April 2019 arXiv papers — page 32

Michael Drmota, Lander Ramos, Clément Requilé, Juanjo Rué

The goal of this paper is to obtain quantitative results on the number and on the size of maximal independent sets and maximal matchings in several block-stable graph classes that satisfy a proper sub-criticality condition. In particular we cover trees, cacti graphs and series-parallel graphs. The proof methods are based on a generating function approach and

Y. Hino, H. Furuta, F. Suekane

Stainless steel is a candidate of the inner surface of the storage container for LAB-based Gadolinium loaded liquid scintillator (Gd-LS) to be used in the JSNS$^2$ neutrino detector. Aging effect on Gd concentration of Gd-LS was investigated with the Gd-LS sample stored in the passivated stainless steel bottle in two independent methods. The direct compariso

Andrei Micu

Starting from the idea of realising constant roll inflation in string theory we develop the constant roll formalism for two scalar fields. We derive the two-field potential which is compatible with a constant roll regime and discuss possible applications to string-models.

Anders Braarud Hanssen, Stefano Nichele

In this paper we present a set of key demarcations, particularly important when discussing ethical and societal issues of current AI research and applications. Properly distinguishing issues and concerns related to Artificial General Intelligence and weak AI, between symbolic and connectionist AI, AI methods, data and applications are prerequisites for an in

Eita Nakamura, Yasuyuki Saito, Kazuyoshi Yoshii

Automatic estimation of piano fingering is important for understanding the computational process of music performance and applicable to performance assistance and education systems. While a natural way to formulate the quality of fingerings is to construct models of the constraints/costs of performance, it is generally difficult to find appropriate parameter

Victor Lazzarini, Joseph Timoney

This paper re-appraises the role of analogue computers within electronic and computer music and provides some pointers to future areas of research. It begins by introducing the idea of analogue computing and placing in the context of sound and music applications. This is followed by a brief examination of the classic constituents of an analogue computer, con

Susana Molina Sedgwick, Stephen F. King, Stephen J. Parke, Nicholas W. Prouse

This project aims to explore the effects that changes in a matter density profile could have on neutrino oscillations, and whether these could potentially be seen by the future Hyper-Kamiokande experiment (T2HK). The analysis is extended to include the possibility of having a second detector in Korea (T2HKK).

Yoshinori Imai, Katsuya Konno, Yoshinao Hasegawa, Takuya Aoyama

We study on transport and magnetic properties of hydrated and lithium-intercalated $α$-RuCl$_3$, Li$_x$RuCl$_3 \cdot y$H$_2$O, for investigating the effect on mobile-carrier doping into candidate materials for a realization of a Kitaev model. From thermogravitometoric and one-dimensional electron map analyses, we find two crystal structures of this system, t

Jaehoon Cho, Dongbo Min, Youngjung Kim, Kwanghoon Sohn

Current self-supervised methods for monocular depth estimation are largely based on deeply nested convolutional networks that leverage stereo image pairs or monocular sequences during a training phase. However, they often exhibit inaccurate results around occluded regions and depth boundaries. In this paper, we present a simple yet effective approach for mon

Ankush Agarwal, Christian-Oliver Ewald, Yongjie Wang

Pension schemes all over the world are under increasing pressure to efficiently hedge the longevity risk posed by ageing populations. In this work, we study an optimal investment problem for a defined contribution pension scheme which decides to hedge the longevity risk using a mortality-linked security, typically a longevity bond. The pension scheme invests

Filip Mazowiecki, Michał Pilipczuk

In this paper we consider the reachability problem for bounded branching VASS. Bounded VASS are a variant of the classic VASS model where all values in all configurations are upper bounded by a fixed natural number, encoded in binary in the input. This model gained a lot of attention in 2012 when Haase et al. showed its connections with timed automata. Later

Andrew Newman

There are (at least) two reasons to study random polytopes. The first is to understand the combinatorics and geometry of random polytopes especially as compared to other classes of polytopes, and the second is to analyze average-case complexity for algorithms which take polytopal data as input. However, establishing results in either of these directions ofte

Alessandro Landra, Christoph Hufnagel, Lim Chin Chean, Thomas Weigner

Hybrid quantum systems have the potential of mitigating current challenges in developing a scalable quantum computer. Of particular interest is the hybridization between atomic and superconducting qubits. We demonstrate a novel experimental setup for transferring and trapping ultracold atoms inside a millikelvin cryogenic environment, where interactions betw

