May 2020 arXiv papers — page 37

Aïssatou M. Ndiaye

In this paper, we investigate eigenvalues of the Wentzel-Laplace operator on a bounded domain in some Riemannian manifold. We prove asymptotically optimal estimates, according to the Weyl's law through bounds that are given in terms of the isoperimetric ratio of the domain. Our results show that the isoperimetric ratio allows to control the entire spectrum o

Priyadarshini Kumari, Subhasis Chaudhuri

In the real world, we often come across soft objects having spatially varying stiffness, such as human palm or a wart on the skin. In this paper, we propose a novel approach to render thin, deformable objects having spatially varying stiffness (inhomogeneous material). We use the classical Kirchhoff thin plate theory to compute the deformation. In general, t

Raul Jimenez, Alan F. Heavens

In the light of the discovery of numerous (almost) dark galaxies from the ALFALAFA and LITTLE THINGS surveys, we revisit the predictions of Jimenez et al. 1997, based on the Toomre stability of rapidly-spinning gas disks. We have updated the predictions for $\Lambda$CDM with parameters given by Planck18, computing the expected number densities of dark object

Pranav Poduval, Hrushikesh Loya, Amit Sethi

Deep neural networks have revolutionized medical image analysis and disease diagnosis. Despite their impressive performance, it is difficult to generate well-calibrated probabilistic outputs for such networks, which makes them uninterpretable black boxes. Bayesian neural networks provide a principled approach for modelling uncertainty and increasing patient

Argyrios Deligkas, Themistoklis Melissourgos, Paul G. Spirakis

We study the complexity of finding a Walrasian equilibrium in markets where the agents have $k$-demand valuations. These valuations are an extension of unit-demand valuations where a bundle's value is the maximum of its $k$-subsets' values. For unit-demand agents, where the existence of a Walrasian equilibrium is guaranteed, we show that the problem is in qu

Elad Michael, Tony A. Wood, Chris Manzie, Iman Shames

We examine the robustness of bottleneck assignment problems to perturbations in the assignment weights. We derive two algorithms that provide uncertainty bounds for robust assignment. We prove that the bottleneck assignment is guaranteed to be invariant to perturbations which lie within the provided bounds. We apply the method to an example of task assignmen

Geir Ole Tysse, Andrej Cibicik, Olav Egeland

A vision-based controller for a knuckle boom crane is presented. The controller is used to control the motion of the crane tip and at the same time compensate for payload oscillations. The oscillations of the payload are measured with three cameras that are fixed to the crane king and are used to track two spherical markers fixed to the payload cable. Based

Haruko A. Miyazawa, Kodai Wada, Akira Yasuhara

Dabkowski and Sahi defined an invariant of a link in the $3$-sphere, which is preserved under $4$-moves. This invariant is a quotient of the fundamental group of the complement of the link. It is generally difficult to distinguish the Dabkowski-Sahi invariants of given links. In this paper, we give a necessary condition for the existence of an isomorphism be

Pokou Nagacy, Justin Feuto

We generalize Wiener amalgam spaces by using Dunkl translation instead of the classical one, and we give some relationship between these spaces, Dunkl-Lebesgue spaces and Dunkl-Morrey spaces. We prove that the Hardy-Litlewood maximal function associated with the Dunkl operators is bounded on these generalized Dunkl-Morrey spaces.

Allan L. Alinea, Takahiro Kubota

Primordial cosmological perturbations are the seeds that were cultivated by inflation and the succeeding dynamical processes, eventually leading to the current Universe. In this work, we investigate the behavior of the gauge-invariant scalar and tensor perturbations under the general extended disformal transformation, namely, $g_{\mu\nu} \rightarrow A(X,Y,Z)

Elad Michael, Tony A. Wood, Chris Manzie, Iman Shames

In this paper, the following question is addressed: given a linear assignment problem, how much can the all of the individual assignment weights be perturbed without changing the optimal assignment? The extension of results involving perturbations in just one edge or one row/column are presented. Algorithms for the derivation of these bounds are provided. We

Sourav Das, Nitin Awathare, Ling Ren, Vinay Joseph Ribeiro

Proof-of-Work~(PoW) based blockchains typically allocate only a tiny fraction (e.g., less than 1% for Ethereum) of the average interarrival time~($\mathbb{I}$) between blocks for validating transactions. A trivial increase in validation time~($\tau$) introduces the popularly known Verifier's Dilemma, and as we demonstrate, causes more forking and increases u

