November 2018 arXiv papers — page 18

Yuan Li, Dun Zhao, Qingxuan Wang

We study the following nonlinear Hartree-type equation \begin{equation*} -\Delta u+V(x)u-a(\frac{1}{|x|^\gamma}\ast |u|^2)u=\lambda u,~\text{in}~\mathbb{R}^N, \end{equation*} where $a>0$, $N\geq3$, $\gamma\in(0,2)$ and $V(x)$ is an external potential. We first study the asymptotic behavior of the ground state of equation for $V(x)\equiv1$, $a=1$ and $\lambda

M. Ablikim, M. N. Achasov, S. Ahmed, M. Albrecht

We report a study of the decay $D^0 \rightarrow \bar{K}^0\pi^-e^+\nu_{e}$ based on a sample of $2.93~\mathrm{fb}^{-1}$ $e^+e^-$ annihilation data collected at the center-of-mass energy of 3.773~GeV with the BESIII detector at the BEPCII collider. The total branching fraction is determined to be $\mathcal{B}(D^0\rightarrow \bar{K}^0\pi^-e^+\nu_{e})=(1.434\pm0

Yufang Cui, Anders Lindquist

This paper provides a new method to solve analytic interpolation problems with rationality and derivative constraints, occurring in many applications to system and control. It is based on the covariance extension equation previously proposed by Byrnes and Lindquist in a different context. A complete solution for the scalar problem is provided, and a homotopy

J Ignacio Deza, Hisham Ihshaish

We introduce a software generator for a class of colored (self-correlated) and non-Gaussian noise, whose statistics and spectrum depend on two parameters, $q$ and $\tau$. Inspired by Tsallis' nonextensive formulation of statistical physics, the so-called $q$-distribution is a handy source of self-correlated noise for a large range of applications. The $q$-no

Humza Haider, Bret Hoehn, Sarah Davis, Russell Greiner

An accurate model of a patient's individual survival distribution can help determine the appropriate treatment for terminal patients. Unfortunately, risk scores (e.g., from Cox Proportional Hazard models) do not provide survival probabilities, single-time probability models (e.g., the Gail model, predicting 5 year probability) only provide for a single time

Sean Gomes, Andrew Hassell

We show that for almost all perturbations in a one-parameter family of KAM Hamiltonians on a smooth compact surface, for almost all KAM Lagrangian tori $\Lambda_\omega$, we can find a semiclassical measure with positive mass on $\Lambda_\omega$.

Dabin Zheng, Mu Yuan, Nian Li, Lei Hu

An involution over finite fields is a permutation polynomial whose inverse is itself. Owing to this property, involutions over finite fields have been widely used in applications such as cryptography and coding theory. As far as we know, there are not many involutions, and there isn't a general way to construct involutions over finite fields. This paper give

Dong-Hui Li, Hong-Bo Guan, Xiao-Zhou Wang

We are concerned with the tensor equation with an M-tensor or Z-tensor, which we call the M- tensor equation or Z-tensor equation respectively. We derive a necessary and sufficient condition for a Z (or M)-tensor equation to have nonnegative solutions. We then develop a monotone iterative method to find a nonnegative solution to an M-tensor equation. The met

Liang Jin, Lu Peng, Xiaojun Cui

We show that if $(\mathbb{T}^{2},g)$ is a class A Lorentzian 2-torus with timelike poles, then there exists a Lipschitz foliation by complete future-directed timelike geodesics with any pre-assigned asymptotic direction in the interior of the stable time cone. This is done by constructing certain $C^{1,1}$ solutions to the equation $g(\nabla u,\nabla u)=-1$

Yunsheng Sun, Congjian Ni, Yingda Ge, Hong Qian

In pancreatic $\beta$-cells, calcium oscillation signal is the core part of glucose-stimulated insulin secretion. Intracellular calcium concentration oscillates in response to the intake of glucose, which triggers the exocytosis of insulin secretory granules. ATP plays a crucial part in this process. ATP increases as the result of glucose intake, then ATP bi

Marco Cavallo, Çağatay Demiralp

Dimensionality reduction is a common method for analyzing and visualizing high-dimensional data. However, reasoning dynamically about the results of a dimensionality reduction is difficult. Dimensionality-reduction algorithms use complex optimizations to reduce the number of dimensions of a dataset, but these new dimensions often lack a clear relation to the

