equation that might depend on different stochastic factors and we provide an approximate evaluation of the option's price,

Jiaxin Cheng, Yue Wu, Wael Abd-Almageed, Prem Natarajan

The image-to-GPS verification problem asks whether a given image is taken at a claimed GPS location. In this paper, we treat it as an image verification problem -- whether a query image is taken at the same place as a reference image retrieved at the claimed GPS location. We make three major contributions: 1) we propose a novel custom bottom-up pattern match

Timothy D. Brandt

This paper presents a cross-calibrated catalog of Hipparcos and Gaia astrometry to enable their use in measuring changes in proper motion, i.e., accelerations in the plane of the sky. The final catalog adopts the reference frame of the second Gaia data release (DR2) and locally cross-calibrates both the scaled Hipparcos-Gaia DR2 positional differences and th

Kazumi Suematsu, Haruo Ogura, Seiiti Inayama, Toshihiko Okamoto

We present the alternative derivation of the excluded volume equation. The resulting equation is mathematically identical to the one proposed in the preceding paper. As a result, the theory reproduces well the observed points by SANS (small angle neutron scattering) experiments. The equation is applied to the coil-globule transition of branched molecules. It

Soyeon Park, Sangho Lee, Wen Xu, Hyungon Moon

Intel memory protection keys (MPK) is a new hardware feature to support thread-local permission control on groups of pages without requiring modification of page tables. Unfortunately, its current hardware implementation and software supports suffer from security, scalability, and semantic-gap problems: (1) MPK is vulnerable to protection-key-use-after-free

G. Ali Mansoori, Enrico Matteoli

The statistical mechanical basis of the fluctuation theory of mixtures is reviewed. An overview of the statistical mechanical relations between the microscopic properties of a system and its macroscopic properties is presented. The distribution functions in equilibrium systems are defined and relations between the distribution functions and thermodynamic pro

Felix G. Hamza-Lup, Stephen White

Technology is influencing education, providing new delivery and assessment models. A combination between online and traditional course, the hybrid (blended) course, may present a solution with many benefits as it provides a gradual transition towards technology enabled education. This research work provides a set of definitions for several course delivery ap

Doga Murat Kurkcuoglu, C. A. R. Sá de Melo

We describe the emergence of color superfluidity in ultra-cold fermions induced by color-orbit and color-flip fields that transform a conventional singlet-pairing s-wave system into an unconventional non-s-wave superfluid with quintuplet pairing. We show that the tuning of interactions, color-orbit and color-flip fields transforms a momentum-independent scal

Un-Hyang Ho, Hye-Ok Kong

It is important to study on genes affecting to growing environment of main crops. Especially the recognition problem of promoter region, which is the problem to predict whether DNA sequences contain promoter regions or not, is prior to find abiotic stress-inducible genes. Studies on predicting promoter sequences in DNA sequences have been studied by traditio

Bolin Liu, Xiao Shu, Xiaolin Wu

In many applications of deep learning, particularly those in image restoration, it is either very difficult, prohibitively expensive, or outright impossible to obtain paired training data precisely as in the real world. In such cases, one is forced to use synthesized paired data to train the deep convolutional neural network (DCNN). However, due to the unavo

Francesco Fusco

The growing complexity of the power grid, driven by increasing share of distributed energy resources and by massive deployment of intelligent internet-connected devices, requires new modelling tools for planning and operation. Physics-based state estimation models currently used for data filtering, prediction and anomaly detection are hard to maintain and ad

Si Tiep Dinh, Krzysztof Kurdyka, Tien Son Pham

In this paper, we prove a version of global Łojasiewicz inequality for $C^1$ semialgebraic functions and relate its existence to the set of asymptotic critical values.

