July 2019 arXiv papers — page 14

Chenfeng Xu, Kai Qiu, Jianlong Fu, Song Bai

Dense crowd counting aims to predict thousands of human instances from an image, by calculating integrals of a density map over image pixels. Existing approaches mainly suffer from the extreme density variances. Such density pattern shift poses challenges even for multi-scale model ensembling. In this paper, we propose a simple yet effective approach to tack

J. Sperling, W. Vogel

We study the quasiprobability representation of quantum light, as introduced by Glauber and Sudarshan, for the unified characterization of quantum phenomena. We begin with reviewing the past and current impact of this technique. Regularization and convolution methods are specifically considered since they are accessible in experiments. We further discuss mor

Guanghui Hu, Peijun Li, Yue Zhao

Consider the elastic scattering of a plane or point incident wave by an unbounded and rigid rough surface. The angular spectrum representation (ASR) for the time-harmonic Navier equation is derived in three dimensions. The ASR is utilized as a radiation condition to the elastic rough surface scattering problem. The uniqueness is proved through a Rellich-type

Amy Tabb, Khalil M. Ahmad Yousef

Robot-world, hand-eye calibration is the problem of determining the transformation between the robot end-effector and a camera, as well as the transformation between the robot base and the world coordinate system. This relationship has been modeled as $\mathbf{AX}=\mathbf{ZB}$, where $\mathbf{X}$ and $\mathbf{Z}$ are unknown homogeneous transformation matric

Bo Jiang, Xiang Meng, Zaiwen Wen, Xiaojun Chen

Optimization with nonnegative orthogonality constraints has wide applications in machine learning and data sciences. It is NP-hard due to some combinatorial properties of the constraints. We first propose an equivalent optimization formulation with nonnegative and multiple spherical constraints and an additional single nonlinear constraint. Various constrain

D. T. Adroja, Shivani Sharma, C. Ritter, A. D. Hillier

The magnetic ground state of double perovskite Sr2DyRuO6 has been investigated using muon spin rotation and relaxation (muSR), neutron powder diffraction (NPD) and inelastic neutron scattering (INS), in addition to heat capacity and magnetic susceptibility (ac and dc) measurements. A clear signature of a long-range ordered magnetic ground state has been obse

Benedetto Militello, Nikolay Vitanov

The multistate Majorana model in the presence of dissipation and dephasing is considered. It is proven that increasing the Hilbert space dimension the system becomes more and more fragile to quantum noise. The impossibility to recast the problem in the form of a set of independent spin-$1/2$ problems because of the presence of the noise is pointed out.

Jaroslav Čmejla, Tomáš Kounovský, Sharon Gannot, Zbyněk Koldovský

We introduce a database of multi-channel recordings performed in an acoustic lab with adjustable reverberation time. The recordings provide information about room impulse responses (RIR) for various positions of a loudspeaker. In particular, the main positions correspond to 4104 vertices of a cube-shaped dense grid within a 46x36x32 cm volume. The database t

Takara Suzuki, Yuta Saito, Paul Fons, Alexander V. Kolobov

Chalcogenide superlattices (SL) consist of alternate stacking of GeTe and Sb$_{2}$Te$_{3}$ layers. The structure can become a 3D topological insulator depending on the constituent layer thicknesses, making the design of the SL period a central issue for advancing chalcogenide SL as potential candidates for spin devices as well as for optimization of the curr

Tomasz Karpiuk, Marek Nikołajuk, Mariusz Gajda, Mirosław Brewczyk

We study the final stages of the evolution of a binary system consisted of a black hole and a white dwarf star. We implement the quantum hydrodynamic equations and carry out numerical simulations. As a model of a white dwarf star, we consider a zero temperature droplet of attractively interacting degenerate atomic bosons and spin-polarized atomic fermions. S

Nasr Ahmed, Anirudh Pradhan

We investigate the cosmic acceleration and the evolution of dark energy across the cosmological constant boundary in universal extra dimensions UED. We adopt an empirical approach to solve the higher-dimensional cosmological equations so that the deceleration parameter $q$ is consistent with observations. The expressions for the jerk and deceleration paramet

E. Yusofi, M. Khanpour, B. Khanpour, M. Ramzanpour

The cosmological constant is estimated by considering the surface tension of supervoids in a void-dominated cosmic fluid by which we can get a possible source of dark energy. Looking at voids as bubbles, we define the concept of surface tension which is shown to have an almost constant value for supervoids that are enclosed by superclusters. The surface tens

