March 2020 arXiv papers — page 88

Hirotaka Kobayashi

We consider a sum of the derivatives of Dirichlet $L$-functions over the zeros of Dirichlet $L$-functions. We give an asymptotic formula for the sum.

Shreetam Behera, Debi Prosad Dogra, Malay Kumar Bandyopadhyay, Partha Pratim Roy

Crowd flow describes the elementary group behavior of crowds. Understanding the dynamics behind these movements can help to identify various abnormalities in crowds. However, developing a crowd model describing these flows is a challenging task. In this paper, a physics-based model is proposed to describe the movements in dense crowds. The crowd model is bas

Kazuyuki Sugimura, Massimo Ricotti

In this paper we focus on understanding the physical processes that lead to stable or unstable ionization fronts (I-fronts) observed in simulations of moving black holes (BHs). The front instability may trigger bursts of gas accretion, rendering the BH significantly more luminous than at steady-state. We perform a series of idealized three dimensional radiat

Hernan Martin Hernandez Morales

Lead-rubber seismic isolation bearings (LRB) have been installed in a number of essential and critical structures, like hospitals, universities and bridges, located in earthquake-prone areas. The purpose of using LRB is providing the structure with period lengthening and the capacity of dissipating a considerable amount of earthquake energy to mitigate the e

Mikhail Ermakov

We point out necessary and sufficient conditions of uniform consistency of nonparametric sets of alternatives for widespread nonparametric tests. Nonparametric sets of alternatives can be defined both in terms of distribution function and in terms of density (or signals in the problem of signal detection in Gaussian white noise). In this part of paper such c

Santiago Guzmán-Pro, César Hernández-Cruz

Given a set $F$ of oriented graphs, a graph $G$ is an $F$-graph if it admits an $F$-free orientation. Building on previous work by Bang-Jensen and Urrutia, we propose a master algorithm that determines if a graph admits an $F$-free orientation when $F$ is a subset of the orientations of $P_3$ and the transitive triangle. We extend previous results of Skrien

José C. V. S. Junior, Matheus F. Torquato, Toktam Mahmoodi, Mischa Dohler

Tactile internet applications allow robotic devices to be remotely controlled over a communication medium with an unnoticeable time delay. In a bilateral communication, the acceptable round trip latency is usually in the order of 1ms up to 10ms depending on the application requirements. It is estimated that 70% of the total latency is generated by the commun

Santiago Guzmán-Pro, César Hernández-Cruz

In the homomorphism order of digraphs, a duality pair is an ordered pair of digraphs $(G,H)$ such that for any digraph, $D$, $G\to D$ if and only if $D\not\to H$. The directed path on $k+1$ vertices together with the transitive tournament on $k$ vertices is a classic example of a duality pair. This relation between paths and tournaments implies that a graph

Yunier Bello-Cruz, Oday Hazaimah

In this paper, a conceptual algorithm modifying the forward-backward-half-forward (FBHF) splitting method for solving three operator monotone inclusion problems is investigated. The FBHF splitting method adjusts and improves Tseng's forward-backward-forward (FBF) splitting method when the inclusion problem has a third-part operator that is cocoercive. The FB

Dianqiang Li, Tao Li

We study cooperative output feedback tracking control of stochastic linear heterogeneous leader-following multi-agent systems. Each agent has a continuous-time linear heterogeneous dynamics with incompletely measurable state, and there are additive and multiplicative noises along with information exchange among agents. We propose a set of admissible distribu

Minwoo Chae, Pierpaolo De Blasi, Stephen G. Walker

In this paper, we use the class of Wasserstein metrics to study asymptotic properties of posterior distributions. Our first goal is to provide sufficient conditions for posterior consistency. In addition to the well-known Schwartz's Kullback--Leibler condition on the prior, the true distribution and most probability measures in the support of the prior are r

Xue Yang, Junchi Yan

Arbitrary-oriented object detection has been a building block for rotation sensitive tasks. We first show that the boundary problem suffered in existing dominant regression-based rotation detectors, is caused by angular periodicity or corner ordering, according to the parameterization protocol. We also show that the root cause is that the ideal predictions c

Siran Li

We prove the existence, uniqueness, and $W^{1,2}$-regularity for the solution to the Pfaff system with antisymmetric $L^2$-coefficient matrix in arbitrary dimensions. Hence, we establish the equivalence between the existence of $W^{2,2}$-isometric immersions and the weak solubility of the Gauss--Codazzi--Ricci equations on simply-connected domains. The regul

