September 2019 arXiv papers — page 38

R. P. Anstee, Farzin Barekat, Zachary Pellegrin

In this paper we relate t-designs to a forbidden configuration problem in extremal set theory. Let 1_t 0_l denote a column of t 1's on top of l 0's. We assume t>l. Let q. (1_t 0_l) denote the (t+l)xq matrix consisting of t rows of q 1's and l rows of q 0's. We consider extremal problems for matrices avoiding certain submatrices. Let A be a (0

Libin Lu, Matthew J. Morse, Abtin Rahimian, Georg Stadler

High-resolution blood flow simulations have potential for developing better understanding biophysical phenomena at the microscale, such as vasodilation, vasoconstriction and overall vascular resistance. To this end, we present a scalable platform for the simulation of red blood cell (RBC) flows through complex capillaries by modeling the physical system as a

Vaibhav Kumar, Barry Cardiff, Mark. F. Flanagan

Non-orthogonal multiple access (NOMA) and spectrum sharing (SS) are two emerging multiple access technologies for efficient spectrum utilization in future wireless communications standards. In this paper, we present the performance analysis of a NOMA-based cooperative relaying system (CRS) in an underlay spectrum sharing scenario, considering a peak interfer

Xuedou Xiao, Wei Wang, Taobin Chen, Yang Cao

Recent advances in unmanned aerial vehicle (UAV) technology have revolutionized a broad class of civil and military applications. However, the designs of wireless technologies that enable real-time streaming of high-definition video between UAVs and ground clients present a conundrum. Most existing adaptive bitrate (ABR) algorithms are not optimized for the

Christos H Skiadas, Charilaos Skiadas

The analytic derivation of a more general model of survival-mortality and the estimation of a parameter bx related to the Healthy Life Years Lost (HLYL) is followed with the formulation of a computer program providing results similar to those of the World Health Organization for the Healthy Life Expectancy (HALE) and the corresponding HLYL estimates. This pr

Ksh. Newton Singh, Farook Rahaman, Ayan Banerjee

We present a physically plausible solution representing Einstein's cluster mimicking the behaviors of compact star in the context of teleparallel equivalent of general relativity. The Teleparallel gravity (TEGR) is an alternative formulation of gravity which uses tetrads as the dynamical variables. We focus on two particularly interesting scenarios. Firs

Glenna Schluck, Wei Wu, Anuj Srivastava

Intensity estimation for Poisson processes is a classical problem and has been extensively studied over the past few decades. Practical observations, however, often contain compositional noise, i.e. a nonlinear shift along the time axis, which makes standard methods not directly applicable. The key challenge is that these observations are not "aligned&#3

Lingchen Zhu, Tuanfeng Zhang

This paper presents a methodology and workflow that overcome the limitations of the conventional Generative Adversarial Networks (GANs) for geological facies modeling. It attempts to improve the training stability and guarantee the diversity of the generated geology through interpretable latent vectors. The resulting samples are ensured to have the equal pro

Heather Riley, Mohan Sridharan

State of the art algorithms for many pattern recognition problems rely on deep network models. Training these models requires a large labeled dataset and considerable computational resources. Also, it is difficult to understand the working of these learned models, limiting their use in some critical applications. Towards addressing these limitations, our arc

Jacques Giacomoni, Divya Goel, K. Sreenadh

The purpose of this article is twofold. First, an issue of regularity of weak solution to the problem $(P)$ (See below) is addressed. Secondly, we investigate the question of $H^s$ versus $C^0$- weighted minimizers of the functional associated to problem $(P)$ and then give applications to existence and multiplicity results.

Artur Czumaj, Christian Sohler

The problem of characterizing testable graph properties (properties that can be tested with a number of queries independent of the input size) is a fundamental problem in the area of property testing. While there has been some extensive prior research characterizing testable graph properties in the dense graphs model and we have good understanding of the bou

David S. Lipham

We show that if $X$ is a separable locally compact Hausdorff connected space with fewer than $\mathfrak c$ non-cut points, then $X$ embeds into a dendrite $D\subseteq \mathbb R ^2$, and the set of non-cut points of $X$ is a nowhere dense $G_δ$-set. We then prove a Tychonoff cut-point space $X$ is weakly orderable if and only if $βX$ is an irreducible continu

Xi Chen, Christos Papadimitriou, Tim Roughgarden

Proof-of-work blockchains reward each miner for one completed block by an amount that is, in expectation, proportional to the number of hashes the miner contributed to the mining of the block. Is this proportional allocation rule optimal? And in what sense? And what other rules are possible? In particular, what are the desirable properties that any "good