Jiyoung Jung, Sangryun Lee, Byungki Ryu, Seunghwa Ryu

We obtained the analytical expression for the effective thermoelectric properties and dimensionless figure of merit of a composite with interfacial electrical and thermal resistances using a micromechanics-based homogenisation. For the first time, we derived the Eshelby tensor for a spherical inclusion as a function of the interfacial resistances and obtaine

Nan Du, Zhikang Wang, Hanshen Xiao

Generalized Chinese Remainder Theorem (CRT) has been shown to be a powerful approach to solve the ambiguity resolution problem. However, with its close relationship to number theory, study in this area is mainly from a coding theory perspective under deterministic conditions. Nevertheless, it can be proved that even with the best deterministic condition know

K. L. Yang, J. M. Zhang

We point out that by the ``smoothness means fast decay'' principle in Fourier analysis, it is possible to infer the smoothness (or nonsmoothness) of the autocorrelation function from a mere glimpse of the initial state. Specifically, for a generic system with smooth eigenstates, the smoother an initial state is, the faster its decomposition coefficients with

Brittany Terese Fasy, Samuel Micka, David L. Millman, Anna Schenfisch

Shape recognition and classification is a problem with a wide variety of applications. Several recent works have demonstrated that topological descriptors can be used as summaries of shapes and utilized to compute distances. In this abstract, we explore the use of a finite number of Euler Characteristic Curves (ECC) to reconstruct plane graphs. We highlight

Satoru Hayami, Yukitoshi Motome

We report our numerical results for the effect of magnetic anisotropy on a Skyrmion crystal with a high topological number of two, which was recently discovered in an itinerant electron model [R. Ozawa, S. Hayami, and Y. Motome, Phys. Rev. Lett. 118, 147205 (2017)]. By performing numerical simulations based on the kernel polynomial method and the Langevin dy

Yanchao Zhang, Jincan Chen

A theoretical proposal that Coulomb-coupled quantum dots can be used as quantum probes to determine the temperature of a sample (i.e., an electronic reservoir) is proposed. Through the regulation of the positive or negative voltage bias in the thermometer, we are able to judge whether the temperature of the sample is higher or lower than that of the referenc

Sheng-cai Zhu, Lei Wang, Jing-yu Qu, Jun-jie Wang

Electrides, with their excess electrons distributed in crystal cavities playing the role of anions, exhibit a variety of unique electronic and magnetic properties. In this work, we employ the first-principles crystal structure prediction to identify a new prototype of A$_3$B electride in which both interlayer spacings and intralayer vacancies provide channel

Amit Sharma

In this paper we construct a symmetric monoidal closed model category of coherently commutative monoidal categories. The main aim of this paper is to establish a Quillen equivalence between a model category of coherently commutative monoidal categories and a natural model category of Permutative (or strict symmetric monoidal) categories, $\mathbf{Perm}$, whi

Vishnu Vardhan Chetlur, Harpreet S. Dhillon, Carl P. Dettmann

While the Euclidean distance characteristics of the Poisson line Cox process (PLCP) have been investigated in the literature, the analytical characterization of the path distances is still an open problem. In this paper, we solve this problem for the stationary Manhattan Poisson line Cox process (MPLCP), which is a variant of the PLCP. Specifically, we deriv

Erdem Koyuncu, Hamid Jafarkhani

We consider ad-hoc networks consisting of $n$ wireless nodes that are located on the plane. Any two given nodes are called neighbors if they are located within a certain distance (communication range) from one another. A given node can be directly connected to any one of its neighbors and picks its connections according to a unique topology control algorithm

Yuefeng Yin, Michael S. Fuhrer, Nikhil V. Medhekar

Topological materials host robust surface states, which could form the basis for future electronic devices. As such states have spins that are locked to the momentum, they are of particular interest for spintronic applications. Understanding spin textures of the surface states of topologically nontrivial materials, and being able to manipulate their polariza

Sen Wang, Daoyuan Jia, Xinshuo Weng

Reinforcement learning has steadily improved and outperform human in lots of traditional games since the resurgence of deep neural network. However, these success is not easy to be copied to autonomous driving because the state spaces in real world are extreme complex and action spaces are continuous and fine control is required. Moreover, the autonomous dri

Kai Fukami, Koji Fukagata, Kunihiko Taira

We use machine learning to perform super-resolution analysis of grossly under-resolved turbulent flow field data to reconstruct the high-resolution flow field. Two machine-learning models are developed; namely the convolutional neural network (CNN) and the hybrid Downsampled Skip-Connection Multi-Scale (DSC/MS) models. These machine-learning models are appli

