October 2020 arXiv papers — page 103

Alexandros Rekkas, David van Klaveren, Patrick B. Ryan, Ewout W. Steyerberg

The Predictive Approaches to Treatment Effect Heterogeneity statement focused on baseline risk as a robust predictor of treatment effect and provided guidance on risk-based assessment of treatment effect heterogeneity in the RCT setting. The aim of this study was to extend this approach to the observational setting using a standardized scalable framework. Th

Jonathan Homann, Wen-Chi Kuo, Bruce A. Watson

The ergodic theorems of Hopf, Wiener and Birkhoff were extended to the context of Riesz spaces with a weak order unit and conditional expectation operator by Kuo, Labuschagne and Watson in [Ergodic Theory and the Strong Law of Large Numbers on Riesz Spaces. Journal of Mathematical Analysis and Applications, 325,(2007), 422-437.]. However, the precise concept

Abdul Wahab Muzaffar, Muhammad Tahir, Muhammad Waseem Anwar, Qaiser Chaudry

E-learning in higher education is exponentially increased during the past decade due to its inevitable benefits in critical situations like natural disasters, and pandemic. The reliable, fair, and seamless execution of online exams in E-learning is highly significant. Particularly, online exams are conducted on E-learning platforms without the physical prese

Faustin Adiceam, Ioannis Tsokanos

A Delone set in $\mathbb{R}^n$ is a set such that (a) the distance between any two of its points is uniformly bounded below by a strictly positive constant and such that (b) the distance from any point to the remaining points in the set is uniformly bounded above. Delone sets are thus sets of points enjoying nice spacing properties, and appear therefore natu

L. Bassani, F. Ursini, A. Malizia, G. Bruni

We present an update on the sample of soft gamma-ray selected giant radio galaxies (GRGs) extracted from INTEGRAL/IBIS and Swift/BAT surveys; it includes 8 new sources and one candidate object. In the new sample all, but one source, display FR II radio morphologies; the only exception is B21144+35B which is an FR I. The objects belong to both type 1 and 2 AG

Francesca Ronchini, Daniel Arteaga, Andrés Pérez-López

Sound Event Localization and Detection refers to the problem of identifying the presence of independent or temporally-overlapped sound sources, correctly identifying to which sound class it belongs, estimating their spatial directions while they are active. In the last years, neural networks have become the prevailing method for sound Event Localization and

Juergen Hausen, Timo Hummel

We consider possibly singular rational projective k*-surfaces and provide an explicit description of the unit component of the automorphism group in terms of isotropy group orders and intersection numbers of suitable invariant curves. As an application, we characterize the almost homogeneous rational projective k*-surfaces and we specify the two-dimensional

Giulia Orrù, Marco Micheletto, Fabio Terranova, Gian Luca Marcialis

In this study we investigate a textural processing method of electroencephalography (EEG) signal as an indicator to estimate the driver's vigilance in a hypothetical Brain-Computer Interface (BCI) system. The novelty of the solution proposed relies on employing the one-dimensional Local Binary Pattern (1D-LBP) algorithm for feature extraction from pre-pr

Almaz Tesfay, Daniel Tesfay, Shenglan Yuan, James Brannan

Bifurcation analysis has many applications in different scientific fields, such as electronics, biology, ecology, and economics. In population biology, deterministic methods of bifurcation are commonly used. In contrast, stochastic bifurcation techniques are infrequently employed. Here we establish stochastic P-bifurcation behavior of (i) a growth model with

Giulia Orrù, Davide Ghiani, Maura Pintor, Gian Luca Marcialis

We present a novel descriptor for crowd behavior analysis and anomaly detection. The goal is to measure by appropriate patterns the speed of formation and disintegration of groups in the crowd. This descriptor is inspired by the concept of one-dimensional local binary patterns: in our case, such patterns depend on the number of group observed in a time windo

H. Varguet, A. Diaz-Valles, S. Guérin, H. R. Jauslin

Quantum plasmonics extends cavity quantum electrodynamics (cQED) concepts to the nanoscale, taking benefit from the strongly subwavelength confinement of the plasmon modes supported by metal nanostructures. In this work, we describe in detail collective strong coupling to a plasmonic nanocavity. Similarities and differences to cQED are emphasized. We notably

Akhila Sri Manasa Venigalla, Sridhar Chimalakonda

Emails are one of the most frequently used medium of communication in the present day across multiple domains including industry and educational institutions. Understanding sentiments being expressed in an email could have a considerable impact on the recipients' action or response to the email. However, it is difficult to interpret emotions of the sende