Jennifer D. Schuler, Christopher M. Barr, Nathan M. Heckman, Guild Copeland

Nanocrystalline metals typically have high fatigue strengths, but low resistance to crack propagation. Amorphous intergranular films are disordered grain boundary complexions that have been shown to delay crack nucleation and slow crack propagation during monotonic loading by diffusing grain boundary strain concentrations, suggesting they may also be benefic

Enzhi Li

Stationary stochastic processes with independent increments, of which the Poisson process is a prominent example, are widely used to describe real world events. With the basic assumption that a counting process is stationary and has independent increments, here I derive two integral equations to capture the time evolution of any such process. In order to sol

Zhizhong Wang, Lei Zhao, Wei Xing, Dongming Lu

Recent studies using deep neural networks have shown remarkable success in style transfer especially for artistic and photo-realistic images. However, the approaches using global feature correlations fail to capture small, intricate textures and maintain correct texture scales of the artworks, and the approaches based on local patches are defective on global

Jun Hee Kim

Baseball is one of the few sports in which each team plays a game nearly everyday. For instance, in the baseball league in South Korea, namely the KBO (Korea Baseball Organization) league, every team has a game everyday except for Mondays. This consecutiveness of the KBO league schedule could make a team's match outcome be associated to the results of re

Gaoang Wang, Yizhou Wang, Haotian Zhang, Renshu Gu

Multi-object tracking (MOT) is an important and practical task related to both surveillance systems and moving camera applications, such as autonomous driving and robotic vision. However, due to unreliable detection, occlusion and fast camera motion, tracked targets can be easily lost, which makes MOT very challenging. Most recent works treat tracking as a r

Leonard Gross

In the canonical formalism for the free electromagnetic field a solution to Maxwell's equations is customarily identified with its initial gauge potential (in Coulomb gauge) and initial electric field, which together determine a point in phase space. The solutions to Maxwell's equations, all of whose plane waves in their plane wave expansions have po

Junjie Huang, Wei Zou, Zheng Zhu, Jiagang Zhu

Obtained by moving object detection, the foreground mask result is unshaped and can not be directly used in most subsequent processes. In this paper, we focus on this problem and address it by constructing an optical flow based moving foreground analysis framework. During the processing procedure, the foreground masks are analyzed and segmented through two c

Christoph Hauert, Jacek Miȩkisz

The sampling of interaction partners depends on often implicit modelling assumptions, yet has marked effects on the dynamics in evolutionary games. One particularly important aspect is whether or not competitors also interact. Population structures naturally affect sampling such that in a microscopic interpretation of the replicator dynamics in well-mixed po

Yijun Xiao, William Yang Wang

Reliable uncertainty quantification is a first step towards building explainable, transparent, and accountable artificial intelligent systems. Recent progress in Bayesian deep learning has made such quantification realizable. In this paper, we propose novel methods to study the benefits of characterizing model and data uncertainties for natural language proc

Adam Czajka, Zhaoyuan Fang, Kevin W. Bowyer

We propose a new iris presentation attack detection method using three-dimensional features of an observed iris region estimated by photometric stereo. Our implementation uses a pair of iris images acquired by a common commercial iris sensor (LG 4000). No hardware modifications of any kind are required. Our approach should be applicable to any iris sensor th

Xiaohong Lan

Consider an isotropic spherical Gaussian random field T with values in R^{d}. We investigate two problems: (i) When is the level set T^{-1}(t) nonempty with positive probability for any t\in R^{d} ? (ii) If the level set is nonempty, what is its Hausdorff measure? These two question are not only very important in potential theory for random fields, but also

Manveen Kaur, Anjan Rayamajhi, Mizanur Rahman, Jim Martin

Cooperative Adaptive Cruise Control (CACC) is a pivotal vehicular application that would allow transportation field to achieve its goals of increased traffic throughput and roadway capacity. This application is of paramount interest to the vehicular technology community with a large body of literature dedicated to research within different aspects of CACC, i

Shinhoo Kang, Tan Bui-Thanh, Todd Arbogast

We develop a high-order hybridized discontinuous Galerkin (HDG) method for a linear degenerate elliptic equation arising from a two-phase mixture of mantle convection or glacier dynamics. We show that the proposed HDG method is well-posed by using an energy approach. We derive ${\it a priori}$ error estimates for the proposed HDG method on simplicial meshes

Jeff Anderson, Engin Kayraklioglu, Volker Sorger, Tarek El-Ghazawi

The call for efficient computer architectures has introduced a variety of application-specific compute engines to the heterogeneous computing landscape. One particular engine, the analog mesh computer, has been well received due to its ability to efficiently solve partial differential equations by eliminating the iterative stages common to numerical solvers.