Mina Nazari, Min Xi, Mark Aronson, Mi K. Hong

Pan-microbial inactivation technologies that do not require high temperatures, reactive chemical compounds, or UV radiation could address gaps in current infection control strategies and provide efficient sterilization of biologics in the biotechnological industry. Here, we demonstrate that femtosecond (fs) laser irradiation of resonant gold nanoparticles (N

Moshe A. Milevsky

Who {\em values} life annuities more? Is it the healthy retiree who expects to live long and might become a centenarian, or is the unhealthy retiree with a short life expectancy more likely to appreciate the pooling of longevity risk? What if the unhealthy retiree is pooled with someone who is much healthier and thus forced to pay an implicit loading? To ans

Xinshuo Weng, Wentao Han

Across a majority of modern learning-based tracking systems, expensive annotations are needed to achieve state-of-the-art performance. In contrast, the Lucas-Kanade (LK) algorithm works well without any annotation. However, LK has a strong assumption of photometric (brightness) consistency on image intensity and is easy to drift because of large motion, occl

Xuan Thinh Duong, Ji Li, Dongyong Yang

Let $p\in(1,\infty)$, $\rho\in (2, \infty)$ and $W$ be a matrix $A_p$ weight. In this article, we introduce a version of variation $\mathcal{V}_{\rho}({\mathcal T_n}_{\,,\,\ast})$ for matrix Calder\'on--Zygmund operators with modulus of continuity satisfying the Dini condition. We then obtain the $L^p(W)$-boundedness of $\mathcal{V}_{\rho}({\mathcal T_n}_{\,

Shangxuan Wu, Xinshuo Weng

Most existing methods for object segmentation in computer vision are formulated as a labeling task. This, in general, could be transferred to a pixel-wise label assignment task, which is quite similar to the structure of hidden Markov random field. In terms of Markov random field, each pixel can be regarded as a state and has a transition probability to its

Dipayan Banerjee, Karen Smilowitz

We consider the school bus scheduling problem (SBSP) which simultaneously determines school bell times and route schedules. Often, the goal of the SBSP is to minimize the number of buses required by a school district. We extend a time-indexed integer programming model to incorporate additional considerations related to equity and efficiency. We seek to equit

Yu-Chen Cheng, Wenning Wang, Zhiyue Lu, Hong Qian

The theory of probability shows that, as the fraction $X_n/Y\to 0$, the conditional probability for $X_n$, given $X_n+Y \in h_{\delta}:=[h, h+\delta]$, has a limit law $f_{X_n}(x)e^{-\psi_n(h_\delta)x}$, where $\psi_n(h_\delta) $ equals to $[\partial \ln P(Y \in y_\delta)/\partial y]_{y=h}$ plus an additional term, contributed from the correlation between $X

M. F. Francis

Colossal Ion Conductivity (CIC) is the phenomenon in which large changes in oxygen conductivity are observed when a solid state oxygen electrolyte is placed in a heterolayer super lattice. Several hypotheses have been posed concerning both structural changes of the ion conducting material and of the ion conducting mechanism. The posed structural hypotheses a

Yu Shi, Xinwei He, Naijing Zhang, Carl Yang

Heterogeneous information networks (HINs) with rich semantics are ubiquitous in real-world applications. For a given HIN, many reasonable clustering results with distinct semantic meaning can simultaneously exist. User-guided clustering is hence of great practical value for HINs where users provide labels to a small portion of nodes. To cater to a broad spec

Ryusuke Hamazaki, Kohei Kawabata, Masahito Ueda

Many-body localization is shown to suppress imaginary parts of complex eigenenergies for general non-Hermitian Hamiltonians having time-reversal symmetry. We demonstrate that a real-complex transition, which we conjecture occurs upon many-body localization, profoundly affects the dynamical stability of non-Hermitian interacting systems with asymmetric hoppin

Hongyu Xu, Xutao Lv, Xiaoyu Wang, Zhou Ren

In this paper, we propose a novel object detection algorithm named "Deep Regionlets" by integrating deep neural networks and a conventional detection schema for accurate generic object detection. Motivated by the effectiveness of regionlets for modeling object deformations and multiple aspect ratios, we incorporate regionlets into an end-to-end trainable dee

Danil Annenkov

We present three projects concerned with applications of proof assistants in the area of programming language theory and mathematics. The first project is about a certified compilation technique for a domain-specific programming language for financial contracts (the CL language). The code in CL is translated into a simple expression language well-suited for

