December 2020 arXiv papers — page 136

Carlos A. Michelén Ströfer, Xin-Lei Zhang, Heng Xiao

In many areas of science and engineering, it is a common task to infer physical fields from sparse observations. This paper presents the DAFI code intended as a flexible framework for two broad classes of such inverse problems: data assimilation and field inversion. DAFI generalizes these diverse problems into a general formulation and solves it with ensembl

David Williamson, Hugo Martel

We present a series of chemodynamical simulations of Magellanic-like systems consisting of two interacting, equal-mass dwarf galaxies orbiting a massive host galaxy, including feedback and star formation, tides, and ram pressure. We study the star formation and chemical enrichment history of the dwarfs, and the production of a Magellanic Stream analogue. The

Bo Hu, Keping Qiu, Yue Cao, Junhao Liu

DR21 south filament (DR21SF) is a unique component of the giant network of filamentary molecular clouds in the north region of Cygnus X complex. Unlike the highly fragmented and star-forming active environment it resides, DR21SF exhibits a coherent profile in the column density map with very few star formation signposts, even though the previously reported l

Daniel Strüber

We present a solution to the Round-Trip Migration case of the Transformation Tool Contest 2020, based on the Henshin model transformation language. The task is to support four scenarios of transformations between two versions of the same data metamodel, a problem inspired by the application scenario of Web API migration, where such a round-trip migration met

Soumik Sarker, Arnob Kumar Saha, Md Sadek Ferdous

Blockchain is one of the emerging technologies with the potential to disrupt many application domains. Cloud is an on-demand service paradigm facilitating the availability of shared resources for data storage and computation. In recent years, the integration of blockchain and cloud has received significant attention for ensuring efficiency, transparency, sec

Faranak Abri, Luis Felipe Gutiérrez, Akbar Siami Namin, David R. W. Sears

Sonification is the science of communication of data and events to users through sounds. Auditory icons, earcons, and speech are the common auditory display schemes utilized in sonification, or more specifically in the use of audio to convey information. Once the captured data are perceived, their meanings, and more importantly, intentions can be interpreted

Sohan Kumar Jha, Himangshu Barman, Anisur Rahaman

A metric with a Lorentz violating parameter is associated with the bumblebee gravity model. We study the motion of a particle in this bumblebee background where the dynamical variables satisfy non-canonical Snyder algebra along with some critical survey on the classical observations in the bumblebee background to see how these would likely differ from Schwar

Wenchao Zhang, Chong Fu, Haoyu Xie, Mai Zhu

RoIPool/RoIAlign is an indispensable process for the typical two-stage object detection algorithm, it is used to rescale the object proposal cropped from the feature pyramid to generate a fixed size feature map. However, these cropped feature maps of local receptive fields will heavily lose global context information. To tackle this problem, we propose a nov

Zachary J. Lee, George Lee, Ted Lee, Cheng Jin

We describe the architecture and algorithms of the Adaptive Charging Network (ACN), which was first deployed on the Caltech campus in early 2016 and is currently operating at over 100 other sites in the United States. The architecture enables real-time monitoring and control and supports electric vehicle (EV) charging at scale. The ACN adopts a flexible Adap

Fatemeh Asgari, Mohammad Hossein Alamatsaz, Valeria Vitelli, Saeed Hayati

In this paper, we study a functional regression setting where the random response curve is unobserved, and only its dichotomized version observed at a sequence of correlated binary data is available. We propose a practical computational framework for maximum likelihood analysis via the parameter expansion technique. Compared to existing methods, our proposal

J. Song, Z. Zuo, M. Basin

To reduce the chattering and overestimation phenomena existing in classical adaptive sliding mode control, this paper presents a new class K_infinity function-based adaptive sliding mode control scheme. Two controllers are proposed in terms of concave and convex barrier functions to implement this kind of control methodology. To avoid large initial control m

Alexandre Araujo, Laurent Meunier, Rafael Pinot, Benjamin Negrevergne

It has been empirically observed that defense mechanisms designed to protect neural networks against $\ell_\infty$ adversarial examples offer poor performance against $\ell_2$ adversarial examples and vice versa. In this paper we conduct a geometrical analysis that validates this observation. Then, we provide a number of empirical insights to illustrate the

Ho-Joon Kim, Soojoon Lee, Ludovico Lami, Martin B. Plenio

We show that the dynamic resource theory of quantum entanglement can be formulated using the superchannel theory. In this formulation, we identify the separable channels and the class of free superchannels that preserve channel separability as free resources, and choose the swap channels as dynamic entanglement golden units. Our first result is that the one-