M. Ablikim, M. N. Achasov, P. Adlarson, S. Ahmed

We search for $J/ψ$ radiative decays into a weakly interacting neutral particle, namely an invisible particle, using the $J/ψ$ produced through the process $ψ(3686)\toπ^+π^-J/ψ$ in a data sample of $(448.1\pm2.9)\times 10^6$ $ψ(3686)$ decays collected by the BESIII detector at BEPCII. No significant signal is observed. Using a modified frequentist method, up

Yecheng Lyu, Xinming Huang, Ziming Zhang

In contrast to the literature where local patterns in 3D point clouds are captured by customized convolutional operators, in this paper we study the problem of how to effectively and efficiently project such point clouds into a 2D image space so that traditional 2D convolutional neural networks (CNNs) such as U-Net can be applied for segmentation. To this en

Mohammad Heydari, Babak Teimourpour

We are living in the data age. Communications over scientific networks creates new opportunities for researchers who aim to discover the hidden pattern in these huge repositories. This study utilizes network science to create collaboration network of Iranian Scientific Institutions. A modularity-based approach applied to find network communities. To reach a

Martin Bauer, Nicolas Charon, Eric Klassen, Alice Le Brigant

This chapter reviews some past and recent developments in shape comparison and analysis of curves based on the computation of intrinsic Riemannian metrics on the space of curves modulo shape-preserving transformations. We summarize the general construction and theoretical properties of quotient elastic metrics for Euclidean as well as non-Euclidean curves be

G R W Quispel, D I McLaren, P H van der Kamp

We present a novel 8-parameter integrable map in $\mathbb{R}^4$. The map is measure-preserving and possesses two functionally independent 2-integrals, as well as a measure-preserving 2-symmetry.

Pongpisit Thanasutives, Ken-ichi Fukui, Masayuki Numao, Boonserm Kijsirikul

In this paper, we propose two modified neural networks based on dual path multi-scale fusion networks (SFANet) and SegNet for accurate and efficient crowd counting. Inspired by SFANet, the first model, which is named M-SFANet, is attached with atrous spatial pyramid pooling (ASPP) and context-aware module (CAN). The encoder of M-SFANet is enhanced with ASPP

Majid Farhadi, Anand Louis, Mohit Singh, Prasad Tetali

Bobkov, Houdr\'e, and the last author [2000] introduced a Poincar\'e-type functional parameter, $\lambda_\infty$, of a graph and related it to connectivity of the graph via Cheeger-type inequalities. A work by the second author, Raghavendra, and Vempala [2013] related the complexity of $\lambda_\infty$ to the so-called small-set expansion (SSE) problem and f

Hau-Wen Huang

Assume that $\mathbb F$ is an algebraically closed field and let $q$ denote a nonzero scalar in $\mathbb F$ that is not a root of unity. The universal Askey--Wilson algebra $\triangle_q$ is a unital associative $\mathbb F$-algebra defined by generators and relations. The generators are $A,B, C$ and the relations state that each of $$ A+\frac{q BC-q^{-1} CB}{

Yanni Li, Bing Liu, Zhi Wang, Jiangtao Cui

Today, we are all threatened by an unprecedented pandemic: COVID-19. How different is it from other coronaviruses? Will it be attenuated or become more virulent? Which animals may be its original host? In this study, we collected and analyzed nearly thirty thousand publicly available complete genome sequences for COVID-19 virus from 79 different countries, t

Yulin Cai

For a fixed singular modulus $\alpha$, we give an effective lower bound of norm of $x-\alpha$ for another singular modulus $x$ with large discriminant. We then generalize this result for $\Phi_m(x,\alpha)$, where $\Phi_m(X,Y) \in \Z[X,Y]$ is the $m$-th modular polynomial.

Alexander L. Gavrilyuk, Akihiro Munemasa, Yoshio Sano, Tetsuji Taniguchi

In this paper, we show that every connected signed graph with smallest eigenvalue strictly greater than $-2$ and large enough minimum degree is switching equivalent to a complete graph. This is a signed analogue of a theorem of Hoffman. The proof is based on what we call Hoffman's limit theorem which we formulate for Hermitian matrices, and also the extensio

Hau-Wen Huang

Assume that $\mathbb F$ is an algebraically closed field and let $q$ denote a nonzero scalar in $\mathbb F$ that is not a root of unity. The universal DAHA (double affine Hecke algebra) $\mathfrak H_q$ of type $(C_1^\vee,C_1)$ is a unital associative $\mathbb F$-algebra defined by generators and relations. The generators are $\{t_i^{\pm 1}\}_{i=0}^3$ and the

