April 2020 arXiv papers — page 55

Pardeep Kumar, Thakshila M. Herath, Vadym Apalkov, Mark I. Stockman

We theoretically investigate the interaction of an ultrastrong femtosecond-long linearly polarized optical pulse with AB-stacked bilayer graphene. The pulse excite electrons from the valence into the conduction band, resulting in finite conduction band population. Such a redistribution of electrons results in the generation of current which can be manipulate

Zheng Zhang, Lizi Liao, Xiaoyan Zhu, Tat-Seng Chua

Most existing approaches for goal-oriented dialogue policy learning used reinforcement learning, which focuses on the target agent policy and simply treat the opposite agent policy as part of the environment. While in real-world scenarios, the behavior of an opposite agent often exhibits certain patterns or underlies hidden policies, which can be inferred an

Yu-HOng Dai, Liwei Zhang

Minimax optimization problems arises from both modern machine learning including generative adversarial networks, adversarial training and multi-agent reinforcement learning, as well as from tradition research areas such as saddle point problems, numerical partial differential equations and optimality conditions of equality constrained optimization. For the

Lasitha Wijayarathne, Frank L. Hammond

Although autonomous control of robotic manipulators has been studied for several decades, they are not commonly used in safety-critical applications due to lack of safety and performance guarantees - many of them concerning the modulation of interaction forces. This paper presents a mechanical probing strategy for estimating the environmental impedance param

Xuanyu YIN, Yoko SASAKI, Weimin WANG, Kentaro SHIMIZU

Lidar based 3D object detection and classification tasks are essential for automated driving(AD). A Lidar sensor can provide the 3D point coud data reconstruction of the surrounding environment. But the detection in 3D point cloud still needs a strong algorithmic challenge. This paper consists of three parts.(1)Lidar-camera calib. (2)YOLO, based detection an

Amit Jash, Sayantan Ghosh, A. Bharathi, S. S. Banerjee

Sensitive ac susceptibility measurements of a topological insulator, Bi$_2$Se$_3$ single crystal, using mutual two coil inductance technique (Ref. 32) shows coupling and decoupling of high conducting surface states. The coupling of the surface states exists upto thickness of 70 microns, which is much larger than the direct coupling limit of thickness approxi

A. R. Abdulghany

In this study, two novel improvements for the theoretical calculation of the neutron distributions are presented. First, the available experimental proton distributions are used as a constraint rather than inferred from the calculation. Second, the recently proposed distribution formula, d3pF, is used for the neutron density, which is more detailed than the

Sheng Chen, Shuiqing Li

We carry out direct numerical simulation combined with adhesive discrete element calculations to investigate collision-induced breakage of agglomerates in homogeneous isotropic turbulence. Based on extensive simulation runs, an adhesion parameter Adn is constructed to quantify the possibility of occurrence of sticking, rebound, and breakage events. The colli

Simona Santamaria, David Dao, Björn Lütjens, Ce Zhang

International stakeholders increasingly invest in offsetting carbon emissions, for example, via issuing Payments for Ecosystem Services (PES) to forest conservation projects. Issuing trusted payments requires a transparent monitoring, reporting, and verification (MRV) process of the ecosystem services (e.g., carbon stored in forests). The current MRV process

Abd AlRahman AlMomani, Erik Bollt

Our recently developed tool, called Directed Affinity Segmentation was originally designed for data-driven discovery of coherent sets in fluidic systems. Here we interpret that it can also be used to indicate early warning signs of critical transitions in ice shelves as seen from remote sensing data. We apply a directed spectral clustering methodology, inclu

Philip K. Schwartz, Domenico Giulini

This paper deals with the Newton--Wigner position observable for Poincar\'e-invariant classical systems. We prove an existence and uniqueness theorem for elementary systems that parallels the well-known Newton--Wigner theorem in the quantum context. We also discuss and justify the geometric interpretation of the Newton--Wigner position as `centre of spin', a

Baichuan Huang, Hongwei Yi, Can Huang, Yijia He

The present Multi-view stereo (MVS) methods with supervised learning-based networks have an impressive performance comparing with traditional MVS methods. However, the ground-truth depth maps for training are hard to be obtained and are within limited kinds of scenarios. In this paper, we propose a novel unsupervised multi-metric MVS network, named M^3VSNet,

Viet Trinh, Vikrant More, Samira Zare, Sheideh Homayon

Online reviews have become a valuable and significant resource, for not only consumers but companies, in decision making. In the absence of a trusted system, highly popular and trustworthy internet users will be assumed as members of the trusted circle. In this paper, we describe our focus on quarantining deceiving Yelp's users that employ both review spike