Robert Scheidweiler, Eberhard Triesch

We consider competitive algorithms for adaptive group testing problems. In the first part of the paper, we develop an algorithm with competitive constant c < 1.452 thus improving the up to now best known algorithms with constants 1.5+epsilon from 2003. In the second part, we prove the first nontrivial lower bound for competitive constants, namely that c is a

Zhiyong Huang, Kekai Sheng, Weiming Dong, Xing Mei

Semi-supervised domain adaptation (SSDA) methods have demonstrated great potential in large-scale image classification tasks when massive labeled data are available in the source domain but very few labeled samples are provided in the target domain. Existing solutions usually focus on feature alignment between the two domains while paying little attention to

Mojtaba Forghani, Yizhou Qian, Jonghyun Lee, Matthew W. Farthing

Fast and reliable prediction of riverine flow velocities is important in many applications, including flood risk management. The shallow water equations (SWEs) are commonly used for prediction of the flow velocities. However, accurate and fast prediction with standard SWE solvers is challenging in many cases. Traditional approaches are computationally expens

Stefan Schröder, Simon Stellmer, Jürgen Kusche

The GRACE and GRACE-FO missions have provided an unprecedented quantification of large-scale changes in the water cycle. However, it is still an open problem of how these missions&#39; data sets can be referenced to a ground truth. Meanwhile, stationary optical clocks show fractional instabilities below $10^{-18}$ when averaged over an hour, and continue to

Shmuel Onn

We show that the {\em column sum optimization problem}, of finding a $(0,1)$-matrix with prescribed row sums which minimizes the sum of evaluations of given functions at its column sums, can be solved in polynomial time, either when all functions are the same or when all row sums are bounded by any constant. We conjecture that the more general {\em line sum

Gwenael Le Gal, Laure-Line Rouve, Agustin Palacios-Laloy

We present here a new parametric resonance magnetometer scheme based on elliptically polarized pumping light and two radio-frequency fields applied along the two optical pumping directions. At optimum ellipticity and radio-frequency fields amplitudes the three components of the magnetic field are measured with an isotropic sensitivity. Compared to the usual

Krister Lindén, Tommi Jauhiainen, Sam Hardwick

Sentiment analysis and opinion mining is an important task with obvious application areas in social media, e.g. when indicating hate speech and fake news. In our survey of previous work, we note that there is no large-scale social media data set with sentiment polarity annotations for Finnish. This publications aims to remedy this shortcoming by introducing

Noboru Ito, Yusuke Takimura

We consider 32 homotopy classifications of knot projections (images of generic immersions from a circle into a 2-sphere). These 32 equivalence relations are obtained based on which moves are forbidden among the five type of Reidemeister moves. We show that 32 cases contain 20 non-trivial cases that are mutually different. To complete the proof, we obtain new

J. David Ballester-Berman

This report revisits the role of the extinction coefficient in radar backscattering-based models for forest monitoring. A review of a number of works dealing with this issue has revealed a diversity of extinction values being unclear its dependence on the sensor frequency and the forest type. In addition, a backscattering model directly derived from the RVoG

Petra Suková, Michal Zajaček, Vojtěch Witzany, Vladimír Karas

The close neighbourhood of a supermassive black hole contains not only accreting gas and dust, but also stellar-sized objects like stars, stellar-mass black holes, neutron stars, and dust-enshrouded objects that altogether form a dense nuclear star-cluster. These objects interact with the accreting medium and they perturb the otherwise quasi-stationary confi

Kamiokande Collaboration, K. Abe, C. Bronner, Y. Hayato

As a baryon number violating process with $ΔB=2$, neutron-antineutron oscillation ($n\to\bar n$) provides a unique test of baryon number conservation. We have performed a search for $n\to\bar n$ oscillation with bound neutrons in Super-Kamiokande, with the full data set from its first four run periods, representing an exposure of 0.37~Mton-years. The search

Jiri Junek, Karel Zidek

Photoluminesce (PL) spectroscopy offers excellent methods for mapping the PL decay on the nanosecond time scale. However, capturing maps of emission dynamics on the microsecond time scale can be highly time-consuming. We present a new approach to fluorescence lifetime imaging FLIM, which combines the concept of random temporal speckles excitation (RATS) with

