April 2020 arXiv papers — page 12

Gábor Hofer-Szabó

If noncontextuality is defined as the robustness of a system's response to a measurement against other simultaneous measurements, then the Kochen-Specker arguments do not provide an algebraic proof for quantum contextuality. Namely, for the argument to be effective, (i) each operator must be uniquely associated with a measurement and (ii) commuting operators

Zuzana Kukelova, Cenek Albl, Akihiro Sugimoto, Konrad Schindler

The internal geometry of most modern consumer cameras is not adequately described by the perspective projection. Almost all cameras exhibit some radial lens distortion and are equipped with an electronic rolling shutter that induces distortions when the camera moves during the image capture. When focal length has not been calibrated offline, the parameters t

Daniela Polino, Emanuele Grifoni, Roger Rousseau, Michele Parrinello

CO2 has attracted considerable attention in the recent years due to its role in the greenhouse effect and environmental management. While its reaction with water has been studied extensively, the same cannot be said for reactivity in supercritical CO2 phase, where the conjugate acid/base equilibria proceed through different mechanisms and activation barriers

Zhaoyang Qu, Qianhui Xie, Yuqing Liu, Yang Li

Existing power cyber-physical system (CPS) risk prediction results are inaccurate as they fail to reflect the actual physical characteristics of the components and the specific operational status. A new method based on dependent Markov chain for power CPS risk area prediction is proposed in this paper. The load and constraints of the non-uniform power CPS co

Tomomi Shimoikura, Kazuhito Dobashi, Yoshiko Hatano, Fumitaka Nakamura

We present maps in several molecular emission lines of a 1 square-degree region covering the W40 and Serpens South molecular clouds belonging to the Aquila Rift complex. The observations were made with the 45 m telescope at the Nobeyama Radio Observatory. We found that the $^{12}$CO and $^{13}$CO emission lines consist of several velocity components with dif

Edita Máčajová, Giuseppe Mazzuoccolo, Vahan Mkrtchyan, Jean Paul Zerafa

Many conjectures and open problems in graph theory can either be reduced to cubic graphs or are directly stated for cubic graphs. Furthermore, it is known that for a lot of problems, a counterexample must be a snark, i.e. a bridgeless cubic graph which is not 3--edge-colourable. In this paper we deal with the fact that the family of potential counterexamples

Chung-Han Hsieh

In this paper, we consider a simple discrete-time optimal betting problem using the celebrated Kelly criterion, which calls for maximization of the expected logarithmic growth of wealth. While the classical Kelly betting problem can be solved via standard concave programming technique, an alternative but attractive approach is to invoke a Taylor-based approx

Man Hu, Feng Wang, Qian Tao, Li Chen

We report frozen patterns for the water droplets impacting on a cold substrate through fast-speed images. These patterns can be manipulated by several physical parameters (the droplet size, falling height, and substrate temperature), and the scaling analysis has a remarkable agreement with the phase diagram. The observed double-concentric toroidal shape is a

Wojciech Masarczyk, Ivona Tautkute

Catastrophic forgetting is a problem caused by neural networks' inability to learn data in sequence. After learning two tasks in sequence, performance on the first one drops significantly. This is a serious disadvantage that prevents many deep learning applications to real-life problems where not all object classes are known beforehand; or change in data req

Nikolay M. Yanev, Vessela K. Stoimenova, Dimitar V. Atanasov

The aim of the paper is to describe two models of Covid-19 infection dynamics. For this purpose a special class of branching processes with two types of individuals is considered. These models are intended to use only the observed daily statistics to estimate the main parameter of the infection and to give a prediction of the mean value of the non-observed p

Ana María Botero, José Ignacio Burgos Gil

We generalize the intersection theory of nef toric (Weil) b-divisors on smooth and complete toric varieties to the case of smooth and complete toroidal embeddings. As a key ingredient we show the existence of a limit measure, supported on the weakly embedded rational conical polyhedral space attached to the toroidal embedding, which arises as a limit of disc

Norman Haag, Daniel Lüftner, Johannes Seidel, Leah L. Kelly

Transport phenomena in molecular materials are intrinsically linked to the orbital character and the degree of localization of the valence states. Here, we combine angle-resolved photoemission with photoemission tomography to determine the spatial distribution of all molecular states of the valence band structure of a C$_{60}$ thin film. While the two most f

Yunpei Jia, Jie Zhang, Shiguang Shan, Xilin Chen

Existing domain generalization methods for face anti-spoofing endeavor to extract common differentiation features to improve the generalization. However, due to large distribution discrepancies among fake faces of different domains, it is difficult to seek a compact and generalized feature space for the fake faces. In this work, we propose an end-to-end sing