Riccardo Ciolfi, Wolfgang Kastaun, Jay Vijay Kalinani, Bruno Giacomazzo

The recent multimessenger observation of the short gamma-ray burst (SGRB) GRB 170817A together with the gravitational wave (GW) event GW170817 provides evidence for the long-standing hypothesis associating SGRBs with binary neutron star (BNS) mergers. The nature of the remnant object powering the SGRB, which could have been either an accreting black hole (BH

Pablo Barros, German I. Parisi, Stefan Wermter

Recent models of emotion recognition strongly rely on supervised deep learning solutions for the distinction of general emotion expressions. However, they are not reliable when recognizing online and personalized facial expressions, e.g., for person-specific affective understanding. In this paper, we present a neural model based on a conditional adversarial

Aurélien Cavelan, Rubén M. Cabezón, Florina M. Ciorba

Silent data corruptions (SDCs) hinder the correctness of long-running scientific applications on large scale computing systems. Selective particle replication (SPR) is proposed herein as the first particle-based replication method for detecting SDCs in Smoothed particle hydrodynamics (SPH) simulations. SPH is a mesh-free Lagrangian method commonly used to pe

Carmelo Evoli, Roberto Aloisio, Pasquale Blasi

The unprecedented quality of the data collected by the AMS-02 experiment onboard the International Space Station allowed us to address subtle questions concerning the origin and propagation of cosmic rays. Here we discuss the implications of these data for the injection spectrum of elements with different masses and for the diffusion coefficient probed by co

Alexander Zuyev, Victoria Grushkovskaya

This paper deals with the stabilization problem for nonlinear control-affine systems with the use of oscillating feedback controls. We assume that the local controllability around the origin is guaranteed by the rank condition with Lie brackets of length up to 3. This class of systems includes, in particular, mathematical models of rotating rigid bodies. We

Yuval Emek, Shay Kutten, Mordechai Shalom, Shmuel Zaks

A widely studied problem in communication networks is that of finding the maximum number of communication requests that can be scheduled concurrently, subject to node and/or link capacity constraints. In this paper, we consider the problem of finding the largest number of multicast communication requests that can be serviced simultaneously by a network of tr

Nariyuki Saito, Hiroki Sannohe, Nobuhisa Ishii, Teruto Kanai

Photoinduced quantum dynamics in molecules have hierarchical temporal structures with different energy scales that are associated with electron and nuclear motions. Femtosecond-to-attosecond transient absorption spectroscopy (TAS) using high-harmonic generation (HHG) with a photon energy below 300 eV has been a powerful tool to observe such electron and nucl

Marise V. Gielen, Riëlle de Ruiter, Robin B. J. Koldeweij, Detlef Lohse

Hot liquid metal drops impacting onto a cold substrate solidify during their subsequent spreading. Here we experimentally study the influence of solidification on the outcome of an impact event. Liquid tin drops are impacted onto sapphire substrates of varying temperature. The impact is visualised both from the side and from below, which provides a unique vi

Dong-Won Jung, Jungil Lee, Soo-hyeon Nam

We study a classically scale-invariant model with an electroweak singlet scalar mediator together with a scalar dark matter multiplet of global $O(N)$ symmetry. Our most general conformally invariant scalar potential generates the electroweak symmetry breaking via the Coleman-Weinberg mechanism, and the new scalar singlet acquires its mass through radiative

Domenico Fiorenza, Hisham Sati, Urs Schreiber

We consider the hypothesis that the C-field 4-flux and 7-flux forms in M-theory are in the image of the non-abelian Chern character map from the non-abelian generalized cohomology theory called J-twisted Cohomotopy theory. We prove for M2-brane backgrounds in M-theory on 8-manifolds that such charge quantization of the C-field in Cohomotopy theory implies a

Vasyl Kuryliuk, Oleksii Nepochatyi, Patrice Chantrenne, David Lacroix

In this work, we investigated tensile and compression forces effect on the thermal conductivity of silicon. We used equilibrium molecular dynamics approach for the evaluation of thermal conductivity considering different interatomic potentials. More specifically, we tested Stillinger-Weber, Tersoff, Environment-Dependent Interatomic Potential and Modified Em

Brandon Williams

We compute generators and relations for the graded rings of paramodular forms of degree two and levels 5 and 7. The generators are expressed as quotients of Gritsenko lifts and Borcherds products. The computation is made possible by a characterization of modular forms on the Humbert surfaces of discriminant 4 that arise from paramodular forms by restriction.

