September 2020 arXiv papers — page 6

Sijin Kim, Namhyuk Ahn, Kyung-Ah Sohn

In recent years, deep learning-based methods have been successfully applied to the image distortion restoration tasks. However, scenarios that assume a single distortion only may not be suitable for many real-world applications. To deal with such cases, some studies have proposed sequentially combined distortions datasets. Viewing in a different point of com

S. Amiri, C. A. Volkert, R. L. C. Vink

We present Molecular Dynamics simulations of one- and two-dimensional bead-spring models sliding on incommensurate substrates. We investigate how sliding friction is affected by interaction anharmonicity and structural defects. In their absence, we confirm earlier findings, namely, that at special resonance sliding velocities, friction is maximal. When slidi

Nektarios Aslanidis, Aurelio F. Bariviera, Alejandro Perez-Laborda

This paper studies the dynamic market linkages among cryptocurrencies during August 2015 - July 2020 and finds a substantial increase in market linkages for both returns and volatilities. We use different methodologies to check the different aspects of market linkages. Financial and regulatory implications are discussed.

Achiya Jerbi, Roei Herzig, Jonathan Berant, Gal Chechik

Object detection is a fundamental task in computer vision, requiring large annotated datasets that are difficult to collect, as annotators need to label objects and their bounding boxes. Thus, it is a significant challenge to use cheaper forms of supervision effectively. Recent work has begun to explore image captions as a source for weak supervision, but to

Diane Maclagan, Felipe Rincón

Tropical ideals, introduced in arXiv:1609.03838, define subschemes of tropical toric varieties. We prove that the top-dimensional parts of their varieties are balanced polyhedral complexes of the same dimension as the ideal. This means that every subscheme of a tropical toric variety defined by a tropical ideal has an associated class in the Chow ring of the

Ke Hu, Longqing Yi, Tünde Fülöp

When a relativistic, femtosecond laser pulse enters a waveguide, the pulse energy is coupled into waveguide optical modes. The longitudinal laser field effectively accelerates electrons along the axis of the channel, while the asymmetric transverse electromagnetic fields tend to expel fast electrons radially outwards. At the exit of the waveguide, the $\sim$

Alexander Mathiasen, Frederik Hvilshøj

Orthogonal weight matrices are used in many areas of deep learning. Much previous work attempt to alleviate the additional computational resources it requires to constrain weight matrices to be orthogonal. One popular approach utilizes *many* Householder reflections. The only practical drawback is that many reflections cause low GPU utilization. We mitigate

Chaosheng Dong, Bo Zeng

Inverse multiobjective optimization provides a general framework for the unsupervised learning task of inferring parameters of a multiobjective decision making problem (DMP), based on a set of observed decisions from the human expert. However, the performance of this framework relies critically on the availability of an accurate DMP, sufficient decisions of

Francesco Liberati, Andrea Tortorelli, Cesar Mazquiaran, Muhammad Imran

This paper discusses the problem of assembly line control and introduces an optimal control formulation that can be used to improve the performance of the assembly line, in terms of cycle time minimization, resources' utilization, etc. A deterministic formulation of the problem is introduced, based on mixed-integer linear programming. A simple numerical

Jurriaan J. J. Gillissen, Christopher Ness

Under inhomogeneous flow, dense suspensions exhibit complex behaviour that violates the conventional homogenous rheology. Specifically, one finds flowing regions with a macroscopic friction coefficient below the yielding criterion, and volume fraction above the jamming criterion. We demonstrate the underlying physics by incorporating shear rate fluctuations

Yingxue Pang, Xin Li, Xin Jin, Yaojun Wu

Single image super-resolution (SISR) aims to recover the high-resolution (HR) image from its low-resolution (LR) input image. With the development of deep learning, SISR has achieved great progress. However, It is still a challenge to restore the real-world LR image with complicated authentic degradations. Therefore, we propose FAN, a frequency aggregation n

Mark A. Peletier, D. R. Michiel Renger

We study the convergence of a sequence of evolution equations for measures supported on the nodes of a graph. The evolution equations themselves can be interpreted as the forward Kolmogorov equations of Markov jump processes, or equivalently as the equations for the concentrations in a network of linear reactions. The jump rates or reaction rates are divided

Chen Shen, Qiang Gao, Nuno M. Fortunato, Harish K. Singh

Based on high-throughput density functional theory calculations, we performed screening for stable magnetic MAB compounds and predicted potential strong magnets for permanent magnet and magnetocaloric applications. The thermodynamical, mechanical, and dynamical stabilities are systematically evaluated, resulting in 21 unreported compounds on the convex hull,