Mayra Samaniego, Cristian Espana, Ralph Deters

IoT systems have enabled ubiquitous communication in physical spaces, making them smart Nowadays, there is an emerging concern about evaluating suspicious transactions in smart spaces. Suspicious transactions might have a logical structure, but they are not correct under the present contextual information of smart spaces. This research reviews suspicious tra

David Serantes, Daniel Faílde, Daniel Baldomir, Beatriz Pelaz

$Co$-doping of $Fe_{3}O_{4}$ magnetic nanoparticles is an effective way to tailor their magnetic properties. When considering the two extreme cases of the $Co_{x}Fe_{3-x}O_{4}$ series, i.e. the $x=0$ and $x=1$ values, one finds that the system evolves from a negative cubic-anisotropy energy constant, $K_{C}^{-}<0$, to a positive one, $K_{C}^{+}>0$. Thus, wha

Siddhant Garg

Recent works show that ordering of the training data affects the model performance for Neural Machine Translation. Several approaches involving dynamic data ordering and data sharding based on curriculum learning have been analysed for the their performance gains and faster convergence. In this work we propose to empirically study several ordering approaches

Stephen A. Vavasis, Katerina D. Papoulia, M. Reza Hirmand

Cohesive fracture is among the few techniques able to model complex fracture nucleation and propagation with a sharp (nonsmeared) representation of the crack. Implicit time-stepping schemes are often favored in mechanics due to their ability to take larger time steps in quasistatic and moderate dynamic problems. Furthermore, initially rigid cohesive models a

Sarira Sahu, Carlos E. Lopez Fortin, Shigehiro Nagataki

The high energy peaked blazars are known to undergo episodes of flaring in GeV-TeV gamma-rays involving different time scales and the flaring mechanism is not well understood despite long term simultaneous multiwavelength observations. These gamma-rays en route to Earth undergo attenuation by the extra galactic background light. Using the photohadronic model

Jianhang Xu, Mohan Chen, Cui Zhang, Xifan Wu

An accurate ab initio theory of the H-bond structure of liquid water requires a high-level exchange correlation approximation from density functional theory. Based on the liquid structures modeled by ab initio molecular dynamics by using maximally localized Wannier functions as a basis, we study the infrared spectrum of water within the canonical ensemble. I

Rajveer Nehra, Kevin Valson Jacob

We propose a method for characterizing a photodetector by directly reconstructing the Wigner functions of the detector&#39;s Positive-Operator-Value-Measure (POVM) elements. This method extends the works of S. Wallentowitz and Vogel [Phys. Rev. A 53, 4528 (1996)] and Banaszek and Wódkiewicz [Phys. Rev. Lett. 76, 4344 (1996)] for quantum state tomography via

Behrouz Babaki, Golnoosh Farnadi, Gilles Pesant

Factored stochastic constraint programming (FSCP) is a formalism to represent multi-stage decision making problems under uncertainty. FSCP models support factorized probabilistic models and involve constraints over decision and random variables. These models have many applications in real-world problems. However, solving these problems requires evaluating th

Joshua Kline, Jeff Lindquist, Nageswari Shanmugalingam

We prove a Carathéodory-type extension of BQS homeomorphisms between two domains in proper, locally path-connected metric spaces as homeomorphisms between their prime end closures. We also give a Carathéodory-type extension of geometric quasiconformal mappings between two such domains provided the two domains are both Ahlfors $Q$-regular and support a $Q$-Po

Huaqing Zhang, Xiaolin Cheng, Hui Zang, Dae Hoon Park

An important linear algebra routine, GEneral Matrix Multiplication (GEMM), is a fundamental operator in deep learning. Compilers need to translate these routines into low-level code optimized for specific hardware. Compiler-level optimization of GEMM has significant performance impact on training and executing deep learning models. However, most deep learnin

Augusto E. Mejía Gómez, Diego G. Lamas, Ana Gabriela Leyva, Joaquín Sacanell

A simple method has been used to synthesize nanostructured La0.5Ba0.5CoO3 (LBCO) powders, by confining chemical precursors into the pores of polycarbonate filters. The proposed method allows us to obtain powders formed by crystallites of different sizes, it is scalable and does not involve the use of sophisticated deposition techniques. The area specific pol

Diego Rodríguez-Guzmán

We describe the topological types of leaves of generic logarithmic foliations on the complex projective plane. We prove that all leaves, except for a finite many are biholomorphic to $\mathbb{C}$ or homeomorphic to the surface known as Loch Ness monster.