Ondřej Sokol, Vladimír Holý

The knowledge of the number of customers is the pillar of retail business analytics. In our setting, we assume that a portion of customers is monitored and easily counted due to the loyalty program while the rest is not monitored. The behavior of customers in both groups may significantly differ making the estimation of the number of unmonitored customers a

Z. Y. Chen, M. H. Qin, J. M. Liu

The pinning and depinning of antiferromagnetic (AFM) domain wall is certainly the core issue of AFM spintronics. In this work, we study theoretically the Néel-type domain wall pinning and depinning at a notch in an antiferromagnetic (AFM) nano-ribbon. The depinning field depending on the notch dimension and intrinsic physical parameters are deduced and also

Subhadip Dey, Michael Kapovich

We extend several notions and results from the classical Patterson-Sullivan theory to the setting of Anosov subgroups of higher rank semisimple Lie groups, working primarily with invariant Finsler metrics on associated symmetric spaces. In particular, we prove the equality between the Hausdorff dimensions of flag limit sets, computed with respect to a suitab

Chao Wu, De-Cheng Zou, Ming Zhang

We construct charged asymptotically flat black hole solutions in Einstein-Maxwell-Weyl(EMW) gravity. These solutions can be interpreted as generalizations of two different groups: Schwarzschild black hole (SBH) and non-Schwarzschild black hole (NSBH) solutions. In addition, we discuss the thermodynamic properties of two groups of numerical solutions in detai

Quentin Gazda

Let $n$ be an odd positive integer. In this short elementary note, we slightly extend Macdonald's identity for $\mathfrak{sl}_{n}$ into a two-variables identity in the spirit of Jacobi forms. The peculiarity of this work lies in its proof which uses Wronskians of vector-valued $θ$-functions. This complements the work of A. Milas towards modular Wronskian

Zeqing Fu, Wei Hu, Zongming Guo

With the development of 3D laser scanning techniques and depth sensors, 3D dynamic point clouds have attracted increasing attention as a representation of 3D objects in motion, enabling various applications such as 3D immersive tele-presence, gaming and navigation. However, dynamic point clouds usually exhibit holes of missing data, mainly due to the fast mo

Tadayoshi Adachi

In this paper, we consider the Floquet Hamiltonian $K$ associated with a three-body Schr\"odinger operator with time-periodic pair potentials $H(t)$. By introducing a conjugate operator $A$ for $K$ in the standard Mourre theory, we prove the Mourre estimate for $K$.

Joohak Bae, Jaehoon Kang, Panki Kim, Jaehun Lee

In this paper, we consider a symmetric pure jump Markov process $X$ on a metric measure space with volume doubling conditions. Our focus is on estimating the transition density $p(t,x,y)$ of $X$ and studying its stability when the jumping kernel exhibits general mixed polynomial growth. Unlike previous work, in our setting, the rate function governing the ju

Andrej B. Arbuzov, Alexander E. Pavlov

The global time in Geometrodynamics is defined in a covariant under diffeomorphisms form. An arbitrary static background metric is taken in the tangent space. The global intrinsic time is identified with the mean value of the logarithm of the square root of the ratio of the metric determinants. The procedures of the Hamiltonian reduction and deparametrizatio

Eunjeong Lee, Mikiya Masuda, Seonjeong Park

For two elements $v$ and $w$ of the symmetric group $\mathfrak{S}_n$ with $v\leq w$ in Bruhat order, the Bruhat interval polytope $Q_{v,w}$ is the convex hull of the points $(z(1),\ldots,z(n))\in \mathbb{R}^n$ with $v\leq z\leq w$. It is known that the Bruhat interval polytope $Q_{v,w}$ is the moment map image of the Richardson variety $X^{v^{-1}}_{w^{-1}}$.

Benjamin Sliwa, Robert Falkenberg, Thomas Liebig, Nico Piatkowski

The exploitation of vehicles as mobile sensors acts as a catalyst for novel crowdsensing-based applications such as intelligent traffic control and distributed weather forecast. However, the massive increases in Machine-type Communication (MTC) highly stress the capacities of the network infrastructure. With the system-immanent limitation of resources in cel

Kaustav Chakraborty, Srubabati Goswami, Biswajit Karmakar

We investigate the consequences of $μ-τ$ reflection symmetry in presence of a light sterile neutrino for the $3+1$ neutrino mixing scheme. We discuss the implications of total $μ-τ$ reflection symmetry as well partial $μ-τ$ reflection symmetry. For the total $μ-τ$ reflection symmetry we find values of $θ_{23}$ and $δ$ remains confined near $π/4$ and $\pm π/2

Ching Hua Lee, Amanda Sutrisno, Tobias Hofmann, Tobias Helbig

Knots are intricate structures that cannot be unambiguously distinguished with any single topological invariant. Momentum space knots, in particular, have been elusive due to their requisite finely tuned long-ranged hoppings. Even if constructed, probing their intricate linkages and topological "drumhead" surface states will be challenging due to the high pr

