November 2020 arXiv papers — page 17

B. Chencarek, M. Nascimento, A. M. Souza, R. S. Sarthour

In this work, we present a characterization of phase configuration in water-saturated sintered glass bead samples after oil injection, through the analysis of time-dependent diffusion coefficients obtained from sets of one-dimensional pulsed field gradient nuclear magnetic resonance (PFG NMR) measurements, pre and post drainage. Estimates of samples surface-

Achraf Ben Miled, Taoufik Yeferny, Amira ben Rabeh

Alzheimer's disease is a neurogenerative disease that alters memories, cognitive functions leading to death. Early diagnosis of the disease, by detection of the preliminary stage, called Mild Cognitive Impairment (MCI), remains a challenging issue. In this respect, we introduce, in this paper, a powerful classification architecture that implements the pre-tr

Maximilian Probst Gutenberg

In this thesis, we present new techniques to deal with fundamental algorithmic graph problems where graphs are directed and partially dynamic, i.e. undergo either a sequence of edge insertions or deletions: - Single-Source Reachability (SSR), - Strongly-Connected Components (SCCs), and - Single-Source Shortest Paths (SSSP). These problems have recently recei

Yilmaz Simsek

The aim of this paper is to give a novel generalization of the Leibnitz numbers derived from application of the Beta function to the modification for the Bernstein basis functions. We also give some properties of the Leibnitz numbers with the aid of their generating functions derived from the Volkenborn integral on the set of $p$-adic integers. We also give

Jan Beyersmann, Tim Friede, Claudia Schmoor

As a reaction to the pandemic of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a multitude of clinical trials for the treatment of SARS-CoV-2 or the resulting corona disease (COVID-19) are globally at various stages from planning to completion. Although some attempts were made to standardize study designs, this was hindered by the ferocit

C. Schreiber, K. Glazebrook, C. Papovich, T. Diaz-Santos

Understanding the process of quenching is one of the major open questions in galaxy evolution, and crucial insights may be obtained by studying quenched galaxies at high redshifts, at epochs when the Universe and the galaxies were younger and simpler to model. However, establishing the degree of quiescence in high redshift galaxies is a challenging task. One

Thomas Bendokat, Ralf Zimmermann, P. -A. Absil

The Grassmann manifold of linear subspaces is important for the mathematical modelling of a multitude of applications, ranging from problems in machine learning, computer vision and image processing to low-rank matrix optimization problems, dynamic low-rank decompositions and model reduction. With this mostly expository work, we aim to provide a collection o

Sofian Hamad, Taoufik Yeferny

Thanks to the great progress in mobile and wireless technologies, Internet-distributed applications like P2P file sharing are nowadays deployed over MANET (i.e., P2P mobile systems). These applications allow users to search and share diverse multimedia resources over MANET. Due the nature of MANET, P2P mobile systems brought up many new thriving challenges r

Mickael Tardy, Diana Mateus

We study the fully convolutional neural networks in the context of malignancy detection for breast cancer screening. We work on a supervised segmentation task looking for an acceptable compromise between the precision of the network and the computational complexity.

Morten Nielsen

In this article we construct orthonormal bases compatible with bi-variate homogeneous $\alpha$-modulation spaces and the associated spaces of Triebel-Lizorkin type. The construction is based on generating a separable $\alpha$-covering and using carefully selected tensor products of univariate brushlet functions with regards to this covering. We show that the

Mingfu Xue, Chengxiang Yuan, Can He, Zhiyu Wu

Recently, the membership inference attack poses a serious threat to the privacy of confidential training data of machine learning models. This paper proposes a novel adversarial example based privacy-preserving technique (AEPPT), which adds the crafted adversarial perturbations to the prediction of the target model to mislead the adversary's membership infer

Sjoerd van der Heide, Ruben S. Luis, Benjamin J. Puttnam, Georg Rademacher

We introduce a flexible, software-defined real-time multi-modulation format receiver implemented on an off-the-shelf general-purpose graphics processing unit (GPU). The flexible receiver is able to process 2 GBaud 2-, 4-, 8-, and 16-ary pulse-amplitude modulation (PAM) signals as well as 1 GBaud 4-, 16- and 64-ary quadrature amplitude modulation (QAM) signal

Vincent Audigier, Ndèye Niang

Multiple imputation (MI) is a popular method for dealing with missing values. However, the suitable way for applying clustering after MI remains unclear: how to pool partitions? How to assess the clustering instability when data are incomplete? By answering both questions, this paper proposed a complete view of clustering with missing data using MI. The prob