L. Noel, M. Schmidt, C. Messe, J. A. Evans

This paper presents an adaptive discretization strategy for level set topology optimization of structures based on hierarchical B-splines. This work focuses on the influence of the discretization approach and the adaptation strategy on the optimization results and computational cost. The geometry of the design is represented implicitly by the iso-contour of

Gulmira Yergaliyeva, Tolkynay Myrzakul, Gulgassyl Nugmanova, Kuralay Yesmakhanova

In this paper, we study one of generalized Heisenberg ferromagnet equations with self-consistent sources, namely, the so-called M-CIV equation with self-consistent sources (M-CIVESCS). The Lax representation of the M-CIVESCS is presented. We have shown that the M-CIVESCS and the CH equation with self-consistent sources (CHESCS) is geometrically equivalent ea

Nalini Ravishanker, Renjie Chen

The study of topology is strictly speaking, a topic in pure mathematics. However in only a few years, Topological Data Analysis (TDA), which refers to methods of utilizing topological features in data (such as connected components, tunnels, voids, etc.) has gained considerable momentum. More recently, TDA is being used to understand time series. This article

Raya Dastidar, Kuntal Misra, Stefano Valenti, Jamison Burke

We present the photometry and spectroscopy of SN 2015an, a Type II Supernova (SN) in IC 2367. The recombination phase of the SN lasts up to $\sim$120 d, with a decline rate of 1.24 mag/100d, higher than the typical SNe IIP. The SN exhibits bluer colours than most SNe II, indicating higher ejecta temperatures. The absolute $V$-band magnitude of SN 2015an at 5

Sebastian Goodman, Zhenzhong Lan, Radu Soricut

Neural models for abstractive summarization tend to achieve the best performance in the presence of highly specialized, summarization specific modeling add-ons such as pointer-generator, coverage-modeling, and inferencetime heuristics. We show here that pretraining can complement such modeling advancements to yield improved results in both short-form and lon

Jose A. Carrillo, Edgard A. Pimentel, Vardan K. Voskanyan

In this paper we consider a mean field optimal control problem with an aggregation-diffusion constraint, where agents interact through a potential, in the presence of a Gaussian noise term. Our analysis focuses on a PDE system coupling a Hamilton-Jacobi and a Fokker-Planck equation, describing the optimal control aspect of the problem and the evolution of th

Lin Jiu, Diane Y. H. Shi

Abstract. We generalize the $b$-ary binomial coefficients with negative entries, which is based on the generating function obtained in early work. Besides an explicit expression involving the restricted partition, several properties such as symmetry, congruence and Pascal-like recurrence are studies. Finally, we also provide two different generalizations, pa

Anders W. Sandvik

The Stochastic Series Expansion (SSE) technique is a quantum Monte Carlo method that is especially efficient for many quantum spin systems and boson models. It was the first generic method free from the discretization errors affecting previous path integral based approaches. These lecture notes give a brief overview of the SSE method and its applications. In

Ilyas Noor Bhatti, Imtiaz Noor Bhatti, Rabindra Nath Mahato, M. A. H. Ahsan

3$d$ based double perovskite materials have received much attention in recent years due to their exotic magnetic structure and magneto-electric coupling. In this work we have prepared and studied the nano-crystalline sample of Ho$_2$CoMnO$_6$. Structural, magnetic, Raman and dielectric properties have been studied in detail. The structural analysis shows tha

Eric Jankowski, Charles R. Johnson

It is known (see e.g. [2], [4], [5], [6]) that continuous variations in the entries of a complex square matrix induce continuous variations in its eigenvalues. If such a variation arises from one real parameter $α\in [0, 1]$, then the eigenvalues follow continuous paths in the complex plane as $α$ shifts from $0$ to $1$. The intent here is to study the natur

Ximing Rong, Xinbo Chen, Weida Chen, Xiuwen Zhang

We have introduced the auxetic effect in MBP-analog Sb for the first time, and achieve NPR modulations on monolayer As and Sb via first-principles calculation. Comparing with As, the monolayer Sb is phonon unstable. By applying an uniaxial strain along each directions, we discovered a zigzag-vertical reversibility on out-of-plane NPR, and the NPR values for

Adam Zettel, Mihai Horoi

In a recent article (arxiv:1803.06332) we noticed that the electron density in condensed matter exhibits large spikes close to the atomic nuclei. We showed that these spikes in the electron densities, 3-4 orders of magnitude larger than those inside the Sun&#39;s core, have no effect on the neutrino emission and absorption probabilities or on the neutrinoles

