April 2019 arXiv papers — page 121

Saurabh Sharma, Pavan Teja Varigonda, Prashast Bindal, Abhishek Sharma

Monocular 3D human-pose estimation from static images is a challenging problem, due to the curse of dimensionality and the ill-posed nature of lifting 2D-to-3D. In this paper, we propose a Deep Conditional Variational Autoencoder based model that synthesizes diverse anatomically plausible 3D-pose samples conditioned on the estimated 2D-pose. We show that CVA

Xiaolun Jia, Xiangyun Zhou

In this paper, we examine the error performance of backscatter communication in the presence of ambient interference, where the backscatter device acts as a relay. Specifically, the performance comparison of amplify-and-forward (AF) and decode-and-forward (DF) backscatter relaying is considered for the first time. Considering energy-based detection for on-of

Pei-Ming Ho, Yoshinori Matsuo, Shu-Jung Yang

For a black hole of Schwarzschild radius $a$, we argue that the back-reaction of the vacuum energy-momentum tensor is in general important at the apparent horizon when the time scale of a process is larger than order $a$. In particular, in a double-shell model, we show that the ignorance of the back-reaction leads to a divergence in the outgoing vacuum energ

Michael Messer

A method for change point detection is proposed. We consider a univariate sequence of independent random variables with piecewise constant expectation and variance, apart from which the distribution may vary periodically. We aim to detect change points in both expectation and variance. For that, we propose a statistical test for the null hypothesis of no cha

Paul Boes, Rodrigo Gallego, Nelly H. Y. Ng, Jens Eisert

Fluctuation theorems impose constraints on possible work extraction probabilities in thermodynamical processes. These constraints are stronger than the usual second law, which is concerned only with average values. Here, we show that such constraints, expressed in the form of the Jarzysnki equality, can be bypassed if one allows for the use of catalysts - ad

Guillaume Delorme, Yihong Xu, Stephane Lathuilière, Radu Horaud

Unsupervised person re-ID is the task of identifying people on a target data set for which the ID labels are unavailable during training. In this paper, we propose to unify two trends in unsupervised person re-ID: clustering & fine-tuning and adversarial learning. On one side, clustering groups training images into pseudo-ID labels, and uses them to fine-tun

Mor Rozner, Evgeni Grishin, Yonadav Barry Ginat, Andrei P. Igoshev

We investigate the extent to which resonances between an oscillating background of ultra-light axion and a binary Keplerian system can affect the motion of the latter. These resonances lead to perturbations in the instantaneous time-of-arrivals, and to secular variations in the period of the binary. While the secular changes at exact resonance have recently

Luigi Bonati, Yue-Yu Zhang, Michele Parrinello

Sampling complex free energy surfaces is one of the main challenges of modern atomistic simulation methods. The presence of kinetic bottlenecks in such surfaces often renders a direct approach useless. A popular strategy is to identify a small number of key collective variables and to introduce a bias potential that is able to favor their fluctuations in ord

Sheng Shen, Daniel Fried, Jacob Andreas, Dan Klein

We improve the informativeness of models for conditional text generation using techniques from computational pragmatics. These techniques formulate language production as a game between speakers and listeners, in which a speaker should generate output text that a listener can use to correctly identify the original input that the text describes. While such ap

Pablo Pedregal

Starting from a Pfaffian equation in dimension $N$ and focusing on compact solutions for it, we place in perspective the variational method used in [29] to solve Hilbert's 16th problem. In addition to exploring how this viewpoint can help in detecting and finding approximations for limit cycles of planar systems, we recall some of the initial important f

Timo Stoffregen, Guillermo Gallego, Tom Drummond, Lindsay Kleeman

In contrast to traditional cameras, whose pixels have a common exposure time, event-based cameras are novel bio-inspired sensors whose pixels work independently and asynchronously output intensity changes (called "events"), with microsecond resolution. Since events are caused by the apparent motion of objects, event-based cameras sample visual information ba

Jaume Llibre, Pablo Pedregal

We provide an upper bound for the number of limit cycles that planar polynomial differential systems of a given degree may have. The bound turns out to be a polynomial of degree four in the degree of the system. The strategy brings together variational and dynamical system techniques by transforming the task of counting limit cycles into counting critical po

Ville Salo

We show that the CPE class $α$ of Barbieri and García-Ramos contains a one-dimensional subshift for all countable ordinals $α$, i.e.\ the process of alternating topological and transitive closure on the entropy pairs relation of a subshift can end on an arbitrary ordinal. This is the composition of three constructions: We first realize every ordinal as the l