I. D. Breev, K. V. Likhachev, V. V. Yakovleva, R. Hübner

We grow AlN/4H-SiC and AlN/6H-SiC heterostructures by physical vapor deposition and characterize the heterointerface with nanoscale resolution. Furthermore, we investigate the spatial stress and strain distribution in these heterostructures using confocal Raman spectroscopy. We measure the spectral shifts of various vibrational Raman modes across the heteroi

Xiaojun Wu

In this work, following the fundamental work of Boucksom we construct the nef cone of a compact complex manifold in higher codimension and give explicit examples where these cones are different. In the third section, we give two versions of Kawamata-Viehweg vanishing theorems in terms of nefness in higher codimension and numerical dimensions. We also show by

Mingfu Xue, Chengxiang Yuan, Can He, Jian Wang

In this paper, we propose a natural and robust physical adversarial example attack method targeting object detectors under real-world conditions. The generated adversarial examples are robust to various physical constraints and visually look similar to the original images, thus these adversarial examples are natural to humans and will not cause any suspicion

G. Ramesh, B. Sudip ranjan, D. Venku Naidu

We study the hypercyclic, supercyclic and cyclic properties of composition operator $C_{\phi}$ on the Segal-Bargmann space $\mathscr{H}(\mathscr{E})$, where $\phi (z)=Az+b$, $A\in \mathcal{B}(\mathscr{E})$, $b\in \mathscr{E}$ with $\left\|A\right\|\leq 1$ and $A^*b\in (I-A^*A)^{\frac{1}{2}}$. In this connection we also give a characterization of the symbols

Brahmanandam Javvaji, Ramakrishna Vasireddi, Xiaoying Zhuang, D Roy Mahapatra

Synthesis of graphene with reduced use of chemical reagents is essential for manufacturing scale-up and to control its structure and properties. In this paper, we report on a novel chemical-free mechanism of graphene exfoliation from graphite using laser impulse. Our experimental setup consists of a graphite slab irradiated with an Nd:YAG laser of wavelength

Andrei Haidu, Michael Beetz

In this paper we present a system capable of collecting and annotating, human performed, robot understandable, everyday activities from virtual environments. The human movements are mapped in the simulated world using off-the-shelf virtual reality devices with full body, and eye tracking capabilities. All the interactions in the virtual world are physically

Chenyan Wu, Yukun Chen, Jiajia Luo, Che-Chun Su

Body orientation estimation provides crucial visual cues in many applications, including robotics and autonomous driving. It is particularly desirable when 3-D pose estimation is difficult to infer due to poor image resolution, occlusion or indistinguishable body parts. We present COCO-MEBOW (Monocular Estimation of Body Orientation in the Wild), a new large

Marc Chataigner, Stephane Crepey, Jiang Pu

We devise a neural network based compression/completion methodology for financial nowcasting. The latter is meant in a broad sense encompassing completion of gridded values, interpolation, or outlier detection, in the context of financial time series of curves or surfaces (also applicable in higher dimensions, at least in theory). In particular, we introduce

Meng-Hua Zhu, Kai Wunnemann, Ross W. K. Potter, Thorsten Kleine

The Moon exhibits striking geological asymmetries in elevation, crustal thickness, and composition between its nearside and farside. Although several scenarios have been proposed to explain these asymmetries, their origin remains debated. Recent remote sensing observations suggest that (1) the crust on the farside highlands consists of two layers: a primary

Arindam Mazumdar, Subhendra Mohanty, Priyank Parashari

Self-interaction in the active neutrinos is studied in the literature to alleviate the $H_0$ tension. Similar self-interaction can also explain the observed dips in the flux of the neutrinos coming from the distant astro-physical sources in IceCube detectors. In contrast to the flavour universal neutrino interaction considered for solving the $H_0$ tension,

Takuya Minamikawa, Toru Kojo, Masayasu Harada

We construct an equation of state (EOS) for neutron stars by interpolating hadronic EOS at low density and quark EOS at high density. A hadronic model based on the parity doublet structure is used for hadronic matter and a quark model of Nambu--Jona-Lasinio type is for quark matter. We assume crossover between hadronic matter and quark matter in the the colo

Daiji Tsutsui

In order to circumvent the difficulties in solving numerically the discrete optimal transport problem, in which one minimizes the linear target function $P\mapsto\langle C,P\rangle:=\sum_{i,j}C_{ij}P_{ij}$, Cuturi introduced a variant of the problem in which the target function is altered by a convex one $\Phi(P)=\langle C,P\rangle-\lambda\mathcal{H}(P)$, wh