Shaddin Dughmi, Rad Niazadeh, Alexandros Psomas, S. Matthew Weinberg

Lagrangian duality underlies both classical and modern mechanism design. In particular, the dual perspective often permits simple and detail-free characterizations of optimal and approximately optimal mechanisms. This paper applies this same methodology to a close cousin of traditional mechanism design, one which shares conceptual and technical elements with

Vince Kurtz, Hai Lin

Real-world measurement noise in applications like robotics is often correlated in time, but we typically assume i.i.d. Gaussian noise for filtering. We propose general Gaussian Processes as a non-parametric model for correlated measurement noise that is flexible enough to accurately reflect correlation in time, yet simple enough to enable efficient computati

DV Vavoulis, AT Pagnamenta, SJL Knight, MM Pentony

In the context of pharmacogenomics, whole genome sequencing provides a powerful approach for identifying correlations between response variability to specific drugs and genomic polymorphisms in a population, in an unbiased manner. In this study, we employed whole genome sequencing of DNA samples from patients showing extreme response (n=72) and non-response

Grusha Prasad, Marten van Schijndel, Tal Linzen

Neural language models (LMs) perform well on tasks that require sensitivity to syntactic structure. Drawing on the syntactic priming paradigm from psycholinguistics, we propose a novel technique to analyze the representations that enable such success. By establishing a gradient similarity metric between structures, this technique allows us to reconstruct the

Cintia Yamashita, Silvia Helena de Mello e Sousa, Michael A. Kaminski, Maria Virgínia Alves Martins

The distribution of living (rose Bengal stained) Reophax pyriformis Yamashita, Sousa and Kaminski, n. sp., an agglutinated benthic foraminiferal species, was analyzed in the area of the Campos Basin (southeastern Brazilian continental margin). The study is based on 34 oceanographic stations (54 samples), located between 400 m and 3,000 m water depth. The dis

Isam Asaad, Bilal Chiha

In this research, we are going to design a neural nonlinear predictive functional controller (PFC) to achieve a reduced fuel consumption for a chosen autonomous car walks according to a supplied speed trajectory on known roads. We used a fitting neural network as a simple tool for modelling the car&#39;s engine and control laws needed to calculate the suitab

Jiachen Xu, Moritz Grosse-Wentrup, Vinay Jayaram

Methods based on Riemannian geometry have proven themselves to be good models for decoding in brain-computer interfacing (BCI). However, one major drawback of these methods is that it is not possible to determine what aspect of the signal the classifier is built on, leaving open the possibility that artifacts drive classification performance. In areas where

Hieu Thai

We describe some regular behavior in the motivic wedge, which is a subalgebra of the cohomology Ext$_{\mathbf{A}}(\mathbb{M}_2,\mathbb{M}_2)$ of the $\mathbb{C}$-motivic Steenrod algebra. The key tool is to compare motivic computations to classical computations, to Ext$_{\mathbf{A}(2)}(\mathbb{M}_2,\mathbb{M}_2)$, or to $h_1$-localization of Ext$_{\mathbf{A}

AKM Iqtidar Newaz, Amit Kumar Sikder, Mohammad Ashiqur Rahman, A. Selcuk Uluagac

The integration of Internet-of-Things and pervasive computing in medical devices have made the modern healthcare system &#34;smart&#34;. Today, the function of the healthcare system is not limited to treat the patients only. With the help of implantable medical devices and wearables, Smart Healthcare System (SHS) can continuously monitor different vital sign

Wei Zhang, Wei Wei, Lingjie Xu, Lingling Jin

Alibaba has China&#39;s largest e-commerce platform. To support its diverse businesses, Alibaba has its own large-scale data centers providing the computing foundation for a wide variety of software applications. Among these applications, deep learning (DL) has been playing an important role in delivering services like image recognition, objection detection,

Anh Doan, Michael Eracleous, Jessie C. Runnoe, Jia Liu

Velocity offsets in the broad Balmer lines of quasars and their temporal variations serve as indirect evidence for bound supermassive black hole binaries (SBHBs) at sub-parsec separations. In this work, we test the SBHB hypothesis for 14 quasars with double-peaked broad emission lines using their long-term (14--41 years) radial velocity curves. We improve on

Jemin George, Anjaly Parayil, He Bai

This paper presents the formulation and analysis of a two time-scale optimization algorithm for multi-agent coordination for the purpose of distributed beamforming. Each agent is assumed to be randomly positioned with respect to each other with random phase offsets and amplitudes. Agents are tasked with coordinate among themselves to position themselves and