I. L. Buchbinder, M. V. Khabarov, T. V. Snegirev, Yu. M. Zinoviev

In the recent paper [1] the classification of non-unitary representations of the three dimensional superconformal group has been constructed. From AdS/CFT they must correspond to N=1 supermultiplets containing partially massless fields in $AdS_4$. Moreover, the simplest example of such supermultiplets which contains a partially massless spin-2 was explicitly

Yuxin He, Yang Zhao, Kwok Leung Tsui

Travel demand analysis at the planning stage is important for metro system development. In practice, travel demand can be affected by various factors. This paper focuses on investigating the factors influencing Taipei metro ridership at station level over varying time periods. Ordinary Least Square (OLS) multiple regression models with backward stepwise feat

Francis P Chmiel, Dharmalingam Prabahakaran, Paul Steadman, Jiahao Chen

By employing resonant X-ray microdiffraction, we image the magnetisation and magnetic polarity domains of the Y-type hexaferrite Ba$_{0.5}$Sr$_{1.5}$Mg$_2$Fe$_{12}$O$_{22}$. We show that the magnetic polarity domain structure can be controlled by both magnetic and electric fields, and that full inversion of these domains can be achieved simply by reversal of

Guillaume Scamps, Cédric Simenel

Fission of atomic nuclei often produces mass asymmetric fragments. However, the origin of this asymmetry was believed to be different in actinides and in the sub-lead region [A. Andreyev {\it et al.}, Phys. Rev. Lett. {\bf 105}, 252502 (2010)]. It has recently been argued that quantum shell effects stabilising pear shapes of the fission fragments could expla

Jack H. Koolen, Brhane Gebremichel, Jae Young Yang, Qianqian Yang

Let $λ\geq2$ be an integer. For strongly regular graphs with parameters $(v, k, a,c)$ and smallest eigenvalue $-λ$, Neumaier gave two bounds on $c$ by using algebraic property of strongly regular graphs. In this paper, we will study a new class of regular graphs called sesqui-regular graphs, which contains strongly regular graphs as a subclass, and prove tha

Juan M. Losada, Arne Brataas, Alireza Qaiumzadeh

Light enables ultrafast, direct and nonthermal control of the exchange and Dzyaloshinskii-Moriya interactions. We consider two-dimensional honeycomb lattices described by the Kane-Mele-Hubbard model at half filling and in the strongly correlated limit, i.e., the Mott insulator phase of a canted antiferromagnet. Based on Floquet theory, we demonstrate that by

Jarkko Kari, Etienne Moutot

In this paper we study colorings (or tilings) of the two-dimensional grid $\mathbb{Z}^2$. A coloring is said to be valid with respect to a set $P$ of $n\times m$ rectangular patterns if all $n\times m$ sub-patterns of the coloring are in $P$. A coloring $c$ is said to be of low complexity with respect to a rectangle if there exist $m,n\in\mathbb{N}$ and a se

Olivier Bernardi, Philippe Nadeau

Let G be a graph, and let $χ$G be its chromatic polynomial. For any non-negative integers i, j, we give an interpretation for the evaluation $χ$ (i) G (--j) in terms of acyclic orientations. This recovers the classical interpretations due to Stanley and to Green and Zaslavsky respectively in the cases i = 0 and j = 0. We also give symmetric function refineme

Subhankar Roy, Enver Sangineto, Begüm Demir, Nicu Sebe

Hashing methods have been recently found very effective in retrieval of remote sensing (RS) images due to their computational efficiency and fast search speed. The traditional hashing methods in RS usually exploit hand-crafted features to learn hash functions to obtain binary codes, which can be insufficient to optimally represent the information content of

Hongliang Zhang, Lingyang Song, Zhu Han, H. Vincent Poor

Unmanned aerial vehicles (UAVs) are powerful Internet-of-Things components to provide sensing and communications in the air due to their advantages in mobility and flexibility. As aerial users, UAVs are envisioned to support various sensing applications in the next generation cellular systems, which have been studied by the Third Generation Partnership Proje

Jose R. Leon, José León, Alain Rouault

We revisit Wschebor's theorems on small increments for processes with scaling and stationary properties and deduce large deviation principles.

Saiei-Jaeyeong Matsubara-Heo, Nobuki Takayama

We show that the cohomology intersection number of a twisted Gauss-Manin connection with regularization condition is a rational function. As an application, we obtain a new quadratic relation associated to period integrals of a certain family of K3 surfaces.