Li Zhou, Yan-Chun Liang, Jun-Qiang Ge, Yi-Nan Zhu

By using Data Analysis Pipeline (DAP) products of Mapping Nearby Galaxies at Apache Point Observatory (MaNGA), which are publicly available from the SDSS Data Release 15, we analyze the local properties at the SN explosion sites and global properties of different types of SN host galaxies to explore the explosion environments of different types of SNe. In ou

Kristina Kislyakova, Lena Noack

Aims. We investigate possible driving mechanisms of volcanic activity on rocky super-Earths with masses exceeding 3-4 Mearth. Due to high gravity and pressures in the mantles of these planets, melting in deep mantle layers can be suppressed, even if the energy releae due to tidal heating and radioactive decay is substantial. Here we investigate whether a new

Georgios Paraskevopoulos, Srinivas Parthasarathy, Aparna Khare, Shiva Sundaram

This paper presents an audio visual automatic speech recognition (AV-ASR) system using a Transformer-based architecture. We particularly focus on the scene context provided by the visual information, to ground the ASR. We extract representations for audio features in the encoder layers of the transformer and fuse video features using an additional crossmodal

M. A. Guerrero, G. Ramos-Larios, J. A. Toala, B. Balick

We present a detailed comparative study of the arcs and fragmented ring-like features in the haloes of the planetary nebulae (PNe) NGC 6543, NGC 7009, and NGC 7027 and the spiral pattern around the carbon star AFGL 3068 using high-quality multi-epoch HST images. This comparison allows us to investigate the connection and possible evolution between the regula

Kento Ueda, Sadashige Matsuo, Hiroshi Kamata, Yosuke Sato

We report on half-integer Shapiro steps observed in an InAs nanowire Josephson junction. We observed the Shapiro steps of the short ballistic InAs nanowire Josephson junction and found anomalous half-integer steps in addition to the conventional integer steps. The half-integer steps disappear as the temperature increases or transmission of the junction decre

S. Reschke, A. A. Tsirlin, N. Khan, L. Prodan

We report on the structural and spectroscopic characterization of the multiferroic Fe$_2$Mo$_3$O$_8$. Synchrotron x-ray and neutron diffraction, as well as thermal expansion measurements reveal a lattice anomaly at $T_{\mathrm{N}}\simeq 60\,$K but do not show any symmetry lowering in the magnetically ordered state. The lattice parameter $c$ exhibits a non-mo

Changhao Chen

S. Baker (2019), B. B\'ar\'any and A. K\"{a}enm\"{a}ki (2019) independently showed that there exist iterated function systems without exact overlaps and there are super-exponentially close cylinders at all small levels. We adapt the method of S. Baker and obtain further examples of this type. We prove that for any algebraic number $\beta\ge 2$ there exist re

Thomas Gabor, Sebastian Feld, Hila Safi, Thomy Phan

Current hardware limitations restrict the potential when solving quadratic unconstrained binary optimization (QUBO) problems via the quantum approximate optimization algorithm (QAOA) or quantum annealing (QA). Thus, we consider training neural networks in this context. We first discuss QUBO problems that originate from translated instances of the traveling s

Thomas Gabor, Leo Sünkel, Fabian Ritz, Thomy Phan

We discuss the synergetic connection between quantum computing and artificial intelligence. After surveying current approaches to quantum artificial intelligence and relating them to a formal model for machine learning processes, we deduce four major challenges for the future of quantum artificial intelligence: (i) Replace iterative training with faster quan

Jens Schreiber, Bernhard Sick

Multi-task learning (mtl) provides state-of-the-art results in many applications of computer vision and natural language processing. In contrast to single-task learning (stl), mtl allows for leveraging knowledge between related tasks improving prediction results on the main task (in contrast to an auxiliary task) or all tasks. However, there is a limited num

Ulrich Gallersdörfer, Florian Matthes

Although almost all information about Smart Contract addresses is shared via websites, emails, or other forms of digital communication, Blockchains and distributed ledger technology are unable to establish secure bindings between websites and corresponding Smart Contracts. For a user, it is impossible to differentiate whether a website links to a legitimate

Akram Aldroubi, Karlheinz Gröchenig, Longxiu Huang, Philippe Jaming

We analyze the problem of reconstruction of a bandlimited function $f$ from the space-time samples of its states $f_t=\phi_t\ast f$ resulting from the convolution with a kernel $\phi_t$. It is well-known that, in natural phenomena, uniform space-time samples of $f$ are not sufficient to reconstruct $f$ in a stable way. To enable stable reconstruction, a spac

