October 2020 arXiv papers — page 119

Rhys M. Kennard, Clayton J. Dahlman, Ryan A. DeCrescent, Jon A. Schuller

Mechanical strain can modify the structural and electronic properties of methylammonium lead iodide MAPbI3. The consequences of ferroelastic hysteresis, which involves the retention of structural memory upon cycles of deformation, in polycrystalline thin films of MAPbI3 are reported. Repeatedly bent films of MAPbI3 on flexible polyimide substrates were exami

Ivan Novikov

We study Feynman checkers, the most elementary model of electron motion introduced by R. Feynman. For the model, we prove that the probability to find an electron vanishes nowhere inside the light cone. We also prove several results on the average electron velocity. In addition, we present a lot of identities related to the model.

Patrizio Vanella, Ugofilippo Basellini, Berit Lange

The current outbreak of COVID-19 has called renewed attention to the need for sound statistical analysis for monitoring mortality patterns and trends over time. Excess mortality has been suggested as the most appropriate indicator to measure the overall burden of the pandemic on mortality. As such, excess mortality has received considerable interest during t

Kipp Cannon, Sarah Caudill, Chiwai Chan, Bryce Cousins

The GstLAL library, derived from Gstreamer and the LIGO Algorithm Library, supports a stream-based approach to gravitational-wave data processing. Although GstLAL was primarily designed to search for gravitational-wave signatures of merging black holes and neutron stars, it has also contributed to other gravitational-wave searches, data calibration, and dete

C. Klein, J. -C. Saut, Yuexun Wang

We consider in this paper modified fractional Korteweg-de Vries and related equations (modified Burgers-Hilbert and Whitham). They have the advantage with respect to the usual fractional KdV equation to have a defocusing case with a different dynamics. We will distinguish the weakly dispersive case where the phase velocity is unbounded for low frequencies an

Tanujit Chakraborty, Indrajit Ghosh, Tirna Mahajan, Tejasvi Arora

The coronavirus disease 2019 (COVID-19) has become a public health emergency of international concern affecting more than 200 countries and territories worldwide. As of September 30, 2020, it has caused a pandemic outbreak with more than 33 million confirmed infections and more than 1 million reported deaths worldwide. Several statistical, machine learning,

Henry Jin, Marios Mattheakis, Pavlos Protopapas

Eigenvalue problems are critical to several fields of science and engineering. We present a novel unsupervised neural network for discovering eigenfunctions and eigenvalues for differential eigenvalue problems with solutions that identically satisfy the boundary conditions. A scanning mechanism is embedded allowing the method to find an arbitrary number of s

Alessandro Paticchio, Tommaso Scarlatti, Marios Mattheakis, Pavlos Protopapas

Studying the dynamics of COVID-19 is of paramount importance to understanding the efficiency of restrictive measures and develop strategies to defend against upcoming contagion waves. In this work, we study the spread of COVID-19 using a semi-supervised neural network and assuming a passive part of the population remains isolated from the virus dynamics. We

Miguel Perez-Torres, Seppo Mattila, Almudena Alonso-Herrero, Susanne Aalto

Nearby galaxies offer unique laboratories allowing multi-wavelength spatially resolved studies of the interstellar medium, star formation and nuclear activity across a broad range of physical conditions. In particular, detailed studies of individual local luminous infrared galaxies (LIRGs) are crucial for gaining a better understanding of these processes and

Antonios Mitsopoulos, Michael Tsamparlis, Andronikos Paliathanasis

We consider the generic quadratic first integral (QFI) of the form $I=K_{ab}(t,q)\dot{q}^{a}\dot{q}^{b}+K_{a}(t,q)\dot{q}^{a}+K(t,q)$ and require the condition $dI/dt=0$. The latter results in a system of partial differential equations which involve the tensors $K_{ab}(t,q)$, $K_{a}(t,q)$, $K(t,q)$ and the dynamical quantities of the dynamical equations. The

Timothy Kohl, Robert Underwood

Let $K$ be a finite field extension of $\Q$ and let $N$ be a finite group with automorphism group $F=\Aut(N)$. R. Haggenmüller and B. Pareigis have shown that there is a bijection \[Θ: {\mathcal Gal}(K,F)\rightarrow {\mathcal Hopf}(K[N])\] from the collection of $F$-Galois extensions of $K$ to the collection of Hopf forms of the group ring $K[N]$. For $N=C_n