C. Aiswarya, Paul Gastin

We consider weighted tiling systems to represent functions from graphs to a commutative semiring such as the Natural semiring or the Tropical semiring. The system labels the nodes of a graph by its states, and checks if the neighbourhood of every node belongs to a set of permissible tiles, and assigns a weight accordingly. The weight of a labeling is the sem

Cheng-Jian Xiao, Dian-Yong Chen, Yu-Bing Dong, Guang-Wei Meng

In this work, we investigated the decays of the fully open-flavor tetraquark state $X_0(2900)$ which was observed by the LHCb Collaboration very recently. Here, the $X_0(2900)$ was assigned as a $S-$wave $\bar D^\ast K^\ast$ hadronic molecule with $I=0$, and the effective lagrangian approach was applied to estimate the partial decay widths. Moreover, we also

Sinuo Liu, Xiaokun Wang, Xiaojuan Ban, Yanrui Xu

A major issue in Smoothed Particle Hydrodynamics (SPH) approaches is the numerical dissipation during the projection process, especially under coarse discretizations. High-frequency details, such as turbulence and vortices, are smoothed out, leading to unrealistic results. To address this issue, we introduce a Vorticity Refinement (VR) solver for SPH fluids

Giovanni Di Fratta, Ansgar Jüngel, Dirk Praetorius, Valeriy Slastikov

In this paper, we consider spin-diffusion Landau-Lifshitz-Gilbert equations (SDLLG), which consist of the time-dependent Landau-Lifshitz-Gilbert (LLG) equation coupled with a time-dependent diffusion equation for the electron spin accumulation. The model takes into account the diffusion process of the spin accumulation in the magnetization dynamics of ferrom

Yimian Dai, Yiquan Wu, Fei Zhou, Kobus Barnard

Single-frame infrared small target detection remains a challenge not only due to the scarcity of intrinsic target characteristics but also because of lacking a public dataset. In this paper, we first contribute an open dataset with high-quality annotations to advance the research in this field. We also propose an asymmetric contextual modulation module speci

Muxi Li, Mao Sheng

We provide a Hodge theoretical characterization of the set of algebraic numbers which arises from the complete list, due to A. Beauville, of semistable families of elliptic curves over $\mathbb{P}^1$ with four singular fibers. Our technical innovation is the analysis of the periodicity of the uniformizing Higgs bundle attached to $\mathbb{P}^1$ minus four po

J. Hagelberg, N. Engler, C. Fontanive, S. Daemgen

Recent surveys indicate that planets in binary systems are more abundant than previously thought, which is in agreement with theoretical work on disc dynamics and planet formation in binaries. In order to measure the abundance and physical characteristics of wide-orbit giant exoplanets in binary systems, we have designed the 'VIsual Binary Exoplanet surv

Hiroyuki Abe, Shuntaro Aoki, Yu Asai, Yutaka Sakamura

We pursue the time evolution of the domain walls in 5D gravitational theory with a compact extra dimension by numerical calculation. In order to avoid a kink-antikink pair that decays into the vacuum, we introduce a topological winding in the field space. In contrast to the case of non-gravitational theories, there is no static domain-wall solution in the se

Aleš Berkopec

In this article we present the following hypothesis: thunder-cell ejects highly energetic protons, each of which creates a tree-structure of weakly ionized trajectories that can develop into a lightning channel. The tree-structure and the channel have the same geometry so the mean free path of a proton corresponds to the average length of the channel between

Piyush Yadav, Edward Curry

Multimedia data is highly expressive and has traditionally been very difficult for a machine to interpret. Middleware systems such as complex event processing (CEP) mine patterns from data streams and send notifications to users in a timely fashion. Presently, CEP systems have inherent limitations to process multimedia streams due to its data complexity and

Deniz Beker, Hiroharu Kato, Mihai Adrian Morariu, Takahiro Ando

3D object detection from monocular images is an ill-posed problem due to the projective entanglement of depth and scale. To overcome this ambiguity, we present a novel self-supervised method for textured 3D shape reconstruction and pose estimation of rigid objects with the help of strong shape priors and 2D instance masks. Our method predicts the 3D location

Dominik Schiller, Silvan Mertes, Elisabeth André

Traditional approaches to automatic emotion recognition are relying on the application of handcrafted features. More recently however the advent of deep learning enabled algorithms to learn meaningful representations of input data automatically. In this paper, we investigate the applicability of transferring knowledge learned from large text and audio corpor

Mao Sheng, Jilong Tong

The notion of Higgs-de Rham flows was introduced by Lan-Sheng-Zuo, as an analogue of Yang-Mills-Higgs flows in the complex nonabelian Hodge theory. In this short note we investigate a small part of this theory, and study those Higgs-de Rham flows which are of level zero. We improve the original definition of level-zero Higgs-de Rham flows (which works for ge