Sami El-Ferik, Hashim. A. Hashim, Frank L. Lewis

This paper proposes a neuro-adaptive distributive cooperative tracking control with prescribed performance function (PPF) for highly nonlinear multi-agent systems. PPF allows error tracking from a predefined large set to be trapped into a predefined small set. The key idea is to transform the constrained system into unconstrained one through transformation o

Ju-Jun Xie, Eulogio Oset

A $Σ^*$ resonance with spin-parity $J^P = 1/2^-$ and mass in the vicinity of the $\bar{K}N$ threshold has been predicted in the unitary chiral approach and inferred from the analysis of CLAS data on the $γp \to K^+ π^0 Σ^0$ reaction. In this work, based on the dominant Cabibbo favored weak decay mechanism, we perform a study of $Λ_c^+ \to π^+ π^0 Σ^*$ with t

Swapnil Dhamal, Walid Ben-Ameur, Tijani Chahed, Eitan Altman

We propose a setting for two-phase opinion dynamics in social networks, where a node's final opinion in the first phase acts as its initial biased opinion in the second phase. In this setting, we study the problem of two camps aiming to maximize adoption of their respective opinions, by strategically investing on nodes in the two phases. A node's ini

Wenxuan Wu, Zhongang Qi, Li Fuxin

Unlike images which are represented in regular dense grids, 3D point clouds are irregular and unordered, hence applying convolution on them can be difficult. In this paper, we extend the dynamic filter to a new convolution operation, named PointConv. PointConv can be applied on point clouds to build deep convolutional networks. We treat convolution kernels a

Mike Gartrell, Elvis Dohmatob, Jon Alberdi

Determinantal point processes (DPPs) have attracted significant attention as an elegant model that is able to capture the balance between quality and diversity within sets. DPPs are parameterized by a positive semi-definite kernel matrix. While DPPs have substantial expressive power, they are fundamentally limited by the parameterization of the kernel matrix

Samuel Gomes, Carlos Martinho, João Dias

Nowadays, big effort is being put to study gamification and how game elements can be used to engage players. In this scope, we believe there is a growing need to explore the impact game mechanics have on the players' interactions and perception. This work focuses on the application of game mechanics to lead players to achieve certain types of social inte

Sung-Sik Lee

Relatively local Hamiltonians are a class of background independent non-local Hamiltonians from which local theories emerge within a set of short-range entangled states. The dimension, topology and geometry of the emergent local theory is determined by the initial state to which the Hamiltonian is applied. In this paper, we study dynamical properties of a si

Kyle Kastner, João Felipe Santos, Yoshua Bengio, Aaron Courville

Recent character and phoneme-based parametric TTS systems using deep learning have shown strong performance in natural speech generation. However, the choice between character or phoneme input can create serious limitations for practical deployment, as direct control of pronunciation is crucial in certain cases. We demonstrate a simple method for combining m

Hugo García-Compeán, Norma Quiroz

We establish a relation between the boundary and the topological entropies for the conformal minimal models in some of the simplest models of the unitary A-A series. We show that in these models the boundary entropy is a difference of topological entropies. Furthermore, we define the crosscap entropy as the analog to the boundary entropy in non-oriented theo

Marco A. S. Trindade, Sergio Floquet, Lourival M. S. Filho

We developed a strategic of optimal portfolio based on information theory and Tsallis statistics. The growth rate of a stock market is defined by using $q$-deformed functions and we find that the wealth after n days with the optimal portfolio is given by a $q$-exponential function. In this context, the asymptotic optimality is investigated on causal portfoli

Ting Ye, Jun Shao

Covariate-adaptive randomization is popular in clinical trials with sequentially arrived patients for balancing treatment assignments across prognostic factors which may have influence on the response. However, existing theory on tests for treatment effect under covariate-adaptive randomization is limited to tests under linear or generalized linear models, a

