March 2020 arXiv papers — page 20

William W. Symes

Nonlinear least squares data-fitting driven by physical process simulation is a classic and widely successful technique for the solution of inverse problems in science and engineering. Known as "Full Waveform Inversion" in application to seismology, it can extract detailed maps of earth structure from near-surface seismic observations, but also suffers from

Péter Madarasi

In this paper, we prove that the multicolored Ramsey number $R(G_1,\dots,G_n,K_{n_1},\dots,K_{n_r})$ is at least $(\gamma-1)(\kappa-1)+1$ for arbitrary connected graphs $G_1,\dots,G_n$ and $n_1,\dots,n_r\in\mathbb{N}$, where $\gamma=R(G_1,\dots,G_n)$ and $\kappa=R(K_{n_1},\dots,K_{n_r})$. Erd\H os at al. conjectured that $R(C_n,K_l)=(n-1)(l-1)+1$ for every $

Wansheng Wang

In this paper we investigate the long time stability of the implicit Euler scheme for the Cahn-Hilliard equation with polynomial nonlinearity. The uniform estimates in $H^{-1}$ and $\mathcal H^s_\alpha$ ($s=1,2,3$) spaces independent of the initial data and time discrete step-sizes are derived for the numerical solution produced by this classical scheme with

Akshith Ullal, Ram Bilas Pachori

Epilepsy affects about 1% of the population every year, and is characterized by abnormal and sudden hyper-synchronous excitation of the neurons in the brain. The electroencephalogram(EEG) is the most widely used method to record brain signals and diagnose epilepsy and seizure cases. In this paper we use the method of Variational Mode Decomposition (VMD) in o

Minjie Lei, James D. Wells

We present a simple modification of the Altarelli-Feruglio $A_4$ flavor symmetry model using a minimal number of parameters congruous with the symmetries of the original theory. The resulting model is consistent with all presently known data on neutrino masses and mixings. Furthermore, it makes testable tight predictions for future experiments aimed at impro

C. A. Aidala, S. Altaf, R. Belmont, S. Boose

sPHENIX is a new experiment under construction for the Relativistic Heavy Ion Collider at Brookhaven National Laboratory which will study the quark-gluon plasma to further the understanding of QCD matter and interactions. A prototype of the sPHENIX electromagnetic calorimeter (EMCal) was tested at the Fermilab Test Beam Facility in Spring 2018 as experiment

Chun Zhang, Tao Li

Although it is well accepted that the spin-$\frac{1}{2}$ triangular lattice Heisenberg antiferromagnet(TLHAF) has a long range ordered ground state, a thorough understanding of its spin dynamics is still missing. While the linear spin wave theory(LSWT) predicts three branches of magnon mode in the magnetic Brillouin zone(MBZ), the 1/S expansion at the next o

Caitlin Feltner, Emily Lewis, Jamie Peck, Mark Shipps

Although each year brings rapid advancement in meteorology and forecasting technology, the threat of natural disasters is not totally predictable. Predictability, however, still will not guarantee avoidability, thus adequate time to react to predictions remains a chief concern. Considerable effort by city authorities is often put forth to prepare for such ev

Naoyuki Kanda, Yashesh Gaur, Xiaofei Wang, Zhong Meng

This paper proposes serialized output training (SOT), a novel framework for multi-speaker overlapped speech recognition based on an attention-based encoder-decoder approach. Instead of having multiple output layers as with the permutation invariant training (PIT), SOT uses a model with only one output layer that generates the transcriptions of multiple speak

Andrew J. Morgan, Harry M. Quiney, Saša Bajt, Henry N. Chapman

We present a method for the measurement of the phase gradient of a wavefront by tracking the relative motion of speckles in projection holograms as a sample is scanned across the wavefront. By removing the need to obtain an un-distorted reference image of the sample, this method is suitable for the metrology of highly divergent wavefields. Such wavefields al

Nam Ho-Nguyen, Fatma Kılınç-Karzan, Simge Küçükyavuz, Dabeen Lee

We consider exact deterministic mixed-integer programming (MIP) reformulations of distributionally robust chance-constrained programs (DR-CCP) with random right-hand sides over Wasserstein ambiguity sets. The existing MIP formulations are known to have weak continuous relaxation bounds, and, consequently, for hard instances with small radius, or with large p

Fei Dong, Keyou You

The isoline tracking of this work is concerned with the control design for a sensing robot to track a given isoline of an unknown 2-D scalar filed. To this end, we propose a coordinate-free controller with a simple PI-like form using only the concentration feedback for a Dubins robot, which is particularly useful in GPS-denied environments. The key idea lies

N. D. Hari Dass

Through a very careful analysis of Dirac's 1932 paper on the Lagrangian in Quantum Mechanics as well as the second and third editions of his classic book {\it The Principles of Quantum Mechanics}, I show that Dirac's contributions to the birth of the path-integral approach to quantum mechanics is not restricted to just his seminal demonstration of how Lagran

Yong Wang

In this paper, we define and classify minimal translation surfaces with respect to a kind of semi-symmetric metric connections and a kind of semi-symmetric non-metric connections in $\mathbb{R}^3$ and $\mathbb{R}^3_1$.

