October 2020 arXiv papers — page 3

Paul Manns

Multibang regularization and combinatorial integral approximation decompositions are two actively researched techniques for integer optimal control. We consider a class of polyhedral functions that arise particularly as convex lower envelopes of multibang regularizers and show that they have beneficial properties with respect to regularization of relaxations

Leyang Bo, Yuguang Shi

In this paper, we consider the problem of nonnegative scalar curvature (NNSC) cobordism of Bartnik data $(\Sigma_1^{n-1}, \gamma_1, H_1)$ and $(\Sigma_2^{n-1}, \gamma_2, H_2)$. We prove that given two metrics $\gamma_1$ and $\gamma_2$ on $S^{n-1}$ ($3\le n\le 7$) with $H_1$ fixed, then $(S^{n-1}, \gamma_1, H_1)$ and $(S^{n-1}, \gamma_2, H_2)$ admit no NNSC c

Junyuan Gao, Yongpeng Wu, Yongjian Wang, Wenjun Zhang

In cell-free massive multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems, user equipments (UEs) are served by many distributed access points (APs), where channels are correlated due to finite angle-delay spread in realistic outdoor wireless propagation environments. Meanwhile, the number of UEs is growing rapidly f

Ryota Kotani, Soichi Yokoyama, Shunpei Nobusue, Shigehiro Yamaguchi

Understanding the transmission of nanoscale forces in the pico-to-nanonewton range is important in polymer physics. While physical approaches have limitations in analyzing the local force distribution in condensed environments, chemical analysis using force probes is promising. However, there are stringent requirements for probing the local forces generated

Kengo Terai

This paper is concerned with the asymptotic analysis of infinite systems of weakly coupled stationary Hamilton-Jacobi-Bellman equations as the discount factor tends to zero. With a specific Hamiltonian, we show the convergence of the solution and prove the solvability of the corresponding ergodic problem.

Xu Xiang

This report describes the systems submitted to the first and second tracks of the VoxCeleb Speaker Recognition Challenge (VoxSRC) 2020, which ranked second in both tracks. Three key points of the system pipeline are explored: (1) investigating multiple CNN architectures including ResNet, Res2Net and dual path network (DPN) to extract the x-vectors, (2) using

Longwen Zhou, Qianqian Du

Dynamical quantum phase transitions (DQPTs) are characterized by nonanalytic behaviors of physical observables as functions of time. When a system is subject to time-periodic modulations, the nonanalytic signatures of its observables could recur periodically in time, leading to the phenomena of Floquet DQPTs. In this work, we systematically explore Floquet D

Behnam Pourhassan, Mir Faizal

In this paper we study the thermodynamics of black branes at quantum scales. We analyze both perturbative and non-perturbative corrections to the thermodynamics of such black branes. It will be observed that these corrections will modify the relation between the entropy and area of these black branes. This will in turn modify their specific heat, and thus th

Jingzhen Hu, Qingzhong Liang, Narayanan Rengaswamy, Robert Calderbank

Physical platforms such as trapped ions suffer from coherent noise where errors manifest as rotations about a particular axis and can accumulate over time. We investigate passive mitigation through decoherence free subspaces, requiring the noise to preserve the code space of a stabilizer code, and to act as the logical identity operator on the protected info

Siddhartha Gairola, Francis Tom, Nipun Kwatra, Mohit Jain

Auscultation of respiratory sounds is the primary tool for screening and diagnosing lung diseases. Automated analysis, coupled with digital stethoscopes, can play a crucial role in enabling tele-screening of fatal lung diseases. Deep neural networks (DNNs) have shown a lot of promise for such problems, and are an obvious choice. However, DNNs are extremely d

Wenyu Xing, Yang Ma, Yunyan Yao, Ranran Cai

Magnon-polarons are coherently mixed quasiparticles that originate from the strong magnetoelastic coupling of lattice vibrations and spin waves in magnetic-ordered materials. Recently, magnon-polarons have attracted a lot of attention since they provide a powerful tool to manipulate magnons, which is essential for magnon-based spintronic devices. In this wor

Ali Lotfi Rezaabad, Rahi Kalantari, Sriram Vishwanath, Mingyuan Zhou

Efficient modeling of relational data arising in physical, social, and information sciences is challenging due to complicated dependencies within the data. In this work, we build off of semi-implicit graph variational auto-encoders to capture higher-order statistics in a low-dimensional graph latent representation. We incorporate hyperbolic geometry in the l