Giacomo Vaccario, Luca Verginer, Frank Schweitzer

High skill labour is an important factor underpinning the competitive advantage of modern economies. Therefore, attracting and retaining scientists has become a major concern for migration policy. In this work, we study the migration of scientists on a global scale, by combining two large data sets covering the publications of 3.5 Mio scientists over 60 year

Saadet S. Özer

In the present paper we consider a general family of two dimensional wave equations which represents a great variety of linear and nonlinear equations within the framework of the transformations of equivalence groups. We have investigated the existence problem of point transformations that lead mappings between linear and nonlinear members of particular fami

Yunze Man, Xinshuo Weng, Xi Li, Kris Kitani

We focus on estimating the 3D orientation of the ground plane from a single image. We formulate the problem as an inter-mingled multi-task prediction problem by jointly optimizing for pixel-wise surface normal direction, ground plane segmentation, and depth estimates. Specifically, our proposed model, GroundNet, first estimates the depth and surface normal i

George Bouzianis, Lane Hughston

We consider the problem of determining the Lévy exponent in a Lévy model for asset prices given the price data of derivatives. The model, formulated under the real-world measure $\mathbb P$, consists of a pricing kernel $\{π_t\}_{t\geq0}$ together with one or more non-dividend-paying risky assets driven by the same Lévy process. If $\{S_t\}_{t\geq0}$ denotes

Natalia Antropova, Andrew L. Beam, Brett K. Beaulieu-Jones, Irene Chen

This volume represents the accepted submissions from the Machine Learning for Health (ML4H) workshop at the conference on Neural Information Processing Systems (NeurIPS) 2018, held on December 8, 2018 in Montreal, Canada.

Tianlin Liu, Lyle Ungar, João Sedoc

Word vectors are at the core of many natural language processing tasks. Recently, there has been interest in post-processing word vectors to enrich their semantic information. In this paper, we introduce a novel word vector post-processing technique based on matrix conceptors (Jaeger2014), a family of regularized identity maps. More concretely, we propose to

Rodrigo Nemmen, Raniere de Menezes, Vasileios Paschalidis

We report the analysis of the gamma-ray variability of NGC 1275--the radio galaxy at the center of the Perseus cluster. NGC 1275 has been observed continuously with the Fermi Large Area Telescope over the last nine years. We applied different time-domain analysis methods including Fourier, wavelets and Bayesian methods, in order to search for quasi-periodic

Bryan A. Plummer, Kevin J. Shih, Yichen Li, Ke Xu

Most existing work that grounds natural language phrases in images starts with the assumption that the phrase in question is relevant to the image. In this paper we address a more realistic version of the natural language grounding task where we must both identify whether the phrase is relevant to an image and localize the phrase. This can also be viewed as

Jacob M. Springer, Charles S. Strauss, Austin M. Thresher, Edward Kim

Although deep learning has shown great success in recent years, researchers have discovered a critical flaw where small, imperceptible changes in the input to the system can drastically change the output classification. These attacks are exploitable in nearly all of the existing deep learning classification frameworks. However, the susceptibility of deep spa

Miloš S. Kurilić

A complete first order theory of a relational signature is called monomorphic iff all its models are monomorphic (i.e. have all the $n$-element substructures isomorphic, for each positive integer $n$). We show that a complete theory ${\mathcal T}$ having infinite models is monomorphic iff it has a countable monomorphic model and confirm the Vaught conjecture

Stefan Webb, Tom Rainforth, Yee Whye Teh, M. Pawan Kumar

We present a new approach to assessing the robustness of neural networks based on estimating the proportion of inputs for which a property is violated. Specifically, we estimate the probability of the event that the property is violated under an input model. Our approach critically varies from the formal verification framework in that when the property can b

Nobuaki Yagita

Let $G$ be a compact Lie group and $T$ its maximal torus. In this paper, we try to compute $gr_{\gamma}^*(G/T)$ the graded ring associated with the gamma filtration of the complex $K$-theory $K^0(G/T)$ for $G=Spin(n)$. In particular, we give a counterexample for a conjecture by Karpenko when $G=Spin(17)$. The arguments for $E_7$ in $\S 11$ of the old version