Panumate Chetprayoon, Fumihiko Takahashi, Yusuke Uchida

The lane number that the vehicle is traveling in is a key factor in intelligent vehicle fields. Many lane detection algorithms were proposed and if we can perfectly detect the lanes, we can directly calculate the lane number from the lane detection results. However, in fact, lane detection algorithms sometimes underperform. Therefore, we propose a new approa

G. Maciejewski, M. Fernandez, A. Sota, A. J. Garcia Segura

The WASP-148 planetary system has a rare architecture with a transiting Saturn-mass planet on a tight orbit which is accompanied by a slightly more massive planet on a nearby outer orbit. Using new space-born photometry and ground-based follow-up transit observations and data available in literature, we performed modeling that accounts for gravitational inte

Viviana Niro

Among the gamma-ray sources detected by the HAWC observatory, we consider in details in this work the gamma-ray sources eHWC J1907+063 and eHWC J2019+368. These two sources belong to the three most luminous sources detected by HAWC, with emission above 100 TeV. In addition to those, we have considered also a source for which IceCube currently report an exces

Jingwei Xu, Jianjin Zhang, Zhiyu Yao, Yunbo Wang

This technical report presents a solution for the 2020 Traffic4Cast Challenge. We consider the traffic forecasting problem as a future frame prediction task with relatively weak temporal dependencies (might be due to stochastic urban traffic dynamics) and strong prior knowledge, \textit{i.e.}, the roadmaps of the cities. For these reasons, we use the U-Net a

Valeria Gutiérrez

Given a nilpotent Lie algebra, we study the space of all diagonalizable derivations such that the corresponding one-dimensional solvable extension admits a left-invariant metric with negative Ricci curvature. It has been conjectured by Lauret-Will that such a space coincides with an open and convex subset of derivations defined in terms of the moment map for

C. M. Ekpo, Ephraim P. Inyang, P. O. Okoi, T. O. Magu

In this study, we obtain the approximate analytical solutions of the radial Schrodinger equation for the New Generalized Morse-Like Potential in arbitrary dimensions by using the Nikiforov Uvarov Method. Energy eigenvalues and corresponding eigenfunction are obtain analytically. The rotational-vibrational energy eigenvalues for some diatomic molecules are co

Chiman Kwan, Bence Budavari

Since targets are small in long range infrared (IR) videos, it is challenging to accurately detect targets in those videos. In this paper, we propose a high performance approach to detecting small targets in long range and low quality infrared videos. Our approach consists of a video resolution enhancement module, a proven small target detector based on loca

Khalid Alnajjar, Mika Hämäläinen, Jack Rueter, Niko Partanen

We present an open-source online dictionary editing system, Ve&#39;rdd, that offers a chance to re-evaluate and edit grassroots dictionaries that have been exposed to multiple amateur editors. The idea is to incorporate community activities into a state-of-the-art finite-state language description of a seriously endangered minority language, Skolt Sami. Prob

Alexandre C. M. Correia

A giant collision is believed to be at the origin of the Pluto-Charon system. As a result, the initial orbit and spins after impact may have substantially differed from those observed today. More precisely, the distance at periapse may have been shorter, subsequently expanding to its current separation by tides raised simultaneously on the two bodies. Here w

Jin Cao, Maoyuan Wang, Cheng-Cheng Liu, Yugui Yao

The newly realized twisted graphene systems such as twisted bilayer graphene (TBG), twisted double bilayer graphene (TDBG), and twisted trilayer graphene (TTG) have attracted widespread theoretical attention. Therefore, a simple and accurate model of the systems is of vital importance for the further study. Here, we construct the symmetry-adapted localized W

Dahui Wang, Yinren Shou, Pengjie Wang, Jianbo Liu

Single-shot laser-induced damage threshold (LIDT) measurements of multi-type free-standing ultrathin foils were performed in vacuum environment for 800 nm laser pulses with durations τ ranging from 50 fs to 200 ps. Results show that the laser damage threshold fluences (DTFs) of the ultrathin foils are significantly lower than those of corresponding bulk mate

W. J. Torres Bobadilla, G. F. R. Sborlini, P. Banerjee, S. Catani

In this report, we present a discussion about different frameworks to perform precise higher-order computations for high-energy physics. These approaches implement novel strategies to deal with infrared and ultraviolet singularities in quantum field theories. A special emphasis is devoted to the local cancellation of these singularities, which can enhance th

Eric Ricard

We prove a basic inequality involving anticommutators in noncommutative $L_p$-spaces. We use it to complete our study of the noncommutative Mazur maps from $L_p$ to $L_q$ showing that they are Lipschitz on balls when $0<q<p<\infty$.