Yunrong Zhu

In this paper, we develop the auxiliary space preconditioners for solving the linear system arising from the virtual element methods discretization on polytopal meshes for the second order elliptic equations. The preconditioners are constructed based on an auxiliary simplicial mesh. The condition numbers of the preconditioned systems are uniformly bounded, i

Cristina Turcu, Cornel Turcu, Vasile Gaitan

This paper aims to propose a more efficient distributed monitoring and control approach for water utility in order to reduce the current water loss. This approach will help utilities operators improve water management systems, especially by exploiting the emerging technologies. The Internet of Things could prove to be one of the most important methods for de

Oleg O. Khamisov, Janusz W. Bialek, Anatoly Dymarsky

Introduction of renewable generation leads to significant reduction of inertia in power system, which deteriorates the quality of frequency control. This paper suggests a new control scheme utilizing controllable load to deal with low inertia systems. Optimization problem is formulated to minimize the systems deviations from the last economically optimal ope

Jiangyi Liu, Chunping Wang, Wei Wang

Most multi-target tracking filters assume that one target and its observation follow a Hidden Markov Chain (HMC) model, but the implicit independence assumption of HMC model is invalid in many practical applications, and a Pairwise Markov Chain (PMC) model is more universally suitable than traditional HMC model. A particle probability hypothesis density filt

Ulrich Bunke, Daniel Kasprowski, Christoph Winges

We construct an equivariant coarse homology theory arising from the algebraic $K$-theory of spherical group rings and use this theory to derive split injectivity results for associated assembly maps. On the way, we prove that the fundamental structural theorems for Waldhausen's algebraic $K$-theory functor carry over to its nonconnective counterpart defi

Nathan McClanahan, Nicholas Stegmeier, Rylee Sundermann, Jeffrey Doom

We present a 2D parallel implementation of the modified Cahn-Hilliard equation for the simulation of a biofilm in an aqueous enviroment. Biofilms are attached microbial communities made of many different components and can have both positive and negative effects. They can be used for bioremediation but also are the cause of the majority of chronic infections

Wasilij Barsukow

There is a qualitative difference between one-dimensional and multi-dimensional solutions to the Euler equations: new features that arise are vorticity and a nontrivial incompressible (low Mach number) limit. They present challenges to finite volume methods. It seems that an important step in this direction is to first study the new features for the multi-di

Ronny Ramlau, Christoph Koutschan, Bernd Hofmann

In theory and practice of inverse problems, linear operator equations $Tx=y$ with compact linear forward operators $T$ having a non-closed range $\mathcal{R}(T)$ and mapping between infinite dimensional Hilbert spaces plays some prominent role. As a consequence of the ill-posedness of such problems, regularization approaches are required, and due to its unli

Katsuhiro Shiohama, Bankteshwar Tiwari

The aim of this article is to present a comparative review of Riemannian and Finsler geometry. The structures of cut and conjugate loci on Riemannian manifolds have been discussed by many geometers including H. Busemann, M. Berger and W. Klingenberg. The key point in the study of Finsler manifolds is the non-symmetric property of its distance functions. We d

Simona Perotto, Michele Giuliano Carlino, Francesco Ballarin

Hierarchical Model reduction and Proper Generalized Decomposition both exploit separation of variables to perform a model reduction. After setting the basics, we exemplify these techniques on some standard elliptic problems to highlight pros and cons of the two procedures, both from a methodological and a numerical viewpoint.

Pierre Ablin, Jean-François Cardoso, Alexandre Gramfort

The approximate joint diagonalization of a set of matrices consists in finding a basis in which these matrices are as diagonal as possible. This problem naturally appears in several statistical learning tasks such as blind signal separation. We consider the diagonalization criterion studied in a seminal paper by Pham (2001), and propose a new quasi-Newton me

Faizal Hafiz, Akshya Swain, Eduardo MAM Mendes

The present study proposes a new structure selection approach for non-linear system identification based on Two-Dimensional particle swarms (2D-UPSO). The 2D learning framework essentially extends the learning dimension of the conventional particle swarms and explicitly incorporates the information about the cardinality, i.e., number of terms, into the searc

Dwaipayan Mukherjee, Shashi Ranjan Kumar

This paper presents a finite-time heterogeneous cyclic pursuit scheme that ensures consensus among agents modelled as integrators. It is shown that for the proposed sliding mode control, even when the gains corresponding to each agent are non-identical, consensus results within a finite-time provided all the gains are positive. An algorithm is presented to c