Pertti Mattila

We give conditions on a general family $P_{\lambda}:\R^n\to\R^m, \lambda \in \Lambda,$ of orthogonal projections which guarantee that the Hausdorff dimension formula $\dim A\cap P_{\lambda}^{-1}\{u\}=s-m$ holds generically for measurable sets $A\subset\Rn$ with positive and finite $s$-dimensional Hausdorff measure, $s>m$, and with positive lower density. As

Hadi Mardani Kamali, Kimia Zamiri Azar, Houman Homayoun, Avesta Sasan

In this paper, we introduce SCRAMBLE, as a novel logic locking solution for sequential circuits while the access to the scan chain is restricted. The SCRAMBLE could be used to lock an FSM by hiding its state transition graph (STG) among a large number of key-controlled false transitions. Also, it could be used to lock sequential circuits (sequential datapath

Mircea Sofonea, Domingo A. Tarzia

We consider an optimal control problem $\cQ$ governed by an elliptic quasivariational inequality with unilateral constraints. The existence of optimal pairs of the problem is a well known result, see \cite{SS}, for instance. We associate to $\cQ$ a new optimal control problem $\wQ$, obtained by perturbing the state inequality (including the set of constraint

Anne Lauscher, Olga Majewska, Leonardo F. R. Ribeiro, Iryna Gurevych

Following the major success of neural language models (LMs) such as BERT or GPT-2 on a variety of language understanding tasks, recent work focused on injecting (structured) knowledge from external resources into these models. While on the one hand, joint pretraining (i.e., training from scratch, adding objectives based on external knowledge to the primary L

Hossein Safi, Akbar Dargahi, Julian Cheng, Majid Safari

Integrating high altitude platforms (HAPs) and free-space optical (FSO) communications is a promising solution to establish high data rate aerial links for the next-generation wireless networks. However, practical limitations such as pointing errors and angle-of-arrival (AOA) fluctuations of the optical beam due to the orientation deviations of hovering HAPs

Saverio Ranciati, Alberto Roverato, Alessandra Luati

Neuroimaging is the growing area of neuroscience devoted to produce data with the goal of capturing processes and dynamics of the human brain. We consider the problem of inferring the brain connectivity network from time dependent functional magnetic resonance imaging (fMRI) scans. To this aim we propose the symmetric graphical lasso, a penalized likelihood

Theodora Bourni, Julie Clutterbuck, Xuan Hien Nguyen, Alina Stancu

For the Laplace operator with Dirichlet boundary conditions on convex domains in $\mathbb H^n$, $n\geq 2$, we prove that the product of the fundamental gap with the square of the diameter can be arbitrarily small for domains of any diameter.

Farrukh A. Chishtie

In this work, we explicate a new approach for eliminating renormalization scale and scheme (RSS) dependence in observables. We develop this approach by matching RSS dependent observables (such as cross-sections and decay rates) to a theory which is independent of both these forms of dependencies. We term the fundamental basis behind this approach as the prin

K. Beauvois, N. Qureshi, R. Tsunoda, Y. Hirose

We report the magnetic structure of nominally 10% Cd-doped CeIrIn$_5$, CeIr(In$_{0.9}$Cd$_{0.1}$)$_5$, determined by elastic neutron scattering. Magnetic intensity was observed only at the ordering wave vector $Q_{AF} = (1/2,1/2,1/2)$, commensurate with the crystal lattice. A staggered moment of 0.47(3)$\mu_B$ at 1.8 K resides on the Ce ion. The magnetic mom

V. V. Brovkin, A. A. Kon'kov

We obtain necessary and sufficient existence conditions for solutions of the boundary value problem $$ \Delta_p u = f \quad \mbox{on } M, \quad \left. \left| \nabla u \right|^{p - 2} \frac{\partial u}{\partial \nu} \right|_{ \partial M } = h, $$ where $p > 1$ is a real number, $M$ is a connected oriented complete Riemannian manifold with boundary, and $\nu$

Zhongxu Hu, Yang Xing, Chen Lv, Peng Hang

Head pose estimation is a crucial problem for many tasks, such as driver attention, fatigue detection, and human behaviour analysis. It is well known that neural networks are better at handling classification problems than regression problems. It is an extremely nonlinear process to let the network output the angle value directly for optimization learning, a

Joonho Lee, David R. Reichman

We explore the use of the stochastic resolution-of-the-identity (sRI) with the phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC) method. sRI is combined with four existing local energy evaluation strategies in ph-AFQMC, namely (1) the half-rotated electron repulsion integral tensor (HR), (2) Cholesky decomposition (CD), (3) tensor hypercontraction (TH

