August 2022 arXiv papers — page 5

Pooja Bhattacharjee

With the growing interest in indirect detection for dark matter signature, the thesis aims to investigate the signal originating from the self-annihilation of dark matter candidates. The methods for targeting the dark matter signal are two-fold, on one hand, we explore the gamma rays resulting from dark matter particles. On the other hand, we focus on comple

Rodrigue Lelotte

In this paper, we study the multimarginal optimal transport with Coulomb cost, also known in the physics literature as the Strictly-Correlated Electrons (SCE) functional. We prove that the dual Kantorovich potential is an electrostatic potential induced by an external charge density, which we call the dual charge. We study its properties and use it to discre

Tim Becker, Jens Teiser, Teresa Jardiel, Marco Peiteado

Emission of dust up to a few micrometer in size by impacts of sand grains during saltation is thought to be one source of dust within the Martian atmosphere. To study this dust fraction, we carried out laboratory impact experiments. Small numbers of particles of about 200\textmu{}m in diameter impacted a simulated Martian soil (bimodal \textit{Mars Global Si

Phoebe M Asquith, Hisham Ihshaish

The classification of electroencephalography (EEG) signals is useful in a wide range of applications such as seizure detection/prediction, motor imagery classification, emotion classification and drug effects diagnosis, amongst others. With the large number of EEG channels acquired, it has become vital that efficient data-reduction methods are developed, wit

Louis Vaslin, Samuel Calvet, Vincent Barra, Julien Donini

The BumpHunter algorithm is widely used in the search for new particles in High Energy Physics analysis. This algorithm offers the advantage of evaluating the local and global p-values of a localized deviation in the observed data without making any hypothesis on the supposed signal. The increasing popularity of the Python programming language motivated the

Sylvain N. Breton, Allan Sacha Brun, Rafael A. García

There are no strong constraints placed thus far on the amplitude of internal gravity waves (IGWs) that are stochastically excited in the radiative interiors of solar-type stars. Late F-type stars have relatively thin convective envelopes with fast convective flows and tend to be fast rotators compared to solar-type stars of later spectral types. These two el

Yair Glasner, Waltraud Lederle

Let $\Gamma$ be a countable group and $\mathrm{Sub}(\Gamma)$ its Chabauty space, namely the compact $\Gamma$-space consisting of all subgroups of $\Gamma$. We call a subgroup $\Delta \in \mathrm{Sub}(\Gamma)$ a boomerang subgroup if for every $\gamma \in \Gamma$, $\gamma^{n_i} \Delta \gamma^{-n_i} \rightarrow \Delta$ for some subsequence $\{n_i \} \subset \m

H. Hushnud

ALICE is a general purpose experiment designed to investigate nucleus-nucleus collisions at the Large Hadron Collider (LHC), located at CERN. The ALICE detector is optimized for the reconstruction of quarkonia through the dimuon decay channel at foward rapidity as well as the dielectron decay channel at midrapidity. In this contribution, quarkonium measureme

Umang Goenka, Param Patil, Kush Gosalia, Aaryan Jagetia

Classifying Electroencephalogram(EEG) signals helps in understanding Brain-Computer Interface (BCI). EEG signals are vital in studying how the human mind functions. In this paper, we have used an Arithmetic Calculation dataset consisting of Before Calculation Signals (BCS) and During Calculation Signals (DCS). The dataset consisted of 36 participants. In ord

Margot Boughelilba, Anita Reimer, Lukas Merten

The low-luminosity Active Galactic Nuclei M87, archetype of Fanaroff-Riley I radio-galaxies, was observed in a historically quiet state in 2017. While one-zone leptonic jet models alone cannot explain the core radio-to-gamma-ray spectrum, we explore a hybrid jet-disc scenario. In this work, we model the overall spectral energy distribution of M87's core with

Gyula Klima

In this talk, I argue that there are certain pragmatic features of natural language (that I will call 'productivity' and 'malleability', on top of syntactical generativity and semantical compositionality), which are not only hard, but even impossible to capture in an artificial language used by an AI system, and the reason for this is to be found in certain

Ori Roth

Grigore showed that Java generics are Turing complete by describing a reduction from Turing machines to Java subtyping. We apply Grigore's algorithm to Python type hints and deduce that they are Turing complete. In addition, we present an alternative reduction in which the Turing machines are simulated in real time, resulting in significantly lower compilati