Hiroyuki Yamase, Matías Bejas, Andrés Greco

Employing a large-N scheme of the layered t-J model with the long-range Coulomb interaction, which captures fine details of the charge excitation spectra recently observed in cuprate superconductors, we explore the role of the charge fluctuations on the electron self-energy. We fix temperature at zero and focus on quantum charge fluctuations. We find a prono

Haochen Liu, Zitao Liu, Zhongqin Wu, Jiliang Tang

The automatic evaluation for school assignments is an important application of AI in the education field. In this work, we focus on the task of personalized multimodal feedback generation, which aims to generate personalized feedback for various teachers to evaluate students' assignments involving multimodal inputs such as images, audios, and texts. This tas

Hancheng Cao, Zhilong Chen, Mengjie Cheng, Shuling Zhao

As an emerging business phenomenon especially in China, instant messaging (IM) based social commerce is growing increasingly popular, attracting hundreds of millions of users and is becoming one important way where people make everyday purchases. Such platforms embed shopping experiences within IM apps, e.g., WeChat, WhatsApp, where real-world friends post a

Duan-Shin Lee, Miao Zhu

In this paper, we present a susceptible-infected-recovered (SIR) model with individuals wearing facial masks and individuals who do not. The disease transmission rates, the recovering rates and the fraction of individuals who wear masks are all time dependent in the model. We develop a progressive estimation of the disease transmission rates and the recoveri

Gaofeng Huang, Amir H. Jafari

Generative adversarial networks (GANs) are one of the most powerful generative models, but always require a large and balanced dataset to train. Traditional GANs are not applicable to generate minority-class images in a highly imbalanced dataset. Balancing GAN (BAGAN) is proposed to mitigate this problem, but it is unstable when images in different classes l

Sagarika Nayak, Palash Kumar Manna, Braj Bhusan Singh, Subhankar Bedanta

Exchange bias in ferromagnetic/antiferromagnetic systems can be explained in terms of various interfacial phenomena. Among these spin glass frustration can affect the magnetic properties in exchange bias systems. Here we have studied a NiMn/CoFeB exchange bias system in which spin glass frustration seems to play a crucial role. In order to account the effect

Bingxu Li, Fanyong Cheng, Xin Zhang, Can Cui

In practical chiller systems, applying efficient fault diagnosis techniques can significantly reduce energy consumption and improve energy efficiency of buildings. The success of the existing methods for fault diagnosis of chillers relies on the condition that sufficient labeled data are available for training. However, label acquisition is laborious and cos

Chen Wei, Yiping Tang, Chuang Niu, Haihong Hu

Recently proposed neural architecture search (NAS) algorithms adopt neural predictors to accelerate the architecture search. The capability of neural predictors to accurately predict the performance metrics of neural architecture is critical to NAS, and the acquisition of training datasets for neural predictors is time-consuming. How to obtain a neural predi

M. D. E. Denys, P. M. R. Brydon

We consider the origin of the anomalous Hall effect in a general model of a clean two-band chiral superconductor. Within the Kubo formalism we derive an analytic expression for the high-frequency ac Hall conductivity valid close to the critical temperature. This expression involves two distinct gauge-invariant time-reversal-odd bilinear (TROB) functions invo

Renshu Gu, Gaoang Wang, Jenq-Neng Hwang

3D human pose estimation (HPE) is crucial in many fields, such as human behavior analysis, augmented reality/virtual reality (AR/VR) applications, and self-driving industry. Videos that contain multiple potentially occluded people captured from freely moving monocular cameras are very common in real-world scenarios, while 3D HPE for such scenarios is quite c

Shuo Kong, Volker Ossenkopf-Okada, Héctor G. Arce, John Bally

A unique filament is identified in the {\it Herschel} maps of the Orion A giant molecular cloud. The filament, which, we name the Stick, is ruler-straight and at an early evolutionary stage. Transverse position-velocity diagrams show two velocity components closing in on the Stick. The filament shows consecutive rings/forks in C$^{18}$O(1-0) channel maps, wh

Lin Zheng

In the context of texture segmentation in images, and provide some theoretical guarantees for the prototypical approach which consists in extracting local features in the neighborhood of a pixel and then applying a clustering algorithm for grouping the pixel according to these features. On the one hand, for stationary textures, which we model with Gaussian M

Asma Azizi, Anamika Mubayi, Anuj Mubayi

College-aged students are one of the most vulnerable populations to high-risk alcohol drinking behaviors that could cause them consequences such as injury or sexual assault. An important factor that may influence college students' decision on alcohol drinking behavior is socializing at certain contexts across university environment. The present study aims to

Ravindra Kumar Yadav, Wenxiao Liu, Ran Li, Teri W. Odom

Single photon sources (SPS), especially those based on solid state quantum emitters, are key elements in future quantum technologies. What is required is the development of broadband, high quantum efficiency, room temperature SPS which can also be tunably coupled to optical cavities which could lead to development of all-optical quantum communication platfor

Héctor Cancela, Gustavo Guerberoff, Franco Robledo, Pablo Romero

The operation of a system, such as a vehicle, communication network or automatic process, heavily depends on the correct operation of its components. A Stochastic Binary System (SBS) mathematically models the behavior of on-off systems, where the components are subject to probabilistic failures. Our goal is to understand the reliability of the global system.