Yashaswini Murthy, Ravi Banavar

The need to develop models to predict the motion of microrobots, or robots of a much smaller scale, moving in fluids in a low Reynolds number regime, and in particular, in non Newtonian fluids, cannot be understated. The article develops a Lagrangian based model for one such mechanism - a two-link mechanism termed a microscallop, moving in a low Reynolds num

Massimo Carraturo, Elisabetta Rocca, Elena Bonetti, Dietmar Hömberg

In the present work we introduce a novel graded-material design based on phase-field and topology optimization. The main novelty of this work comes from the introduction of an additional phase-field variable in the classical single-material phase-field topology optimization algorithm. This new variable is used to grade the material properties in a continuous

Peter K. F. Kuhfittig

It is shown in this note that a noncommutative-geometry background determines the modified-gravity function $f(R)$ for modeling dark matter.

Gaurav Chaudhary, Dmitry K. Efimkin, Allan H. MacDonald

We derive exact sum-rules that relate the tunneling density of states (TDOS) of spinful electrons in the fractional quantum Hall (FQH) regime to the spin-dependent many body ground state correlation energy. Because the tunneling process is spin-conserving, the 2D (two-dimensional) to 2D tunneling current $I$ at a given bias voltage $V$ in a spin-polarized sy

Genildo de Jesus Nery

In this paper we establish lower and upper bounds for the cardinality of the profinite genus of the fundamental group $\pi_{1}(M_A)\cong (\mathbb{Z} \times \mathbb{Z})\rtimes_{A}\mathbb{Z}$ of a torus bundle $M_{A}$ in terms of the number of ideal classes of the order $\mathbb{Z}[\lambda]$, where $\lambda$ is an eigenvalue of the matrix $A$ in $\mathrm{GL}_{

Vidhi Lalchand, A. C. Faul

In their standard form Gaussian processes (GPs) provide a powerful non-parametric framework for regression and classificaton tasks. Their one limiting property is their $\mathcal{O}(N^{3})$ scaling where $N$ is the number of training data points. In this paper we present a framework for GP training with sequential selection of training data points using an i

Maciej Rybczyński, Grzegorz Wilk, Zbigniew Włodarczyk

Multiplicity distributions exhibit, after closer inspection, peculiarly enhanced void probability and oscillatory behavior of the modified combinants. We discuss the possible sources of these oscillations and their impact on our understanding of the multiparticle production mechanism. Theoretical understanding of both phenomena within the class of compound d

Nadia Lafrenière

This paper describes a combinatorial way of obtaining all the eigenvalues of the symmetrized shuffling operators introduced by Victor Reiner, Franco Saliola and Volkmar Welker. It allows us to prove their conjecture that these eigenvalues are integers. This work generalizes the case of the random-to-random Markov chain.

José Luís da Silva, Mohamed Erraoui

The generalized grey Brownian motion is a time continuous self-similar with stationary increments stochastic process whose one dimensional distributions are the fundamental solutions of a stretched time fractional differential equation. Moreover, the distribution of the time-changed Brownian motion by an inverse stable process solves the same equation, hence

Michael J. A. Smith, Zeshan Yousaf, Prasad Potluri, William J. Parnell

The mechanical response of syntactic foams comprising hollow thermoplastic microspheres (HTMs) embedded in a polyurethane matrix were experimentally examined under uniaxial compressive strain. Phenomenological strain energy models were subsequently developed to capture both the axial stress-strain and transverse strain response of the foams. HTM syntactic fo

Wei Dai, Zhao Liu

In this paper, we are concerned with static Schr\"{o}dinger-Hartree and Schr\"{o}dinger-Maxwell equations with combined nonlinearities. We derive the explicit forms for positive solution $u$ in the critical case and non-existence of nontrivial nonnegative solutions in the subcritical cases (see Theorem \ref{Thm0} and \ref{Thm1}). The arguments used in our pr

Hochul Shin, Hyeon Cho, Dongyi Kim, Daekwan Ko

Humans can infer approximate interaction force between objects from only vision information because we already have learned it through experiences. Based on this idea, we propose a recurrent convolutional neural network-based method using sequential images for inferring interaction force without using a haptic sensor. For training and validating deep learnin