Xueping Zhao, Qi Wang

We present a linear, second order fully discrete numerical scheme on a staggered grid for a thermodynamically consistent hydrodynamic phase field model of binary compressible fluid flow mixtures derived from the generalized Onsager Principle. The hydrodynamic model not only possesses the variational structure, but also warrants the mass, linear momentum cons

Christoph Reisinger, Zhenru Wang

In this article, we propose an implicit finite difference scheme for a two-dimensional parabolic stochastic partial differential equation (SPDE) of Zakai type. The scheme is based on a Milstein approximation to the stochastic integral and an alternating direction implicit (ADI) discretisation of the elliptic term. We prove its mean-square stability and conve

Yoshiaki Nakada

We analyze the effects of energy and commodity prices on commodity output using a three-factor, two-good general equilibrium trade model with three factors: capital, labor, and imported energy. We derive a sufficient condition for each sign pattern of each relationship to hold, which no other studies have derived. We assume factor-intensity ranking is consta

Tao Sun, Hao Jiang, Lizhi Cheng, Wei Zhu

In this paper, we consider the convergence of an abstract inexact nonconvex and nonsmooth algorithm. We promise a pseudo sufficient descent condition and a pseudo relative error condition, which are both related to an auxiliary sequence, for the algorithm; and a continuity condition is assumed to hold. In fact, a lot of classical inexact nonconvex and nonsmo

Marco Avella-Medina, Francesca Parise, Michael T. Schaub, Santiago Segarra

As relational datasets modeled as graphs keep increasing in size and their data-acquisition is permeated by uncertainty, graph-based analysis techniques can become computationally and conceptually challenging. In particular, node centrality measures rely on the assumption that the graph is perfectly known -- a premise not necessarily fulfilled for large, unc

Wuchen Li, Penghang Yin, Stanley Osher

We propose a fast algorithm to approximate the optimal transport distance. The main idea is to add a Fisher information regularization into the dynamical setting of the problem, originated by Benamou and Brenier. The regularized problem is shown to be smooth and strictly convex, thus many classical fast algorithms are available. In this paper, we adopt Newto

Corentin Briat

Co-design conditions for the design of a jumping-rule and a sampled-data control law for impulsive and impulsive switched systems subject to aperiodic sampled-data measurements are provided. Semi-infinite discrete-time Lyapunov-Metzler conditions are first obtained. As these conditions are difficult to check and generalize to more complex systems, an equival

Sérgio Rebelo, Pedro Martins, João Bicker, Penousal Machado

Graphic Design encompasses a wide range of activities from the design of traditional print media (e.g., books and posters) to site-specific (e.g., signage systems) and electronic media (e.g., interfaces). Its practice always explores the new possibilities of information and communication technologies. Therefore, interactivity and participation have become ke

John Cantwell

We give a proof of the Neilsen-Thurston classification theorem of a homeomorphism f of a standard surface of finite type as either periodic, pseudo-Anosov, or reducible. In the periodic case, we show that there exists an integer n>0 such that f is isotopic to h with h^n isotopic to the identity. This is the weaker version of the Nielsen-Thurston theorem.

Fred Guth, Teofilo E. deCampos

In this paper we approach the problem of skin lesion segmentation using a convolutional neural network based on the U-Net architecture. We present a set of training strategies that had a significant impact on the performance of this model. We evaluated this method on the ISIC Challenge 2018 - Skin Lesion Analysis Towards Melanoma Detection, obtaining thresho

Eddy El Khalil

In this paper I introduce a new and intuitive first-order foundational theory (where the concept of set is not primitive) and use it to show that the power set of an infinite set does not exist. In particular, proofs of uncountability of a set are essentially proofs of the non-existence of that specified set. In a certain sense, uncountability is shown to be

Samuel N. Richards, Samuel H. Moseley, Gordon Stacey, Matthew Greenhouse

The HIgh-Resolution Mid-infrarEd Spectrometer (HIRMES) is the 3rd Generation Instrument for the Stratospheric Observatory For Infrared Astronomy (SOFIA), currently in development at the NASA Goddard Space Flight Center (GSFC), and due for commissioning in 2019. By combining direct-detection Transition Edge Sensor (TES) bolometer arrays, grating-dispersive sp

Shamane Siriwardhana, Rivindu Weerasekera, Suranga Nanayakkara

Being able to navigate to a target with minimal supervision and prior knowledge is critical to creating human-like assistive agents. Prior work on map-based and map-less approaches have limited generalizability. In this paper, we present a novel approach, Hybrid Asynchronous Universal Successor Representations (HAUSR), which overcomes the problem of generali