Md Ashad Alam, Chuan Qiu, Hui Shen, Yu-Ping Wang

In recent years, a comprehensive study of multi-view datasets (e.g., multi-omics and imaging scans) has been a focus and forefront in biomedical research. State-of-the-art biomedical technologies are enabling us to collect multi-view biomedical datasets for the study of complex diseases. While all the views of data tend to explore complementary information o

Alberto Marmodoro, Sebastian Wimmer, Ondrej Sipr, Masako Ogura

Recent x-ray absorption experiments have demonstrated the possibility to accurately monitor the magnetism of metallic hetero-structures controlled via a time-independent perturbation caused for example by a static electric field. Using a first-principles, non-equilibrium Green function scheme, we show how the measured dichroic signal for the corresponding st

Weiwei Zhu, Di Li, Rui Luo, Chenchen Miao

We report the discovery of a highly dispersed fast radio burst, FRB~181123, from an analysis of $\sim$1500~hr of drift-scan survey data taken using the Five-hundred-meter Aperture Spherical radio Telescope (FAST). The pulse has three distinct emission components, which vary with frequency across our 1.0--1.5~GHz observing band. We measure the peak flux densi

Tewfik Sari, Boumediene Benyahia

The Anaerobic Digestion Model No. 1 (ADM1) is a complex model which is widely accepted as a common platform for anaerobic process modeling and simulation. However, it has a large number of parameters and states that hinder its analytical study. Here, we consider the two-step reduced model of anaerobic digestion (AM2) which is a four-dimensional system of ord

E. V. Tkalya

In the paper, a unique process of the decay of the $^{229m}$Th($3/2^+,8.28\pm 0.17$ eV) low energy nuclear isomer via the internal conversion (IC) channel on Rydberg states is considered for the first time. The Rydberg atom $^{229m}$Th$^{+}+e^-_{Ry}$ is a unique object where IC is possible exclusively on the Rydberg electron $e^-_{Ry}$. It is shown that in t

Stephan Deist, Jens Schreiber, Maarten Bieshaar, Bernhard Sick

This article is about an extension of a recent ensemble method called Coopetitive Soft Gating Ensemble (CSGE) and its application on power forecasting as well as motion primitive forecasting of cyclists. The CSGE has been used successfully in the field of wind power forecasting, outperforming common algorithms in this domain. The principal idea of the CSGE i

Yunlian Lv, Ning Xie, Yimin Shi, Zijiao Wang

Embodied artificial intelligence (AI) tasks shift from tasks focusing on internet images to active settings involving embodied agents that perceive and act within 3D environments. In this paper, we investigate the target-driven visual navigation using deep reinforcement learning (DRL) in 3D indoor scenes, whose navigation task aims to train an agent that can

Sungjin Park, Taesun Whang, Yeochan Yoon, Heuiseok Lim

Visual dialog is a challenging vision-language task in which a series of questions visually grounded by a given image are answered. To resolve the visual dialog task, a high-level understanding of various multimodal inputs (e.g., question, dialog history, and image) is required. Specifically, it is necessary for an agent to 1) determine the semantic intent o

Maximilian Neidhardt, Marcel Bengs, Sarah Latus, Matthias Schlüter

Mechanical properties of tissue provide valuable information for identifying lesions. One approach to obtain quantitative estimates of elastic properties is shear wave elastography with optical coherence elastography (OCE). However, given the shear wave velocity, it is still difficult to estimate elastic properties. Hence, we propose deep learning to directl

E. V. Tkalya, R. Si

A process of the decay of the anomalously low lying nuclear isomer $^{229m}$Th$(3/2^+,8.28 \pm 0.17$ eV) in the Thorium anion (Th$^-$) via the internal conversion (IC) channel is studied. We show that the half life of the nuclear isomer in the $6d_{3/2}^37s_{1/2}^2$ ground state and in the $6d_{3/2}^2 7s_{1/2}^2 7p_{1/2}^1$ excited state of Th$^-$ is $\appro

Mathieu Dutour Sikirić, Anna Haensch, John Voight, Wessel P. J. van Woerden

We exhibit an explicit, deterministic algorithm for finding a canonical form for a positive definite matrix under unimodular integral transformations. We use characteristic sets of short vectors and partition-backtracking graph software. The algorithm runs in a number of arithmetic operations that is exponential in the dimension $n$, but it is practical and

Xiangpeng Wei, Heng Yu, Yue Hu, Yue Zhang

Recent evidence reveals that Neural Machine Translation (NMT) models with deeper neural networks can be more effective but are difficult to train. In this paper, we present a MultiScale Collaborative (MSC) framework to ease the training of NMT models that are substantially deeper than those used previously. We explicitly boost the gradient back-propagation f

