December 2020 arXiv papers — page 99

Frederik Mallmann-Trenn, Matthew Cavorsi, Stephanie Gil

We characterize the advantage of using a robot's neighborhood to find and eliminate adversarial robots in the presence of a Sybil attack. We show that by leveraging the opinions of its neighbors on the trustworthiness of transmitted data, robots can detect adversaries with high probability. We characterize a number of communication rounds required to ach

Hongshun Tang, Lijun Wu, Weiqing Liu, Jiang Bian

Stock trend forecasting has become a popular research direction that attracts widespread attention in the financial field. Though deep learning methods have achieved promising results, there are still many limitations, for example, how to extract clean features from the raw stock data. In this paper, we introduce an \emph{Augmented Disentanglement Distillati

Markus Chimani, Martina Juhnke-Kubitzke, Alexander Nover

Given a graph $G=(V,E)$, the maximum bond problem searches for a maximum cut $δ(S) \subseteq E$ with $S \subseteq V$ such that $G[S]$ and $G[V\setminus S]$ are connected. This problem is closely related to the well-known maximum cut problem and known under a variety of names such as largest bond, maximum minimal cut and maximum connected (sides) cut. The bon

Ralph Neuhaeuser, Dagmar L. Neuhaeuser, Jesse Chapman

Galactic novae and supernovae can be studied by utilizing historical observations, yielding explosion time, location on sky~etc. Recent publications by Hoffmann & Vogt present CVs, supernova remnants, planetary nebulae etc. as potential counterparts based on their list of historically reported transients from the Classical Chinese text corpus. Since their ca

Mohammad Dashti, Alexandra Fedorova

Systems integrating heterogeneous processors with unified memory provide seamless integration among these processors with minimal development complexity. These systems integrate accelerators such as GPUs on the same die with CPU cores to accommodate running parallel applications with varying levels of parallelism. Such integration is becoming very common on

Derrick Timmerman, Swaroop Bennabhaktula, Enrique Alegre, George Azzopardi

The identification of source cameras from videos, though it is a highly relevant forensic analysis topic, has been studied much less than its counterpart that uses images. In this work we propose a method to identify the source camera of a video based on camera specific noise patterns that we extract from video frames. For the extraction of noise pattern fea

Kun-Hsi Tsai, Wei-Chien Wang, Chui-Hsuan Cheng, Chan-Yen Tsai

Auscultation is the most efficient way to diagnose cardiovascular and respiratory diseases. To reach accurate diagnoses, a device must be able to recognize heart and lung sounds from various clinical situations. However, the recorded chest sounds are mixed by heart and lung sounds. Thus, effectively separating these two sounds is critical in the pre-processi

Rui Kato, Ahmet Cetinkaya, Hideaki Ishii

Motivated by recent security issues in cyber-physical systems, this technical note studies the stabilization problem of networked control systems under Denial-of-Service (DoS) attacks. In particular, we consider to stabilize a nonlinear system with limited data rate via linearization. We employ a deterministic DoS attack model constrained in terms of attacks

Zhe Lin, Sharad Sinha, Wei Zhang

Decision trees are machine learning models commonly used in various application scenarios. In the era of big data, traditional decision tree induction algorithms are not suitable for learning large-scale datasets due to their stringent data storage requirement. Online decision tree learning algorithms have been devised to tackle this problem by concurrently

Valentina Viotto, Elisa Portaluri, Carmelo Arcidiacono, Maria Bergomi

The ingot wavefront sensor (I-WFS) has been proposed, for ELT-like apertures, as a possible pupil plane WFS, to cope with the geometrical characteristics of a laser guide star (LGS). Within the study and development of such a WFS, on-going in the framework of the MAORY project, the final purpose of the I-WFS simulation is to estimate its performance in terms

Valentin Mendelev, Tina Raissi, Guglielmo Camporese, Manuel Giollo

Automatic Speech Recognition (ASR) based on Recurrent Neural Network Transducers (RNN-T) is gaining interest in the speech community. We investigate data selection and preparation choices aiming for improved robustness of RNN-T ASR to speech disfluencies with a focus on partial words. For evaluation we use clean data, data with disfluencies and a separate da

Andrew King, Rebecca Nealon

The sample of dwarf galaxies with measured central black hole masses $M$ and velocity dispersions $σ$ has recently doubled, and gives a close fit to the extrapolation of the $M \propto σ$ relation for more massive galaxies. We argue that this is difficult to reconcile with suggestions that the scaling relations between galaxies and their central black holes