Dhanya Jothimani, Ravi Shankar, Surendra S. Yadav

With the advent of Web 2.0, various types of data are being produced every day. This has led to the revolution of big data. Huge amount of structured and unstructured data are produced in financial markets. Processing these data could help an investor to make an informed investment decision. In this paper, a framework has been developed to incorporate both s

Farzad Kianvash, Marco Fanizza, Vittorio Giovannetti

The impossibility of undoing a mixing process is analysed in the context of quantum information theory. The optimal machine to undo the mixing process is studied in the case of pure states, focusing on qubit systems. Exploiting the symmetry of the problem we parametrise the optimal machine in such a way that the number of parameters grows polynomially in the

Antonio Irpino, Francisco De Carvalho, Rosanna Verde, Antonio Balzanella

The paper deals with a Batch Self Organizing Map algorithm (DBSOM) for data described by distributional-valued variables. This kind of variables is characterized to take as values one-dimensional probability or frequency distributions on a numeric support. The objective function optimized in the algorithm depends on the choice of the distance measure. Accord

Cheng-Yaw Low, Jaewoo Park, Andrew Beng-Jin Teoh

Stacking-based deep neural network (S-DNN) is aggregated with pluralities of basic learning modules, one after another, to synthesize a deep neural network (DNN) alternative for pattern classification. Contrary to the DNNs trained end to end by backpropagation (BP), each S-DNN layer, i.e., a self-learnable module, is to be trained decisively and independentl

A. Gauzzi, F. Milton, V. Pascotto Gastaldo, M. Verseils

Pyroelectric current and magnetoelectric coupling measurements on polycrystalline samples of the quadruple perovskite (LaMn$_{3}$)Mn$_{4}$O$_{12}$ give evidence of ferroelectricity driven by the antiferromagnetic ordering of the $B$-site Mn$^{3+}$ ions at $T_{N,B}$=78 K with record values of remnant electric polarization up to $P$=0.56 $\mu$C cm$^{-2}$. X-ra

M. Mena, N. Hänni, S. Ward, E. Hirtenlechner

We have used neutron spectroscopy to investigate the spin dynamics of the quantum (S = 1/2) antiferromagnetic Ising chains in RbCoCl3. The structure and magnetic interactions in this material conspire to produce two magnetic phase transitions at low temperatures, presenting an ideal opportunity for thermal control of the chain environment. The high-resolutio

A. P. Garrão, N. Martins-Ferreira, M. Raposo, M. Sobral

We show that the category of cancellative conjugation semigroups is weakly Mal'tsev and give a characterization of all admissible diagrams there. In the category of cancellative conjugation monoids we describe, for Schreier split epimorphisms with codomain B and kernel X, all morphisms h from X to B which induce a reflexive graph, an internal category or

Joseph L. Garrett, David A. T. Somers, Kyle Sendgikoski, Jeremy N. Munday

Quantum electrodynamic fluctuations cause an attractive force between metallic surfaces. At separations where the finite speed of light affects the interaction, it is called the Casimir force. Thermal motion determines the fundamental sensitivity limits of its measurement at room temperature, but several other systematic errors contribute uncertainty as well

Ali Reza Hashemi, Mahmood Hosseini-Farzad

A class of hybrid photonic-plasmonic structures (HPPS) with vertical cylindrical cavities is proposed and its performance in providing a coherent light from spontaneous emission is investigated. It is shown that the proposed easy-to-fabricate and robust anodic aluminum oxide structure dramatically enhances the temporal and spatial coherence compared to the p

Sherif Abdulatif, Fady Aziz, Karim Armanious, Bernhard Kleiner

Obtaining a smart surveillance requires a sensing system that can capture accurate and detailed information for the human walking style. The radar micro-Doppler ($\boldsymbol{\mu}$-D) analysis is proved to be a reliable metric for studying human locomotions. Thus, $\boldsymbol{\mu}$-D signatures can be used to identify humans based on their walking styles. A