Monika Kodrycka, Konrad Patkowski

The leading-order dispersion and exchange-dispersion terms in symmetry-adapted perturbation theory (SAPT), $E^{(20)}_{\rm disp}$ and $E^{(20)}_{\rm exch-disp}$, suffer from slow convergence to the complete basis set limit. To alleviate this problem, explicitly correlated variants of these corrections, $E^{(20)}_{\rm disp}$-F12 and $E^{(20)}_{\rm exch-disp}$-

I-Kun Chen, Ping-Han Chuang, Chun-Hsiung Hsia, Jhe-Kuan Su

In the present work, we adopt the idea of velocity averaging lemma to establish regularity for stationary linearized Boltzmann equations in a bounded convex domain. Considering the incoming data, with three iterations, we establish regularity in fractional Sobolev space in space variable up to order $1^-$.

Shuman Peng, Weilian Song, Martin Ester

The goal of few-shot classification is to learn a model that can classify novel classes using only a few training examples. Despite the promising results shown by existing meta-learning algorithms in solving the few-shot classification problem, there still remains an important challenge: how to generalize to unseen domains while meta-learning on multiple see

Guangyao Chen, Limeng Qiao, Yemin Shi, Peixi Peng

Open set recognition is an emerging research area that aims to simultaneously classify samples from predefined classes and identify the rest as 'unknown'. In this process, one of the key challenges is to reduce the risk of generalizing the inherent characteristics of numerous unknown samples learned from a small amount of known data. In this paper, we propos

Maoqiang Wu, Xinyue Zhang, Jiahao Ding, Hien Nguyen

Deep learning has attracted broad interest in healthcare and medical communities. However, there has been little research into the privacy issues created by deep networks trained for medical applications. Recently developed inference attack algorithms indicate that images and text records can be reconstructed by malicious parties that have the ability to que

Guang Hua, Qingyi Wang, Dengpan Ye, Haijian Zhang

Power system frequency could be captured by digital recordings and extracted to compare with a reference database for forensic time-stamp verification. It is known as the electric network frequency (ENF) criterion, enabled by the properties of random fluctuation and intra-grid consistency. In essence, this is a task of matching a short random sequence within

Jisheng Bai, Jianfeng Chen, Mou Wang

Noise pollution significantly affects our daily life and urban development. Urban Sound Tagging (UST) has attracted much attention recently, which aims to analyze and monitor urban noise pollution. One weakness of the previous UST studies is that the spatial and temporal context of sound signals, which contains complementary information about when and where

Ryusuke Sagawa, Yusuke Higuchi, Hiroshi Kawasaki, Ryo Furukawa

This paper proposes a method of estimating micro-motion of an object at each pixel that is too small to detect under a common setup of camera and illumination. The method introduces an active-lighting approach to make the motion visually detectable. The approach is based on speckle pattern, which is produced by the mutual interference of laser light on objec

David Garofalo, Katie Bishop

Recent work on red and blue quasi-stellar objects (QSOs) has identified peculiar number distributions as a function of radio loudness that we explore and attempt to explain from the perspective of a picture in which a subset of the population of active galaxies evolves from the radio loud to the radio quiet state. Because the time evolution is slowed down by

Md Tanzil Shahriar, Huyue Li

Quality of image always plays a vital role in in-creasing object recognition or classification rate. A good quality image gives better recognition or classification rate than any unprocessed noisy images. It is more difficult to extract features from such unprocessed images which in-turn reduces object recognition or classification rate. To overcome problems

Xuan Kien Phung

Let $G$ be a countable monoid and let $A$ be an Artinian group (resp. an Artinian module). Let $\Sigma \subset A^G$ be a closed subshift which is also a subgroup (resp. a submodule) of $A^G$. Suppose that $\Gamma$ is a finitely generated monoid consisting of pairwise commuting cellular automata $\Sigma \to \Sigma$ that are also homomorphisms of groups (resp.