Meng-Hua Zhu, Natalia Artemieva, Alessandro Morbidelli, Qing-Zhu Yin

The importance of highly siderophile elements (HSEs) to track planetary late accretion has long been recognized. However, the precise nature of the Moon's accretional history remains enigmatic. There exists a significant mismatch of HSE budgets between the Earth and Moon, with the Earth disproportionally accreted far more HSEs than the Moon did. Several scen

Arjun Mani, Nobline Yoo, Will Hinthorn, Olga Russakovsky

Visual Question Answering (VQA) has become one of the key benchmarks of visual recognition progress. Multiple VQA extensions have been explored to better simulate real-world settings: different question formulations, changing training and test distributions, conversational consistency in dialogues, and explanation-based answering. In this work, we further ex

Leonardo Santilli, Miguel Tierz

We show that the Riemannian Gaussian distributions on symmetric spaces, introduced in recent years, are of standard random matrix type. We exploit this to compute analytically marginals of the probability density functions. This can be done fully, using Stieltjes-Wigert orthogonal polynomials, for the case of the space of Hermitian matrices, where the distri

Francisco Araújo, Paulo R. Pinto

Every representation of the Cuntz algebra $\mathcal{O}_n$ leads to a unitary representation of the Higman-Thompson group $V_n$. We consider the family $\{\pi_x\}_{x\in [0,1[}$ of permutative representations of $\mathcal{O}_n$ that arise from the interval map $f(x)=nx$ (mod 1) acting on the Hilbert space that underlies each orbit, and then study the unitary e

Andras Gyarfas, Gabor N. Sarkozy

In this paper we study Tur\'an and Ramsey numbers in linear triple systems, defined as $3$-uniform hypergraphs in which any two triples intersect in at most one vertex. A famous result of Ruzsa and Szemer\'edi is that for any fixed $c>0$ and large enough $n$ the following Tur\'an-type theorem holds. If a linear triple system on $n$ vertices has at least $cn^

Songtao Liu, Zeming Li, Jian Sun

In this paper, we propose a novel self-supervised representation learning method, Self-EMD, for object detection. Our method directly trained on unlabeled non-iconic image dataset like COCO, instead of commonly used iconic-object image dataset like ImageNet. We keep the convolutional feature maps as the image embedding to preserve spatial structures and adop

Anderson Queiroz, Eduardo Oliveira, Maria Barbosa, Kelvin Dias

With the advent of Intelligent Transportation Systems (ITS), data from diverse sensors either embedded into the vehicles or present along with the smart city infrastructure, are of utmost importance and require both processing power and efficient trust mechanisms for information exchange in vehicle-to-everything (V2X) communications. To accomplish these requ

Yang Zhao, Wei Jia, Ronggang Wang

With the rapid development of image restoration techniques, high-definition reconstruction of early videos has achieved impressive results. However, there are few studies about the interlacing artifacts that often appear in early videos and significantly affect visual perception. Traditional deinterlacing approaches are mainly focused on early interlacing sc

Christian Fredrik Sætre, Anton S. Shiriaev, Leonid B. Freidovich, Sergei V. Gusev

The design of robust orbitally stabilizing feedback is considered. From a known orbitally stabilizing controller for a nominal, disturbance-free system, a robustifying feedback extension is designed utilizing the sliding-mode control (SMC) methodology. The main contribution of the paper is to provide a constructive procedure for designing the time-invariant

Xiaojun Wu

Junyan Cao has obtained a very general vanishing theorem, valid on any compact K\"ahler manifold, for the cohomology groups with values in a pseudoeffective line bundle twisted by the associated multiplier ideal sheaf. In this note, we give a version of this result in terms of the numerical dimension of the line bundle, instead of the numerical dimension of

Peter Schmelcher

Superexponential systems are characterized by a potential where dynamical degrees of freedom appear in both the base and the exponent of a power law. We explore the scattering dynamics of many-body systems governed by superexponential potentials. Each potential term exhibits a characteristic crossover via two saddle points from a region with a confining chan

Foster Tom

In recent years, Alexandersson and others proved combinatorial formulas for the Schur function expansion of the horizontal-strip LLT polynomial $G_\lambda(x;q)$ in some special cases. We associate a weighted graph $\Pi$ to $\lambda$ and we use it to express a linear relation among LLT polynomials. We apply this relation to prove an explicit combinatorial Sch