Hossein Rangani Jahromi, Kobra Mahdavipour, Mahshid Khazaei Shadfar, Rosario Lo Franco

Non-Markovian effects can speed up the dynamics of quantum systems while the limits of the evolution time can be derived by quantifiers of quantum statistical speed. We introduce a witness for characterizing the non-Markovianity of quantum evolutions through the Hilbert-Schmidt speed (HSS), which is a special type of quantum statistical speed. This witness h

Mohammed Almatrafi, Raymond Baldwin, Kiyoharu Aizawa, Keigo Hirakawa

We propose DistSurf-OF, a novel optical flow method for neuromorphic cameras. Neuromorphic cameras (or event detection cameras) are an emerging sensor modality that makes use of dynamic vision sensors (DVS) to report asynchronously the log-intensity changes (called "events") exceeding a predefined threshold at each pixel. In absence of the intensity value at

Zohaib Amjad Khan, Azeddine Beghdadi, Faouzi Alaya Cheikh, Mounir Kaaniche

Laparoscopic videos can be affected by different distortions which may impact the performance of surgery and introduce surgical errors. In this work, we propose a framework for automatically detecting and identifying such distortions and their severity using video quality assessment. There are three major contributions presented in this work (i) a proposal f

Manolis Kargiantoulakis

The Mu2e experiment will search for the neutrino-less conversion of a muon into an electron in the field of an aluminum nucleus. An observation would be the first signal of charged lepton flavor violation and de facto evidence for new physics beyond the Standard Model. The clean signature of the conversion process offers an opportunity for a powerful search:

Stefano Marchesini, Anuradha Trivedi, Pablo Enfedaque, Talita Perciano

Tomographic imaging has benefited from advances in X-ray sources, detectors and optics to enable novel observations in science, engineering and medicine. These advances have come with a dramatic increase of input data in the form of faster frame rates, larger fields of view or higher resolution, so high performance solutions are currently widely used for ana

Krishan Saraswat, Niayesh Afshordi

We study how the evaporation rate of spherically symmetric black holes is affected through the extraction of radiation close to the horizon. We adopt a model of extraction that involves a perfectly absorptive screen placed close to the horizon and show that the evaporation rate can be changed depending on how close to the horizon the screen is placed. We app

Zhiyuan Yao, Chang Liu, Pengfei Zhang, Hui Zhai

A recent experiment [Nature Physics 10, 1 (2019)] has realized a dynamical gauge system with $\mathbb{Z}_2$ gauge symmetry in a double-well potential. In this work we propose a method to generalize this model from a single double well to a one-dimensional chain. We show that although there is no disordered potential in the original model, the phenomenon of m

Michael Basin, Pablo Rodriguez-Ramirez

This note discusses three examples given in the recent technical correspondence paper [1], which addresses the results presented in [2,3,4]. It is shown that the first example ([1], Section 3) is irrelevant to the results of [2]. The second example ([1], Section 4) establishes a well-known fact that a continuous differentiator can exactly differentiate a sig

Amit Kohli, Vincent Sitzmann, Gordon Wetzstein

The recent success of implicit neural scene representations has presented a viable new method for how we capture and store 3D scenes. Unlike conventional 3D representations, such as point clouds, which explicitly store scene properties in discrete, localized units, these implicit representations encode a scene in the weights of a neural network which can be

Qing-Miao Hu, Rui Yang

The substitutional solute atom induced local lattice distortion (LLD) in dilute metal solid solution was believed to be uniform that may even be modeled by using soap bubble raft. Contrary to this conventional picture, we report in this manuscript that the Mo induced LLD in dilute Ti-Mo solid solution is highly non-uniform as evidenced by our first principle

Phuong-Duy Nguyen, Long Bao Le

Network function Virtualization (NFV) and Mobile Edge Computing (MEC) are promising 5G technologies to support resource-demanding mobile applications. In NFV, one must process the service function chain (SFC) in which a set of network functions must be executed in a specific order. Moreover, the MEC technology enables computation offloading of service reques