Arnab Chakrabarti, Rituparna Sen

Copula is a powerful tool to model multivariate data. We propose the modelling of intraday financial returns of multiple assets through copula. The problem originates due to the asynchronous nature of intraday financial data. We propose a consistent estimator of the correlation coefficient in case of Elliptical copula and show that the plug-in copula estimat

Benjamin Sliwa, Christian Wietfeld

Novel vehicular communication methods are mostly analyzed simulatively or analytically as real world performance tests are highly time-consuming and cost-intense. Moreover, the high number of uncontrollable effects makes it practically impossible to reevaluate different approaches under the exact same conditions. However, as these methods massively simplify

Xiang-You Chen, Yu-Yu Zhang, Hang Zheng

We develop a systematic variational coherent-squeezed-state expansion for the ground state of the quantum Rabi model, which includes an additional squeezing effect with comparisons to previous coherent-state approach. For finite large ratio between the atomic and field frequency, the essential feature of the ground-state wave function in the super-radiant ph

Benjamin Sliwa, Christian Wietfeld

Multi-Mobile Network Operator (MNO) networking is a promising method to exploit the joint force of multiple available cellular data connections within vehicular networks. By applying anticipatory communication principles, data transmissions can dynamically utilize the mobile network with the highest estimated network performance in order to achieve improveme

Katsuki Aoki, Keigo Shimada

We reveal the existence of a certain hidden symmetry in general ghost-free scalar-tensor theories which can only be seen when generalizing the geometry of the spacetime from Riemannian. For this purpose, we study scalar-tensor theories in the metric-affine (Palatini) formalism of gravity, which we call scalar-metric-affine theories for short, where the metri

Arkaprava Das, Chetan Prakash Saini

In this paper, we report the high temperature mediated structural phase transformation from B1 to B2 phase in solgel derived Cd0.2Zn0.8O nanocomposite thin film for the temperature range of 700 to 900 degree centigrade. Xray diffraction pattern provides a direct and unambiguous indication of phase evolution with increase in annealing Temperature from 700 to

Antonio Calcagnì, Massimiliano Pastore, Gianmarco Altoè

Recent technological advances have provided new settings to enhance individual-based data collection and computerized-tracking data have became common in many behavioral and social research. By adopting instantaneous tracking devices such as computer-mouse, wii, and joysticks, such data provide new insights for analysing the dynamic unfolding of response pro

Tianyu Shi, Pin Wang, Xuxin Cheng, Ching-Yao Chan

We apply Deep Q-network (DQN) with the consideration of safety during the task for deciding whether to conduct the maneuver. Furthermore, we design two similar Deep Q learning frameworks with quadratic approximator for deciding how to select a comfortable gap and just follow the preceding vehicle. Finally, a polynomial lane change trajectory is generated and

Shaghayegh Najari, Mostafa Salehi, Vahid Ranjbar, Mahdi Jalili

Some networked systems can be better modelled by multilayer structure where the individual nodes develop relationships in multiple layers. Multilayer networks with similar nodes across layers are also known as multiplex networks. This manuscript proposes a novel framework for predicting forthcoming or missing links in multiplex networks. The link prediction

Gang Yang, Jialun Ping, Pablo G. Ortega, Jorge Segovia

A constituent quark model, which has recently been successfully applied to the study of heavy quarkonium properties such as its spectrum but also a diverse array of observables related with their electromagnetic, strong and weak decays and reactions, is used herein to compute ground- and excited-state masses of $QQQ$-baryons containing either $c$- or $b$-qua

Tao Li, Jinwen Ma

Tensor completion and robust principal component analysis have been widely used in machine learning while the key problem relies on the minimization of a tensor rank that is very challenging. A common way to tackle this difficulty is to approximate the tensor rank with the $\ell_1-$norm of singular values based on its Tensor Singular Value Decomposition (T-S

Isra Mohamed Ali, Maurantonio Caprolu, Roberto Di Pietro

Cryptographic algorithms have been used not only to create robust ciphertexts but also to generate cryptograms that, contrary to the classic goal of cryptography, are meant to be broken. These cryptograms, generally called puzzles, require the use of a certain amount of resources to be solved, hence introducing a cost that is often regarded as a time delay--