Sayed Hadi Hashemi, Sangeetha Abdu Jyothi, Brighten Godfrey, Roy Campbell

The method of choice for parameter aggregation in Deep Neural Network (DNN) training, a network-intensive task, is shifting from the Parameter Server model to decentralized aggregation schemes (AllReduce) inspired by theoretical guarantees of better performance. However, current implementations of AllReduce overlook the interdependence of communication and c

Sangin Kim, C. Y. Hui, Jongsu Lee, Kwangmin Oh

In this work, we study the X-ray bow-shock nebula powered by the mature pulsar PSR B1929+10 using data from XMM-Newton, with an effective exposure of $\sim$ 300 ks, offering the deepest investigation of this system thus far. We found the X-ray axial outflow extends as long as $\sim$ 8 arc minute behind the proper motion direction, which is a factor of two lo

Gregory A. L. White, Charles D. Hill, Felix A. Pollock, Lloyd C. L. Hollenberg

In the scale-up of quantum computers, the framework underpinning fault-tolerance generally relies on the strong assumption that environmental noise affecting qubit logic is uncorrelated (Markovian). However, as physical devices progress well into the complex multi-qubit regime, attention is turning to understanding the appearance and mitigation of correlated

Dongyub Lee, Myeongcheol Shin, Taesun Whang, Seungwoo Cho

Text summarization refers to the process that generates a shorter form of text from the source document preserving salient information. Many existing works for text summarization are generally evaluated by using recall-oriented understudy for gisting evaluation (ROUGE) scores. However, as ROUGE scores are computed based on n-gram overlap, they do not reflect

D. V. Piatnytskyi, O. O. Zdorevskyi, S. N. Volkov

Ion beam therapy is one of the most progressive methods in cancer treatment. Studies of the water radiolysis process show that the most long-living species that occur in the medium of a biological cell under the action of ionizing irradiation are hydrogen peroxide (H$_2$O$_2$) molecules. But the role of H$_2$O$_2$ molecules in the DNA deactivation of cancer

Daisuke Kaji, Kazuho Watanabe, Masahiro Kobayashi

Clustering algorithms have wide applications and play an important role in data analysis fields including time series data analysis. However, in time series analysis, most of the algorithms used signal shape features or the initial value of hidden variable of a neural network. Little has been discussed on the methods based on the generative model of the time

Krzysztof Dȩbicki, Enkelejd Hashorva, Konrad Krystecki

Let $(W_1(s), W_2(t)), s,t\ge 0$ be a bivariate Brownian motion with standard Brownian motion marginals and constant correlation $\rho \in (-1,1)$ and define the joint survival probability of both supremum functionals $\pi_\rho(c_1,c_2; u, v)$ by $$\pi_\rho(c_1,c_2; u, v)=\mathbb{P}\left(\sup_{s \in [0,1]} \left(W_1(s)-c_1s\right)>u,\sup_{t \in [0,1]} \left(

Jialin Liu, Antoine Moreau, Mike Preuss, Baptiste Roziere

Choosing automatically the right algorithm using problem descriptors is a classical component of combinatorial optimization. It is also a good tool for making evolutionary algorithms fast, robust and versatile. We present Shiwa, an algorithm good at both discrete and continuous, noisy and noise-free, sequential and parallel, black-box optimization. Our algor

Long Zhang, Lin Zhang, Xiong-Jun Liu

The conventional characterization of periodically driven systems usually necessitates the time-domain information beyond Floquet bands, hence lacking universal and direct schemes of measuring Floquet topological invariants. Here we propose a unified theory based on quantum quenches to characterize generic $d$-dimensional ($d$D) Floquet topological phases, in

Quentin Labriet

We study holographic operators associated with Rankin-Cohen brackets which are symmetry breaking operators for the restriction of tensor products of holomorphic discrete series of SL2(R). Furthermore, we investigate a geometrical interpretation of these operators and their relations to classical Jacobi polynomials.

Lucas J. Fernández-Alcázar, Huanan Li, Tsampikos Kottos

By utilizing Floquet driving protocols and interlacing them with a judicious reservoir emission engineering we achieve extreme non-reciprocal thermal radiation. We show that the latter is rooted in an interplay between a direct radiation process occurring due to temperature bias between two thermal baths and the modulation process which is responsible for pu

Clément Bénard, Gérard Biau, Sébastien da Veiga, Erwan Scornet

We introduce SIRUS (Stable and Interpretable RUle Set) for regression, a stable rule learning algorithm which takes the form of a short and simple list of rules. State-of-the-art learning algorithms are often referred to as "black boxes" because of the high number of operations involved in their prediction process. Despite their powerful predictivity, this l