Katarzyna Biesialska, Magdalena Biesialska, Henryk Rybinski

In natural language the intended meaning of a word or phrase is often implicit and depends on the context. In this work, we propose a simple yet effective method for sentiment analysis using contextual embeddings and a self-attention mechanism. The experimental results for three languages, including morphologically rich Polish and German, show that our model

Yuki Hino, Hisao Hayakawa

We investigate a heat engine under an adiabatic (Thouless) pumping process. In this process, the extracted work and lower bound on dissipated availability are characterized by a vector potential and a Riemannian metric tensor, respectively. We derive a trade-off relation between the power and effective efficiency. We also explicitly calculate the trade-off r

J. Hernandez-Sanchez, C. G. Honorato, S. Moretti, S. Rosado-Navarro

We analyse the production of a light charged Higgs boson at the Large Hadron Collider (LHC) via the quark-fusion mechanism $c \bar{b} \to H^- $ considering the decay channel $H^- \to τ\bar ν_τ$ in the final state. We study this process in the framework of the 2-Higgs Doublet Model Type III (2HDM-III) which assumes a four-zero texture in the Yukawa matrices a

Ryan A. Davis, W. A. Angermeier, R. Hermsmeier, Thomas G. White

We perform nonadiabatic simulations of warm dense aluminum based on the electron-force field (EFF) variant of wave-packet molecular dynamics. Comparison of the static ion-ion structure factor with density functional theory (DFT) is used to validate the technique across a range of temperatures and densities spanning the warm dense matter regime. Focusing on a

Y. Jiang, M. P. Nielsen, A. J. Baldacchino, M. A. Green

The economic value of a photovoltaic installation depends upon both its lifetime and power conversion efficiency. Progress towards the latter includes mechanisms to circumvent the Shockley- Queisser limit, such as tandem designs and multiple exciton generation (MEG). Here we explain how both silicon tandem and MEG enhanced silicon cell architectures result i

Naoto Kan, Shun'ya Mizoguchi, Taro Tani

We consider resolutions of codimension-two enhanced singularities from $SO(12)$ to $E_7$ and from $E_7$ to $E_8$ in six-dimensional F-theory, where a half-hypermultiplet arises for generic complex structures achieving them. The exceptional fibers at the enhanced point exhibit different structures depending on how the colliding 7-brane approaches the stack of

Maxwell I. Nye, Armando Solar-Lezama, Joshua B. Tenenbaum, Brenden M. Lake

Many aspects of human reasoning, including language, require learning rules from very little data. Humans can do this, often learning systematic rules from very few examples, and combining these rules to form compositional rule-based systems. Current neural architectures, on the other hand, often fail to generalize in a compositional manner, especially when

Zhizhong Han, Guanhui Qiao, Yu-Shen Liu, Matthias Zwicker

Structure learning for 3D shapes is vital for 3D computer vision. State-of-the-art methods show promising results by representing shapes using implicit functions in 3D that are learned using discriminative neural networks. However, learning implicit functions requires dense and irregular sampling in 3D space, which also makes the sampling methods affect the

Osman Gulseven

This article investigates the effect of prices and socio-demographic variables on the farmers decision to purchase agricultural insurance. A survey has been conducted to 200 farmers most of whom are engaged in diversified income-generating activities. The logistic estimation results suggest that education and household income from farming activities positive

Baliram Lone

First principles based DFT calculations performed to insight structural and electronic properties of Boron doped Magnesium atom decorated graphene sheet for application of hydrogen storage. The four H2 molecules stably binds magnesium atom with Boron doped graphene sheet. The average binding energy extracted in the range-0.566 to -0.687 eV/H2.Partial density

Waleed Al-Qallaf, Kyriakos Papadopoulos

We give an exact mathematical construction of a spacelike order $<$, which is dual to the standard chronological order $\ll$ in the $n$-dimensional Minkowski space $M^n$, and we discuss its order-theoretic, geometrical as well as its topological implications, conjecturing a possible extension to curved spacetimes.