Michael Taynnan Barros, Harun Siljak, Peter Mullen, Constantinos Papadias

Classification of biological neuron types and networks poses challenges to the full understanding of the brain's organisation and functioning. In this paper, we develop a novel objective classification model of biological neuronal types and networks based on the communication metrics of neurons. This presents advantages against the existing approaches since

Stephen Giblin, Jordan Tompkins

New technology, the ultrastable low-noise current amplifier and the electron pump, provide new methods for making traceable measurements of small DC electric currents. We review four traceability routes for small current measurements and discuss the merits of each one. We present three case studies of small current calibrations, highlighting the role of nois

Tooba Aamir, Hai Dong, Athman Bouguettaya

The extensive use of social media platforms and overwhelming amounts of imagery data creates unique opportunities for sensing, gathering and sharing information about events. One of its potential applications is to leverage crowdsourced social media images to create a tapestry scene for scene analysis of designated locations and time intervals. The existing

Mikhail Lomonosov, Vladimir Shiltsev

One of Russia most prominent Enlightenment figures, Mikhail Lomonosov (1711-1765) was a polymath, scientist and writer, who made important contributions to physics, chemistry, astronomy, literature and education. Among his discoveries were the atmosphere of Venus and the law of conservation of mass in chemical reactions. These Panegyrics to Peter the Great a

Giuseppe Dattoli, Emanuele Di Palma, Silvia Licciardi, Elio Sabia

In a previous note we made an analysis of the spreading of the COVID disease in Italy. We used a model based on the logistic and Hubbert functions, the analysis we exploited has shown limited usefulness in terms of predictions and failed in fixing fundamental indications like the point of inflection of the disease growth. In this note we elaborate on the pre

Ahmed S. Zamzam, Bo Yang, Nicholas D. Sidiropoulos

In this paper, we address the challenge of recovering an accurate breakdown of aggregated tensor data using disaggregation examples. This problem is motivated by several applications. For example, given the breakdown of energy consumption at some homes, how can we disaggregate the total energy consumed during the same period at other homes? In order to addre

Fenxi Xiao, Bo Huang, Xia Wu

In this paper, we propose and end-to-end deep Chinese font generation system. This system can generate new style fonts by interpolation of latent style-related embeding variables that could achieve smooth transition between different style. Our method is simpler and more effective than other methods, which will help to improve the font design efficiency

Pedro Cisneros-Velarde, Saber Jafarpour, Francesco Bullo

In this note, we provide an overarching analysis of primal-dual dynamics associated to linear equality-constrained optimization problems using contraction analysis. For the well-known standard version of the problem: we establish convergence under convexity and the contracting rate under strong convexity. Then, for a canonical distributed optimization proble

Rogério J. de Assis, J. S. Sales, Udson C. Mendes, Norton G. de Almeida

Recent theoretical and experimental studies in quantum heat engines show that, in the quasi-static regime, it is possible to have higher efficiency than the limit imposed by Carnot, provided that engineered reservoirs are used. The quasi-static regime, however, is a strong limitation to the operation of heat engines, since infinitely long time is required to

Cedric Münger, Steffen Börm, Jörg Ostrowski

The prediction of a dielectric breakdown in a high-voltage device is based on criteria that evaluate the electric field along field lines. Therefore it is necessary to efficiently compute the electric field at arbitrary points in space. A boundary element method (BEM) based on an indirect formulation, realized with MPI-parallel collocation, has proven to cop

S. Hasibul Hassan Chowdhury, Talal Ahmed Chowdhury, MD Arman Ud Duha

In this paper we consider an electron moving on a two dimensional noncommutative plane immersed in a constant magnetic field under the influence of an anisotropic harmonic potential. We work out the gauge invariant energy spectra of this system using a consistent gauge prescription proposed in \cite{nctori,gauge-wigfunc}. We also show subsequently that strai

Jacopo Borga, Raul Penaguiao

We study proportions of consecutive occurrences of permutations of a given size. Specifically, the feasible limits of such proportions on large permutations form a region, called feasible region. We show that this feasible region is a polytope, more precisely the cycle polytope of a specific graph called overlap graph. This allows us to compute the dimension

Orevaoghene Ahia, Kelechi Ogueji

Nigerian Pidgin is arguably the most widely spoken language in Nigeria. Variants of this language are also spoken across West and Central Africa, making it a very important language. This work aims to establish supervised and unsupervised neural machine translation (NMT) baselines between English and Nigerian Pidgin. We implement and compare NMT models with