Patrick Valageas, Takahiro Nishimichi

We study the predictions for the matter redshift-space power spectrum and correlation function of a Lagrangian-space Gaussian ansatz introduced in a previous work. This model is a natural extension of the Zeldovich approximation, where the displacement and velocity power spectra are determined by the equations of motion, instead of being set equal to the lin

Laura Zabawa, Anna Kicherer, Lasse Klingbeil, Reinhard Töpfer

The extraction of phenotypic traits is often very time and labour intensive. Especially the investigation in viticulture is restricted to an on-site analysis due to the perennial nature of grapevine. Traditionally skilled experts examine small samples and extrapolate the results to a whole plot. Thereby different grapevine varieties and training systems, e.g

Karl Oskar Ekvall

We propose a principal components regression method based on maximizing a joint pseudo-likelihood for responses and predictors. Our method uses both responses and predictors to select linear combinations of the predictors relevant for the regression, thereby addressing an oft-cited deficiency of conventional principal components regression. The proposed esti

Reina Akama, Sho Yokoi, Jun Suzuki, Kentaro Inui

Large-scale dialogue datasets have recently become available for training neural dialogue agents. However, these datasets have been reported to contain a non-negligible number of unacceptable utterance pairs. In this paper, we propose a method for scoring the quality of utterance pairs in terms of their connectivity and relatedness. The proposed scoring meth

Flavien Mabilat

A Theorem of V.Ovsienko characterizes sequences of positive integers $(a_1,a_2,\ldots,a_n)$ such that the $(2\times2)$-matrix $\begin{pmatrix} a_n & -1 \\ 1 & 0 \end{pmatrix}\cdots \begin{pmatrix} a_1 & -1 \\ 1 & 0 \end{pmatrix}$ is equal to $\pm Id$. In this paper, we study this equation when we replace $\pm Id$ by $\pm M$. In particular, we give a combinat

E. V. Tkalya

Excitation of the anomalously low lying nuclear isomer $^{229m}$Th$(3/2^+, 8.28 \pm 0.17$ eV) in the process of inelastic electron scattering is studied theoretically in the framework of the perturbation theory for the quantum electrodynamics. The calculated cross sections of $^{229m}$Th by the extremely low energy electrons in the range 9 eV--12 eV for the

Dibakar Dey, Pradip Majhi

In the present paper, we characterize almost Kenmotsu manifolds admitting holomorphically planar conformal vector (HPCV) fields. We have shown that if an almost Kenmotsu manifold $M^{2n+1}$ admits a non-zero HPCV field $V$ such that $\phi V = 0$, then $M^{2n+1}$ is locally a warped product of an almost Kaehler manifold and an open interval. As a corollary of

Chenglei Si, Ziqing Yang, Yiming Cui, Wentao Ma

Machine Reading Comprehension (MRC) is an important testbed for evaluating models' natural language understanding (NLU) ability. There has been rapid progress in this area, with new models achieving impressive performance on various benchmarks. However, existing benchmarks only evaluate models on in-domain test sets without considering their robustness under

Arjun D. Desai, Francesco Caliva, Claudia Iriondo, Naji Khosravan

Purpose: To organize a knee MRI segmentation challenge for characterizing the semantic and clinical efficacy of automatic segmentation methods relevant for monitoring osteoarthritis progression. Methods: A dataset partition consisting of 3D knee MRI from 88 subjects at two timepoints with ground-truth articular (femoral, tibial, patellar) cartilage and menis

Peter Benner, Xin Liang

This paper is concerned with the convergence analysis of an extended variation of the locally optimal preconditioned conjugate gradient method (LOBPCG) for the extreme eigenvalue of a Hermitian matrix polynomial which admits some extended form of Rayleigh quotient. This work is a generalization of the analysis by Ovtchinnikov (SIAM J. Numer. Anal., 46(5):256

Jörg Wenninger

This lecture gives an overview of the impacts on linear machine optics of machine imperfections due to incorrect field settings and misalignments. The effects of imperfections in dipole, quadrupole, and sextupole magnets are presented, along with beam observables and correction techniques that may be used to restore the nominal machine parameters. The main c

Max A. Alekseyev, Joseph Samuel Myers, Richard Schroeppel, S. R. Shannon

Although 10^230 terms of Recaman's sequence have been computed, it remains a mystery. Here three distant cousins of that sequence are described, one of which is also mysterious. (i) {A(n), n >= 3} is defined as follows. Start with n, and add n+1, n+2, n+3, ..., stopping after adding n+k if the sum n + (n+1) + ... + (n+k) is divisible by n+k+1. Then A(n)=k. W