Hongxin Wei, Wei Feng, Yunfei Chen, Cheng-Xiang Wang

Due to the rapid development of Internet of Things (IoT), a massive number of devices are connected to the Internet. For these distributed devices in IoT networks, how to ensure their security and privacy becomes a significant challenge. The blockchain technology provides a promising solution to protect the data integrity, provenance, privacy, and consistenc

Murong Ma, Haiwei Wu, Xuyang Wang, Lin Yang

In this paper, we propose a deep convolutional neural network-based acoustic word embedding system on code-switching query by example spoken term detection. Different from previous configurations, we combine audio data in two languages for training instead of only using one single language. We transform the acoustic features of keyword templates and searchin

Jacob Swambo, Spencer Hommel, Bob McElrath, Bryan Bishop

A bitcoin \textit{covenant} is a mechanism to enforce conditions on future bitcoin transactions. A bitcoin \textit{vault} is a specific type of covenant transaction that enforces a time-lock on the transfer of control of funds to a hot wallet, but enables an immediate transfer of funds into a deep cold recovery wallet. This paper demonstrates how to integrat

Bin Yuan, Ludovico Cademartiri

Our understanding of the growth of crystals is dominated by the classical description according to which individual atoms or molecules, driven by supersaturation, add to crystal facets. As a result, the growth of hard matter is still mostly considered to be fundamentally incomparable to the growth of soft matter, like polymers or liquids. By a combination of

Irina Blazhievska

Thesis is devoted to the application of cumulant analysis in the estimation of impulse response functions for continuous time-invariant linear systems, including systems with inner noises. The main assumption of the work is the second-order integration of the impulse response function. Our study deals with cumulant analysis of sample cross-correlograms betwe

Vitalii Konarovskyi

We prove the existence of a sticky-reflected solution to the heat equation on the spatial interval $[0,1]$ driven by colored noise. The process can be interpreted as an infinite-dimensional analog of the sticky-reflected Brownian motion on the real line, but now the solution obeys the usual stochastic heat equation except points where it reaches zero. At zer

Bartosz Zieliński, Agnieszka Sroka-Oleksiak, Dawid Rymarczyk, Adam Piekarczyk

Preliminary diagnosis of fungal infections can rely on microscopic examination. However, in many cases, it does not allow unambiguous identification of the species by microbiologist due to their visual similarity. Therefore, it is usually necessary to use additional biochemical tests. That involves additional costs and extends the identification process up t

Sergi Arias, Salvador Rodríguez-López

In this paper we establish mapping properties of bilinear Coifman-Meyer multipliers acting on the product spaces $H^1(\mathbb{R}^n)\times\mathrm{bmo}(\mathbb{R}^n)$ and $L^p(\mathbb{R}^n)\times\mathrm{bmo}(\mathbb{R}^n)$, with $1<p<\infty$. As application of these results, we obtain some related Kato-Ponce-type inequalities involving the endpoint space $\mat

Junjie Liang, Yanting Wu, Dongkuan Xu, Vasant Honavar

Gaussian processes offer an attractive framework for predictive modeling from longitudinal data, i.e., irregularly sampled, sparse observations from a set of individuals over time. However, such methods have two key shortcomings: (i) They rely on ad hoc heuristics or expensive trial and error to choose the effective kernels, and (ii) They fail to handle mult

Shang-Yi Chuang, Yu Tsao, Chen-Chou Lo, Hsin-Min Wang

Previous studies have confirmed the effectiveness of incorporating visual information into speech enhancement (SE) systems. Despite improved denoising performance, two problems may be encountered when implementing an audio-visual SE (AVSE) system: (1) additional processing costs are incurred to incorporate visual input and (2) the use of face or lip images m

Jiajing Wan, Xinting Huang

This paper presents our strategies in SemEval 2020 Task 4: Commonsense Validation and Explanation. We propose a novel way to search for evidence and choose the different large-scale pre-trained models as the backbone for three subtasks. The results show that our evidence-searching approach improves model performance on commonsense explanation task. Our team

Seshu Vardhan, Bharat Z. Dholakiya, Suban K Sahoo

Objective: Total 186 biologically important phenylpropanoids and polyketides compounds from different Indian medicinal plants and dietary sources were screened to filter potential compounds that bind at the active site of the therapeutic target proteins of SARS-CoV-2. Method: The molecular docking studies were carried out by using the Autodock Vina. The in s

Alexander L. Gavrilyuk, Roman Nedela, Ilia Ponomarenko

A graph is said to be distance-hereditary if the distance function in every connected induced subgraph is the same as in the graph itself. We prove that the ordinary Weisfeiler-Leman algorithm correctly tests the isomorphism of any two graphs if one of them is distance-hereditary; more precisely, the Weisfeiler-Leman dimension of the class of finite distance