M. Fiori, L. Zampieri, A. Burtovoi, P. Caraveo

SNR G0.9+0.1 is a well known source in the direction of the Galactic Center composed by a Supernova Remnant (SNR) and a Pulsar Wind Nebula (PWN) in the core. We investigate the potential of the future Cherenkov Telescope Array (CTA), simulating observations of SNR G0.9+0.1. We studied the spatial and spectral properties of this source and estimated the syste

Narjes Torabi, Nimar S. Arora, Emma Yu, Kinjal Shah

Online Social Networks (OSNs) provide a platform for users to share their thoughts and opinions with their community of friends or to the general public. In order to keep the platform safe for all users, as well as to keep it compliant with local laws, OSNs typically create a set of community standards organized into policy groups, and use Machine Learning (

Álvaro del Pino, Tobias Shin

Let $ξ$ be an analytic bracket-generating distribution. We show that the subspace of germs that are singular (in the sense of Control Theory) has infinite codimension within the space of germs of smooth curves tangent to $ξ$. We formalise this as an asymptotic statement about finite jets of tangent curves. This solves, in the analytic setting, a conjecture o

Stevan Andrić, Tijana Tomašević-Ilić, Marko V. Bošković, Milija Sarajlić

Humidity sensing is important to a variety of technologies and industries, ranging from environmental and industrial monitoring to medical applications. Although humidity sensors abound, few available solutions are thin, transparent, compatible with large-area sensor production and flexible, and almost none are fast enough to perform human respiration monito

Kuno Kurzhals, Michael Burch, Daniel Weiskopf

Technical progress in hardware and software enables us to record gaze data in everyday situations and over long time spans. Among a multitude of research opportunities, this technology enables visualization researchers to catch a glimpse behind performance measures and into the perceptual and cognitive processes of people using visualization techniques. The

Prashant Goswami, Christopher Batty

This paper presents novel and efficient strategies to spatially adapt the amount of computational effort applied based on the local dynamics of a free surface flow, for both classic weakly compressible SPH (WCSPH) and predictive-corrective incompressible SPH (PCISPH). Using a convenient and readily parallelizable block-based approach, different regions of th

Hans Vanrompay, Alexander Skorikov, Eva Bladt, Armand Béché

Electron tomography is a widely used experimental technique for analyzing nanometer-scale structures of a large variety of materials in three dimensions. Unfortunately, the acquisition of conventional electron tomography tilt series can easily take up one hour or more, depending on the complexity of the experiment. Using electron tomography, it is therefore

Argyrios Christodoulou

This article concerns the locus of all locally constant $\mathrm{SL}(2,\mathbb{R})$-valued cocycles that are uniformly hyperbolic, called the hyperbolic locus. Using the theory of semigroups of Möbius transformations we introduce a new locus in $\mathrm{SL}(2,\mathbb{R})^N$ which allows us to study the complement of the hyperbolic locus. Our results answer a

Zihan Liu, Genta Indra Winata, Peng Xu, Zhaojiang Lin

Despite the promising results of current cross-lingual models for spoken language understanding systems, they still suffer from imperfect cross-lingual representation alignments between the source and target languages, which makes the performance sub-optimal. To cope with this issue, we propose a regularization approach to further align word-level and senten

Aravind Krishnamoorthy, Nitish Baradwaj, Aiichiro Nakano, Rajiv K. Kalia

Engineering thermal transport in two dimensional materials, alloys and heterostructures is critical for the design of next-generation flexible optoelectronic and energy harvesting devices. Direct experimental characterization of lattice thermal conductivity in these ultra-thin systems is challenging and the impact of dopant atoms and hetero-phase interfaces,

Tome Eftimov, Gorjan Popovski, Quentin Renau, Peter Korosec

Automated per-instance algorithm selection and configuration have shown promising performances for a number of classic optimization problems, including satisfiability, AI planning, and TSP. The techniques often rely on a set of features that measure some characteristics of the problem instance at hand. In the context of black-box optimization, these features

Yaming Hao, Yefei Li, Jianxiang Wu, Jinling Wang

NiFe oxyhydroxide is one of the most promising oxygen evolution reaction (OER) catalysts for renewable hydrogen production, and deciphering the identity and reactivity of the oxygen intermediates on its surface is a key challenge but is critical to understanding the OER mechanism as well as designing water-splitting catalysts with higher efficiencies. Here,