Tao Shen, Xiubo Geng, Chongyang Tao, Can Xu

In large-scale retrieval, the lexicon-weighting paradigm, learning weighted sparse representations in vocabulary space, has shown promising results with high quality and low latency. Despite it deeply exploiting the lexicon-representing capability of pre-trained language models, a crucial gap remains between language modeling and lexicon-weighting retrieval

Simone Di Marino, Lorenzo Portinale, Emanuela Radici

We study the discretization of generalized Wasserstein distances with nonlinear mobilities on the real line via suitable discrete metrics on the cone of N ordered particles, a setting which naturally appears in the framework of deterministic particle approximation of partial differential equations. In particular, we provide a $\Gamma$-convergence result for

Paolo Gazzaneo, Tommaso Maria Mazzocchi, Jan Lotze, Enrico Arrigoni

We study a model for photovoltaic energy collection consisting of a Mott insulating layer in presence of acoustic phonons, coupled to two wide-band fermion leads at different chemical potentials and driven into a nonequilibrium steady state by a periodic electric field. We treat electron correlations with nonequilibrium dynamical mean-field theory (DMFT) usi

Zhi Ji, Jia Tu, Xinrong Guan, Wendong Yang

In this paper, we study an unmanned aerial vehicle (UAV) enabled data collection system, where an intelligent reflecting surface (IRS) is deployed to assist in the communication from a cluster of Internet-of-Things (IoT) devices to a UAV in the presence of a jammer. We aim to improve the energy efficiency (EE) via the joint design of UAV trajectory, IRS pass

Tom Dyer, Jordan Smith, Gaetan Dissez, Nicole Tay

Purpose: Artificial intelligence (AI) solutions for medical diagnosis require thorough evaluation to demonstrate that performance is maintained for all patient sub-groups and to ensure that proposed improvements in care will be delivered equitably. This study evaluates the robustness of an AI solution for the diagnosis of normal chest X-rays (CXRs) by compar

Filippo Carnovalini, Alessandro Pelizzo, Antonio Rodà, Sergio Canazza

Kansei models were used to study the connotative meaning of music. In multimedia and mixed reality, automatically generated melodies are increasingly being used. It is important to consider whether and what feelings are communicated by this music. Evaluation of computer-generated melodies is not a trivial task. Considered the difficulty of defining useful qu

Debbie Lim, Patrick Rebentrost

Portfolio optimization plays a central role in finance to obtain optimal portfolio allocations that aim to achieve certain investment goals. Over the years, many works have investigated different variants of portfolio optimization. Portfolio optimization also provides a rich area to study the application of quantum computers to obtain advantages over classic

Filippo Carnovalini, Antonio Rodà, Paolo Caneva

Making music with other people is a social activity as well as an artistic one. Music therapists take advantage of the social aspects of music to obtain benefits for the patients, interacting with them musically, but this activity requires an high level of expertise. We propose a serious game that helps people even without musical skills interact with each o

Filippo Carnovalini, Antonio Rodà, Nicholas Harley, Steven T. Homer

Computational models of music, while providing good descriptions of melodic development, still cannot fully grasp the general structure comprised of repetitions, transpositions, and reuse of melodic material. We present a corpus of strongly structured baroque allemandes, and describe a top-down approach to abstract the shared structure of their musical conte

Hagop Sazdjian

Due to the reducibility of tetraquark operators into mesonic clusters, a strong interplay exists in tetraquarks between compact and molecular structures. This issue is studied within an effective field theory approach, where the compact tetraquark is treated as an elementary particle. Under the influence of the coupling to the mesonic clusters, an initially

Christian Berger, Sadok Ben Toumia, Hans P. Reiser

The novel blockchain generation of Byzantine fault-tolerant (BFT) state machine replication (SMR) protocols focuses on scalability and performance to meet requirements of distributed ledger technology (DLT), e.g., decentralization and geographic dispersion. Validating scalability and performance of BFT protocol implementations requires careful evaluation. Wh

Suman Das, Chethan Krishnan, A. Preetham Kumar, Arnab Kundu

We consider a black hole with a stretched horizon as a toy model for a fuzzball microstate. The stretched horizon provides a cut-off, and therefore one can determine the normal (as opposed to quasi-normal) modes of a probe scalar in this geometry. For the BTZ black hole, we compute these as a function of the level $n$ and the angular quantum number $J$. Conv