Cedric Renggli, André Susano Pinto, Luka Rimanic, Joan Puigcerver

Transfer learning has been recently popularized as a data-efficient alternative to training models from scratch, in particular for computer vision tasks where it provides a remarkably solid baseline. The emergence of rich model repositories, such as TensorFlow Hub, enables the practitioners and researchers to unleash the potential of these models across a wi

Rahul Singh, Fang Liu, Yin Sun, Ness Shroff

We study a variant of the classical multi-armed bandit problem (MABP) which we call as Multi-Armed Bandits with dependent arms. More specifically, multiple arms are grouped together to form a cluster, and the reward distributions of arms belonging to the same cluster are known functions of an unknown parameter that is a characteristic of the cluster. Thus, p

Hyuga Yoshizaki

We study a generalization of Pell's equation, whose coefficients are certain algebraic integers. Let $X_0=0$ and $X_n=\sqrt{2+X_{n-1}}$ for each $n\in \mathbb{Z}_{\ge 1}$. We study the $\mathbb{Z}[X_{n-1}]$-solutions of the equation $x^2-X_n^2y^2=1$. By imitating the solution to the classical Pell's equation, we introduce new continued fraction expan

Ekta Sood, Simon Tannert, Diego Frassinelli, Andreas Bulling

While neural networks with attention mechanisms have achieved superior performance on many natural language processing tasks, it remains unclear to which extent learned attention resembles human visual attention. In this paper, we propose a new method that leverages eye-tracking data to investigate the relationship between human visual attention and neural a

A. Ravlic, E. Yuksel, Y. F. Niu, N. Paar

$β$-decay properties of nuclei are investigated within the relativistic nuclear energy density functional framework by varying the temperature and density, conditions relevant to the final stages of stellar evolution. Both thermal and nuclear pairing effects are taken into account in the description of nuclear properties and in the finite temperature proton-

Adrià Delhom, J. R. Nascimento, Gonzalo J. Olmo, A. Yu. Petrov

We consider the metric-affine formulation of bumblebee gravity, derive the field equations, and show that the connection can be written as Levi-Civita of a disformally related metric in which the bumblebee field determines the disformal part. As a consequence, the bumblebee field gets coupled to all the other matter fields present in the theory, potentially

Scott L. Todd, Giacomo Pantaleoni, Valentina Baccetti, Nicolas C. Menicucci

We investigate a simple toy model of particle scattering in the flat spacetime limit of an analogue-gravity model. The analogue-gravity medium is treated as a scalar field of phonons that obeys the Klein-Gordon equation and thus admits a Lorentz symmetry with respect to $c_\mathrm{s}$, the speed of sound in the medium. The particle from which the phonons are

Jingfei Chang

The existing convolutional neural network pruning algorithms can be divided into two categories: coarse-grained clipping and fine-grained clipping. This paper proposes a coarse and fine-grained automatic pruning algorithm, which can achieve more efficient and accurate compression acceleration for convolutional neural networks. First, cluster the intermediate

Giacomo Aletti, Irene Crimaldi

We introduce the Generalized Rescaled Polya (GRP) urn, that provides a generative model for a chi-squared test of goodness of fit for the long-term probabilities of clustered data, with independence between clusters and correlation, due to a reinforcement mechanism, inside each cluster. We apply the proposed test to a data set of Twitter posts about COVID-19

David Landa-Marbán, Svenn Tveit, Kundan Kumar, Sarah E. Gasda

Microbially induced calcite precipitation (MICP) is a new and sustainable technology which utilizes biochemical processes to create barriers by calcium carbonate cementation; therefore, this technology has a potential to be used for sealing leakage zones in geological formations. The complexity of current MICP models and present computer power limit the size

Fabian Meyer, Marcel Hark, Jürgen Giesl

We present a novel modular approach to infer upper bounds on the expected runtime of probabilistic integer programs automatically. To this end, it computes bounds on the runtime of program parts and on the sizes of their variables in an alternating way. To evaluate its power, we implemented our approach in a new version of our open-source tool KoAT.