Yoonho Boo, Sungho Shin, Jungwook Choi, Wonyong Sung

The quantization of deep neural networks (QDNNs) has been actively studied for deployment in edge devices. Recent studies employ the knowledge distillation (KD) method to improve the performance of quantized networks. In this study, we propose stochastic precision ensemble training for QDNNs (SPEQ). SPEQ is a knowledge distillation training scheme; however,

Chao Wang, Zan Li, Gen Xiang Xia, Jia Shi

The secure transmission of confidential information in cellular vehicle-to-everything (C-V2X) communication networks is vitally important for user's personal safety. However, for C-V2X there have not been much studies on the physical layer security (PLS). Since artificial noise (AN) and secure beamforming are popular PLS techniques for cellular communica

Md Delowar Hossain, Muhammad Ashad Kabir, Adnan Anwar, Md Zahidul Islam

Autism Spectrum Disorder (ASD), which is a neuro development disorder, is often accompanied by sensory issues such an over sensitivity or under sensitivity to sounds and smells or touch. Although its main cause is genetics in nature, early detection and treatment can help to improve the conditions. In recent years, machine learning based intelligent diagnosi

Rohit Sharma, Marina Battaglia, Yingjie Luo, Bin Chen

Solar flares are sudden energy release events in the solar corona, resulting from magnetic reconnection, that accelerates particles and heats the ambient plasma. During a flare, there are often multiple, temporally and spatially separated individual energy release episodes that can be difficult to resolve depending on the observing instrument. We present mul

Leonardo Colombo, Patricio Moreno, Mengbin Ye, Hector Garcia de Marina

A multi-agent system designed to achieve distance-based shape control with flocking behavior can be seen as a mechanical system described by a Lagrangian function and subject to additional external forces. Forced variational integrators are given by the discretization of Lagrange-d'Alembert principle for systems subject to external forces, and have prove

M. Masuko, R. Yoshimi, A. Tsukazaki, M. Kawamura

We report a systematic study on the growth conditions of Sn$_{1-x}$In$_x$Te thin films by molecular beam epitaxy for maximization of superconducting transition temperature $T_\mathrm{c}$. Careful tuning of the flux ratios of Sn, In, and Te enables us to find an optimum condition for substituting rich In content ($x$ = 0.66) into Sn site in a single phase of

Q. Meng, E. Hiyama, A. Hosaka, M. Oka

Bound states of double-heavy tetraquarks are studied in a constituent quark model. Two bound states are found for isospin and spin-parity I(J^P ) = 0(1^+) in the bb\bar{u}\bar{d} channel. One is deeply bound and compact made of colored diquarks, while the other is shallow and extended as a BB^* molecule. The former agrees well with lattice QCD results. A sys

J. Larrea Jiménez, S. P. G. Crone, E. Fogh, M. E. Zayed

At the familiar liquid-gas phase transition in water, the density jumps discontinuously at atmospheric pressure, but the line of these first-order transitions defined by increasing pressures terminates at the critical point, a concept ubiquitous in statistical thermodynamics. In correlated quantum materials, a critical point was predicted and measured termin

Miguel A. Martin-Delgado

A hypothetical exclusion principle for quantum particles is introduced that generalizes the exclusion and inclusion principles for fermions and bosons, respectively: the correlated exclusion principle. The sum-free condition for Schur numbers can be read off as a form of exclusion principle for quantum particles. Consequences of this interpretation are analy

Juan Zhang, Xiaobo Li, Mingyu Ge, Haisheng Zhao

Insight-HXMT, the first X-ray astronomical satellite in China, aims to reveal new sources in the Galaxy and to study fundamental physics of X-ray binaries from 1\,keV to 250\,keV. It has three collimated telescopes, the High Energy X-ray telescope (HE), the Medium Energy X-ray telescope (ME) and the Low Energy X-ray telescope (LE). Before the launch, in-orbi

Yao-Qiang Li

Let $(t_n)_{n\ge0}$ be the well konwn $\pm1$ Thue-Morse sequence $$+1,-1,-1,+1,-1,+1,+1,-1,\cdots.$$ Since the 1982-1983 work of Coquet and Dekking, it is known that $\sum_{k<n}t_ke^\frac{2kπi}{3}$ is strongly related to the famous Koch curve. As a natural generalization, for integer $m\ge1$, we use $\sum_{k<n}δ_ke^\frac{2kπi}{m}$ to define generalized Koch

Arash Akbarinia, Raquel Gil-Rodríguez, Alban Flachot, Matteo Toscani

Vector quantised variational autoencoders (VQ-VAE) are characterised by three main components: 1) encoding visual data, 2) assigning $k$ different vectors in the so-called embedding space, and 3) decoding the learnt features. While images are often represented in RGB colour space, the specific organisation of colours in other spaces also offer interesting fe