Laxman Raju Thoutam, Jin Yue, Peng Xu, Bharat Jalan

Electronic transport near the insulator-metal transition is investigated in the molecular beam epitaxy-grown SrTiO3/Nd1-xTiO3/SrTiO3 heterostructures using temperature dependent magnetotransport measurements. It was found that Nd-vacancies introduce localized electronic states resulting in the variable range hopping transport at low temperatures. At a fixed

Kevin McCloskey, Ankur Taly, Federico Monti, Michael P. Brenner

Deep neural networks have achieved state of the art accuracy at classifying molecules with respect to whether they bind to specific protein targets. A key breakthrough would occur if these models could reveal the fragment pharmacophores that are causally involved in binding. Extracting chemical details of binding from the networks could potentially lead to s

Biplab Dey

The electroweak sector of the Standard Model contains three generations of charged leptons $\ell^-\in\{e^-,\mu^-,\tau^-\}$ as exact replicas of each other, except for their Yukawa couplings to the Higgs that determine their masses. The Yukawas, and thereby, the masses, are not predicted but are parameters in the theory. A basic tenet in the formalism, known

B. Matusch, C. Amole, M. Ardid, I. J. Arnquist

The identification of non-signal events is a major hurdle to overcome for bubble chamber dark matter experiments such as PICO-60. The current practice of manually developing a discriminator function to eliminate background events is difficult when available calibration data is frequently impure and present only in small quantities. In this study, several dif

Craig Macartney, Tillman Weyde

We study the use of the Wave-U-Net architecture for speech enhancement, a model introduced by Stoller et al for the separation of music vocals and accompaniment. This end-to-end learning method for audio source separation operates directly in the time domain, permitting the integrated modelling of phase information and being able to take large temporal conte

Jose Risomar Sousa

This paper presents formulae for the sum of the terms of a harmonic progression of order $k$ with integer parameters, $\mathrm{HP}_k(n)$, and for the partial sums of its two associated Fourier series, $C^z_{k}(a,b,n)$ and $S^z_{k}(a,b,n)$. $\mathrm{HP}_k(n)$ is built from the ground up, with a power series for $1/(aj+b)^k$ that is summed over $j$ using Faulh

Ali Shafahi, Mahyar Najibi, Zheng Xu, John Dickerson

Standard adversarial attacks change the predicted class label of a selected image by adding specially tailored small perturbations to its pixels. In contrast, a universal perturbation is an update that can be added to any image in a broad class of images, while still changing the predicted class label. We study the efficient generation of universal adversari

Jingbo Liu, Ayfer Ozgur

The primitive relay channel, introduced by Cover in 1987, is the simplest single-source single-destination network model that captures some of the most essential features and challenges of relaying in wireless networks. Recently, Wu and Ozgur developed upper bounds on the capacity of this channel that are tighter than the cutset bound. In this paper, we reco

Immanuel Manohar

An observed $K$-dimensional series $\left\{ y_{n}\right\} _{n=1}^{N}$ is expressed in terms of a lower $p$-dimensional latent series called factors $f_{n}$ and random noise $\varepsilon_{n}$. The equation, $y_{n}=Qf_{n}+\varepsilon_{n}$ is taken to relate the factors with the observation. The goal is to determine the dimension of the factors, $p$, the factor

Matthew Norton, Valentyn Khokhlov, Stan Uryasev

Conditional Value-at-Risk (CVaR) and Value-at-Risk (VaR), also called the superquantile and quantile, are frequently used to characterize the tails of probability distribution's and are popular measures of risk. Buffered Probability of Exceedance (bPOE) is a recently introduced characterization of the tail which is the inverse of CVaR, much like the CDF is t

Markus Rausch, Stefan Lämmer, Martin Treiber

We propose a novel self-organized traffic management strategy for incidents in traffic-light-controlled road networks. During incidents, it regulates the inflow into already congested road segments by restricting or skipping green times. Simultaneously, the remaining green times are used for the yet free turning directions. In this way, drivers can utilize u

Spyridon Kakaroumpas, Sergei Treil

For an $A_p$ weight $w$ the norm of the Hilbert Transform in $L^p(w)$, $1<p<\infty$ is estimated by $[w]_{A_p}^{s}$, where $[w]_{A_p}$ is the $A_p$ characteristic of the weight $w$ and $s = \max(1,1/(p-1))$; as simple examples with power weights show, these estimates are sharp. A natural question to ask, is whether it is possible to improve the exponent $s$