Chaoen Zhang

The purpose of this paper is to extend the hypocoercivity results for the kinetic Fokker-Planck equation in $H^1$ space in Villani's memoir \cite{Villani} to higher order Sobolev spaces. As in the $L^2$ and $H^1$ setting, there is lack of coercivity in $H^k$ for the associated operator. To remedy this issue, we shall modify the usual $H^k$ norm with cert

Gustavo E. Medina, Bertrand Lemasle, Eva K. Grebel, Steffi X. Yen

Classical Cepheids in open clusters are key ingredients for stellar population studies and the characterization of variable stars, as they are tracers of young and massive populations and of recent star formation episodes. Cluster Cepheids are of particular importance since they can be age dated by using the cluster's stellar population to obtain the Cep

Spyridon Dendrinos, Kevin Hughes, Marco Vitturi

We apply Christ's method of refinements to the $\ell^p$-improving problem for discrete averages $\mathcal{A}_N$ along polynomial curves in $\mathbb{Z}^d$. Combined with certain elementary estimates for the number of solutions to certain special systems of diophantine equations, we obtain some restricted weak-type $p \to p'$ estimates for the averages

Christian Requena-Mesa, Vitus Benson, Joachim Denzler, Jakob Runge

Climate change is global, yet its concrete impacts can strongly vary between different locations in the same region. Seasonal weather forecasts currently operate at the mesoscale (> 1 km). For more targeted mitigation and adaptation, modelling impacts to < 100 m is needed. Yet, the relationship between driving variables and Earth&#39;s surface at such local

F. Chezani Sharahi, M. Monemzadeh

In this study, pentaquark Pc(4380) composed of a baryon sigma_c and a D_* meson is considered. Pentaquark is as a bound state of two-body systems composed of a baryon and a meson. The calculated potential will be expanded and replaced in the Schrodinger equation until tenth sentences of expansion. Solving the Schrodinger equation with the expanded potential

Vitalii Ozvenchuk, Antoni Szczurek, Andrzej Rybicki

We present our calculation of electromagnetic effects, induced by the spectator charge on Feynman-$x_F$ distributions of charged pions in peripheral $Pb+Pb$ collisions at CERN SPS energies, including realistic initial space-time-momentum conditions for pion emission. The calculation is performed in the framework of a specific implementation of the fire-strea

Gangtao Xin, Pingyi Fan

Soft compression is a lossless image compression method, which is committed to eliminating coding redundancy and spatial redundancy at the same time by adopting locations and shapes of codebook to encode an image from the perspective of information theory and statistical distribution. In this paper, we propose a new concept, compressible indicator function w

Benoit Van der Schueren, Hamza El Marouazi, Anurag Mohanty, Patrick Lévêque

Quasi all water soluble composites use graphene oxide (GO) or reduced graphene oxide (rGO) as graphene based additives despite the long and harsh conditions required for their preparation. Herein, polyvinyl alcohol (PVA) films containing few layer graphene (FLG) are prepared by the co-mixing of aqueous colloids and casting, where the FLG colloid is first obt

Francisco Borges, Georgios Balikas, Marc Brette, Guillaume Kempf

Natural Language Search (NLS) extends the capabilities of search engines that perform keyword search allowing users to issue queries in a more &#34;natural&#34; language. The engine tries to understand the meaning of the queries and to map the query words to the symbols it supports like Persons, Organizations, Time Expressions etc.. It, then, retrieves the i

Ugo Comignani, Laure Berti-Équille, Noël Novelli

In this paper, we study the problem of discovering join FDs, i.e., functional dependencies (FDs) that hold on multiple joined tables. We leverage logical inference, selective mining, and sampling and show that we can discover most of the exact join FDs from the single tables participating to the join and avoid the full computation of the join result. We prop

Abhinaba Roy, Deepanway Ghosal, Erik Cambria, Navonil Majumder

Zero shot learning -- the problem of training and testing on a completely disjoint set of classes -- relies greatly on its ability to transfer knowledge from train classes to test classes. Traditionally semantic embeddings consisting of human defined attributes (HA) or distributed word embeddings (DWE) are used to facilitate this transfer by improving the as

Agata Zubkiewicz, Anna Szymczyk, Piotr Franciszczak, Agnieszka Kochmanska

The influence of carbon multi-walled nanotubes (MWCNTs) and halloysite nanotubes (HNTs) on the physical, thermal, mechanical, and electrical properties of EVA (ethylene vinyl acetate) copolymer was investigated. EVA-based nanocomposites containing MWCNTs or HNTs, as well as hybrid nanocomposites containing both nanofillers were prepared by melt blending. Sca

