March 2020 arXiv papers — page 95

Farah Karim, Maria-Esther Vidal, Sören Auer

Knowledge graphs have become a popular formalism for representing entities and their properties using a graph data model, e.g., the Resource Description Framework (RDF). An RDF graph comprises entities of the same type connected to objects or other entities using labeled edges annotated with properties. RDF graphs usually contain entities that share the same

Yu Gao, Xintong Han, Xun Wang, Weilin Huang

Fine-grained image categorization is challenging due to the subtle inter-class differences.We posit that exploiting the rich relationships between channels can help capture such differences since different channels correspond to different semantics. In this paper, we propose a channel interaction network (CIN), which models the channel-wise interplay both wi

Absos Ali Shaikh, Chandan Kumar Mondal, Prosenjit Mandal

In this paper we have investigated some aspects of gradient $ρ$-Einstein Ricci soliton in a complete Riemannian manifold. First, we have proved that the compact gradient $ρ$-Einstein soliton is isometric to the Euclidean sphere by showing that the scalar curvature becomes constant. Second, we have showed that in a non-compact gradient $ρ$-Einstein soliton sa

Derek Reitz, Junxue Li, Wei Yuan, Jing Shi

We develop a low-temperature, long-wavelength theory for the interfacial spin Seebeck effect (SSE) in easy-axis antiferromagnets. The field-induced spin-flop (SF) transition of Néel order is associated with a qualitative change in SSE behavior: Below SF, there are two spin carriers with opposite magnetic moments, with the carriers polarized along the field f

Luca Parisi, Stefano Giorgini

We use exact Quantum Monte Carlo techniques to study the properties of quantum droplets in two-component bosonic mixtures with contact interactions in one spatial dimension. We systematically study the surface tension, the density profile and the breathing mode as a function of the number of particles in the droplet and of the ratio of coupling strengths bet

Michael Buchholz, Jan Strohbeck, Anna-Maria Adaktylos, Friedrich Vogl

Information and communication technology (ICT) is an enabler for establishing automated vehicles (AVs) in today's traffic systems. By providing complementary and/or redundant information via radio communication to the AV's perception by on-board sensors, higher levels of automated driving become more comfortable, safer, or even possible without inter

Oscar Rodriguez de Rivera, Antonio López-Quílez, Marta Blangiardo, Martyna Wasilewska

Forest fires are the outcome of a complex interaction between environmental factors, topography and socioeconomic factors (Bedia et al, 2014). Therefore, understand causality and early prediction are crucial elements for controlling such phenomenon and saving lives.The aim of this study is to build spatio-temporal model to understand causality of forest fire

Thomas Howson, Ineke De Moortel, Jack Reid

Aims. We investigate the formation of small scales and the dissipation of MHD wave energy through non-linear interactions of counter-propagating, phase-mixed Alfvenic waves in a complex magnetic field. Methods. We conducted fully 3-D, non-ideal MHD simulations of transverse waves in complex magnetic fields. Continuous wave drivers were imposed on the foot po

R. A. Bindu, A. A. Neloy, S. Alam, S. Siddique

This paper presents the design and integration of 3 Survivor, a rough terrain negotiable teleoperated mobile rescue and service robot. 3 Survivor is an improved version of two previously studied surveillance robots named Sigma 3 and Alpha N. In 3 Survivor, a modified double tracked with caterpillar mechanism is incorporated in the body design. A passive adju

S. Munoz, J. Ros, J. L. Escalona

The aim of this work is to develop a model-based methodology for monitoring lateral track irregularities based on the use of inertial sensors mounted on an in-service train. To this end, a gyroscope is used to measure the wheelset yaw angular velocity and two accelerometers are used to measure lateral acceleration of the wheelset and the bogie frame. Using a

Yiming Li, Changhong Fu, Ziyuan Huang, Yinqiang Zhang

Correlation filter-based tracking has been widely applied in unmanned aerial vehicle (UAV) with high efficiency. However, it has two imperfections, i.e., boundary effect and filter corruption. Several methods enlarging the search area can mitigate boundary effect, yet introducing undesired background distraction. Existing frame-by-frame context learning stra

Sascha Hunold, Bartłomiej Przybylski

We introduce the Scheduling.jl Julia package, which is intended for collaboratively conducting scheduling research and for sharing implementations of algorithms. It provides the fundamental building blocks for implementing scheduling algorithms following the three-field notation of Graham et al., i.e., it has functionality to describe machine environments, j