Ziming Qiu, Nitin Nair, Jack Langerman, Orlando Aristizabal

High-frequency ultrasound (HFU) is well suited for imaging embryonic mice in vivo because it is non-invasive and real-time. Manual segmentation of the brain ventricles (BVs) and whole body from 3D HFU images is time-consuming and requires specialized training. This paper presents a deep-learning-based segmentation pipeline which automates several time-consum

Gregory Farquhar, Shimon Whiteson, Jakob Foerster

Gradient-based methods for optimisation of objectives in stochastic settings with unknown or intractable dynamics require estimators of derivatives. We derive an objective that, under automatic differentiation, produces low-variance unbiased estimators of derivatives at any order. Our objective is compatible with arbitrary advantage estimators, which allows

Stefano Carrazza, Juan Cruz-Martinez, Jesús Urtasun-Elizari, Emilio Villa

In this proceedings we describe the computational challenges associated to the determination of parton distribution functions (PDFs). We compare the performance of the convolution of the parton distributions with matrix elements using different hardware instructions. We quantify and identify the most promising data-model configurations to increase PDF fittin

W. Ishibashi

Growing observational evidence confirms the existence of massive black holes ($M_{BH} \sim 10^9 M_{\odot}$), accreting at rates close to the Eddington limit, at very high redshifts ($z \gtrsim 6-7$) in the early Universe. Recent observations indicate that the host galaxies of the first quasars are chemically evolved systems, containing unexpectedly large amo

S. S. Jensen, J. K. Jørgensen, L. E. Kristensen, K. Furuya

The deuterium fractionation of water can serve as a tracer for the chemical and physical evolution of water during star formation and can constrain the origin of water in Solar System bodies. We determine the HDO/H$_2$O ratio in the inner warm gas toward three low-mass Class 0 protostars selected to be in isolated cores, i.e., not associated with any cloud c

Cukanovaite E., P. -E. Tremblay, B. Freytag, H. -G. Ludwig

We perform a calibration of the mixing length parameter at the bottom boundary of the convection zone for helium-dominated atmospheres of white dwarfs. This calibration is based on a grid of 3D DB (pure-helium) and DBA (helium-dominated with traces of hydrogen) model atmospheres computed with the CO5BOLD code, and a grid of 1D DB and DBA envelope structures.

Thayne Currie, Olivier Guyon, Julien Lozi, Tyler Groff

We describe the current performance of the Subaru Coronagraphic Extreme Adaptive Optics (SCExAO) instrument on the Subaru telescope on Maunakea, Hawaii and present early science results for SCExAO coupled with the CHARIS integral field spectrograph. SCExAO now delivers H band Strehl ratios up to $\sim$ 0.9 or better, extreme AO corrections for optically fain

David Puertas Centeno, Mariela Portesi

The well-known Heisenberg--Robertson uncertainty relation for a pair of noncommuting observables, is expressed in terms of the product of variances and the commutator among the operators, computed for the quantum state of a system. Different modified commutation relations have been considered in the last years with the purpose of taking into account the effe

Baoning Wang, Lixin He, Yanqing He, Yinfu Zhang

An all-optical measurement of high-order fractional molecular echoes is demonstrated by using high-order harmonic generation (HHG). Excited by a pair of time-delayed short laser pulses, the signatures of full and high order fractional (1/2 and 1/3) alignment echoes are observed in the HHG signals measured from CO2 molecules at various time delays of the prob

Eko Prasetyo, Prayitno, Jing-Doo Wang, Karisma Trinanda Putra

Recently, extracting some information as a knowledge from big data is very challenging activity. The size of data is very huge and it requires some special techniques and adequate processing hardware. It is also applied in vehicles transportation data at Taiwan National Freeway from the Traffic Data Collection System (TDCS). The results of this extraction wi

Masato Mimura, Norihide Tokushige

Fix a vector space over a finite field and a system of linear equations. We provide estimates, in terms of the dimension of the vector space, of the maximum of the sizes of subsets of the space that do not admit solutions of the system consisting of more than one point. That from above is derived by slice rank method of Tao; to obtain one from below, we defi

Michael J. Schlosser

This is a small contribution to the (September 15, 2019) Liber Amicorum Richard &#34;Dick&#34; Allen Askey. At the end a positivity conjecture related to the First and Second Borwein Conjectures is offered.

Masato Mimura, Norihide Tokushige

We provide an upper bound of the size of a subset A of F_p^n that does not admit a k-star of 3-APs (three-term arithmetic progressions). Namely, the subset A is assumed to contain no configuration of k 3-APs, sharing the middle term, such that all 2k+1 terms are distinct. In the proof, we adapt a new method in the recent work of Sauermann.