Wen Tang, Alireza Chakeri, Hamid Krim

With rapid development of socio-economics, the task of discovering functional zones becomes critical to better understand the interactions between social activities and spatial locations. In this paper, we propose a framework to discover the real functional zones from the biased and extremely sparse Point of Interests (POIs). To cope with the bias and sparsi

Xiangpeng Wan, Hakim Ghazzai, Yehia Massoud

In this paper, we propose two automated text processing frameworks specifically designed to analyze online reviews. The objective of the first framework is to summarize the reviews dataset by extracting essential sentence. This is performed by converting sentences into numerical vectors and clustering them using a community detection algorithm based on their

Jim Samuel, Myles Garvey, Rajiv Kashyap

Information exchange and message diffusion have moved from traditional media to social media platforms. Messages on platforms such as Twitter have become the default mode of company communications replacing lengthier public announcements and updates. Businesses and organizations have increased their use of Twitter to connect with stakeholders. As a result, i

Taylor Blose, Prasanna Umar, Anna Squicciarini, Sarah Rajtmajer

We study observed incidence of self-disclosure in a large dataset of Tweets representing user-led English-language conversation about the Coronavirus pandemic. Using an unsupervised approach to detect voluntary disclosure of personal information, we provide early evidence that situational factors surrounding the Coronavirus pandemic may impact individuals' p

Jinghui Lu, Brian MacNamee

Active learning has been shown to be an effective way to alleviate some of the effort required in utilising large collections of unlabelled data for machine learning tasks without needing to fully label them. The representation mechanism used to represent text documents when performing active learning, however, has a significant influence on how effective th

Benjamin Metha, Michele Trenti

The rate of long-duration gamma ray bursts (GRBs) has been identified as a potential proxy for the star formation rate (SFR) across redshift, but the exact relationship depends on GRB progenitor models (single versus binary). The single-progenitor collapsar model accounts for the preference towards low-metallicity GRB progenitors, but is in apparent tension

Mayank Singh, Arindam Pal, Lipika Dey, Animesh Mukherjee

Research and innovation is important agenda for any company to remain competitive in the market. The relationship between innovation and revenue is a key metric for companies to decide on the amount to be invested for future research. Two important parameters to evaluate innovation are the quantity and quality of scientific papers and patents. Our work studi

Lei Cheng, Liang Liu, Shuguang Cui

This paper studies the massive machine-type communications (mMTC) for the future Internet of Things (IoT) applications, where a large number of IoT devices exist in the network and a random subset of them become active at each time instant. Building upon the fact that the covariance matrix of the received signal can be accurately estimated in the spatial dom

Karim Eldefrawy, Michael Locasto, Norrathep Rattanavipanon, Hassen Saidi

Implementation flaws in cryptographic libraries, design flaws in underlying cryptographic primitives, and weaknesses in protocols using both, can all lead to exploitable vulnerabilities in software. Manually fixing such issues is challenging and resource consuming, especially when maintaining legacy software that contains broken or outdated cryptography, and

Xiangpeng Wan, Hakim Ghazzai, Yehia Massoud

Modern urbanization is demanding smarter technologies to improve a variety of applications in intelligent transportation systems to relieve the increasing amount of vehicular traffic congestion and incidents. Existing incident detection techniques are limited to the use of sensors in the transportation network and hang on human-inputs. Despite of its data ab

Soshun Ozaki, Masao Ogata

We examine the magnetic susceptibility of topological insulators microscopically and find that the orbital-Zeeman (OZ) cross term, the cross term between the orbital effect and the spin Zeeman effect, is directly related to the Berry curvature when the $z$-component of spin is conserved. In particular, the OZ cross term reflects the spin Chern number, which

Marc Besson, Sam Jeralds, Joshua Kiers

Let $\mathscr{K}(G)$ be the rational cone generated by pairs $(\lambda, \mu)$ where $\lambda$ and $\mu$ are dominant integral weights and $\mu$ is a nontrivial weight space in the representation $V_{\lambda}$ of $G$. We produce all extremal rays of $\mathscr{K}(G)$ by considering the vertices of corresponding intersection polytopes $IP_{\lambda}$, the set of

Gianlucca Zuin, Adriano Veloso, João Cândido Portinari, Nivio Ziviani

In this paper, we deal with the problem of automatic tag recommendation for painting artworks. Diachronic descriptions containing deviations on the vocabulary used to describe each painting usually occur when the work is done by many experts over time. The objective of this work is to provide a framework that produces a more accurate and homogeneous set of t

