March 2023 arXiv papers — page 114

Guyue Li, Paul Staat, Haoyu Li, Markus Heinrichs

Channel Reciprocity-based Key Generation (CRKG) exploits reciprocal channel randomness to establish shared secret keys between wireless terminals. This new security technique is expected to complement existing cryptographic techniques for secret key distribution of future wireless networks. In this paper, we present a new attack, reconfigurable intelligent s

Wuyang Luo, Su Yang, Weishan Zhang

Face inpainting aims at plausibly predicting missing pixels of face images within a corrupted region. Most existing methods rely on generative models learning a face image distribution from a big dataset, which produces uncontrollable results, especially with large-scale missing regions. To introduce strong control for face inpainting, we propose a novel ref

Kohji Tsumura, Shuji Matsuura, Kei Sano, Takahiro Iwata

Zodiacal light (ZL) is sunlight scattered by interplanetary dust particles (IDPs) at optical wavelengths. The spatial distribution of IDPs in the Solar System may hold an important key to understanding the evolution of the Solar System and material transportation within it. The number density of IDPs can be expressed as $n(r) \sim r^{-\alpha}$, and the expon

Hongxiang Huang, Daihui Yang, Gang Dai, Zhen Han

The study of ancient writings has great value for archaeology and philology. Essential forms of material are photographic characters, but manual photographic character recognition is extremely time-consuming and expertise-dependent. Automatic classification is therefore greatly desired. However, the current performance is limited due to the lack of annotated

Chuan Tang, Xi Yang

Current 3D instance segmentation models generally use multi-stage methods to extract instance objects, including clustering, feature extraction, and post-processing processes. However, these multi-stage approaches rely on hyperparameter settings and hand-crafted processes, which restrict the inference speed of the model. In this paper, we propose a new 3D po

Alfredo Fiorentino, Paolo Pegolo, Stefano Baroni

In the past few years, the theory of thermal transport in amorphous solids has been substantially extended beyond the Allen-Feldman model. The resulting formulation, based on the Green-Kubo linear response or the Wigner-transport equation, bridges this model for glasses with the traditional Boltzmann kinetic approach for crystals. The computational effort re

Ritam Majumdar, Vishal Jadhav, Anirudh Deodhar, Shirish Karande

Physics-informed Neural Networks (PINNs) have been widely used to obtain accurate neural surrogates for a system of Partial Differential Equations (PDE). One of the major limitations of PINNs is that the neural solutions are challenging to interpret, and are often treated as black-box solvers. While Symbolic Regression (SR) has been studied extensively, very

Alastair Langtry, Christian Ghiglino

This paper adapts ideas from social identity theory to set out a new framework for modelling conspicuous consumption. Agents derive utility from their consumption of a status good and from belonging to an identity group with high status good consumption. Importantly, these two sources of utility are substitutes. Agents also feel pressure to conform with thei

Sándor P. Fekete, Phillip Keldenich, Dominik Krupke, Stefan Schirra

We give an overview of the 2023 Computational Geometry Challenge targeting the problem Minimum Coverage by Convex Polygons, which consists of covering a given polygonal region (possibly with holes) by a minimum number of convex subsets, a problem with a long-standing tradition in Computational Geometry.

Alessandro Georgoudis, Carlo Heissenberg, Ingrid Vazquez-Holm

We calculate the inelastic $2\to3$ one-loop amplitude for the scattering of two point-like, spinless objects with generic masses involving the additional emission of a single graviton. We focus on the near-forward, or classical, limit. Our results include the leading and subleading orders in the soft-region expansion, which captures all non-analytic contribu

Zirun Zhu, Hemin Yang, Min Tang, Ziyi Yang

Audio-visual speech enhancement (AV-SE) methods utilize auxiliary visual cues to enhance speakers' voices. Therefore, technically they should be able to outperform the audio-only speech enhancement (SE) methods. However, there are few works in the literature on an AV-SE system that can work in real time on a CPU. In this paper, we propose a low-latency real-