Marcel Klett, Nils Wentzell, Thomas Schäfer, Fedor Simkovic

We revisit the cellular dynamical mean-field theory (CDMFT) for the single band Hubbard model on the square lattice at half filling, reaching real-space cluster sizes of up to 9 x 9 sites. Using benchmarks against direct lattice diagrammatic Monte Carlo at high temperature, we show that the self-energy obtained from a cluster center focused extrapolation con

Lukas Failer, Piotr Minakowski, Thomas Richter

We study the impact of using fluid-structure interactions (FSI) to simulate blood flow in a large stenosed artery. We compare typical flow configurations using Navier-Stokes in a rigid geometry setting to a fully coupled FSI model. The relevance of vascular elasticity is investigated with respect to several questions of clinical importance. Namely, we study

Tarmo Uustalu, Niccolò Veltri, Noam Zeilberger

Szlachányi's skew monoidal categories are a well-motivated variation of monoidal categories in which the unitors and associator are not required to be natural isomorphisms, but merely natural transformations in a particular direction. We present a sequent calculus for skew monoidal categories, building on the recent formulation by one of the authors of a

Shuang Li, Jiaxi Jiang, Philipp Ruppel, Hongzhuo Liang

In this paper, we present a multimodal mobile teleoperation system that consists of a novel vision-based hand pose regression network (Transteleop) and an IMU-based arm tracking method. Transteleop observes the human hand through a low-cost depth camera and generates not only joint angles but also depth images of paired robot hand poses through an image-to-i

Luca Biasco, Luigi Chierchia

We consider a 1D mechanical system $$\bar {\mathtt H}(\mathtt P,\mathtt Q)=\mathtt P^2+\bar {\mathtt G}(\mathtt Q)$$ in action-angle variable $(\mathtt P,\mathtt Q)$ where $\bar {\mathtt G}$ is a $2π$-periodic analytic function with non degenerate critical points. Then, we consider a small analytic perturbation of $\bar {\mathtt H}$ of the form $${\mathtt H}

Asma Khatun, Sk. Golam Sarowar Hossain

Elder people consequence a variety of problems while living Activities of Daily Living (ADL) for the reason of age, sense, loneliness and cognitive changes. These cause the risk to ADL which leads to several falls. Getting real life fall data is a difficult process and are not available whereas simulated falls become ubiquitous to evaluate the proposed metho

Mohammad A. Hoque, Ashwin Rao, Sasu Tarkoma

Understanding network and application performance are essential for debugging, improving user experience, and performance comparison. Meanwhile, modern mobile systems are optimized for energy-efficient computation and communications that may limit the performance of network and applications. In recent years, several tools have emerged that analyze network pe

Olivera Kostoska, Viktor Stojkoski, Ljupco Kocarev

The expansion of global production networks has raised many important questions about the interdependence among countries and how future changes in the world economy are likely to affect the countries' positioning in global value chains. We are approaching the structure and lengths of value chains from a completely different perspective than has been ava

Markus Steck, Yuri A. Litvinov

Storage rings have been employed over three decades in various kinds of nuclear and atomic physics experiments with highly charged ions. Storage ring operation and precision physics experiments benefit from the availability of beam cooling which is common to nearly all facilities. The basic aspects of the storage ring components and the operation of the ring

Luisa Di Paola, Alessandro Giuliani

Coronaviruses are a class of virus responsible of the recent outbreak of Human Severe Acute Respiratory Syndrome. The molecular machinery behind the viral entry and thus infectivity is based on the formation of the complex of virus spike protein with the angiotensin-converting enzyme 2 (ACE2). The detection of putative allosteric sites on the viral spike pro

Yijun Yuan, Jiawei Hou, Andreas Nüchter, Sören Schwertfeger

In this work, we propose to learn local descriptors for point clouds in a self-supervised manner. In each iteration of the training, the input of the network is merely one unlabeled point cloud. On top of our previous work, that directly solves the transformation between two point sets in one step without correspondences, the proposed method is able to train

Debojoti Kuzur, Rupamoy Bhattacharyya, Ritam Mallick

Charged particles at the crust of compact stars may be ejected and accelerated by the electric field generated due to the rotation of the magnetized star. For neutron or hybrid stars, the negatively charged particles are usually electrons, and the positively charged particles are mainly protons and Iron. Whereas the existence of strange stars also includes t

Nicolas Riesterer, Daniel Brand, Marco Ragni

Understanding the fundamentals of human reasoning is central to the development of any system built to closely interact with humans. Cognitive science pursues the goal of modeling human-like intelligence from a theory-driven perspective with a strong focus on explainability. Syllogistic reasoning as one of the core domains of human reasoning research has see