Thushari Atapattu, Mahen Herath, Georgia Zhang, Katrina Falkner

Cyberbullying is a prevalent and growing social problem due to the surge of social media technology usage. Minorities, women, and adolescents are among the common victims of cyberbullying. Despite the advancement of NLP technologies, the automated cyberbullying detection remains challenging. This paper focuses on advancing the technology using state-of-the-a

Artur Stephan

We perform a fast-reaction limit for a linear reaction-diffusion system consisting of two diffusion equations coupled by a linear reaction. We understand the linear reaction-diffusion system as a gradient flow of the free energy in the space of probability measure equipped with a geometric structure, which contains the Wasserstein metric for the diffusion pa

Hacene Belbachir, Yassine Otmani

We give a combinatorial identity related to the Franel numbers involving the sum of fourth power of binomial coefficients. Furthermore, investigating in J. Mikic&#39;s proof of the first Strehl Identity, we provide a combinatorial proof of this identity using the double counting argument.

Michael Hoese, Michael K. Koch, Vibhav Bharadwaj, Johannes Lang

The negatively-charged NV$^-$-center in diamond has shown great success in nanoscale, high-sensitivity magnetometry. Efficient fluorescence detection is crucial for improving the sensitivity. Furthermore, integrated devices enable practicable sensors. Here, we present a novel architecture which allows us to create NV$^-$-centers a few nanometers below the di

A. Tiribocchi, A. Montessori, F. Bonaccorso, M. Lauricella

We numerically study the dynamic behavior under a symmetric shear flow of selected examples of concentrated phase emulsions with multi-core morphology confined within a microfluidic channel. A variety of new nonequilibrium steady states is reported. Under low shear rates, the emulsion is found to exhibit a solid-like behavior, in which cores display a period

V. D. Viellieber, M. Aßenmacher

Recently it has been shown that large pre-trained language models like BERT (Devlin et al., 2018) are able to store commonsense factual knowledge captured in its pre-training corpus (Petroni et al., 2019). In our work we further evaluate this ability with respect to an application from industry creating a set of probes specifically designed to reveal technic

L. Ji, V. Doroshenko, V. Suleimanov, A. Santangelo

We investigate the absorption and emission features in observations of GX 301-2 detected with Insight-HXMT/LE in 2017-2019. At different orbital phases, we found prominent Fe Kalpha, Kbeta and Ni Kalpha lines, as well as Compton shoulders and Fe K-shell absorption edges. These features are due to the X-ray reprocessing caused by the interaction between the r

Claudio Canella, Mario Werner, Daniel Gruss, Michael Schwarz

Software vulnerabilities in applications undermine the security of applications. By blocking unused functionality, the impact of potential exploits can be reduced. While seccomp provides a solution for filtering syscalls, it requires manual implementation of filter rules for each individual application. Recent work has investigated automated approaches for d

Qi Jia, Hongru Huang, Kenny Q. Zhu

Interpersonal language style shifting in dialogues is an interesting and almost instinctive ability of human. Understanding interpersonal relationship from language content is also a crucial step toward further understanding dialogues. Previous work mainly focuses on relation extraction between named entities in texts. In this paper, we propose the task of r

Fabio Caccioli, Daniele De Martino

Epidemic spreading can be suppressed by the introduction of containment measures such as social distancing and lock downs. Yet, when such measures are relaxed, new epidemic waves and infection cycles may occur. Here we explore this issue in compartmentalized epidemic models on graphs in presence of a feedback between the infection state of the population and

Rajko Nenadov, Angelika Steger, Pascal Su

We design a randomized algorithm that finds a Hamilton cycle in $\mathcal{O}(n)$ time with high probability in a random graph $G_{n,p}$ with edge probability $p\ge C \log n / n$. This closes a gap left open in a seminal paper by Angluin and Valiant from 1979.