Tian-Xiao He

For an integer $p\geq 2$ we construct vertical and horizontal one-pth Riordan arrays from a Riordan array. When $p=2$, one-pth Riordan arrays reduced to well known half Riordan arrays. The generating functions of the $A$-sequences of vertical and horizontal one-pth Riordan arrays are found. The vertical and horizontal one-pth Riordan arrays provide an approa

Pinyan Lu, Xuandi Ren, Enze Sun, Yubo Zhang

Generalized sorting problem, also known as sorting with forbidden comparisons, was first introduced by Huang et al. together with a randomized algorithm which requires $\tilde O(n^{3/2})$ probes. We study this problem with additional predictions for all pairs of allowed comparisons as input. We propose a randomized algorithm which uses $O(n \log n+w)$ probes

Zhaowei She, Zilong Wang, Turgay Ayer, Asmae Toumi

Rapid and accurate detection of community outbreaks is critical to address the threat of resurgent waves of COVID-19. A practical challenge in outbreak detection is balancing accuracy vs. speed. In particular, while estimation accuracy improves with longer fitting windows, speed degrades. This paper presents a machine learning framework to balance this trade

Niket Tandon, Keisuke Sakaguchi, Bhavana Dalvi Mishra, Dheeraj Rajagopal

We present the first dataset for tracking state changes in procedural text from arbitrary domains by using an unrestricted (open) vocabulary. For example, in a text describing fog removal using potatoes, a car window may transition between being foggy, sticky,opaque, and clear. Previous formulations of this task provide the text and entities involved,and ask

R. Luo, B. J. Wang, Y. P. Men, C. F. Zhang

Fast radio bursts (FRBs) are millisecond-duration radio transients of unknown origin. Two possible mechanisms that could generate extremely coherent emission from FRBs invoke neutron star magnetospheres or relativistic shocks far from the central energy source. Detailed polarization observations may help us to understand the emission mechanism. However, the

Shamiul Alam, Md Shafayat Hossain, Ahmedullah Aziz

The interplay between ferromagnetism and topological properties of electronic band structures leads to a precise quantization of Hall resistance without any external magnetic field. This so-called quantum anomalous Hall effect (QAHE) is born out of topological correlations, and is oblivious of low-sample quality. It was envisioned to lead towards dissipation

Hu Xu, Lei Shu, Philip S. Yu, Bing Liu

This paper analyzes the pre-trained hidden representations learned from reviews on BERT for tasks in aspect-based sentiment analysis (ABSA). Our work is motivated by the recent progress in BERT-based language models for ABSA. However, it is not clear how the general proxy task of (masked) language model trained on unlabeled corpus without annotations of aspe

Aniruddha Tamhane, Jie Ying Wu, Mathias Unberath

Self-supervised, multi-modal learning has been successful in holistic representation of complex scenarios. This can be useful to consolidate information from multiple modalities which have multiple, versatile uses. Its application in surgical robotics can lead to simultaneously developing a generalised machine understanding of the surgical process and reduce

Kirsti Pajunen, Paolo Celli, Chiara Daraio

In this letter, we provide experimental evidence of bandgap tunability with global prestrain in additively-manufactured tensegrity-inspired lattice structures. These lattices are extremely lightweight and designed to exhibit a nonlinear compressive response that mimics that of a tensegrity structure. We fabricate them out of a stiff polymer but, owing to the

E. V. Sokolov

Let $G$ be a generalized Baumslag-Solitar group and $\mathcal{C}$ be a class of groups containing at least one non-unit group and closed under taking subgroups, extensions, and Cartesian products of the form $\prod_{y \in Y}X_{y}$, where $X, Y \in \mathcal{C}$ and $X_{y}$ is an isomorphic copy of $X$ for every $y \in Y$. We give a criterion for $G$ to be res

Esmaeil Seraj, Xiyang Wu, Matthew Gombolay

The purpose of this tutorial is to help individuals use the \underline{FireCommander} game environment for research applications. The FireCommander is an interactive, probabilistic joint perception-action reconnaissance environment in which a composite team of agents (e.g., robots) cooperate to fight dynamic, propagating firespots (e.g., targets). In FireCom

Yu Qi, Zhaolan Zheng

Neural network realizes multi-parameter optimization and control by simulating certain mechanisms of the human brain. It can be used in many fields such as signal processing, intelligent driving, optimal combination, vehicle abnormality detection, and chemical process optimization control. Supercritical extraction is a new type of high-efficiency chemical se

Tao Xu, Fanhua Shang, Yuanyuan Liu, Hongying Liu

In this paper, we study efficient differentially private alternating direction methods of multipliers (ADMM) via gradient perturbation for many machine learning problems. For smooth convex loss functions with (non)-smooth regularization, we propose the first differentially private ADMM (DP-ADMM) algorithm with performance guarantee of $(\epsilon,\delta)$-dif