I. D. Karachentsev, L. N. Makarova

We use images from the Hubble Space Telescope to determine the distances to a dozen objects with low surface brightness recently observed around the bright nearby spiral M101. Only two dwarf galaxies, M101-DwA and M101-Dw9, turn out to be actual satellites of M101 at distances of about 7 Mpc. The other objects are probably members of a distant group around t

Wanli Shi, Bin Gu, Xiang Li, Xiang Geng

Semi-supervised learning is pervasive in real-world applications, where only a few labeled data are available and large amounts of instances remain unlabeled. Since AUC is an important model evaluation metric in classification, directly optimizing AUC in semi-supervised learning scenario has drawn much attention in the machine learning community. Recently, i

Nantia Makrynioti, Ruy Ley-Wild, Vasilis Vassalos

We present sql4ml, a system for expressing supervised machine learning (ML) models in SQL and automatically training them in TensorFlow. The primary motivation for this work stems from the observation that in many data science tasks there is a back-and-forth between a relational database that stores the data and a machine learning framework. Data preprocessi

Daichi Kagamihara, Daisuke Inotani, Yoji Ohashi

We theoretically investigate the shear viscosity $\eta$ in the BCS-BEC crossover regime of an ultracold Fermi gas with a Feshbach resonance. Within the framework of the strong-coupling self-consistent $T$-matrix approximation, we examine how a strong pairing interaction associated with a Feshbach resonance affects this transport coefficient, in the normal st

Fabian Sperrle, Rita Sevastjanova, Rebecca Kehlbeck, Mennatallah El-Assady

Argumentation Mining addresses the challenging tasks of identifying boundaries of argumentative text fragments and extracting their relationships. Fully automated solutions do not reach satisfactory accuracy due to their insufficient incorporation of semantics and domain knowledge. Therefore, experts currently rely on time-consuming manual annotations. In th

Yu Sun, Shuohuan Wang, Yukun Li, Shikun Feng

Recently, pre-trained models have achieved state-of-the-art results in various language understanding tasks, which indicates that pre-training on large-scale corpora may play a crucial role in natural language processing. Current pre-training procedures usually focus on training the model with several simple tasks to grasp the co-occurrence of words or sente

B. Prabadevi, N. Jeyanthi, Nur Izura Udzir, Dhinaharan Nagamalai

Sniffing is one of the most prominent causes for most of the attacks in the digitized computing environment. Through various packet analyzers or sniffers available free of cost, the network packets can be captured and analyzed. The sensitive information of the victim like user credentials, passwords, a PIN which is of more considerable interest to the assail

Kevin Bandura, Emanuele Castorina, Liam Connor, Simon Foreman

PUMA is a proposal for an ultra-wideband, low-resolution and transit interferometric radio telescope operating at $200-1100\,\mathrm{MHz}$. Its design is driven by six science goals which span three science themes: the physics of dark energy (measuring the expansion history and growth of the universe up to $z=6$), the physics of inflation (constraining primo

Tianyi Wu, Sheng Tang, Rui Zhang, Guodong Guo

Scene parsing is challenging as it aims to assign one of the semantic categories to each pixel in scene images. Thus, pixel-level features are desired for scene parsing. However, classification networks are dominated by the discriminative portion, so directly applying classification networks to scene parsing will result in inconsistent parsing predictions wi

Chaoyun Zhang, Marco Fiore, Iain Murray, Paul Patras

This paper introduces CloudLSTM, a new branch of recurrent neural models tailored to forecasting over data streams generated by geospatial point-cloud sources. We design a Dynamic Point-cloud Convolution (DConv) operator as the core component of CloudLSTMs, which performs convolution directly over point-clouds and extracts local spatial features from sets of

Hyun Min Lee

We give a brief overview on the successes and theoretical problems of the Standard Model and discuss the basics of low-scale supersymmetry. We also address some of recent proposals for physics beyond the Standard Model and the connection to the production mechanisms for thermal dark matter.