Daniel Rebain, Baptiste Angles, Julien Valentin, Nicholas Vining

The medial axis transform has applications in numerous fields including visualization, computer graphics, and computer vision. Unfortunately, traditional medial axis transformations are usually brittle in the presence of outliers, perturbations and/or noise along the boundary of objects. To overcome this limitation, we introduce a new formulation of the medi

C. Opitom, A. Guilbert-Lepoutre, S. Besse, B. Yang

Observations of comet 67P/Churyumov-Gerasimenko were performed with MUSE at large heliocentric distances post-perihelion, between March 3 and 7, 2016. Those observations were part of a simultaneous ground-based campaign aimed at providing large-scale information about comet 67P that complement the ESA/Rosetta mission. We obtained a total of 38 datacubes over

D. Afanasiev, J. R. Hortensius, M. Matthiesen, S. Mañas-Valero

Magnetic van der Waals materials provide an ideal playground for exploring the fundamentals of low-dimensional magnetism and open new opportunities for ultrathin spin processing devices. The Mermin-Wagner theorem dictates that as in reduced dimensions isotropic spin interactions cannot retain long-range correlations; the order is stabilized by magnetic aniso

Roberto Giambò, Orlando Luongo, Hernando Quevedo

We show that in the inhomogeneous Lema{î}tre-Tolman-Bondi space-time there are specific regions in which repulsive gravity exists. To find these regions, we use an invariant definition of repulsive gravity based upon the behavior of the curvature eigenvalues. In addition, we analyze the effects of repulsive gravity on the dynamics of the gravitational collap

David S. Lee, Justin McCrary, Marcelo J. Moreira, Jack Porter

In the single IV model, current practice relies on the first-stage F exceeding some threshold (e.g., 10) as a criterion for trusting t-ratio inferences, even though this yields an anti-conservative test. We show that a true 5 percent test instead requires an F greater than 104.7. Maintaining 10 as a threshold requires replacing the critical value 1.96 with 3

Wei Du, Depeng Xu, Xintao Wu, Hanghang Tong

Federated learning is an emerging framework that builds centralized machine learning models with training data distributed across multiple devices. Most of the previous works about federated learning focus on the privacy protection and communication cost reduction. However, how to achieve fairness in federated learning is under-explored and challenging espec

Polina Pilyugina, Rodrigo Rivera-Castro, Eugeny Burnaev

This work is devoted to a comprehensive analysis of topological data analysis fortime series classification. Previous works have significant shortcomings, such aslack of large-scale benchmarking or missing state-of-the-art methods. In this work,we propose TOTOPO for extracting topological descriptors from different types ofpersistence diagrams. The results s

Yury Grabovsky

This is a report of the massive multi-year effort by the author and two graduate students Huilin Chen and Sarah Childs to compute all exact relations and links for two-dimensional thermoelectric composites. At the moment I have no time to prepare a proper "archival quality" manuscript with a good introduction and references. However, I believe that t

Peng Gao

Large batch jobs such as Deep Learning, HPC and Spark require far more computational resources and higher cost than conventional online service. Like the processing of other time series data, these jobs possess a variety of characteristics such as trend, burst, and seasonality. Cloud providers offer short-term instances to achieve scalability, stability, and

Luca Franci, Daniele Del Sarto, Emanuele Papini, Alice Giroul

How the turbulent energy cascade develops below the magnetohydrodynamic scales in space and astrophysical plasmas is a major open question. Here, we measure the power spectrum of magnetic fluctuations in Parker Solar Probe's observations close to the Sun and in state-of-the-art numerical simulations of plasma turbulence. Both reveal a power-law behavior

Franziska Geiger, Michelle Martin, Monika Pichlmair, Ilhan Aslan

Digitalization is changing the nature of tools and materials, which are used in artistic practices in professional and non-professional settings. For example, today it is common that even children express their ideas and explore their creativity by drawing on tablets as digital canvases. While there are many software-based tools, which resemble traditional t

Jack Madden

From life on other planets to virtual classrooms this thesis spans a wide array of research topics all based on how we see other worlds. Our understanding of everything from moon phases, the planets in our Solar System, and exoplanet atmospheres come from our interpretation of light and one day, our knowledge of light will be used as evidence for the discove

Fabio Bagarello, Sergey Kuzhel

It is known that self-adjoint Hamiltonians with purely discrete eigenvalues can be written as (infinite) linear combination of mutually orthogonal projectors with eigenvalues as coefficients of the expansion. The projectors are defined by the eigenvectors of the Hamiltonians. In some recent papers, this expansion has been extended to the case in which these

Jan Hubička

We survey recent developments concerning two properties of classes of finite structures: the Ramsey property and the extension property for partial automorphisms (EPPA).

