May 2020 arXiv papers — page 10

B. K. Choi, S. Ulstrup, S. M. Gunasekera, J. Kim

Many properties of layered materials change as they are thinned from their bulk forms down to single layers, with examples including indirect-to-direct band gap transition in 2H semiconducting transition metal dichalcogenides as well as thickness-dependent changes in the valence band structure in post-transition metal monochalcogenides and black phosphorus.

Rémy Mariétan, Stephan Morgenthaler

This paper investigates a statistical procedure for testing the equality of two independently estimated covariance matrices when the number of potentially dependent data vectors is large and proportional to the size of the vectors, that is, the number of variables. Inspired by the spike models used in random matrix theory, we concentrate on the largest eigen

ALICE Collaboration

A measurement of dielectron production in proton-proton (pp) collisions at $\sqrt{s} = 13$ TeV, recorded with the ALICE detector at the CERN LHC, is presented in this Letter. The data set was recorded with a reduced magnetic solenoid field. This enables the investigation of a kinematic domain at low dielectron invariant mass $m_{\rm ee}$ and pair transverse

Hengjia Wei, Xin Wang, Moshe Schwartz

We construct integer error-correcting codes and covering codes for the limited-magnitude error channel with more than one error. The codes are lattices that pack or cover the space with the appropriate error ball. Some of the constructions attain an asymptotic packing/covering density that is constant. The results are obtained via various methods, including

ALICE Collaboration

The inclusive J/$\psi$ elliptic ($v_2$) and triangular ($v_3$) flow coefficients measured at forward rapidity (2.5 $<y<$ 4) and the $v_2$ measured at midrapidity ($|y|<$ 0.9) in Pb-Pb collisions at $\sqrt{s_{\rm NN}}$ = 5.02 TeV using the ALICE detector at the LHC are reported. The entire Pb-Pb data sample collected during Run 2 is employed, amounting to an

Affan Idrees, Zahid Iqbal, Maria Ishfaq

Blind navigation is an accessibility application that enables blind to use an android Smartphone in an easy way for indoor navigation with instructions in audio form. We have proposed a prototype which is an indoor navigation application for blinds that uses QR codes. It is developed for android Smart phones and does not require any additional hardware for n

Sophia Han, Madappa Prakash

Prospects of establishing the radii of massive neutron stars in PSR J1614-2230 and PSR J0740+6620 from NICER and Chandra observatories hold the potential to constrain the equation of state (EoS) of matter to densities well beyond those encountered in canonical stars of mass $\sim 1.4\,{\rm M}_{\odot}$. In this work, we investigate the relation between the ra

Mohamed Abdi, Meryem Ould-Rouiss, Abdelkader Noureddine

A large eddy simulation (LES) with an extended Smagorinsky model has been carried to investigate numerically the fully developed turbulent flow of a shear thinning fluid (n=0.75) in a stationary pipe at a simulation's Reynolds number equals to 4000 with a grid resolution of 65 3 gridpoints in axial, radial and circumferential directions and a domain length o

Roderich Tumulka

We prove the uncertainty relation $\sigma_T \, \sigma_E \geq \hbar/2$ between the time $T$ of detection of a quantum particle on the surface $\partial \Omega$ of a region $\Omega\subset \mathbb{R}^3$ containing the particle's initial wave function, using the "absorbing boundary rule" for detection time, and the energy $E$ of the initial wave function. Here,

Philipp del Hougne

Irregular propagation environments with complex scattering effects challenge traditional ray-tracing-based localization. However, the environment's complexity enables solutions based on wave fingerprints (WFPs). Yet, since WFPs rely on the extreme sensitivity of the chaotic wave field to geometrical details, it is not clear how viable WFP techniques may be i

Yan Peng

In the black hole spacetime, a no short hair theorem was proved, which states that the effective radius of black hole hairs must extend beyond the null circular orbit. In the present paper, in the horizonless gravity, we find a similar no short hair behavior that the effective radius of matter fields must also extend beyond the null circular orbit of ultra-c

Navid Alemi Koohbanani, Mostafa Jahanifar, Neda Zamani Tajadin, Nasir Rajpoot

Object segmentation is an important step in the workflow of computational pathology. Deep learning based models generally require large amount of labeled data for precise and reliable prediction. However, collecting labeled data is expensive because it often requires expert knowledge, particularly in medical imaging domain where labels are the result of a ti

Lars Fritsche, Jens Kosiol, Andy Schürr, Gabriele Taentzer

Model synchronization, i.e., the task of restoring consistency between two interrelated models after a model change, is a challenging task. Triple Graph Grammars (TGGs) specify model consistency by means of rules that describe how to create consistent pairs of models. These rules can be used to automatically derive further rules, which describe how to propag

Didier Clamond, David Henry

The aim of this note is to examine the efficacy of a recently developed approach to the recovery of nonlinear water waves from pressure measurements at the seabed, by applying it to the celebrated extreme Stokes wave.