Christopher H. Broadbent, Arnaud Carayol, C. -H. Luke Ong, Olivier Serre

This paper studies the logical properties of a very general class of infinite ranked trees, namely those generated by higher-order recursion schemes. We consider, for both monadic second-order logic and modal mu-calculus, three main problems: model-checking, logical reflection (aka global model-checking, that asks for a finite description of the set of eleme

Jinting Wu, Yujia Zhang, Xiaoguang Zhao, Wenbin Gao

Although automatic emotion recognition from facial expressions and speech has made remarkable progress, emotion recognition from body gestures has not been thoroughly explored. People often use a variety of body language to express emotions, and it is difficult to enumerate all emotional body gestures and collect enough samples for each category. Therefore,

Eleftherios Avramidis, Vivien Macketanz, Ursula Strohriegel, Aljoscha Burchardt

This paper describes a test suite submission providing detailed statistics of linguistic performance for the state-of-the-art German-English systems of the Fifth Conference of Machine Translation (WMT20). The analysis covers 107 phenomena organized in 14 categories based on about 5,500 test items, including a manual annotation effort of 45 person hours. Two

Jiahui Chen, Kaifu Gao, Rui Wang, Guowei Wei

Antibody therapeutics and vaccines are among our last resort to end the raging COVID-19 pandemic. They, however, are prone to over 5,000 mutations on the spike (S) protein uncovered by a Mutation Tracker based on over 200,000 genome isolates. It is imperative to understand how mutations would impact vaccines and antibodies in the development. In this work, w

Fuli Luo, Pengcheng Yang, Shicheng Li, Xuancheng Ren

Pre-trained self-supervised models such as BERT have achieved striking success in learning sequence representations, especially for natural language processing. These models typically corrupt the given sequences with certain types of noise, such as masking, shuffling, or substitution, and then try to recover the original input. However, such pre-training app

Yi-Xin Xiao, Kun Ding, Ruo-Yang Zhang, Zhi Hong Hang

An astroid-shaped loop of exceptional points (EPs), comprising four cusps, is found to spawn from the triple degeneracy point in the Brillouin zone (BZ) of a Lieb lattice with nearest-neighbor hoppings when non-Hermiticity is introduced. The occurrence of the EP loop is due to the realness of the discriminant which is guaranteed by the non-Hermitian chiral s

Zongxin Yang, Yunchao Wei, Yi Yang

This paper investigates the principles of embedding learning to tackle the challenging semi-supervised video object segmentation. Unlike previous practices that focus on exploring the embedding learning of foreground object (s), we consider background should be equally treated. Thus, we propose a Collaborative video object segmentation by Foreground-Backgrou

E. Rofors, N. Mauritzson, H. Perrey, R. Al Jebali

The response of a position-sensitive Li-glass scintillator detector being developed for thermal-neutron detection with 6 mm position resolution has been investigated using collimated beams of thermal neutrons. The detector was moved perpendicularly through the neutron beams in 0.5 to 1.0 mm horizontal and vertical steps. Scintillation was detected in an 8 X

Simon Hubmer, Ronny Ramlau

We consider the decomposition of bounded linear operators on Hilbert spaces in terms of functions forming frames. Similar to the singular-value decomposition, the resulting frame decompositions encode information on the structure and ill-posedness of the problem and can be used as the basis for the design and implementation of efficient numerical solution me

Eléa Prat, Spyros Chatzivasileiadis

Bilevel programming can be used to formulate many problems in the field of power systems, such as strategic bidding. However, common reformulations of bilevel problems to mixed-integer linear programs make solving such problems hard, which impedes their implementation in real-life. In this paper, we significantly improve solution speed and tractability by in

Zu-Xing Yang, Nicolas Michel, Xiao-Hua Fan, Wei Zuo

We study a problem of $π$ production in heavy ion collisions in the context of the Isospin-dependent Boltzmann-Uehling-Uhlenbeck (IBUU) transport model. We generated nucleon densities using two different models, the Skyrme-Hartree-Fock (SHF) model and configuration interaction shell model (SM). Indeed, inter-nucleon correlations are explicitly taken into acc

Pritam Pai, Jeroen Bosch, Allard P. Mosk

The study of the optical transmission matrix (TM) of a sample reveals important statistics of light transport through it. The accuracy of the statistics depends strongly on the orthogonality and completeness of the basis in which the TM is measured. While conventional experimental methods suffer from sampling effects and optical aberrations, we use a basis o

Randolf Altmeyer, Till Bretschneider, Josef Janák, Markus Reiß

As a concrete setting where stochastic partial differential equations (SPDEs) are able to model real phenomena, we propose a stochastic Meinhardt model for cell repolarisation and study how parameter estimation techniques developed for simple linear SPDE models apply in this situation. We establish the existence of mild SPDE solutions and we investigate the

Wei-Jia Huang, Wei-Chen Chien, Chien-Hung Cho, Che-Chun Huang

We have studied carefully the behaviors of entangled qubits on the IBM Rochester with various connectivities and under a "noisy" environment. A phase trajectory analysis based on our measurements of the GHZ-like states is performed. Our results point to an important fact that entangled qubits are "protected" against environmental noise by a s