Martin R. Vasilev, Fabrice B. R. Parmentier, Julie A. Kirkby

Novel or unexpected sounds that deviate from an otherwise repetitive sequence of the same sound cause behavioural distraction. Recent work has suggested that distraction also occurs during reading as fixation durations increased when a deviant sound was presented at the fixation onset of words. The present study tested the hypothesis that this increase in fi

Huibin Chang, Roland Glowinski, Stefano Marchesini, Xue-cheng Tai

In ptychography experiments, redundant scanning is usually required to guarantee the stable recovery, such that a huge amount of frames are generated, and thus it poses a great demand of parallel computing in order to solve this large-scale inverse problem. In this paper, we propose the overlapping Domain Decomposition Methods(DDMs) to solve the nonconvex op

Jing-Yang You, Bo Gu, Gang Su

Honeycomb or triangular lattices were extensively studied and thought to be proper platforms for realizing quantum anomalous Hall effect (QAHE), where magnetism is usually caused by d orbitals of transition metals. Here we propose that square lattice can host three magnetic topological states, including the fully spin polarized nodal loop semimetal, QAHE and

Jinghang Lin, Xiaoxi Shen, Qing Lu

Neural networks are becoming an increasingly important tool in applications. However, neural networks are not widely used in statistical genetics. In this paper, we propose a new neural networks method called expectile neural networks. When the size of parameter is too large, the standard maximum likelihood procedures may not work. We use sieve method to con

Gustavo Z. Felipe, Jacqueline N. Zanoni, Camila C. Sehaber-Sierakowski, Gleison D. P. Bossolani

Studies recently accomplished on the Enteric Nervous System have shown that chronic degenerative diseases affect the Enteric Glial Cells (EGC) and, thus, the development of recognition methods able to identify whether or not the EGC are affected by these type of diseases may be helpful in its diagnoses. In this work, we propose the use of pattern recognition

Shiva Chidambaram

It is known that any Galois representation $\rho : G_{\mathbb{Q}} \rightarrow \mathrm{GL}(2,\mathbb{F}_p)$ with determinant equal to the mod-$p$ cyclotomic character, arises from the $p$-torsion of an elliptic curve over $\mathbb{Q}$, if and only if $p \leq 5$. In dimension $g = 2$, when $p \le 3$, it is again known that any Galois representation valued in $

H. Kurokawa, B. L. Ehlmann, M. C. De Sanctis, M. G. A. Lapôtre

The Visible-Infrared Mapping Spectrometer (VIR) on board the Dawn spacecraft revealed that aqueous secondary minerals -- Mg-phyllosilicates, NH4-bearing phases, and Mg/Ca carbonates -- are ubiquitous on Ceres. Ceres' low reflectance requires dark phases, which were assumed to be amorphous carbon and/or magnetite (~80 wt.%). In contrast, the Gamma Ray and Neu

Wei-Yuan Liu, Kun Xue, Feng Wan, Min Chen

Energetic spin-polarized positrons are extremely demanded for forefront researches, such as $e^- e^+$ collider physics, but making compact positron sources is still very challenging. Here we put forward an efficient scheme of trapping and acceleration of polarized positrons in plasma wakefields. Seed electrons colliding with a bichromatic laser create polari

Kei Ota, Devesh K. Jha, Tadashi Onishi, Asako Kanezaki

The main novelty of the proposed approach is that it allows a robot to learn an end-to-end policy which can adapt to changes in the environment during execution. While goal conditioning of policies has been studied in the RL literature, such approaches are not easily extended to cases where the robot's goal can change during execution. This is something that

Petr Cagas, Ammar Hakim, Bhuvana Srinivasan

Multifluid simulations of plasma sheaths are increasingly used to model a wide variety of problems in plasma physics ranging from global magnetospheric flows around celestial bodies to plasma-wall interactions in thrusters and fusion devices. For multifluid problems, accurate boundary conditions to model an absorbing wall that resolves a classical sheath rem

Albert Liu, Steven T. Cundiff, Diogo B. Almeida, Ronald Ulbricht

Many applications of nitrogen-vacancy (NV) centers in diamond crucially rely on a spectrally narrow and stable optical zero-phonon line transition. Though many impressive proof-of-principle experiments have been demonstrated, much work remains in engineering NV centers with spectral properties that are sufficiently robust for practical implementation. To elu

Joseph Squillace

Given $n\in\mathbb{N}$, let $\omega\left(n\right)$ denote the number of distinct prime factors of $n$, let $Z$ denote a standard normal variable, and let $P_{n}$ denote the uniform distribution on $\left\{ 1,\ldots,n\right\} $. The Erd\H{o}s-Kac Theorem states that $$P_{n}\left(m\le n:\omega\left(m\right)-\log\log n\le x\left(\log\log n\right)^{1/2}\right)\t

Peter Nelson, Kazuhiro Nomoto

We determine the smallest simple triangle-free binary matroids that have no five-element independent flat. This solves a special case of a conjecture of Nelson and Norin.