Alex Küronya, Sönke Rollenske

Let $X$ be a general hypersurface of degree $md$ in the weighted projective space with weights $1,1,1,m$ for some for $d\geq 2$ and $m\geq 3$. We prove that the Seshadri constant of the ample generator of the Néron-Severi space at a general point $x\in X$ lies in the interval $\left[\sqrt{d}- \frac d m, \sqrt{d}\right]$ and thus approaches the possibly irrat

Justo Puerto, Carlos Valverde

In this paper we deal with an extension of the crossing postman problem to design Hamiltonian routes that have to visit different shapes of dimensional elements (neighborhoods or polygonal chains) rather than edges. This problem models routes of drones that must visit a number of geographical elements to deliver some good or service and then move directly to

DongHyun Song, Kyungeon Choi, Youngun Jeng, Yechan Kang

A gas electron multiplier (GEM) detector with a gadolinium cathode has been developed to explore its potential application as a neutron detector. It consists of three standard-sized ($10\times 10$ cm${}^{2}$) GEM foils and a thin gadolinium plate as the cathode, which is used as a neutron converter. The neutron detection efficiencies were measured for two di

Antoni Szczurek, Piotr Lebiedowicz

The cross section for inclusive production of $f_2(1270)$ meson is calculated. We include both the mechanism of gluon-gluon fusion as well as the $ππ$ final-state rescattering. The contribution of the gluon-gluon fusion is calculated within the $k_t$-factorization approach with modern unintegrated gluon distribution functions (UGDFs). Some parameters for the

José Carlos Aradillas, Juan José Murillo-Fuentes, Pablo M. Olmos

In this paper, we face the problem of offline handwritten text recognition (HTR) in historical documents when few labeled samples are available and some of them contain errors in the train set. Three main contributions are developed. First we analyze how to perform transfer learning (TL) from a massive database to a smaller historical database, analyzing whi

Jason Sang Hun Lee, Sang Man Lee, Yunjae Lee, Inkyu Park

Deep learning techniques are currently being investigated for high energy physics experiments, to tackle a wide range of problems, with quark and gluon discrimination becoming a benchmark for new algorithms. One weakness is the traditional reliance on Monte Carlo simulations, which may not be well modelled at the detail required by deep learning algorithms.

Gautham Krishna Gudur, Satheesh K. Perepu

Various health-care applications such as assisted living, fall detection, etc., require modeling of user behavior through Human Activity Recognition (HAR). Such applications demand characterization of insights from multiple resource-constrained user devices using machine learning techniques for effective personalized activity monitoring. On-device Federated

Manato Fujimoto, Mikito Koshino

We study the edge states of twisted bilayer graphene and their topological origin. We show that the twisted bilayer graphene has special edge states associated with the moiré pattern, and the emergence of these moiré edge states is linked with the sliding Chern number, which describes topological charge pumping caused by relative interlayer sliding. When one

Basilis Mamalis, Marios Perlitis

Organizing sensor nodes in clusters is an effective method for energy preservation in a Wireless Sensor Network (WSN). Throughout this research work we present a novel hybrid clustering scheme, that combines a typical gradient clustering protocol with an evolutionary optimization method that is mainly based on the Gravitational Search Algorithm (GSA). The pr

Daizong Liu, Dongdong Yu, Changhu Wang, Pan Zhou

Although deep learning based methods have achieved great progress in unsupervised video object segmentation, difficult scenarios (e.g., visual similarity, occlusions, and appearance changing) are still not well-handled. To alleviate these issues, we propose a novel Focus on Foreground Network (F2Net), which delves into the intra-inter frame details for the f

Igor Protsenko, Alexander Uskov, Emil C. André, Jesper Mørk

A new approach for analytically solving quantum nonlinear Langevin equations is proposed and applied to calculations of spectra of superradiant lasers where collective effects play an important role. We calculate lasing spectra for arbitrary pump rates and recover well-known results such as the pump dependence of the laser linewidth across the threshold regi

Jason Sang Hun Lee, Inkyu Park, Ian James Watson, Seungjin Yang

Currently, newly developed artificial intelligence techniques, in particular convolutional neural networks, are being investigated for use in data-processing and classification of particle physics collider data. One such challenging task is to distinguish quark-initiated jets from gluon-initiated jets. Following previous work, we treat the jet as an image by

Johanna Rock, Mate Toth, Paul Meissner, Franz Pernkopf

Radar sensors are crucial for environment perception of driver assistance systems as well as autonomous cars. Key performance factors are a fine range resolution and the possibility to directly measure velocity. With a rising number of radar sensors and the so far unregulated automotive radar frequency band, mutual interference is inevitable and must be deal

Roja Hosseinzadeh

Let $\mathcal{A}$ and $\mathcal{B}$ be standard operator algebras on Banach spaces $\mathcal{X}$ and $\mathcal{Y}$, respectively. In this paper, we show that every bijection completely preserving quadratic operators from $\mathcal{A}$ onto $\mathcal{B}$ is either an isomorphism or (in the complex case) a conjugate isomorphism.