Izhak Shafran, Nan Du, Linh Tran, Amanda Perry

There is a growing interest in creating tools to assist in clinical note generation using the audio of provider-patient encounters. Motivated by this goal and with the help of providers and medical scribes, we developed an annotation scheme to extract relevant clinical concepts. We used this annotation scheme to label a corpus of about 6k clinical encounters

Haiyan Yin, Dingcheng Li, Xu Li, Ping Li

Training generative models that can generate high-quality text with sufficient diversity is an important open problem for Natural Language Generation (NLG) community. Recently, generative adversarial models have been applied extensively on text generation tasks, where the adversarially trained generators alleviate the exposure bias experienced by conventiona

Kamran Ali, Mohammed Alloulah, Fahim Kawsar, Alex X. Liu

WiFi channel state information (CSI) has emerged as a plausible modality for sensing different human vital signs, i.e. respiration and body motion, as a function of modulated wireless signals that travel between WiFi devices. Although a remarkable proposition, most of the existing research in this space struggles to withstand robust performance beyond experi

Christina Khalil, Ioanna Rapti, Fernando Lopez-caballero

The major cause of earthquake damage to an embankment is the liquefaction of the soil foundation that induces ground level deformations. It is well known that the liquefaction appears when the soil loses its shear strength due to the excess of pore water pressure. This phenomenon leads to several disastrous damages of the soil foundation. The aim of this pap

James Daniel Whitfield

Quantum technology is seeing a remarkable explosion in interest due to a wave of successful commercial technology. As a wider array of engineers and scientists are needed, it is time we rethink quantum educational paradigms. Current approaches often start from classical physics, linear algebra, or differential equations. This chapter advocates for beginning

Natasa Sarafijanovic-Djukic, Jesse Davis

The goal of anomaly detection is to identify examples that deviate from normal or expected behavior. We tackle this problem for images. We consider a two-phase approach. First, using normal examples, a convolutional autoencoder (CAE) is trained to extract a low-dimensional representation of the images. Here, we propose a novel architectural choice when desig

Selim Ickin, Markus Fiedler, Konstantinos Vandikas

The development of QoE models by means of Machine Learning (ML) is challenging, amongst others due to small-size datasets, lack of diversity in user profiles in the source domain, and too much diversity in the target domains of QoE models. Furthermore, datasets can be hard to share between research entities, as the machine learning models and the collected u

Chengcheng Jia, Bo Wu, Xiao-Ping Zhang

Dynamic spatial graph construction is a challenge in graph neural network (GNN) for time series data problems. Although some adaptive graphs are conceivable, only a 2D graph is embedded in the network to reflect the current spatial relation, regardless of all the previous situations. In this work, we generate a spatial tensor graph (STG) to collect all the d

Steffen Wiewel, Byungsoo Kim, Vinicius C. Azevedo, Barbara Solenthaler

We propose an end-to-end trained neural networkarchitecture to robustly predict the complex dynamics of fluid flows with high temporal stability. We focus on single-phase smoke simulations in 2D and 3D based on the incompressible Navier-Stokes (NS) equations, which are relevant for a wide range of practical problems. To achieve stable predictions for long-te

Thazin Aye, Jian Fang, Yingli Pan

Starting from an age-structured diffusive population growth law for single species in a discrete and periodic habitat, we formulate a stage structured population model with spatially periodic dispersal, mortality and recruitment. With a KPP type setting, after establishing the fundamental solution of a discretized heat equation with spatially periodic disper

Ehsan Variani, David Rybach, Cyril Allauzen, Michael Riley

This paper proposes and evaluates the hybrid autoregressive transducer (HAT) model, a time-synchronous encoderdecoder model that preserves the modularity of conventional automatic speech recognition systems. The HAT model provides a way to measure the quality of the internal language model that can be used to decide whether inference with an external languag

Hsu-Yung Cheng, Ping-Huan Kuo, Yamin Shen, Chiou-Jye Huang

In the modern power market, electricity trading is an extremely competitive industry. More accurate price forecast is crucial to help electricity producers and traders make better decisions. In this paper, a novel method of convolutional neural network (CNN) is proposed to rapidly provide hourly forecasting in the energy market. To improve prediction accurac

Osman Gulseven, Michael Wohlgenant

This article introduces the Hedonic Metric (HM) approach as an original method to model the demand for differentiated products. Using this approach, initially, we create an n-dimensional hedonic space based on the characteristic information available to consumers. Next, we allocate products into this space and estimate the elasticities using distances. Our m

M. Naya-Varela, A. Faina, R. J. Duro

Morphological development is part of the way any human or animal learns. The learning processes starts with the morphology at birth and progresses through changing morphologies until adulthood is reached. Biologically, this seems to facilitate learning and make it more robust. However, when this approach is transferred to robotic systems, the results found i