D. A. Green, N. Madhusudhan

We present radio observations made towards the exoplanets Qatar-1b and WASP-80b near 150~MHz with the Giant Meterwave Radio Telescope. These targets are relatively nearby irradiated giant exoplanets, a hot Jupiter and a hot Saturn, with sizes comparable to Jupiter but different masses and lower densities. Both the targets are expected to host extended H/He e

Xiangnan Ren, Neha Sengupta, Xuguang Ren, Junhu Wang

In this paper, we study the following problem: given a knowledge graph (KG) and a set of input vertices (representing concepts or entities) and edge labels, we aim to find the smallest connected subgraphs containing all of the inputs. This problem plays a key role in KG-based search engines and natural language question answering systems, and it is a natural

D. Opherden, F. Bärtl, Sh. Yamamoto, Z. T. Zhang

We present a detailed $^{31}$P nuclear magnetic resonance (NMR) study of the molecular rotation in the compound [Cu(pz)$_{2}$(2-HOpy)$_{2}$](PF$_{6}$)$_{2}$, where pz = C$_4$H$_4$N$_2$ and 2-HOpy = C$_5$H$_4$NHO. Here, a freezing of the PF$_6$ rotation modes is revealed by several steplike increases of the temperature-dependent second spectral moment, with a

Boris Doubrov, Joël Merker, Dennis The

Holomorphically homogeneous CR real hypersurfaces $M^3 \subset \mathbb{C}^2$ were classified by Élie Cartan in 1932. In the next dimension, we complete the classification of simply-transitive Levi non-degenerate hypersurfaces $M^5 \subset \mathbb{C}^3$ using a novel Lie algebraic approach independent of any earlier classifications of abstract Lie algebras. C

Leena Ruha, Tero Lähderanta, Lauri Lovén, Markku Kuismin

Capacitated spatial clustering, a type of unsupervised machine learning method, is often used to tackle problems in compressing, classifying, logistic optimization and infrastructure optimization. Depending on the application at hand, a wide set of extensions may be necessary in clustering. In this article we propose a number of novel extensions to PACK that

Rebekka S. Beddig, Peter Benner, Ines Dorschky, Timo Reis

Suppressing vibrations in mechanical systems, usually described by second-order dynamical models, is a challenging task in mechanical engineering in terms of computational resources even nowadays. One remedy is structure-preserving model order reduction to construct easy-to-evaluate surrogates for the original dynamical system having the same structure. In o

Riwaj Byanju, Stefan Klein, Alexandra Cristobal-Huerta, J. A. Hernandez-Tamames

To realize Quantitative MRI (QMRI) with clinically acceptable scan time, acceleration factors achieved by conventional parallel imaging techniques are often inadequate. Further acceleration is possible using model-based reconstruction. We propose a theoretical metric called TEUSQA: Time Efficiency for UnderSampled QMRI Acquisitions to inform sequence design

Lei Hao

We propose methods for synthesizing multilayer optical lattices of cold atoms in a layer-by-layer manner, to unlock the potential of optical lattices in simulating the fascinating physics of multilayer systems. Central to the approach is to compress the beam profile of a red-detuned Gaussian laser beam from disklike to a thin line by a telescope with two cyl

Elena V. Epure, Guillaume Salha, Manuel Moussallam, Romain Hennequin

The music genre perception expressed through human annotations of artists or albums varies significantly across language-bound cultures. These variations cannot be modeled as mere translations since we also need to account for cultural differences in the music genre perception. In this work, we study the feasibility of obtaining relevant cross-lingual, cultu

Dan A. Calian, Daniel J. Mankowitz, Tom Zahavy, Zhongwen Xu

Deploying Reinforcement Learning (RL) agents to solve real-world applications often requires satisfying complex system constraints. Often the constraint thresholds are incorrectly set due to the complex nature of a system or the inability to verify the thresholds offline (e.g, no simulator or reasonable offline evaluation procedure exists). This results in s

Marko Bjelonic, Ruben Grandia, Oliver Harley, Cla Galliard

Our paper proposes a model predictive controller as a single-task formulation that simultaneously optimizes wheel and torso motions. This online joint velocity and ground reaction force optimization integrates a kinodynamic model of a wheeled quadrupedal robot. It defines the single rigid body dynamics along with the robot's kinematics while treating the

George Kaye

We examine a variant of hypergraphs that we call interfaced linear hypergraphs, with the aim of creating a sound and complete graphical language for symmetric traced monoidal categories (STMCs) suitable for graph rewriting. In particular, we are interested in rewriting for categorical settings with a Cartesian structure, such as digital circuits. These are i