Rodrigo A. Velez, Alexander L. Brown

We study the plausibility of sub-optimal Nash equilibria of the direct revelation mechanism associated with a strategy-proof social choice function. By using the recently introduced empirical equilibrium analysis (Velez and Brown, 2019, arXiv:1804.07986) we determine that this behavior is plausible only when the social choice function violates a non-bossines

A Müller, S Schippers, J Hellhund, A L D Kilcoyne

Experimental and theoretical cross sections are reported for single-photon single ionization of W$^{5+}$ ions. Absolute measurements were conducted employing the photon-ion merged-beams technique. Detailed photon-energy scans were performed at (67$\pm$10)~meV resolution in the 20 -- 160 eV range. In contrast to photoionization of tungsten ions in lower charg

Mario Coccia

Killer technology is a radical innovation, based on new products and/or processes, that with high technical and/or economic performance destroys the usage value of established techniques previously sold and used. Killer technology is a new concept in economics of innovation that may be useful for bringing a new perspective to explain and generalize the behav

Sylvain Rubenthaler

We are interested in a fragmentation process. We observe fragments frozen when their sizes are less than $\epsilon$ ($\epsilon$ > 0). Is is known ([BM05]) that the empirical measure of these fragments converges in law, under some renormalization. In [HK11], the authors show a bound for the rate of convergence. Here, we show a central-limit theorem, under som

Luis Miranda, Guido Schillaci

This work deals with the portability of greenhouse models, as we believe that this is a challenge to their practical usage in control strategies under production conditions. We address this task by means of adaptive neural networks, which re-adjust their weights when transferred to new conditions. Such an adaptive account for computational models is typical

Jean-Marc Ginoux, Heikki Ruskeepää, Matjaž Perc, Roomila Naeck

A database of ten type 1 diabetes patients wearing a continuous glucose monitoring device has enabled to record their blood glucose continuous variations every minute all day long during fourteen consecutive days. These recordings represent, for each patient, a time series consisting of 1 value of glycaemia per minute during 24 hours and 14 days, i.e., 20,16

Michaela Regneri, Julia S. Georgi, Jurij Kost, Niklas Pietsch

We present an approach to compute the monetary value of individual data points, in context of an automated decision system. The proposed method enables us to explore and implement a paradigm of data minimalism for large-scale machine learning systems. Data minimalistic implementations enhance scalability, while maintaining or even optimizing a system's perfo

Yuriy Zacchia Lun, Alessandro D'Innocenzo

The communication channels used to convey information between the components of wireless networked control systems (WNCSs) are subject to packet losses due to time-varying fading and interference. The WNCSs with missing packets can be modeled as Markov jump linear systems with one time-step delayed mode observations. While the problem of the optimal linear q

Hans Boehringer, Gayoung Chon, Chris A. Collins

For precision cosmological studies it is important to know the local properties of the reference point from which we observe the Universe. Particularly for the determination of the Hubble constant with low-redshift distance indicators, the values observed depend on the average matter density within the distance range covered. Here we used the spatial distrib

Akinori F. Ebihara, Kazuyuki Sakurai, Hitoshi Imaoka

In light of the rising demand for biometric-authentication systems, preventing face spoofing attacks is a critical issue for the safe deployment of face recognition systems. Here, we propose an efficient face presentation attack detection (PAD) algorithm that requires minimal hardware and only a small database, making it suitable for resource-constrained dev

Tomoaki Niiyama, Genki Furuhata, Atsushi Uchida, Makoto Naruse

Decision making is a fundamental capability of living organisms, and has recently been gaining increasing importance in many engineering applications. Here, we consider a simple decision-making principle to identify an optimal choice in multi-armed bandit (MAB) problems, which is fundamental in the context of reinforcement learning. We demonstrate that the i

Matthew Ludkin, Chris Sherlock

We introduced the Hug and Hop Markov chain Monte Carlo algorithm for estimating expectations with respect to an intractable distribution. The algorithm alternates between two kernels: Hug and Hop. Hug is a non-reversible kernel that repeatedly applies the bounce mechanism from the recently proposed Bouncy Particle Sampler to produce a proposal point far from

Laurent Chuat, Sarah Plocher, Adrian Perrig

User authentication can rely on various factors (e.g., a password, a cryptographic key, biometric data) but should not reveal any secret or private information. This seemingly paradoxical feat can be achieved through zero-knowledge proofs. Unfortunately, naive password-based approaches still prevail on the web. Multi-factor authentication schemes address som

G. Rastelli, W. Belzig

We discuss two theoretical proposals for controlling the nonequilibrium steady state of nanomechanical resonators using quantum electronic transport. Specifically?, we analyse two approaches to achieve the ground-state cooling of the mechanical vibration coupled to a quantum dot embedded between (i) spin-polarised contacts or (ii) a normal metal and a superc

Satoshi Sunada, Atsushi Uchida

High-dimensional nonlinear dynamical systems including neural networks can be utilized as a computational resource for information processing. In this sense, nonlinear wave systems are good candidate for such a computational resource. Here, we propose and numerically demonstrate information processing based on nonlinear wave dynamics in microcavity lasers, i

Elena Kopylova

We prove global well-posedness for 3D Dirac equation with a concentrated nonlinearity.