Benjamin Jones

In this paper we construct parameterizations of elliptic curves over the rationals which have many consecutive integral multiples. Using these parameterizations, we perform searches in GMP and Magma to find curves with points of small height, curves with many integral multiples of a point, curves with high multiples of a point integral, and over two hundred

Jens Braun, Marc Leonhardt, Jan M. Pawlowski, Daniel Rosenblüh

The nature and location of the QCD phase transition close to the chiral limit restricts the phase structure of QCD with physical pion masses at non-vanishing density. At small pion masses, explicit $U(1)_{\rm A}$-breaking, as induced by a non-trivial topological density, is of eminent importance. It triggers the &#39;t Hooft interactions and also manifests i

Daniel Myers, Andrew Espenlaub, Kristina Gelzinyte, Erin Young

We report on the direct measurement of hot electrons generated in the active region of blue light-emitting diodes grown by ammonia molecular beam epitaxy by electron emission spectroscopy. The external quantum efficiency of these devices is <1% and does not droop; thus, the efficiency losses from the intrinsic, interband, electron-electron-hole, or electron-

Sébastien Andrieux, Pierre Müller, Manish Kaushal, Nadia Sofía

Investigations of free-standing liquid films enjoy an increasing popularity due to their relevance for many fundamental and applied scientific problems. They constitute soap bubbles and foams, serve as membranes for gas transport or as model membranes in biophysics. More generally, they provide a convenient tool for the investigation of numerous fundamental

Julen Urain, Davide Tateo, Tianyu Ren, Jan Peters

We present a new family of deep neural network-based dynamic systems. The presented dynamics are globally stable and can be conditioned with an arbitrary context state. We show how these dynamics can be used as structured robot policies. Global stability is one of the most important and straightforward inductive biases as it allows us to impose reasonable be

Steff Horemans, Matthaios Pitoulias, Alexandria Holland, Panos Soultanas

Cells have evolved a metabolic control of DNA replication to respond to a wide range of nutritional conditions. Accumulating data suggest that this poorly understood control depends, at least in part, on Central Carbon Metabolism (CCM). In Bacillus subtilis , the glycolytic pyruvate kinase (PykA) is intricately linked to replication. This 585 amino-acid-long

Eline M. Hutter, Reiny Sangster, Christa Testerink, Bruno Ehrler

Highly-efficient solar cells containing lead halide perovskites are expected to revolutionize sustainable energy production in the coming years. Combining these next-generation solar panels with agriculture, can optimize land-use, but brings new risks in case of leakage into the soil. Perovskites are generally assumed to be toxic because of the lead (Pb), bu

B. Asbani, J. -L. Dellis, A. Lahmar, M. Amjoud

Over the past decades, there has been significant interest in new cooling technology based on the electrocaloric effect. The large electrocaloric effect observed in polymeric and inorganic ferroelectric materials made possible development of dielectric cooling devices of a new generation. We report a significant impact of annealing on the electrocaloric effe

Z. H. A Almtiri, S. J. Miah

The primary task of the study is to inspect the affiliation between the implementation of technology and e-commerce success. It is imperative to study such an important relationship that directly impacts the rapid growth of Internet technology, new dimensions of e-services, and innovative measures that are necessary factors for electronic commerce operations

Kathrin Glau, Linus Wunderlich

We propose the deep parametric PDE method to solve high-dimensional parametric partial differential equations. A single neural network approximates the solution of a whole family of PDEs after being trained without the need of sample solutions. As a practical application, we compute option prices in the multivariate Black-Scholes model. After a single traini

Armin Okic, Lanfranco Zanzi, Vincenzo Sciancalepore, Alessandro Redondi

Vehicle-to-everything (V2X) is expected to become one of the main drivers of 5G business in the near future. Dedicated \emph{network slices} are envisioned to satisfy the stringent requirements of advanced V2X services, such as autonomous driving, aimed at drastically reducing road casualties. However, as V2X services become more mission-critical, new soluti

Robert Laterveer

Motivated by the generalized Bloch conjecture, we formulate a conjecture about the Chow groups of Plücker hypersurfaces in Grassmannians. We prove weak versions of this conjecture.