Daniel Gillick, Sayali Kulkarni, Larry Lansing, Alessandro Presta

We show that it is feasible to perform entity linking by training a dual encoder (two-tower) model that encodes mentions and entities in the same dense vector space, where candidate entities are retrieved by approximate nearest neighbor search. Unlike prior work, this setup does not rely on an alias table followed by a re-ranker, and is thus the first fully

Stanislav Stefanik, Dalibor Nosek

Reconstruction of energies of very-high-energy gamma-rays observed by imaging atmospheric Cherenkov telescopes is affected by changes in the atmospheric conditions and the performance of telescope components. Reliable calibration schemes aimed at these effects are necessary for the forthcoming Cherenkov Telescope Array (CTA) to achieve its goals on the maxim

Chunhui Guo, Zhicheng Fu, Zhenyu Zhang, Shangping Ren

Improving the effectiveness and safety of patient care is the ultimate objective for medical cyber-physical systems. Many medical best practice guidelines exist, but most of the existing guidelines in handbooks are difficult for medical staff to remember and apply clinically. Furthermore, although the guidelines have gone through clinical validations, valida

Roy Fairstein, Adam Lauz, Kobi Gal, Reshef Meir

Despite the prevalence of voting systems in the real world there is no consensus among researchers of how people vote strategically, even in simple voting settings. This paper addresses this gap by comparing different approaches that have been used to model strategic voting, including expected utility maximization, heuristic decisionmaking, and bounded ratio

Jiahao Guo, Pramesh Singh, Kevin E. Bassler

We introduce an ensemble learning scheme for community detection in complex networks. The scheme uses a Machine Learning algorithmic paradigm we call Extremal Ensemble Learning. It uses iterative extremal updating of an ensemble of network partitions, which can be found by a conventional base algorithm, to find a node partition that maximizes modularity. At

Amnon Rosenmann

The problem of inclusion of the language accepted by timed automaton $A$ (e.g., the implementation) in the language accepted by $B$ (e.g., the specification) is, in general, undecidable in the class of non-deterministic timed automata. In order to tackle this disturbing problem we show how to effectively construct deterministic timed automata $A_d$ and $B_d$

Visak C V Kumar, Sehoon Ha, Gergory Sawicki, C. Karen Liu

Fall prevention is one of the most important components in senior care. We present a technique to augment an assistive walking device with the ability to prevent falls. Given an existing walking device, our method develops a fall predictor and a recovery policy by utilizing the onboard sensors and actuators. The key component of our method is a robust human

P. P. Kong, V. S. Minkov, M. A. Kuzovnikov, S. P. Besedin

The discovery of high-temperature conventional superconductivity in H3S with a critical temperature of Tc=203 K was followed by the recent record of Tc ~250 K in the face-centered cubic (fcc) lanthanum hydride LaH10 compound. It was realized in a new class of hydrogen-dominated compounds having a clathrate-like crystal structure in which hydrogen atoms form

Binil Starly, Atin Angrish, Paul Cohen

The digitalization of manufacturing has created opportunities for consumers to customize products that fit their individualized needs which in turn would drive demand for manufacturing services. However, this pull-based manufacturing system production of extremely low quantity and limitless variety for products is expensive to implement. New emerging technol

Alexey Demyanchuk, Ekaterina Pushkina, Nikolay Russkikh, Dmitry Shtokalo

The hydrocephalus can be either an independent disease or a concomitant symptom of a number of pathologies, therefore representing an urgent issue in the present-day clinical practice. Deep Learning is an evolving technology and the part of a broader field of Machine Learning. Deep learning is currently actively researched in the field of radiology. The aim

Nicolas Espitia, Iasson Karafyllis, Miroslav Krstic

This paper deals with an event-triggered boundary control of constant-parameters reaction-diffusion PDE systems. The approach relies on the emulation of backstepping control along with a suitable triggering condition which establishes the time instants at which the control value needs to be sampled/updated. In this paper, it is shown that under the proposed

Aravind V R, Pradeep Sarvepalli, Andrew Thangaraj

Coded caching is a technique where we utilize multi-casting opportunities to reduce rate in cached networks. One limitation of coded caching schemes is that they reveal the demands of all users to their peers. In this work, we consider coded caching schemes that assure privacy for user demands with a particular focus on reducing subpacketization. For the 2-u

Li Jiang, Hengshuang Zhao, Shu Liu, Xiaoyong Shen

We achieve 3D semantic scene labeling by exploring semantic relation between each point and its contextual neighbors through edges. Besides an encoder-decoder branch for predicting point labels, we construct an edge branch to hierarchically integrate point features and generate edge features. To incorporate point features in the edge branch, we establish a h