Mohamed Sayed, John Gibson, Jamie Watson, Victor Prisacariu

Traditionally, 3D indoor scene reconstruction from posed images happens in two phases: per-image depth estimation, followed by depth merging and surface reconstruction. Recently, a family of methods have emerged that perform reconstruction directly in final 3D volumetric feature space. While these methods have shown impressive reconstruction results, they re

Gaetan Dissez, Nicole Tay, Tom Dyer, Matthew Tam

Objectives: The present study evaluated the impact of a commercially available explainable AI algorithm in augmenting the ability of clinicians to identify lung cancer on chest X-rays (CXR). Design: This retrospective study evaluated the performance of 11 clinicians for detecting lung cancer from chest radiographs, with and without assistance from a commerci

Taeyoung Kim, Dongsoo Har

In multi-goal reinforcement learning with a sparse binary reward, training agents is particularly challenging, due to a lack of successful experiences. To solve this problem, hindsight experience replay (HER) generates successful experiences even from unsuccessful ones. However, generating successful experiences from uniformly sampled ones is not an efficien

Z. Shi, K. Jefimovs, M. Stampanoni, L. Romano

Structuring Si in arrays of vertical high aspect ratio pillars, ranging from nanoscale to macroscale feature dimensions, is essential for producing functional interfaces for many applications. Arrays of silicon 3D nanostructures are needed to realize photonic and phononic crystals, waveguides, metalenses, X-ray wavefront sensors, detectors, microstructures a

Bikash R. Dinda, Narayan Banerjee

We put constraints on the peak absolute magnitude, $M_B$ of type Ia supernova using the Pantheon sample for type Ia supernova observations and the cosmic chronometers data for the Hubble parameter by a model independent and non-parametric approach. Our analysis is based on the Gaussian process regression. We find percent level bounds on the peak absolute mag

Emmanuel Hainry, Bruce M. Kapron, Jean-Yves Marion, Romain Péchoux

The class of Basic Feasible Functionals BFF is the second-order counterpart of the class of first-order functions computable in polynomial time. We present several implicit characterizations of BFF based on a typed programming language of terms. These terms may perform calls to non-recursive imperative procedures. The type discipline has two layers: the term

Jianlin Liu, Zhuofei Huang, Dihe Huang, Shang Xu

3D object detection from monocular image(s) is a challenging and long-standing problem of computer vision. To combine information from different perspectives without troublesome 2D instance tracking, recent methods tend to aggregate multiview feature by sampling regular 3D grid densely in space, which is inefficient. In this paper, we attempt to improve mult

Guangyu Tan, Yijun Hou, Hui Tian

Supra-arcade downflows (SADs) are dark structures descending towards post-reconnection flare loops observed in extreme ultraviolet or X-ray observations and are closely related to magnetic reconnection during solar flares. Due to the lack of statistical study on SADs in a single flare, evolutions of kinematic and thermal properties of SADs during the flare p

Neena Gupta

In this article, we shall discuss the solution to the Zariski Cancellation Problem in positive characteristic, various approaches taken so far towards the possible solution in characteristic zero, and several other questions related to this problem.

Gonzalo Galiano

We study Talenti's type symmetrization properties for solutions of linear stationary and evolution problems. Our main result establishes the comparison in norm between the solution of a problem and its symmetric version when nonlocal diffusion defined through integrable kernels is replacing the usual local diffusion defined by a second order differential ope

Filippo Carnovalini

Musical Metacreation tries to obtain creative behaviors from computers algorithms composing music. In this paper I briefly analyze how this field evolved from algorithmic composition to be focused on the search for creativity, and I point out some issues in pursuing this goal. Finally, I argue that hybridization of algorithms can be a useful direction for re

U. Munari, G. L. Righetti, S. Dallaporta

Our photometric and spectroscopic monitoring shows that starting with 2020 June 4, day +217 from optical maximum and well into its advanced nebular stage, Nova Sct 2019 began displaying a series of nine large amplitude flares (up to Delta(m)~1.7 mag), characterized by a rapid rise to peak (=<10 hours) and a fast exponential decline (e-folding time =<50 hours

Javier Canto, Lizaveta Ihnatsyeva, Juha Lehrbäck, Antti V. Vähäkangas

We examine the relations between different capacities in the setting of a metric measure space. First, we prove a comparability result for the Riesz $(\beta,p)$-capacity and the relative Hajlasz $(\beta,p)$-capacity, for $1<p<\infty$ and $0<\beta \le 1$, under a suitable kernel estimate related to the Riesz potential. Then we show that in geodesic spaces the