Tadej Mežnaršič, Rok Žitko, Katja Gosar, Jure Pirman

Matter-wave jets are ejected from a Bose-Einstein condensate subjected to a modulation of the interaction strength. For sufficiently strong modulation additional higher harmonic matter-wave jets emerge. Here we report the first experimental observation of incommensurable "golden" $\frac{1+\sqrt{5}}{2}$ matter-wave jets in a Bose-Einstein condensate exposed t

Islam Debicha, Benjamin Cochez, Tayeb Kenaza, Thibault Debatty

Nowadays, numerous applications incorporate machine learning (ML) algorithms due to their prominent achievements. However, many studies in the field of computer vision have shown that ML can be fooled by intentionally crafted instances, called adversarial examples. These adversarial examples take advantage of the intrinsic vulnerability of ML models. Recent

Michael Kerber, Matthias Söls

We propose an extension of the classical union-of-balls filtration of persistent homology: fixing a point $q$, we focus our attention to a ball centered at $q$ whose radius is controlled by a second scale parameter. We discuss an absolute variant, where the union is just restricted to the $q$-ball, and a relative variant where the homology of the $q$-ball re

Jorge Dueñas-Lerín, Raúl Lara-Cabrera, Fernando Ortega, Jesús Bobadilla

Recommendation to groups of users is a challenging subfield of recommendation systems. Its key concept is how and where to make the aggregation of each set of user information into an individual entity, such as a ranked recommendation list, a virtual user, or a multi-hot input vector encoding. This paper proposes an innovative strategy where aggregation is m

Namkyeong Lee, Heewoong Noh, Sungwon Kim, Dongmin Hyun

The density of states (DOS) is a spectral property of materials, which provides fundamental insights on various characteristics of materials. In this paper, we propose a model to predict the DOS by reflecting the nature of DOS: DOS determines the general distribution of states as a function of energy. Specifically, we integrate the heterogeneous information

Marius Schubert, Tobias Riedlinger, Karsten Kahl, Daniel Kröll

Labeling datasets for supervised object detection is a dull and time-consuming task. Errors can be easily introduced during annotation and overlooked during review, yielding inaccurate benchmarks and performance degradation of deep neural networks trained on noisy labels. In this work, we for the first time introduce a benchmark for label error detection met

Bo-hyun Kwon

An important issue in classifying the rational $3$-tangle is how to know whether or not the given tangle is the trivial rational 3-tangle called $\infty$-tangle. The author\cite{1} provided a certain algorithm to detect the $\infty$-tangle. In this paper, we give a much simpler method to detect the $\infty$-tangle by using the $\textit{bridge arc replacement

Ulf A. Hamster, Ji-Ung Lee, Alexander Geyken, Iryna Gurevych

Training and inference on edge devices often requires an efficient setup due to computational limitations. While pre-computing data representations and caching them on a server can mitigate extensive edge device computation, this leads to two challenges. First, the amount of storage required on the server that scales linearly with the number of instances. Se

Yanandlall Gopee, Margot Gaetani-Liseo, Anne Blavette, Guy Camilleri

In the field of microgrids with a significant integration of Renewable Energy Sources, the efficient and practical power storage systems requirement is causing DC microgrids to gain increasing attention. However, uncertainties in power generation and load consumption along with the fluctuations of electricity prices require the design of a reliable control a

F. Formisano, T. T. Gareev, D. I. Khusyainov, A. E. Fedianin

Controlled generation of coherent spin waves with highest possible frequencies and the shortest possible wavelengths is a cornerstone of spintronics and magnonics. Here, using the Heisenberg antiferromagnet RbMF$_3$, we demonstrate that laser-induced THz spin dynamics corresponding to pairs of mutually coherent counter propagating spin waves with the wavevec

Matteo Erbi, Hakim Amara, Riccardo Gatti

Understanding and mastering the mechanical properties of metallic nanoparticles is crucial for their use in a wide range of applications. In this context, we use atomic-scale (Molecular Dynamics) and continuous (Finite Elements) calculations to investigate in details gold nanoparticles under deformation. By combining these two approaches, we show that the el