Jing Wang, E. Athanassoula, Si-Yue Yu, Christian Wolf

Bars in disc-dominated galaxies are able to drive gas inflow inside the corotation radius, thus enhancing the central star formation rate (SFR). Previous work, however, has found that disc-dominated galaxies with centrally suppressed SFR frequently host a bar. Here we investigate possible causes for the suppression of central SFR in such cases. We compare ph

Steffen Haas, Florian Wilkens, Mathias Fischer

Public networks are exposed to port scans from the Internet. Attackers search for vulnerable services they can exploit. In large scan campaigns, attackers often utilize different machines to perform distributed scans, which impedes their detection and might also camouflage the actual goal of the scanning campaign. In this paper, we present a correlation algo

Primoz Potocnik, Micael Toledo

The theory of voltage graphs has become a standard tool in the study graphs admitting a semiregular group of automorphisms. We introduce the notion of a cyclic generalised voltage graph to extend the scope of this theory to graphs admitting a cyclic group of automorphism that may not be semiregular. We use this new tool to classify all cubic graphs admitting

Tara Abrishami, Maria Chudnovsky, Marcin Pilipczuk, Paweł Rzążewski

A hole in a graph is an induced cycle of length at least 4. A hole is long if its length is at least 5. By $P_t$ we denote a path on $t$ vertices. In this paper we give polynomial-time algorithms for the following problems: the Maximum Weight Independent Set problem in long-hole-free graphs, and the Feedback Vertex Set problem in $P_5$-free graphs. Each of t

Olaide Ayodeji Agbolade, Samson A. Oyetunji

The research presents a voice conversion model using coefficient mapping and neural network. Most previous works on parametric speech synthesis did not account for losses in spectral details causing over smoothing and invariably, an appreciable deviation of the converted speech from the targeted speaker. An improved model that uses both linear predictive cod

Dominique Beaini, Sofiane Achiche, Maxime Raison

Current research in convolutional neural networks (CNN) focuses mainly on changing the architecture of the networks, optimizing the hyper-parameters and improving the gradient descent. However, most work use only 3 standard families of operations inside the CNN, the convolution, the activation function, and the pooling. In this work, we propose a new family

Hitoshi Nakada, Wolfgang Steiner

We show the ergodicity of Tanaka-Ito type $α$-continued fraction maps and construct their natural extensions. We also discuss the relation between entropy and the size of the natural extension domain.

Elisa Davoli, Martin Kružík, Paolo Piovano, Ulisse Stefanelli

Starting from the three-dimensional setting, we derive a limit model of a thin magnetoelastic film by means of Γ-convergence techniques. As magnetization vectors are defined on the elastically deformed configuration, our model features both Lagrangian and Eulerian terms. This calls for qualifying admissible three-dimensional deformations of planar domains in

Iyas Ismail, Marc Simon, Francis Penent

MOSARIX is a collaborative project between three research group in Sorbonne University to build a x-ray spectrometer (2-5 keV) portable to large scale facilities with high efficiency and good resolution. X-ray spectroscopy and coincidences experiment are planned. A prototype with a single HADP crystal with von Hamos geometry has been tested (resolution and e

Yongho Shin, Kangsan Kim, Seungmin Lee, Hyung-Chan An

In the online bipartite matching with reassignments problem, an algorithm is initially given only one side of the vertex set of a bipartite graph; the vertices on the other side are revealed to the algorithm one by one, along with its incident edges. The algorithm is required to maintain a matching in the current graph, where the algorithm revises the matchi

Jose Blanchet, Renyuan Xu, Zhengyuan Zhou

In this paper, we consider online learning in generalized linear contextual bandits where rewards are not immediately observed. Instead, rewards are available to the decision-maker only after some delay, which is unknown and stochastic. We study the performance of two well-known algorithms adapted to this delayed setting: one based on upper confidence bounds

Ltaief Ben Ltaief, Mykola Shcherbinin, Suddhasattwa Mandel, Sivarama Krishnan

Alkali metal dimers attached to the surface of helium nanodroplets are found to be efficiently doubly ionized by electron transfer-mediated decay (ETMD) when photoionizing the helium droplets. This process is evidenced by detecting in coincidence two energetic ions created by Coulomb explosion and one low-kinetic energy electron. The kinetic energy spectra o

Julien Bichon, Maeva Paradis

We provide isomorphism results for Hopf algebras that are obtained as graded twistings of function algebras on finite groups by cocentral actions of cyclic groups. More generally , we also consider the isomorphism problem for finite-dimensional Hopf algebras fitting into abelian cocentral extensions. We apply our classification results to a number of concret