Ararat Harutyunyan, Michael Lampis, Nikolaos Melissinos

In $k$-Digraph Coloring we are given a digraph and are asked to partition its vertices into at most $k$ sets, so that each set induces a DAG. This well-known problem is NP-hard, as it generalizes (undirected) $k$-Coloring, but becomes trivial if the input digraph is acyclic. This poses the natural parameterized complexity question what happens when the input

Jesus Toledo, Hector Ramirez, Yongxin Wu, Yann Le Gorrec

The design of an observer-based state feedback (OBSF) controller with guaranteed passivity properties for port-Hamiltonian systems (PHS) is addressed using linear matrix inequalities (LMIs). The observer gain is freely chosen and the LMIs conditions such that the state feedback is equivalent to control by interconnection with an input strictly passive (ISP)

Xi Lin, Zhiyuan Yang, Qingfu Zhang, Sam Kwong

A multi-task learning (MTL) system aims at solving multiple related tasks at the same time. With a fixed model capacity, the tasks would be conflicted with each other, and the system usually has to make a trade-off among learning all of them together. For many real-world applications where the trade-off has to be made online, multiple models with different p

Yue Wang, Zhuo Xu, Lu Bai, Yao Wan

Joint-event-extraction, which extracts structural information (i.e., entities or triggers of events) from unstructured real-world corpora, has attracted more and more research attention in natural language processing. Most existing works do not fully address the sparse co-occurrence relationships between entities and triggers, which loses this important info

Miguel Angel Fernandez-Rodriguez, Maria-Nefeli Antonopoulou, Lucio Isa

Understanding and engineering the self-assembly of soft colloidal particles (microgels) at liquid-liquid interfaces is broadening their use in colloidal lithography. Here, we present a new route to assemble rectangular lattices of microgels at near zero surface pressure relying on the balance between attractive quadrupolar capillary interactions and steric r

M. J. Kronenburg

The higher derivatives of the tangent and hyperbolic tangent functions are determined. Formulas for the higher derivatives of the inverse tangent and inverse hyperbolic tangent functions as polynomials are stated and proved. Using another formula for the higher derivatives of the inverse tangent function from literature, two known formulas for the Chebyshev

Sungnyun Kim, Gihun Lee, Sangmin Bae, Se-Young Yun

Contrastive learning has shown remarkable results in recent self-supervised approaches for visual representation. By learning to contrast positive pairs' representation from the corresponding negatives pairs, one can train good visual representations without human annotations. This paper proposes Mix-up Contrast (MixCo), which extends the contrastive lea

Nan Xu, Hassan Askari, Yanjun Huang, Jianfeng Zhou

The concept of intelligent tires has drawn attention of researchers in the areas of autonomous driving, advanced vehicle control, and artificial intelligence. The focus of this paper is on intelligent tires and the application of machine learning techniques to tire force estimation. We present an intelligent tire system with a tri-axial acceleration sensor,

Melvyn B. Nathanson

For certain sequences $A$ of positive integers with missing $g$-adic digits, the Dirichlet series $F_A(s) = \sum_{a\in A} a^{-s}$ has abscissa of convergence $σ_c < 1$. The number $σ_c$ is computed. This generalizes and strengthens a classical theorem of Kempner on the convergence of the sum of the reciprocals of a sequence of integers with missing decimal d

Théo Benoit-Cattin, Delia Velasco-Montero, Jorge Fernández-Berni

Many application scenarios of edge visual inference, e.g., robotics or environmental monitoring, eventually require long periods of continuous operation. In such periods, the processor temperature plays a critical role to keep a prescribed frame rate. Particularly, the heavy computational load of convolutional neural networks (CNNs) may lead to thermal throt

Ronnie Sebastian, Amit Tripathi

We prove that a double cover of $\mathbb{P}^2$ ramified along a general smooth curve B of degree $2s$, for $s \geq 3$, supports a rank 2 special Ulrich bundle.