M. O. Musa, H. Temimi, Y. Zhu

We present detailed numerical simulations of semiclassical and quantum spectra of a cavity quantum electrodynamics system consisting of a single three-level atom in $\Lambda$-configuration with one of its transitions strongly interacting with a quantized cavity mode while the other is driven by a coherent classical field. After deriving the equations of moti

P. Murali Doraiswamy, Charlotte Blease, Kaylee Bodner

Futurists have predicted that new technologies, embedded with artificial intelligence (AI) and machine learning (ML), will lead to substantial job loss in many sectors disrupting many aspects of healthcare. Mental health appears ripe for such disruption given the global illness burden, stigma, and shortage of care providers. Using Sermo, a global networking

Michael Fröwis, Rainer Böhme

Efficient transfers to many recipients present a host of issues on Ethereum. First, accounts are identified by long and incompressible constants. Second, these constants have to be stored and communicated for each payment. Third, the standard interface for token transfers does not support lists of recipients, adding repeated communication to the overhead. Si

Matin Hosseinzadeh, Patrick Brand, Henkjan Huisman

We propose and evaluate a novel method for automatically detecting clinically significant prostate cancer (csPCa) in bi-parametric magnetic resonance imaging (bpMRI). Prostate zones play an important role in the assessment of prostate cancer on MRI. We hypothesize that the inclusion of zonal information can improve the performance of a deep learning based cs

Javad Asadollahi, Rasool Hafezi, Somayeh Sadeghi

Let $\Lambda$ be an artin algebra. In this paper, the notion of $n\mathbb{Z}$-Gorenstein cluster tilting subcategories will be introduced. It is shown that every $n\mathbb{Z}$-cluster tilting subcategory of ${\rm{mod}}{\mbox{-}}\Lambda$ is $n\mathbb{Z}$-Gorenstein if and only if $\Lambda$ is an Iwanaga-Gorenstein algebra. Moreover, it will be shown that an $

Kristine Heiney, Ola Huse Ramstad, Ioanna Sandvig, Axel Sandvig

In this work, we report the preliminary analysis of the electrophysiological behavior of in vitro neuronal networks to identify when the networks are in a critical state based on the size distribution of network-wide avalanches of activity. The results presented here demonstrate the importance of selecting appropriate parameters in the evaluation of the size

Jing-Yang You, Bo Gu, Gang Su

In recent experiments, superconductivity and correlated insulating states were observed in twisted bilayer graphene (TBG) with small magic angles, which highlights the importance of the flat bands near Fermi energy. However, the moir\'e pattern of TBG consists of more than ten thousand carbon atoms that is not easy to handle with conventional methods. By den

Valerio Sorichetti, Virginie Hugouvieux, Walter Kob

In our previous publication (Ref. 1) we have shown that the data for the normalized diffusion coefficient of the polymers, $D_p/D_{p0}$, falls on a master curve when plotted as a function of $h/\lambda_d$, where $h$ is the mean interparticle distance and $\lambda_d$ is a dynamic length scale. In the present note we show that also the normalized diffusion coe

Daniel V. Mathews

We give another version of Huang's proof that an induced subgraph of the n-dimensional cube graph containing over half the vertices has maximal degree at least $\sqrt{n}$, which implies the Sensitivity Conjecture. This argument uses Clifford algebras of positive definite signature in a natural way. We also prove a weighted version of the result.

B. Olmi, N. Bucciantini

Bow shock pulsar wind nebulae are observed with a variety of complex morphologies at different wavelengths, most likely due to differences in the magnetic field strength and pulsar wind geometry. Here we present a detailed analysis, showing how these differences affect the observational properties in these systems, focusing on non-thermal synchrotron emissio

Reinmar J. Kobler, Andreea I. Sburlea, Valeria Mondini, Gernot R. Müller-Putz

A high fraction of artifact-free signals is highly desirable in functional neuroimaging and brain-computer interfacing (BCI). We present the high-variance electrode artifact removal (HEAR) algorithm to remove transient electrode pop and drift (PD) artifacts from electroencephalographic (EEG) signals. Transient PD artifacts reflect impedance variations at the

Shengyu Zhao, Yue Dong, Eric I-Chao Chang, Yan Xu

We present recursive cascaded networks, a general architecture that enables learning deep cascades, for deformable image registration. The proposed architecture is simple in design and can be built on any base network. The moving image is warped successively by each cascade and finally aligned to the fixed image; this procedure is recursive in a way that eve