Wai Chun Wong, Wenyan Wang, Wang Tat Yau, Kin Hung Fung

We introduce topological theory of perfect isolation: perfect transmission from one side and total reflection from another side simultaneously. The theory provides an efficient approach for determining whether such a perfect isolation point exists within a finite parameter space. Herein, we demonstrate the theory using an example of a Lorentz non-reciprocal

Thomas Lartigue, Simona Bottani, Stephanie Baron, Olivier Colliot

Gaussian Graphical Models (GGM) are often used to describe the conditional correlations between the components of a random vector. In this article, we compare two families of GGM inference methods: nodewise edge selection and penalised likelihood maximisation. We demonstrate on synthetic data that, when the sample size is small, the two methods produce graph

Saravanan Ramanathan, Arvind Easwaran, Hyeonjoong Cho

In this paper we consider the problem of mixed-criticality (MC) scheduling of implicit-deadline sporadic task systems on a homogenous multiprocessor platform. Focusing on dual-criticality systems, algorithms based on the fluid scheduling model have been proposed in the past. These algorithms use a dual-rate execution model for each high-criticality task depe

Karine Bertin, Nicolas Klutchnikoff, Fabien Panloup, Maylis Varvenne

We build and study a data-driven procedure for the estimation of the stationary density f of an additive fractional SDE. To this end, we also prove some new concentrations bounds for discrete observations of such dynamics in stationary regime.

Xiao Wen, Lan Wen

We prove that every singular hyperbolic chain transitive set with a singularity does not admit the shadowing property. Using this result we show that if a star flow has the shadowing property on its chain recurrent set then it satisfies Axiom A and the no-cycle conditions; and that if a multisingular hyperbolic set has the shadowing property then it is hyper

Xiaozhe Gu, Arvind Easwaran

Systems in many safety-critical application domains are subject to certification requirements. In such a system, there are typically different applications providing functionalities that have varying degrees of criticality. Consequently, the certification requirements for functionalities at these different criticality levels are also varying, with very high

Yusuke Hashimoto, Koji Sato, Tom H. Johansen, Eiji Saitoh

Excitation and propagation dynamics of spin waves in an iron-based garnet film under out-of-plane magnetic field were investigated by time-resolved magneto-optical imaging. The experimental results and the following data analysis by phase-resolved spin-wave tomography reveal the excitation of spin waves triggered by photo-induced demagnetization (PID) along

Wagner Barreto-Souza, Vinícius D. Mayrink, Alexandre B. Simas

Beta regression has been extensively used by statisticians and practitioners to model bounded continuous data and there is no strong and similar competitor having its main features. A class of normalized inverse-Gaussian (N-IG) process was introduced in the literature, being explored in the Bayesian context as a powerful alternative to the Dirichlet process.

Shir Peleg, Amir Shpilka

In this work we prove a version of the Sylvester-Gallai theorem for quadratic polynomials that takes us one step closer to obtaining a deterministic polynomial time algorithm for testing zeroness of $Σ^{[3]}ΠΣΠ^{[2]}$ circuits. Specifically, we prove that if a finite set of irreducible quadratic polynomials $\mathcal{Q}$ satisfy that for every two polynomial

Hiroki Saito

We apply the technique of reinforcement learning to the control of nonlinear matter waves. In this method, an agent controls the position, strength, and shape of an external Gaussian potential to create and manipulate quantized vortices in a Bose-Einstein condensate (BEC) trapped in a harmonic potential. The density and velocity distributions of the BEC at e

Zhongzhi Yu, Yemin Shi, Tiejun Huang, Yizhou Yu

This paper presents a novel network compression framework Kernel Quantization (KQ), targeting to efficiently convert any pre-trained full-precision convolutional neural network (CNN) model into a low-precision version without significant performance loss. Unlike existing methods struggling with weight bit-length, KQ has the potential in improving the compres

Nicolas Heist, Heiko Paulheim

When it comes to factual knowledge about a wide range of domains, Wikipedia is often the prime source of information on the web. DBpedia and YAGO, as large cross-domain knowledge graphs, encode a subset of that knowledge by creating an entity for each page in Wikipedia, and connecting them through edges. It is well known, however, that Wikipedia-based knowle

Zi-Xuan Zhou, Celso Grebogi, Hai-Peng Ren

Chaos is shown to occur in the flexible shaft rotating-lifting (FSRL) system of the mono-silicon crystal puller. Chaos is, however, harmful for the quality of mono-silicon crystal production. Therefore, it should be suppressed. Many chaos control methods have been proposed theoretically and some have even been used in applications. For a practical plant disp