Azka Muji Burohman, Bart Besselink, Jacquelien M. A. Scherpen, M. Kanat Camlibel

A new method for data-driven interpolatory model reduction is presented in this paper. Using the so-called data informativity perspective, we define a framework that enables the computation of moments at given (possibly complex) interpolation points based on time-domain input-output data only, without explicitly identifying the high-order system. Instead, by

Anindo Saha, Fakrul I. Tushar, Khrystyna Faryna, Vincent M. D'Anniballe

Weakly supervised disease classification of CT imaging suffers from poor localization owing to case-level annotations, where even a positive scan can hold hundreds to thousands of negative slices along multiple planes. Furthermore, although deep learning segmentation and classification models extract distinctly unique combinations of anatomical features from

Anindo Saha, Prem Prasad, Abdullah Thabit

Fully automatic detection of skin lesions in dermatoscopic images can facilitate early diagnosis and repression of malignant melanoma and non-melanoma skin cancer. Although convolutional neural networks are a powerful solution, they are limited by the illumination spectrum of annotated dermatoscopic screening images, where color is an important discriminativ

Erhan Bayraktar, Ibrahim Ekren, Xin Zhang

We study the problem of prediction with expert advice with adversarial corruption where the adversary can at most corrupt one expert. Using tools from viscosity theory, we characterize the long-time behavior of the value function of the game between the forecaster and the adversary. We provide lower and upper bounds for the growth rate of regret without rely

Guoliang Kang, Yunchao Wei, Yi Yang, Yueting Zhuang

Domain adaptive semantic segmentation aims to train a model performing satisfactory pixel-level predictions on the target with only out-of-domain (source) annotations. The conventional solution to this task is to minimize the discrepancy between source and target to enable effective knowledge transfer. Previous domain discrepancy minimization methods are mai

Bat-Od Battseren

We define a sequence of functions, namely tame cuts, in the Fourier algebra $A(G)$ of a locally compact group $G$, that satisfies certain convergence and growth conditions. This new consideration allows us to give a group admitting a Fourier multiplier that is not completely bounded. Furthermore, we show that the induction map $MA(\Gamma)\rightarrow MA(G)$ i

Robert Carlson

Boundary analysis is developed for a rich class of generally infinite weighted graphs with compact metric completions. These graph completions have totally disconnected boundaries. The classical notion of $\epsilon$-components and the existence of suitable measures are used to construct generalized Haar bases and Hilbert spaces of functions on the boundaries

Samarth Gupta, Saurabh Amin

Error-Correcting Output Codes (ECOCs) offer a principled approach for combining simple binary classifiers into multiclass classifiers. In this paper, we investigate the problem of designing optimal ECOCs to achieve both nominal and adversarial accuracy using Support Vector Machines (SVMs) and binary deep learning models. In contrast to previous literature, w

Hiroyuki Kasahara, Yoichi Sugita

Commonly used methods of production function and markup estimation assume that a firm's output quantity can be observed as data, but typical datasets contain only revenue, not output quantity. We examine the nonparametric identification of production function and markup from revenue data when a firm faces a general nonparametri demand function under imperfec

Hidekazu Furusho

Our aim of this paper is to propose a method of analytic continuation of Carlitz multiple (star) polylogarithms to the whole space by using Artin-Schreier equation and present a treatment of their branches by introducing the notion of monodromy modules. As applications of this method, we obtain (1) a method of continuation of the logarithms of higher tensor

Manuel Cruz Rodriguez, Victoria Hernández Mederos, Jorge Estrada Sarlabous, Eduardo Moreno Hernández

In this work, the propagation of an ultrasonic pulse in a thin plate is computed solving the differential equations modeling this problem. To solve these equations finite differences are used to discretize the temporal variable, while spacial variables are discretized using Finite Element method. The variational formulation of the problem corresponding to a

H. Capettini, M. Cécere, A. Costa, G. Krause

We analyse the capability of different type of perturbations -associated with usual environment energy fluctuations of the solar corona- to excite slow and sausage modes in solar flaring loops. We perform numerical simulations of the MHD ideal equations considering straight plasma magnetic tubes subject to local and global energy depositions. We find that lo