Wenjing Dong, Edmund W. Tedford, Mona Rahmani, Gregory A. Lawrence

The effects of different initial perturbations on the evolution of stratified shear flows that are subject to Kelvin-Helmholtz instability and vortex pairing have been investigated through Direct Numerical Simulation (DNS). The effects of purely random perturbations of the background flow are sensitive to the phase of the subharmonic component of the perturb

Arash Tavakoli, Vitaly Levdik, Riashat Islam, Christopher M. Smith

We consider the generic approach of using an experience memory to help exploration by adapting a restart distribution. That is, given the capacity to reset the state with those corresponding to the agent's past observations, we help exploration by promoting faster state-space coverage via restarting the agent from a more diverse set of initial states, as wel

Sucheta Mondal, Md Ahsanul Abeed, Koustuv Dutta, Anulekha De

Magneto-elastic (or "straintronic") switching has emerged as an extremely energy-efficient mechanism for switching the magnetization of magnetostrictive nanomagnets in magnetic memory, logic and non-Boolean circuits. Here, we investigate the ultrafast magneto-dynamics associated with straintronic switching in a single quasi-elliptical magnetostrictive Co nan

Richard T. Marriott, Sami Romdhani, Liming Chen

Generative Adversarial Networks (GANs) are able to learn mappings between simple, relatively low-dimensional, random distributions and points on the manifold of realistic images in image-space. The semantics of this mapping, however, are typically entangled such that meaningful image properties cannot be controlled independently of one another. Conditional G

Markus Rausch, Martin Treiber, Stefan Lämmer

We propose a microscopic decision model for route choice based on discrete choice theory. The correlation of overlapping routes is included in the random portions of the utility explicitly. For computational efficiency, we restrict the choice set to the turning possibilities at the next intersection, assuming shortest paths to the destination afterwards. The

R. Johnston, J. Bernauer, C. M. Cooke, R. Corliss

The design, construction, installation, and testing of a Faraday Cup intended to measure the current of a 3 MeV, 1 microampere electron beam is described. Built as a current monitor for a M{\o}ller scattering measurement at the MIT High Voltage Research Laboratory, the device combines a large angular acceptance with the capability to measure a continuous, lo

Randall L. Rathbun

By examining the 3 surface angles which exist at any of the 8 vertices of a Diophantine parallelepiped, and classifying them by the appearance of a right angle, it is discovered that 5 unique classes of Diophantine parallelepipeds exist. It is proposed to name these classes: acute (triclinic), obtuse (triclinic), 1-ortho (biclinic), 2-ortho (monoclinic), and

Jens Kügel, Michael Karolak, Andreas Krönlein, David Serrate

The quantum mechanical screening of a spin via conduction electrons depends sensitively on the environment seen by the magnetic impurity. A high degree of responsiveness can be obtained with metal complexes, as the embedding of a metal ion into an organic molecule prevents intercalation or alloying and allows for a good control by an appropriate choice of th

Rebekah Overdorf, Bogdan Kulynych, Ero Balsa, Carmela Troncoso

In addition to their benefits, optimization systems can have negative economic, moral, social, and political effects on populations as well as their environments. Frameworks like fairness have been proposed to aid service providers in addressing subsequent bias and discrimination during data collection and algorithm design. However, recent reports of neglect

Zhiping Wang, Sahar Sharifzadeh, Zhenfei Liu, Peter Doak

We combine a GW approach and ab initio Molecular Dynamics (AIMD) simulations to study the impact of thermal effects on transport gap in solid pentacene (C22H14). The dynamic disorder induced by thermal fluctuations is simulated by AIMD, providing the ensemble-averaged density of states (DOS) near the band gap. The GW corrected DOS, averaged over hundreds of

Maximilian Beikirch, Simon Cramer, Martin Frank, Philipp Otte

We study the qualitative and quantitative appearance of stylized facts in several agent-based computational economic market (ABCEM) models. We perform our simulations with the SABCEMM (Simulator for Agent-Based Computational Economic Market Models) tool recently introduced by the authors (Trimborn et al. 2019). Furthermore, we present novel ABCEM models crea

Ben Moews, J. Michael Herrmann, Gbenga Ibikunle

Trend change prediction in complex systems with a large number of noisy time series is a problem with many applications for real-world phenomena, with stock markets as a notoriously difficult to predict example of such systems. We approach predictions of directional trend changes via complex lagged correlations between them, excluding any information about t