Giambattista Giacomin, Benjamin Havret

One dimensional pinning models have been widely studied in the physical and mathematical literature, also in presence of disorder. Roughly speaking, they undergo a transition between a delocalized phase and a localized one. In mathematical terms these models are obtained by modifying the distribution of a discrete renewal process via a Boltzmann factor with

Hao Xu, Luqi Wang, Yichen Zhang, Kejie Qiu

The collaboration of unmanned aerial vehicles (UAVs) has become a popular research topic for its practicability in multiple scenarios. The collaboration of multiple UAVs, which is also known as aerial swarm is a highly complex system, which still lacks a state-of-art decentralized relative state estimation method. In this paper, we present a novel fully dece

Ajian Li, Zichang Tan, Xuan Li, Jun Wan

Ethnic bias has proven to negatively affect the performance of face recognition systems, and it remains an open research problem in face anti-spoofing. In order to study the ethnic bias for face anti-spoofing, we introduce the largest up to date CASIA-SURF Cross-ethnicity Face Anti-spoofing (CeFA) dataset (briefly named CeFA), covering $3$ ethnicities, $3$ m

Ikumi Hashimoto, Masakatsu Chiba, Nozomi Okada, Hideo Ogawa

As deformations of the main reflector of a radio telescope directly affect the observations, the evaluation of the deformation is extremely important. Dynamic characteristics of the main reflector of the Nobeyama 45 m radio telescope, Japan, are measured under two conditions: The first is when the pointing observation is in operation, and the second is when

Venkata Pavan Kumar Miriyala, Kale Rahul Vishwanath, Xuanyao Fong

Magnetic skyrmions are emerging as potential candidates for next generation non-volatile memories. In this paper, we propose an in-memory binary neural network (BNN) accelerator based on the non-volatile skyrmionic memory, which we call as SIMBA. SIMBA consumes 26.7 mJ of energy and 2.7 ms of latency when running an inference on a VGG-like BNN. Furthermore,

Haibin Wan, Wen Chen, Jianbo Ji

In this letter, a novel linear transmission strategy to design the linear precoding matrix~(PM) at base station~(BS) and the beamforming matrix~(BM) at relay station~(RS) for multiple-input multiple-output~(MIMO) relaying broadcast channels with direct channel (DC) is proposed, in which a linear PM is designed at BS based on DC, and the RS utilizes the PM, t

Haibin Wan, Wen Chen

In this paper, we investigate joint source precoding matrices and relay processing matrix design for multi-user multiple-input multiple-output~(MU-MIMO) non-regenerative relay networks in the presence of the direct source-destination~(S-D) links. We consider both capacity and mean-squared error~(MSE) criterions subject to the distributed power constraints, w

Hufei Zhu, Wen Chen, Bin Li, Feifei Gao

A fast algorithm for inverse Cholesky factorization is proposed, to compute a triangular square-root of the estimation error covariance matrix for Vertical Bell Laboratories Layered Space-Time architecture (V-BLAST). It is then applied to propose an improved square-root algorithm for V-BLAST, which speedups several steps in the previous one, and can offer fu

Daiki Fujikura, Kenjiro Tadakuma, Masahiro Watanabe, Yoshito Okada

Currently, drone research and development has received significant attention worldwide. Particularly, delivery services employ drones as it is a viable method to improve delivery efficiency by using a several unmanned drones. Research has been conducted to realize complete automation of drone control for such services. However, regarding the takeoff and land

Sergey P. Shary

The paper presents a construction of a quantitative measure of variability for parameter estimates in the data fitting problem under interval uncertainty. It shows the degree of variability and ambiguity of the estimate, and the need for its introduction is dictated by non-uniqueness of answers to the problems with interval data. A substantiation of the new

Takuya Iwasaki, Shu Nakaharai, Yutaka Wakayama, Kenji Watanabe

Graphene/hexagonal boron nitride (hBN) moiré superlattices have attracted interest for use in the study of many-body effects and fractal physics in Dirac fermion systems. Many exotic transport properties have been intensively examined in such superlattices, but previous studies have not focused on single-carrier transport. The investigation of the single-car

Yiying Yan, Zhiguo Lü, JunYan Luo, Hang Zheng

We study the origin of the symmetry of the fluorescence spectrum from the two-level system subjected to a low-frequency periodic modulation and a near-resonant high-frequency monochromatic excitation by using the analytical and numerical methods based on the Floquet theory. We find that the fundamental origin of symmetry of the spectrum can be attributed to