Myoung-Ki Kim, Jeong-Hyun Cho, Ji-Hoon Jeong

Brain-computer interface allows people who have lost their motor skills to control robot limbs based on electroencephalography. Most BCIs are guided only by visual feedback and do not have somatosensory feedback, which is an important component of normal motor behavior. The sense of touch is a very crucial sensory modality, especially in object recognition a

Hengkuan Lu, Jian Wang

Orthogonal matching pursuit (OMP) is a greedy algorithm popularly being used for the recovery of sparse signals. In this paper, we study the performance of OMP for support recovery of sparse signal under noise. Our analysis shows that under mild constraint on the minimum-to-average ratio of nonzero entries in the sparse signal and the signal-to-noise ratio,

Davide Bilò, Tobias Friedrich, Pascal Lenzner, Stefanie Lowski

Understanding real-world networks has been a core research endeavor throughout the last two decades. Network Creation Games are a promising approach for this from a game-theoretic perspective. In these games, selfish agents corresponding to nodes in a network strategically decide which links to form to optimize their centrality. Many versions have been intro

Lavinia De Divitiis, Federico Becattini, Claudio Baecchi, Alberto Del Bimbo

Fashion plays a pivotal role in society. Combining garments appropriately is essential for people to communicate their personality and style. Also different events require outfits to be thoroughly chosen to comply with underlying social clothing rules. Therefore, combining garments appropriately might not be trivial. The fashion industry has turned this into

Yinrui Sun, Hangjin Jiang

In the era of big data, variable selection is a key technology for handling high-dimensional problems with a small sample size but a large number of covariables. Different variable selection methods were proposed for different models, such as linear model, logistic model and generalized linear model. However, fewer works focused on variable selection for sin

Mohammadreza Doostmohammadian, Hamid R. Rabiee

In this paper, we study large-scale networks in terms of observability and controllability. In particular, we compare the number of unmatched nodes in two main types of Scale-Free (SF) networks: the Barab{á}si-Albert (BA) model and the Holme-Kim (HK) model. Comparing the two models based on theory and simulation, we discuss the possible relation between clus

V. V. Andreev

To describe a relativistic hydrogen atom we used the Poincare-covariant model of a two particle system with gauge invariant potential. The kernel of the radial integral equation is obtained which describes a system of two fermions with electromagnetic interaction.

Zhao Liua, Hongyang Ma, Charles C. Sorrell, Pramod Koshy

It has been demonstrated in previous experimental and computational work that doping CeO2 with transition metals is an effective way of tuning its properties. However, each previous study on CeO2 doping has been limited to a single or a few dopants. In this paper, we systematically study the formation energies, structural stability and electronic properties

Lang Nie, Chunyu Lin, Kang Liao, Yao Zhao

Image stitching is a classical and crucial technique in computer vision, which aims to generate the image with a wide field of view. The traditional methods heavily depend on the feature detection and require that scene features be dense and evenly distributed in the image, leading to varying ghosting effects and poor robustness. Learning methods usually suf

Mudit Kapoor, Shamika Ravi

We analyse the Bihar assembly elections of 2020, and find that poverty was the key driving factor, over and above female voters as determinants. The results show that the poor were more likely to support the NDA. The relevance of this result for an election held in the midst of a pandemic, is very crucial, given that the poor were the hardest hit. Secondly,

Tomoharu Iwata, Yoshinobu Kawahara

Koopman spectral analysis has attracted attention for understanding nonlinear dynamical systems by which we can analyze nonlinear dynamics with a linear regime by lifting observations using a nonlinear function. For analysis, we need to find an appropriate lift function. Although several methods have been proposed for estimating a lift function based on neur

Simeon Ball, Guillermo Gamboa, Michel Lavrauw

Let $C$ be a $(n,q^{2k},n-k+1)_{q^2}$ additive MDS code which is linear over ${\mathbb F}_q$. We prove that if $n \geqslant q+k$ and $k+1$ of the projections of $C$ are linear over ${\mathbb F}_{q^2}$ then $C$ is linear over ${\mathbb F}_{q^2}$. We use this geometrical theorem, other geometric arguments and some computations to classify all additive MDS code

Nasir Saeed, Heba Almorad, Hayssam Dahrouj, Tareq Y. Al-Naffouri

This paper overviews point-to-point (P2P) links for integrated satellite-aerial networks, which are envisioned to be among the key enablers of the sixth-generation (6G) of wireless networks vision. The paper first outlines the unique characteristics of such integrated large-scale complex networks, often denoted by spatial networks, and focuses on two particu

Zhongguo Li, Magnus Oskarsson, Anders Heyden

The task of reconstructing detailed 3D human body models from images is interesting but challenging in computer vision due to the high freedom of human bodies. In order to tackle the problem, we propose a coarse-to-fine method to reconstruct a detailed 3D human body from multi-view images combining voxel super-resolution based on learning the implicit repres

Çağın Ararat

We study a static portfolio optimization problem with two risk measures: a principle risk measure in the objective function and a secondary risk measure whose value is controlled in the constraints. This problem is of interest when it is necessary to consider the risk preferences of two parties, such as a portfolio manager and a regulator, at the same time.