Alessandro Sestini, Alexander Kuhnle, Andrew D. Bagdanov

Deep Reinforcement Learning achieves very good results in domains where reward functions can be manually engineered. At the same time, there is growing interest within the community in using games based on Procedurally Content Generation (PCG) as benchmark environments since this type of environment is perfect for studying overfitting and generalization of a

Qizhang Li, Yiwen Guo, Hao Chen

The study of adversarial vulnerabilities of deep neural networks (DNNs) has progressed rapidly. Existing attacks require either internal access (to the architecture, parameters, or training set of the victim model) or external access (to query the model). However, both the access may be infeasible or expensive in many scenarios. We investigate no-box adversa

Armengol Gasull

The aim of this paper is to share with the mathematical community a list of 33 problems that I have found along the years during my research. I believe that it is worth to think about them and, hopefully, it will be possible either to solve some of the problems or to make some substantial progress. Many of them are about planar differential equations but the

Sami Akın, Maxim Penner, Jürgen Peissig

Modern communication systems organize receivers in blocks in order to simplify their analysis and design. However, an approach that considers the receiver design from a wider perspective rather than treating it block-by-block may take advantage of the impacts of these blocks on each other and provide better performance. Herein, we can benefit from machine le

Manuel Radons, Siegfried M. Rump

Let $A$ be a real $n\times n$ matrix and $z,b\in \mathbb R^n$. The piecewise linear equation system $z-A\vert z\vert = b$ is called an \textit{absolute value equation}. We consider two solvers for this problem, one direct, one semi-iterative, and extend their previously known ranges of convergence.

Shinji Horiuchi, Blake Molyneux, Jamie B. Stevens, Graham Baines

We report results of Canberra-ATCA Doppler-only continuous wave (CW) radar observations of near-Earth asteroid (163899) 2003 SD220 at a receiving frequency of 7159 MHz (4.19 cm) on 2018 December 20, 21, and 22 during its close approach within 0.019 au (7.4 lunar distances). Echo power spectra provide evidence that the shape is significantly elongated, asymme

Kyosuke Adachi, Kyogo Kawaguchi

The motility-induced phase separation (MIPS) is the spontaneous aggregation of active particles, while equilibrium phase separation (EPS) is thermodynamically driven by attractive interactions between passive particles. Despite such difference in the microscopic mechanism, similarities between MIPS and EPS like free energy structure and critical phenomena ha

Patrick Esser, Robin Rombach, Björn Ommer

It is tempting to think that machines are less prone to unfairness and prejudice. However, machine learning approaches compute their outputs based on data. While biases can enter at any stage of the development pipeline, models are particularly receptive to mirror biases of the datasets they are trained on and therefore do not necessarily reflect truths abou

Antoni Ferragut, Armengol Gasull, Xiang Zhang

We give an upper bound for the number of functionally independent meromorphic first integrals that a discrete dynamical system generated by an analytic map $f$ can have in a neighborhood of one of its fixed points. This bound is obtained in terms of the resonances among the eigenvalues of the differential of $f$ at this point. Our approach is inspired on sim

Valeria Ageeva, Aleksey Novokhrestov, Maria Kholodova

The purpose of the study is to supplement and update the list of threats to the confidentiality and integrity of the system. The article focuses on the already compiled list of threats and a model of system, but also considers new threats and types of threats. Scientific novelty is in the interdisciplinary consideration of the issue with the involvement of t

Behzad Shahrasbi, Venugopal Mani, Apoorv Reddy Arrabothu, Deepthi Sharma

Recommender systems are an essential part of any e-commerce platform. Recommendations are typically generated by aggregating large amounts of user data. A malicious actor may be motivated to sway the output of such recommender systems by injecting malicious datapoints to leverage the system for financial gain. In this work, we propose a semi-supervised attac

Dominique Mariko, Hanna Abi Akl, Estelle Labidurie, Stéphane Durfort

We present the FinCausal 2020 Shared Task on Causality Detection in Financial Documents and the associated FinCausal dataset, and discuss the participating systems and results. Two sub-tasks are proposed: a binary classification task (Task 1) and a relation extraction task (Task 2). A total of 16 teams submitted runs across the two Tasks and 13 of them contr