Jasabanta Patro, Rameshwar Bhaskaran, Animesh Mukherjee

Follower count is a factor that quantifies the popularity of celebrities. It is a reflection of their power, prestige and overall social reach. In this paper we investigate whether the social connectivity or the language choice is more correlated to the future follower count of a celebrity. We collect data about tweets, retweets and mentions of 471 Indian ce

Vincent Conitzer, Christian Kroer, Debmalya Panigrahi, Okke Schrijvers

Mature internet advertising platforms offer high-level campaign management tools to help advertisers run their campaigns, often abstracting away the intricacies of how each ad is placed and focusing on aggregate metrics of interest to advertisers. On such platforms, advertisers often participate in auctions through a proxy bidder, so the standard incentive a

George Ciprian Modoi

We give a method for constructing (possible large) self--small modules via some special homomorphisms of rings, called here weak epimorphisms.

Sung-Won Kim

Recently we solved the Einstein's field equations to obtain the exact solution of the cosmological model with the Morris-Thorne type wormhole. We found the apparent horizons and analyzed their geometric natures, including the causal tructures. We also derived the Hawking temperature near the apparent cosmological horizon with a proper definition of the K

F. Raimondi, C. Barbieri

Microscopic calculations of the electromagnetic response of medium-mass nuclei are now feasible thanks to the availability of realistic nuclear interactions with accurate saturation and spectroscopic properties, and the development of large-scale computing methods for many-body physics. The purpose is to compute isovector dipole electromagnetic (E1) response

Yang Xu, Min Chen, Wei Yang, Sheng Chen

The study of human gait recognition has been becoming an active research field. In this paper, we propose to adopt the attention-based Recurrent Neural Network (RNN) encoder-decoder framework to implement a cycle-independent human gait and walking direction recognition system in Wi-Fi networks. For capturing more human walking dynamics, two receivers togethe

V. M. Khatsymovsky

Faddeev gravity using a $d$-dimensional tetrad (normally $d = 10$) is classically equivalent to general relativity (GR). The discrete Faddeev gravity on the piecewise flat spacetime normally assumes slowly varying metric and tetrad from vertex to vertex. Meanwhile, Faddeev action is finite (although not unambiguously defined) for discontinuous tetrad fields

Konstantin Y. Bliokh, Franco Nori

We consider spin angular momentum density in inhomogeneous acoustic fields: evanescent waves and surface waves at interfaces with negative-density metamaterials. Despite being purely longitudinal (curl-free), acoustic waves possess intrinsic vector properties described by the velocity field. Motivated by the recent description and observation of the spin pro

Ronnie Loeffen, Pierre Patie, Mladen Savov

We start by providing an explicit characterization and analytical properties, including the persistence phenomena, of the distribution of the extinction time $\mathbb{T}$ of a class of non-Markovian self-similar stochastic processes with two-sided jumps that we introduce as a stochastic time-change of Markovian self-similar processes. For a suitably chosen t

Gurkirt Singh, Fabio Cuzzolin

Recently, three dimensional (3D) convolutional neural networks (CNNs) have emerged as dominant methods to capture spatiotemporal representations in videos, by adding to pre-existing 2D CNNs a third, temporal dimension. Such 3D CNNs, however, are anti-causal (i.e., they exploit information from both the past and the future frames to produce feature representa

Lorenzo Cavallina, Toshiaki Yachimura

We consider an overdetermined problem of Serrin-type with respect to an operator in divergence form with piecewise constant coefficients. We give sufficient condition for unique solvability near radially symmetric configurations by means of a perturbation argument relying on shape derivatives and the implicit function theorem. This problem is also treated nu

Anatoly Shusterman, Lachlan Kang, Yarden Haskal, Yosef Meltser

Website fingerprinting attacks, which use statistical analysis on network traffic to compromise user privacy, have been shown to be effective even if the traffic is sent over anonymity-preserving networks such as Tor. The classical attack model used to evaluate website fingerprinting attacks assumes an on-path adversary, who can observe all traffic traveling

Heron Caldas

We study phase separation in a dilute two-component Fermi system with attractive interactions as a function of the coupling strength and the polarization or number density asymmetry between the two components. In weak and strong couplings with a finite number density asymmetry, phase separation is energetically more favorable. A heterogeneous phase containin