Rakesh Kumar, Ravinder Kumar, Tanya Sharma

In present analysis, nanofluid transport near to a stagnation region over a bidirectionally deforming surface is scrutinized. The region is embedded with Darcy-Forchheimer medium which supports permeability. The porous matrix is suspended with nanofluid, and surface is under the influence of inconsistent heat source/sink. Using similarity functions, framed g

Hassan Firouzjahi, Bahram Mashhoon

We find exact nonlinear solutions of general relativity that represent twisted gravitational waves (TGWs) in the presence of a cosmological constant. A TGW is a nonplanar wave propagating along a fixed spatial direction with a null Killing wave vector that has a nonzero twist tensor. The solutions all turn out to have wave fronts with negative Gaussian curva

Walid Abdullah Al, Il Dong Yun, Eun Ju Chun

Left atrial appendage (LAA) closure (LAAC) is a minimally invasive implant-based method to prevent cardiovascular stroke in patients with non-valvular atrial fibrillation. Assessing the LAA orifice in preoperative CT angiography plays a crucial role in choosing an appropriate LAAC implant size and a proper C-arm angulation. However, accurate orifice localiza

Erika Kawakami, Asem Elarabi, Denis Konstantinov

We propose and experimentally demonstrate a new spectroscopic method, image-charge detection, for the Rydberg states of surface electrons on liquid helium. The excitation of the Rydberg states of the electrons induces an image current in the circuit to which the electrons are capacitively coupled. In contrast to the conventional microwave absorption measurem

Carl Heiles, Di Li, Naomi McClure-Griffiths, Lei Qian

The gases of the interstellar medium (ISM) possess orders of magnitude more mass than those of all the stars combined and are thus the prime component of the baryonic universe. With L-band surface sensitivity even better than the planned phase one Square-Kilometer-Array (SKA1), the Five-hundred-meter Aperture Spherical radio Telescope (FAST) promises unprece

Ali Ebrahimpour-Boroojeny, Sanjay Rajopadhye, Hamidreza Chitsaz

RNA-RNA interaction (RRI) is ubiquitous and has complex roles in the cellular functions. In human health studies, miRNA-target and lncRNAs are among an elite class of RRIs that have been extensively studied. Bacterial ncRNA-target and RNA interference are other classes of RRIs that have received significant attention. In recent studies, mRNA-mRNA interaction

Kazuki Iida, Maiko Kofu, Katsuhiro Suzuki, Naoki Murai

Low-energy incommensurate (IC) magnetic fluctuations in the multiband superconductor Sr$_2$RuO$_4$ is investigated by high-resolution inelastic neutron scattering measurements and random phase approximation (RPA) calculations. Below $T_\text{c}$, the substantial spin gap is observed at $\mathbf{Q}_\text{IC}=(0.3, 0.3, L)$ where the quasi-one-dimensional $α$

Demitry Farfurnik, Nir Bar-Gill

Spin-bath noise characterization, which is typically performed by multi-pulse control sequences, is essential for understanding most spin dynamics in the solid-state. Here, we theoretically propose a method for extracting the characteristic parameters of a noise source with a known spectrum, using a single modified Hahn-echo sequence. By varying the applicat

Kira Alhorn, Holger Dette, Kirsten Schorning

In this paper we construct optimal designs for frequentist model averaging estimation. We derive the asymptotic distribution of the model averaging estimate with fixed weights in the case where the competing models are non-nested and none of these models is correctly specified. A Bayesian optimal design minimizes an expectation of the asymptotic mean squared

Mirek Giersz, Abbas Askar, Long Wang, Arkadiusz Hypki

We investigate the dissolution process for dynamically evolving star clusters embedded in an external tidal field by exploring the MOCCA Survey Database I, with focus on the presence and evolution of a stellar-mass black hole subsystem. We argue that the presence of a black hole subsystem can lead to the dissolution of tidally filling star clusters and this

Efrain Rojas

We show that the Lovelock type brane gravity is naturally holographic by providing a correspondence between bulk and surface terms that appear in the Lovelock-type brane gravity action functional. We prove the existence of relationships between the $\mathcal{L}_{\mbox{\tiny bulk}}$ and $\mathcal{L}_{\mbox{\tiny surf}}$ allowing $\mathcal{L}_{\mbox{\tiny surf

K. Narayan

We describe connected timelike codim-2 extremal surfaces stretching between the future and the past boundaries in the static patch coordinatization of de Sitter space. These are analogous to rotated versions of certain surfaces in the $AdS$ black hole. The existence of these surfaces via the $dS/CFT$ framework suggests the speculation that $dS_4$ is dual to