Hannaneh Barahouei Pasandi, Tamer Nadeem

Nowadays, video cameras are deployed in large scale for spatial monitoring of physical places (e.g., surveillance systems in the context of smart cities). The massive camera deployment, however, presents new challenges for analyzing the enormous data, as the cost of high computational overhead of sophisticated deep learning techniques imposes a prohibitive o

Hassan Rafique, Tong Wang, Qihang Lin

Driven by an increasing need for model interpretability, interpretable models have become strong competitors for black-box models in many real applications. In this paper, we propose a novel type of model where interpretable models compete and collaborate with black-box models. We present the Model-Agnostic Linear Competitors (MALC) for partially interpretab

Gianluca Cassese

We give an elementary proof of Kelley&#39;s theorem based on a minimax argument. Some applications to related problems are also developed.

Ram Prakash Pandeya, Arindam Pramanik, Anup Pradhan Sakhya, A. Thamizhavel

Surface of quantum materials often exhibits significantly different behavior than the bulk due to changed topologies and symmetry protections. The outstanding problem is to find out if the exoticity of a material is linked to the changed topology at the surface or it is a bulk property. Hard x-ray photoemission spectroscopy (HAXPES) is a significantly bulk s

John McDowall, David J Miller

The Higgs boson quartic self-coupling in the Standard Model appears to become zero just below the Planck scale, with interesting implications to the stability fo the Higgs vacuum at high energies. We review the Multiple Point Principle that suggests the quartic self-coupling should vanish exactly at the Planck scale. Although this vanishing is not consistent

Bruno Bézard, Sandrine Vinatier

We have analyzed spectra recorded between 50 and 650 cm$^{-1}$ by the Composite Infrared Spectrometer (CIRS) aboard the Cassini spacecraft at low and high emission angles to determine simultaneously the H$_2$ mole fraction and ortho-to-para ratio in Titan&#39;s troposphere. We used constraints from limb spectra between 50 and 900 cm$^{-1}$ and from in situ m

A. V. Ivanov, N. N. Leonenko, I. V. Orlovskyi

A continuous-time nonlinear regression model with Lévy-driven linear noise process is considered. Sufficient conditions of consistency and asymptotic normality of the Whittle estimator for the parameter of the noise spectral density are obtained in the paper.

Muhammad Aslam, Abdulaziz Deajim

For square-free positive integers $n$, we study the action of the modular group $\mbox{PSL}(2,\mathbb{Z})$ on the subsets $\{\,\frac{a+\sqrt{-n}}{c}\in \mathbb{Q}(\sqrt{-n})\, | \, a,b=\frac{a^2+n}{c},c \in \mathbb{Z} \,\}$ of the imaginary quadratic number fields $\mathbb{Q}(\sqrt{-n})$. In particular, we compute the number of orbits under this action for a

Pranava Madhyastha, Rishabh Jain

In this paper, we focus on quantifying model stability as a function of random seed by investigating the effects of the induced randomness on model performance and the robustness of the model in general. We specifically perform a controlled study on the effect of random seeds on the behaviour of attention, gradient-based and surrogate model based (LIME) inte

Alfred Gautschy

The shape of light cures of fundamental-mode and of first-overtone pulsators, as observed in RR~Lyrae variables and Cepheids, differ characteristically. The stellar physical origin of the morphological differences is not well documented and the topic seems not to be part of the elementary curriculum of students of stellar variability. To ameliorate the situa

Xiangying Huang, Rick Durrett

A little over 25 years ago Pemantle pioneered the study of the contact process on trees, and showed that on homogeneous trees the critical values $λ_1$ and $λ_2$ for global and local survival were different. He also considered trees with periodic degree sequences, and Galton-Watson trees. Here, we will consider periodic trees in which the number of children

Cullen H. Blake, Dan Li, Joseph R. Tufts, Joe Ninan

Modern precise radial velocity spectrometers are designed to infer the existence of planets orbiting other stars by measuring few-nm shifts in the positions of stellar spectral lines recorded at high spectral resolution on a large-area digital detector. While the spectrometer may be highly stabilized in terms of temperature, the detector itself may undergo c

Sara Heap, Jonathan Arenberg, Tony Hull, Steven Kendrick

The mission concept, Cosmic Origins Through UV Surveys (CETUS) is an all-UV space mission concept that was selected and funded by NASA for study in 2017. The main capabilities of CETUS that even Hubble doesn&#39;t have are: (1) wide-field (17.4&#39;x17.4&#39;) imaging and spectroscopy of astronomical sources with <0.5&#39;&#39; resolution; (2) spectral sensi