Wang Yifan, Shihao Wu, Hui Huang, Daniel Cohen-Or

We present a detail-driven deep neural network for point set upsampling. A high-resolution point set is essential for point-based rendering and surface reconstruction. Inspired by the recent success of neural image super-resolution techniques, we progressively train a cascade of patch-based upsampling networks on different levels of detail end-to-end. We pro

Andrew V. Sills

A generalized Bailey pair, which contains several special cases considered by Bailey (\emph{Proc. London Math. Soc. (2)}, 50 (1949), 421--435), is derived and used to find a number of new Rogers-Ramanujan type identities. Consideration of associated $q$-difference equations points to a connection with a mild extension of Gordon's combinatorial generalization

Wen-Sheng Xu, Christopher N. Lam, Jan-Michael Y. Carrillo, Bobby G. Sumpter

The classical rheological theories of entangled polymeric liquids are built upon two pillars: Gaussian statistics of entanglement strands and the assumption that the stress arises exclusively from the change of intramolecular configuration entropy. We show that these two hypotheses are not supported by molecular dynamics simulations of polymer melts. Specifi

Raviteja Vemulapalli, Aseem Agarwala

Most of the existing work on automatic facial expression analysis focuses on discrete emotion recognition, or facial action unit detection. However, facial expressions do not always fall neatly into pre-defined semantic categories. Also, the similarity between expressions measured in the action unit space need not correspond to how humans perceive expression

Gavin P. Salam

Particle physics is sometimes described as going through a crisis, notably because of the continued lack of discovery of physics beyond the Standard Model, despite the LHC having operated at close to maximal energy for some years now. Here, I argue that we should not underestimate the significance of recent progress and future prospects in the Higgs sector o

Sihem Mesnager, Kwang Ho Kim, Myong Song Jo

To determine the dimension of null space of any given linearized polynomial is one of vital problems in finite field theory, with concern to design of modern symmetric cryptosystems. But, the known general theory for this task is much far from giving the exact dimension when applied to a specific linearized polynomial. The first contribution of this paper is

Tim Brooks, Jonathan T. Barron

We present a technique for synthesizing a motion blurred image from a pair of unblurred images captured in succession. To build this system we motivate and design a differentiable "line prediction" layer to be used as part of a neural network architecture, with which we can learn a system to regress from image pairs to motion blurred images that span the cap

Junyao Guo, Unmesh Kurup, Mohak Shah

With recent advances in learning algorithms and hardware development, autonomous cars have shown promise when operating in structured environments under good driving conditions. However, for complex, cluttered and unseen environments with high uncertainty, autonomous driving systems still frequently demonstrate erroneous or unexpected behaviors, that could l

Tian Xie, Guan-Hua Tu, Bangjie Yin, Chi-Yu Li

Since 2016, all of four major U.S. operators have rolled out nationwide Wi-Fi calling services. They are projected to surpass VoLTE (Voice over LTE) and other VoIP services in terms of mobile IP voice usage minutes in 2018. They enable mobile users to place cellular calls over Wi-Fi networks based on the 3GPP IMS (IP Multimedia Subsystem) technology. Compare

Henry Bendekgey

We present a method for encoding game logs as numeric features in the card game Dominion. We then run the manifold learning algorithm t-SNE on these encodings to visualize the landscape of player strategies. By quantifying game states as the relative prevalence of cards in a player's deck, we create visualizations that capture qualitative differences in play

A. Bravo, S. Encinas, B. Pascual-Escudero

We study contact loci sets of arcs and the behavior of Hironaka's order function defined in constructive Resolution of singularities. We show that this function can be read in terms of the irreducible components of the contact loci sets at a singular point of an algebraic variety.

Leonardo A. Cano G, Pedro H. Zambrano

We remark that forcing on fiber bundles of structures of first order languages is not a compatible semantics with the pullback (of fiber bundles) and we describe a semantics which behaves well with respect to it. This new semantics uses parallel transport and allows to introduce two different types of extensions for the formulae: vertical and horizontal exte

Kai Li, Pei-Ying Chen, Erjia Yan

The rise of software as a research object is mirrored in the increasing interests towards quantitative studies of scientific software. However, due to the inconsistent practice of citing software, most of the existing studies analyzing the impact of scientific software are based on identification of software name mentions in full-text publications. Despite i

Greg Olmschenk, Zhigang Zhu, Hao Tang

In this work, we generalize semi-supervised generative adversarial networks (GANs) from classification problems to regression problems. In the last few years, the importance of improving the training of neural networks using semi-supervised training has been demonstrated for classification problems. We present a novel loss function, called feature contrastin