Timm Faulwasser, Lars Grüne

The turnpike property refers to the phenomenon that in many optimal control problems, the solutions for different initial conditions and varying horizons approach a neighborhood of a specific steady state, then stay in this neighborhood for the major part of the time horizon, until they may finally depart. While early observations of the phenomenon can be tr

Marlon Marcon, Olga Regina Pereira Bellon, Luciano Silva

Object recognition and 6DoF pose estimation are quite challenging tasks in computer vision applications. Despite efficiency in such tasks, standard methods deliver far from real-time processing rates. This paper presents a novel pipeline to estimate a fine 6DoF pose of objects, applied to realistic scenarios in real-time. We split our proposal into three mai

Nathalie Ysard

A key element when modeling dust in any astrophysical environment is a self-consistent treatment of the evolution of the dust material properties (size distribution, chemical composition and structure) as they react to and adjust to the local radiation field intensity and hardness and to the gas density and dynamics. The best way to achieve this goal is to a

Ning-Chen Sun, Justyn R. Maund, Paul A. Crowther, Xuan Fang

Core-collapse supernovae (SNe) are the inevitable fate of most massive stars. Since most stars form in groups, SN progenitors can be constrained with information of their environments. It remains challenging to accurately analyse the various components in the environment and to correctly identify their relationships with the SN progenitors. Using a combined

Vesa Julin, Joonas Niinikoski

We consider the flat flow approach for the mean curvature equation with forcing in an Euclidean space $\mathbb R^n$ of dimension at least 2. Our main results states that tangential balls in $\mathbb R^n$ under any flat flow with a bounded forcing term will experience fattening, which generalizes the result by Fusco, Julin and Morini from the planar case to h

Gioacchino Antonelli, Enrico Le Donne

We generalize both the notion of polynomial functions on Lie groups and the notion of horizontally affine maps on Carnot groups. We fix a subset $S$ of the algebra $\mathfrak g$ of left-invariant vector fields on a Lie group $\mathbb G$ and we assume that $S$ Lie generates $\mathfrak g$. We say that a function $f:\mathbb G\to \mathbb R$ (or more generally a

Jonas Blessing, Michael Kupper

Under suitable conditions on a family $(I(t))_{t\ge 0}$ of Lipschitz mappings on a complete metric space, we show that up to a subsequence the strong limit $S(t):=\lim_{n\to\infty}(I(t 2^{-n}))^{2^n}$ exists for all dyadic time points $t$, and extends to a strongly continuous semigroup $(S(t))_{t\ge 0}$. The common idea in the present approach is to find con

Sanjoy Basak, Sreeraj Rajendran, Sofie Pollin, Bart Scheers

Detecting UAVs is becoming more crucial for various industries such as airports and nuclear power plants for improving surveillance and security measures. Exploiting radio frequency (RF) based drone control and communication enables a passive way of drone detection for a wide range of environments and even without favourable line of sight (LOS) conditions. I

Fajri Koto, Timothy Baldwin, Jey Han Lau

In this paper, we propose FFCI, a framework for fine-grained summarization evaluation that comprises four elements: faithfulness (degree of factual consistency with the source), focus (precision of summary content relative to the reference), coverage (recall of summary content relative to the reference), and inter-sentential coherence (document fluency betwe

Yuansi Chen

We prove an almost constant lower bound of the isoperimetric coefficient in the KLS conjecture. The lower bound has the dimension dependency $d^{-o_d(1)}$. When the dimension is large enough, our lower bound is tighter than the previous best bound which has the dimension dependency $d^{-1/4}$. Improving the current best lower bound of the isoperimetric coeff

Roy Maartens, Sheean Jolicoeur, Obinna Umeh, Eline M. De Weerd

Next-generation galaxy and 21cm intensity mapping surveys will rely on a combination of the power spectrum and bispectrum for high-precision measurements of primordial non-Gaussianity. In turn, these measurements will allow us to distinguish between various models of inflation. However, precision observations require theoretical precision at least at the sam

Falk Bannuscher, Alastair Litterick, Tomohiro Uchiyama

Let $k$ be a nonperfect separably closed field. Let $G$ be a connected reductive algebraic group defined over $k$. We study rationality problems for Serre's notion of complete reducibility of subgroups of $G$. In particular, we present the first example of a connected nonabelian $k$-subgroup $H$ of $G$ that is $G$-completely reducible but not $G$-completely