Peter B. Rau, Armen Sedrakian

Binary neutron star mergers, such as the multimessenger GW170817 event, may produce hypermassive compact objects which are supported against collapse by the internal circulation of the fluid within the star. We compute their unstable modes of oscillations driven by gravitational wave radiation and shear viscosity, modeling them as triaxial Riemann ellipsoids

A. S. Elwakil, M. E. Fouda, S. Majzoub, A. G. Radwan

This paper shows that pinched hysteresis can be observed in simple nonlinear resonance circuits containing a single diode that behaves as a voltage-controlled switch. Mathematical models are derived and numerically validated for both series and parallel resonator circuits. The lobe area of the pinched loop is found to increase with increased frequency and mu

Sushanta Tripathy

Recent results for high multiplicity pp and p-Pb collisions have revealed that they exhibit heavy-ion-like behaviors. To understand the origin(s) of these unexpected phenomena, event shape observables such as transverse spherocity ($S_{\rm 0}^{p_{\rm T} = 1}$) and the relative transverse activity classifier ($R_{\rm{T}}$) can be exploited as a powerful tools

Samuel Hsia, Udit Gupta, Mark Wilkening, Carole-Jean Wu

Deep learning based recommendation systems form the backbone of most personalized cloud services. Though the computer architecture community has recently started to take notice of deep recommendation inference, the resulting solutions have taken wildly different approaches - ranging from near memory processing to at-scale optimizations. To better design futu

Tyson Bulmer, Lloyd Montgomery, Daniela Damian

When a developer is writing code they are usually focused and in a state-of-mind which some refer to as flow. Breaking out of this flow can cause the developer to lose their train of thought and have to start their thought process from the beginning. This loss of thought can be caused by interruptions and sometimes slow IDE interactions. Predictive functiona

Thomas S. -Y. Lai, J. D. T. Smith, Shunsuke Baba, Henrik W. W. Spoon

We present a large sample of 2.5-38 $μm$ galaxy spectra drawn from a cross-archival comparison in the AKARI-Spitzer Extragalactic Spectral Survey (ASESS), and investigate a subset of 113 star-forming galaxies with prominent polycyclic aromatic hydrocarbon (PAH) emission spanning a wide range of star formation properties. With AKARI's extended 2.5-5 $μm$

Paul Pollack, Noah Snyder

We give a short proof -- not relying on ideal classes or the geometry of numbers -- of a known criterion for quadratic orders to possess unique factorization.

B. Santhosh Kumar, Rajesh Narayana Perumal, C. Venkateswaran

We report the ferroelectric property in Tb2Ti2O7 pyrochlore, prepared by a two-step solid-state reaction method. A concave P-E (polarisation vs electric field) loop observed from 382 K confirms ferroelectricity, below which the loop remains as pointed or banana-shaped. Dielectric plots clearly show an anomaly at 383 K and the magnetic data reveals a deviatio

Lucia Pons, Josué Feliu, José Puche, Chaoyi Huang

Understanding inter-VM interference is of paramount importance to provide a sound knowledge and understand where performance degradation comes from in the current public cloud. With this aim, this paper devises a workload taxonomy that classifies applications according to how the major system resources affect their performance (e.g., tail latency) as a funct

Tian Yao, Benjian Lv, Kaishun Wang

Let $\mathscr{P}$ be a symplectic polar space over a finite field $\mathbb{F}_q$, and $\mathscr{P}_m$ denote the set of all $m$-dimensional subspaces in $\mathscr{P}$. We say a $t$-intersecting subfamily of $\mathscr{P}_m$ is trivial if there exists a $t$-dimensional subspace contained in each member of this family. In this paper, we determine the structure

Giovanni Batignani, Carino Ferrante, Tullio Scopigno

Excited-state vibrations are crucial for determining photophysical and photochemical properties of molecular compounds. Stimulated Raman scattering can coherently stimulate and probe molecular vibrations with optical pulses, but it is generally restricted to ground state properties. Working in resonance conditions, indeed, enables cross-section enhancement a

Brahim Amaziane, Leonid Pankratov, Andrey Piatnitski

The paper deals with homogenization of a model problem describing an immiscible compressible two-phase flow in random statistically homogeneous porous media. We derive the effective (macroscopic) problem and prove the convergence of solutions. Our approach relies on stochastic two-scale convergence techniques, the realization-wise notion of stochastic two-sc