Nicola Melillo, Adam S. Darwich

In pharmaceutical research and development decision-making related to drug candidate selection, efficacy and safety is commonly supported through modelling and simulation (M\&S). Among others, physiologically-based pharmacokinetic models are used to describe drug absorption, distribution and metabolism in human. Global sensitivity analysis (GSA) is gaining i

Kun Zhao, Xinzhu Xu, Wei Ren, Peng Xi

Achieving localization with molecular precision has been of great interest for extending fluorescence microscopy to nanoscopy. MINFLUX pioneers this transition through point spread function (PSF) engineering, yet its performance is primarily limited by the signal-to-background ratio. Here we demonstrate that applying two-photon excitation to MINFLUX would do

Dominique Mariko, Estelle Labidurie, Yagmur Ozturk, Hanna Abi Akl

This document explains the annotation schemes used to label the data for the FinCausal Shared Task (Mariko et al., 2020). This task is associated to the Joint Workshop on Financial Narrative Processing and MultiLing Financial Summarisation (FNP-FNS 2020), to be held at The 28th International Conference on Computational Linguistics (COLING&#39;2020), on Decem

Seung Yeon Cho, Sebastiano Boscarino, Maria Groppi, Giovanni Russo

In this work, we propose a class of high order semi-Lagrangian scheme for a general consistent BGK model for inert gas mixtures. The proposed scheme not only fulfills indifferentiability principle, but also asymptotic preserving property, which allows us to capture the behaviors of hydrodynamic limit models. We consider two hydrodynamic closure which can be

Sahil Gangurde, Krishnakant Tiwari

Image steganography is the art of hiding data into images. Secret data such as messages, audio, images can be hidden inside the cover image. This is mainly achieved by hiding the data into the LSB(Least Significant Bit) of the image pixels. To improve the security of steganography, this paper studied data encryption with AES(Advanced Encryption Standard) and

Vincent Lafage

The differences between the sets in which ideal arithmetics takes place and the sets of floating point numbers are outlined. A set of classical problems in correct numerical evaluation is presented, to increase the awareness of newcomers to the field. A self-defense, prophylactic approach to numerical computation is advocated.

Junlin Yu, Man Hon Cheung, Jianwei Huang

To exploit users&#39; heterogeneous data demands, several mobile network operators worldwide have launched the mobile data trading markets, where users can trade mobile data quota with each other. In this paper, we aim to understand the importance of data trading market (DTM) by studying the users&#39; operator selection and trading decisions, and analyzing

Heiko Kroener, Matteo Novaga, Paola Pozzi

We consider motion by anisotropic curvature of a network of three curves immersed in the plane meeting at a triple junction and with the other ends fixed. We show existence, uniqueness and regularity of a maximal geometric solution and we prove that, if the maximal time is finite, then either the length of one of the curves goes to zero or the $L^2$ norm of

Shuang Li, Wei Xiong, Renzhuo Wan

The production of heavy quarks (charm and beauty) provides unique insights into the transport properties of the Quark-Gluon Plasma (QGP) in heavy-ion collisions. Experimentally, the nuclear modification factor ${{R}_{\rm AA}}$ and the azimuthal anisotropy coefficient ${v}_{\rm 2}$ of heavy-flavor mesons are powerful observables to study the medium-related ef

L. D. Kong, S. Zhang, Y. P. Chen, S. N. Zhang

We present the analysis of the brightest flare that was recorded in the \emph{Insight}-HMXT data set, in a broad energy range (2$-$200 keV) from the microquasar GRS~1915+105 during an unusual low-luminosity state. This flare was detected by \emph{Insight}-HXMT among a series of flares during 2 June 2019 UTC 16:37:06 to 20:11:36, with a 2-200 keV luminosity o

Nikolaos G. Fytas, Argyro Mainou, Panagiotis E. Theodorakis, Anastasios Malakis

We investigate the scaling of the interfacial adsorption of the two-dimensional Blume-Capel model using Monte Carlo simulations. In particular, we study the finite-size scaling behavior of the interfacial adsorption of the pure model at both its first- and second-order transition regimes, as well as at the vicinity of the tricritical point. Our analysis bene

N. G. Fytas, P. E. Theodorakis

We report on large-scale Wang-Landau Monte Carlo simulations of the critical behavior of two spin models in two- (2d) and three-dimensions (3d), namely the 2d random-bond Ising model and the pure 3d Blume-Capel model at zero crystal-field coupling. The numerical data we obtain and the relevant finite-size scaling analysis provide clear answers regarding the