Tao Yang, Peiran Ren, Xuansong xie, Lei Zhang

In supervised image restoration tasks, one key issue is how to obtain the aligned high-quality (HQ) and low-quality (LQ) training image pairs. Unfortunately, such HQ-LQ training pairs are hard to capture in practice, and hard to synthesize due to the complex unknown degradation in the wild. While several sophisticated degradation models have been manually de

Noufel Frikha, Maximilien Germain, Mathieu Laurière, Huyên Pham

We study policy gradient for mean-field control in continuous time in a reinforcement learning setting. By considering randomised policies with entropy regularisation, we derive a gradient expectation representation of the value function, which is amenable to actor-critic type algorithms, where the value functions and the policies are learnt alternately base

Rob Brekelmans, Sicong Huang, Marzyeh Ghassemi, Greg Ver Steeg

Mutual information (MI) is a fundamental quantity in information theory and machine learning. However, direct estimation of MI is intractable, even if the true joint probability density for the variables of interest is known, as it involves estimating a potentially high-dimensional log partition function. In this work, we present a unifying view of existing

Luc Absil, Yann Balland, Franck Pereira dos Santos

We report our method for transporting ultracold atoms over macroscopic distances and trapping them back in a vertical mixed trap, consisting of the superposition of a vertical lattice and a transverse confinement beam. The transport is performed with Bloch oscillations allowing us to move up to 25% of a sub-micro-Kelvin atomic cloud on a distance of the orde

Zhonghua Ma, Markus Rambach, Kaumudibikash Goswami, Some Sankar Bhattacharya

Quantum correlations and non-projective measurements underlie a plethora of information-theoretic tasks, otherwise impossible in the classical world. Existing schemes to certify such non-classical resources in a device-independent manner require seed randomness, which is often costly and vulnerable to loopholes, for choosing the local measurements performed

G. Romagnoli, E. Marchiori, K. Bagani, M. Poggio

We demonstrate the fabrication of scanning superconducting quantum interference devices (SQUIDs) on the apex of sharp quartz scanning probes -- known as SQUID-on-tip probes -- using conventional magnetron sputtering. We produce and characterize SQUID-on-tips made of both Nb and MoGe with effective diameters ranging from 50 to 80 nm, magnetic flux noise down

Ning Xu, Sarah E. Bohndiek, Zexing Li, Cilong Zhang

Point-scanning microscopy approaches are transforming super-resolution imaging. Despite achieving parallel high-speed imaging using multifocal techniques, efficient multi-color capability with high-quality illumination is currently lacking. In this paper, we present for the first time Mechanical-scan-free and multi-Color Super-resolution Microscopy (MCoSM) b

Georges Gagneré, Andy Lavender, Cédric Plessiet, Tim White

We describe1 two case studies of AvatarStaging theatrical mixed reality framework combining avatars and performers acting in an artistic context. We outline a qualitative approach toward the condition for stage presence for the avatars. We describe the motion control solutions we experimented with from the perspective of building a protocol of avatar directi

Anni Hakanen, Ismael G. Yero

This investigation is firstly focused into showing that two metric parameters represent the same object in graph theory. That is, we prove that the multiset resolving sets and the ID-colorings of graphs are the same thing. We also consider some computational and combinatorial problems of the multiset dimension, or equivalently, the ID-number of graphs. We pr

Daniel González-Cuadra, Dolev Bluvstein, Marcin Kalinowski, Raphael Kaubruegger

Simulating the properties of many-body fermionic systems is an outstanding computational challenge relevant to material science, quantum chemistry, and particle physics. Although qubit-based quantum computers can potentially tackle this problem more efficiently than classical devices, encoding non-local fermionic statistics introduces an overhead in the requ

Georges Gagneré, Cédric Plessiet

We introduce the setup and programming framework of AvatarStaging theatrical mixed reality experiment. We focus on a configuration addressing movement issues between physical and 3D digital spaces from performers and directors' points of view. We propose 3 practical exercises.