Stefanie Walz, Tobias Gruber, Werner Ritter, Klaus Dietmayer

Gated imaging is an emerging sensor technology for self-driving cars that provides high-contrast images even under adverse weather influence. It has been shown that this technology can even generate high-fidelity dense depth maps with accuracy comparable to scanning LiDAR systems. In this work, we extend the recent Gated2Depth framework with aleatoric uncert

Patricia Lara, Guadalupe Cordero-Tercero, Christine Allen

The major semiaxes of the planets in our Solar System obey a simple geometric progression known as the Titius-Bode Relation (TBR), whose physical origin remains disputed. It has been shown that the exoplanetary systems follow a similar (but not identical) progression of the form a_n= a_0 e^(bn), where a_0, b are constants to be determined for each system. Si

Tomoya Takahashi, Masahiro Watanabe, Kenjiro Tadakuma, Masashi Konyo

Soft robots have attracted much attention in recent years owing to their high adaptability. Long articulated soft robots enable diverse operations, and tip-extending robots that navigate their environment through growth are highly effective in robotic search applications. Because the robot membrane extends from the tip, these robots can lengthen without fric

Stella Biderman

Magic: the Gathering is a popular and famously complicated card game about magical combat. Recently, several authors including Chatterjee and Ibsen-Jensen (2016) and Churchill, Biderman, and Herrick (2019) have investigated the computational complexity of playing Magic optimally. In this paper we show that the ``mate-in-$n$'' problem for Magic is $Δ^

F. Ratnikov, D. Derkach, A. Boldyrev, A. Shevelev

In this paper, we discuss the way advanced machine learning techniques allow physicists to perform in-depth studies of the realistic operating modes of the detectors during the stage of their design. Proposed approach can be applied to both design concept (CDR) and technical design (TDR) phases of future detectors and existing detectors if upgraded. The mach

Daniel C. X. Ung, Marcin Sokolowski, Adrian T. Sutinjo, David B. Davidson

This paper presents a framework to compute the receiver noise temperature (Trcv) of two low-frequency radio telescopes, the Murchison Widefield Array (MWA) and the Engineering Development Array (EDA). The MWA was selected because it is the only operational low-frequency Square Kilometre Array (SKA) precursor at the Murchison Radio-astronomy Observatory, whil

Huy Nguyen, Nicholas Adrian, Joyce Lim Xin Yan, Jonathan M. Salfity

With the rapid rise of 3D-printing as a competitive mass manufacturing method, manual "decaking" - i.e. removing the residual powder that sticks to a 3D-printed part - has become a significant bottleneck. Here, we introduce, for the first time to our knowledge, a robotic system for automated decaking of 3D-printed parts. Combining Deep Learning for 3

Milad Ghaznavi, Ali Jose Mashtizadeh, Bernard Wong, Raouf Boutaba

Middleboxes are increasingly deployed across geographically distributed data centers. In these scenarios, the WAN latency between different sites can significantly impact the performance of stateful middleboxes. The deployment of middleboxes across such infrastructures can even become impractical due to the high cost of remote state accesses. We introduce Co

Nicole F. Allard, John F. Kielkopf, Siyi Xu, Grégoire Guillon

The spectra of helium-dominated white dwarf stars with hydrogen in their atmosphere present a distinctive broad feature centered around 1160~Å\/ in the blue wing of the Lyman-$α$ line. It is extremely apparent in WD 1425+540 recently observed with HST COS. With new theoretical line profiles based on ab initio atomic interaction potentials we show that this f

Teruaki Hayashi, Yukio Ohsawa

Recently, data exchange platforms have emerged in the digital economy to enable better resource allocation in a data-driven society, which requires cross-organizational data collaborations. Understanding the characteristics of the data on these platforms is important for their application; however, the structures of such platforms have not been extensively i

Geovane Fedrecheski, Jan M. Rabaey, Laisa C. P. Costa, Pablo C. Calcina Ccori

This paper analyses the concept of Self-Sovereign Identity (SSI), an emerging approach for establishing digital identity, in the context of the Internet of Things (IoT). We contrast existing approaches for identity on the Internet, such as cloud-based accounts and digital certificates, with SSI standards such as Decentralized Identifiers (DIDs) and Verifiabl

Daisuke Kazukawa, Takashi Shioya

We prove the convergence of (solid) ellipsoids to a Gaussian space in Gromov's concentration/weak topology as the dimension diverges to infinity. This gives the first discovered example of an irreducible nontrivial convergent sequence in the concentration topology, where 'irreducible nontrivial' roughly means to be not constructed from Levy famil