Qiongxiu Li, Richard Heusdens, Mads Græsbøll Christensen

As the modern world becomes increasingly digitized and interconnected, distributed signal processing has proven to be effective in processing its large volume of data. However, a main challenge limiting the broad use of distributed signal processing techniques is the issue of privacy in handling sensitive data. To address this privacy issue, we propose a nov

Chenglin Xu, Wei Rao, Eng Siong Chng, Haizhou Li

Speaker extraction is to extract a target speaker's voice from multi-talker speech. It simulates humans' cocktail party effect or the selective listening ability. The prior work mostly performs speaker extraction in frequency domain, then reconstructs the signal with some phase approximation. The inaccuracy of phase estimation is inherent to the frequency do

Yozo Tonaki, Yusuke Kaino, Masayuki Uchida

We consider the adaptive test for the parameter change in discretely observed ergodic diffusion processes based on the cusum test. Using two test statistics based on the two quasi-log likelihood functions of the diffusion parameter and the drift parameter, we perform the change point tests for both diffusion and drift parameters of the diffusion process. It

Jorge Peña Queralta, Li Qingqing, Tuan Nguyen Gia, Hong-Linh Truong

More widespread adoption requires swarms of robots to be more flexible for real-world applications. Multiple challenges remain in complex scenarios where a large amount of data needs to be processed in real-time and high degrees of situational awareness are required. The options in this direction are limited in existing robotic swarms, mostly homogeneous rob

Nitin Yadav, R. H. Cameron, S. K. Solanki

The relationship between vortex flows at different spatial scales and their contribution to the energy balance in the chromosphere is not yet fully understood. We perform three-dimensional (3D) radiation-magnetohydrodynamic (MHD) simulations of a unipolar solar plage region at a spatial resolution of 10 km using the MURaM code. We use the swirling-strength c

Yansheng Liang, Zhaojun Wang, Ming Lei

Optical trapping of metallic microparticles remains a big challenge because of the strong scattering and absorption of light by the particles. In the paper, we report a new mechanism for stable trapping of metallic microparticles by using a tightly focused linearly polarized Gaussian spot. We theoretically and experimentally demonstrated that metallic microp

Yan Benhammou, Erez Etzion, Gilad Mizrachi, Meny Raviv Moshe

We report on studies of non-toxic scintillating liquid useful for large surface detectors. Arrays of liquid scintillators offer a rather simple tool for detecting charged particles traversing a surface and tracking their path through a defined volume. Insertion of wavelength shifting fibres along the liquid scintillating containers significantly improves the

Ha-Reem Kim, Min-Soo Hwang, Daria Smirnova, Kwang-Yong Jeong

Topological photonics provides a fundamental framework for robust manipulation of light, including directional transport and localization with built-in immunity to disorder. Combined with an optical gain, active topological cavities hold special promise for a design of light-emitting devices. Most studies to date have focused on lasing at topological edges o

Bikash Chakraborty, Jayanta Kamila, Amit Kumar Pal, Sudip Saha

In this paper, we exhibit the equivalence between different notions of unique range sets, namely, unique range sets, weighted unique range sets and weak-weighted unique range sets under certain conditions.\par Also, we present some uniqueness theorems which show how two meromorphic functions are uniquely determined by their two finite shared sets. Moreover,

Guillaume Noyel, Christine Vartin, Peter Boyle, Laurent Kodjikian

We introduce a novel method to extract the vessels in eye fun-dus images which is adaptive to lighting variations. In the Logarithmic Image Processing framework, a 3-segment probe detects the vessels by probing the topographic surface of an image from below. A map of contrasts between the probe and the image allows to detect the vessels by a threshold. In a

Katalin Feher, Asta Zelenkauskaite

With the increased expectation of artificial intelligence, academic research face complex questions of human-centred, responsible and trustworthy technology embedded into society and culture. Several academic debates, social consultations and impact studies are available to reveal the key aspects of the changing human-machine ecosystem. To contribute to thes

Tomoyuki Nakagawa, Shintaro Hashimoto

This paper presents objective priors for robust Bayesian estimation against outliers based on divergences. The minimum $\gamma$-divergence estimator is well-known to work well estimation against heavy contamination. The robust Bayesian methods by using quasi-posterior distributions based on divergences have been also proposed in recent years. In objective Ba

Jason Atnip, Hiroki Sumi, Mariusz Urbański

We study skew-product dynamics for a large class of finitely-generated semi--hyperbolic semigroups of rational maps acting on the Riemann sphere, which generalizes both the theory of iteration of a single rational map of a single complex variable complex/holomorphic dynamics) and the theory of countable alphabet conformal iterated function systems (CIFSs). W