Nasimeh Heydaribeni, Achilleas Anastasopoulos

In the standard Mechanism Design framework, agents' messages are gathered at a central point and allocation/tax functions are calculated in a centralized manner, i.e., as functions of all network agents' messages. This requirement may cause communication and computation overhead and necessitates the design of mechanisms that alleviate this bottleneck

Shruti Nagpal, Maneet Singh, Richa Singh, Mayank Vatsa

Do very high accuracies of deep networks suggest pride of effective AI or are deep networks prejudiced? Do they suffer from in-group biases (own-race-bias and own-age-bias), and mimic the human behavior? Is in-group specific information being encoded sub-consciously by the deep networks? This research attempts to answer these questions and presents an in-dep

Hitoshi Murakami, Anh T. Tran

We calculate the asymptotic behavior of the Kashaev invariant of a twice-itarated torus knot and obtain topological interpretation of the formula in terms of the Chern--Simons invariant and the twisted Reidemeister torsion.

Luis Rey Díaz-Barrón, Abraham Espinoza-García, S. Pérez-Payán, J. Socorro

In this work we construct a noncommutative version of the Friedmann equations in the framework of effective loop quantum cosmology, extending and applying the ideas presented in a previous proposal by some of the authors. The model under consideration is a flat FRW spacetime with a free scalar field. First, noncommutativity in the momentum sector is introduc

Ben Li, Carsten Schuett, Elisabeth M. Werner

We introduce the notion of Loewner (ellipsoid) function for a log concave function and show that it is an extension of the Loewner ellipsoid for convex bodies. We investigate its duality relation to the recently defined John (ellipsoid) function by Alonso-Gutierrez, Merino, Jimenez and Villa. For convex bodies, John and Loewner ellipsoids are dual to each ot

Azumi Mamiya, Genki Ichinose

The theory of repeated games analyzes the long-term relationship of interacting players and mathematically reveals the condition of how cooperation is achieved, which is not achieved in a one-shot game. In the repeated prisoner's dilemma (RPD) game with no errors, zero-determinant (ZD) strategies allow a player to unilaterally set a linear relationship b

Daisuke Kishimoto, Toshiyuki Miyauchi

Let $(G,H)=(SU(2n+1),SO(2n+1)),\,(SU(2n),Sp(n)),\,(SO(2n),SO(2n-1)),\,(E_6,F_4),\,(Spin(8),G_2)$, and let $p$ be any prime $\ge 5$ for $(G,H)=(E_6,F_4)$, any prime $p\ne 3$ for $(G,H)=(Spin(8),G_2)$, and any odd prime otherwise. The classical result of Harris on the relation between the homotopy groups of $G$ and $H$ is reinterpreted as a $p$-local homotopy

Mike Li, X. Rosalind Wang

We present ChromAlignNet, a deep learning model for alignment of peaks in Gas Chromatography-Mass Spectrometry (GC-MS) data. In GC-MS data, a compound's retention time (RT) may not stay fixed across multiple chromatograms. To use GC-MS data for biomarker discovery requires alignment of identical analyte's RT from different samples. Current methods of

Manolis Savva, Abhishek Kadian, Oleksandr Maksymets, Yili Zhao

We present Habitat, a platform for research in embodied artificial intelligence (AI). Habitat enables training embodied agents (virtual robots) in highly efficient photorealistic 3D simulation. Specifically, Habitat consists of: (i) Habitat-Sim: a flexible, high-performance 3D simulator with configurable agents, sensors, and generic 3D dataset handling. Habi

Jesus Tordesillas, Juncal Arbelaiz

Reinforcement learning algorithms are gaining popularity in fields in which optimal scheduling is important, and oncology is not an exception. The complex and uncertain dynamics of cancer limit the performance of traditional model-based scheduling strategies like Optimal Control. Motivated by the recent success of model-free Deep Reinforcement Learning (DRL)

Stephan M. Bischofberger, Munir Hiabu, Alex Isakson

We introduce a continuous-time framework for the prediction of outstanding liabilities, in which chain-ladder development factors arise as a histogram estimator of a cost-weighted hazard function running in reversed development time. We use this formulation to show that under our assumptions on the individual data chain-ladder is consistent. Consistency is u

Sulaiman A. Alghunaim, Ali H. Sayed

In this work, we revisit a classical incremental implementation of the primal-descent dual-ascent gradient method used for the solution of equality constrained optimization problems. We provide a short proof that establishes the linear (exponential) convergence of the algorithm for smooth strongly-convex cost functions and study its relation to the non-incre