Chris D. White

The classical double copy relates exact solutions of gauge, gravity and other theories. Although widely studied, its origins and domain of applicability have remained mysterious. In this letter, we show that a particular incarnation - the Weyl double copy - can be derived using well-established ideas from twistor theory. As well as explaining where the Weyl

Rita Pucci, Christian Micheloni, Gian Luca Foresti, Niki Martinel

Human beings can imagine the colours of a grayscale image with no particular effort thanks to their ability of semantic feature extraction. Can an autonomous system achieve that? Can it hallucinate plausible and vibrant colours? This is the colourisation problem. Different from existing works relying on convolutional neural network models pre-trained with su

E. Nji Nde Aboringong, I. Ngek Ndifon, Alain M. Dikandé

Exciton-polariton solitons are strongly nonlinear quasiparticles composed of coupled exciton-photon states due to the interaction of light with matter. In semiconductor microcavity systems such as semiconductor micro and nanowires, polaritons are characterized by a negative mass which when combined with the repulsive nonlinear exciton-exciton interaction, le

Yanan Wang, Yong Ge, Li Li, Rui Chen

Reinforcement learning (RL) has shown great promise in optimizing long-term user interest in recommender systems. However, existing RL-based recommendation methods need a large number of interactions for each user to learn a robust recommendation policy. The challenge becomes more critical when recommending to new users who have a limited number of interacti

F. Mesple, A. Missaoui, T. Cea, L. Huder

The moiré of twisted graphene bilayers can generate flat bands in which charge carriers do not posses enough kinetic energy to escape Coulomb interactions with each other leading to the formation of novel strongly correlated electronic states. This exceptionally rich physics relies on the precise arrangement between the layers.We survey published Scanning Tu

Rabayet Sadnan, Anamika Dubey

The limitations of centralized optimization methods for power systems operation have led to the distributed computing paradigm, particularly in power distribution systems. The existing techniques reported in recent literature for solving distributed optimization problems are not viable for power distribution systems applications. The essential drawback remai

F. Naha Nzoupe, Alain M. Dikandé, C. Tchawoua

Recent studies have emphasized the important role that a shape deformability of scalar-field models pertaining to the same class with the standard $ϕ^4$ field, can play in controlling the production of a specific type of breathing bound states so-called oscillons. In the context of cosmology, the built-in mechanism of oscillons suggests that they can affect

Esra Pamukçu, Mehmet Niyazi Çankaya

Model selection is basically a process of finding the best model from the subset of models in which the explanatory variables are effective on the response variable. The log likelihood function for the lack of fit term and a specified penalty term are used as two parts in a model selection criteria. In this paper, we derive a new tool for the model selection

Mickaël Buchet, Emerson G. Escolar

Multidimensional persistence has been proposed to study the persistence of topological features in data indexed by multiple parameters. In this work, we further explore its algebraic complications from the point of view of higher dimensional indecomposable persistence modules containing lower dimensional ones as hyperplane restrictions. Our previous work con

Ngan Le, Trung Le, Kashu Yamazaki, Toan Duc Bui

Medical image segmentation has played an important role in medical analysis and widely developed for many clinical applications. Deep learning-based approaches have achieved high performance in semantic segmentation but they are limited to pixel-wise setting and imbalanced classes data problem. In this paper, we tackle those limitations by developing a new d

Daniel Grießhaber, Johannes Maucher, Ngoc Thang Vu

Recently, leveraging pre-trained Transformer based language models in down stream, task specific models has advanced state of the art results in natural language understanding tasks. However, only a little research has explored the suitability of this approach in low resource settings with less than 1,000 training data points. In this work, we explore fine-t

D. W. Gardenier, L. Connor, J. van Leeuwen, L. C. Oostrum

The observed Fast Radio Burst (FRB) population can be divided into one-off and repeating FRB sources. Either this division is a true dichotomy of the underlying sources, or selection effects and low activity prohibit us from observing repeat pulses from all constituents making up the FRB source population. We attempt to break this degeneracy through FRB popu

Jie Yang, Lin Gao, Qingyang Tan, Yihua Huang

Deformation component analysis is a fundamental problem in geometry processing and shape understanding. Existing approaches mainly extract deformation components in local regions at a similar scale while deformations of real-world objects are usually distributed in a multi-scale manner. In this paper, we propose a novel method to exact multiscale deformation