Sherif Sakr, Angela Bonifati, Hannes Voigt, Alexandru Iosup

Graphs are by nature unifying abstractions that can leverage interconnectedness to represent, explore, predict, and explain real- and digital-world phenomena. Although real users and consumers of graph instances and graph workloads understand these abstractions, future problems will require new abstractions and systems. What needs to happen in the next decad

Longyan Gong

We propose a family of one-dimensional mosaic models inlaid with a slowly varying potential $V_n=λ\cos(παn^ν)$, where $n$ is the lattice site index and $0<ν<1$. Combinating the asymptotic heuristic argument with the theory of trace map of transfer matrix, mobility edges (MEs) and pseudo-mobility edges (PMEs) in their energy spectra are solved semi-analytical

Ara Ioannisian, Carlo Giunti, Gioacchino Ranucci

We present the results of a new analysis of the data of the MiniBooNE experiment taking into account the additional background of photons. MiniBooNE normalises the rate of photon production to the measured $π^0$ production rate. We study neutral current (NC) neutrino-induced $π^0$/photon production ($ν_μ+ A \to ν_μ+1π^0 / γ+ X$) on carbon nucleus (A=12). Our

Sascha Kurz

We classify 8-divisible binary linear codes with minimum distance 24 and small length. As an application we consider the codes associated to nodal sextics with 65 ordinary double points.

Chao-Ming Zhang, De-Cheng Zou, Ming Zhang

By treating the cosmological constant as a thermodynamic pressure, we investigate the thermodynamic behaviors of Born-Infeld AdS black hole in 4D Einstein-Gauss-Bonnet (EGB) gravity. The result shows that the Van der Waals like small/large black hole (SBH/LBH) phase transition always appears for any positive parameters $α$ and $β$. Moreover, we observe a new

Nikhil Prakash, Kory W. Mathewson

As artificial intelligence (AI) systems are getting ubiquitous within our society, issues related to its fairness, accountability, and transparency are increasing rapidly. As a result, researchers are integrating humans with AI systems to build robust and reliable hybrid intelligence systems. However, a proper conceptualization of these systems does not unde

Aaram J. Kim, Philipp Werner, Evgeny Kozik

We show that the numerically exact bold-line diagrammatic theory for the $2d$ Hubbard model exhibits a non-Fermi-liquid (NFL) strange metal state, which is connected to the SYK NFL in the strong-interaction limit. The solution for the doped system features the expected phenomenology with the NFL near half-filling at strong couplings and in a wide temperature

Hua Chen, Bingheng Wang, Zejun Hong, Cong Shen

This paper studies jumping for wheeled-bipedal robots, a motion that takes full advantage of the benefits from the hybrid wheeled and legged design features. A comprehensive hierarchical scheme for motion planning and control of jumping with wheeled-bipedal robots is developed. Underactuation of the wheeled-bipedal dynamics is the main difficulty to be addre

Jenő Szirmai

In the present paper we study $\SXR$ and $\HXR$ geometries, which are homogeneous Thurston 3-geometries. We define and determine the generalized Apollonius surfaces and with them define the &#34;surface of a geodesic triangle&#34;. Using the above Apollonius surfaces we develop a procedure to determine the centre and the radius of the circumscribed geodesic

Xiaoqi Jiao, Huating Chang, Yichun Yin, Lifeng Shang

Knowledge distillation (KD) which transfers the knowledge from a large teacher model to a small student model, has been widely used to compress the BERT model recently. Besides the supervision in the output in the original KD, recent works show that layer-level supervision is crucial to the performance of the student BERT model. However, previous works desig

V. SRajashekhar, M. R. Vibha, Kaushik Das, Debasish Ghose

Aerial transportation requires a simple yet reliable gripper for picking and placing objects of interest. In this work, we design an aerial gripper for passive grasping and impulsive release of ferrous coated objects. Permanent magnets are used for passive grasping and the Scotch Yoke mechanism is used for providing impulsive force to drop the object. The lo