Sarkis Halladjian, Haichao Miao, David Kouřil, M. Eduard Gröller

We present ScaleTrotter, a conceptual framework for an interactive, multi-scale visualization of biological mesoscale data and, specifically, genome data. ScaleTrotter allows viewers to smoothly transition from the nucleus of a cell to the atomistic composition of the DNA, while bridging several orders of magnitude in scale. The challenges in creating an int

Joey M. van Langen

We prove that the equation ${ (x - y)^4 + x^4 + (x + y)^4 = z^n }$ has no integer solutions ${ x, y, z}$ with ${ \gcd(x, y) = 1 }$ for all integers ${ n > 1 }$. We mainly use a modular approach with two Frey ${ \mathbb{Q} }$-curves defined over the field ${ \mathbb{Q}( \sqrt{30} ) }$.

Oliver Goertsches, Eugenia Loiudice

We observe that the class of metric $f$-$K$-contact manifolds, which naturally contains that of $K$-contact manifolds, is closed under forming mapping tori of automorphisms of the structure. We show that the de Rham cohomology of compact metric $f$-$K$-contact manifolds naturally splits off an exterior algebra, and relate the closed leaves of the characteris

Matteo Ravasi, Ivan Vasconcelos

Linear operators and optimisation are at the core of many algorithms used in signal and image processing, remote sensing, and inverse problems. For small to medium-scale problems, existing software packages (e.g., MATLAB, Python numpy and scipy) allow for explicitly building dense (or sparse) matrices and performing algebraic operations (e.g., computation of

Sourav Ghosh

In this article we construct the pressure form on the moduli space of higher dimensional Margulis spacetimes without cusps and study its properties. We show that the Margulis spacetimes are infinitesimally determined by their marked Margulis invariant spectrums. We use it to show that the restrictions of the pressure form give Riemannian metrics on the const

Xiang Li, Tianhan Wei, Yau Pun Chen, Yu-Wing Tai

Over the past few years, we have witnessed the success of deep learning in image recognition thanks to the availability of large-scale human-annotated datasets such as PASCAL VOC, ImageNet, and COCO. Although these datasets have covered a wide range of object categories, there are still a significant number of objects that are not included. Can we perform th

Anton Rodomanov, Yurii Nesterov

In this paper, we study derivatives of powers of Euclidean norm. We prove their H\"older continuity and establish explicit expressions for the corresponding constants. We show that these constants are optimal for odd derivatives and at most two times suboptimal for the even ones. In the particular case of integer powers, when the H\"older continuity transfor

Jesús J. Doménech, John P. Gallagher, Samir Genaim

Control-flow refinement refers to program transformations whose purpose is to make implicit control-flow explicit, and is used in the context of program analysis to increase precision. Several techniques have been suggested for different programming models, typically tailored to improving precision for a particular analysis. In this paper we explore the use

Thomas Eiter, Paul Ogris, Konstantin Schekotihin

Stream reasoning systems are designed for complex decision-making from possibly infinite, dynamic streams of data. Modern approaches to stream reasoning are usually performing their computations using stand-alone solvers, which incrementally update their internal state and return results as the new portions of data streams are pushed. However, the performanc

Jacopo Pantaleoni

In order to efficiently sample specular-diffuse-glossy and glossy-diffuse-glossy transport phenomena, Tokuyoshi and Harada introduced hierarchical Russian roulette, a smart algorithm that allows to compute the minimum of the random numbers associated to leaves of a tree at each internal node. The algorithm is used to efficiently cull the connections between

Xuelong Li, Hongli Li, Yongsheng Dong

Existing video summarization approaches mainly concentrate on sequential or structural characteristic of video data. However, they do not pay enough attention to the video summarization task itself. In this paper, we propose a meta learning method for performing task-driven video summarization, denoted by MetaL-TDVS, to explicitly explore the video summariza

J. S. K. -L. Gibson, J. Gonzalez-Julian, S. Krishnan, R. Vaßen

MAX phases have great potential under demands of both high-temperature and high-stress performance, with their mixed atomic bonding producing the temperature and oxidation resistance of ceramics with the mechanical resilience of metals. Here, we measure the mechanical properties up to 980C by nanoindentation on highly dense and pure Cr$_2$AlC, as well as aft

Peng Zhao, Guanghui Wang, Lijun Zhang, Zhi-Hua Zhou

Bandit Convex Optimization (BCO) is a fundamental framework for modeling sequential decision-making with partial information, where the only feedback available to the player is the one-point or two-point function values. In this paper, we investigate BCO in non-stationary environments and choose the \emph{dynamic regret} as the performance measure, which is