Apostolos I. Rikos, Christoforos N. Hadjicostis

We study the distributed average consensus problem in multi-agent systems with directed communication links that are subject to quantized information flow. The goal of distributed average consensus is for the nodes, each associated with some initial value, to obtain the average (or some value close to the average) of these initial values. In this paper, we p

Rohit Bhattacharya, Razieh Nabi, Ilya Shpitser

Identification theory for causal effects in causal models associated with hidden variable directed acyclic graphs (DAGs) is well studied. However, the corresponding algorithms are underused due to the complexity of estimating the identifying functionals they output. In this work, we bridge the gap between identification and estimation of population-level cau

D. Dalmazi, A. L. R. dos Santos

Here we start from a dual version of Vasiliev's first order action for massless spin-2 particles (linearized first order Einstein-Hilbert) and derive, via Kaluza-Klein dimensional reduction from $D+1$ to $D$ dimensions, a set of dual massive spin-2 models. This set includes the massive "BR" model, a spin-2 analogue of the spin-1 Cremmer-Scherk model. In our

Maarten V. de Hoop, Joonas Ilmavirta, Matti Lassas, Teemu Saksala

The broken scattering relation consists of the total lengths of broken geodesics that start from the boundary, change direction once inside the manifold, and propagate to the boundary. We show that if two reversible Finsler manifolds satisfying a convex foliation condition have the same broken scattering relation, then they are isometric. This implies that s

Sudhakantha Girmohanta, Robert Shrock

We study baryon-number-violating processes, including proton and bound neutron decays and $n-\bar n$ oscillations, in a left-right-symmetric (LRS) model in which quarks and leptons have localized wavefunctions in extra dimensions. In this model we show that, while one can easily suppress baryon-number-violating nucleon decays well below experimental bounds,

Santosh Kumar Radha, Walter R. L. Lambrecht

Higher Order Topological Insulators (HOTI) are $d$-spatial dimensional systems featuring topologically protected gap-less states at their $(d-n)$-dimensional boundaries. With the help of \textit{ab-initio} calculations and tight binding models along with symmetry considerations we show that monolayer buckled honeycomb structures of group-V elements (Sb,As),

Z. Koohi Lai, A. Namaki, A. Hosseiny, G. R. Jafari

In this paper, we are interested to focus on the critical periods in the economy which are characterized by large fluctuations in macroeconomic indicators. To capture unusual and large fluctuations of inflation and unemployment, we concentrate on the non-Gaussianity of their distributions. To this aim, by using the coupled multifractal approach, we analyze U

A. B. Balantekin, H. R. Band, C. D. Bass, D. E. Bergeron

Reactor neutrino experiments have seen major improvements in precision in recent years. With the experimental uncertainties becoming lower than those from theory, carefully considering all sources of $\overline{\nu}_{e}$ is important when making theoretical predictions. One source of $\overline{\nu}_{e}$ that is often neglected arises from the irradiation of

Saeed Moghimi, Andre van der Westhuysen, Ali Abdolali, Edward Myers

To enable flexible model coupling in coastal inundation studies, a coupling framework based on ESMF/NUOPC technology under a common modeling framework called the NOAA Environmental Modeling System (NEMS) was developed. The framework is essentially a software wrapper around atmospheric, wave and storm surge models that enables its components communicate seaml

Ghanem Meriem, Bouroubi Sadek

One of the methods used in order to protect a secret K is a secret sharing scheme. In this scheme the secret K is distributed among a finite set of participants P by a special participant called the dealer, in such a way that only predefined subsets of participants can recover the secret after collaborating with their secret shares. The construction of secre

Yuri V. Kovchegov, M. Gabriel Santiago

We calculate the single transverse spin asymmetry (STSA) in polarized proton-proton ($p^{\uparrow}+p$) and polarized proton-nucleus ($p^{\uparrow}+A$) collisions ($A_N$) generated by a partonic lensing mechanism. The polarized proton is considered in the quark-diquark model while its interaction with the unpolarized target is calculated using the small-$x$/s

Sai Bi, Kalyan Sunkavalli, Federico Perazzi, Eli Shechtman

We present a method to improve the visual realism of low-quality, synthetic images, e.g. OpenGL renderings. Training an unpaired synthetic-to-real translation network in image space is severely under-constrained and produces visible artifacts. Instead, we propose a semi-supervised approach that operates on the disentangled shading and albedo layers of the im

Taras Turiv, Jess Krieger, Greta Babakhanova, Hao Yu

Biological cells in living tissues form dynamic patterns with local orientational order and topological defects. Here we demonstrate an approach to produce cell monolayer with the predesigned orientational patterns using human dermal fibroblast cells (HDF) placed onto a photoaligned liquid crystal elastomer (LCE). The alignment of cells is caused by anisotro

E. A. Sevost'yanov

We study mappings satisfying the so-called inverse Poletsky inequality. Under integrability of the corresponding majorant, it is proved that these mappings are logarithmic H\"{o}lder continuous in the neighborhood of the boundary points. In particular, the indicated properties hold for homeomorphisms whose inverse satisfy the weighted Poletsky inequality.