Keli Guo, Chuyun Ye, Jun Fan, Lixing Zhu

The research described herewith is to re-visit the classical doubly robust estimation of average treatment effect by conducting a systematic study on the comparisons, in the sense of asymptotic efficiency, among all possible combinations of the estimated propensity score and outcome regression. To this end, we consider all nine combinations under, respective

A. Alastuey, V. Ballenegger, D. Wendland

We consider a quantum multi-component plasma made with S species of point charged particles interacting via the Coulomb potential. We derive the screened activity series for the pressure in the grand-canonical ensemble within the Feynman-Kac path integral representation of the system in terms of a classical gas of loops. This series is useful for computing e

Philip Blagoveschensky, Anh Huy Phan

Neural networks have achieved state of the art results in many areas, supposedly due to parameter sharing, locality, and depth. Tensor networks (TNs) are linear algebraic representations of quantum many-body states based on their entanglement structure. TNs have found use in machine learning. We devise a novel TN based model called Deep convolutional tensor

Duncan Deveaux, Takamasa Higuchi, Seyhan Uçar, Jérôme Härri

To operate intelligent vehicular applications such as automated driving, machine learning, artificial intelligence and other mechanisms are used to abstract from information what is commonly referred to as knowledge. Defined as a state of understanding obtained through experience and analysis of collected information, knowledge is promising for vehicular app

Gabriel de A. Gleizer, Manuel Mazo

We provide a method to construct finite abstractions exactly bisimilar to linear systems under a modified periodic event-triggered control (PETC), when considering as output the inter-event times they generate. Assuming that the initial state lies on a known compact set, these finite-state models can exactly predict all sequences of sampling times until a sp

Clemens Bombach, Dennis Gallaun, Christian Seifert, Martin Tautenhahn

We study (approximate) null-controllability of parabolic equations in $L_p(\mathbb{R}^d)$ and provide explicit bounds on the control cost. In particular we consider systems of the form $\dot{x}(t) = -A_p x(t) + \mathbf{1}_E u(t)$, $x(0) = x_0\in L_p (\mathbb{R}^d)$, with interior control on a so-called thick set $E \subset \mathbb{R}^d$, where $p\in [1,\inft

Uzair Nadeem, Mohammed Bennamoun, Roberto Togneri, Ferdous Sohel

This paper proposes a novel concept to directly match feature descriptors extracted from 2D images with feature descriptors extracted from 3D point clouds. We use this concept to directly localize images in a 3D point cloud. We generate a dataset of matching 2D and 3D points and their corresponding feature descriptors, which is used to learn a Descriptor-Mat

Kevin Fauvel, Véronique Masson, Élisa Fromont

Our research aims to propose a new performance-explainability analytical framework to assess and benchmark machine learning methods. The framework details a set of characteristics that systematize the performance-explainability assessment of existing machine learning methods. In order to illustrate the use of the framework, we apply it to benchmark the curre

Y. X. Zhao, Y. Lu, Shengyuan A. Yang

We present an exactly solvable spin-3/2 model defined on a pentacoordinated three-dimensional graphite lattice, which realizes a novel quantum spin liquid with second-order topology. The exact solutions are described by Majorana fermions coupled to a background $\mathbb{Z}_2$ gauge field, whose ground-state flux configuration gives rise to an emergent off-ce

Alexandra Bünger, Valeria Simoncini, Martin Stoll

PDE-constrained optimization problems arise in a broad number of applications such as hyperthermia cancer treatment or blood flow simulation. Discretization of the optimization problem and using a Lagrangian approach result in a large-scale saddle-point system, which is challenging to solve, and acquiring a full space-time solution is often infeasible. We pr

Tomas Andrade, Roberto Emparan, Aron Jansen, David Licht

We study how black hole entropy is generated and the role it plays in several highly dynamical processes: the decay of unstable black strings and ultraspinning black holes; the fusion of two rotating black holes; and the subsequent fission of the merged system into two black holes that fly apart (which can occur in dimension $D\geq 6$, with a mild violation

Wei-Hsiang Wang, Po-Chun Chang, Pei-hsun Jiang, Wen-Chin Lin

We demonstrate control of magnetic domain structures in continuous FePd thin films by patterning their surfaces with plasma treatment. The Fe-oxide layer formed on the surface upon ambient exposure of the FePd alloy thin film grown on an Al$_2$O$_3$(0001) substrate was patterned into microstructures by e-beam lithography followed by O$_2$- or Ar-plasma treat