K. Abe, N. Akhlaq, R. Akutsu, A. Ali

We report measurements of the flux-integrated $\bar{\nu}_\mu$ and $\bar{\nu}_\mu+\nu_\mu$ charged-current cross-sections on water and hydrocarbon targets using the T2K anti-neutrino beam, with a mean neutrino energy of 0.86 GeV. The signal is defined as the (anti-)neutrino charged-current interaction with one induced $\mu^\pm$ and no detected charged pion no

Junlong Li, Zhuosheng Zhang, Hai Zhao

Multi-choice machine reading comprehension (MRC) requires models to choose the correct answer from candidate options given a passage and a question. Our research focuses dialogue-based MRC, where the passages are multi-turn dialogues. It suffers from two challenges, the answer selection decision is made without support of latently helpful commonsense, and th

Thibault Cavalié, Olivia Venot, Yamila Miguel, Leigh N. Fletcher

The distant ice giants of the Solar System, Uranus and Neptune, have only been visited by one space mission, Voyager 2. The current knowledge on their composition remains very limited despite some recent advances. A better characterization of their composition is however essential to constrain their formation and evolution, as a significant fraction of their

Matthieu Dussaule

This is the second of a series of two papers dealing with local limit theorems in relatively hyperbolic groups. In this second paper, we restrict our attention to non-spectrally degenerate random walks and we prove precise asymptotics of the probability $p_n(e, e)$ of going back to the origin at time $n$. We combine techniques adapted from thermodynamic form

Jingbo Wang, Sijie Yan, Yuanjun Xiong, Dahua Lin

We propose a new loss function, called motion loss, for the problem of monocular 3D Human pose estimation from 2D pose. In computing motion loss, a simple yet effective representation for keypoint motion, called pairwise motion encoding, is introduced. We design a new graph convolutional network architecture, U-shaped GCN (UGCN). It captures both short-term

Jan Helmig, Fabian Key, Marek Behr, Stefanie Elgeti

For most finite element simulations, boundary-conforming meshes have significant advantages in terms of accuracy or efficiency. This is particularly true for complex domains. However, with increased complexity of the domain, generating a boundary-conforming mesh becomes more difficult and time consuming. One might therefore decide to resort to an approach wh

Zhengyuan Liu, Ke Shi, Nancy F. Chen

Much progress has been made in text summarization, fueled by neural architectures using large-scale training corpora. However, in the news domain, neural models easily overfit by leveraging position-related features due to the prevalence of the inverted pyramid writing style. In addition, there is an unmet need to generate a variety of summaries for differen

Mitsuaki Hirasawa, Akira Matsumoto, Jun Nishimura, Atis Yosprakob

Monte Carlo simulation of gauge theories with a $\theta$ term is known to be extremely difficult due to the sign problem. Recently there has been major progress in solving this problem based on the idea of complexifying dynamical variables. Here we consider the complex Langevin method (CLM), which is a promising approach for its low computational cost. The d

André Schlichting, Christian Seis

In this paper, we propose a finite-volume scheme for aggregation-diffusion equations based on a Scharfetter--Gummel approximation of the quadratic, nonlocal flux term. This scheme is analyzed concerning well-posedness and convergence towards solutions to the continuous problem. Also, it is proven that the numerical scheme has several structure-preserving fea

Matthew Sims, David Bamman

We present the task of modeling information propagation in literature, in which we seek to identify pieces of information passing from character A to character B to character C, only given a description of their activity in text. We describe a new pipeline for measuring information propagation in this domain and publish a new dataset for speaker attribution,

Bruce X. B. Yu, Yan Liu, Keith C. C. Chan

The data-driven approach that learns an optimal representation of vision features like skeleton frames or RGB videos is currently a dominant paradigm for activity recognition. While great improvements have been achieved from existing single modal approaches with increasingly larger datasets, the fusion of various data modalities at the feature level has seld

Yash Khanna, Anand Louis

Given an undirected graph $G$, the Densest $k$-subgraph problem (DkS) asks to compute a set $S \subset V$ of cardinality $\left\lvert S\right\rvert \leq k$ such that the weight of edges inside $S$ is maximized. This is a fundamental NP-hard problem whose approximability, inspite of many decades of research, is yet to be settled. The current best known approx

Bruce X. B. Yu, Yan Liu, Keith C. C. Chan

Most recent work on vision-based human activity recognition (HAR) focuses on designing complex deep learning models for the task. In so doing, there is a requirement for large datasets to be collected. As acquiring and processing large training datasets are usually very expensive, the problem of how dataset size can be reduced without affecting recognition a

Jannatul Ferdous, Suvrajit Karmaker, A K M Shahariar Azad Rabby, Syed Akhter Hossain