Gustavo Jasso

These notes are an expanded version of my talk at the ICRA 2018 in Prague, Czech Republic; they are based on joint work with Tobias Dyckerhoff and Tashi Walde. In them we relate Iyama's higher Auslander algebras of type $\mathbb{A}$ to Eilenberg--Mac Lane spaces in algebraic topology and to higher-dimensional versions of the Waldhausen $\operatorname{S}$-con

Salman Sajad Wani, Behnam Pourhassan, Mir Faizal, Ahmed Jellal

As the loop quantum gravity is based on polymer quantization, we will argue that the polymer length (like string length) can be several orders larger than the Planck length, and this can have low energy consequences. We will demonstrate that a short distance modification of a quantum system by polymer quantization and by string theoretical considerations can

Feng Xue, Anlong Ming, Menghan Zhou, Yu Zhou

For tiny obstacle discovery in a monocular image, edge is a fundamental visual element. Nevertheless, because of various reasons, e.g., noise and similar color distribution with background, it is still difficult to detect the edges of tiny obstacles at long distance. In this paper, we propose an obstacle-aware discovery method to recover the missing contours

Wing Hong Wong, Yifei Lou, Stefano Marchesini, Tieyong Zeng

Recovering a signal from its Fourier magnitude is referred to as phase retrieval, which occurs in different fields of engineering and applied physics. This paper gives a new characterization of the phase retrieval problem. Particularly useful is the analysis revealing that the common gradient-based regularization does not restrict the set of solutions to a s

Linsen Dong, Guanyu Gao, Xinyi Zhang, Liangyu Chen

Model-Based Reinforcement Learning (MBRL) is one category of Reinforcement Learning (RL) algorithms which can improve sampling efficiency by modeling and approximating system dynamics. It has been widely adopted in the research of robotics, autonomous driving, etc. Despite its popularity, there still lacks some sophisticated and reusable open-source framewor

Lai Tian, Feiping Nie, Xuelong Li

This paper presents new algorithms to solve the feature-sparsity constrained PCA problem (FSPCA), which performs feature selection and PCA simultaneously. Existing optimization methods for FSPCA require data distribution assumptions and are lack of global convergence guarantee. Though the general FSPCA problem is NP-hard, we show that, for a low-rank covaria

Shing-Jiuan Liu, Ronald Y. Chang, Feng-Tsun Chien

Device-free Wi-Fi indoor localization has received significant attention as a key enabling technology for many Internet of Things (IoT) applications. Machine learning-based location estimators, such as the deep neural network (DNN), carry proven potential in achieving high-precision localization performance by automatically learning discriminative features f

Yuhang Jiang, Jinhai Mao, Xinyuan Lai, Kenji Watanabe

The discovery of correlated electronic phases, including Mott-like insulators and superconductivity, in twisted bilayer graphene (TBLG) near the magic angle, and the intriguing similarity of their phenomenology to that of the high-temperature superconductors, has spurred a surge of research to uncover the underlying physical mechanism. Local spectroscopy, wh

Yuankai Qi, Qi Wu, Peter Anderson, Xin Wang

One of the long-term challenges of robotics is to enable robots to interact with humans in the visual world via natural language, as humans are visual animals that communicate through language. Overcoming this challenge requires the ability to perform a wide variety of complex tasks in response to multifarious instructions from humans. In the hope that it mi

Murod S. Bahovadinov, Oğuz Gülseren, Jürgen Schnack

In this letter, we propose an application of String Order Parameter (SOP), commonly used in quantum spin systems, to identify symmetry-protected topological phase (SPT) in fermionic systems in the example of the dimerized fermionic chain. As a generalized form of dimerized model, we consider a one-dimensional spin-1/2 XX model with alternating spin couplings

Yuka Fujiki, Kousuke Yakubo

Many real-world networks exhibit degree-degree correlations between nodes separated by more than one step. Such long-range degree correlations (LRDCs) can be fully described by one joint and four conditional probability distributions with respect to degrees of two randomly chosen nodes and shortest path distance between them. While LRDCs are induced by neare

Xiang Gao, Wei Hu, Zongming Guo

Graph Convolutional Neural Networks (GCNNs) are generalizations of CNNs to graph-structured data, in which convolution is guided by the graph topology. In many cases where graphs are unavailable, existing methods manually construct graphs or learn task-driven adaptive graphs. In this paper, we propose Graph Learning Neural Networks (GLNNs), which exploit the

Sibo Zheng

Compared to the minimal supersymmetric standard model, an extension by vectorlike fermions is able to explain the Higgs mass while retains the grand unification. We investigate the minimal vectorlike model by focusing on the vectorlike electroweak sector. We firstly derive the mass spectrum in the electroweak sector, then calculate the one-loop effects on th