Christian Rauch, Markus Holzer

We investigate the accepting state complexity of deterministic finite automata for regular languages obtained by applying one of the following operations to languages accepted by permutation automata: union, quotient, complement, difference, intersection, Kleene star, Kleene plus, and reversal. The paper thus joins the study of accepting state complexity of

Benedek Nagy

Watson-Crick (WK) finite automata are working on a Watson-Crick tape, that is, on a DNA molecule. A double stranded DNA molecule contains two strands, each having a 5' and a 3' end, and these two strands together form the molecule with the following properties. The strands have the same length, their 5' to 3' directions are opposite, and in each position, th

František Mráz, Friedrich Otto

Here we propose a variant of the nondeterministic finite automaton with translucent letters (NFAwtl) which, after reading and deleting a letter, does not return to the left end of its tape, but rather continues from the position of the letter just deleted. When the end-of-tape marker is reached, our automaton can decide whether to accept, to reject, or to co

Dominika Klobučníková, Zbyněk Křivka, Alexander Meduna

This paper presents a new approach to regulation of grammars. It divides the derivation trees generated by grammars into two sections-generative and conclusive (the conclusion). The former encompasses generation of symbols up till the moment when the lowest rightmost terminal of the derivation tree is generated, whereas the latter represents the final steps

Pál Dömösi, Adama Diene

In this paper we show that a recently published finite automaton stream cipher can be considered as a quasigroup based stream cipher. Some additional properties of the discussed cipher are also given.

Moritz Humer, Michael E. Harding, Martin Schlipf, Amir Taheridehkordi

The direct random-phase approximation (dRPA) is used to calculate and compare atomization energies for the HEAT set and 10 selected molecules of the G2-1 set using both plane waves and Gaussian-type orbitals. We describe detailed procedures to obtain highly accurate and well converged results for the projector augmented-wave (PAW) method as implemented in th

Jürgen Dassow, Bianca Truthe

We continue the research on the generative capacity of contextual grammars where contexts are adjoined around whole words (externally) or around subwords (internally) which belong to special regular selection languages. All languages generated by contextual grammars where all selection languages are elements of a certain subregular language family form again

Samira Attou, Ludovic Mignot, Clément Miklarz, Florent Nicart

We propose another interpretation of well-known derivatives computations from regular expressions, due to Brzozowski, Antimirov or Lombardy and Sakarovitch, in order to abstract the underlying data structures (e.g. sets or linear combinations) using the notion of monad. As an example of this generalization advantage, we introduce a new derivation technique b

Artiom Alhazov, Rudolf Freund, Sergiu Ivanov

Membrane computing and P systems are a paradigm of massively parallel natural computing introduced by Gheorghe P\u{a}un in 1999, inspired by the structure of the living cell and by its biochemical reactions. In spite of this explicit biological motivation, P systems have not been extensively used in modelling real-world systems. To confirm this intuition, we

Maria Kosche, Tore Koß, Florin Manea, Stefan Siemer

In this paper we provide an overview of a series of recent results regarding algorithms for searching for subsequences in words or for the analysis of the sets of subsequences occurring in a word.

M. Gomtsyan, C. Lévy-Leduc, S. Ouadah, L. Sansonnet

We propose a novel and efficient iterative two-stage variable selection approach for multivariate sparse GLARMA models, which can be used for modelling multivariate discrete-valued time series. Our approach consists in iteratively combining two steps: the estimation of the autoregressive moving average (ARMA) coefficients of multivariate GLARMA models and th

Philippe Clément

The aim of this book is to introduce the reader to the beauty of Algebra, through a journey from the natural numbers to prime fields and finite fields, with some detours. Many books are devoted to the construction of these fields from the natural numbers. Perhaps the first one is [Landau 1930], see also the books [Ebbinghaus et.al. 1991], [Lay 2005], and the

Martin Kutrib, Andreas Malcher

Deterministic one-way time-bounded multi-counter automata are studied with respect to their ability to perform reversible computations, which means that the automata are also backward deterministic and, thus, are able to uniquely step the computation back and forth. We study the computational capacity of such devices and obtain separation results between irr