Planck Collaboration, Y. Akrami, M. Ashdown, J. Aumont

The largest temperature anisotropy in the cosmic microwave background (CMB) is the dipole, which has been measured with increasing accuracy for more than three decades, particularly with the Planck satellite. The simplest interpretation of the dipole is that it is due to our motion with respect to the rest frame of the CMB. Since current CMB experiments infe

Graham D. Finlayson, Yuteng Zhu

When we place a colored filter in front of a camera the effective camera response functions are equal to the given camera spectral sensitivities multiplied by the filter spectral transmittance. In this paper, we solve for the filter which returns the modified sensitivities as close to being a linear transformation from the color matching functions of human v

Erick Schulz, Ralf Hiptmair

We couple the mixed variational problem for the generalized Hodge-Helmholtz or Hodge-Laplace equation posed on a bounded three-dimensional Lipschitz domain with the first-kind boundary integral equation arising from the latter when constant coefficients are assumed in the unbounded complement. Recently developed Calderon projectors for the relevant boundary

Anderson Ara, Mateus Maia, Samuel Macêdo, Francisco Louzada

Machine learning techniques always aim to reduce the generalized prediction error. In order to reduce it, ensemble methods present a good approach combining several models that results in a greater forecasting capacity. The Random Machines already have been demonstrated as strong technique, i.e: high predictive power, to classification tasks, in this article

Sai Bi, Zexiang Xu, Kalyan Sunkavalli, David Kriegman

We introduce a novel learning-based method to reconstruct the high-quality geometry and complex, spatially-varying BRDF of an arbitrary object from a sparse set of only six images captured by wide-baseline cameras under collocated point lighting. We first estimate per-view depth maps using a deep multi-view stereo network; these depth maps are used to coarse

Petr Pokorny, Menelaos Sarantos, Diego Janches, Erwan Mazarico

While the floors of deep lunar craters are largely shielded from solar radiation and thus provide an ideal thermal environment for water ice accumulation, meteoroids on highly inclined orbits can easily access permanently shadowed regions and alter the surface properties via hyper-velocity impacts. Here we consider the detailed topography of lunar poles and

Jacopo Borga, Mickaël Maazoun

Baxter permutations, plane bipolar orientations, and a specific family of walks in the non-negative quadrant are well-known to be related to each other through several bijections. We introduce a further new family of discrete objects, called coalescent-walk processes, that are fundamental for our results. We relate these new objects with the other previously

Vinicius G. Goecks, Grayson Woods, John Valasek

Advances in machine learning and deep neural networks for object detection, coupled with lower cost and power requirements of cameras, led to promising vision-based solutions for sUAS detection. However, solely relying on the visible spectrum has previously led to reliability issues in low contrast scenarios such as sUAS flying below the treeline and against

Erfaun Noorani, Yagiz Savas, Alec Koppel, John Baras

We consider a network of agents that locate themselves in an environment through sensor measurements and aim to transmit a message signal to a base station via collaborative beamforming. The agents' sensor measurements result in localization errors, which degrade the quality of service at the base station due to unknown phase offsets that arise in the agents

Peter Bierhorst, Yanbao Zhang

We classify the extreme points of a polytope of probability distributions in the (2,2,2) CHSH-Bell setting that is induced by a single Tsirelson bound. We do the same for a class of polytopes obtained from a parametrized family of multiple Tsirelson bounds interacting non-trivially. Such constructions can be applied to device-independent random number genera

C. Seshadhri, Aneesh Sharma, Andrew Stolman, Ashish Goel

The study of complex networks is a significant development in modern science, and has enriched the social sciences, biology, physics, and computer science. Models and algorithms for such networks are pervasive in our society, and impact human behavior via social networks, search engines, and recommender systems to name a few. A widely used algorithmic techni

D. Nesvorny, D. Vokrouhlicky, W. F. Bottke, H. F. Levison

A recent examination of K2 lightcurves indicates that ~15% of Jupiter Trojans have very slow rotation (spin periods Ps>100 h). Here we consider the possibility that these bodies formed as equal-size binaries in the massive outer disk at ~20-30 au. Prior to their implantation as Jupiter Trojans, tight binaries tidally evolved toward a synchronous state with P