Enrico Camporeale, Algo Carè

In this paper we focus on the problem of assigning uncertainties to single-point predictions generated by a deterministic model that outputs a continuous variable. This problem applies to any state-of-the-art physics or engineering models that have a computational cost that does not readily allow to run ensembles and to estimate the uncertainty associated to

Tianwei Zhang, Huayan Zhang, Yang Li, Yoshihiko Nakamura

Dynamic environments are challenging for visual SLAM since the moving objects occlude the static environment features and lead to wrong camera motion estimation. In this paper, we present a novel dense RGB-D SLAM solution that simultaneously accomplishes the dynamic/static segmentation and camera ego-motion estimation as well as the static background reconst

Beheshteh T. Rakhshan, Guillaume Rabusseau

We introduce a novel random projection technique for efficiently reducing the dimension of very high-dimensional tensors. Building upon classical results on Gaussian random projections and Johnson-Lindenstrauss transforms~(JLT), we propose two tensorized random projection maps relying on the tensor train~(TT) and CP decomposition format, respectively. The tw

Songpo Li, Michael Bowman, Xiaoli Zhang

Shared control in teleoperation leverages both human and robot's strengths and has demonstrated great advantages of reducing the difficulties in teleoperating a robot and increasing the task performance. One fundamental question in shared control is how to effectively allocate the control power to the human and robot. Researchers have been subjectively d

Juan Cao, Peng Qi, Qiang Sheng, Tianyun Yang

The increasing popularity of social media promotes the proliferation of fake news, which has caused significant negative societal effects. Therefore, fake news detection on social media has recently become an emerging research area of great concern. With the development of multimedia technology, fake news attempts to utilize multimedia content with images or

Zura Kakushadze, Willie Yu

We give explicit algorithms and source code for extracting factors underlying Treasury yields using (unsupervised) machine learning (ML) techniques, such as nonnegative matrix factorization (NMF) and (statistically deterministic) clustering. NMF is a popular ML algorithm (used in computer vision, bioinformatics/computational biology, document classification,

Wonjik Kim, Masayuki Tanaka, Masatoshi Okutomi, Yoko Sasaki

In this paper, we propose an automatic labeled sequential data generation pipeline for human segmentation and velocity estimation with point clouds. Considering the impact of deep neural networks, state-of-the-art network architectures have been proposed for human recognition using point clouds captured by Light Detection and Ranging (LiDAR). However, one di

Xiaohuan Xue

Multivariate meta-analysis can be adapted to a wide range of situations for multiple outcomes and multiple treatment groups when combining studies together. The within-study correlation between effect sizes is often assumed known in multivariate meta-analysis while it is not always known practically. In this paper, we propose a generic method to approximate

Heejong Kim, Martin Styner, Joseph Piven, Guido Gerig

Building of atlases plays a crucial role in the analysis of brain images. In scenarios where early growth, aging or disease trajectories are of key importance, longitudinal atlases become necessary as references, most often created from cross-sectional data. New opportunities will be offered by creating longitudinal brain atlases from longitudinal subject-sp

Lele Bai, Xin Wen, Yulin Yang, Jun He

Laser intensity noise suppression has essential effects on preparation and characterization of the audio-frequency squeezed vacuum state of light based on a sub-threshold optical parametric oscillator (OPO).We have implemented two feedback loops by using relevant acousto-optical modulators (AOM) to stabilize the intensity of 795-nm near infrared (NIR) fundam

Marco A. S. Trindade, Sergio Floquet, J. D. M. Vianna

In this work we explore the structure of Clifford algebras and the representations of the algebraic spinors in quantum information theory. Initially we present an general formulation through elements of left minimal ideals in tensor products of the Clifford algebra $Cl^{+}_{1,3}$. Posteriorly we perform some applications in quantum computation: qubits, entan

Seug-Yeal Ha, Shi Jin, Doheon Kim

We present convergence and error estimates of the time-discrete consensus-based optimization(CBO) algorithms proposed in [arXiv:1909.09249] for general nonconvex functions. In authors' recent work [arxiv: 1910.08239], rigorous error analysis of the first-order consensus-based optimization algorithm proposed in [arXiv:1909.09249] was studied at the partic

Qian Guan, Brian J. Reich, Eric B. Laber

Malaria is an infectious disease affecting a large population across the world, and interventions need to be efficiently applied to reduce the burden of malaria. We develop a framework to help policy-makers decide how to allocate limited resources in realtime for malaria control. We formalize a policy for the resource allocation as a sequence of decisions, o