Yunpeng Zhao, Peter Bickel, Charles Weko

Statistical network analysis primarily focuses on inferring the parameters of an observed network. In many applications, especially in the social sciences, the observed data is the groups formed by individual subjects. In these applications, the network is itself a parameter of a statistical model. Zhao and Weko (2019) propose a model-based approach, called

Dmitriy I. Podolskiy, Andrei O. Barvinsky, Robert Lanza

One of the sources of incompatibility between general relativity and quantum mechanics is perturbative non-renormalizability of quantum gravity in $3+1$ spacetime dimensions. Here, we show that in the presence of disorder induced by random networks of observers measuring covariant quantities (such as scalar curvature) $(3+1)$-dimensional quantum gravity exhi

Marcin Bownik, Baode Li, Jinxia Li

We introduce the class of variable anisotropic singular integral operators associated to a continuous multi-level ellipsoid cover $\Theta$ of $\mathbb{R}^n$ introduced by Dahmen, Dekel, and Petrushev \cite{ddp}. This is an extension of the classical isotropic singular integral operators on $\mathbb{R}^n$ of arbitrary smoothness and their anisotropic analogue

T. Ikeda, T. Shimada, H. Ishiura, K. D. Nakamura

A negative ion micro time projection chamber (NI$\mu$TPC) was developed and its performance studied. An NI$\mu$TPC is a novel technology that enables the measurement of absolute $z$ coordinates for self-triggering TPCs. This technology provides full-fiducialization analysis, which is not possible with conventional gaseous TPCs, and is useful for directional

Fatai Sado, Chu Kiong Loo, Wei Shiung Liew, Matthias Kerzel

Recent applications of autonomous agents and robots, such as self-driving cars, scenario-based trainers, exploration robots, and service robots have brought attention to crucial trust-related challenges associated with the current generation of artificial intelligence (AI) systems. AI systems based on the connectionist deep learning neural network approach l

Paata Ivanisvili, Ryan Russell

Talagrand observed that finiteness of $\mathbb{E}\, e^{\frac{1}{2}|\nabla f(X)|^{2}}$ implies finiteness of $\mathbb{E}\, e^{\, f(X)}$ where $X$ is the standard Gaussian vector in $\mathbb{R}^{n}$ and $f$ is a smooth function with zero average. However, in this paper we show that finiteness of $ \mathbb{E}\, e^{\frac{1}{2}|\nabla f|^{2}} (1+|\nabla f|)^{-1}$

Will Y. Zou, Smitha Shyam, Michael Mui, Mingshi Wang

Causal inference methods are widely applied in the fields of medicine, policy, and economics. Central to these applications is the estimation of treatment effects to make decisions. Current methods make binary yes-or-no decisions based on the treatment effect of a single outcome dimension. These methods are unable to capture continuous space treatment polici

Will Y. Zou, Shuyang Du, James Lee, Jan Pedersen

User marketing is a key focus of consumer-based internet companies. Learning algorithms are effective to optimize marketing campaigns which increase user engagement, and facilitates cross-marketing to related products. By attracting users with rewards, marketing methods are effective to boost user activity in the desired products. Rewards incur significant c

Dian-Yong Chen, Jing Liu, Jun He

In the present work, we reanalyzed the cross sections for $e^+ e^- \to K^+K^-$, where a new structure $X(2240)$ was reported by BES III Collaboration. By including the interference between the direct coupling and vector meson intermediate processes, we find the mass and width of $X(2240)$ are $2197.4\pm 4.4$ MeV and $75.6\pm 7.2 $ MeV, respectively, which ar

Rory Smith, Colm Talbot, Francisco Hernandez Vivanco, Eric Thrane

The vast majority of compact binary mergers in the Universe produce gravitational waves that are too weak to yield unambiguous detections; they are unresolved. We present a method to infer the population properties of compact binaries -- such as their merger rates, mass spectrum, and spin distribution -- using both resolved and unresolved gravitational waves

Robin Cockett, Richard Garner

We prove a generalisation of the correspondence, due to Resende and Lawson--Lenz, between \'etale groupoids---which are topological groupoids whose source map is a local homeomorphisms---and complete pseudogroups---which are inverse monoids equipped with a particularly nice representation on a topological space. Our generalisation improves on the existing fu