Davis Gilton, Ruotian Luo, Rebecca Willett, Greg Shakhnarovich

This paper presents a framework for the analysis of changes in visual streams: ordered sequences of images, possibly separated by significant time gaps. We propose a new approach to incorporating unlabeled data into training to generate natural language descriptions of change. We also develop a framework for estimating the time of change in visual stream. We

Tamzidul Hoque, Shuo Yang, Aritra Bhattacharyay, Jonathan Cruz

Economic and operational advantages have led the supply chain of printed circuit boards (PCBs) to incorporate various untrusted entities. Any of the untrusted entities are capable of introducing malicious alterations to facilitate a functional failure or leakage of secret information during field operation. While researchers have been investigating the threa

Zhibin Gao, Minghui LiWang, Seyyedali Hosseinalipour, Huaiyu Dai

Vehicular cloud computing has emerged as a promising solution to fulfill users' demands on processing computation-intensive applications in modern driving environments. Such applications are commonly represented by graphs consisting of components and edges. However, encouraging vehicles to share resources poses significant challenges owing to users' selfishn

Anastasiia Sheveleva, Ugo Andral, Bertrand Kibler, Sonia Boscolo

We analyse the temporal properties of the optical pulse wave that is obtained by applying a set of spectral $\pi/2$ phase shifts to continuous-wave light that is phase-modulated by a temporal sinusoidal wave. We develop an analytical model to describe this new optical waveform that we name 'besselon'. We also discuss the reduction of sidelobes in the wave in

Raniere de Menezes, Raul A. Amaya-Almazán, Ezequiel J. Marchesini, Harold A. Peña-Herazo

The fourth Fermi Large Area Telescope Source Catalog (4FGL) lists over 5000 gamma-ray sources with statistical significance above 4$\sigma$. About 23% of the sources listed in this catalog are unidentified/unassociated gamma-ray sources while ~26% of the sources are classified as blazar candidates of uncertain type (BCUs), lacking optical spectroscopic infor

Trevor W. Richardson, Wencheng Wu, Lei Lin, Beilei Xu

We consider the topic of data imputation, a foundational task in machine learning that addresses issues with missing data. To that end, we propose MCFlow, a deep framework for imputation that leverages normalizing flow generative models and Monte Carlo sampling. We address the causality dilemma that arises when training models with incomplete data by introdu

Kai Xuan, Liping Si, Lichi Zhang, Zhong Xue

High-quality magnetic resonance (MR) image, i.e., with near isotropic voxel spacing, is desirable in various scenarios of medical image analysis. However, many MR acquisitions use large inter-slice spacing in clinical practice. In this work, we propose a novel deep-learning-based super-resolution algorithm to generate high-resolution (HR) MR images with smal

Martin Redmann, Sebastian Riedel

We study Runge-Kutta methods for rough differential equations which can be used to calculate solutions to stochastic differential equations driven by processes that are rougher than a Brownian motion. We use a Taylor series representation (B-series) for both the numerical scheme and the solution of the rough differential equation in order to determine condit

Qian Wang, Neelanjan Bhowmik, Toby P. Breckon

X-ray Computed Tomography (CT) based 3D imaging is widely used in airports for aviation security screening whilst prior work on prohibited item detection focuses primarily on 2D X-ray imagery. In this paper, we aim to evaluate the possibility of extending the automatic prohibited item detection from 2D X-ray imagery to volumetric 3D CT baggage security scree

Gang Zhao, D. Michelle Bailey, Adam J. Fleisher, Joseph T. Hodges

We report Doppler-free two-photon absorption of N$_2$O at $\lambda$ = 4.53 $\mu$m, measured by cavity ring-down spectroscopy. High power was achieved by optical self-locking of a quantum cascade laser to a linear resonator of finesse $F$ = 22730, and accurate laser detuning over a 400 MHz range was measured relative to an optical frequency comb. At a sample

Kurt Schab

Relative bounds on radiation efficiency are established for time-modulated antenna systems where radiation is generated by broadband conduction currents impressed using idealized non-radiating time-varying subsystems, such as those found in direct antenna modulation (DAM) transmitters. Analytical and numerical examples demonstrate that the condition of quasi

Armen Avetisyan, Tatiana Khanova, Christopher Choy, Denver Dash

We present a novel approach to reconstructing lightweight, CAD-based representations of scanned 3D environments from commodity RGB-D sensors. Our key idea is to jointly optimize for both CAD model alignments as well as layout estimations of the scanned scene, explicitly modeling inter-relationships between objects-to-objects and objects-to-layout. Since obje