Adrien Bussonnière, Isabelle Cantat

Liquid foam exhibits surprisingly high viscosity, higher than each of its phases. This dissipation enhancement has been rationalized by invoking either a geometrical confinement of the shear in the liquid phase, or the influence of the interface viscosity. However, a precise localization of the dissipation, and its mechanism, at the bubble scale is still lac

Lirong Deng, Xuan Zhang, Tianshu Yang, Hongbin Sun

In this paper, we address an optimal management problem of community energy storage in the real-time electricity market under a stochastic renewable environment. In a real-time electricity market, complete market information may not be assessable for a strategic participant, hence we propose a paradigm that uses partial information including the forecast of

A. Armatol, E. Armengaud, W. Armstrong, C. Augier

The CUPID Collaboration is designing a tonne-scale, background-free detector to search for double beta decay with sufficient sensitivity to fully explore the parameter space corresponding to the inverted neutrino mass hierarchy scenario. One of the CUPID demonstrators, CUPID-Mo, has proved the potential of enriched Li$_{2}$$^{100}$MoO$_4$ crystals as suitabl

Payam Shahsavari Baboukani, Carina Graversen, Emina Alickovic, Jan Østergaard

We propose a new estimator to measure directed dependencies in time series. The dimensionality of data is first reduced using a new non-uniform embedding technique, where the variables are ranked according to a weighted sum of the amount of new information and improvement of the prediction accuracy provided by the variables. Then, using a greedy approach, th

Matteo Fael, Kay Schönwald, Matthias Steinhauser

We compute corrections of order $\alpha_s^3$ to the decay $b \to c \ell \bar\nu$ taking into account massive charm quarks. In the on-shell scheme large three-loop corrections are found. However, in the kinetic scheme the three-loop corrections are below 1\% and thus perturbation theory is well under control. We furthermore provide results for the order $\alp

Xiaojun Wu

In this note, we state various generalisations of the Nakano vanishing theorem under weak positivity assumptions, and compare them with the known results.

Lirong Deng, Xuan Zhang, Tianshu Yang, Hongbin Sun

In this paper, we propose a convex planning model of integrated heat and electricity systems considering variable mass flow rates. The main challenge comes from the non-convexity of the bilinear terms in the district heating network, i.e., the product of mass flow rate and nodal temperature. To resolve this issue, we first reformulate the district heating ne

Linus Bergqvist

We study membership of rational inner functions in Dirichlet-type spaces in polydisks. In particular, we prove a theorem relating such inclusions to $H^p$ integrability of partial derivatives of a RIF, and as a corollary we prove that all rational inner functions on $\mathbb{D}^n$ belong to $\mathcal{D}_{1/n, \ldots ,1/n}(\mathbb{D}^n)$. Furthermore, we show

Yu Deng, Jiaolong Yang, Xin Tong

We propose a novel Deformed Implicit Field (DIF) representation for modeling 3D shapes of a category and generating dense correspondences among shapes. With DIF, a 3D shape is represented by a template implicit field shared across the category, together with a 3D deformation field and a correction field dedicated for each shape instance. Shape correspondence

Takuma Doi, Fumio Okura, Toshiki Nagahara, Yasuyuki Matsushita

This paper proposes a multi-view extension of instance segmentation without relying on texture or shape descriptor matching. Multi-view instance segmentation becomes challenging for scenes with repetitive textures and shapes, e.g., plant leaves, due to the difficulty of multi-view matching using texture or shape descriptors. To this end, we propose a multi-v

Julien Sedro

We show that the response, frozen and semifreddo fractional susceptibility functions of certain real-analytic unimodal families, at Misiurewicz parameters and for fractional differentiation index $0\le\eta<1/2$, are holomorphic on a disk of radius greater than one. This is a step towards solving a conjecture of Baladi and Smania, in the case of the aforement

Simone Mellace, K Vani, Alessandro Antonucci

When coping with literary texts such as novels or short stories, the extraction of structured information in the form of a knowledge graph might be hindered by the huge number of possible relations between the entities corresponding to the characters in the novel and the consequent hurdles in gathering supervised information about them. Such issue is address

Zhihua Sun, Yi Liu, Kani Chen, Gang Li

Broken adaptive ridge (BAR) is a computationally scalable surrogate to $L_0$-penalized regression, which involves iteratively performing reweighted $L_2$ penalized regressions and enjoys some appealing properties of both $L_0$ and $L_2$ penalized regressions while avoiding some of their limitations. In this paper, we extend the BAR method to the semi-paramet