Hua Li, Yuheng Jia, Runmin Cong, Wenhui Wu

Superpixel segmentation aims at dividing the input image into some representative regions containing pixels with similar and consistent intrinsic properties, without any prior knowledge about the shape and size of each superpixel. In this paper, to alleviate the limitation of superpixel segmentation applied in practical industrial tasks that detailed boundar

Jie Gu, Feng Wang, Qinghui Sun, Zhiquan Ye

User modeling is critical for developing personalized services in industry. A common way for user modeling is to learn user representations that can be distinguished by their interests or preferences. In this work, we focus on developing universal user representation model. The obtained universal representations are expected to contain rich information, and

Mayank Gokarna, Raju Singh

DevOps is an emerging practice to be followed in Software Development life cycle. The name DevOps indicates that its an integration of Development and Operations team. It is followed to integrate the various stages of the development lifecycle. DevOps is an extended version of the existing Agile method. DevOps aims at Continuous Integration, Continuous Deliv

Markus Holzer, Martin Bauer, Ulrich Rüde

A high-performance implementation of a multiphase lattice Boltzmann method based on the conservative Allen-Cahn model supporting high-density ratios and high Reynolds numbers is presented. Metaprogramming techniques are used to generate optimized code for CPUs and GPUs automatically. The coupled model is specified in a high-level symbolic description and opt

Matīss Rikters, Ryokan Ri, Tong Li, Toshiaki Nakazawa

Sentence-level (SL) machine translation (MT) has reached acceptable quality for many high-resourced languages, but not document-level (DL) MT, which is difficult to 1) train with little amount of DL data; and 2) evaluate, as the main methods and data sets focus on SL evaluation. To address the first issue, we present a document-aligned Japanese-English conve

Arun Dev Sharma, Inderjeet Kaur

SARS-CoV-2 (COVID-19), a positive single stranded RNA virus, member of corona virus family, is spreading its tentacles across the world due to lack of drugs at present. Being associated with cough, fever, and respiratory distress, this disease caused more than 15 % mortality worldwide. Due to its vital role in virus replication, Mpro/3CLpro has recently been

Beibin Li, Ezgi Mercan, Sachin Mehta, Stevan Knezevich

In this study, we propose the Ductal Instance-Oriented Pipeline (DIOP) that contains a duct-level instance segmentation model, a tissue-level semantic segmentation model, and three-levels of features for diagnostic classification. Based on recent advancements in instance segmentation and the Mask R-CNN model, our duct-level segmenter tries to identify each d

Lingbo Yang, Zhanning Gao, Peiran Ren, Siwei Ma

Temporal consistency is crucial for extending image processing pipelines to the video domain, which is often enforced with flow-based warping error over adjacent frames. Yet for human video synthesis, such scheme is less reliable due to the misalignment between source and target video as well as the difficulty in accurate flow estimation. In this paper, we p

Bin Xiao, Tao Geng, Xiuli Bi, Weisheng Li

Local binary pattern (LBP) as a kind of local feature has shown its simplicity, easy implementation and strong discriminating power in image recognition. Although some LBP variants are specifically investigated for color image recognition, the color information of images is not adequately considered and the curse of dimensionality in classification is easily

Joshua Frankie Rayo, Vena Pearl Boñgolan

The Advanced Circulation (ADCIRC) and Simulating Nearshore Waves (SWAN) coupled model is modified to include a stochastic term in the shallow water equations that represents random external forces from debris carried by surge and short-term local scale atmospheric fluctuations. We added $α$-stable noise, uncorrelated in space and time, in the forcing terms o

Yaojun Zhang, Aakash Basu, Taekjip Ha, William Bialek

Modern genomics experiments measure functional behaviors for many thousands of DNA sequences. We suggest that, especially when these sequences are chosen at random, it is natural to compute correlation functions between sequences and measured behaviors. In simple models for the dependence of DNA flexibility on sequence, for example, correlation functions can

Zhihao Xia, Jason Lawrence, Supreeth Achar

Casual photography is often performed in uncontrolled lighting that can result in low quality images and degrade the performance of downstream processing. We consider the problem of estimating surface normal and reflectance maps of scenes depicting people despite these conditions by supplementing the available visible illumination with a single near infrared

Haziq Razali, Basura Fernando

The use of latent variable models has shown to be a powerful tool for modeling probability distributions over sequences. In this paper, we introduce a new variational model that extends the recurrent network in two ways for the task of video frame prediction. First, we introduce 3D convolutions inside all modules including the recurrent model for future fram