At present, recognition of the Bangla handwriting compound character has been an essential issue for many years. In recent years there have been application-based researches in machine learning, and deep learning, which is gained interest, and most notably is handwriting recognition because it has a tremendous application such as Bangla OCR. MatrriVasha, the

Ke Wang, Lu Chen

Newton's constant has observational effects on both the CMB power spectra and the light curves of SNIa. We use Planck data, BAO data and the SNIa measurement to constrain the varying Newton's constant $G$ during the CMB epoch and the redshift ranges of PANTHEON samples, and find no evidence indicating that $G$ is varying with redshift. By extending the $\Lam

Jinzhi Huang, Zhongxiao Jia

A Cross-Product Free (CPF) Jacobi-Davidson (JD) type method is proposed to compute a partial generalized singular value decomposition (GSVD) of a large regular matrix pair $(A,B)$. It implicitly solves the mathematically equivalent generalized eigenvalue problem of $(A^TA,B^TB)$ but does not explicitly form the cross-product matrices and thus avoids the poss

S. M. Ghoreyshi

The observations and simulations have revealed that large-scale magnetic field and outflows can exist in the inner regions of an advection-dominated accretion disc where the resistive diffusion may also be important. In the present paper, the roles of large-scale magnetic field and outflows in the structure of resistive advection-dominated accretion discs ar

Lutz Bornmann, Robin Haunschild, Vanash M. Patel

We propose to use Twitter data as social-spatial sensors. This study deals with the question whether research papers on certain diseases are perceived by people in regions (worldwide) that are especially concerned by the diseases. Since (some) Twitter data contain location information, it is possible to spatially map the activity of Twitter users referring t

Enyu Cai, Sriram Baireddy, Changye Yang, Melba Crawford

Plant phenotyping focuses on the measurement of plant characteristics throughout the growing season, typically with the goal of evaluating genotypes for plant breeding. Estimating plant location is important for identifying genotypes which have low emergence, which is also related to the environment and management practices such as fertilizer applications. T

Jaspreet Singh, Zhenye Wang, Megha Khosla, Avishek Anand

Learning-to-rank (LTR) is a class of supervised learning techniques that apply to ranking problems dealing with a large number of features. The popularity and widespread application of LTR models in prioritizing information in a variety of domains makes their scrutability vital in today's landscape of fair and transparent learning systems. However, limited w

Youssef Hammadi, David Ryckelynck, Amin El-Bakkali

We propose a machine learning approach aiming at reducing Bond Graphs. The output of the machine learning is a hybrid modeling that contains a reduced Bond Graph coupled to a simple artificial neural network. The proposed coupling enables knowledge continuity in machine learning. In this paper, a neural network is obtained by a linear calibration procedure.

Zekun Tong, Yuxuan Liang, Changsheng Sun, David S. Rosenblum

Graph Convolutional Networks (GCNs) have been widely used due to their outstanding performance in processing graph-structured data. However, the undirected graphs limit their application scope. In this paper, we extend spectral-based graph convolution to directed graphs by using first- and second-order proximity, which can not only retain the connection prop

Luyu Gao, Zhuyun Dai, Tongfei Chen, Zhen Fan

This paper presents CLEAR, a retrieval model that seeks to complement classical lexical exact-match models such as BM25 with semantic matching signals from a neural embedding matching model. CLEAR explicitly trains the neural embedding to encode language structures and semantics that lexical retrieval fails to capture with a novel residual-based embedding le

Bibhas Kumar Dutta, Pradipta panchadhyayee, Indranil Bayal, Nityananda Das

We propose a multi-field-coupled atomic model that exhibits controllable $symmetric$ and $asymmetric$ evolution of significantly enhanced diffraction peaks in an opto-atomic grating at far-field regime. Such results are obtained by the linear and nonlinear modulation of the intensities of the diffraction peaks as a result of multi-wave-mixing-induced modific

Subhadra Dasgupta, Siuli Mukhopadhyay, Jonathan Keith

This article focuses on the estimation and design aspects of a bivariate collocated cokriging experiment. For a large class of covariance matrices, a linear dependency criterion is identified, which allows the best linear unbiased estimator of the primary variable in a bivariate collocated cokriging setup to reduce to a univariate kriging estimator. Exact op

Ayuki Kamada, Masaki Yamada, Tsutomu T. Yanagida

A strongly interacting massive particle (SIMP) is an interesting candidate for dark matter (DM) because its self-interaction cross section can be naturally strong enough to address the astrophysical problem of small-scale structure formation. A simple model was proposed by assuming a monopole condensation, where composite SIMP comes from a "strongly interact