Sabyasachi Chakraborty, Tuhin S. Roy

We report that models of electroweak supersymmetry with gaugino mass unification and sequestered scalar masses can still produce viable spectra, as long as we include a set of non-standard supersymmetry breaking terms, which are trilinear in scalars like the A-terms, but are non-holomorphic in visible sector fields unlike the A- terms. These terms impart a s

Jiawei Zhou

The rational homotopy type of a differential graded algebra (DGA) can be represented by a family of tensors on its cohomology, which constitute an $A_\infty$-minimal model of this DGA. When only the cohomology is needed to determine the rational homotopy type, then the DGA is called formal. By a theorem of Miller, a compact $k$-connected manifold is formal i

Krishanu Sadhukhan, Antonio Politano, Amit Agarwal

We predict the existence of a novel long-lived gapless plasmon mode in a type-II Dirac semimetal (DSM). This gapless mode arises from the out-of-phase oscillations of the density fluctuations in the electron and the hole pockets of a type-II DSM. It originates beyond a critical wave-vector along the direction of the tilt axis, owing to the momentum separatio

Abdelrahman Taha, Muhammad Alrabeiah, Ahmed Alkhateeb

Employing large intelligent surfaces (LISs) is a promising solution for improving the coverage and rate of future wireless systems. These surfaces comprise a massive number of nearly-passive elements that interact with the incident signals, for example by reflecting them, in a smart way that improves the wireless system performance. Prior work focused on the

Hee-Soo Heo, Jee-weon Jung, Hye-jin Shim, Ha-Jin Yu

Acoustic scene classification identifies an input segment into one of the pre-defined classes using spectral information. The spectral information of acoustic scenes may not be mutually exclusive due to common acoustic properties across different classes, such as babble noises included in both airports and shopping malls. However, conventional training proce

Jee-weon Jung, Hye-jin Shim, Hee-Soo Heo, Ha-Jin Yu

In this study, we concentrate on replacing the process of extracting hand-crafted acoustic feature with end-to-end DNN using complementary high-resolution spectrograms. As a result of advance in audio devices, typical characteristics of a replayed speech based on conventional knowledge alter or diminish in unknown replay configurations. Thus, it has become i

Matthias Mergenthaler, Ani Nersisyan, Andrew Patterson, Martina Esposito

Hybrid circuit quantum electrodynamics (QED) involves the study of coherent quantum physics in solid state systems via their interactions with superconducting microwave circuits. Here we present an implementation of a hybrid superconducting qubit that employs a carbon nanotube as a Josephson junction. We realize the junction by contacting a carbon nanotube w

Sean Symon, Denis Sipp, Beverley J. McKeon

The flows around a NACA 0018 airfoil at a Reynolds number of 10250 and angles of attack of alpha = 0 (A0) and alpha = 10 (A10) are modelled using resolvent analysis and limited experimental measurements obtained from particle image velocimetry. The experimental mean velocity profiles are data-assimilated so that they are solutions of the incompressible Reyno

Peng Gao, Ruyue Yuan, Fei Wang, Liyi Xiao

In this paper, we investigate the impacts of three main aspects of visual tracking, i.e., the backbone network, the attentional mechanism, and the detection component, and propose a Siamese Attentional Keypoint Network, dubbed SATIN, for efficient tracking and accurate localization. Firstly, a new Siamese lightweight hourglass network is specially designed f

Melissa Beer, Robert Davis, Thomas Elgin, Matthew Hertel

In the 1970s, O'Keefe and Dostrovsky discovered that certain neurons, called place cells, in an animal's brain are tied to its location within its arena. A combinatorial neural code is a collection of $0/1$-vectors which encode the patterns of co-firing activity among the place cells. Gross, Obatake, and Youngs have recently used techniques from toric algebr

Prateeksha Varshney, Yogesh Simmhan

Cloud computing has grown to become a popular distributed computing service offered by commercial providers. More recently, Edge and Fog computing resources have emerged on the wide-area network as part of Internet of Things (IoT) deployments. These three resource abstraction layers are complementary, and provide distinctive benefits. Scheduling applications

Doru Thom Popovici, Martin D. Schatz, Franz Franchetti, Tze Meng Low

Multi-dimensional discrete Fourier transforms (DFT) are typically decomposed into multiple 1D transforms. Hence, parallel implementations of any multi-dimensional DFT focus on parallelizing within or across the 1D DFT. Existing DFT packages exploit the inherent parallelism across the 1D DFTs and offer rigid frameworks, that cannot be extended to incorporate

Taiane Schaedler Prass, Sílvia Regina Costa Lopes, José G. Dórea, Rejane C. Marques