Sayantan Mondal, Saumyak Mukherjee, Biman Bagchi

We study the influence of the rate of the attainment of herd immunity (HI), in the absence of an approved vaccine, on the vulnerable population. We essentially ask the question: how hard the evolution towards the desired herd immunity could be on the life of the vulnerables? We employ mathematical modelling (chemical network theory) and cellular automata bas

Jack Richings, Carlos Frenk, Adrian Jenkins, Andrew Robertson

We present a cosmological hydrodynamical simulation of a 10^13 Msun galaxy group and its environment (out to 10 times the virial radius) carried out using the EAGLE model of galaxy formation. Exploiting a novel technique to increase the resolution of the dark matter calculation independently of that of the gas, the simulation resolves dark matter haloes and

Yong Lu, Jingwen Wu

Let $G^{\sigma}=(G,\sigma)$ be a signed graph and $A(G,\sigma)$ be its adjacency matrix. Denote by $m(G)$ the matching number of $G$. Let $\eta(G,\sigma)$ be the nullity of $(G,\sigma)$. He et al. [Bounds for the matching number and cyclomatic number of a signed graph in terms of rank, Linear Algebra Appl. 572 (2019), 273--291] proved that $$|V(G)|-2m(G)-c(G

Takeo Kato, Yuichi Ohnuma, Mamoru Matsuo

We consider a microscopic theory for the spin Hall magnetoresistance (SMR). We generally formulate a spin conductance at an interface between a normal metal and a magnetic insulator in terms of spin susceptibilities. We reveal that SMR is composed of static and dynamic parts. The static part, which is almost independent of the temperature, originates from sp

Yanhao Wang, Yuchen Li, Raymond Chi-Wing Wong, Kian-Lee Tan

Selecting a small set of representatives from a large database is important in many applications such as multi-criteria decision making, web search, and recommendation. The $k$-regret minimizing set ($k$-RMS) problem was recently proposed for representative tuple discovery. Specifically, for a large database $P$ of tuples with multiple numerical attributes,

Mark V Lawson

This report assumes the basics of inverse semigroup theory as described in the first primer but goes on to show how they may be analysed using ideas from category theory.

Mark V Lawson

This is an overview of the basics of inverse semigroup theory written for the Workshop on Semigroups and Categories held at the University of Ottawa in 2010.

Vivek Sadhu

In this article, we study the Heller relative $K_{0}$ group of the map $\mathbb{P}_{X}^{r} \to \mathbb{P}_{S}^{r},$ where $X$ and $S$ are quasi-projective schemes over a commutative ring. More precisely, we prove that the projective bundle formula holds for Heller's relative $K_{0},$ provided $X$ is flat over $S.$ As a corollary, we get a description of the

Md. Shariful Islam, Md. Robiul Islam, Md. Shorif Hossan, Md. Hasan Kibria

The aim of this paper is to find a general formula to generate any row of Pascal's triangle as an extension of the concept of $\left(11\right)^{n}$. In this study, the visualization of each row of Pascal's triangle has been presented by extending the concept of the power of 11 to the power of 101, 1001, 10001, and so on. We briefly discuss how our proposed c

Patrick Wilken, Tamer Alkhouli, Evgeny Matusov, Pavel Golik

In simultaneous machine translation, the objective is to determine when to produce a partial translation given a continuous stream of source words, with a trade-off between latency and quality. We propose a neural machine translation (NMT) model that makes dynamic decisions when to continue feeding on input or generate output words. The model is composed of

Yu-Chin Lu, Chia-Wei Tsai, Tzonelih Hwang

We calculate the key sharing rate of Lu et al.'s Quantum Key Recycling (QKR) protocol. The key sharing rate is another version of the key rate, but it can be calculated for both the Quantum Key Distribution (QKD) protocols and the QKR protocols. We define the key sharing rate in this study and compare the key sharing rate of the QKR protocol to the rate of t

Karel Dekimpe, Pieter Senden

Given a group $G$ and an automorphism $\varphi$ of $G$, two elements $x, y \in G$ are said to be $\varphi$-conjugate if $x = g y \varphi(g)^{-1}$ for some $g \in G$. The number of equivalence classes is the Reidemeister number $R(\varphi)$ of $\varphi$, and if $R(\varphi) = \infty$ for all automorphisms of $G$, then $G$ is said to have the $R_\infty$-propert