Monowar Hasan, Sibin Mohan, Takayuki Shimizu, Hongsheng Lu

Modern vehicular wireless technology enables vehicles to exchange information at any time, from any place, to any network -- forms the vehicle-to-everything (V2X) communication platforms. Despite benefits, V2X applications also face great challenges to security and privacy -- a very valid concern since breaches are not uncommon in automotive communication ne

Garret Sobczyk

Perhaps the most significant, if not the most important, achievements in chemistry and physics are the Periodic Table of the Elements in Chemistry and the Standard Model of Elementary Particles in Physics. A comparable achievement in mathematics is the Periodic Table of Geometric Numbers discussed here. In 1878 William Kingdon Clifford discovered the definin

Sérgio N. Silva, Felipe F. Lopes, Carlos Valderrama, Marcelo A. C. Fernandes

This work proposes dedicated hardware for an intelligent control system on Field Programmable Gate Array (FPGA). The intelligent system is represented as Takagi-Sugeno Fuzzy-PI controller. The implementation uses a fully parallel strategy associated with a hybrid bit format scheme (fixed-point and other floating-point). Two hardware designs are proposed; the

Korupalli V Rajesh Kumar, Susan Elias

Human neck postures and movements need to be monitored, measured, quantified and analyzed, as a preventive measure in healthcare applications. Improper neck postures are an increasing source of neck musculoskeletal disorders, requiring therapy and rehabilitation. The motivation for the research presented in this paper was the need to develop a notification m

Pai-Yu Tan, Po-Yao Chuang, Yen-Ting Lin, Cheng-Wen Wu

Neural network hardware is considered an essential part of future edge devices. In this paper, we propose a binary-weight spiking neural network (BW-SNN) hardware architecture for low-power real-time object classification on edge platforms. This design stores a full neural network on-chip, and hence requires no off-chip bandwidth. The proposed systolic array

R. Yarmukhamedov, K. I. Tursunmakhatov

A new dispersion (asymptotic) theory is proposed for the peripheral sub- and above-barrier charged particle transfer $A(x,y)B$ reaction in the three-body ($A$, $a$ and $y$) model where $ x= y +a$ and $B=A+a$, and $ a$ is a transferred particle. It is based on the combination of the dispersion theory and the conventional DWBA method. The explicit forms have b

Elisa Palezzato, Michele Torielli

In this article, we study the $k$-Lefschetz properties for non-Artinian algebras, proving that several known results in the Artinian case can be generalized in this setting. Moreover, we describe how to characterize the graded algebras having the $k$-Lefschetz properties using sectional matrices. We then apply the obtained results to the study of the Jacobia

Sushil Bhunia, Ayan Mahalanobis, Pralhad Shinde, Anupam Singh

This paper presents some algorithms in linear algebraic groups. These algorithms solve the word problem and compute the spinor norm for orthogonal groups. This gives us an algorithmic definition of the spinor norm. We compute the double coset decomposition with respect to a Siegel maximal parabolic subgroup, which is important in computing infinite-dimension

Claire Autebert, Gaëtan Gras, Emna Amri, Matthieu Perrenoud

One of the key properties of single-photon detectors is their recovery time, i.e. the time required for the detector to recover its nominal efficiency. In the case of superconducting nanowire single-photon detectors (SNSPDs), which can feature extremely short recovery times in free-running mode, a precise characterisation of this recovery time and its time d

B. B. Levchenko

Exact 2D analytic expressions for E and B fields and their potentials created by a linear beam of relativistic charged particles between infinite perfectly conductive plates and ferromagnetic poles are derived. The solutions are obtained by summing an infinite sequence of fields from linear charge-images and current-images in complex space. Knowledge of the

Daniel B. de Freitas

The present work attempts to analytically explain the effects on the moment of inertia, $I$, caused by the evolution of stellar velocity in main-sequence stars. We have found that the effects linked to stellar oblateness can be estimated from the variation of the magnetic braking index denoted by $Δq$. We have also found that the effect of $\dot{I}$ is here

J. F. Jardine

The hierarchy poset and branch point poset for a data set both admit a calculus of least upper bounds. A method involving upper bounds is used to show that the map of branch points associated to the inclusion of data sets is a controlled homotopy equivalence, where the control is expressed by an upper bound relation that is constrained by Hausdorff distance.