Y. A. Ovchenkov, D. A. Chareev, D. E. Presnov, I. G. Puzanova

We have investigated the elastoresistance of two FeSe${}_{1-x}$Te${}_{x}$ (x about 0.4 - 0.5) compounds that have a close chemical composition but differ significantly in electronic properties. The first compound has a negative temperature coefficient of resistance and does not show any phase transitions other than superconducting. The elastoresistance of th

Matthias Kirchhart, Erick Schulz

We consider the problem of recovering the divergence-free velocity field ${\mathbf U}\in\mathbf{L}^2(\Omega)$ of a given vorticity ${\mathbf F}=\mathrm{curl}\,{\mathbf U}$ on a bounded Lipschitz domain $\Omega\subset\mathbb{R}^3$. To that end, we solve the "div-curl problem" for a given ${\mathbf F}\in{\mathbf H}^{-1}(\Omega)$. The solution is expressed in t

Suman Banerjee, Mamata Jenamani, Dilip Kumar Pratihar

In this paper, we study the Budgeted Influence Maximization with Delay Problem, for which the number of literature are limited. We propose an approximate marginal spread computation\mbox{-}based approach for solving this problem. The proposed methodology has been implemented with three benchmark social network datasets and the obtained results are compared w

Huiping Pan

We show that every $\mathbb R$-linear surjective isometry between the cotangent spaces to the Teichm\"uller space equipped with the Thurston norm is induced by some isometry between the underlying hyperbolic surfaces, which is an analogue of Royden's theorem concerning the Teichm\"uller metric.

Pere Masjuan, Pablo Roig, Pablo Sanchez-Puertas

We revisit well-known short-distance constraints relating the hadronic light-by light Green's function to the $\langle VVA \rangle$ one, that have been a subject of debate over the past years in the context of the muon $(g-2)$. Specifically, we identify a relation among the longitudinal and transverse degrees of freedom that is enforced by the axial anomaly

Chi-Chang Lee, Yu-Chen Lin, Hsuan-Tien Lin, Hsin-Min Wang

Numerous noise adaptation techniques have been proposed to fine-tune deep-learning models in speech enhancement (SE) for mismatched noise environments. Nevertheless, adaptation to a new environment may lead to catastrophic forgetting of the previously learned environments. The catastrophic forgetting issue degrades the performance of SE in real-world embedde

David Z. Li, Marco T. Manzoni, Darrick E. Chang

Systems consisting of cold atoms trapped near photonic crystal waveguides have recently emerged as an exciting platform for quantum atom-light interfaces. Such a system enables realization of tunable long-range interactions between internal states of atoms (spins), mediated by guided photons. Currently, experimental platforms are still limited by low filling

Eric Goles, Pedro Montealegre, Martín Ríos-Wilson, Guillaume Theyssier

An automata network is a network of entities, each holding a state from a finite set and evolving according to a local update rule which depends only on its neighbors in the network's graph. It is freezing if there is an order on states such that the state evolution of any node is non-decreasing in any orbit. They are commonly used to model epidemic propagat

Zhensu Sun, Yan Liu, Ziming Cheng, Chen Yang

Third-party libraries are crucial to the development of software projects. To get suitable libraries, developers need to search through millions of libraries by filtering, evaluating, and comparing. The vast number of libraries places a barrier for programmers to locate appropriate ones. To help developers, researchers have proposed automated approaches to r

GeunHyeong Lee, Soo-Yong Shin

As deep learning have been applied in a clinical context, privacy concerns have increased because of the collection and processing of a large amount of personal data. Recently, federated learning (FL) has been suggested to protect personal privacy because it does not centralize data during the training phase. In this study, we assessed the reliability and pe

Luís H. Reis, Saulo H. S. Silva, Emmanuel Pereira

We consider the accurate investigation of the energy current and its components, heat and work, in some boundary driven quantum spin systems. The expressions for the currents, as well as the associated Lindblad master equation, are obtained via a repeated interaction scheme. We consider small systems in order to analytically compute the steady distribution t

Saint-Cyr E. R. Koyaguerebo-Imé, Yves Bourgault

This paper provides a new approach to derive various arbitrary high order finite difference formulae for the numerical differentiation of analytic functions. In this approach, various first and second order formulae for the numerical approximation of analytic functions are given with error terms explicitly expanded as Taylor series of the analytic function.