Ramtin Hosseini, Xingyi Yang, Pengtao Xie

In deep learning applications, the architectures of deep neural networks are crucial in achieving high accuracy. Many methods have been proposed to search for high-performance neural architectures automatically. However, these searched architectures are prone to adversarial attacks. A small perturbation of the input data can render the architecture to change

Kouki Yonaga, Masamichi J. Miyama, Masayuki Ohzeki

We propose a new method for solving binary optimization problems under inequality constraints using a quantum annealer. To deal with inequality constraints, we often use slack variables, as in previous approaches. When we use slack variables, we usually conduct a binary expansion, which requires numerous physical qubits. Therefore, the problem of the current

Erik Wijmans, Irfan Essa, Dhruv Batra

PointGoal navigation has seen significant recent interest and progress, spurred on by the Habitat platform and associated challenge. In this paper, we study PointGoal navigation under both a sample budget (75 million frames) and a compute budget (1 GPU for 1 day). We conduct an extensive set of experiments, cumulatively totaling over 50,000 GPU-hours, that l

Jie Zhang, Manuela Temmer, Nat Gopalswamy, Olga Malandraki

This review article summarizes the advancement in the studies of Earth-affecting solar transients in the last decade that encompasses most of solar cycle 24. The Sun Earth is an integrated physical system in which the space environment of the Earth sustains continuous influence from mass, magnetic field and radiation energy output of the Sun in varying time

S. A. Sapozhnikov, D. A. Kovaleva, O. Yu. Malkov, A. Yu. Sytov

We describe a homogeneous catalog compilation of common proper motion stars based on Gaia DR2. A preliminary list of all pairs of stars within the radius of 100 pc around the Sun with a separation less than a parsec was compiled. Also, a subset of comoving pairs, wide binary stars, was selected. The clusters and systems with multiplicity larger than 2 were e

You Li, Binli Luo, Ning Gui

Low-dimension graph embeddings have proved extremely useful in various downstream tasks in large graphs, e.g., link-related content recommendation and node classification tasks, etc. Most existing embedding approaches take nodes as the basic unit for information aggregation, e.g., node perception fields in GNN or con-textual nodes in random walks. The main d

Pranav Mahajan, Advait Rane, Swapna Sasi, Basabdatta Sen Bhattacharya

We present a collated set of algorithms to obtain objective measures of synchronisation in brain time-series data. The algorithms are implemented in MATLAB; we refer to our collated set of &#39;tools&#39; as SyncBox. Our motivation for SyncBox is to understand the underlying dynamics in an existing population neural network, commonly referred to as neural ma

Weixin Wang

Recently, literature on dynamic coherent risk measures has broadened the choices for risk-sensitive performance evaluation. A running example includes Cumulative prospect theory and Conditional variance at risk. Most of them can be can be interpreted in general as a non-linear transformation of a given random variable. Non-convexity property has implied a lo

Haoxi Zhan, Xiaobing Pei

Deep learning models for graphs, especially Graph Convolutional Networks (GCNs), have achieved remarkable performance in the task of semi-supervised node classification. However, recent studies show that GCNs suffer from adversarial perturbations. Such vulnerability to adversarial attacks significantly decreases the stability of GCNs when being applied to se

Zhongguo Li, Anders Heyden, Magnus Oskarsson

This paper presents a novel method for 3D human pose and shape estimation from images with sparse views, using joint points and silhouettes, based on a parametric model. Firstly, the parametric model is fitted to the joint points estimated by deep learning-based human pose estimation. Then, we extract the correspondence between the parametric model of pose f

Elsa de la Calleja, Roberto Zenit

Intricate patterns in abstract art many times can be wrongly characterized as being complex. Complexity can be an indicator of the internal dynamic of the whole system, regardless of the type of system in question, including art creation. In this investigation, we use two different techniques to objectively quantify complexity in abstract images: the fractal

Jian-Jun Shu, Kunal Krishnaraj Shastri

The incomplete version of the Macdonald function has various appellations in literature and earns a well-deserved reputation of being a computational challenge. This paper ties together the previously disjoint literature and presents the basic properties of the incomplete Macdonald function, such as recurrence and differential relations, series and asymptoti

Xin Jia, Wenjie Zhou, Xu Sun, Yunfang Wu

Question Generation (QG) is an essential component of the automatic intelligent tutoring systems, which aims to generate high-quality questions for facilitating the reading practice and assessments. However, existing QG technologies encounter several key issues concerning the biased and unnatural language sources of datasets which are mainly obtained from th