Birth weight data (22,012 live-births) from a public hospital in Porto Velho (Amazon) was used in multiple statistical models to assess the effects of forest-fire smoke on human reproductive outcome. Mean birth weights for girls (3,139 g) and boys (3,393 g) were considered statistically different (p-value < 2.2e-16). Among all models analyzed, the means were

Angelo Ricarte, Michael Tremmel, Priyamvada Natarajan, Thomas Quinn

We study the link between supermassive black hole growth and the stellar mass assembly of their host galaxies in the state-of-the-art Romulus suite of simulations. The cosmological simulations Romulus25 and RomulusC employ innovative recipes for the seeding, accretion, and dynamics of black holes in the field and cluster environments respectively. We find th

Christopher J. Vogl, Andrew Steyer, Daniel R. Reynolds, Paul A. Ullrich

The nonhydrostatic High Order Method Modeling Environment (HOMME-NH) atmospheric dynamical core supports acoustic waves that propagate significantly faster than the advective wind speed, thus greatly limiting the timestep size that can be used with standard explicit time-integration methods. Resolving acoustic waves is unnecessary for accurate climate and we

Sebastian Gonzalez Hermosillo de la Maza, Seyyed Aliasghar Hosseini, Fiachra Knox, Bojan Mohar

The game of cops and robbers is a well-known game played on graphs. In this paper we consider the straight-ahead orientations of 4-regular quadrangulations of the torus and the Klein bottle and we prove that their cop number is bounded by a constant. We also show that the cop number of every k-regularly oriented toroidal grid is at most 13.

Yan Yan, Yi Xu, Qihang Lin, Lijun Zhang

Previous studies on stochastic primal-dual algorithms for solving min-max problems with faster convergence heavily rely on the bilinear structure of the problem, which restricts their applicability to a narrowed range of problems. The main contribution of this paper is the design and analysis of new stochastic primal-dual algorithms that use a mixture of sto

Jiaozhen She, Jiawei Hu, Hongwei Yu

We investigate, in the framework of open quantum systems, the entanglement dynamics of two circularly accelerated two-level atoms with the same centripetal acceleration interacting with a bath of fluctuating electromagnetic fields in the Minkowski vacuum. We assume that the two atoms rotate synchronically with their separation perpendicular to the rotating p

Viraj Bangari, Bicky A. Marquez, Heidi B. Miller, Alexander N. Tait

Convolutional Neural Networks (CNNs) are powerful and highly ubiquitous tools for extracting features from large datasets for applications such as computer vision and natural language processing. However, a convolution is a computationally expensive operation in digital electronics. In contrast, neuromorphic photonic systems, which have experienced a recent

Aaron Pollack

We consider a special theta lift $\theta(f)$ from cuspidal Siegel modular forms $f$ on $\mathrm{Sp}_4$ to "modular forms" $\theta(f)$ on $\mathrm{SO}(4,4)$. This lift can be considered an analogue of the Saito-Kurokawa lift, where now the image of the lift is representations of $\mathrm{SO}(4,4)$ that are quaternionic at infinity. We relate the Fourier coeff

Steffen Bondorf, Binbin Chen, Jonathan Scarlett, Haifeng Yu

The group testing problem consists of determining a small set of defective items from a larger set of items based on tests on groups of items, and is relevant in applications such as medical testing, communication protocols, pattern matching, and many more. While rigorous group testing algorithms have long been known with runtime at least linear in the numbe

Rutwig Campoamor-Stursberg, Ian Marquette

A generalization $\mathfrak{Gal}_{\ell}(p,q)$ of the conformal Galilei algebra $\mathfrak{g}_{\ell}(d)$ with Levi subalgebra isomorphic to $\mathfrak{sl}(2,\mathbb{R})\oplus\mathfrak{so}(p,q)$ is introduced and a virtual copy of the latter in the enveloping algebra of the extension is constructed. Explicit expressions for the Casimir operators are obtained f

Eder M. Correa

In this paper, we provide a systematic and constructive description of Vaisman structures on certain principal elliptic bundles over complex flag manifolds. From this description we explicitly classify homogeneous l.c.K. structures on compact homogeneous Hermitian manifolds using elements of representation theory of complex simple Lie algebras. Moreover, we

David A. Benson, Stephen Pankavich, Michael Schmidt, Guillem Sole-Mari

Traditional random-walk particle-tracking (PT) models of advection and dispersion do not track entropy, because particle masses remain constant. Newer mass-transfer particle tracking (MTPT) models have the ability to do so because masses of all compounds may change along trajectories. Additionally, the probability mass functions (PMF) of these MTPT models ma