Sharu Theresa Jose, Osvaldo Simeone

In transfer learning, training and testing data sets are drawn from different data distributions. The transfer generalization gap is the difference between the population loss on the target data distribution and the training loss. The training data set generally includes data drawn from both source and target distributions. This work presents novel informati

Ahmad M. N. Zaza, Suleiman K. Kharroub, Khalid Abualsaud

Internet of Things (IoT) is becoming more frequently used in more applications as the number of connected devices is in a rapid increase. More connected devices result in bigger challenges in terms of scalability, maintainability and most importantly security especially when it comes to 5G networks. The security aspect of IoT devices is an infant field, whic

Csaba Farkas

In the present paper, we deal with a quasilinear elliptic equation involving a critical Sobolev exponent on non-compact Randers spaces. Under very general assumptions on the perturbation, we prove the existence of a non-trivial solution. The approach is based on the direct methods of the calculus of variations. One of the key steps is to prove that the energ

Lukáš Nadvorník, Martin Borchert, Liane Brandt, Richard Schlitz

Anisotropic magnetoresistance (AMR) is a ubiquitous and versatile probe of magnetic order in contemporary spintronics research. Its origins are usually ascribed to extrinsic effects (i.e. spin-dependent electron scattering), whereas intrinsic (i.e. scattering-independent) contributions are neglected. Here, we measure AMR of polycrystalline thin films of the

Sriram Aananthakrishnan, Shamsul Abedin, Vincent Cave, Fabio Checconi

High performance large scale graph analytics are essential to timely analyze relationships in big data sets. Conventional processor architectures suffer from inefficient resource usage and bad scaling on those workloads. To enable efficient and scalable graph analysis, Intel developed the Programmable Integrated Unified Memory Architecture (PIUMA) as a part

Malintha Fernando, Lantao Liu

Swarms are highly robust systems that offer unique benefits compared to their alternatives. In this work, we propose a bio-inspired and artificial potential field-driven robot swarm control method, where the swarm formation dynamics are modeled on the basis of Markov Random Field (MRF) optimization. We integrate the internal agent-wise local interactions and

Jacopo Borga, Raul Penaguiao

We study the feasible region for consecutive patterns of pattern-avoiding permutations. More precisely, given a family $\mathcal C$ of permutations avoiding a fixed set of patterns, we consider the limit of proportions of consecutive patterns on large permutations of $\mathcal C$. These limits form a region, which we call the consecutive patterns feasible re

Martin Raum

We prove that Ramanujan-type congruences for integral weight modular forms away from the level and the congruence prime are equivalent to specific congruences for Hecke eigenvalues. In particular, we show that Ramanujan-type congruences are preserved by the action of the shallow Hecke algebra. More generally, we show for weakly holomorphic modular forms of i

Anssi T. Karttunen, J. N. Reddy

A discrete-to-continuum transformation to model 2-D discrete lattices as energetically equivalent 1-D continuum beams is developed. The study is initiated in a classical setting but results in a non-classical two-scale micropolar beam model via a novel link within a unit cell between the second-order macrorotation-gradient and the micropolar antisymmetric sh

Jean-Luc Baril, Alexander Burstein, Sergey Kirgizov

We study the distribution and the popularity of some patterns in $k$-ary faro words, i.e. words over the alphabet $\{1, 2, \ldots, k\}$ obtained by interlacing the letters of two nondecreasing words of lengths differing by at most one. We present a bijection between these words and dispersed Dyck paths (i.e. Motzkin paths with all level steps on the $x$-axis

Hansi Hettiarachchi, Tharindu Ranasinghe

This paper presents the team BRUMS submission to SemEval-2020 Task 3: Graded Word Similarity in Context. The system utilises state-of-the-art contextualised word embeddings, which have some task-specific adaptations, including stacked embeddings and average embeddings. Overall, the approach achieves good evaluation scores across all the languages, while main

Domenico P. L. Castrigiano

Unbounded (and bounded) Toeplitz operators (TO) with rational symbols are analysed in detail showing that they are densely defined closed and have finite dimensional kernels and deficiency spaces. The latter spaces as well as the domains, ranges, spectral and Fredholm points are determined. In particular, in the symmetric case, i.e., for a real rational symb

Darshana Rathnayake, Ashen de Silva, Dasun Puwakdandawa, Lakmal Meegahapola

Natural human interactions for Mixed Reality Applications are overwhelmingly multimodal: humans communicate intent and instructions via a combination of visual, aural and gestural cues. However, supporting low-latency and accurate comprehension of such multimodal instructions (MMI), on resource-constrained wearable devices, remains an open challenge, especia

G. Kishore, Anupam Kundu

In this paper, we study the local time spent by an Ornstein-Uhlenbeck particle at some location till time t. Using the Feynman-Kac formalism, the computation of the moment generating function of the local time can be mapped to the problem of finding the eigenvalues and eigenfunctions of a quantum particle. We employ quantum perturbation theory to compute the

Abhiroop Lahiri, Swapan K Pati

We have considered and alternating Heisenberg spin chain with nearest-neighbor ($J_1$), next-nearest neighbor ($J_2$) antiferromagnetic couplings along with z-component of the Dzyaloshinskii-Moriya(DM) ($D_z$) interactions. The Hamiltonian has been studied using (a) Linear Spin-Wave Theory(LSWT) and (b) Density Matrix Renormalization Group (DMRG). The system