Jun Wang, Qianying Liu, Haotian Xie, Zhaogang Yang

In recent years, advances in the development of whole-slide images have laid a foundation for the utilization of digital images in pathology. With the assistance of computer images analysis that automatically identifies tissue or cell types, they have greatly improved the histopathologic interpretation and diagnosis accuracy. In this paper, the Convolutional

Beiran Chen, Yi Zhang, George Iosifidis, Mingming Liu

Wireless networks used for Internet of Things (IoT) are expected to largely involve cloud-based computing and processing. Softwarised and centralised signal processing and network switching in the cloud enables flexible network control and management. In a cloud environment, dynamic computational resource allocation is essential to save energy while maintain

Gidon Ernst

Cuvée is a program verification tool that reads SMT-LIB-like input files where terms may additionally contain weakest precondition operators over abstract programs. Cuvée translates such inputs into first-order SMT-LIB by symbolically executing these programs. The input format used by Cuvée is intended to achieve a similar unification of tools for that for e

Rui Wang, Yilin Wang, Y. X. Zhao, Baigeng Wang

Quantum impurities serve as in-situ probes of the frustrated quantum magnets, and Dirac spin liquids are an important class of quantum spin liquids. Here, we present a general method, a combination of the Chern-Simons fermionization and the Wess-Zumino-Witten theory, to study the quantum impurity in Dirac spin liquids. Under the Chern-Simons fermionization,

Abdelkerim Amari, Lutz Lampe, O. S. Sunish Kumar, Yunus Can Gultekin

In optical communication systems, short blocklength probabilistic enumerative sphere shaping (ESS) provides both linear shaping gain and nonlinear tolerance. In this work, we investigate the performance and complexity of ESS in comparison with fiber nonlinearity compensation via digital back propagation (DBP) with different steps per span. We evaluate the im

A. V. Eremeev, A. S. Yurkov

Solution and analysis of mathematical programming problems may be simplified when these problems are symmetric under appropriate linear transformations. In particular, a knowledge of the symmetries may help reduce the problem dimension, cut the search space by linear cuts or obtain new local optima from the ones previously found. While the previous studies o

Horst Alzer, Man Kam Kwong

Let $$ T(q)=\sum_{k=1}^\infty d(k) q^k, \quad |q|<1, $$ where $d(k)$ denotes the number of positive divisors of the natural number $k$. We present monotonicity properties of functions defined in terms of $T$. More specifically, we proved that $$ H(q) := T(q)- \frac{\log(1-q)}{\log(q)} $$ is strictly increasing in $ (0,1) $ while $$ F(q) := \frac{1-q}{q} \,H(

Dong Hyuk Ko, Graham G. Brown, Chunmei Zhang, P. B. Corkum

Multiphoton-ionized electrons are born into a strong light field that will determine their short-term future. By controlling the infrared beam, we enable atoms or molecules to generate extreme ultraviolet (XUV) pulses and synthesize attosecond pulses - the shortest controlled events ever produced. Here we show that a weak obliquely incident beam imposes an o

Lidia Talavera-Martínez, Pedro Bibiloni, Manuel González-Hidalgo

The process of removing occluding hair has a relevant role in the early and accurate diagnosis of skin cancer. It consists of detecting hairs and restore the texture below them, which is sporadically occluded. In this work, we present a model based on convolutional neural networks for hair removal in dermoscopic images. During the network&#39;s training, we

David Jewitt, Yoonyoung Kim

Quasi-Hilda asteroid P/2010 H2 (Vales) underwent a spectacular photometric outburst by 7.5 magnitudes (factor of 1000) in 2010. Here, we present our optical observations of this event in the four month period from April 20 to August 10. The outburst, starting UT 2010 April 15.76, released dust particles of total cross-section 17,600 sq km (albedo 0.1 assumed

Peng Chen, Xinghu Jin, Xiang Li, Lihu Xu

We generalize the { ${\rm M}$-estimator} put forward by Catoni in his seminal paper [C12] to the case in which samples can have finite $α$-th moment with $α\in (1,2)$ rather than finite variance, our approach is by slightly modifying the influence function $φ$ therein. The choice of the new influence function is inspired by the Taylor-like expansion develope

Denis Kuzminykh, Laida Kushnareva, Timofey Grigoryev, Alexander Zatolokin

Finding an interpretable non-redundant representation of real-world data is one of the key problems in Machine Learning. Biological neural networks are known to solve this problem quite well in unsupervised manner, yet unsupervised artificial neural networks either struggle to do it or require fine tuning for each task individually. We associate this with th