Henrik Stenlund

This study handles spatial three-dimensional solution of the nonlinear diffusion equation without particular initial conditions. The functional behavior of the equation and the concentration have been studied in new ways. An auxiliary function for diffusion is given having an interesting relationship with the concentration. A set of new integro-differential

Ufuk Beyaztas, Han Lin Shang

Recent technological developments have enabled us to collect complex and high-dimensional data in many scientific fields, such as population health, meteorology, econometrics, geology, and psychology. It is common to encounter such datasets collected repeatedly over a continuum. Functional data, whose sample elements are functions in the graphical forms of c

Christian Scheller, Yanick Schraner, Manfred Vogel

Sample inefficiency of deep reinforcement learning methods is a major obstacle for their use in real-world applications. In this work, we show how human demonstrations can improve final performance of agents on the Minecraft minigame ObtainDiamond with only 8M frames of environment interaction. We propose a training procedure where policy networks are first

Antonio Di Crescenzo, Barbara Martinucci, Paola Paraggio, Shelemyahu Zacks

We analyze the one-dimensional telegraph random process confined by two boundaries, 0 and $H>0$. The process experiences hard reflection at the boundaries (with random switching to full absorption). Namely, when the process hits the origin (the threshold $H$) it is either absorbed, with probability $α$, or reflected upwards (downwards), with probability $1-α

Aditya Chilukuri, Josh Milthorpe, Beau Johnston

High-performance computing developers are faced with the challenge of optimizing the performance of OpenCL workloads on diverse architectures. The Architecture-Independent Workload Characterization (AIWC) tool is a plugin for the Oclgrind OpenCL simulator that gathers metrics of OpenCL programs that can be used to understand and predict program performance o

Fares J. Abu-Dakka, Ville Kyrki

In many robot control problems, factors such as stiffness and damping matrices and manipulability ellipsoids are naturally represented as symmetric positive definite (SPD) matrices, which capture the specific geometric characteristics of those factors. Typical learned skill models such as dynamic movement primitives (DMPs) can not, however, be directly emplo

Wang Jiaxiang, Wang Xu-jia, Zhou Bin

In this paper, we prove a Moser-Trudinger type inequality for pluri-subharmonic functions vanishing on the boundary. Our proof uses a descent gradient flow for the complex Monge-Ampere functional.

Wang Jiaxiang, Wang Xu-jia, Zhou Bin

In this paper, we prove a Moser-Trudinger type inequality for pluri-subharmonic functions vanishing on the boundary. Our proof uses a descent gradient flow for the complex Monge-Ampere functional.

Kaiyang Zhou, Yongxin Yang, Timothy Hospedales, Tao Xiang

Machine learning models typically suffer from the domain shift problem when trained on a source dataset and evaluated on a target dataset of different distribution. To overcome this problem, domain generalisation (DG) methods aim to leverage data from multiple source domains so that a trained model can generalise to unseen domains. In this paper, we propose

Chen Ling, Guangmo Tong, Mozi Chen

Online discussion forum creates an asynchronous conversation environment for online users to exchange ideas and share opinions through a unique thread-reply communication mode. Accurately modeling information dynamics under such a mode is important, as it provides a means of mining latent spread patterns and understanding user behaviors. In this paper, we de

Mandana Saebi, Steven Krieg, Chuxu Zhang, Meng Jiang

Path-based relational reasoning over knowledge graphs has become increasingly popular due to a variety of downstream applications such as question answering in dialogue systems, fact prediction, and recommender systems. In recent years, reinforcement learning (RL) has provided solutions that are more interpretable and explainable than other deep learning mod

Hermina Petric Maretic, Mireille El Gheche, Matthias Minder, Giovanni Chierchia

We propose a novel method for comparing non-aligned graphs of different sizes, based on the Wasserstein distance between graph signal distributions induced by the respective graph Laplacian matrices. Specifically, we cast a new formulation for the one-to-many graph alignment problem, which aims at matching a node in the smaller graph with one or more nodes i

Chao Wang, Ching Cheng

Turbulent characteristics within shear layer have been studied, recently, within vegetative canopy, buildings, dunes. Kevin-Helmholtz instability triggered hairpin vortex shedding has been widely concluded as the &#34;signature&#34; of mixing layer analogy. However, convoluted roughness types complicate the observing practice of turbulent evolving progress.