Juste Raimbault

Firm clusters are seen as having a positive effect on innovations, what can be interpreted as economies of scale or knowledge spillovers. The processes underlying the success of these clusters remain difficult to isolate. We propose in this paper a stylised agent-based model to test the role of geographical proximity and informal knowledge exchanges between

France Gheeraert

The class of (eventually) dendric words generalizes well-known families such as the Arnoux-Rauzy words or the codings of interval exchanges. There are still many open questions about the link between dendricity and morphisms. In this paper, we focus on two questions. The first one is the evolution of the factor complexity when applying a non-erasing morphism

Filippo Carnovalini, Antonio Rodà

Music is a form of expression that often requires interaction between players. If one wishes to interact in such a musical way with a computer, it is necessary for the machine to be able to interpret the input given by the human to find its musical meaning. In this work, we propose a system capable of detecting basic rhythmic features that can allow an appli

Ivan Contreras, Adele Long, Sophia Marx, Rajan Amit Mehta

We give some new examples of Frobenius objects in the category of sets and relations $\textbf{Rel}$. One example is a groupoid with a twisted counit. Another example is the set of conjugacy classes of a group. We also classify Frobenius objects in $\textbf{Rel}$ with two or three elements, and we compute the associated surface invariants using the partition

Davide Fazio, Antonio Ledda, Francesco Paoli

We show that intuitionistic logic is deductively equivalent to Connexive Heyting Logic (CHL), hereby introduced as an example of a strong connexive logic with intuitive semantics. We use the reverse algebraisation paradigm: CHL is presented as the assertional logic of a point regular variety (whose structure theory is examined in detail) that turns out to be

Lukas Beckenbach, Pavel Osinenko, Stefan Streif

Reinforcement learning is commonly associated with training of reward-maximizing (or cost-minimizing) agents, in other words, controllers. It can be applied in model-free or model-based fashion, using a priori or online collected system data to train involved parametric architectures. In general, online reinforcement learning does not guarantee closed loop s

Mykyta Narusevych

We give elementary proof that theory $T^1_2(R)$ augmented by the weak pigeonhole principle for all $\Delta^b_1(R)$-definable relations does not prove the bijective pigeonhole principle for $R$. This can be derived from known more general results but our proof yields a model of $T^1_2(R)$ in which $ontoPHP^{n+1}_n(R)$ fails for some nonstandard element $n$ wh

Hongxing Chen, Changchang Xi

Tachikawa's second conjecture predicts that a finitely generated, orthogonal module over a finite-dimensional self-injective algebra is projective. This conjecture is an important part of the Nakayama conjecture. Our principal motivation of this work is a systematic understanding of finitely generated, orthogonal generators over a self-injective Artin algebr

Boris Kazarnovskii

The probability that a zero of a random real polynomial of increasing degree is real tends to zero. However, passing from polynomials to Laurent polynomials yields a surprising result: the probability that a root is real tends not to zero, but to $1/\sqrt{3}$. A similar phenomenon has also been observed for systems of Laurent polynomials in several variables

F. Gégény, S. Nagy, K. Sailer

The functional renormalization group treatment of the conform reduced Einstein-Hilbert gravity is extended by following the evolution of the time and space derivatives separately, in order to consider the Lorentz symmetry during the evolution. We found the Reuter fixed point in the ultraviolet region. It is shown that starting from the Gaussian fixed point t

Tamás Baranyai

In his work on stress functions Maxwell noted that given a planar truss the internal force distribution may be described by a piecewise linear, $C^0$ continuous version of the Airy stress function. Later Williams and McRobie proposed that one can consider planar moment-bearing frames, where the stress function need not be even $C^0$ continuous. The two autho

Juhyeon Kim, Joonsuk Huh, Daniel K. Park

Machine learning using quantum convolutional neural networks (QCNNs) has demonstrated success in both quantum and classical data classification. In previous studies, QCNNs attained a higher classification accuracy than their classical counterparts under the same training conditions in the few-parameter regime. However, the general performance of large-scale

Shaonan Zhong, Junyang Mo, Zhantao Liu

Automatic segmentation of tumor lesions is a critical initial processing step for quantitative PET/CT analysis. However, numerous tumor lesion with different shapes, sizes, and uptake intensity may be distributed in different anatomical contexts throughout the body, and there is also significant uptake in healthy organs. Therefore, building a systemic PET/CT