A. Harikumar, F. Donatini, C. Bougerol, E. Bellet-Amalric

In this paper, we describe the growth and characterization of 530-nm-thick superlattices (100 periods) of AlxGa1-xN/AlN (x = 0, 0.1) Stranski-Krastanov quantum dots for application as the active region of electron-beam pumped ultraviolet lamps. Highly dense (>10e11 cm-2) quantum dot layers are deposited by molecular beam epitaxy, and we explore the effect of

Evangelos Bartzos, Ioannis Z. Emiris, Josef Schicho

Rigid graph theory is an active area with many open problems, especially regarding embeddings in $\mathbb{R}^d$ or other manifolds, and tight upper bounds on their number for a given number of vertices. Our premise is to relate the number of embeddings to that of solutions of a well-constrained algebraic system and exploit progress in the latter domain. In p

Eleonora Andreotti, Raffaella Mulas

The spectral theory of the normalized Laplacian for chemical hypergraphs is further investigated. The signless normalized Laplacian is introduced and it is shown that its spectrum for classical hypergraphs coincides with the spectrum of the normalized Laplacian for bipartite chemical hypergraphs. Furthermore, the spectra of special families of hypergraphs ar

L. Frogner, B. V. Gudiksen, H. Bakke

Observational and theoretical evidence suggest that beams of accelerated particles are produced in flaring events of all sizes in the solar atmosphere, from X-class flares to nanoflares. Current models of these types of particles in flaring loops assume an isolated 1D atmosphere. A more realistic environment for modelling accelerated particles can be provide

Philip Adsley, Umberto Battino, Andreas Best, Antonio Caciolli

The competing $^{22}$Ne($\alpha,\gamma$)$^{26}$Mg and $^{22}$Ne($\alpha,n$)$^{25}$Mg reactions control the production of neutrons for the weak $s$-process in massive and AGB stars. In both systems, the ratio between the corresponding reaction rates strongly impacts the total neutron budget and strongly influences the final nucleosynthesis. The $^{22}$Ne($\al

Hiroaki W. H. Tahara, Tsutomu Kobayashi, Jun'ichi Yokoyama

We construct a model of higher dimensional cosmology in which extra dimensions are frozen by virtue of the cubic-order Lovelock gravity throughout the cosmic history from inflation to the present with radiation and matter-dominated regimes in between.

Wenwu Ye, Jin Yao, Hui Xue, Yi Li

Localizing thoracic diseases on chest X-ray plays a critical role in clinical practices such as diagnosis and treatment planning. However, current deep learning based approaches often require strong supervision, e.g. annotated bounding boxes, for training such systems, which is infeasible to harvest in large-scale. We present Probabilistic Class Activation M

Arjen van den Berg, Mylene Caruel, Matthew Hunt, Sam Ladak

Three-dimensional nanostructured functional materials are important systems, allowing new means to intricately control electromagnetic properties. A key problem is realising a 3D printing methodology upon the nanoscale that can yield a range of functional materials. In this letter, it is shown that two-photon lithography when combined with femtosecond machin

Richard M. Rowan-Robinson, Jérome Hurst, Agne Ciuciulkaite, Ioan-Augustin Chioar

Nanometer-thin rare-earth-transition metal (RE-TM) alloys with precisely controlled compositions and out-of-plane magnetic anisotropy are currently in the focus for ultrafast magnetophotonic applications. However, achieving lateral nanoscale dimensions, crucial for potential device downscaling, while maintaining designable optomagnetic functionality and out-

Jike Lyu, Tingfeng Song, Ignasi Fina, Florencio Sánchez

Ferroelectric HfO$_2$ is a promising material for new memory devices, but significant improvement of important properties is necessary to reach applications. However, precedent literature shows that a dilemma between polarization, endurance and retention exists. Since all these properties should be simultaneously high, overcoming this issue is of the highest

Shuang Yu, Jianhui Qiu, Changjun Gao

Exact black hole solutions in the Einstein-Maxwell-scalar theory are constructed. They are the extensions of dilaton black holes in de Sitter or anti de Sitter universe. As a result, except for a scalar potential, a coupling function between the scalar field and the Maxwell invariant is present. Then the corresponding Smarr formula and the first law of therm

Yordan S. Yordanov, David R. M. Arvidsson-Shukur, Crispin H. W. Barnes

Molecular quantum simulations with the variational quantum eigensolver (VQE) rely on ansatz states that approximate the molecular ground states. These ansatz states are generally defined by parametrized fermionic excitation operators and an initial reference state. Efficient ways to perform fermionic excitations are vital for the realization of the VQE on no