Prafull Prakash, Saurabh Kumar Shashidhar, Wenlong Zhao, Subendhu Rongali

The current state-of-the-art task-oriented semantic parsing models use BERT or RoBERTa as pretrained encoders; these models have huge memory footprints. This poses a challenge to their deployment for voice assistants such as Amazon Alexa and Google Assistant on edge devices with limited memory budgets. We propose to learn compositional code embeddings to gre

Wanqing Cui, Yanyan Lan, Liang Pang, Jiafeng Guo

This paper proposes a novel approach to learn commonsense from images, instead of limited raw texts or costly constructed knowledge bases, for the commonsense reasoning problem in NLP. Our motivation comes from the fact that an image is worth a thousand words, where richer scene information could be leveraged to help distill the commonsense knowledge, which

Jitender Kumar, Sandeep Dalal, Pranav Pandey

The commuting graph of a finite non-commutative semigroup S, denoted by Δ(S), is the simple graph whose vertices are the non-central elements of S and two distinct vertices x; y are adjacent if xy = yx. In the present paper, we study various graph-theoretic properties of the commuting graph Δ(B_n) of Brandt semigroup B_n including its diameter, clique number

Weijie Jin, Robert Brandenberger, Lavinia Heisenberg

We study the effects of particle production on the evolution of the inflaton field in an axion monodromy model with the goal of discovering in which situations the resulting dynamics will be consistent with the {\it swampland constraints}. In the presence of a modulated potential the evolving background field (solution of the inflaton homogeneous in space) i

Paolo Amore, Francisco M. Fernández

We analyze the eigenvalues and eigenfunctions stemming from a recent study of the interaction of a scalar particle with a Coulomb potential in the presence of a background of the violation of the Lorentz symmetry established by a tensor field. We show, beyond any doubt, that the physical conclusions drawn by the authors from a truncation of a power series, c

Zhiyu Tian

We study zero cycles on rationally connected varieties defined over characteristic zero Laurent fields with algebraically closed residue fields. We show that the degree map induces an isomorphism for rationally connected threefolds defined over such fields. In general, the degree map is an isomorphism if rationally connected varieties defined over algebraica

Vahid Haghighatdoost, Siavash Khorsandi, Hamed Ahmadi

Price and the quality of service are two key factors taken into account by wireless network users when they choose their network provider. The recent advances in wireless technology and massive infrastructure deployments has led to better coverage, and currently at each given wirelessly covered area there are a few network providers and each have different p

Lei Zhou, Liang Ding, Koichi Takeda

This paper describes our submission of the WMT 2020 Shared Task on Sentence Level Direct Assessment, Quality Estimation (QE). In this study, we empirically reveal the \textit{mismatching issue} when directly adopting BERTScore to QE. Specifically, there exist lots of mismatching errors between the source sentence and translated candidate sentence with token

Kazuaki Murakami

Let $p$ be an odd prime number and $k$ an imaginary quadratic field in which $p$ splits. In this paper, we consider a weak form of Greenberg&#39;s generalized conjecture for $p$ and $k$, which states that the non-trivial Iwasawa module of the maximal multiple $\mathbb{Z}_p$-extension field over $k$ has a non-trivial pseudo-null submodule. We prove this conje

Piyawat Lertvittayakumjorn, Lucia Specia, Francesca Toni

Since obtaining a perfect training dataset (i.e., a dataset which is considerably large, unbiased, and well-representative of unseen cases) is hardly possible, many real-world text classifiers are trained on the available, yet imperfect, datasets. These classifiers are thus likely to have undesirable properties. For instance, they may have biases against som

V Ryzhii, T Otsuji, M Ryzhii, V Leiman

We develop the device model for the proposed injection (electrically) driven thermal light emitters (IDLEs) based on the vertical Hexagonal Boron Nitride Layer/Graphene Layer/ Hexagonal Boron Nitride Layer (hBNL/GL/hBNL) heterostructures and analyze their dynamic response. The operation of the IDLEs is associated with the light emission of the hot two-dimens

Duanduan Wan, Sharon C. Glotzer

Using computer simulations, we explore how thermal noise-induced randomness in a self-assembled photonic crystal affects its photonic band gaps (PBGs). We consider a two-dimensional photonic crystal comprised of a self-assembled array of parallel dielectric hard rods of infinite length with circular or square cross section. We find the PBGs can exist over a