Tianhao Wang, Joann Qiongna Chen, Zhikun Zhang, Dong Su

In this paper, we study the problem of publishing a stream of real-valued data satisfying differential privacy (DP). One major challenge is that the maximal possible value can be quite large; thus it is necessary to estimate a threshold so that numbers above it are truncated to reduce the amount of noise that is required to all the data. The estimation must

Chaohua Jia

Let $p$ be a sufficiently large prime number, $r$ be any given positive integer. Suppose that $a_1,\,\dots,\,a_r$ are pairwise distinct and not zero modulo $p$. Let $N(a_1,\,\dots,\,a_r;\,p)$ denote the number of $\alpha_1,\,\dots,\,\alpha_r,\,\beta$, which are primitive roots modulo $p$, such that $\alpha_1+\beta\equiv a_1,\,\dots,\,\alpha_r+\beta\equiv a_r

Valeriy G. Bardakov, Tatyana A. Kozlovskaya

In the present paper we study the singular pure braid group $SP_{n}$ for $n=2, 3$. We find generators, defining relations and the algebraical structure of these groups. In particular, we prove that $SP_{3}$ is a semi-direct product $SP_{3} = \widetilde{V}_3 \leftthreetimes \mathbb{Z}$, where $\widetilde{V}_3$ is an HNN-extension with base group $\mathbb{Z}^2

Sayantan Choudhury

The out-of-time-ordered correlation (OTOC) function is an important new probe in quantum field theory which is treated as a significant measure of random quantum correlations. In this paper, with the slogan "Cosmology meets Condensed Matter Physics" we demonstrate a formalism using which for the first time we compute the Cosmological OTOC during the stochast

Vladimir Dvorkin, Jalal Kazempour, Pierre Pinson

We develop a stochastic equilibrium model for an electricity market with asymmetric renewable energy forecasts. In our setting, market participants optimize their profits using public information about a conditional expectation of energy production but use private information about the forecast error distribution. This information is given in the form of sam

Ahmet Çevik, Selçuk Topal

We introduce a novel set-intersection operator called `most-intersection' based on the logical quantifier `most', via natural density of countable sets, to be used in determining the majority characteristic of a given countable (possibly infinite) collection of systems. The new operator determines, based on the natural density, the elements which are in `mos

Dhruv Sharma, Jean-Philippe Bouchaud, Marco Tarzia, Francesco Zamponi

We introduce a prototype agent-based model of the macroeconomy, with budgetary constraints at its core. The model is related to a class of constraint satisfaction problems (CSPs), which has been thoroughly investigated in computer science. The CSP paradigm allows us to propose an alternative price-setting mechanism: given agents' preferences and budgets, wha

M. Romero-Bastida, Juan M. Lopez

We study the performance of an electromechanical harmonic oscillator chain as an energy harvester to extract power from finite-bandwidth ambient random vibrations, which are modelled by colored noise. The proposed device is numerically simulated and its performance assessed by means of the net electrical power generated and its efficiency in converting the e

Jitender Singh Virk, Deepti R. Bathula

Limited availability of annotated medical imaging data poses a challenge for deep learning algorithms. Although transfer learning minimizes this hurdle in general, knowledge transfer across disparate domains is shown to be less effective. On the other hand, smaller architectures were found to be more compelling in learning better features. Consequently, we p

Marie-Liesse Cauwet, Olivier Teytaud

We study a test-based population size adaptation (TBPSA) method, inspired from population control, in the noise-free multimodal case. In the noisy setting, TBPSA usually recommends, at the end of the run, the center of the Gaussian as an approximation of the optimum. We show that combined with a more naive recommendation, namely recommending the visited poin

Toshio Nagano, Naoya Miyazaki

In this paper, we first generalize the Fresnel integrals by changing of a path for integration in the proof of the Fresnel integrals by Cauchy's integral theorem. Next, according to oscillatory integral, we also obtain further generalization of the extended Fresnel integrals. Moreover by using this result, we have an asymptotic expansion of an oscillatory in

Viacheslav V. Saenko

The integral representation of the two-parameter Mittag-Leffler function $E_{\rho,\mu}(z)$ is considered in the paper that expresses its value in terms of the contour integral. For this integral representation, the transition is made from integration over a complex variable to integration over real variables. It is shown that as a result of such a transition

Kim P. Wabersich, Melanie N. Zeilinger

Tight performance specifications in combination with operational constraints make model predictive control (MPC) the method of choice in various industries. As the performance of an MPC controller depends on a sufficiently accurate objective and prediction model of the process, a significant effort in the MPC design procedure is dedicated to modeling and ide