Julien R. Landel, François J. Peaudecerf, Fernando Temprano-Coleto, Frédéric Gibou

Superhydrophobic surfaces (SHSs) have the potential to reduce drag at solid boundaries. However, multiple independent studies have recently shown that small amounts of surfactant, naturally present in the environment, can induce Marangoni forces that increase drag, at least in the laminar regime. To obtain accurate drag predictions, one must solve the mass,

Yi Wan, Zaheer Abbas, Adam White, Martha White

Distribution and sample models are two popular model choices in model-based reinforcement learning (MBRL). However, learning these models can be intractable, particularly when the state and action spaces are large. Expectation models, on the other hand, are relatively easier to learn due to their compactness and have also been widely used for deterministic e

Antônio H. Ribeiro, Manoel Horta Ribeiro, Gabriela M. M. Paixão, Derick M. Oliveira

The role of automatic electrocardiogram (ECG) analysis in clinical practice is limited by the accuracy of existing models. Deep Neural Networks (DNNs) are models composed of stacked transformations that learn tasks by examples. This technology has recently achieved striking success in a variety of task and there are great expectations on how it might improve

Anton Arnold, Shi Jin, Tobias Wöhrer

We review the Lyapunov functional method for linear ODEs and give an explicit construction of such functionals that yields sharp decay estimates, including an extension to defective ODE systems. As an application, we consider three evolution equations, namely the linear convection-diffusion equation, the two velocity BGK model and the Fokker-Planck equation.

Pengfei Zhang, Cuiling Lan, Wenjun Zeng, Junliang Xing

Skeleton-based human action recognition has attracted great interest thanks to the easy accessibility of the human skeleton data. Recently, there is a trend of using very deep feedforward neural networks to model the 3D coordinates of joints without considering the computational efficiency. In this paper, we propose a simple yet effective semantics-guided ne

Hao Jia

We prove linear inviscid damping near a general class of monotone shear flows in a finite channel, in Gevrey spaces. It is an essential step towards proving nonlinear inviscid damping for general shear flows that are not close to the Couette flow, which is a major open problem in 2d Euler equations.

Ilya Gekhtman, Giulio Tiozzo

We prove a generalization of the fundamental inequality of Guivarc'h relating entropy, drift and critical exponent to Gibbs measures on geometrically finite quotients of CAT(-1) metric spaces. For random walks with finite superexponential moment, we show that the equality is achieved if and only if the Gibbs density is equivalent to the hitting measure.

Hanting Chen, Yunhe Wang, Chang Xu, Zhaohui Yang

Learning portable neural networks is very essential for computer vision for the purpose that pre-trained heavy deep models can be well applied on edge devices such as mobile phones and micro sensors. Most existing deep neural network compression and speed-up methods are very effective for training compact deep models, when we can directly access the training

Xuehe Wang, Lingjie Duan

Fueled by the rapid development of communication networks and sensors in portable devices, today many mobile users are invited by content providers to sense and send back real-time useful information (e.g., traffic observations and sensor data) to keep the freshness of the providers' content updates. However, due to the sampling cost in sensing and trans

Nitish Nag, Aditya Bharadwaj, Aditya Narendra Rao, Akash Kulhalli

We propose a mechanism to use the features of flavour to enhance the quality of food recommendations. An empirical method to determine the flavour of food is incorporated into a recommendation engine based on major gustatory nerves. Such a system has advantages of suggesting food items that the user is more likely to enjoy based upon matching with their flav

Hao Li, Xiangxiong Zhang

The classical continuous finite element method with Lagrangian $Q^k$ basis reduces to a finite difference scheme when all the integrals are replaced by the $(k+1)\times (k+1)$ Gauss-Lobatto quadrature. We prove that this finite difference scheme is $(k+2)$-th order accurate in the discrete 2-norm for an elliptic equation with Dirichlet boundary conditions, w

Shahinur Alam, Mohammed Yeasin

SafeAccess is an integrated system designed to provide easier and safer access to a smart home for people with or without disabilities. The system is designed to enhance safety and promote the independence of people with disability (i.e., visually impaired). The key functionality of the system includes the detection and identification of human and generating

George Lusztig, Zhiwei Yun

For a split reductive group $G$ over a finite field, we show that the neutral block of its mixed Hecke category with a fixed monodromy under the torus action is monoidally equivalent to the mixed Hecke category of the corresponding endoscopic group $H$ with trivial monodromy. We also extend this equivalence to all blocks. We give two applications. One is a r