Maryam Parsa, Catherine D. Schuman, Prasanna Date, Derek C. Rose

Training neural networks for neuromorphic deployment is non-trivial. There have been a variety of approaches proposed to adapt back-propagation or back-propagation-like algorithms appropriate for training. Considering that these networks often have very different performance characteristics than traditional neural networks, it is often unclear how to set eit

A. David-Uraz, M. E. Shultz, V. Petit, D. M. Bowman

In this paper, we present results from the spectropolarimetric follow-up of photometrically selected candidate magnetic B stars from the MOBSTER project. Out of four observed targets, one (HD 38170) is found to host a detectable surface magnetic field, with a maximum longitudinal field measurement of 105$\pm$14 G. This star is chemically peculiar and classif

Kevin Coulembier, Ross Street, Michel van den Bergh

Given a monoidal category $\mathscr{C}$ with an object $J$, we construct a monoidal category $\mathscr{C}[J^{\vee}]$ by freely adjoining a right dual $J^{\vee}$ to $J$. We show that the canonical strong monoidal functor $\Omega : \mathscr{C}\to \mathscr{C}[J^{\vee}]$ provides the unit for a biadjunction with the forgetful 2-functor from the 2-category of mon

Bo-Yong Chen

We show that every bounded pseudoconvex domain with H\"older boundary in $\mathbb C^n$ is hyperconvex.

Amir Javadpour, Samira Rezaei, Kuan-Ching Li, Guojun Wang

Due to the fast-growing volume of text documents and reviews in recent years, current analyzing techniques are not competent enough to meet the users' needs. Using feature selection techniques not only support to understand data better but also lead to higher speed and also accuracy. In this article, the Whale Optimization algorithm is considered and applied

Amir Javadpour, Guojun Wang, Xiaofei Xing

Network virtualization is a way to simultaneously run multiple heterogeneous architectures on a shared substrate. The main issue in the virtualization of networks is the problem of mapping virtual networks to the substrate network. How to manage substrate resources when performing the mapping will have an effective role in improving the use of infrastructure

Federico Vaccaro, Marco Bertini, Tiberio Uricchio, Alberto Del Bimbo

In this paper, we address the problem of image retrieval by learning images representation based on the activations of a Convolutional Neural Network. We present an end-to-end trainable network architecture that exploits a novel multi-scale local pooling based on NetVLAD and a triplet mining procedure based on samples difficulty to obtain an effective image

Wei Zhu, Haofu Liao, Wenbin Li, Weijian Li

Skin disease classification from images is crucial to dermatological diagnosis. However, identifying skin lesions involves a variety of aspects in terms of size, color, shape, and texture. To make matters worse, many categories only contain very few samples, posing great challenges to conventional machine learning algorithms and even human experts. Inspired

Amir Javadpour

Wireless Sensor Network WSN is consisted of nodes with different sizes and a specific goal. Tracking applications are very important in WSNs. This study proposes a method for reducing energy consumption in WSNs, considering target tracking. A prediction method is also presented with the help of MAC Medium Access Control layer in which a few number of nodes a

Takumi Sato, Yasuhiro Asano

We study the effects of random nonmagnetic impurities on superconducting transition temperature $T_c$ in a Cu-doped Bi$_2$Se$_3$, for which four types of pair potentials have been proposed. Although all the candidates belong to $s$-wave symmetry, two orbital degree of freedom in electronic structures enriches the symmetry variety of a Cooper pair such as eve

Akihide Hanaki

We define modular Terwilliger algebras of association schemes, Terwilliger algebras over a positive characteristic field, and consider basic properties. We give a condition for the modular Terwilliger algebra to be non-semisimple. We show that the dimension of a Terwilliger algebra of a Johnson scheme depends on the characteristic of the coefficient field. W

Mirgahney Mohamed, Gabriele Cesa, Taco S. Cohen, Max Welling

Thanks to their improved data efficiency, equivariant neural networks have gained increased interest in the deep learning community. They have been successfully applied in the medical domain where symmetries in the data can be effectively exploited to build more accurate and robust models. To be able to reach a much larger body of patients, mobile, on-device

Sumanta Chakraborty

In a scalar-coupled-gravity model, the quadratically divergent counter term appearing in the mass renormalization of the scalar fields must inherit corrections arising out of gravitational interactions. In this work we have explicitly demonstrated that there are no such corrections of gravitational origin to the quadratic divergences in the mass counter term

Joël Bellaïche

We study the algebraic dynamics of self-correspondences on a curve. A self-correspondence on a (proper and smooth) curve $C$ over an algebraically closed field is the data of another curve $D$ and two non-constant separable morphisms $\pi_1$ and $\pi_2$ from $D$ to $C$. A subset $S$ of $C$ is complete if $\pi_1^{-1}(S)=\pi_2^{-1}(S)$. We show that self-corre