Paulina Pankowska, Daniel L. Oberski

Clustering consists of a popular set of techniques used to separate data into interesting groups for further analysis. Many data sources on which clustering is performed are well-known to contain random and systematic measurement errors. Such errors may adversely affect clustering. While several techniques have been developed to deal with this problem, littl

Sean Oughton, William H. Matthaeus

A discussion of the advantages and limitations of the concept of critical balance, as employed in turbulence phenomenologies, is presented. The incompressible magnetohydrodynamic (MHD) case is a particular focus. The discussion emphasizes the status of the original Goldreich & Sridhar (1995) critical balance conjecture relative to related theoretical issues

Yu Zeng, Zhe Lin, Jimei Yang, Jianming Zhang

Existing image inpainting methods often produce artifacts when dealing with large holes in real applications. To address this challenge, we propose an iterative inpainting method with a feedback mechanism. Specifically, we introduce a deep generative model which not only outputs an inpainting result but also a corresponding confidence map. Using this map as

Virginia Aglietti, Xiaoyu Lu, Andrei Paleyes, Javier González

This paper studies the problem of globally optimizing a variable of interest that is part of a causal model in which a sequence of interventions can be performed. This problem arises in biology, operational research, communications and, more generally, in all fields where the goal is to optimize an output metric of a system of interconnected nodes. Our appro

Zhouyang Ge, Luca Brandt

We describe and summarize a class of minimal numerical models emerged from recent development of simulation methods for dense particle suspensions in overdamped linear flows. The main ingredients include (i) a frame-invariant, short-range lubrication model for spherical particles, and (ii) a soft-core, stick/slide frictional contact model activated when part

Shi Jin, Lei Li

The Random Batch Method proposed in our previous work [Jin et al., J. Comput. Phys., 400(1), 2020] is not only a numerical method for interacting particle systems and its mean-field limit, but also can be viewed as a model of particle system in which particles interact, at discrete time, with randomly selected mini-batch of particles. In this paper we invest

Mario Barrantes, Benedikt Herudek, Richard Wang

We apply the Adversarial NLI dataset to train the NLI model and show that the model has the potential to enhance factual correctness in abstract summarization. We follow the work of Falke et al. (2019), which rank multiple generated summaries based on the entailment probabilities between an source document and summaries and select the summary that has the hi

Rico Krueger, Prateek Bansal, Prasad Buddhavarapu

The identification of accident hot spots is a central task of road safety management. Bayesian count data models have emerged as the workhorse method for producing probabilistic rankings of hazardous sites in road networks. Typically, these methods assume simple linear link function specifications, which, however, limit the predictive power of a model. Furth

Kun Xie, Sylvain Hallé

A bitmap is a data structure designed to compactly represent sets of integers; it provides very fast operations for querying and manipulating such sets, exploiting bit-level parallelism. In this paper, we describe a technique for the offline verification of arbitrary expressions of Linear Temporal Logic using bitmap manipulation. An event trace is first prep

Raghavendra Addanki, Shiva Prasad Kasiviswanathan, Andrew McGregor, Cameron Musco

We consider recovering a causal graph in presence of latent variables, where we seek to minimize the cost of interventions used in the recovery process. We consider two intervention cost models: (1) a linear cost model where the cost of an intervention on a subset of variables has a linear form, and (2) an identity cost model where the cost of an interventio

Marcin Plata, Piotr Syga

Watermarking is an operation of embedding an information into an image in a way that allows to identify ownership of the image despite applying some distortions on it. In this paper, we presented a novel end-to-end solution for embedding and recovering the watermark in the digital image using convolutional neural networks. The method is based on spreading th

Huangxin Chen, Amiya K. Pani, Weifeng Qiu

In this paper, a new mixed finite element scheme using element-wise stabilization is introduced for the biharmonic equation with variable coefficient on Lipschitz polyhedral domains. The proposed scheme doesn't involve any integration along mesh interfaces. The gradient of the solution is approximated by $H({\rm div})$-conforming $BDM_{k+1}$ element or vecto

S. A. Buterin, A. E. Choque-Rivero, M. A. Kuznetsova

We consider the irregular (in the Birkhoff and even the Stone sense) transmission eigenvalue problem of the form $-y''+q(x)y=\rho^2 y,$ $y(0)=y(1)\cos\rho a-y'(1)\rho^{-1}\sin\rho a=0.$ The main focus is on the ''most'' irregular case $a=1,$ which is important for applications. The uniqueness questions of recovering the potential $q(x)$ from transmission eig