Kamran Chitsaz, Mohsen Hajabdollahi, Nader Karimi, Shadrokh Samavi

Convolutional neural networks (CNNs) have a large number of variables and hence suffer from a complexity problem for their implementation. Different methods and techniques have developed to alleviate the problem of CNN's complexity, such as quantization, pruning, etc. Among the different simplification methods, computation in the Fourier domain is regarded a

Karlo Lelas, Ozana Čelan, David Prelogović, Hrvoje Buljan

We theoretically investigate the phenomenon of modulation instability for systems obeying nonlinear Schr\"odinger equation, which are under the influence of an external homogeneous synthetic magnetic field. For an initial condition, the instability is detected numerically by comparing dynamics with and without a small initial perturbation; the perturbations

Xavier Carvajal, Liliana Esquivel, Raphael Santos

We consider the initial value problem associated to a system consisting modified Korteweg-de Vries type equations $$ \partial_tv + \partial_x^3v + \partial_x(vw^2) =0,\ \ v(x,0)=\phi(x), $$ $$ \partial_tw + \alpha\partial_x^3w + \partial_x(v^2w) =0,\ \ w(x,0)=\psi(x),$$ and prove the local well-posedness results for given data in low regularity Sobolev space

Alex Golts, Yoav Y. Schechner

Computer vision tasks are often expected to be executed on compressed images. Classical image compression standards like JPEG 2000 are widely used. However, they do not account for the specific end-task at hand. Motivated by works on recurrent neural network (RNN)-based image compression and three-dimensional (3D) reconstruction, we propose unified network a

Hugo Aduén, Sigifredo Herrón

The present work has two objectives. First, we prove that a weight\-ed superlinear elliptic problem has infinitely many nonradial solutions in the unit ball. Second, we obtain the same conclusion in annuli for a more general nonlinearity which also involves a weight. We use a lower estimate of the energy level of radial solutions with $k-1$ zeros in the inte

Hamid Rajabalipanah, Mohammad Hosein Fakheri, Ali Abdolali

Over the last couple of years, the digital coding acoustic metasurfaces have been developed rapidly as a highly active research area for their unique and flexible manipulation of acoustic wavefronts. Nevertheless, all recent attentions in the acoustic community have been mainly concentrated on space-encoded architectures, leaving the room free for benefiting

Roman Belousov, Muhammad Nawaz Qaisrani, Ali Hassanali, Édgar Roldán

The extent to which biological interfaces affect the dynamics of water plays a key role in the exchange of matter and chemical interactions that are essential for life. The density and the mobility of water molecules depend on their proximity to biological interfaces and can play an important role in processes such as protein folding and aggregation. In this

T. Alshaabi, J. R. Minot, M. V. Arnold, J. L. Adams

In confronting the global spread of the coronavirus disease COVID-19 pandemic we must have coordinated medical, operational, and political responses. In all efforts, data is crucial. Fundamentally, and in the possible absence of a vaccine for 12 to 18 months, we need universal, well-documented testing for both the presence of the disease as well as confirmed

Xuezhou Zhang, Yuzhe Ma, Adish Singla, Xiaojin Zhu

In reward-poisoning attacks against reinforcement learning (RL), an attacker can perturb the environment reward $r_t$ into $r_t+\delta_t$ at each step, with the goal of forcing the RL agent to learn a nefarious policy. We categorize such attacks by the infinity-norm constraint on $\delta_t$: We provide a lower threshold below which reward-poisoning attack is

Feliks Przytycki, Anna Zdunik

We prove that for every polynomial of one complex variable of degree at least 2 and Julia set not being totally disconnected nor a circle, nor interval, Hausdorff dimension of this Julia set is larger than 1. Till now this was known only in the connected Julia set case. We give also an example of a polynomial with non-connected but not totally disconnected J

Angelo A. Salatino, Francesco Osborne, Enrico Motta

Ontologies of research areas have been proven to be useful in many application for analysing and making sense of scholarly data. In this chapter, we present the Computer Science Ontology (CSO), which is the largest ontology of research areas in the field of Computer Science, and discuss a number of applications that build on CSO, to support high-level tasks,

Zhiqiang Sui, Haonan Chang, Ning Xu, Odest Chadwicke Jenkins

We propose GeoFusion, a SLAM-based scene estimation method for building an object-level semantic map in dense clutter. In dense clutter, objects are often in close contact and severe occlusions, which brings more false detections and noisy pose estimates from existing perception methods. To solve these problems, our key insight is to consider geometric consi