Tengfei Liang, Yi Jin, Yidong Li, Tao Wang

In the past few decades, to reduce the risk of X-ray in computed tomography (CT), low-dose CT image denoising has attracted extensive attention from researchers, which has become an important research issue in the field of medical images. In recent years, with the rapid development of deep learning technology, many algorithms have emerged to apply convolutio

Jun Li, Juliane Manitz, Enrico Bertuzzo, Eric D. Kolaczyk

We investigate the source detection problem in epidemiology, which is one of the most important issues for control of epidemics. Mathematically, we reformulate the problem as one of identifying the relevant component in a multivariate Gaussian mixture model. Focusing on the study of cholera and diseases with similar modes of transmission, we calibrate the pa

Rabiul Islam, Sajahan Molla, Mehedi Kalam

A new strange star model based on Durgapal IV metric (Durgapal 1982) is presented here.Here we have applied a specific method to study the inner physical properties of the compact objects 4U 1702-429, 2A 1822-371, PSR J1756-2251,PSR J1802-2124 and PSR J1713+0747.The main objective of our study is to determine central density ($\rho_{0}$), surface density ($\

Nathan Ng, Marzyeh Ghassemi, Narendran Thangarajan, Jiacheng Pan

Building user trust in dialogue agents requires smooth and consistent dialogue exchanges. However, agents can easily lose conversational context and generate irrelevant utterances. These situations are called dialogue breakdown, where agent utterances prevent users from continuing the conversation. Building systems to detect dialogue breakdown allows agents

W. Yao, A. Fazzini, S. N. Chen, K. Burdonov

Charged particles can be accelerated to high energies by collisionless shock waves in astrophysical environments, such as supernova remnants. By interacting with the magnetized ambient medium, these shocks can transfer energy to particles. Despite increasing efforts in the characterization of these shocks from satellite measurements at the Earth's bow shock

Kyungkeun Kang, Baishun Lai, Chen-Chih Lai, Tai-Peng Tsai

We prove the first ever pointwise estimates of the (unrestricted) Green tensor and the associated pressure tensor of the nonstationary Stokes system in the half-space, for every space dimension greater than one. The force field is not necessarily assumed to be solenoidal. The key is to find a suitable Green tensor formula which maximizes the tangential decay

Plácido L Vidal, Joaquim de Moura, Jorge Novo, Marcos Ortega

One of the main challenges in times of sanitary emergency is to quickly develop computer aided diagnosis systems with a limited number of available samples due to the novelty, complexity of the case and the urgency of its implementation. This is the case during the current pandemic of COVID-19. This pathogen primarily infects the respiratory system of the af

Tongtong Li, Ivan Yotov

We develop a mixed finite element method for the coupled problem arising in the interaction between a free fluid governed by the Stokes equations and flow in deformable porous medium modeled by the Biot system of poroelasticity. Mass conservation, balance of stress, and the Beavers--Joseph--Saffman condition are imposed on the interface. We consider a fully

Yen Hung Chen

Given a complete graph $G=(V,E)$, with nonnegative edge costs, two subsets $R \subset V$ and $R^{\prime} \subset R$, a partition $\mathcal{R}=\{R_1,R_2,\ldots,R_k\}$ of $R$, $R_i \cap R_j=\phi$, $i \neq j$ and $\mathcal{R}^{\prime}=\{R^{\prime}_1,R^{\prime}_2,\ldots,R^{\prime}_k\}$ of $R^{\prime}$, $R^{\prime}_i \subset R_i$, a clustered Steiner tree is a tr

Camille Dunning

Signal-based early detection of illnesses has been a key topic in research and hospital settings; it reduces technological costs and paves the way for quick and effective patient-care operations. Elementary machine learning and signal processing algorithms have proven to be sufficient in classifying the onset of viral and bacterial conditions before clinical

Yen Hung Chen

Given an undirected graph $G=(V,E)$ with a nonnegative edge length function and an integer $p$, $0 < p < |V|$, the $p$-centdian problem is to find $p$ vertices (called the {\it centdian set}) of $V$ such that the {\it eccentricity} plus {\it median-distance} is minimized, in which the {\it eccentricity} is the maximum (length) distance of all vertices to the

Thorsten Stezelberger, John Joseph, Vamsi Vytla, Sergio Zimmermann

The Gamma Ray Energy Tracking Array (GRETA) is a 4-{\pi} detector system, currently under development, capable of determining energy, timing and tracking of multiple gamma-ray interactions inside germanium crystals as demonstrated in the Gamma Ray Energy Tracking In-Beam Array (GRETINA). Charge sensitive amplifiers instrument the crystals and their outputs a