Razan Ghzouli, Thorsten Berger, Einar Broch Johnsen, Swaib Dragule

Autonomous robots combine a variety of skills to form increasingly complex behaviors called missions. While the skills are often programmed at a relatively low level of abstraction, their coordination is architecturally separated and often expressed in higher-level languages or frameworks. Recently, the language of Behavior Trees gained attention among robot

Changhong Fu, Bowen Li, Fangqiang Ding, Fuling Lin

Aerial tracking, which has exhibited its omnipresent dedication and splendid performance, is one of the most active applications in the remote sensing field. Especially, unmanned aerial vehicle (UAV)-based remote sensing system, equipped with a visual tracking approach, has been widely used in aviation, navigation, agriculture,transportation, and public secu

Mariana Neves, Jurica Seva

Manual annotation of textual documents is a necessary task when constructing benchmark corpora for training and evaluating machine learning algorithms. We created a comprehensive directory of annotation tools that currently includes 93 tools. We analyzed the tools over a set of 31 features and implemented simple scripts and a Web application that filters the

Marzena Ciszak, Francesco Marino, Alessandro Torcini, Simona Olmi

Population bursts in a large ensemble of coupled elements result from the interplay between the local excitable properties of the nodes and the global network topology. Here collective excitability and self-sustained bursting oscillations are shown to spontaneously emerge in adaptive networks of globally coupled non-excitable units. The ingredients to observ

Jiajun Qi, Wu Guo, Jingjing Shi, Yafeng Chen

The universal speech attributes for x-vector based speaker verification (SV) are addressed in this paper. The manner and place of articulation form the fundamental speech attribute unit (SAU), and then new speech attribute (NSA) units for acoustic modeling are generated by tied tri-SAU states. An improved cross-stitch network is adopted as a multitask learni

Sandra Nestler, Christian Keup, David Dahmen, Matthieu Gilson

Cortical networks are strongly recurrent, and neurons have intrinsic temporal dynamics. This sets them apart from deep feed-forward networks. Despite the tremendous progress in the application of feed-forward networks and their theoretical understanding, it remains unclear how the interplay of recurrence and non-linearities in recurrent cortical networks con

Fares J. Abu-Dakka, Matteo Saveriano

Robots that physically interact with their surroundings, in order to accomplish some tasks or assist humans in their activities, require to exploit contact forces in a safe and proficient manner. Impedance control is considered as a prominent approach in robotics to avoid large impact forces while operating in unstructured environments. In such environments,

A. R. Kuzmak, V. M. Tkachuk

We study the entanglement between a certain qubit and the remaining system in rank- 2 mixed states prepared on the quantum computer. The protocol, which we propose for this purpose, is based on the relation of geometric measure of entanglement with correlations between qubits. As a special case, we consider a two-qubit rank-2 mixed state and find the relatio

Ivan Biočić, Zoran Vondraček, Vanja Wagner

We study semilinear problems in general bounded open sets for non-local operators with exterior and boundary conditions. The operators are more general than the fractional Laplacian. We also give results in case of bounded $C^{1,1}$ open sets.

Frédéric Le Roux, Sobhan Seyfaddini

We prove that toric symplectic manifolds admit Hamiltonian pseudo-rotations with a finite, and in a sense minimal, number of ergodic measures. The set of ergodic measures of these pseudo-rotations consists of the measure induced by the symplectic volume form and the Dirac measures supported at the fixed points of the torus action. Our construction relies on

Donald C. Warren, Catherine A. A. Beauchemin, Maxim V. Barkov, Shigehiro Nagataki

Relativistic shocks propagating into a medium with low magnetization are generated and sustained by small-scale but very strong magnetic field turbulence. This so-called "microturbulence" modifies the typical shock acceleration process, and in particular that of electrons. In this work we perform Monte Carlo (MC) simulations of electrons encountering shocks

Shanquan Lan, Hong Liu, Yu Tian, Hongbao Zhang

Consider at a finite temperature $T$ a superfluid moving with a velocity $v$ relative to the thermal bath or its normal component. From Landau's argument there exists a critical $v_c (T)$ beyond which excitations can be spontaneously generated and the system becomes unstable. Identifying the final state induced by such an instability has been an outstanding