Federico Sebastiani, Trandon A. Bender, Simone Pezzotti, Wan-Lu Li

Water under nanoconfinement at ambient conditions has exhibited low-dimensional ice formation and liquid-solid phase transitions, but with structural and dynamical signatures which map onto known regions of waters phase diagram. Using THz absorption spectroscopy and ab initio molecular dynamics, we have investigated the ambient water confined in a supramolec

Chao Zhang

In this paper, we consider the characterizations of the Lipschitz spaces and homogeneous Lipschitz spaces associated to the biharmonic operator $\Delta^2.$ With this characterizations, we prove the boundedness of the Bessel potentials, fractional integrals, fractional powers, Riesz transforms and multipliers of Laplace transforms type associated to $\Delta^2

Jia-Wei Luo, Bing Zhang

The reported association of high-energy neutrino event IceCube-170922A and blazar TXS 0506+056 has sparkled discussion about blazars as sources of cosmic neutrinos. In this paper, we use publicly released IceCube data and blazar locations from Roma-BzCat to test spacial correlation between neutrino events and blazar locations. We also scrutinize the correlat

Nina Rajcic, Jon McCormack

This paper introduces a new form of real-time affective interface that engages the user in a process of conceptualisation of their emotional state. Inspired by Barrett's Theory of Constructed Emotion, `Mirror Ritual' aims to expand upon the user's accessible emotion concepts, and to ultimately provoke emotional reflection and regulation. The interface uses c

Colin S. Wallace, Edward E. Prather, John A. Milsom, Ken Johns

In this paper we put forth a model for physics course reform that uniquely uses proven, research-based active learning strategies to help students improve their physics knowledge and problem-solving skills. In this study, we compared the exam performance of students in two sections of the same introductory physics course. One section (the traditional section

G. Bruhaug, L. Beveridge

A novel use of high temperature superconducting (HTS) electromagnets for human sized microgravity research and mitigation is outlined. Recent advances in HTS technology have resulted in electromagnets that potentially could levitate large diamagnetic targets, such as human organs, for additive manufacturing or entire humans for microgravity training. These a

Sami Davies, Janardhan Kulkarni, Thomas Rothvoss, Jakub Tarnawski

We consider the classic problem of scheduling jobs with precedence constraints on identical machines to minimize makespan, in the presence of communication delays. In this setting, denoted by $\mathsf{P} \mid \mathsf{prec}, c \mid C_{\mathsf{max}}$, if two dependent jobs are scheduled on different machines, then at least $c$ units of time must pass between t

D. Dakota Blair, Joel David Hamkins, Kevin O'Bryant

For a real number $x$ and set of natural numbers $A$, define $x \ast A := \{ x a \bmod 1: a\in A\}\subseteq [0,1).$ We consider relationships between $x$, $A$, and the order-type of $x\ast A$. For example, for every irrational $x$ and order-type $α$, there is an $A$ with $x\ast A \simeq α$, but if $α$ is a well order, then $A$ must be a thin set. If, however

Yingruo Fan, Jacqueline C. K. Lam, Victor O. K. Li

The intensity estimation of facial action units (AUs) is challenging due to subtle changes in the person's facial appearance. Previous approaches mainly rely on probabilistic models or predefined rules for modeling co-occurrence relationships among AUs, leading to limited generalization. In contrast, we present a new learning framework that automatically lea

Xingyuan Xu, Mengxi Tan, Jiayang Wu, Andreas Boes

We report a broadband radio frequency (RF) channelizer with up to 92 channels using a coherent microcomb source. A soliton crystal microcomb, generated by a 49 GHz micro-ring resonator (MRR), is used as a multi-wavelength source. Due to its ultra-low comb spacing, up to 92 wavelengths are available in the C band, yielding a broad operation bandwidth. Another

Najmeddine Dhieb, Hakim Ghazzai, Hichem Besbes, Yehia Massoud

Internet-of-things (IoT) is perpetually revolutionizing our daily life and rapidly transforming physical objects into an ubiquitous connected ecosystem. Due to their massive deployment and moderate security levels, those devices face a lot of security, management, and control challenges. Their classical centralized architecture is still cloaking vulnerabilit