Fabian Klos, Daniel Roggenkamp

We study bulk RG flows in the context of TQFTs and show how IR theories can be entirely represented within the respective UV theories by means of codimension-one projection defects. What is more, RG flows of the bulk theory can be described in terms of RG flows of the codimension-one identity defect in the fixed UV bulk theory. We illustrate this in the exam

Xiao Li, Fengcheng Wu, Allan H. MacDonald

Small-twist-angle bilayer graphene supports strongly correlated insulating states and superconductivity. Twisted few-layer graphene systems are likely to open up new directions for strong correlation physics in moir\'e superlattices. We derive and study moir\'e band models that describe the electronic structure of graphene trilayers in which one of the three

Sherman W. Marcus, Ariel Epstein

Realization of the anomalous refraction effects predicted by Huygens' metasurfaces (HMS) have required tedious and time-consuming trial-and-error numerical full-wave computations. It is shown herein that these requirements can be alleviated for transverse magnetic (TM) propagation by a periodic dielectric-based HMS consisting of an electrically thick array o

Umar Riaz Muhammad, Yongxin Yang, Timothy M. Hospedales, Tao Xiang

Automatic data abstraction is an important capability for both benchmarking machine intelligence and supporting summarization applications. In the former one asks whether a machine can `understand' enough about the meaning of input data to produce a meaningful but more compact abstraction. In the latter this capability is exploited for saving space or human

Robert Ganian, Sebastian Ordyniak, Stefan Szeider

We propose joinwidth, a new complexity parameter for the Constraint Satisfaction Problem (CSP). The definition of joinwidth is based on the arrangement of basic operations on relations (joins, projections, and pruning), which inherently reflects the steps required to solve the instance. We use joinwidth to obtain polynomial-time algorithms (if a correspondin

Pieterjan Robbe, Dirk Nuyens, Stefan Vandewalle

In many models used in engineering and science, material properties are uncertain or spatially varying. For example, in geophysics, and porous media flow in particular, the uncertain permeability of the material is modelled as a random field. These random fields can be highly anisotropic. Efficient solvers, such as the Multiple Semi-Coarsened Multigrid (MSG)

Eugeny Babichev, Keisuke Izumi, Norihiro Tanahashi, Masahide Yamaguchi

We formulate explicitly the necessary and sufficient conditions for the local invertibility of a field transformation involving derivative terms. Our approach is to apply the method of characteristics of differential equations, by treating such a transformation as differential equations that give new variables in terms of original ones. The obtained results

Arpan Das, Deepak Kumar, Hiranmaya Mishra

We estimate here chiral susceptibility at finite temperature within the framework of the Nambu-Jona-Lasinio model (NJL) using the Wigner function approach. We also estimate it in the presence of chiral chemical potential ($\mu_5$) as well as a non vanishing magnetic field ($B$). We use medium separation regularization scheme (MSS) to calculate the chiral con

Pedro M. Gordaliza, Juan José Vaquero, Sally Sharpe, Fergus Gleeson

We propose a learning method well-suited to infer the presence of Tuberculosis (TB) manifestations on Computer Tomography (CT) scans mimicking the radiologist reports. Latent features are extracted from the CT volumes employing the V-Net encoder and those are the input to a Feed-Forward Neural Network (FNN) for multi-class classification. To overtake the iss

Grzegorz Jacenków, Agisilaos Chartsias, Brian Mohr, Sotirios A. Tsaftaris

We compare two conditioning mechanisms based on concatenation and feature-wise modulation to integrate non-imaging information into convolutional neural networks for segmentation of anatomical structures. As a proof-of-concept we provide the distribution of class labels obtained from ground truth masks to ensure strong correlation between the conditioning da

K. Sowndhariya, A. Muthusamy

we define the sunlet graph is the graph obtained by taking one copy of the cycle and joined every vertex of the cycle to an exactly one pendant vertex such that the degree of each vertex in the cycle is three. In this paper, we establish necessary and sufficient conditions for the existence of decomposition of the Cartesian product of complete graphs into su

Vlad Bally, Lucia Caramellino, Guillaume Poly

We provide a simple abstract formalism of integration by parts under which we obtain some regularization lemmas. These lemmas apply to any sequence of random variables $(F_n)$ which are smooth and non-degenerated in some sense and enable one to upgrade the distance of convergence from smooth Wasserstein distances to total variation in a quantitative way. Thi