M E Dieckmann, M Falk, D Folini, R Walder

We study with a two-dimensional particle-in-cell simulation the stability of a discontinuity or piston, which separates an electron-positron cloud from a cooler electron-proton plasma. Such a piston might be present in the relativistic jets of accreting black holes separating the jet material from the surrounding ambient plasma and when pair clouds form duri

Renato Negrinho, Matthew R. Gormley, Geoffrey J. Gordon

Structured prediction is often approached by training a locally normalized model with maximum likelihood and decoding approximately with beam search. This approach leads to mismatches as, during training, the model is not exposed to its mistakes and does not use beam search. Beam-aware training aims to address these problems, but unfortunately, it is not yet

Simone Fontana, Domenico G. Sorrenti

Probabilistic Point Clouds Registration (PPCR) is an algorithm that, in its multi-iteration version, outperformed state of the art algorithms for local point clouds registration. However, its performances have been tested using a fixed high number of iterations. To be of practical usefulness, we think that the algorithm should decide by itself when to stop,

Guangzheng Hu, Yuanheng Zhu, Dongbin Zhao, Mengchen Zhao

Communicating with each other in a distributed manner and behaving as a group are essential in multi-agent reinforcement learning. However, real-world multi-agent systems suffer from restrictions on limited-bandwidth communication. If the bandwidth is fully occupied, some agents are not able to send messages promptly to others, causing decision delay and imp

Xiangming Gu, Xiang Cheng

Deep neural networks (DNNs) demonstrate great success in classification tasks. However, they act as black boxes and we don&#39;t know how they make decisions in a particular classification task. To this end, we propose to distill the knowledge from a DNN into a fuzzy inference system (FIS), which is Takagi-Sugeno-Kang (TSK)-type in this paper. The model has

Zhaohui Shang

Dome A in Antarctica has been demonstrated to be the best site on earth for optical, infrared, and terahertz astronomical observations by more and more evidence, such as excellent free-atmosphere seeing, extremely low perceptible water vapor, low sky background, and continuous dark time, etc. In this review paper, we present a complete picture of the develop

Navid Khezrian, Jafar Habibi, Issa Annamoradnejad

Online Q&A and open source communities use tags and keywords to index, categorize, and search for specific content. The most obvious advantage of tag recommendation is the correct classification of information. In this study, we used the BERT pre-training technique in tag recommendation task for online Q&A and open-source communities for the first time. Our

Yingxue Zhang, Fandong Meng, Peng Li, Ping Jian

As conventional answer selection (AS) methods generally match the question with each candidate answer independently, they suffer from the lack of matching information between the question and the candidate. To address this problem, we propose a novel reinforcement learning (RL) based multi-step ranking model, named MS-Ranker, which accumulates information fr

Rayimbaev Javlon, Demyanova Alexandra, Ugur Camci, Ahmadjon Abdujabbarov

This paper investigates the motion and acceleration of a particle that is electrically and magnetically charged, which rotates around a cylindrical black hole in the presence of an external asymptotically uniform magnetic field parallel to the z axis. Basically, the work considers the circular orbits of particles rotating around the central object and studie

Andras I. Stipsicz, Zoltan Szabo

We introduce a numerical invariant β(K) of a knot K which measures how non-alternating K is. We prove an inequality between β(K) and the (knot Floer) thickness of K. As an application we show that all Montesinos knots have thickness at most one.

Xixian Chen, Haiqin Yang, Shenglin Zhao, Michael R. Lyu

Estimating covariance matrix from massive high-dimensional and distributed data is significant for various real-world applications. In this paper, we propose a data-aware weighted sampling based covariance matrix estimator, namely DACE, which can provide an unbiased covariance matrix estimation and attain more accurate estimation under the same compression r

Tanmay Bhore, Siddharth Chaini, Siddharth Bachoti, Vipin Khade

In this text, we implement a monte carlo algorithm to study thermodynamic properties of ice. Our program, written in Python, is open-sourced and available at https://github.com/AKnightWing/ColdAsIce. We develop a novel scheme to compute the residual entropy of a two dimensional lattice model of ice at absolute zero. A model of energetic ice is also considere

Nguyen Hong Nam, Vu Anh My, Ta Ngoc Anh, Hy Duc Manh

In this paper, a non-linear Lanchester-type model involving supply units is introduced. The model describes a battle where the Blue party consisting of one armed force $B$ is fighting against the Red party. The Red party consists of $n$ armed forces each of which is supplied by a supply unit. A new variable called &#34;fire allocation&#34; is associated to t