Weijun Fang, Jun Zhang, Shu-Tao Xia1, Fang-Wei Fu

A linear code is called an MDS self-dual code if it is both an MDS code and a self-dual code with respect to the Euclidean inner product. The parameters of such codes are completely determined by the code length. In this paper, we consider new constructions of MDS self-dual codes via generalized Reed-Solomon (GRS) codes and their extended codes. The critical

Yan-Xia Ren, Renming Song, Zhenyao Sun, Jianjie Zhao

This paper is a continuation of our recent paper (Elect. J. Probab. 24 (2019), no. 141) and is devoted to the asymptotic behavior of a class of supercritical super Ornstein-Uhlenbeck processes $(X_t)_{t\geq 0}$ with branching mechanisms of infinite second moment. In the aforementioned paper, we proved stable central limit theorems for $X_t(f) $ for some func

Julian Skirzyński, Frederic Becker, Falk Lieder

When making decisions, people often overlook critical information or are overly swayed by irrelevant information. A common approach to mitigate these biases is to provide decision-makers, especially professionals such as medical doctors, with decision aids, such as decision trees and flowcharts. Designing effective decision aids is a difficult problem. We pr

Jianfeng Liu, Feiyang Pan, Ling Luo

A chatbot that converses like a human should be goal-oriented (i.e., be purposeful in conversation), which is beyond language generation. However, existing dialogue systems often heavily rely on cumbersome hand-crafted rules or costly labelled datasets to reach the goals. In this paper, we propose Goal-oriented Chatbots (GoChat), a framework for end-to-end t

Muyang Liu, Ke Li, Tao Chen

Security is unarguably the most serious concern for Web applications, to which SQL injection (SQLi) attack is one of the most devastating attacks. Automatically testing SQLi vulnerabilities is of ultimate importance, yet is unfortunately far from trivial to implement. This is because the existence of a huge, or potentially infinite, number of variants and se

Thomas Simons, Dganit Meidan, Alessandro Romito

We examine the heat and charge transport of a driven topological superconductor. Our particular system of interest consists of a Y-junction of topological superconducting wires, hosting non-Abelian Majorana zero modes at their edges. The system is contacted to two leads which act as continuous detectors of the system state. We calculate, via a scattering mat

T. Pailas, N. Dimakis, Andronikos Paliathanasis, Petros A. Terzis

We find the symmetry generators for the Friedman equations emanating from a perfect fluid source, in the presence of a cosmological constant term. The relevant dynamics is seen to be governed by two coupled, first order ordinary differential equations, the continuity and the quadratic constraint equation. Arbitrary functions appear in the components of the s

Oluwasegun Ojo, Augusto García-Agundez, Benjamin Girault, Harold Hernández

The world is suffering from a pandemic called COVID-19, caused by the SARS-CoV-2 virus. National governments have problems evaluating the reach of the epidemic, due to having limited resources and tests at their disposal. This problem is especially acute in low and middle-income countries (LMICs). Hence, any simple, cheap and flexible means of evaluating the

Simon C. Eriksson, Rubén Asensio Torres, Markus Janson, Yuhiko Aoyama

Context. Intrinsic H$\alpha$ emission can be advantageously used to detect substellar companions because it improves contrasts in direct imaging. Characterising this emission from accreting exoplanets allows for the testing of planet formation theories. Aims. We characterise the young circumbinary planetary mass companion 2MASS J01033563-5515561 (AB)b (Delor

Angelika Skarysz, Dahlia Salman, Michael Eddleston, Martin Sykora

Volatile organic compounds (VOCs) in human breath can reveal a large spectrum of health conditions and can be used for fast, accurate and non-invasive diagnostics. Gas chromatography-mass spectrometry (GC-MS) is used to measure VOCs, but its application is limited by expert-driven data analysis that is time-consuming, subjective and may introduce errors. We

Le Wu, Yonghui Yang, Lei Chen, Defu Lian

With the increasing availability of videos, how to edit them and present the most interesting parts to users, i.e., video highlight, has become an urgent need with many broad applications. As users'visual preferences are subjective and vary from person to person, previous generalized video highlight extraction models fail to tailor to users' unique preferenc

Nikos Voskarides, Dan Li, Pengjie Ren, Evangelos Kanoulas

In this work we focus on multi-turn passage retrieval as a crucial component of conversational search. One of the key challenges in multi-turn passage retrieval comes from the fact that the current turn query is often underspecified due to zero anaphora, topic change, or topic return. Context from the conversational history can be used to arrive at a better