A. Galiano, F. Dirri, E. Palomba, A. Longobardo

In order to investigate the causes of different spectral slope in ccps, different grain-sizes of Ceres analogue mixtures were produced, heated to remove absorption of atmospheric water, and spectrally analyzed. First, the end-members which compose the Ceres surface (using the antigorite as Mg-phyllosilicate, the NH4-montmorillonite as NH4-phyllosilicate, the

Cong-Hua Yan, Ming Li, Xin-Biao Xu, Yan-Lei Zhang

Single-photon transport in non-ideal chiral photon-atom interaction structures generally contains information backflow and thus limits the capabilities to transfer information between distant emitters in cascaded quantum networks. Here, in the non-ideal chiral case, a V -type atom coupled to a waveguide is proposed to realize completely unidirectional transm

Rongjiang Nie, Li Chen, Nan Zhao, Yunfei Chen

Time-division-duplexing massive multiple-input multiple-output (MIMO) systems estimate the channel state information (CSI) by leveraging the uplink-downlink channel reciprocity, which is no longer valid when the mismatch arises from the asymmetric uplink and downlink radio frequency (RF) chains. Existing works treat the reciprocity mismatch as constant for s

Andrea Lincoln, Adam Polak, Virginia Vassilevska Williams

The most studied linear algebraic operation, matrix multiplication, has surprisingly fast $O(n^ω)$ time algorithms for $ω<2.373$. On the other hand, the $(\min,+)$ matrix product which is at the heart of many fundamental graph problems such as APSP, has received only minor improvements over its brute-force cubic running time and is widely conjectured to requ

Eneko Osaba, Esther Villar-Rodriguez, Javier Del Ser

The main goal of the multitasking optimization paradigm is to solve multiple and concurrent optimization tasks in a simultaneous way through a single search process. For attaining promising results, potential complementarities and synergies between tasks are properly exploited, helping each other by virtue of the exchange of genetic material. This paper is f

A. Raponi, M. Ciarniello, F. Capaccioni, V. Mennella

The ESA Rosetta mission has acquired unprecedented measurements of comet 67/P-Churyumov-Gerasimenko (hereafter 67P) nucleus surface, whose composition, as determined by in situ and remote sensing instruments including VIRTIS (Visible, InfraRed and Thermal Imaging Spectrometer) appears to be made by an assemblage of ices, minerals, and organic material. We pe

Mark de Berg, Aleksandar Markovic, Seeun William Umboh

Let $P=\{p_0,\ldots,p_{n-1}\}$ be a set of points in $\mathbb{R}^d$, modeling devices in a wireless network. A range assignment assigns a range $r(p_i)$ to each point $p_i\in P$, thus inducing a directed communication graph $G_r$ in which there is a directed edge $(p_i,p_j)$ iff $\textrm{dist}(p_i, p_j) \leq r(p_i)$, where $\textrm{dist}(p_i,p_j)$ denotes th

Yiran Wang, Eric Chung, Lina Zhao

In this paper, we develop the constraint energy minimization generalized multiscale finite element method (CEM-GMsFEM) in mixed formulation applied to parabolic equations with heterogeneous diffusion coefficients. The construction of the method is based on two multiscale spaces: pressure multiscale space and velocity multiscale space. The pressure space is c

Aravind Krishnamoorthy, Ankit Mishra, Deepak Kamal, Sungwook Hong

Parameterization of interatomic forcefields is a necessary first step in performing molecular dynamics simulations. This is a non-trivial global optimization problem involving quantification of multiple empirical variables against one or more properties. We present EZFF, a lightweight Python library for parameterization of several types of interatomic forcef

Tianyue Lu, Haiyang Pan, Mingyu Chen

In recent years, memory wall has been a great performance bottleneck of computer system. To overcome it, Non-Volatile Main Memory (NVMM) technology has been discussed widely to provide a much larger main memory capacity. Last year, Intel released AEP Optane DIMM, which provides hundreds of GB capacity as a promising replacement of traditional DRAM memory. Bu

Hui Zeng, Jianrui Cai, Lida Li, Zisheng Cao

Recent years have witnessed the increasing popularity of learning based methods to enhance the color and tone of photos. However, many existing photo enhancement methods either deliver unsatisfactory results or consume too much computational and memory resources, hindering their application to high-resolution images (usually with more than 12 megapixels) in