Gee-Choon Lau, Wai-Chee Shiu, K. Premalatha, Ruixue Zhang

Let $G = (V,E)$ be a connected simple graph. A bijection $f: E \rightarrow \{1,2,\ldots,|E|\}$ is called a local antimagic labeling of $G$ if $f^+(u) \neq f^+(v)$ holds for any two adjacent vertices $u$ and $v$, where $f^+(u) = \sum_{e\in E(u)} f(e)$ and $E(u$) is the set of edges incident to $u$. A graph $G$ is called local antimagic if $G$ admits at least

Zhaowen Li, Xu Zhao, Chaoyang Zhao, Ming Tang

Previous unsupervised domain adaptation methods did not handle the cross-domain problem from the perspective of frequency for computer vision. The images or feature maps of different domains can be decomposed into the low-frequency component and high-frequency component. This paper proposes the assumption that low-frequency information is more domain-invaria

Qi Wang, Zhe Ding, Gary Wong, and Jia Zhou

Acoustic mixing of droplets is a promising way to implement biosensors that combine high speed and minimal reagent consumption. To date, this type of droplet mixing is driven by a volume force resulting from the absorption of high-frequency acoustic waves in the bulk of the fluid. Here, we show that the speed of these sensors is limited by the slow advection

Jiaqi Ma, Shengyuan Yan, Lefei Zhang, Guoli Wang

In order to get raw images of high quality for downstream Image Signal Process (ISP), in this paper we present an Efficient Locally Multiplicative Transformer called ELMformer for raw image restoration. ELMformer contains two core designs especially for raw images whose primitive attribute is single-channel. The first design is a Bi-directional Fusion Projec

Hélène Bloch, Pascal Tremblin, Matthias González, Edouard Audit

We present a geometric multigrid solver for the M1 model of radiative transfer without source terms. In radiative hydrodynamics applications, the radiative transfer needs to be solved implicitly because of the fast propagation speed of photons relative to the fluid velocity. The M1 model is hyperbolic and can be discretized with an HLL solver, whose time imp

Mariano Santander

This article contains the last part of the mini-course `Spaces: a perspective view' delivered at the IFWGP2012. Here I deal with the part of the mini-course which centers on the classification questions associated to the simple real Lie groups. I review the original introduction of the Magic Square `a la Freudenthal', putting the emphasis in the role played

T. Chaumont-Frelet

We consider interior penalty discontinuous Galerkin discretizations of time-harmonic wave propagation problems modeled by the Helmholtz equation, and derive novel a priori and a posteriori estimates. Our analysis classically relies on duality arguments of Aubin-Nitsche type, and its originality is that it applies under minimal regularity assumptions. The est

Johanne Cohen, Laurence Pilard, Mikaël Rabie, Jonas Sénizergues

We propose a way to transform synchronous distributed algorithms solving locally greedy and mendable problems into self-stabilizing algorithms in anonymous networks. Mendable problems are a generalization of greedy problems where any partial solution may be transformed -- instead of completed -- into a global solution: every time we extend the partial soluti

Xingchao Liu, Lemeng Wu, Mao Ye, Qiang Liu

Diffusion-based generative models have achieved promising results recently, but raise an array of open questions in terms of conceptual understanding, theoretical analysis, algorithm improvement and extensions to discrete, structured, non-Euclidean domains. This work tries to re-exam the overall framework, in order to gain better theoretical understandings a

Jakob Weissteiner, Jakob Heiss, Julien Siems, Sven Seuken

We study the combinatorial assignment domain, which includes combinatorial auctions and course allocation. The main challenge in this domain is that the bundle space grows exponentially in the number of items. To address this, several papers have recently proposed machine learning-based preference elicitation algorithms that aim to elicit only the most impor

Natalia P. Bondarenko

This paper is concerned with inverse spectral problems for higher-order ($n > 2$) ordinary differential operators. We develop an approach to the reconstruction from the spectral data for a wide range of differential operators with either regular or distribution coefficients. Our approach is based on the reduction of an inverse problem to a linear equation in

Yan-Xia Ren, Ting Yang, Rui Zhang

Recently Ren et al. [Stoch. Proc. Appl., 137 (2021)] have proved that the extremal process of the super-Brownian motion converges in distribution in the limit of large times. Their techniques rely heavily on the study of the convergence of solutions to the Kolmogorov-Petrovsky-Piscounov equation along the lines of [M. Bramson, Mem. Amer. Math. Soc., 44 (1983