Rui Guo, Ivor Simpson, Thor Magnusson, Chris Kiefer

Many of the music generation systems based on neural networks are fully autonomous and do not offer control over the generation process. In this research, we present a controllable music generation system in terms of tonal tension. We incorporate two tonal tension measures based on the Spiral Array Tension theory into a variational autoencoder model. This al

Jonathan Berrisch, Florian Ziel

We examine the problem of modeling and forecasting European Day-Ahead and Month-Ahead natural gas prices. For this, we propose two distinct probabilistic models that can be utilized in risk- and portfolio management. We use daily pricing data ranging from 2011 to 2020. Extensive descriptive data analysis shows that both time series feature heavy tails, condi

Rathindra Nath Das, Sourav Dutta, Archana Maji

In this article, we study the scrambling dynamics in supersymmetric quantum mechanical systems. The eigenstate representation of such supersymmetric systems allows us to present an explicit form of the $2N$-point out-of-time-order correlator (OTOC) using two equivalent formalisms viz. "Tensor Product formalism" and "Partner Hamiltonian formalism". We analyti

Anubhav Garg, Amit Kumar Saha, Debo Dutta

Neural Architecture Search (NAS) is a collection of methods to craft the way neural networks are built. We apply this idea to Federated Learning (FL), wherein predefined neural network models are trained on the client/device data. This approach is not optimal as the model developers can&#39;t observe the local data, and hence, are unable to build highly accu

Felix P. Kemeth, Bernold Fiedler, Sindre W. Haugland, Katharina Krischer

We reduce the dynamics of an ensemble of mean-coupled Stuart-Landau oscillators close to the synchronized solution. In particular, we map the system onto the center manifold of the Benjamin-Feir instability, the bifurcation destabilizing the synchronized oscillation. Using symmetry arguments, we describe the structure of the dynamics on this center manifold

Lin Gao, Tong Wu, Yu-Jie Yuan, Ming-Xian Lin

We introduce TM-NET, a novel deep generative model for synthesizing textured meshes in a part-aware manner. Once trained, the network can generate novel textured meshes from scratch or predict textures for a given 3D mesh, without image guidance. Plausible and diverse textures can be generated for the same mesh part, while texture compatibility between parts

Koar Marntirosian, Tom Schrijvers, Bruno C. d. S. Oliveira, Georgios Karachalias

Resolution and subtyping are two common mechanisms in programming languages. Resolution is used by features such as type classes or Scala-style implicits to synthesize values automatically from contextual type information. Subtyping is commonly used to automatically convert the type of a value into another compatible type. So far the two mechanisms have been

Arijit Manna, Sabyasachi Pal, Mangal Hazra

Amino acids are considered to be prime ingredients in chemistry, leading to life. Glycine is the simplest amino acid and most commonly found in animal proteins. It is a glucogenic and non-essential amino acid that is produced naturally by living bodies and plays a key role in the creation of several other important bio-compounds and proteins. We report the f

Matthew Evanusa, Cornelia Fermüller, Yiannis Aloimonos

Deep Reservoir Computing has emerged as a new paradigm for deep learning, which is based around the reservoir computing principle of maintaining random pools of neurons combined with hierarchical deep learning. The reservoir paradigm reflects and respects the high degree of recurrence in biological brains, and the role that neuronal dynamics play in learning

José Andrés Armario, Ivan Bailera, Ronan Egan

In this paper we study Butson Hadamard matrices, and codes over finite rings coming from these matrices in logarithmic form, called BH-codes. We introduce a new morphism of Butson Hadamard matrices through a generalized Gray map on the matrices in logarithmic form, which is comparable to the morphism given in a recent note of Ó Catháin and Swartz. That is, w

P. Baczyk, W. Satula

Background: Small asymmetry between neutrons and protons, caused by the differences in masses and charges of the up and down constituent quarks leads to the isospin symmetry breaking. The isospin non-conservation affects broad range of observables from superallowed Fermi weak interaction to isospin-forbidden electromagnetic rates. Its most profound and clean

Artūrs Stafanovičs, Toms Bergmanis, Mārcis Pinnis

When translating &#34;The secretary asked for details.&#34; to a language with grammatical gender, it might be necessary to determine the gender of the subject &#34;secretary&#34;. If the sentence does not contain the necessary information, it is not always possible to disambiguate. In such cases, machine translation systems select the most common translatio

He-Liang Huang, Yuxuan Du, Ming Gong, Youwei Zhao

Quantum machine learning is expected to be one of the first practical applications of near-term quantum devices. Pioneer theoretical works suggest that quantum generative adversarial networks (GANs) may exhibit a potential exponential advantage over classical GANs, thus attracting widespread attention. However, it remains elusive whether quantum GANs impleme