H. Buglia, R. R. Lopes

In this letter, we propose a Voronoi shaping method with reduced encoding complexity. The method works for integer shaping and coding lattices satisfying the chain $\Lambda_s \subseteq \textbf{K}\mathbb{Z}^n \subseteq \Lambda_c$, with $\textbf{K}$ an integer diagonal matrix. This assumption is easily satisfied for lattices obtained from error-correcting code

Weizhe Hua, Muhammad Umar, Zhiru Zhang, G. Edward Suh

This paper introduces MGX, a near-zero overhead memory protection scheme for hardware accelerators. MGX minimizes the performance overhead of off-chip memory encryption and integrity verification by exploiting the application-specific properties of the accelerator execution. In particular, accelerators tend to explicitly manage data movement between on-chip

Abolfazl Mohajer

In this paper we consider the Prym variety $P(\widetilde{C}/C)$ associated to a Galois coverings of curves $f:\widetilde{C}\to C$ branched at $r$ points. We discuss some properties and equivalent definitions and then consider the Prym map $\mathcal{P}=\mathcal{P}(G,g,r):R(G,g,r)\to A_{p,\delta}$ with $\delta$ the type of the polarization. For Galois covering

Finbarr Timbers, Nolan Bard, Edward Lockhart, Marc Lanctot

Researchers have demonstrated that neural networks are vulnerable to adversarial examples and subtle environment changes, both of which one can view as a form of distribution shift. To humans, the resulting errors can look like blunders, eroding trust in these agents. In prior games research, agent evaluation often focused on the in-practice game outcomes. W

Yiming Lin, Daokun Jiang, Roberto Yus, Georgios Bouloukakis

This paper explores the data cleaning challenges that arise in using WiFi connectivity data to locate users to semantic indoor locations such as buildings, regions, rooms. WiFi connectivity data consists of sporadic connections between devices and nearby WiFi access points (APs), each of which may cover a relatively large area within a building. Our system,

Ali Hassan, Deepjyoti Deka, Michael Chertkov, Yury Dvorkin

Demand response (DR) programs aim to engage distributed small-scale flexible loads, such as thermostatically controllable loads (TCLs), to provide various grid support services. Linearly Solvable Markov Decision Process (LS-MDP), a variant of the traditional MDP, is used to model aggregated TCLs. Then, a model-free reinforcement learning technique called Z-l

Scott Aaronson, Jiahui Liu, Qipeng Liu, Mark Zhandry

Quantum copy protection uses the unclonability of quantum states to construct quantum software that provably cannot be pirated. Copy protection would be immensely useful, but unfortunately little is known about how to achieve it in general. In this work, we make progress on this goal, by giving the following results: - We show how to copy protect any program

John Paul Francis, Hongzhi Wang, Kate White, Tanveer Syeda-Mahmood

The Pancreatic beta cell is an important target in diabetes research. For scalable modeling of beta cell ultrastructure, we investigate automatic segmentation of whole cell imaging data acquired through soft X-ray tomography. During the course of the study, both complete and partial ultrastructure annotations were produced manually for different subsets of t

Lucas Massa, Adriano Barbosa, Krerley Oliveira, Thales Vieira

Measuring and analyzing the flow of customers in retail stores is essential for a retailer to better comprehend customers' behavior and support decision-making. Nevertheless, not much attention has been given to the development of novel technologies for automatic people counting. We introduce LRCN-RetailNet: a recurrent neural network architecture capable of

Yifei Zhao

The goal of this paper is to assign an intrinsic meaning to the space of quantum parameters $\operatorname{Par}_G$ appearing in the geometric Langlands program of Beilinson-Drinfeld. We introduce tame twistings, a variant of twisted differential operators (TDOs) for which regularity of twisted $\mathscr D$-modules is well-defined. Our main result is that for

Yijun Xu, Weirong Huang, Hui Deng, Ying Mei

Significant progress in the classification of Fermi unassociated sources , has led to an increasing number of blazars are being found. The optical spectrum is effectively used to classify the blazars into two groups such as BL Lacs and flat spectrum radio quasars (FSRQs). However, the accurate classification of the blazars without optical spectrum informatio

Pekka Koskela, Aleksis Koski, Jani Onninen

Given the planar unit disk as the source and a Jordan domain as the target, we study the problem of extending a given boundary homeomorphism as a Sobolev homeomorphism. For general targets, this Sobolev variant of the classical Jordan-Schoenflies theorem may admit no solution - it is possible to have a boundary homeomorphism which admits a continuous $W^{1,2