Philip Reinhold, Serge Rosenblum, Wen-Long Ma, Luigi Frunzio

To solve classically hard problems, quantum computers need to be resilient to the influence of noise and decoherence. In such a fault-tolerant quantum computer, noise-induced errors must be detected and corrected in real-time to prevent them from propagating between components. This requirement is especially pertinent while applying quantum gates, when the i

Anna S. Bodrova, Igor M. Sokolov

We consider a random two-phase process which we call a reset-return one. The particle starts its motion at the origin. The first, displacement, phase corresponds to a stochastic motion of a particle and is finished at a resetting event. The second, return, phase corresponds to the particle's motion towards the origin from the position it attained at the end

Tomáš Masopust, Markus Krötzsch

Partially ordered automata are automata where the transition relation induces a partial order on states. The expressive power of partially ordered automata is closely related to the expressivity of fragments of first-order logic on finite words or, equivalently, to the language classes of the levels of the Straubing-Th\'erien hierarchy. Several fragments (le

Adeboye Stephen Oyeniran, Raimund Ubar, Maksim Jenihhin, Cemil Cem Gursoy

A new high-level implementation independent functional fault model for control faults in microprocessors is introduced. The fault model is based on the instruction set, and is specified as a set of data constraints to be satisfied by test data generation. We show that the high-level test, which satisfies these data constraints, will be sufficient to guarante

Samuele Cornia, Francesco Rossella, Valeria Demontis, Valentina Zannier

With downscaling of electronic circuits, components based on semiconductor quantum dots are assuming increasing relevance for future technologies. Their response under external stimuli intrinsically depend on their quantum properties. Here we investigate single-electron tunneling in hard-wall InAs/InP nanowires in the presence of an off-resonant microwave dr

N. F. Shul'ga, V. D. Koriukina

On the basis of the eikonal approximation of quantum scattering theory, the problem of fast charged particles scattering in a thin crystal when particles fall along one its plane of atoms and in a thin layer of amorphous matter is considered. It is shown that the scattering cross section in this problem, for parameters, which are beyond the scope of applicat

Andreas Defant, Ingo Schoolmann

A theorem of Henry Helson shows that for every ordinary Dirichlet series $\sum a_n n^{-s}$ with a square summable sequence $(a_n)$ of coefficients, almost all vertical limits $\sum a_n \chi(n) n^{-s}$, where $\chi: \mathbb{N} \to \mathbb{T}$ is a completely multiplicative arithmetic function, converge on the right half-plane. We survey on recent improvements

Jonas Greitemann, Ke Liu, Ludovic D. C. Jaubert, Han Yan

Machine-learning techniques have proved successful in identifying ordered phases of matter. However, it remains an open question how far they can contribute to the understanding of phases without broken symmetry, such as spin liquids. Here we demonstrate how a machine learning approach can automatically learn the intricate phase diagram of a classical frustr

Hans van Ditmarsch, Malvin Gattinger, Louwe B. Kuijer, Pere Pardo

Distributed dynamic gossip is a generalization of the classic telephone problem in which agents communicate to share secrets, with the additional twist that also telephone numbers are exchanged to determine who can call whom. Recent work focused on the success conditions of simple protocols such as "Learn New Secrets" (LNS) wherein an agent a may only call a

Etienne Savalle, Christine Guerlin, Pacôme Delva, Frédéric Meynadier

We investigate the performance of the upcoming ACES (Atomic Clock Ensemble in Space) space mission in terms of its primary scientific objective, the test of the gravitational redshift. Whilst the ultimate performance of that test is determined by the systematic uncertainty of the on-board clock at 2-3 ppm, we determine whether, and under which conditions, th

Haipeng Zeng, Xingbo Wang, Aoyu Wu, Yong Wang

Emotions play a key role in human communication and public presentations. Human emotions are usually expressed through multiple modalities. Therefore, exploring multimodal emotions and their coherence is of great value for understanding emotional expressions in presentations and improving presentation skills. However, manually watching and studying presentat

Susanna Risa, Carlo Sinestrari

We consider geometric flows of hypersurfaces expanding by a function of the extrinsic curvature and we show that the homothethic sphere is the unique solution of the flow which converges to a point at the initial time. The result does not require assumptions on the speed other than positivity and monotonicity and it is proved using a reflection argument. Our

Bruno Rodriguez Del Pino, Santiago Arribas, Javier Piqueras Lopez, Alejandro Crespo Gomez