Martin Ottersten, Hua-Dong Yao, Lars Davidson

In this study, tonal noise produced by an isolated centrifugal fan is investigated using unsteady Reynolds-averaged Navier-Stokes (URANS) equations. This type of fans is used in ventilation systems. As the fan propagates tonal noise in the system, it can severely affect the life quality of people that reside in the buildings. Our simulation shows that turbul

V. D. Paccoia, O. Panella, P. Roy

We study the quantum backflow problem in the noncommutative plane. In particular, we have considered a charged particle with and without an oscillator interaction with noncommuting momentum operators and examined angular momentum backflow in each case and how they differ from each other. We also propose a probability associated with the occurence of angular

Qianhang Ding

We show that the gravitational wave signals from primordial black hole (PBH) binaries at high redshift can be detected. The detectability of PBH binaries is enhanced by redshift bias and more PBH binaries at high redshift. The initial clustering of PBHs is also included and enhances the effectively detectable mass ranges of PBHs at high redshift. Future obse

M. M. Bandi

Face masks in general, and N95 filtering facepiece respirators (FRs) that protect against SARS-Cov-2 virion in particular, have become scarce during the ongoing COVID-19 global pandemic. This work presents practical design principles for the fabrication of electrocharged filtration layers employed in N95 FRs using commonly available materials and easily repl

Sergey Ershkov, Alla Rachinskaya

In this paper, we present a new ansatz for approximated solving equations of motion of the infinitesimal mass m in case of bi-elliptic restricted problem of four bodies (BiER4BP) (where three primaries M1, M2, M3 are rotating around their common centre of mass on elliptic orbits with hierarchical configuration M3 < M2 << M1). A new type of the solving proced

Piotr Lepucki, Raphael Havemann, Adam P. Dioguardi, Francesco Scaravaggi

We determine the phase diagram of LaFe$_{1-x}$Co$_x$AsO single crystals by using nuclear magnetic resonance (NMR). Up to a nominal doping of $x=0.03$, it follows the phase diagram for F-doped polycrystals. Above $x=0.03$, the F-doped samples become superconducting, whereas for Co-doping the structural and magnetic transitions can be observed up to $x=0.042$,

Sergio Messina

Determination of stellar age is a crucial task in astrophysics research. Different methods are nowadays used either model dependent or based on calibrated empirical relations. The most reliable results are generally obtained when different methods are used in complementary way. We propose a new method for the age determination of young stellar associations a

Giulio Peruginelli, Dario Spirito

Let $V$ be a valuation domain of rank one with quotient field $K$. We study the set of extensions of $V$ to the field of rational functions $K(X)$ induced by pseudo-convergent sequences of $K$ from a topological point of view, endowing this set either with the Zariski or with the constructible topology. In particular, we consider the two subspaces induced by

Nadeem Kafi, Zubair Ahmed Shaikh, Muhammad Shahid Shaikh

KG (Knowledge Generation) and understanding have traditionally been a Human-centric activity. KE (Knowledge Engineering) and KM (Knowledge Management) have tried to augment human knowledge on two separate planes: the first deals with machine interpretation of knowledge while the later explore interactions in human networks for KG and understanding. However,

Jan Rosenzweig

Standard, PCA-based factor analysis suffers from a number of well known problems due to the random nature of pairwise correlations of asset returns. We analyse an alternative based on ICA, where factors are identified based on their non-Gaussianity, instead of their variance. Generalizations of portfolio construction to the ICA framework leads to two semi-op

Miao Qin, Yongchuan Tang

This paper investigates the issues of combination and normalization of interval-valued belief structures within the framework of Dempster-Shafer theory of evidence. Existing approaches are reviewed and thoroughly analyzed. The advantages and drawbacks of previous approach are presented. A new optimality approach based on uncertainty measure is developed, whe

Cheng Yang, Shengnan Wang, Chao Yang, Yuechuan Li

Pre-trained language models, such as BERT, have achieved significant accuracy gain in many natural language processing tasks. Despite its effectiveness, the huge number of parameters makes training a BERT model computationally very challenging. In this paper, we propose an efficient multi-stage layerwise training (MSLT) approach to reduce the training time o

Apostolos Avranas, Marios Kountouris, Philippe Ciblat

The problem of resource constrained scheduling in a dynamic and heterogeneous wireless setting is considered here. In our setup, the available limited bandwidth resources are allocated in order to serve randomly arriving service demands, which in turn belong to different classes in terms of payload data requirement, delay tolerance, and importance/priority.