Antonin Chambolle, Vito Crismale

In this paper we continue the study of the Griffith brittle fracture energy minimisation under Dirichlet boundary conditions, suggested by Francfort and Marigo in 1998. In a recent paper, we proved the existence of weak minimisers of the problem. Now we show that these minimisers are indeed strong solutions, namely their jump set is closed and they are smoot

Marta Kwiatkowska, Gethin Norman, David Parker, Gabriel Santos

Probabilistic model checking for stochastic games enables formal verification of systems that comprise competing or collaborating entities operating in a stochastic environment. Despite good progress in the area, existing approaches focus on zero-sum goals and cannot reason about scenarios where entities are endowed with different objectives. In this paper,

Emmanouil Markoulakis, Emmanuel Antonidakis, George S. Stavrakakis

The following analysis and presentation summarizes the implementation in Matlab / Simulink environment of a prototype model digital energy circuit for measurement of the consumption of electric energy of an electrification network in the installations of customer of electric energy that can be applied as part of any consumption smart meter.

Zeinab Ganjei, Ahmed Rezine, Ludovic Henrio, Petru Eles

We address the problem of statically checking safety properties (such as assertions or deadlocks) for parameterized phaser programs. Phasers embody a non-trivial and modern synchronization construct used to orchestrate executions of parallel tasks. This generic construct supports dynamic parallelism with runtime registrations and deregistrations of spawned t

Mauro Escobar, Daniel Bienstock, Michael Chertkov

Assuming access to synchronized stream of Phasor Measurement Unit (PMU) data over a significant portion of a power system interconnect, say controlled by an Independent System Operator (ISO), what can you extract about past, current and future state of the system? We have focused on answering this practical questions pragmatically - empowered with nothing bu

Takanori Ayano, Victor Buchstaber

Buchstaber and Mikhailov introduced the polynomial dynamical systems in $\mathbb{C}^4$ with two polynomial integrals on the basis of commuting vector fields on the symmetric square of hyperelliptic curves. In our previous paper, we constructed the field of meromorphic functions on the sigma divisor of hyperelliptic curves of genus 3 and solutions of the syst

Tsubasa Kusano, Yoshiki Masuyama, Kohei Yatabe, Yasuhiro Oikawa

Many audio signal processing methods are formulated in the time-frequency (T-F) domain which is obtained by the short-time Fourier transform (STFT). The properties of the STFT are fully characterized by window function, number of frequency channels, and time-shift. Thus, designing a better window is important for improving the performance of the processing e

Christopher Spalding, Woodward W. Fischer, Gregory Laughlin

Models of the Sun's long-term evolution suggest that its luminosity was substantially reduced 2-4 billion years ago, which is inconsistent with substantial evidence for warm and wet conditions in the geological records of both ancient Earth and Mars. Typical solutions to this so-called "faint young Sun paradox" consider changes in the atmospheric

Rohith AP, Ambedkar Dukkipati, Gaurav Pandey

The primary objective of domain adaptation methods is to transfer knowledge from a source domain to a target domain that has similar but different data distributions. Thus, in order to correctly classify the unlabeled target domain samples, the standard approach is to learn a common representation for both source and target domain, thereby indirectly address

Zuozhuo Dai, Mingqiang Chen, Xiaodong Gu, Siyu Zhu

Since the person re-identification task often suffers from the problem of pose changes and occlusions, some attentive local features are often suppressed when training CNNs. In this paper, we propose the Batch DropBlock (BDB) Network which is a two branch network composed of a conventional ResNet-50 as the global branch and a feature dropping branch. The glo

Hana Hirose, Naoto Ito, Masashi Kawaguchi, Yong-Chang Lau

We have studied the circular photogalvanic effect (CPGE) in Cu/Bi bilayers. When a circularly polarized light in the visible range is irradiated to the bilayer from an oblique incidence, we find a photocurrent that depends on the helicity of light. Such photocurrent appears in a direction perpendicular to the light plane of incidence but is absent in the par