We present and discuss the properties of an ionized component with extreme kinematics in an off-nuclear HII region located at 0.8 - 1.0 kpc from the nucleus of SDSS J143245.98+404300.3, recently reported in Rodriguez del Pino et al. (2019). The high-velocity gas component is identified by the detection of very broad emission wings in the Halpha line, with Fu

Kazumi Kashiyama, Kotaro Fujisawa, Toshikazu Shigeyama

WD J005311 is a newly identified white dwarf (WD) in a mid-infrared nebula. The spectroscopic observation indicates the existence of a neon-enriched carbon/oxygen wind with a terminal velocity of $v_{\infty,\rm obs}\sim 16,000\,\rm km\,s^{-1}$ and a mass loss rate of $\dot M_{\rm obs}\sim 3.5\times 10^{-6}\,M_\odot$ yr$^{-1}$. Here we consistently explain th

Eugénio Ribeiro, Ricardo Ribeiro, David Martins de Matos

Dialog acts reveal the intention behind the uttered words. Thus, their automatic recognition is important for a dialog system trying to understand its conversational partner. The study presented in this article approaches that task on the DIHANA corpus, whose three-level dialog act annotation scheme poses problems which have not been explored in recent studi

Christian Helanow

The basal sliding of glaciers and ice sheets can constitute a large part of the total observed ice velocity, in particular in dynamically active areas. It is therefore important to accurately represent this process in numerical models. The condition that the sliding velocity should be tangential to the bed is realized by imposing an impenetrability condition

Thomas L. A. van den Heuvel, Chris L. de Korte, Bram van Ginneken

In this study, we combine a standardized acquisition protocol with image analysis algorithms to investigate if it is possible to automatically detect maternal risk factors without a trained sonographer. The standardized acquisition protocol can be taught to any health care worker within two hours. This protocol was acquired from 280 pregnant women at St.\ Lu

Weiyong He, Lu Xu, Mingbo Zhang

The Gursky-Streets equation are introduced as the geodesic equation of a metric structure in conformal geometry. This geometric structure has played a substantial role in the proof of uniqueness of $\sigma_2$ Yamabe problem in dimension four. In this paper we solve the Gursky-Streets equations with uniform $C^{1, 1}$ estimates for $2k\leq n$. An important ne

Giulia Codenotti, Francisco Santos

We show that the following classes of lattice polytopes have unimodular covers, in dimension three: the class of parallelepipeds, the class of centrally symmetric polytopes, and the class of Cayley sums $\text{Cay}(P,Q)$ where the normal fan of $Q$ refines that of $P$. This improves results of Beck et al.~(2018) and Haase et al.~(2008) where the last two cla

Masato Tsuboi, Yoshimi Kitamura, Takahiro Tsutsumi, Ryosuke Miyawaki

We detected a compact ionized gas associated physically with IRS13E3, an Intermediate Mass Black Hole (IMBH) candidate in the Galactic Center, in the continuum emission at 232 GHz and H30$\alpha$ recombination line using ALMA Cy.5 observation (2017.1.00503.S, P.I. M.Tsuboi). The continuum emission image shows that IRS13E3 is surrounded by an oval-like struct

Anna Miriam Benini, Núria Fagella

We consider entire transcendental maps with bounded set of singular values such that periodic rays exist and land. For such maps, we prove a refined version of the Fatou-Shishikura inequality which takes into account rationally invisible periodic orbits, that is, repelling cycles which are not landing points of any periodic ray. More precisely, if there are

Sushrut Thorat, Giacomo Aldegheri, Marcel A. J. van Gerven, Marius V. Peelen

In daily life situations, we have to perform multiple tasks given a visual stimulus, which requires task-relevant information to be transmitted through our visual system. When it is not possible to transmit all the possibly relevant information to higher layers, due to a bottleneck, task-based modulation of early visual processing might be necessary. In this

Roland Bauerschmidt, Thierry Bodineau

We derive a multiscale generalisation of the Bakry--\'Emery criterion for a measure to satisfy a Log-Sobolev inequality. Our criterion relies on the control of an associated PDE well known in renormalisation theory: the Polchinski equation. It implies the usual Bakry--\'Emery criterion, but we show that it remains effective for measures which are far from lo

Philipp Gorczak, Caner Bektas, Fabian Kurtz, Thomas Lübcke

Unmanned aerial vehicles (UAV) are a promising technology for fast, large scale survey operations such as maritime search and rescue (SAR). However, providing reliable communications over long distances remains a challenge. Cellular technology such as Long Term Evolution (LTE) is designed to perform well in the presence of fast-moving clients and highly dyna