Oguz Selvitopi, Saliya Ekanayake, Giulia Guidi, Georgios Pavlopoulos

Identifying similar protein sequences is a core step in many computational biology pipelines such as detection of homologous protein sequences, generation of similarity protein graphs for downstream analysis, functional annotation and gene location. Performance and scalability of protein similarity searches have proven to be a bottleneck in many bioinformati

Laura Matzen, Kristin Divis, Deborah Cronin, Michael Haass

One of the major challenges for evaluating the effectiveness of data visualizations and visual analytics tools arises from the fact that different users may be using these tools for different tasks. In this paper, we present a simple example of how different tasks lead to different patterns of attention to the same underlying data visualizations. We argue th

Grigorii Guz, Peyman Bateni, Darius Muglich, Giuseppe Carenini

This paper evaluates the utility of Rhetorical Structure Theory (RST) trees and relations in discourse coherence evaluation. We show that incorporating silver-standard RST features can increase accuracy when classifying coherence. We demonstrate this through our tree-recursive neural model, namely RST-Recursive, which takes advantage of the text&#39;s RST fe

Runze Chen, Chen Li, Yu Li, James J. Miles

Magnetic skyrmions have attracted considerable interest, especially after their recent experimental demonstration at room temperature in multilayers. The robustness, nanoscale size and non-volatility of skyrmions have triggered a substantial amount of research on skyrmion-based low-power, ultra-dense nanocomputing and neuromorphic systems such as artificial

Molei Liu, Yi Zhang, Doudou Zhou

We propose double/debiased machine learning approaches to infer (at the parametric rate) the parametric component of a logistic partially linear model with the binary response following a conditional logistic model of a low dimensional linear parametric function of some key (exposure) covariates and a nonparametric function adjusting for the confounding effe

Sharmin Akter, Yoh Yamamoto, Carlos M. Diaz, Koblar A. Jackson

We studied the effect of self-interaction error (SIE) on the static dipole polarizabilities of water clusters modelled with three increasingly sophisticated, non-empirical density functional approximations (DFAs), viz. the local spin density approximation (LDA), the Perdew-Burke-Ernzherof (PBE) generalized-gradient approximation (GGA), and the strongly const

Reda Khalaf, Mireille Makary

Recent studies showed a huge interest in social networks sentiment analysis. Twitter, which is a microblogging service, can be a great source of information on how the users feel about a certain topic, or what their opinion is regarding a social, economic and even political matter. On October 17, Lebanon witnessed the start of a revolution; the LebanonUprisi

Thomas Navidi, Chloe Leblanc, Abbas El Gamal, Ram Rajagopal

Reliability and voltage quality in distribution networks have been achieved via a combination of transformer power rating satisfaction and voltage management asset control. To maintain reliable operation under this paradigm, however, future grids with deep DER penetrations would require costly equipment upgrades. These upgrades can be mitigated via judicious

Uday Shankar Shanthamallu, Jayaraman J. Thiagarajan, Andreas Spanias

Graph Neural Networks (GNNs), a generalization of neural networks to graph-structured data, are often implemented using message passes between entities of a graph. While GNNs are effective for node classification, link prediction and graph classification, they are vulnerable to adversarial attacks, i.e., a small perturbation to the structure can lead to a no

Jayaraman J. Thiagarajan, Vivek Narayanaswamy, Rushil Anirudh, Peer-Timo Bremer

With increasing reliance on the outcomes of black-box models in critical applications, post-hoc explainability tools that do not require access to the model internals are often used to enable humans understand and trust these models. In particular, we focus on the class of methods that can reveal the influence of input features on the predicted outputs. Desp

Xichen Shi, Michael O&#39;Connell, Soon-Jo Chung

We present a delay-compensating control method that transforms exponentially stabilizing controllers for an undelayed system into a sample-based predictive controller with numerical integration. Our method handles both first-order and transport delays in actuators and trades-off numerical accuracy with computation delay to guaranteed stability under hardware

Bindya Venkatesh, Jayaraman J. Thiagarajan

Deep predictive models rely on human supervision in the form of labeled training data. Obtaining large amounts of annotated training data can be expensive and time consuming, and this becomes a critical bottleneck while building such models in practice. In such scenarios, active learning (AL) strategies are used to achieve faster convergence in terms of labe

Anousheh Gholami, Nariman Torkzaban, John S. Baras, Chrysa Papagianni

Unmanned Aerial Vehicles (UAVs) have been extensively utilized to provide wireless connectivity in rural and under-developed areas, enhance network capacity and provide support for peaks or unexpected surges in user demand, mainly due to their fast deployment, cost-efficiency and superior communication performance resulting from Line of Sight (LoS)-dominated