Hans Christian Öttinger

The natural constraints for the weak-field approximation to composite gravity, which is obtained by expressing the gauge vector fields of the Yang-Mills theory based on the Lorentz group in terms of tetrad variables and their derivatives, are analyzed in detail within a canonical Hamiltonian approach. Although this higher derivative theory involves a large n

Maiia Marienko, Yulia Nosenko, Alisa Sukhikh, Viktor Tataurov

The article highlights the issues of personalized learning as the global trend of the modern ICTbased educational systems development. The notion, the main stages of evolution, the main features and principles of adaptive learning systems application for teachers training are outlined. It is emphasized that the use and elaboration of the adaptive cloud-based

Roman Flury, Reinhard Furrer

Multiresolution decomposition is commonly understood as a procedure to capture scale-dependent features in random signals. Such methods were first established for image processing and typically rely on raster or regularly gridded data. In this article, we extend a particular multiresolution decomposition procedure to areal count data, i.e.~discrete irregular

Sanjukta Krishnagopal

Many diseases display heterogeneity in clinical features and their progression, indicative of the existence of disease subtypes. Extracting patterns of disease variable progression for subtypes has tremendous application in medicine, for example, in early prognosis and personalized medical therapy. This work present a novel, data-driven, network-based Trajec

H1 collaboration

Exclusive photoproduction of $\rho^0(770)$ mesons is studied using the H1 detector at the $ep$ collider HERA. A sample of about 900000 events is used to measure single- and double-differential cross sections for the reaction $\gamma p \to \pi^{+}\pi^{-}Y$. Reactions where the proton stays intact (${m_Y{=}m_p}$) are statistically separated from those where th

Maria Lucia Sambataro, Salvatore Plumari, Vincenzo Greco

We evaluate drag and diffusion transport coefficients comparing a quasi-particle approximation with on-shell constituents of the QGP medium and a dynamical quasi-particles model with off-shell bulk medium at finite temperature T. We study the effects of the width $\gamma$ of the particles of the bulk medium on the charm quark transport properties exploring t

Shaohuai Shi, Qiang Wang, Xiaowen Chu

Multiplication of a sparse matrix to a dense matrix (SpDM) is widely used in many areas like scientific computing and machine learning. However, existing works under-look the performance optimization of SpDM on modern many-core architectures like GPUs. The storage data structures help sparse matrices store in a memory-saving format, but they bring difficulti

Pengwen Chen, Chung-Kuan Cheng, Xinyuan Wang

We study a stability preserved Arnoldi algorithm for matrix exponential in the time domain simulation of large-scale power delivery networks (PDN), which are formulated as semi-explicit differential algebraic equations (DAEs). The solution can be decomposed to a sum of two projections, one in the range of the system operator and the other in its null space.

Žiga Bizjak, Boštjan Likar, Franjo Pernuš, Žiga Špiclin

Intracranial aneurysms (IAs) are generally asymptomatic and thus often discovered incidentally on angiographic scans like 3D DSA, CTA and MRA. Skilled radiologists achieved a sensitivity of 88% by means of visual detection, which seems inadequate considering that prevalence of IAs in general population is 3-5%. Deep learning models trained and executed on an

Long Li, Su-Dan Wang

In this paper, we confirm the following conjecture of Guo and Schlosser: for any odd integer $n>1$ and $M=(n+1)/2$ or $n-1$, $$ \sum_{k=0}^{M}[4k-1]_{q^2}[4k-1]^2\frac{(q^{-2};q^4)_k^4}{(q^4;q^4)_k^4}q^{4k}\equiv (2q+2q^{-1}-1)[n]_{q^2}^4\pmod{[n]_{q^2}^4\Phi_n(q^2)}, $$ where $[n]=[n]_q=(1-q^n)/(1-q),(a;q)_0=1,(a;q)_k=(1-a)(1-aq)\cdots(1-aq^{k-1})$ for $k\g

Ziyue Wang, Shuzhe Shi, Pengfei Zhuang

We investigate the influence of chiral symmetry which varies along the space-time evolution of the system by considering the chiral phase transition in an non-equilibrium expanding quark-antiquark system. The chiral symmetry is described by the mean field order parameter, whose values is the solution of a self-consistent equation, and affects the space-time

Xiaoya Li, Mingxin Zhou, Jiawei Wu, Arianna Yuan

At the time of writing, the ongoing pandemic of coronavirus disease (COVID-19) has caused severe impacts on society, economy and people's daily lives. People constantly express their opinions on various aspects of the pandemic on social media, making user-generated content an important source for understanding public emotions and concerns. In this paper, we

Julian Arnold, Debasish Koner, Silvan Käser, Narendra Singh

Machine learning-based models to predict product state distributions from a distribution of reactant conditions for atom-diatom collisions are presented and quantitatively tested. The models are based on function-, kernel- and grid-based representations of the reactant and product state distributions. While all three methods predict final state distributions