Yuanbo T. Tang, Phani Karamched, Junliang Liu, Jack C. Haley

The serration of grain boundaries in Inconel 600 caused by heat treatment is studied systematically. A new method based on Fourier transforms is used to analyse the multiple wave-like character of the serrated grain boundaries. A new metric -- the serration index -- is devised and utilised to quantify the degree of serration and more generally to distinguish

Helena Albuquerque, Elisabete Barreiro, Saïd Benayadi, Mohamed Boucetta

Oscillator Lie algebras are the only non commutative solvable Lie algebras which carry a bi-invariant Lorentzian metric. In this paper, we determine all the Poisson structures, and in particular, all symmetric Leibniz algebra structures whose underlying Lie algebra is an oscillator Lie algebra. We give also all the symmetric Leibniz bialgebra structures whos

Helena Albuquerque, Elisabete Barreiro, Antonio J. Calderón, José M. Sánchez

Consider a Leibniz superalgebra $\mathfrak L$ additionally graded by an arbitrary set $I$ (set grading). We show that $\mathfrak L$ decomposes as the sum of well-described graded ideals plus (maybe) a suitable linear subspace. In the case of ${\mathfrak L}$ being of maximal length, the simplicity of ${\mathfrak L}$ is also characterized in terms of connectio

Valentina De Romeri, Dimitrios Karamitros, Oleg Lebedev, Takashi Toma

Sterile neutrinos are one of the leading dark matter candidates. Their masses may originate from a vacuum expectation value of a scalar field. If the sterile neutrino couplings are very small and their direct coupling to the inflaton is forbidden by the lepton number symmetry, the leading dark matter production mechanism is the freeze-in scenario. We study t

Emilie Frost, Eric MSP Veith, Lars Fischer

Modern power grids need to cope with increasingly decentralized, volatile energy sources as well as new business models such as virtual power plants constituted from battery swarms. This warrants both, day-ahead planning of larger schedules for power plants, as well as short-term contracting to counter forecast deviations or to accommodate dynamics of the in

Niklas Kühl, Marc Goutier, Robin Hirt, Gerhard Satzger

The application of "machine learning" and "artificial intelligence" has become popular within the last decade. Both terms are frequently used in science and media, sometimes interchangeably, sometimes with different meanings. In this work, we aim to clarify the relationship between these terms and, in particular, to specify the contribution of machine learni

Svenja Laing, Niklas Kühl

Most people spend up to 90 % of their time indoors. However, literature in the field of facility management and related disciplines mostly focus on energy and cost saving aspects of buildings. Especially in the area of commercial buildings, only few articles take a user-centric perspective and none of them considers the subjectivity of thermal comfort. This

Michael Foxe, Theodore Bowyer, Rachel Carr, John Orrell

Fission explosions produce large numbers of antineutrinos. It is occasionally asked whether this distinctive, unshieldable emission could help reveal clandestine nuclear weapon explosions. The practical challenge encountered is that detectors large enough for this application are cost prohibitive, likely on the multi-billion-dollar scale. In this paper, we r

Tomás Alves, Samuel Gomes, João Dias, Carlos Martinho

Throughout the years, social norms have been promoted as an informal enforcement mechanism for achieving beneficial collective outcomes. Among the most used methods to foster interactions, framing the context of a situation or setting in-game rules have shown strong results as mediators on how an individual interacts with their peers. Nevertheless, we found

Luis C. Barbado, Esteban Castro-Ruiz, Luca Apadula, Časlav Brukner

The Unruh effect is the phenomenon that accelerated observers detect particles even when inertial observers experience the vacuum state. In particular, uniformly accelerated observers are predicted to measure thermal radiation that is proportional to the acceleration. Here we consider the Unruh effect for a detector that follows a quantum superposition of di

Sharad Joshi, Suraj Saxena, Nitin Khanna

Vast volumes of printed documents continue to be used for various important as well as trivial applications. Such applications often rely on the information provided in the form of printed text documents whose integrity verification poses a challenge due to time constraints and lack of resources. Source printer identification provides essential information a

Narges Ghaffarzadeh, Morteza Faghfouri

In this paper, we aim to introduce and study $(\kappa, \mu)$-contact pseudo-metric manifold and prove that if the $\varphi$-sectional curvature of any point of $M$ is independent of the choice of $\varphi$-section at the point, then it is constant on $M$ and accordingly the curvature tensor. Also, we introduce generalized $(\kappa, \mu)$-contact pseudo-metri