Shane Storks, Qiaozi Gao, Joyce Y. Chai

In the NLP community, recent years have seen a surge of research activities that address machines' ability to perform deep language understanding which goes beyond what is explicitly stated in text, rather relying on reasoning and knowledge of the world. Many benchmark tasks and datasets have been created to support the development and evaluation of such

Shang-Hua Gao, Ming-Ming Cheng, Kai Zhao, Xin-Yu Zhang

Representing features at multiple scales is of great importance for numerous vision tasks. Recent advances in backbone convolutional neural networks (CNNs) continually demonstrate stronger multi-scale representation ability, leading to consistent performance gains on a wide range of applications. However, most existing methods represent the multi-scale featu

Anirban Bhattacharjee, Ajay Dev Chhokra, Zhuangwei Kang, Hongyang Sun

Pre-trained deep learning models are increasingly being used to offer a variety of compute-intensive predictive analytics services such as fitness tracking, speech and image recognition. The stateless and highly parallelizable nature of deep learning models makes them well-suited for serverless computing paradigm. However, making effective resource managemen

Sunjin Choi, Seok Kim

We study supersymmetric AdS$_6$ black holes at large angular momenta, from the index of 5d SCFTs on $S^4\times\mathbb{R}$ in the large $N$ and Cardy limit. Our examples are the strong coupling limits of 5d gauge theories on the D4-D8-O8 system. The large $N$ free energy scales like $N^{5/2}$, statistically accounting for the entropy of large black holes in A

V. G. Kogan, R. Prozorov, A. E. Koshelev

We show on a few examples of one-band materials with spheroidal Fermi surfaces and anisotropic order parameters that anisotropies $γ_H$ of the upper critical field and $γ_λ$ of the London penetration depth depend on temperature, the feature commonly attributed to multi-band superconductors. The parameters $γ_H$ and $γ_λ$ may have opposite temperature depende

Amirkoushyar Ziabari, Michael Kirka, Vincent Paquit, Philip Bingham

In this paper, we present a deep learning algorithm to rapidly obtain high quality CT reconstructions for AM parts. In particular, we propose to use CAD models of the parts that are to be manufactured, introduce typical defects and simulate XCT measurements. These simulated measurements were processed using FBP (computationally simple but result in noisy ima

Junlong Feng

Models with a discrete endogenous variable are typically underidentified when the instrument takes on too few values. This paper presents a new method that matches pairs of covariates and instruments to restore point identification in this scenario in a triangular model. The model consists of a structural function for a continuous outcome and a selection mod

Max Glonek, Jonathan Tuke, Lewis Mitchell, Nigel Bean

Graph labelling is a key activity of network science, with broad practical applications, and close relations to other network science tasks, such as community detection and clustering. While a large body of work exists on both unsupervised and supervised labelling algorithms, the class of random walk-based supervised algorithms requires further exploration,

Elias S. Helou, Marcelo V. W. Zibetti, Leon Axel, Kai Tobias Block

Estimation of the Discrete-Time Fourier Transform (DTFT) at points of a finite domain arises in many imaging applications. A new approach to this task, the Golden Angle Linogram Fourier Domain (GALFD), is presented, together with a computationally fast and accurate tool, named Golden Angle Linogram Evaluation (GALE), for approximating the DTFT at points of a

Kouki Nakata, Yuichi Ohnuma, Mamoru Matsuo

Extending a Boltzmann-Langevin theory to magnons, we show a universality of current-noise suppression in diffusive systems against the difference of quantum-statistical properties of bosons and fermions. To this end, starting from a quantum kinetic equation for magnons subjected to thermal gradient in dilute impurities, we derive a bosonic counterpart of the

Qihang Yu, Yingda Xia, Lingxi Xie, Elliot K. Fishman

There has been a debate in 3D medical image segmentation on whether to use 2D or 3D networks, where both pipelines have advantages and disadvantages. 2D methods enjoy a low inference time and greater transfer-ability while 3D methods are superior in performance for hard targets requiring contextual information. This paper investigates efficient 3D segmentati

SNO Collaboration, B. Aharmim, S. N. Ahmed, A. E. Anthony

Neutron production in GeV-scale neutrino interactions is a poorly studied process. We have measured the neutron multiplicities in atmospheric neutrino interactions in the Sudbury Neutrino Observatory experiment and compared them to the prediction of a Monte Carlo simulation using GENIE and a minimally modified version of GEANT4. We analyzed 837 days of expos