Cheng Yang, Shengnan Wang, Yuechuan Li, Chao Yang

In recent years, BERT has made significant breakthroughs on many natural language processing tasks and attracted great attentions. Despite its accuracy gains, the BERT model generally involves a huge number of parameters and needs to be trained on massive datasets, so training such a model is computationally very challenging and time-consuming. Hence, traini

C. Tardioli, D. Farnocchia, M. Vasile, S. R. Chesley

We present an approach to estimate an upper bound for the impact probability of a potentially hazardous asteroid when part of the force model depends on unknown parameters whose statistical distribution needs to be assumed. As case study we consider Apophis' risk assessment for the 2036 and 2068 keyholes based on information available as of 2013. Within the

Luise Rost, Jannik Lehr, Milan Maradiya, Lukas Hellweg

The influence of growth interruption on the luminescence properties of the Ga(As,Sb)/GaAs interface have been studied by continous wave and time resolved photoluminescence spectrosocopy in type II Ga(As,Sb)/GaAs/(Ga,In)As double quantum well structures. A specific highly selective etching technique in combination with atomic force microscopy (AFM) is used to

Koki Yagi, Susumu Nishimura

In their recent paper (GandALF 2018), Goubault, Ledent, and Rajsbaum provided a formal epistemic model for distributed computing. Their logical model, as an alternative to the well-studied topological model, provides an attractive framework for refuting the solvability of a given distributed task by means of logical obstruction: One just needs to devise a fo

Pengfei Wei, Xinghua Qu, Yew Soon Ong, Zejun Ma

Feature-based transfer is one of the most effective methodologies for transfer learning. Existing studies usually assume that the learned new feature representation is \emph{domain-invariant}, and thus train a transfer model $\mathcal{M}$ on the source domain. In this paper, we consider a more realistic scenario where the new feature representation is subopt

Zhenxun Yuan, Xiao Song, Lei Bai, Wengang Zhou

The strong demand of autonomous driving in the industry has lead to strong interest in 3D object detection and resulted in many excellent 3D object detection algorithms. However, the vast majority of algorithms only model single-frame data, ignoring the temporal information of the sequence of data. In this work, we propose a new transformer, called Temporal-

E. I. Kats

Recent discovery of the ferroelectric nematic phase N_F resurrects a question about stability of the uniform N_F state with respect to the formation of either standard for solid ferroelectrics domain structure, or often occurring in liquid crystals space modulation of the polarization vector P (and naturally coupled to P nematic director. In this work within

Johannes Muhle-Karbe, Xiaofei Shi, Chen Yang

We study a risk-sharing economy where an arbitrary number of heterogenous agents trades an arbitrary number of risky assets subject to quadratic transaction costs. For linear state dynamics, the forward-backward stochastic differential equations characterizing equilibrium asset prices and trading strategies in this context reduce to a system of matrix-valued

Fengnan Gao, Tengyao Wang

We introduce a new method for two-sample testing of high-dimensional linear regression coefficients without assuming that those coefficients are individually estimable. The procedure works by first projecting the matrices of covariates and response vectors along directions that are complementary in sign in a subset of the coordinates, a process which we call

J. I. Apiñaniz, S. Malko, R. Fedosejevs, W. Cayzac

We report on the development of a highly directional, narrow energy band, short time duration proton beam operating at high repetition rate, suitable for measurements of stopping power in high energy density plasmas as well as other applications. The protons are generated with an ultrashort-pulse laser interacting with a solid target and converted to a penci

Manan Agarwal, Khushboo K. Rao, Kaushar Vaidya, Souradeep Bhattacharya

The existing open cluster membership determination algorithms are either prior dependent on some known parameters of clusters or are not automatable to large samples of clusters. In this paper, we present, ML-MOC, a new machine learning based approach to identify likely members of open clusters using the Gaia DR2 data, and no a priori information about clust

D. A. Patient, S. A. R. Horsley

Electromagnetic waves at grazing incidence onto a planar medium are analogous to zero energy quantum particles incident onto a potential well. In this limit waves are typically completely reflected. Here we explore dielectric profiles supporting optical analogues of `half-bound states', allowing for zero reflection at grazing incidence. To obtain these profi

Dong Pan, Huading Song, Shan Zhang, Lei Liu

Hybrid semiconductor-superconductor InAs-Al nanowires with uniform and defect-free crystal interfaces are one of the most promising candidates used in the quest for Majorana zero modes (MZMs). However, InAs nanowires often exhibit a high density of randomly distributed twin defects and stacking faults, which result in an uncontrolled and non-uniform InAs-Al