Nikolaj Bittner, Denis Golež, Martin Eckstein, Philipp Werner

We theoretically investigate the effects of the lattice geometry on the nonequilibrium dynamics of photo-excited carriers in a half-filled two-dimensional Hubbard model. Using a nonequilibrium generalization of the dynamical cluster approximation, we compare the relaxation dynamics in lattices which interpolate between the triangular lattice and square latti

Ming Gong, Ming Lu, Haiwen Liu, Hua Jiang

Inside a three-dimensional strong topological insulator, a tube with $h/2e$ magnetic flux carries a pair of protected one-dimensional linear fermionic modes. This phenomenon is known as the "wormhole effect". In this work, we find that the "wormhole effect", as a unique degree of freedom, introduces exotic transport phenomena and thus manipulates the transpo

Thibaut Le Gouic, Jean-Michel Loubes, Philippe Rigollet

In the context of regression, we consider the fundamental question of making an estimator fair while preserving its prediction accuracy as much as possible. To that end, we define its projection to fairness as its closest fair estimator in a sense that reflects prediction accuracy. Our methodology leverages tools from optimal transport to construct efficient

Yanguang Chen

The rank-size distribution of cities follows Zipf's law, and the Zipf scaling exponent often tends to a constant 1. This seems to be a general rule. However, a recent numerical experiment shows that there exists a contradiction between the Zipf exponent 1 and high urbanization level in a large population country. In this paper, mathematical modeling, computa

Daniel Gabric, Narad Rampersad, Jeffrey Shallit

We prove an inequality for the number of periods in a word x in terms of the length of x and its initial critical exponent. Next, we characterize all periods of the length-n prefix of a characteristic Sturmian word in terms of the lazy Ostrowski representation of n, and use this result to show that our inequality is tight for infinitely many words x. We prop

M. Laura Urquiza, Xavier Cartoixà

We have studied the finite bias transport properties of a 2H-1T' MoS$_2$ lateral metal-semiconductor (M-S) junction by non-equilibrium Green's functions calculations, aimed at contacting the 2D channel in a field effect transistor. Our results indicate that (a) despite the fundamentally different electrostatics of line and planar dipoles, the Schottky barrie

Yaxin Shi, Yuangang Pan, Donna Xu, Ivor W. Tsang

Multi-view alignment, achieving one-to-one correspondence of multi-view inputs, is critical in many real-world multi-view applications, especially for cross-view data analysis problems. Recently, an increasing number of works study this alignment problem with Canonical Correlation Analysis (CCA). However, existing CCA models are prone to misalign the multipl

Neslihan Bayramoglu, Miika T. Nieminen, Simo Saarakkala

Knee osteoarthritis (OA) is very common progressive and degenerative musculoskeletal disease worldwide creates a heavy burden on patients with reduced quality of life and also on society due to financial impact. Therefore, any attempt to reduce the burden of the disease could help both patients and society. In this study, we propose a fully automated novel m

Hanxun Xu, Lixin Yan, Yingchao Du, Wenhui Huang

Terahertz (THz)-driven acceleration has recently emerged as a new route for delivering ultrashort bright electron beams efficiently, reliably, and in a compact setup. Many THz-driven acceleration related working schemes and key technologies have been successfully demonstrated and are continuously being improved to new limits. However, the achieved accelerati

Yue Chen, Da-Zhu Ma, Fang Xia

A pure two-body problem has seven integrals including the Kepler energy, the Laplace vector, and the angular momentum vector. However, only five of them are independent. When the five independent integrals are preserved, the two other dependent integrals are naturally preserved from a theoretical viewpoint; but they may not be either from a numerical computa

Seid Miad Zandavi, Taha Hossein Rashidi, Fatemeh Vafaee

To accurately predict the regional spread of Covid-19 infection, this study proposes a novel hybrid model which combines a Long short-term memory (LSTM) artificial recurrent neural network with dynamic behavioral models. Several factors and control strategies affect the virus spread, and the uncertainty arisen from confounding variables underlying the spread

Quentin Gueuning, Antony Brown, Christophe Craeye, Eloy de Lera Acedo

In this paper, we propose a beamforming method for the calibration of the direction-independent gain of the analog chains of aperture arrays. The gain estimates are obtained by cross-correlating the output voltage of each antenna with a voltage beamformed using the other antennas of the array. When the beamforming weights are equal to the average cross-corre

Andrei Cramariuc, Aleksandar Petrov, Rohit Suri, Mayank Mittal

Self-diagnosis and self-repair are some of the key challenges in deploying robotic platforms for long-term real-world applications. One of the issues that can occur to a robot is miscalibration of its sensors due to aging, environmental transients, or external disturbances. Precise calibration lies at the core of a variety of applications, due to the need to