Prakash Adekkanattu, Guoqian Jiang, Yuan Luo, Paul R. Kingsbury

While natural language processing (NLP) of unstructured clinical narratives holds the potential for patient care and clinical research, portability of NLP approaches across multiple sites remains a major challenge. This study investigated the portability of an NLP system developed initially at the Department of Veterans Affairs (VA) to extract 27 key cardiac

Yi Yang, Baile Xu, Furao Shen, Jian Zhao

User response prediction makes a crucial contribution to the rapid development of online advertising system and recommendation system. The importance of learning feature interactions has been emphasized by many works. Many deep models are proposed to automatically learn high-order feature interactions. Since most features in advertising system and recommenda

Djallel Bouneffouf, Irina Rish

In recent years, multi-armed bandit (MAB) framework has attracted a lot of attention in various applications, from recommender systems and information retrieval to healthcare and finance, due to its stellar performance combined with certain attractive properties, such as learning from less feedback. The multi-armed bandit field is currently flourishing, as n

Adam Rambousek, Harry Parkin, Ales Horak

This paper describes the design and development of specific software tools used during the creation of Family Names in Britain and Ireland (FaNBI) research project, started by the University of the West of England in 2010 and finished successfully in 2016. First, the overview of the project and methodology is provided. Next section contains the description o

Shiva Azimi, Brejesh lall, Tapan K. Gandhi

Plant Phenomics based on imaging based techniques can be used to monitor the health and the diseases of plants and crops. The use of 3D data for plant phenomics is a recent phenomenon. However, since 3D point cloud contains more information than plant images, in this paper, we compare the performance of different keypoint detectors and local feature descript

Martin Mundt, Sagnik Majumder, Sreenivas Murali, Panagiotis Panetsos

Recognition of defects in concrete infrastructure, especially in bridges, is a costly and time consuming crucial first step in the assessment of the structural integrity. Large variation in appearance of the concrete material, changing illumination and weather conditions, a variety of possible surface markings as well as the possibility for different types o

Syed Arbaaz Qureshi, Mohammed Hasanuzzaman, Sriparna Saha, Gaël Dias

Depression is a serious medical condition that is suffered by a large number of people around the world. It significantly affects the way one feels, causing a persistent lowering of mood. In this paper, we propose a novel attention-based deep neural network which facilitates the fusion of various modalities. We use this network to regress the depression leve

Minglong Qi, Shengwu Xiong

In the paper of Tor Helleseth and Victor Zinoviev (Designs, Codes and Cryptography, \textbf{17}, 269-288(1999)), the number of solutions of the system of equations from $ Z_{4} $-linear Goethals codes $ G_{4} $ was determined and stated in Theorem 4. We found that Theorem 4 is wrong for $ m $ even. In this note, we complete Theorem 4, and present a series of

Honglei Lang, Zhangju Liu, Yunhe Sheng

Affine structures on a Lie groupoid, including affine $k$-vector fields, $k$-forms and $(p,q)$-tensors are studied. We show that the space of affine structures is a 2-vector space over the space of multiplicative structures. Moreover, the space of affine multivector fields has a natural graded strict Lie 2-algebra structure and affine (1,1)-tensors constitut

Ramakrishna Tipireddy, Paris Perdikaris, Panos Stinis, Alexandre Tartakovsky

We investigate the use of discrete and continuous versions of physics-informed neural network methods for learning unknown dynamics or constitutive relations of a dynamical system. For the case of unknown dynamics, we represent all the dynamics with a deep neural network (DNN). When the dynamics of the system are known up to the specification of constitutive

Hang Zou, Chao Zhang, Samson Lasaulce

In this paper, we propose a new perspective for quantizing a signal and more specifically the channel state information (CSI). The proposed point of view is fully relevant for a receiver which has to send a quantized version of the channel state to the transmitter. Roughly, the key idea is that the receiver sends the right amount of information to the transm

Francesco Calogero, Farrin Payandeh

The evolution equations mentioned in the title of this paper read as follows: x~n = P(n)(x1; x2) , n = 1, 2 , where l is the "discrete-time" independent variable taking integer values (l =0, 1, 2, ...), xn = xn (l) are the 2 dependent variables, x~n = xn (l + 1), and the 2 functions P(n)(x1, x2), n = 1, 2, are 2 polynomials in the 2 dependent variabl

Francesco Calogero, Farrin Payandeh

We tersely review a recently introduced technique to identify systems of two nonlinearly-coupled Ordinary Di§erential Equations (ODEs) solvable by algebraic operations; and we report some specifc examples of this kind, namely systems of 2 first-order ODEs with polynomial right-hand sides, x_ n= P(n)(x1, x2) , n = 1, 2 , satisfied by the 2 (possibly complex )