Weicheng Ma, Ruibo Liu, Lili Wang, Soroush Vosoughi

Authorship identification tasks, which rely heavily on linguistic styles, have always been an important part of Natural Language Understanding (NLU) research. While other tasks based on linguistic style understanding benefit from deep learning methods, these methods have not behaved as well as traditional machine learning methods in many authorship-based tas

Satoshi Tajima, Daigorou Hirai, Yuto Kinoshita, Masashi Tokunaga

The 5d pyrochlore oxide Cd2Re2O7 exhibits successive phase transitions from a cubic pyrochlore structure (phase I) to a tetragonal structure without inversion symmetry below Ts1 of ~200 K (phase II) and further to another noncentrosymmetric tetragonal structure below Ts2 of ~120 K (phase III). The two low-temperature phases may be characterized by odd-parity

Jason Behrstock, Victor Falgas-Ravry, Tim Susse

Given a graph $Γ$, its auxiliary \emph{square-graph} $\square(Γ)$ is the graph whose vertices are the non-edges of $Γ$ and whose edges are the pairs of non-edges which induce a square (i.e., a $4$-cycle) in $Γ$. We determine the threshold edge-probability $p=p_c(n)$ at which the Erd{\H o}s--Rényi random graph $Γ=Γ_{n,p}$ begins to asymptotically almost surel

Shay Deutsch, Stefano Soatto

We introduce an unsupervised graph embedding that trades off local node similarity and connectivity, and global structure. The embedding is based on a generalized graph Laplacian, whose eigenvectors compactly capture both network structure and neighborhood proximity in a single representation. The key idea is to transform the given graph into one whose weigh

Jianjun Yuan

In the era of the big data, we create and collect lots of data from all different kinds of sources: the Internet, the sensors, the consumer market, and so on. Many of the data are coming sequentially, and would like to be processed and understood quickly. One classic way of analyzing data is based on batch processing, in which the data is stored and analyzed

Kunpei Nojiri, Naoko Ashikawa, Yasuhiro Suzuki, Yaowei Yu

The characteristics of wall recycling with different divertor configurations were investigated in this study, focusing on the observations of the spatial distributions of deuterium atomic emissions in the Balmer series (D_α, D_β, D_γ, and D_δ) with different magnetic field configurations in the Experimental Advanced Superconducting Tokamak. The observed D_α

Dai-Nam Le, Van-Hoang Le, Pinaki Roy

The strain engineering technique allows us to alter the electronic properties of graphene in various ways. Within the continuum approximation, the influences of strain result in the appearance of a pseudo-gauge field and modulated Fermi velocity. In this study, we investigate theoretically the effect of linear uniaxial tensile strain and/or stress, which mak

Junhyeong Park, Jun-Sung Park, Seong-Ook Park

As the threats of small drones increase, not only the detection but also the classification of small drones has become important. Many recent studies have applied an approach to utilize the micro-Doppler signature (MDS) for the small drone classification by using frequency modulated continuous wave (FMCW) radars. In this letter, we propose a novel method to

Daniel H. Lee, Tzyy-Ping Jung

The objective of this study is to develop and use a virtual reality game as a tool to assess the effects of realistic stress on the behavioral and physiological responses of participants. The game is based on a popular Steam game called Keep Talking Nobody Explodes, where the player collaborates with another person to defuse a bomb. Varying levels of difficu

Bin Zhang, Shengjie Zhao, Rongqing Zhang

As one of the fundamental tasks in computer vision, semantic segmentation plays an important role in real world applications. Although numerous deep learning models have made notable progress on several mainstream datasets with the rapid development of convolutional networks, they still encounter various challenges in practical scenarios. Unsupervised adapti

Meir Shimon, Yoel Rephaeli

The cosmic microwave background (CMB) temperature, $T$, surely the most precisely measured cosmological parameter, has been inferred from {\it local} measurements of the blackbody spectrum to an exquisite precision of 1 part in $\sim 4700$. On the other hand, current precision allows inference of other basic cosmological parameters at the $\sim 1\%$ level fr

Junhyeong Park, Dae-Hwan Jung, Seong-Ook Park

Frequency modulated continuous wave (FMCW) radar is emerging as a trendy radar system for synthetic aperture radar (SAR). This letter proposes a novel method for the extraction of the SAR image with the FMCW radar. The proposed method can improve the quality of the SAR image. For the verification, we built an automobile SAR (AutoSAR) system and conducted exp

Dongjie Zhu, Haiwen Du, Yundong Sun, Zhaoshuo Tian

Cache prefetching technology has become the mainstream data access optimization strategy in the data centers. However, the rapidly increasing of unstructured data generates massive pairwise access relationships, which can result in a heavy computational burden for the existing prefetching model and lead to severe degradation in the performance of data access