Takuma Kawai, Daiki Matsunaga, Fanlong Meng, Julia M. Yeomans

We investigate the collective motion of magnetic rotors suspended in a viscous fluid under an uniform rotating magnetic field. The rotors are positioned on a square lattice, and low Reynolds hydrodynamics is assumed. For a $3 \times 3$ array of magnets, we observe three characteristic dynamical patterns as the external field strength is varied: a synchronize

Pedro Barroso, Mário Pereira, António Ravara

We present an approach to obtain formally verified implementations of classical Computational Logic algorithms. We choose the Why3 platform because it allows to implement functions in a style very close to the mathematical definitions, as well as it allows a high degree of automation in the verification process. As proof of concept, we present a mathematical

Sam Maksoud, Kun Zhao, Peter Hobson, Anthony Jennings

The difficulty of processing gigapixel whole slide images (WSIs) in clinical microscopy has been a long-standing barrier to implementing computer aided diagnostic systems. Since modern computing resources are unable to perform computations at this extremely large scale, current state of the art methods utilize patch-based processing to preserve the resolutio

Timothy J. Gorey, Borna Zandkarimi, Guangjing Li, Eric T. Baxter

We present a combined experimental/theoretical study of Pt$_n$/SiO$_2$ and Pt$_n$Sn$_x$/SiO$_2$ (n = 4, 7) model catalysts for the endothermic dehydrogenation of hydrocarbons, using the ethylene intermediate as a model reactant. Supported pure Ptn clusters are found to be highly active toward dehydrogenation of C2D4, quickly deactivating due to a combination

L. H. Willems van Beveren, D. L. Creedon, N. Eikenberg, K. Ganesan

We present a study of the structural and electronic properties of ultra-nanocrystalline diamond films that were modified by adding nitrogen to the gas mixture during chemical vapour deposition growth. Hall bar devices were fabricated from the resulting films to investigate their electrical conduction as a function of both temperature and magnetic field. Thro

Shunsuke Murai, Gabriel W. Castellanos, T. V. Raziman, Alberto. G. Curto

We demonstrate an enhanced emission of high quantum yield molecules coupled to dielectric metasurfaces formed by periodic arrays of polycrystalline silicon nanoparticles. Radiative coupling of the nanoparticles, mediated by in-plane diffraction, leads to the formation of collective Mie scattering resonances or Mie surface lattice resonances (M-SLRs), with re

Shengchao Gong, Mengxin Ren, Wei Wu, Wei Cai

Spatial light modulators (SLMs) are devices for modulating amplitude, phase or polarization of a light beam on demand. Such devices have been playing an indispensable inuence in many areas from our daily entertainments to scientific researches. In the past decades, the SLMs have been mainly operated in electrical addressing (EASLM) manner, wherein the writin

Radmila Sazdanovic, Daniel Scofield

We utilize relations between Khovanov and chromatic graph homology to determine extreme Khovanov groups and corresponding coefficients of the Jones polynomial. The extent to which chromatic homology and chromatic polynomial can be used to compute integral Khovanov homology of a link depends on the maximal girth of its all-positive graphs. In this paper we al

Robert Dorward

In this undergraduate thesis, we expand on the study of statistics on restricted growth functions avoiding patterns initiated by Campbell, et. al. Restricted growth functions are of interest because they are in bijection with set partitions. We examine the case when a restricted growth function contains a pattern exactly $k$ times, where $k=0$ corresponds to

Dylan A. Crocker, Waymond R. Scott

Sinuous antennas are capable of producing ultra-wideband radiation with polarization diversity. Such a capability makes the sinuous antenna an attractive candidate for wideband polarimetric radar applications. Additionally, the ability of the sinuous antenna to be implemented as a planar structure makes it a good fit for close in sensing applications such as

Nam N. Tran, Hemanshu R. Pota, Quang N. Tran, Xuefei Yin

The evolution of the traditional power system towards the modern smart grid has posed many new cybersecurity challenges to this critical infrastructure. One of the most dangerous cybersecurity threats is the False Data Injection (FDI) attack, especially when it is capable of completely bypassing the widely deployed Bad Data Detector of State Estimation and i

Ali Anaissi, Seid Miad Zandavi

Multi-way data analysis has become an essential tool for capturing underlying structures in higher-order data sets where standard two-way analysis techniques often fail to discover the hidden correlations between variables in multi-way data. We propose a multi-objective variational autoencoder (MVA) method for smart infrastructure damage detection and diagno