Francesco Calogero, Farrin Payandeh

In this paper we report a few examples of algebraically solvable dynamical systems characterized by 2 coupled Ordinary Differential Equations which read as follows: x_n = P(n) (x1, x2) , n = 1, 2 , with P(n) (x1, x2) specific polynomials of relatively low degree in the 2 dependent variables x1 = x1 (t) and x2 = x2 (t) . These findings are obtained via a new

Francesco Calogero, Farrin Payandeh

In this paper we identify certain peculiar systems of 2 discrete-time evolution equations,x~n = F^(n)(x1; x2) , n = 1, 2 , which are algebraically solvable. Here l is the "discrete-time" independent variable taking integer values (l = 0, 1, 2,...), xn = xn (l) are 2 dependent variables, and x~n = xn (l + 1) are the corresponding 2 updated variables.

M. Vivek

We investigate the connection between the intrinsic C IV absorption line variability and the continuum flux changes of broad absorption line (BAL) quasars using a sample of 78 sources in the Stripe 82 region. The absorption trough variability parameters are measured using the archival multi-epoch spectroscopic data from the Sloan Digital Sky Survey (SDSS), a

Quang Hung Tran

We establish some new constructions of the golden ratio in an arbitrary triangle using symmedians and nine-point circle.

Jorge Pinochet

Between 1974 and 1975, Stephen Hawking revolutionized the world of physics by proposing that black holes have temperature, entropy, and evaporate gradually. The objective of this article is to offer a brief and updated introduction to these three remarkable results, employing only high school algebra and elementary physics. This article may be useful as peda

B. F. Rizzuti, L. M. Gaio, C. Duarte

Abstract axiomatic formulation of mathematical structures are extensively used to describe our physical world. We take here the reverse way. By making basic assumptions as starting point, we reconstruct some features of both geometry and topology in a fully operational manner. Curiously enough, primitive concepts such as points, spaces, straight lines, plane

J. Varela, D. A. Spong, L. Garcia, S. Ohdachi

The aim of this study is to perform a theoretical analysis of the magnetohydrodynamic (MHD) stability and energetic particle effects on a LHD equilibria, calculated during a discharge where energetic-ion-driven resistive interchange mode (EIC) events were triggered. We use the reduced MHD equations to describe the linear evolution of the poloidal flux and th

Trung Hoa Dinh, Minh Toan Ho, Cong Trinh Le, Bich Khue Vo

In this paper we show that for a non-negative operator monotone function $f$ on $[0, \infty)$ such that $f(0)= 0$ and for any positive semidefinite matrices $A$ and $B$, $$ Tr((A-B)(f(A)-f(B))) \le Tr(|A-B|f(|A-B|)). $$ When the function $f$ is operator convex on $[0, \infty)$, the inequality is reversed.

Dun Liang

In this paper we consider plane quartics with to involutions. We compute the Dixmier invariants, the bitangents and the Matrix representation problem of these curves, showing that they have symbolic solutions for the last two questions.

Paul Todorov

We review some practical and philosophical questions raised by the use of machine learning in creative practice. Beyond the obvious problems regarding plagiarism and authorship, we argue that the novelty in AI Art relies mostly on a narrow machine learning contribution : manifold approximation. Nevertheless, this contribution creates a radical shift in the w

Neetik Mukherjee, Amlan K. Roy

Various well-known statistical measures like \emph{López-Ruiz, Mancini, Calbet} (LMC) and \emph{Fisher-Shannon} complexity have been explored for confined isotropic harmonic oscillator (CHO) in composite position ($r$) and momentum ($p$) spaces. To get a deeper insight about CHO, a more generalized form of these quantities with Rényi entropy ($R$) is invoked

C. Saffe, E. Jofre, P. Miquelarena, M. Jaque Arancibia

We explore the probable chemical signature of planet formation in the remarkable binary system HD 106515. The A star hosts a massive long-period planet with 9 MJup detected by radial velocity. We also refine stellar and planetary parameters by using non-solar-scaled opacities when modeling the stars. Methods. We carried out a simultaneous determination of st

Rafael Hernández Heredero, Vladimir Sokolov

We provide a concise introduction to the symmetry approach to integrability. Some results on integrable evolution and systems of evolution equations are reviewed. Quasi-local recursion and Hamiltonian operators are discussed. We further describe non-abelian integrable equations, especially matrix (ODE and PDE) systems. Some non-evolutionary integrable equati