Dabin Zheng, Xiaoqiang Wang, Yayao Li, Mu Yuan

Let $\mathbb{F}_{p^m}$ be a finite field with $p^m$ elements, where $p$ is an odd prime and $m$ is a positive integer. Recently, \cite{Hengar} and \cite{Wang2020} determined the weight distributions of subfield codes with the form $$\mathcal{C}_f=\left\{\left(\left( {\rm Tr}_1^m(a f(x)+bx)+c\right)_{x \in \mathbb{F}_{p^m}}, {\rm Tr}_1^m(a)\right)\, : \, a,b

Yassin Khalifa, Danilo Mandic, Ervin Sejdić

Biomedical signals carry signature rhythms of complex physiological processes that control our daily bodily activity. The properties of these rhythms indicate the nature of interaction dynamics among physiological processes that maintain a homeostasis. Abnormalities associated with diseases or disorders usually appear as disruptions in the structure of the r

Arsalane Chouaib Guidoum

The kedd package providing additional smoothing techniques to the R statistical system. Although various packages on the Comprehensive R Archive Network (CRAN) provide functions useful to nonparametric statistics, kedd aims to serve as a central location for more specifically of a nonparametric functions and data sets. The current feature set of the package

Houmem Belkhechine

A graph $G$ is primarily orientable if it is possible to orient its edges in such a way that the resulting oriented graph is prime, i.e., indecomposable under modular decomposition. We characterize primarily orientable graphs.

Zhao Liu, Biao Wang

Ever since its publication, the Griffith theory is the most widely used criterion for estimating the ideal strength and fracture strength of materials depending on whether the materials contain cracks or not. A Griffith strength limit of ~E/9 is the upper bound for ideal strengths of materials. With the improved quality of fabricated samples and the power of

Yuan Gao, Jian Huang, Yuling Jiao, Jin Liu

We propose an Euler particle transport (EPT) approach for generative learning. The proposed approach is motivated by the problem of finding an optimal transport map from a reference distribution to a target distribution characterized by the Monge-Ampere equation. Interpreting the infinitesimal linearization of the Monge-Ampere equation from the perspective o

Shuai Sun, Hong-Kang Hu, Yao-Kun Xu, Hui-Zu Lin

Under weak illumination, tracking and imaging moving object turns out to be hard. By spatially collecting the signal, single pixel imaging schemes promise the capability of image reconstruction from low photon flux. However, due to the requirement on large number of samplings, how to clearly image moving objects is an essential problem for such schemes. Here

Xinwei Fu, Wook-Hee Kim, Ajay Paddayuru Shreepathi, Mohannad Ismail

The advent of non-volatile main memory (NVM) enables the development of crash-consistent software without paying storage stack overhead. However, building a correct crash-consistent program remains very challenging in the presence of a volatile cache. This paper presents WITCHER, a crash consistency bug detector for NVM software, that is (1) scalable -- does

Y. Gomez-Leyton, Hina Javaid, L. S. Rocha, Francisco Tello-Ortiz

This research develops a well-established analytical solution of the Einstein-Maxwell field equations. We analyze the behavior of a spherically symmetric and static interior driven by a charged anisotropic matter distribution. The class I methodology is used to close the system of equations and a suitable relation between the anisotropy factor and the electr

Shuhei Saito, Wei Wu, Naoki Matsumoto

Given an edge-colored complete graph $K_n$ on $n$ vertices, a perfect (respectively, near-perfect) matching $M$ in $K_n$ with an even (respectively, odd) number of vertices is rainbow if all edges have distinct colors. In this paper, we consider an edge coloring of $K_n$ by circular distance, and we denote the resulting complete graph by $K^{\bullet}_n$. We

Stuart Lee, Ursula Laa, Dianne Cook

Non-linear dimensionality reduction (NLDR) methods such as t-distributed stochastic neighbour embedding (t-SNE) are ubiquitous in the natural sciences, however, the appropriate use of these methods is difficult because of their complex parameterisations; analysts must make trade-offs in order to identify structure in the visualisation of an NLDR technique. W

Yusha Liu, Yining Wang, Aarti Singh

We consider bandit optimization of a smooth reward function, where the goal is cumulative regret minimization. This problem has been studied for $α$-Hölder continuous (including Lipschitz) functions with $0<α\leq 1$. Our main result is in generalization of the reward function to Hölder space with exponent $α>1$ to bridge the gap between Lipschitz bandits and