Wei Chao, JIan-guo Jiang, Min Su

In this paper we consider loop corrections to the spin-independent WIMP-nucleon scattering cross section in bottom-quark flavored scalar-type dark matter models. We focus on two scenarios: (a) a complex scalar dark matter with a scalar particle as the mediator; and (b) a real scalar dark matter with a vector boson as the mediator. In both scenarios, the dire

Divya Kothandaraman, Rohan Chandra, Dinesh Manocha

We present a novel approach for unsupervised road segmentation in adverse weather conditions such as rain or fog. This includes a new algorithm for source-free domain adaptation (SFDA) using self-supervised learning. Moreover, our approach uses several techniques to address various challenges in SFDA and improve performance, including online generation of ps

Shreyas Pitale, Manoranjan Ghosh, S. G. Singh, Husain Manasawala

Schottky barrier contact has been fabricated by thermal deposition of Al on (100) Ge (impurity concentration~1010/cm3 at 80K) that shows extrinsic p-type to intrinsic n-type transition near 180K. Both p and n-type Ge exhibits ideal Schottky behaviour with low reverse current and near unity ideality factors obtained from the linear form of temperature depende

Dmitry I. Khomovsky

Let $a_0=b_0=0$ and $0<a_1\leq b_1<a_2\leq b_2<\ldots\leq b_{n}$ be integers. Let $Q\left(x;\bigcup_{j=1}^{n}[a_j,b_j]\right)$ be the number of integers between $1$ and $x$ such that all exponents in their prime factorization are in $\bigcup_{j=1}^{n}[a_j,b_j]$. The following formula holds: $$\lim_{x\to\infty}{\frac{Q\left(x;\bigcup_{j=1}^{n}[a_j,b_j]\right)

Jaroslav Vrba, Martin Urbanec, Zdeněk Stuchlík, John C. Miller

Extremely compact objects containing a region of trapped null geodesics could be of astrophysical relevance due to trapping of neutrinos with consequent impact on cooling processes or trapping of gravitational waves. These objects have previously been studied under the assumption of spherical symmetry. In the present paper, we consider a simple generalizatio

Siyu Liu, Jason A. Dowling, Craig Engstrom, Peter B. Greer

Medical image translation (e.g. CT to MR) is a challenging task as it requires I) faithful translation of domain-invariant features (e.g. shape information of anatomical structures) and II) realistic synthesis of target-domain features (e.g. tissue appearance in MR). In this work, we propose Manifold Disentanglement Generative Adversarial Network (MDGAN), a

Kehan Qi, Yu Gong, Xinfeng Liu, Xin Liu

Noises, artifacts, and loss of information caused by the magnetic resonance (MR) reconstruction may compromise the final performance of the downstream applications. In this paper, we develop a re-weighted multi-task deep learning method to learn prior knowledge from the existing big dataset and then utilize them to assist simultaneous MR reconstruction and s

Selma Conforti, Mariangela Settimo, Cayetano Santos, Clément Bordereau

An ASIC named CATIROC (Charge And Time Integrated Read Out Chip) has been developed for the next-generation neutrino experiments using a large number of photomultiplier tubes (PMTs). Each CATIROC provides the time and the charge measurements for 16 configurable input channels operating in trigger-less mode. Originally designed for the light emission in water

Jianjun Xu, Wenquan Cui

This article studies global testing of the slope function in functional linear regression model in the framework of reproducing kernel Hilbert space. We propose a new testing statistic based on smoothness regularization estimators. The asymptotic distribution of the testing statistic is established under null hypothesis. It is shown that the null asymptotic

Sebastiano Peotta, Fredrik Brange, Aydin Deger, Teemu Ojanen

Dynamical phase transitions extend the notion of criticality to non-stationary settings and are characterized by sudden changes in the macroscopic properties of time-evolving quantum systems. Investigations of dynamical phase transitions combine aspects of symmetry, topology, and non-equilibrium physics, however, progress has been hindered by the notorious d

Mu Cai, Hong Zhang, Huijuan Huang, Qichuan Geng

Image-to-image translation has been revolutionized with GAN-based methods. However, existing methods lack the ability to preserve the identity of the source domain. As a result, synthesized images can often over-adapt to the reference domain, losing important structural characteristics and suffering from suboptimal visual quality. To solve these challenges,

Harry Crimmins, Benoît Saussol

In this paper we study the quenched distributions of hitting times for a class of random dynamical systems. We prove that hitting times to dynamically defined cylinders converge to a Poisson point process under the law of random equivariant measures with super-polynomial decay of correlations. In particular, we apply our results to uniformly aperiodic random