Andrea Pozzi, Xiangzhong Xie, Davide M Raimondo, René Schenkendorf

Battery management systems may rely on mathematical models to provide higher performance than standard charging protocols. Electrochemical models allow us to capture the phenomena occurring inside a lithium-ion cell and therefore, could be the best model choice. However, to be of practical value, they require reliable model parameters. Uncertainty quantifica

Xiao-Bin Liang, Bo Li, Shao-Ming Fei, Heng Fan

We study the quantum information masking based on isometric linear operators that distribute the information encoded in pure states to the correlations in bipartite states. It is shown that a isometric linear operator can not mask any nonzero measure set of pure states. We present a geometric characterization of the maskable sets, and show that any maskable

Ming Y. Lu, Drew F. K. Williamson, Tiffany Y. Chen, Richard J. Chen

The rapidly emerging field of computational pathology has the potential to enable objective diagnosis, therapeutic response prediction and identification of new morphological features of clinical relevance. However, deep learning-based computational pathology approaches either require manual annotation of gigapixel whole slide images (WSIs) in fully-supervis

Mike R. Jeffrey

We present here a product between vectors and scalars that {\it mixes} them within their own space, using imaginaries to describe geometric products between vectors as complex vectors, rather than introducing higher order/dimensional vector objects. This is done by means of a {\it mixture tensor} that captures the rich geometries of geometric algebras, and s

Zexi Chen, Benjamin Dutton, Bharathkumar Ramachandra, Tianfu Wu

The Mean Teacher (MT) model of Tarvainen and Valpola has shown favorable performance on several semi-supervised benchmark datasets. MT maintains a teacher model's weights as the exponential moving average of a student model's weights and minimizes the divergence between their probability predictions under diverse perturbations of the inputs. However, MT is k

Han Zhang, Qing Huang, Lin Hao, Junyi Yang

We performed a systematic study of the temperature- and field-dependence of magnetization and resistivity of Gd2PdSi3, which is a centrosymmetric skyrmion crystal. While the magnetization behavior is consistent with the reported phase diagram based on susceptibility, we show that a phase diagram can also be constructed based on the anomalous magnetoresistanc

Hosna Jafarmanesh, Maryam Khosravi

We present several sharp upper bounds and some extension for product operators. Among other inequalities, it is shown that if , , are non-negative continuous functions on such that , , then for all non-negative operator monotone decreasing function on , we obtain that As an application of the above inequality, it is shown that where, and .

Adam Dalton, Ehsan Aghaei, Ehab Al-Shaer, Archna Bhatia

We describe Panacea, a system that supports natural language processing (NLP) components for active defenses against social engineering attacks. We deploy a pipeline of human language technology, including Ask and Framing Detection, Named Entity Recognition, Dialogue Engineering, and Stylometry. Panacea processes modern message formats through a plug-in arch

Ishtiak Ahmed, Shannon Warchol, Chris Cunningham, Nagui Rouphail

This study evaluated the performance of pedestrian-bicycle crossing alternatives at Continuous Flow Intersections (CFI). Further, a comparison was also performed of CFI crossing types against a standard intersection designed to provide an equivalent volume-to-capacity ratio. Three CFI crossing alternatives were tested, namely Traditional, Offset, and Midbloc

John H. Schwarz

The duality between the type IIB superstring theory in an $AdS_5 \times S^5$ background with $N$ units of five-form flux and ${\cal N} =4$ super Yang--Mills theory with a $U(N)$ gauge group has been studied extensively. My version of the construction of the superstring world-sheet action is reviewed here. This paper is dedicated to Michael Duff on the occasi

Shixiang Zhu, Alexander W. Bukharin, Le Lu, He Wang

We redesign the police patrol beat in South Fulton, Georgia, in collaboration with the South Fulton Police Department (SFPD), using a predictive data-driven optimization approach. Due to rapid urban development and population growth, the existing police beat design done in the 1970s was far from efficient, which leads to low policing efficiency and long 911

Ardita Kilaj, Hong Gao, Diana Tahchieva, Raghunathan Ramakrishnan

The Diels-Alder cycloaddition, in which a diene reacts with a dienophile to form a cyclic compound, counts among the most important tools in organic synthesis. Achieving a precise understanding of its mechanistic details on the quantum level requires new experimental and theoretical methods. Here, we present an experimental approach that separates different

Amir Caspi, Daniel B. Seaton, Constantine C. C. Tsang, Craig E. DeForest

NASA's WB-57 High Altitude Research Program provides a deployable, mobile, stratospheric platform for scientific research. Airborne platforms are of particular value for making coronal observations during total solar eclipses because of their ability both to follow the Moon's shadow and to get above most of the atmospheric airmass that can interfere with ast