Azam Asanjarani, Benoit Liquet, Yoni Nazarathy

Semi-Markov models are widely used for survival analysis and reliability analysis. In general, there are two competing parameterizations and each entails its own interpretation and inference properties. On the one hand, a semi-Markov process can be defined based on the distribution of sojourn times, often via hazard rates, together with transition probabilit

Qiufu Li, Linlin Shen

In deep networks, the lost data details significantly degrade the performances of image segmentation. In this paper, we propose to apply Discrete Wavelet Transform (DWT) to extract the data details during feature map down-sampling, and adopt Inverse DWT (IDWT) with the extracted details during the up-sampling to recover the details. We firstly transform DWT/

Fred E. Benth, Fabian A. Harang

We investigate the probabilistic and analytic properties of Volterra processes constructed as pathwise integrals of deterministic kernels with respect to the H\"older continuous trajectories of Hilbert-valued Gaussian processes. To this end, we extend the Volterra sewing lemma from \cite{HarangTindel} to the two dimensional case, in order to construct two di

Changxing Miao, Ruipeng Shen, Tengfei Zhao

We consider the scattering theory for the defocusing energy subcritical wave equations with an inverse square potential. By employing the energy flux method we establish energy flux estimates on the light cone. Then by the characteristic line method and radiation theorem, we show that the radial finite-energy solutions scatter to free waves outside of light

Domagoj Ćevid, Loris Michel, Jeffrey Näf, Nicolai Meinshausen

Random Forest (Breiman, 2001) is a successful and widely used regression and classification algorithm. Part of its appeal and reason for its versatility is its (implicit) construction of a kernel-type weighting function on training data, which can also be used for targets other than the original mean estimation. We propose a novel forest construction for mul

Mahdi Barzegar Khalilsarai, Saeid Haghighatshoar, Giuseppe Caire

We study the problem of maximum-likelihood (ML) estimation of an approximate common eigenstructure, i.e. an approximate common eigenvectors set (CES), for an ensemble of covariance matrices given a collection of their associated i.i.d vector realizations. This problem has a direct application in multi-user MIMO communications, where the base station (BS) has

Yunhe Wang, Yixing Xu, Dacheng Tao

Most applications demand high-performance deep neural architectures costing limited resources. Neural architecture searching is a way of automatically exploring optimal deep neural networks in a given huge search space. However, all sub-networks are usually evaluated using the same criterion; that is, early stopping on a small proportion of the training data

Yuichiro Tanaka, Yutaro Ishida, Yushi Abe, Tomohiro Ono

Our team, Hibikino-Musashi@Home (HMA), was founded in 2010. It is based in the Kitakyushu Science and Research Park, Japan. Since 2010, we have participated in the RoboCup@Home Japan Open competition open platform league annually. We have also participated in the RoboCup 2017 Nagoya as an open platform league and domestic standard platform league teams, and

Yajing Wang, Xiangke Wang, Shulong Zhao, Lincheng Shen

This paper studies the collision avoidance problem for autonomous multiple fixedwing UAVs in the complex integrated airspace. By studying and combining the online path planning method, the distributed model predictive control algorithm, and the geometric reactive control approach, a three-layered collision avoidance system integrating conflict detection and

J. R. C. C. C. Correia, C. J. A. P. Martins

Topological defects form at cosmological phase transitions by the Kibble mechanism. Cosmic strings and superstrings can lead to particularly interesting astrophysical and cosmological consequences, but this study is is currently limited by the availability of accurate numerical simulations, which in turn is bottlenecked by hardware resources and computation

Tom Wettlin, Talha Rahman, Jinlong Wei, Stefano Calabrò

We investigate approaches to reduce the computational complexity of Volterra nonlinear equalizers (VNLEs) for short-reach optical transmission systems using intensity modulation and direct detection (IM/DD). In this contribution we focus on a structural reduction of the number of kernels, i.e. we define rules to decide which terms need to be implemented and

Oihana Garaialde Ocaña, Lander Guerrero Sánchez, Jon González-Sánchez

Let p>3 be a prime number and let r be an integer with 1<r<p-1. For each r, let moreover G_r denote the unique quotient of the maximal class pro-p group of size p^{r+1}. We show that the mod-p cohomology ring of G_r has depth one and that, in turn, it satisfies the equalities in Carlson's depth conjecture [3].