Hyun Dong Lee, Seongmin Lee, U Kang

How can we effectively regularize BERT? Although BERT proves its effectiveness in various downstream natural language processing tasks, it often overfits when there are only a small number of training instances. A promising direction to regularize BERT is based on pruning its attention heads based on a proxy score for head importance. However, heuristic-base

Amr A. Adly

In a fast-changing technology-driven era, drafting an implementable strategic roadmap to achieve economic prosperity becomes a real challenge. Although the national and international strategic development plans may vary, they usually target the improvement of the quality of living standards through boosting the national GDP per capita and the creation of dec

Yoonjae Lee, Efstathios Bakolas

We propose a decentralized solution for a pursuit-evasion game involving a heterogeneous group of rational (selfish) pursuers and a single evader based on the framework of potential games. In the proposed game, the evader aims to delay (or, if possible, avoid) capture by any of the pursuers whereas each pursuer tries to capture the latter only if this is to

Chu-ran Wang, Jing Li, Fandong Zhang, Xinwei Sun

Mammogram benign or malignant classification with only image-level labels is challenging due to the absence of lesion annotations. Motivated by the symmetric prior that the lesions on one side of breasts rarely appear in the corresponding areas on the other side, given a diseased image, we can explore a counterfactual problem that how would the features have

Yiqing Huang, Jiansheng Chen

Existing image captioning models are usually trained by cross-entropy (XE) loss and reinforcement learning (RL), which set ground-truth words as hard targets and force the captioning model to learn from them. However, the widely adopted training strategies suffer from misalignment in XE training and inappropriate reward assignment in RL training. To tackle t

Grace H. Zhang, David R. Nelson

Dislocation pileups directly impact the material properties of crystalline solids through the arrangement and collective motion of interacting dislocations. We study the statistical mechanics of these ordered defect structures embedded in two dimensional crystals, where the dislocations themselves form one-dimensional lattices. In particular, pileups exempli

Yanyong Hong

Let $R\subseteq E$ be two Lie conformal algebras and $Q$ be a given complement of $R$ in $E$. Classifying complements problem asks for describing and classifying all complements of $R$ in $E$ up to an isomorphism. It is known that $E$ is isomorphic to a bicrossed product of $R$ and $Q$. We show that any complement of $R$ in $E$ is isomorphic to a deformation

Chang Liu, Fei Liu, Hao Li, Junsheng Chen

Two-dimensional covalent organic frameworks (2D-COFs) are an emerging family of catalytical materials with well-defined molecular structures. The stacking of 2D nanosheets and large intrinsic bandgaps significantly impair their performance. Here, we report coaxial one-dimensional van der Waals heterostructures (1D vdWHs) comprised of a carbon nanotube (CNT)

Shamil Chollampatt, Raymond Hendy Susanto, Liling Tan, Ewa Szymanska

Automatic post-editing (APE) aims to improve machine translations, thereby reducing human post-editing effort. APE has had notable success when used with statistical machine translation (SMT) systems but has not been as successful over neural machine translation (NMT) systems. This has raised questions on the relevance of APE task in the current scenario. Ho

Xingjie Fan, Dawei Wang, Julian Cheng, Jingkai Yang

Few-mode fiber is a significant component of free-space optical communication at the receiver to obtain achievable high coupling efficiency. A theoretical coupling model from the free-space optical communication link to a few-mode fiber is proposed based on a scale-adapted set of Laguerre-Gaussian modes. It is found that the coupling efficiency of various mo

Diana C. Rivera-Agudelo, S. L. Tostado

The Tri-Bi-Maximal pattern has been long investigated as the symmetric scenario that lies behind the neutrino mixing matrix. It predicts a null reactor angle and hence forbids $CP$ violation in the lepton sector, which is in contrast to the current experimental determinations. We explore different deviations from this pattern to restore the compatibility wit

Liang Du, Haiying Zhang, Xin Ren, Xiaolin Lv

Multiple kernel methods based on k-means aims to integrate a group of kernels to improve the performance of kernel k-means clustering. However, we observe that most existing multiple kernel k-means methods exploit the nonlinear relationship within kernels, whereas the local manifold structure among multiple kernel space is not sufficiently considered. In thi

Sunil K. Karna, D. Tristant, J. K. Hebert, G. Cao

An investigation of the structural, magnetic, thermodynamic, and charge transport properties of non-centrosymmetric hexagonal ScFeGe reveals it to be an anisotropic metal with a transition to a weak itinerant incommensurate helimagnetic state below $T_N = 36$ K. Neutron diffraction measurements discovered a temperature and field independent helical wavevecto