A. N. Petrov, J. Brian Pitts

GR and other metric theories of gravity are formulated with an arbitrary auxiliary curved background in a Lagrangian formalism. A new sketch of how to include spinor fields is included. Conserved quantities are obtained using Noether's theorem and expressed as divergences of antisymmetric densities, connecting local perturbations with quasi-local conserved q

Claudia Garetto

In this paper we study the well-posedness of the Cauchy problem for a wave equation with multiplicities and space-dependent irregular coefficients. As in \cite{GR:14} in order to give a meaningful notion of solution, we employ the notion of very weak solution, which construction is based on a parameter dependent regularisation of the coefficients via mollifi

Hippolyte Bourel, Odalric-Ambrym Maillard, Mohammad Sadegh Talebi

The upper confidence reinforcement learning (UCRL2) algorithm introduced in (Jaksch et al., 2010) is a popular method to perform regret minimization in unknown discrete Markov Decision Processes under the average-reward criterion. Despite its nice and generic theoretical regret guarantees, this algorithm and its variants have remained until now mostly theore

Ananda Streit, Gustavo H. A. Santos, Rosa Leão, Edmundo de Souza e Silva

The problem of detecting anomalies in time series from network measurements has been widely studied and is a topic of fundamental importance. Many anomaly detection methods are based on packet inspection collected at the network core routers, with consequent disadvantages in terms of computational cost and privacy. We propose an alternative method in which p

Amit Sharma

The main objective of this paper is to construct a homotopy colimit functor on a category of functors taking values in the model category of quasi-categories.

Giuseppe Zurlo, James Blackwell, Niall Colgan, Michel Destrade

An elastic cylinder subjected to torsion will always elongate.

Zhuo Ye, Feng Zhang, Yong-Xin Yao, Cai-Zhuang Wang

We introduce Gutzwiller conjugate gradient minimization (GCGM) theory, an ab initio quantum many-body theory for computing the ground-state properties of infinite systems. GCGM uses the Gutzwiller wave function but does not use the commonly adopted Gutzwiller approximation (GA), which is a major source of inaccuracy. Instead, the theory uses an approximation

Igor Khavkine

We consider the vector and the Lichnerowicz wave equations on the Schwarzschild spacetime, which correspond to the Maxwell and linearized Einstein equations in harmonic gauges (or, respectively, in Lorenz and de Donder gauges). After a complete separation of variables, the radial mode equations form complicated systems of coupled linear ODEs. We outline a pr

Patricio Gaete, Piero Nicolini, Euro Spallucci

Charged black holes in a ($2+1$)-dimensional anti-de Sitter space-time suffer from some limitations such as the ambiguity in the definition of the mass and the bad short distance behavior. In this paper we present a way to resolve such issues. By extending the parameter space of the BTZ geometry, we properly identify the integration constants in order to rem

Thomas DeGrand

I present a calculation of the topological susceptibility $\chi_T$ in $SU(N_c)$ gauge theory with $N_c=3-5$ colors and $N_f=2$ degenerate flavors of fermions. The results lie on a common curve when expressed in terms of the combination $N_c m_{PS}^2 t_0$ where $m_{PS}$ is the pseudoscalar meson mass and $t_0$ is the flow parameter. $\chi_T$ approaches its qu

C. L. Gnilka, D. M. Crenshaw, T. C. Fischer, M. Revalski

We explore the kinematics of the stars, ionized gas, and warm molecular gas in the Seyfert 2 galaxy Mrk~3 (UGC~3426) on nuclear and galactic scales with {\it Gemini} Near-Infrared Field Spectrograph (NIFS) observations, previous {\it Hubble Space Telescope} data, and new long-slit spectra from the {\it Apache Point Observatory} ({\it APO}) 3.5 m telescope. T

Samuel C. Pinto, Sean B. Andersson, Julien M. Hendrickx, Christos G. Cassandras

We address the problem of persistent monitoring, where a finite set of mobile agents has to persistently visit a finite set of targets. Each of these targets has an internal state that evolves with linear stochastic dynamics. The agents can observe these states, and the observation quality is a function of the distance between the agent and a given target. T

Bingling Wang, Qing Zhou

Discovery of causal relationships from observational data is an important problem in many areas. Several recent results have established the identifiability of causal DAGs with non-Gaussian and/or nonlinear structural equation models (SEMs). In this paper, we focus on nonlinear SEMs defined by non-invertible functions, which exist in many data domains, and p