I. S. S. Carrasco, T. J. Oliveira

We report on the investigation of height distributions (HDs) and spatial covariances of two-dimensional surfaces obtained from extensive numerical simulations of the celebrated Clarke-Vvedensky (CV) model for homoepitaxial thin film growth. In this model, the effect of temperature, deposition flux, and strengths of atom-atom interactions are encoded in two p

Zehua Zhang, Ashish Tawari, Sujitha Martin, David Crandall

A vehicle driving along the road is surrounded by many objects, but only a small subset of them influence the driver&#39;s decisions and actions. Learning to estimate the importance of each object on the driver&#39;s real-time decision-making may help better understand human driving behavior and lead to more reliable autonomous driving systems. Solving this

Zhigang Dai, Jinhua Fu, Qile Zhu, Hengbin Cui

Dialogue act recognition is a fundamental task for an intelligent dialogue system. Previous work models the whole dialog to predict dialog acts, which may bring the noise from unrelated sentences. In this work, we design a hierarchical model based on self-attention to capture intra-sentence and inter-sentence information. We revise the attention distribution

Peter Varnai, Dimos V. Dimarogonas

Signal temporal logic (STL) is a powerful tool for describing complex behaviors for dynamical systems. Among many approaches, the control problem for systems under STL task constraints is well suited for learning-based solutions, because STL is equipped with robustness metrics that quantify the satisfaction of task specifications and thus serve as useful rew

Sergey M. Zagorodnyuk

In this paper we study modified kernel polynomials: $u_n(x) = \sum_{k=0}^n c_k g_k(x)$, depending on parameters $c_k>0$, where $\{ g_k \}_0^\infty$ are orthonormal polynomials on the real line. Besides kernel polynomials with $c_k = g_k(t_0)>0$, for example, $c_k$ may be chosen to be some other solutions of the corresponding second-order difference equation

Alexandra Larsen, Shu Yang, Brian J. Reich, Ana G. Rappold

Wildland fire smoke contains hazardous levels of fine particulate matter PM2.5, a pollutant shown to adversely effect health. Estimating fire attributable PM2.5 concentrations is key to quantifying the impact on air quality and subsequent health burden. This is a challenging problem since only total PM2.5 is measured at monitoring stations and both fire-attr

O. Poch, I. Istiqomah, E. Quirico, P. Beck

The measured nitrogen-to-carbon ratio in comets is lower than for the Sun, a discrepancy which could be alleviated if there is an unknown reservoir of nitrogen in comets. The nucleus of comet 67P/Churyumov-Gerasimenko exhibits an unidentified broad spectral reflectance feature around 3.2 micrometers, which is ubiquitous across its surface. On the basis of la

H. F. Stevance, D. Baade, J. R. Bruten, A. Cikota

SN 1993J is one of the best studied Type IIb supernovae. Spectropolarimetric data analyses were published over two decades ago at a time when the field of supernova spectropolarimetry was in its infancy. Here we present a new analysis of the spectropolarimetric data of SN 1993J and an improved estimate of its interstellar polarization (ISP) as well as a crit

Duccio Fanelli, Francesco Piazza

In this note we analyze the temporal dynamics of the coronavirus disease 2019 outbreak in China, Italy and France in the time window $22/01-09/03/2020$. A first analysis of simple day-lag maps points to some universality in the epidemic spreading, suggesting that simple mean-field models can be meaningfully used to gather a quantitative picture of the epidem

R. I. Woodward, M. R. Majewski, S. D. Jackson

With growing interest in the mid-infrared spectral region, dysprosium has recently been revisited for efficient high-performance infrared source development. Despite historically receiving less attention than other rare earth ions, in recent years lasers utilizing the dysprosium ion as the laser material have set record mid-infrared performance, including tu

Niladri Das, Raktim Bhattacharya

In this work we propose a framework to address the issue of state dependent nonlinear equality-constrained state estimation using Bayesian filtering. This framework is constructed specifically for a linear approximation of Bayesian filtering that uses the theory of Optimal Transport. As a part of this framework, we present three traditionally-used nonlinear

Martin Larsson, Johannes Ruf

We characterize the event of convergence of a local supermartingale. Conditions are given in terms of its predictable characteristics and quadratic variation. The notion of stationarily local integrability plays a key role.