Tomohiro Ono, Yuichiro Tanaka, Yutaro Ishida, Yushi Abe

Our team, Hibikino-Musashi@Home (HMA), was founded in 2010. It is based in Japan in the Kitakyushu Science and Research Park. Since 2010, we have annually participated in the RoboCup@Home Japan Open competition in the open platform league (OPL). We participated as an open platform league team in the 2017 Nagoya RoboCup competition and as a domestic standard

Á. Kereszturi, J. Aszalós, Zs. Heiling, Zs. Kapui

The Special Collection of papers in this issue of Astrobiology provide an overview of the characteristics and potential for future exploration of the Ojos del Salado volcano, located in the Andes Mountains in front of the Atacama Desert in northern Chile. The main benefits of this site compared with others are the combination of strong UV radiation, the pres

Žiga Bizjak, Boštjan Likar, Franjo Pernuš, Žiga Špiclin

Predicting rupture risk and deciding on optimal treatment plan for intracranial aneurysms (IAs) is possible by quantification of their size and shape. For this purpose the IA has to be isolated from 3D angiogram. State-of-the-art methods perform IA isolation by encoding neurosurgeon's intuition about former non-dilated vessel anatomy through principled appro

Michal Švanda, Didier Mourenas, Karla Žertová, Tatiana Výbošťoková

Eruptive events of solar activity often trigger abrupt variations of the geomagnetic field. Through the induction of electric currents, human infrastructures are also affected, namely the equipment of electric power transmission networks. It was shown in past studies that the rate of power-grid anomalies may increase after an exposure to strong geomagnetical

Kengo Takase, Le Duc Anh, Kosuke Takiguchi, Masaaki Tanaka

We demonstrate spin-valve magnetoresistance with a current-in-plane (CIP) configuration in (Ga,Fe)Sb / InAs (thickness $t_\mathrm{InAs}$ nm) / (Ga,Fe)Sb trilayer heterostructures, where (Ga,Fe)Sb is a ferromagnetic semiconductor (FMS) with high Curie temperature ($T_\mathrm{C}$). An MR curve with an open minor loop is clearly observed at 3.7 K in a sample wi

Zhaohui Yang, Yunhe Wang, Xinghao Chen, Jianyuan Guo

Neural Architecture Search (NAS) refers to automatically design the architecture. We propose an hourglass-inspired approach (HourNAS) for this problem that is motivated by the fact that the effects of the architecture often proceed from the vital few blocks. Acting like the narrow neck of an hourglass, vital blocks in the guaranteed path from the input to th

Alexander Thomas

In the physics literature, Bilal--Fock--Kogan \cite{BFK} introduced the idea of parabolic reduced flat connections on a surface to give a geometric origin to $W$-algebras. In this paper, we combine these ideas with higher complex structures, geometric structures defined by Fock and the author in \cite{FockThomas}. A semiclassical analysis of the parabolic re

Olivier Carton

We consider finite state non-deterministic but unambiguous transducers with infinite inputs and infinite outputs, and we consider the property of Borel normality of sequences of symbols. When these transducers are strongly connected, and when the input is a Borel normal sequence, the output is a sequence in which every block has a frequency given by a weight

Zelin Zhu, Shilie Zheng, Xiaowen Xiong, Yuqi Chen

Orbital angular momentum (OAM) has gradually become a research hotspot in radar, communication and other fields because of its phase distribution. However it encounters some problems in the real practice owing to its inherent characteristics. Recently OAM mode group has been proposed to solve these problems. In this paper, a non-uniform OAM source is used to

Stefan Huemmerich, Ernst Paunzen, Klaus Bernhard

Magnetic chemically peculiar (mCP) stars are important to astrophysics because their complex atmospheres lend themselves perfectly to the investigation of the interplay between such diverse phenomena as atomic diffusion, magnetic fields, and stellar rotation. The present work is aimed at identifying new mCP stars using spectra collected by the Large Sky Area

Young-Min Kim, Kyujin Kwak, Chang Ho Hyun, Hana Gil

Neutron star is the ultimate testing place for the physics of dense nuclear matter. Before the detection of gravitational waves from the merger of binary neutron stars, various nuclear equations of state have been used to estimate the macroscopic properties of neutron stars, such as masses and radii, based on the electromagnetic observations. However, recent

Lijun Pan, Yongjin Wang

We extend the model of Parenti (2018) on large and small firms by introducing cost heterogeneity among small firms. We propose a novel necessary and sufficient condition for the existence of such a mixed market structure. Furthermore, in contrast to Parenti (2018), we show that in the presence of cost heterogeneity among small firms, trade liberalization may