Maximilian Köhler, Daniel Balzani

A new relaxation approach is proposed which allows for the description of stress- and strain-softening at finite strains. The model is based on the construction of a convex hull replacing the originally non-convex incremental stress potential which in turn represents damage in terms of the classical $(1-D)$ approach. This convex hull is given as the linear c

Alexandre Lambert, Manolo Dulva Hina, Celine Barth, Assia Soukane

Road accidents have become the eight leading cause of death all over the world. Lots of these accidents are due to a driver's inattention or lack of focus, due to fatigue. Various factors cause driver's fatigue. This paper considers all the measureable data that manifest driver's fatigue, namely those manifested in the vehicle measureable data while driving

Jiaqi Chen

In this paper, we construct a uniform formula that can iteratively reduce all auxiliary scalar product numerators of arbitrary multi-loop Feynman integrals. Integrals with such numerators commonly appear in Integration-By-Parts (IBP) relations. This formula is constructed with the generalized Sylvester's determinant identity. Compared to that using only trad

Christian Aebeloe, Gabriela Montoya, Katja Hose

While the Web of Data in principle offers access to a wide range of interlinked data, the architecture of the Semantic Web today relies mostly on the data providers to maintain access to their data through SPARQL endpoints. Several studies, however, have shown that such endpoints often experience downtime, meaning that the data they maintain becomes inaccess

Jean Van Schaftingen

We prove Gagliardo-Nirenberg interpolation inequalities estimating the Sobolev semi-norm in terms of the bounded mean oscillation semi-norm and a Sobolev semi-norm, with some of the Sobolev semi-norms having fractional order.

Katsuhiko Higuchi, Dipendra Bahadur Hamal, Masahiko Higuchi

We present the second-order phase transition from a band insulator to metal that is induced by a strong magnetic field. The magnetic-field dependences of the magnetization and energy band gap of a crystalline silicon immersed in a magnetic field are investigated by means of the nonperturbative magnetic-field-containing relativistic tight-binding approximatio

Eike-Manuel Bansbach, Yigit Kiyak, Laurent Schmalen

For orthogonal multiple access (OMA) systems, the number of served user equipments (UEs) is limited to the number of available orthogonal resources. On the other hand, non-orthogonal multiple access (NOMA) schemes allow multiple UEs to use the same orthogonal resource. This extra degree of freedom introduces new challenges for resource allocation. Buffer sta

Markus Kirschmer, Jürgen Klüners

We discuss various connections between ideal classes, divisors, Picard and Chow groups of one-dimensional noetherian domains. As a result of these, we give a method to compute Chow groups of orders in global fields and show that there are infinitely many number fields which contain orders with trivial Chow groups.

Zengyuan Guo, Yuechen Yu, Pengyuan Lv, Chengquan Zhang

Table structure recognition is a crucial part of document image analysis domain. Its difficulty lies in the need to parse the physical coordinates and logical indices of each cell at the same time. However, the existing methods are difficult to achieve both these goals, especially when the table splitting lines are blurred or tilted. In this paper, we propos

Dustin Carrión-Ojeda, Hong Chen, Adrian El Baz, Sergio Escalera

We present the design and baseline results for a new challenge in the ChaLearn meta-learning series, accepted at NeurIPS'22, focusing on "cross-domain" meta-learning. Meta-learning aims to leverage experience gained from previous tasks to solve new tasks efficiently (i.e., with better performance, little training data, and/or modest computational resources).

Julie Ducasse, Anke Brock, Christophe Jouffrais

Tactile maps are commonly used to give visually impaired users access to geographical representations. Although those relief maps are efficient tools for acquisition of spatial knowledge, they present several limitations and issues such as the need to read braille. Several research projects have been led during the past three decades in order to improve acce

David Rey, Simon Thomas, Rishabh Sharma, Thomas Badr

Starting from a degenerate Bose gas in a hybrid trap combining a magnetic quadrupole trap and an attractive optical trap resulting from a focused laser beam, we demonstrate the efficient loading of this quantum gas into a shell-shaped trap. The shell trap is purely magnetic and relies on adiabatic potentials for atoms in an inhomogeneous magnetic field dress

Žiga Babnik, Vitomir Štruc

While recent face recognition (FR) systems achieve excellent results in many deployment scenarios, their performance in challenging real-world settings is still under question. For this reason, face image quality assessment (FIQA) techniques aim to support FR systems, by providing them with sample quality information that can be used to reject poor quality d