Louise O. V. Edwards, Matthew Salinas, Steffanie Stanley, Priscilla E. Holguin West

The formation and evolution of local brightest cluster galaxies (BCGs) is investigated by determining the stellar populations and dynamics from the galaxy core, though the outskirts and into the intracluster light (ICL). Integral spectroscopy of 23 BCGs observed out to 4 r_e is collected and high signal-to-noise regions are identified. Stellar population syn

Can Chen, Luca Zanotti Fragonara, Antonios Tsourdos

In order to achieve better performance for point cloud analysis, many researchers apply deeper neural networks using stacked Multi-Layer-Perceptron (MLP) convolutions over irregular point cloud. However, applying dense MLP convolutions over large amount of points (e.g. autonomous driving application) leads to inefficiency in memory and computation. To achiev

Sourav Chakraborty, Arkadev Chattopadhyay, Nikhil S. Mande, Manaswi Paraashar

Buhrman, Cleve and Wigderson (STOC&#39;98) observed that for every Boolean function $f : \{-1, 1\}^n \to \{-1, 1\}$ and $\bullet : \{-1, 1\}^2 \to \{-1, 1\}$ the two-party bounded-error quantum communication complexity of $(f \circ \bullet)$ is $O(Q(f) \log n)$, where $Q(f)$ is the bounded-error quantum query complexity of $f$. Note that the bounded-error ra

Lorenzo Federici, Alessandro Zavoli, Guido Colasurdo

This paper proposes a formulation of the Active Debris Removal (ADR) Mission Design problem as a modified Time-Dependent Traveling Salesman Problem (TDTSP). The TDTSP is a well-known combinatorial optimization problem, whose solution is the cheapest mono-cyclic tour connecting a number of non-stationary cities in a map. The problem is tackled with an optimiz

T. D. Joseph, M. D. Filipović, E. J. Crawford, I. Bojičić

We present two new radio continuum images from the Australian Square Kilometre Array Pathfinder (ASKAP) survey in the direction of the Small Magellanic Cloud (SMC). These images are part of the Evolutionary Map of the Universe (EMU) Early Science Project (ESP) survey of the Small and Large Magellanic Clouds. The two new source lists produced from these image

Maxime Berger

We propose a new definition for the error threshold of a population evolving through mutation and selection. We compute the correction term due to the finiteness of the population by estimating the lifetime of master sequences. Our technique consists in bounding from above and below the number of master sequences in the Moran model, by birth and death chains

Ivan Aidun, Ralph Morrison

In this paper we study Cartesian products of graphs and their divisorial gonality, which is a tropical version of the gonality of an algebraic curve. We present an upper bound on the gonality of the Cartesian product of any two graphs, and provide instances where this bound holds with equality, including for the $m\times n$ rook&#39;s graph with $\min\{m,n\}

Jan Pöppel, Stefan Kopp

The ability to interpret the mental state of another agent based on its behavior, also called Theory of Mind (ToM), is crucial for humans in any kind of social interaction. Artificial systems, such as intelligent assistants, would also greatly benefit from such mentalizing capabilities. However, humans and systems alike are bound by limitations in their avai

Miek Messerschmidt

Previously only two examples of Banach space quotient maps which do not admit uniformly continuous right inverses were known: one due to Aharoni and Lindenstrauss and one due to Kalton ($\ell^\infty\to\ell^\infty/c_{0}$). We show through an application of Kalton&#39;s Monotone Transfinite Sequence Theorem that a quotient map of a subspace of $\ell^\infty$ of

Chih-Hsuan Wei, Kyubum Lee, Robert Leaman, Zhiyong Lu

Automatically locating named entities in natural language text - named entity recognition - is an important task in the biomedical domain. Many named entity mentions are ambiguous between several bioconcept types, however, causing text spans to be annotated as more than one type when simultaneously recognizing multiple entity types. The straightforward solut

Jessica Rivera-Villicana, Fabio Zambetta, James Harland, Marsha Berry

This work focuses on studying players behaviour in interactive narratives with the aim to simulate their choices. Besides sub-optimal player behaviour due to limited knowledge about the environment, the difference in each player&#39;s style and preferences represents a challenge when trying to make an intelligent system mimic their actions. Based on observat

Hongyu Zang, Zhiwei Yu, Xiaojun Wan

In this paper, we explore a new approach for automated chess commentary generation, which aims to generate chess commentary texts in different categories (e.g., description, comparison, planning, etc.). We introduce a neural chess engine into text generation models to help with encoding boards, predicting moves, and analyzing situations. By jointly training