Xinyu Tan, Narayanan Rengaswamy, Robert Calderbank

Unitary $k$-designs are probabilistic ensembles of unitary matrices whose first $k$ statistical moments match that of the full unitary group endowed with the Haar measure. In prior work, we showed that the automorphism group of classical $\mathbb{Z}_4$-linear Kerdock codes maps to a unitary $2$-design, which established a new classical-quantum connection via

Nadish de Silva

The Clifford hierarchy is a nested sequence of sets of quantum gates critical to achieving fault-tolerant quantum computation. Diagonal gates of the Clifford hierarchy and 'nearly diagonal' semi-Clifford gates are particularly important: they admit efficient gate teleportation protocols that implement these gates with fewer ancillary quantum resources such a

P. Kaaret, D. Koutroumpa, K. D. Kuntz, K. Jahoda

The Milky Way galaxy is surrounded by a circumgalactic medium (CGM) that may play a key role in galaxy evolution as the source of gas for star formation and a repository of metals and energy produced by star formation and nuclear activity. The CGM may also be a repository for baryons seen in the early universe, but undetected locally. The CGM has an ionized

Mayukh Nath, Alfred Krister Ulvog, Scott Weigand, Shreyas Sen

With the advent of wearable technologies, Human Body Communication (HBC) has emerged as a physically secure and power-efficient alternative to the otherwise ubiquitous Wireless Body Area Network (WBAN). Whereas the most investigated nodes of HBC have been Electric and Electro-quasistatic (EQS) Capacitive and Galvanic, recently Magnetic HBC (M-HBC) has been p

Shokoufe Faraji, Audrey Trova

In this paper, we constructed the magnetized thick disk model analytically around the static black hole in the presence of an external distribution of matter up to the quadrupole moment. This space-time is a solution to Einstein's field equation describing the exterior of a static and axially symmetric object locally. This work aims to study this space-time

Sajahan Molla, Bidisha Ghosh, Mehedi Kalam

We construct a relativistic model for the newly discovered millisecond pulsar PSR J0514 - 4002A located in the globular cluster NGC 1851 (A. Ridolfi, P.C.C. Freire, Y. Gupta, S.M. Ransom, MNRAS 490, 3860 (2019)) by using Tolman VII spacetime. We have obtained central density ($\rho_{0}$), central pressure ($p_{0}$), probable radius, compactness ($u$) and sur

Vincent Longo

Batson's conjecture is a non-orientable version of Milnor's conjecture, which states that the 4-ball genus of a torus knot $T(p,q)$ is equal to $\frac{(p-1)(q-1)}{2}$. Batson's conjecture states that the nonorientable 4-ball genus is equal to the pinch number of a torus knot, i.e. the number of a specific type of (nonorientable) band surgeries needed to obta

James Belen, Sajad Mousavi, Alireza Shamsoshoara, Fatemeh Afghah

Atrial Fibrillation (AF) is among one of the most common types of heart arrhythmia afflicting more than 3 million people in the U.S. alone. AF is estimated to be the cause of death of 1 in 4 individuals. Recent advancements in Artificial Intelligence (AI) algorithms have led to the capability of reliably detecting AF from ECG signals. While these algorithms

Eugene Vinitsky, Nathan Lichtle, Kanaad Parvate, Alexandre Bayen

We study the ability of autonomous vehicles to improve the throughput of a bottleneck using a fully decentralized control scheme in a mixed autonomy setting. We consider the problem of improving the throughput of a scaled model of the San Francisco-Oakland Bay Bridge: a two-stage bottleneck where four lanes reduce to two and then reduce to one. Although ther

Le Zhou, R. Dennis Cook, Hui Zou

Huber regression (HR) is a popular robust alternative to the least squares regression when the error follows a heavy-tailed distribution. We propose a new method called the enveloped Huber regression (EHR) by considering the envelope assumption that there exists some subspace of the predictors that has no association with the response, which is referred to a

Andrew D. Maris, Bibek Pokharel, Sharan Ganjam Seshachallam, Moses Z. R. Misplon

We study the quantum dissipative Duffing oscillator across a range of system sizes and environmental couplings under varying semiclassical approximations. Using spatial (based on Kullback-Leibler distances between phase-space attractors) and temporal (Lyapunov exponent-based) complexity metrics, we isolate the effect of the environment on quantum-classical d

Yiyan Shou

The Chern-Schwartz-MacPherson (CSM) and motivic Chern (mC) classes of Schubert cells in a Grassmannian are one parameter deformations of the fundamental classes of the Schubert varieties in cohomology and K-theory respectively. Like the fundamental classes, the deformed classes form a basis for the cohomology and K-theory ring of the Grassmannian. The purpos