Zhiyuan He, Yijun Yang, Pin-Yu Chen, Qiang Xu

Deep Neural Networks (DNNs) have achieved excellent performance in various fields. However, DNNs' vulnerability to Adversarial Examples (AE) hinders their deployments to safety-critical applications. This paper presents a novel AE detection framework, named BEYOND, for trustworthy predictions. BEYOND performs the detection by distinguishing the AE's abnormal

Christophe Denis, Mohamed Hebiri, Boris Ndjia Njike, Xavier Siebert

Active learning is a paradigm of machine learning which aims at reducing the amount of labeled data needed to train a classifier. Its overall principle is to sequentially select the most informative data points, which amounts to determining the uncertainty of regions of the input space. The main challenge lies in building a procedure that is computationally

Jean Néraud

Given a finite alphabet $A$ and a binary relation $\tau\subseteq A^*\times A^*$, a set $X$ is $\tau$-{\it independent} if $ \tau(X)\cap X=\emptyset$. Given a quasi-metric $d$ over $A^*$ (in the meaning of \cite{W31}) and $k\ge 1$, we associate the relation $\tau_{d,k}$ defined by $(x,y)\in\tau_{d,k}$ if, and only if, $d(x,y)\le k$ \cite{CP02}.In the spirit o

Ryotaro Koshio

In this article, we prove that induced modules of support $\tau$-tilting modules over blocks of finite groups satisfying inertial-invariant condition are also support $\tau$-tilting modules.

Thomas Witte, Andrea Vogt, Tina Seufert, Matthias Tichy

Novices need to overcome initial barriers while programming cyber-physical systems behavior, like coding quadcopter missions, and should thus be supported by an adequately designed programming environment. Using multiple representations by including graphical previews is a common approach to ease coding and program understanding. However, novices struggle to

Xinrui Guo, Xiaoyang Ma, Franz Muller, Kai Ni

Hardware security has been a key concern in modern information technologies. Especially, as the number of Internet-of-Things (IoT) devices grows rapidly, to protect the device security with low-cost security primitives becomes essential, among which Physical Unclonable Function (PUF) is a widely-used solution. In this paper, we propose the first FeFET-based

Chengleyang Lei, Wei Feng, Jue Wang, Shi Jin

This letter presents a sensing-communication-computing-control (SC3) integrated satellite unmanned aerial vehicle (UAV) network, where the UAV is equipped with on-board sensors, mobile edge computing (MEC) servers, base stations and satellite communication module. Like the nervous system, this integrated network is capable of organizing multiple field robots

P. Mrowiński, P. Holewa, A. Sakanas, G. Sęk

We demonstrate comprehensive numerical studies on a hybrid III-V/Si-based waveguide system, serving as a platform for efficient light coupling between an integrated III-V quantum dot emitter to an on-chip quantum photonic integrated circuit defined on a silicon substrate. We propose a platform consisting of a hybrid InP/Si waveguide and an InP-embedded InAs

Shifan Zuo, Xuelei Chen, Yi Mao

The Principal Component Analysis (PCA) method and the Singular Value Decomposition (SVD) method are widely used for foreground subtraction in 21 cm intensity mapping experiments. We show their equivalence, and point out that the condition for completely clean separation of foregrounds and cosmic 21 cm signal using the PCA/SVD is unrealistic. We propose a PCA

Takahito Yoshizawa, Dave Singelée, Jan Tobias Muehlberg, Stéphane Delbruel

Vehicle-to-Everything (V2X) communication is receiving growing attention from industry and academia as multiple pilot projects explore its capabilities and feasibility. With about 50\% of global road vehicle exports coming from the European Union (EU), and within the context of EU legislation around security and data protection, V2X initiatives must consider

Raphaël Berthier

Diagonal linear networks (DLNs) are a toy simplification of artificial neural networks; they consist in a quadratic reparametrization of linear regression inducing a sparse implicit regularization. In this paper, we describe the trajectory of the gradient flow of DLNs in the limit of small initialization. We show that incremental learning is effectively perf

Bo Tu, Wen-Tai Li, Chau Yuen

This work studies the potential vulnerability of distributed control schemes in smart grids. To this end, we consider an optimal inverter VAR control problem within a PV-integrated distribution network. First, we formulate the centralized optimization problem considering the reactive power priority and further reformulate the problem into a distributed frame