A. Vorobyev

This report presents a project of an experiment for precision studies of the elastic electron proton scattering in the low momentum transfer region. The project is based on an innovative experimental method which allows for detection of recoil protons in a hydrogen &#34;active target&#34;. The goal of the experiment is to measure the $ep$ elastic scattering

Md. Akmal Haidar, Mehdi Rezagholizadeh

Text generation is of particular interest in many NLP applications such as machine translation, language modeling, and text summarization. Generative adversarial networks (GANs) achieved a remarkable success in high quality image generation in computer vision,and recently, GANs have gained lots of interest from the NLP community as well. However, achieving s

Abolghasem Daeichian, Amir Haghani

This paper introduces a multi-agent approach to adjust traffic lights based on traffic situation in order to reduce average delay time. In the traffic model, lights of each intersection are controlled by an autonomous agent. Since decision of each agent affects neighbor agents, this approach creates a classical non-stationary environment. Thus, each agent no

Yoshiki Horii, Hirofumi Nonaka, Elisa Claire Alemán Carreón, Hiroki Horino

Electronic word-of-mouth (eWOM) has become an important resource for the analysis of marketing research. In this study, in order to analyze user needs for consumer game software, we focus on tweet data. And we proposed topic extraction method using entropy-based feature selection based feature expansion. We also applied it to the classification of the data e

Kensei Nakai, Hirofumi Nonaka, Asahi Hentona, Yuki Kanai

Scoring patent documents is very useful for technology management. However, conventional methods are based on static models and, thus, do not reflect the growth potential of the technology cluster of the patent. Because even if the cluster of a patent has no hope of growing, we recognize the patent is important if PageRank or other ranking score is high. The

Amrith Kumar, Kenneth Rugg

In designing a distributed service, three desirable attributes are Consistency, Availability and Partition Tolerance. In this note we explore a framework for characterizing these three in a manner that establishes definite limits and relationships between them, and explore some implications of this characterization.

Jianwu Fang, Dingxin Yan, Jiahuan Qiao, Jianru Xue

Driver attention prediction is currently becoming the focus in safe driving research community, such as the DR(eye)VE project and newly emerged Berkeley DeepDrive Attention (BDD-A) database in critical situations. In safe driving, an essential task is to predict the incoming accidents as early as possible. BDD-A was aware of this problem and collected the dr

Mkhuseli Ngxande, Jule-Raymond Tapamo, Michael Burke

Convolutional Neural Networks (CNNs) have been used successfully across a broad range of areas including data mining, object detection, and in business. The dominance of CNNs follows a breakthrough by Alex Krizhevsky which showed improvements by dramatically reducing the error rate obtained in a general image classification task from 26.2% to 15.4%. In road

Damon Bayer, Semhar Michael

A U.S. Senator from South Dakota donated documents that were accumulated during his service as a house representative and senator to be housed at the Bridges library at South Dakota State University. This project investigated the utility of quantitative statistical methods to explore some portions of this vast document collection. The available scanned docum

Asahi Hentona, Takeshi Sakumoto, Hugo Alberto Mendoza España, Hirofumi Nonaka

The scoring of patents is useful for technology management analysis. Therefore, a necessity of developing citation network clustering and prediction of future citations for practical patent scoring arises. In this paper, we propose a community detection method using the Node2vec. And in order to analyze growth potential we compare three &#39;&#39;time series

Giovanni Brajato, Lars Lundberg, Victor Torres-Company, Darko Zibar

A novel tool, based on Bayesian filtering framework and expectation maximization algorithm, is numerically and experimentally demonstrated for accurate frequency comb noise characterization. The tool is statistically optimum in a mean-square-error-sense, works at wide range of SNRs and offers more accurate noise estimation compared to conventional methods.

Hiroki Horino, Hirofumi Nonaka, Elisa Claire Alemán Carreón, Toru Hiraoka

In recent years, data posted about real estate on the Internet is currently increasing. In this study, in order to analyze user needs for real estate, we focus on &#34;Mansion Community&#34; which is a Japanese bulletin board system (hereinafter referred to as BBS) about Japanese real estate. In our study, extraction of keywords is performed based on the cal

K. N. Singh, S. K. Maurya, Farook Rahaman, Francisco Tello-Ortiz

In the present article, we discuss relativistic anisotropic solutions of the Einstein field equation for the spherically symmetric line element under the class I condition. To do so we apply the embedding class one technique using Eisland condition. Within this approach, one arrives at a particular differential equation that links the two metric components $