Dimitris Vartziotis, Doris Bohnet, Benjamin Himpel

We want to introduce another smoothing approach by treating each geometric element as a player in a game: a quest for the best element quality. In other words, each player has the goal of becoming as regular as possible. The set of strategies for each element is given by all translations of its vertices. Ideally, he would like to quantify this regularity usi

Chetan Kumar Kuraganti, Bryan Paul Robert, Gurunath Gurrala, Ashish Joglekar

Recent cyber-attacks on power grids highlight the necessity to protect the critical functionalities of a control center vital for the safe operation of a grid. Even in a distributed framework one central control center acts as a coordinator in majority of the control center architectures. Such a control center can become a prime target for cyber as well as p

Jingzhou Sun

We study the asymptotic of the partial density function associated to holomorphic section of a postive line bundle vanishing to high orders along a fixed smooth subvariety. Assuming local torus-action-invariance, we describe the forbidden region, generalizing the result of Ross-Singer.

Xingwei Sun, Ze-Feng Gao, Zhong-Yi Lu, Junfeng Li

The deep neural network (DNN) based speech enhancement approaches have achieved promising performance. However, the number of parameters involved in these methods is usually enormous for the real applications of speech enhancement on the device with the limited resources. This seriously restricts the applications. To deal with this issue, model compression t

Xixian Chen, Haiqin Yang, Shenglin Zhao, Michael R. Lyu

Data-dependent hashing methods have demonstrated good performance in various machine learning applications to learn a low-dimensional representation from the original data. However, they still suffer from several obstacles: First, most of existing hashing methods are trained in a batch mode, yielding inefficiency for training streaming data. Second, the comp

Yong Guo, Qingyao Wu, Chaorui Deng, Jian Chen

Batch Normalization (BN) has been a standard component in designing deep neural networks (DNNs). Although the standard BN can significantly accelerate the training of DNNs and improve the generalization performance, it has several underlying limitations which may hamper the performance in both training and inference. In the training stage, BN relies on estim

Hiroyuki Shima

Columnar buckling is a ubiquitous phenomenon that occurs in both living things and man-made objects, regardless of the length scale ranging from macroscopic to nanometric structures. In general, analyzing the post-buckling behavior of a column requires the application of complex mathematical methods because it involves nonlinear problem solving. To complemen

Minh-Duc Nguyen, Alexander Kryukov, Andrey Mikhailov

AstroDS is a distributed storage for Cosmic Ray Astrophysics. The primary goal of Astro DS is to gather data measured by the instruments of various physical experiments such as TAIGA, TUNKA, KASCADE into global storage and provide the users with a standardized user-friendly interface to search for the datasets that match certain conditions. AstroDS consists

Changlong Yu, Jialong Han, Peifeng Wang, Yangqiu Song

We address hypernymy detection, i.e., whether an is-a relationship exists between words (x, y), with the help of large textual corpora. Most conventional approaches to this task have been categorized to be either pattern-based or distributional. Recent studies suggest that pattern-based ones are superior, if large-scale Hearst pairs are extracted and fed, wi

Alexander Kryukov, Igor Bychkov, Elena Korosteleva, Andrey Mikhailov

Currently, the processing of scientific data in astroparticle physics is based on various distributed technologies, the most common of which are Grid and cloud computing. The most frequently discussed approaches are focused on large and even very large scientific experiments, such as Cherenkov Telescope Array. We, by contrast, offer a solution designed for s

Ramtin Babaeipour, Elham Azizi, Hassan Khotanlou

Spreading of COVID-19 virus has increased the efforts to provide testing kits. Not only the preparation of these kits had been hard, rare, and expensive but also using them is another issue. Results have shown that these kits take some crucial time to recognize the virus, in addition to the fact that they encounter with 30% loss. In this paper, we have studi

Jun Kong, Jin Wang, Xuejie Zhang

It is fairly common to use code-mixing on a social media platform to express opinions and emotions in multilingual societies. The purpose of this task is to detect the sentiment of code-mixed social media text. Code-mixed text poses a great challenge for the traditional NLP system, which currently uses monolingual resources to deal with the problem of multil

Rahel Brügger, Helmut Harbrecht, Johannes Tausch

This article provides a functional analytical framework for boundary integral equations of the heat equation in time-dependent domains. More specifically, we consider a non-cylindrical domain in space-time that is the $C^2$-diffeomorphic image of a cylinder, i.e., the tensor product of a time interval and a fixed domain in space. On the non-cylindrical domai

Yue Zheng, Tianyi Yang, Wen Zhang, Dengji Zhao

Barter exchange studies the setting where each agent owns a good, and they can exchange with each other if that gives them more preferred goods. This exchange will give better outcomes if there are more participants. The challenge here is how to get more participants and our goal is to incentivize the existing participants to invite new participants. However

Shan Chen, Zixiao Liu

We establish quantitative asymptotic behavior of positive solutions of a family of nonlinear elliptic equations on the half cylinder near the end. This unifies the study of isolated singularities of some semilinear elliptic equations, such as the Yamabe equation, Hardy-Hénon equation etc.