Xiang Hao, Xiangdong Su, Zhiyu Wang, Qiang Zhang

It is very challenging for speech enhancement methods to achieves robust performance under both high signal-to-noise ratio (SNR) and low SNR simultaneously. In this paper, we propose a method that integrates an SNR-based teachers-student technique and time-domain U-Net to deal with this problem. Specifically, this method consists of multiple teacher models a

R. Phillips, H. Wilder

Over the past few years, there has been a growth in activity, public knowledge, and awareness of cryptocurrencies and related blockchain technology. As the industry has grown, there has also been an increase in scams looking to steal unsuspecting individuals cryptocurrency. Many of the scams operate on visually similar but seemingly unconnected websites, adv

Huanyu Wang, Zequn Qin, Songyuan Li, Xi Li

Dynamic routing networks, aimed at finding the best routing paths in the networks, have achieved significant improvements to neural networks in terms of accuracy and efficiency. In this paper, we see dynamic routing networks in a fresh light, formulating a routing method as a mapping from a sample space to a routing space. From the perspective of space mappi

A. A. Bychek, D. N. Maksimov, A. R. Kolovsky

We study the decay of bosonic many-body states in the three well Bose-Hubbard chain where bosons in the central well can escape into a reservoir. For vanishing inter-particle interaction this system supports a non-decaying many-body state which is the antisymmetric Bose-Einstein condensate with particles occupying only the edge wells. In the classical approa

Ansgar Jüngel, Ulisse Stefanelli, Lara Trussardi

We present a new time discretization scheme adapted to the structure of GENERIC systems. The scheme is variational in nature and is based on a conditional incremental minimization. The GENERIC structure of the scheme provides stability and convergence of the scheme. We prove that the scheme can be rigorously implemented in the case of the damped harmonic osc

Lorenzo Giambagli, Lorenzo Buffoni, Timoteo Carletti, Walter Nocentini

Deep neural networks are usually trained in the space of the nodes, by adjusting the weights of existing links via suitable optimization protocols. We here propose a radically new approach which anchors the learning process to reciprocal space. Specifically, the training acts on the spectral domain and seeks to modify the eigenvalues and eigenvectors of tran

Xiang Hao, Shixue Wen, Xiangdong Su, Yun Liu

In single-channel speech enhancement, methods based on full-band spectral features have been widely studied. However, only a few methods pay attention to non-full-band spectral features. In this paper, we explore a knowledge distillation framework based on sub-band spectral mapping for single-channel speech enhancement. Specifically, we divide the full frequ

Jianxi Yang, Likai Zhang, Cen Chen, Yangfan Li

Structural damage detection has become an interdisciplinary area of interest for various engineering fields, while the available damage detection methods are being in the process of adapting machine learning concepts. Most machine learning based methods heavily depend on extracted ``hand-crafted" features that are manually selected in advance by domain exper

Amir Saberi, Farhad Farokhi, Girish N. Nair

It is known that for a discrete channel with correlated additive noise, the ordinary capacity with or without feedback both equal $ \log q-\mathcal{H} (Z) $, where $ \mathcal{H}(Z) $ is the entropy rate of the noise process $ Z $ and $ q $ is the alphabet size. In this paper, a class of finite-state additive noise channels is introduced. It is shown that the

Siyu Huang, Wensha Gou, Hongbo Cai, Xiaomeng Li

In contrast to the rapid integration of the world economy, many regional trade agreements (RTAs) have also emerged since the early 1990s. This seeming contradiction has encouraged scholars and policy makers to explore the true effects of RTAs, including both regional and global trade relationships. This paper defines synthesized trade resistance and decompos

Zelin Zhu, Shilie Zheng, Xiaowen Xiong, Yuqi Chen

Orbital angular momentum (OAM) has attracted great interest in the past few decades due to its helical phase characteristics. It has been proved that Plane spiral OAM (PSOAM) has potential in pattern reconfiguration of azimuthal domain because it solves the difficulty of mode superposition caused by different main lobe directions of different modes. However,

Efstathios Konstantinidis, Dániel Dorogi, László Baranyi

We present simulations of a circular cylinder undergoing vortex-induced vibration in-line with a free stream in conjunction with a theory for the fluid dynamics. Initially, it is shown that increasing the Reynolds number from 100 to 250 results in a 12-fold increase of the peak response amplitude at a fixed mass ratio of $m^*=5$. Subsequently, $m^*$ is varie

Dariusz Kominiak, Sina Sharif Mansouri, Christoforos Kanellakis, George Nikolakopoulos

The Mining industry considers the deployment of MAV for autonomous inspection of tunnels and shafts to increase safety and productivity. However, mines are challenging and harsh environments that have a direct effect on the degradation of high-end and expensive utilized components over time. Inspired by this effect, this article presents a low cost and modul