Carlos M. Correia, Olivier Fauvarque, Charlotte Z. Bond, Vincent Chambouleyron

Advanced AO systems will likely utilise Pyramid wave-front sensors (PWFS) over the traditional Shack-Hartmann sensor in the quest for increased sensitivity, peak performance and ultimate contrast. Here, we wish to bring knowledge and quantify the PWFS theoretical limits as a means to highlight its properties and use cases. We explore forward models for the P

Sourav Patel, Soham Chakraborty, Blake Lundstrom, Srinivasa Salapaka

Advanced microgrids consisting of distributed energy resources interfaced with multi-inverter systems are becoming more common. Consequently, the effectiveness of voltage and frequency regulation in microgrids using conventional droop-based methodologies is challenged by uncertainty in the sizeand schedule of loads. This article proposes an isochronous archi

Boris Khesin, Daniel Peralta-Salas, Cheng Yang

We prove that the helicity is the only regular Casimir function for the coadjoint action of the volume-preserving diffeomorphism group $\text{SDiff}(M)$ on smooth exact divergence-free vector fields on a closed three-dimensional manifold $M$. More precisely, any regular $C^1$ functional defined on the space of $C^\infty$ (more generally, $C^k$, $k\ge 4$) exa

Vikram Sreekanti, Chenggang Wu, Saurav Chhatrapati, Joseph E. Gonzalez

Serverless computing has grown in popularity in recent years, with an increasing number of applications being built on Functions-as-a-Service (FaaS) platforms. By default, FaaS platforms support retry-based fault tolerance, but this is insufficient for programs that modify shared state, as they can unwittingly persist partial sets of updates in case of failu

Karthikeyan Natesan Ramamurthy, Bhanukiran Vinzamuri, Yunfeng Zhang, Amit Dhurandhar

In recent years, post-hoc local instance-level and global dataset-level explainability of black-box models has received a lot of attention. Much less attention has been given to obtaining insights at intermediate or group levels, which is a need outlined in recent works that study the challenges in realizing the guidelines in the General Data Protection Regu

Martin Schwald

In the definition of irreducible holomorphic symplectic manifolds the condition of being simply connected can be replaced by vanishing irregularity. We discuss finite quotients X of complex tori where the space of reflexive 2-forms is generated by a holomorphic symplectic form, and their Lagrangian fibrations. Neither X nor the base can be smooth unless X is

Niladri Das, Raktim Bhattacharya

We consider the problem of selecting an optimal set of sensor precisions to estimate the states of a non-linear dynamical system using an Ensemble Kalman filter and an Unscented Kalman filter, which uses random and deterministic ensembles respectively. Specifically, the goal is to choose at run-time, a sparse set of sensor precisions for active-sensing that

Martin Ondrejat, Andreas Prohl, Noel Walkington

The numerical analysis of stochastic parabolic partial differential equations of the form $$ du + A(u) = f \,dt + g \, dW, $$ is surveyed, where $A$ is a partial operator and $W$ a Brownian motion. This manuscript unifies much of the theory developed over the last decade into a cohesive framework which integrates techniques for the approximation of determini

Wei Yang, Chris Paxton, Maya Cakmak, Dieter Fox

Transfer of objects between humans and robots is a critical capability for collaborative robots. Although there has been a recent surge of interest in human-robot handovers, most prior research focus on robot-to-human handovers. Further, work on the equally critical human-to-robot handovers often assumes humans can place the object in the robot&#39;s gripper

A. Feldmeier-Krause, W. Kerzendorf, T. Do, F. Nogueras-Lara

We present stellar metallicity measurements of more than 600 late-type stars in the central 10 pc of the Galactic centre. Together with our previously published KMOS data, this data set allows us to investigate, for the first time, spatial variations of the nuclear star cluster&#39;s metallicity distribution. Using the integral-field spectrograph KMOS (VLT)

Francisco J. Chiyah Garcia, José Lopes, Xingkun Liu, Helen Hastie

Large corpora of task-based and open-domain conversational dialogues are hugely valuable in the field of data-driven dialogue systems. Crowdsourcing platforms, such as Amazon Mechanical Turk, have been an effective method for collecting such large amounts of data. However, difficulties arise when task-based dialogues require expert domain knowledge or rapid

Kenan Šehić, Mirza Karamehmedović

We here consider the subset simulation method which approaches a failure event using a decreasing sequence of nested intermediate failure events. The method resembles importance sampling, which actively explores a probability space by conditioning the next evaluation on the previous evaluations using a Markov chain Monte Carlo (MCMC) algorithm. A Markov chai

Erik Wijmans, Julian Straub, Dhruv Batra, Irfan Essa

Recent advances in deep reinforcement learning require a large amount of training data and generally result in representations that are often over specialized to the target task. In this work, we present a methodology to study the underlying potential causes for this specialization. We use the recently proposed projection weighted Canonical Correlation Analy