Zicheng Kan, Yazhan Zhang, Chohei Pang, Michael Yu Wang

Adaptation to various scene configurations and object properties, stability and dexterity in robotic grasping manipulation is far from explored. This work presents an origami-based shape morphing fingertip design to actively tackle the grasping stability and dexterity problems. The proposed fingertip utilizes origami as its skeleton providing degrees of free

Tianhua Zhu

The application of computer technology in the field of art has given rise to novel modes of artistic practice, including media art, and it is a necessity to find a commensurable conceptual fundament. Therefore, computer art starting from the 1950s reenters the view. To clarify the definition, major methods for defining are reviewed, and it is argued that the

Haoming Li, Xin Yang, Jiamin Liang, Wenlong Shi

Ultrasound (US) image segmentation embraced its significant improvement in deep learning era. However, the lack of sharp boundaries in US images still remains an inherent challenge for segmentation. Previous methods often resort to global context, multi-scale cues or auxiliary guidance to estimate the boundaries. It is hard for these methods to approach pixe

Qiansheng Wang, Yuxin Liu, Chengguo Lv, Zhen Wang

Open-domain response generation is the task of generating sensible and informative re-sponses to the source sentence. However, neural models tend to generate safe and mean-ingless responses. While cue-word introducing approaches encourage responses with concrete semantics and have shown tremendous potential, they still fail to explore di-verse responses duri

Yian Zhang

Recent latent tree learning models can learn constituency parsing without any exposure to human-annotated tree structures. One such model is ON-LSTM (Shen et al., 2019), which is trained on language modelling and has near-state-of-the-art performance on unsupervised parsing. In order to better understand the performance and consistency of the model as well a

Vikas Raunak, Siddharth Dalmia, Vivek Gupta, Florian Metze

State-of-the-art Neural Machine Translation (NMT) models struggle with generating low-frequency tokens, tackling which remains a major challenge. The analysis of long-tailed phenomena in the context of structured prediction tasks is further hindered by the added complexities of search during inference. In this work, we quantitatively characterize such long-t

Jianzhou Zhao, Weikang Wu, Jiaojiao Zhu, Yunhao Lu

Anisotropy is a general feature in materials. Strong anisotropy could lead to interesting physical properties and useful applications. Here, based on first-principles calculations and theoretical analysis, we predict a stable two-dimensional (2D) material---the monolayer MoOCl$_2$, and show that it possesses intriguing properties related to its high anisotro

Zhengxuan Wu, Thanh-Son Nguyen, Desmond C. Ong

Neural attention, especially the self-attention made popular by the Transformer, has become the workhorse of state-of-the-art natural language processing (NLP) models. Very recent work suggests that the self-attention in the Transformer encodes syntactic information; Here, we show that self-attention scores encode semantics by considering sentiment analysis

Sachin Shyam Phatak

In this thesis we study field theoretic viewpoints on certain fluid mechanical phenomena. In the Higgs mechanism, the weak gauge bosons acquire masses by interacting with a scalar field, leading to a vector boson mass matrix. On the other hand, a rigid body accelerated through an inviscid, incompressible and irrotational fluid feels an opposing force linear

Qikui Zhu, Liang Li, Jiangnan Hao, Yunfei Zha

Automated medical image segmentation plays an important role in many clinical applications, which however is a very challenging task, due to complex background texture, lack of clear boundary and significant shape and texture variation between images. Many researchers proposed an encoder-decoder architecture with skip connections to combine low-level feature

P. Padmanabhan, F. L. Buessen, R. Tutchton, K. W. C. Kwock

The discovery of two-dimensional (2D) systems hosting intrinsic long-range magnetic order represents a seminal addition to the rich physical landscape of van der Waals (vdW) materials. CrI3 has emerged as perhaps the most salient example, as the interdependence of crystalline structure and magnetic order, along with strong light-matter interactions provides