Sabrina Burgardt, Simon B. Jäger, Julian Feß, Silvia Hiebel

We report the experimental implementation of dynamical decoupling on a small, non-interacting ensemble of up to 25 optically trapped, neutral Cs atoms. The qubit consists of the two magnetic-insensitive Cs clock states $\left| F=3, m_F=0 \right>$ and $\left|F=4, m_F=0\right>$, which are coupled by microwave radiation. We observe a significant enhancement of

Hemant Yadav, Sunayana Sitaram, Rajiv Ratn Shah

Recent developments in pre-trained speech representation utilizing self-supervised learning (SSL) have yielded exceptional results on a variety of downstream tasks. One such technique, known as masked predictive coding (MPC), has been employed by some of the most high-performing models. In this study, we investigate the impact of MPC loss on the type of info

Georges Gagneré, Anastasiia Ternova

After an overview of the use of digital shadows in computing science research projects with cultural and social impacts and a focus on recent researches and insights on virtual theaters, this paper introduces a research mixing the manipulation of shadow avatars and the building of a virtual theater setup inspired by traditional shadow theater (or ``castelet'

Li-Chin Chen, Kuo-Hsuan Hung, Yi-Ju Tseng, Hsin-Yao Wang

The inherent nature of patient data poses several challenges. Prevalent cases amass substantial longitudinal data owing to their patient volume and consistent follow-ups, however, longitudinal laboratory data are renowned for their irregularity, temporality, absenteeism, and sparsity; In contrast, recruitment for rare or specific cases is often constrained d

Xiang Li, Zifei Shen, Marco Squassina, Minbo Yang

In this paper, we establish some Stein-Weiss type inequalities with general kernels on the upper half space and study the existence of extremal functions for this inequality with the optimal constant. Furthermore, we also investigate the regularity, asymptotic estimates, symmetry and non-existence results of the positive solutions of the corresponding Euler-

Christian Flamant

This book starts from the basic questions that had been raised by the founders of Economic theory, Smith, Ricardo, and Marx: what makes the value of commodities, what are production, exchange, money and incomes like profits, wages and rents. The answers that these economists had provided were mostly wrong, above all by defining the equivalence of commodities

Tobias K. S. Ritschel

In this paper, we present a Newton-like method based on model reduction techniques, which can be used in implicit numerical methods for approximating the solution to ordinary differential equations. In each iteration, the Newton-like method solves a reduced order linear system in order to compute the Newton step. This reduced system is derived using a projec

Vipin Vijayan, L. Chotorlishvili, A. Ernst, S. S. P. Parkin

Quantum skyrmionic phase is modelled in a 2D helical spin lattice. This topological skyrmionic phase retains its nature in a large parameter space before moving to a ferromagnetic phase. Next nearest-neighbour interaction improves the stability and it also causes a shift of the topological phase in the parameter space. Nonanalytic behaviour of the rate funct

Serge Bouc, Deniz Yılmaz

Let $k$ be an algebraically closed field of characteristic $p>0$, let $R$ be a commutative ring and let $\mathcal{F}$ be an algebraically closed field of characteristic $0$. We introduce the category $\overline{\mathcal{F}_{Rpp_k}}$ of stable diagonal $p$-permutation functors over $R$. We prove that the category $\overline{\mathcal{F}_{\mathbb{F}pp_k}}$ is s

Tim Downing, Nicos Angelopoulos

The continuing advances of omic technologies mean that it is now more tangible to measure the numerous features collectively reflecting the molecular properties of a sample. When multiple omic methods are used, statistical and computational approaches can exploit these large, connected profiles. Multi-omics is the integration of different omic data sources f

Maria Giovanna Dainotti, Giada Bargiacchi, Malgorzata Bogdan, Salvatore Capozziello

Type Ia Supernovae (SNe Ia) are considered the most reliable \textit{standard candles} and they have played an invaluable role in cosmology since the discovery of the Universe's accelerated expansion. During the last decades, the SNe Ia samples have been improved in number, redshift coverage, calibration methodology, and systematics treatment. These efforts

Edward McCann

We classify Hermitian tight-binding models describing noninteracting electrons on a one-dimensional periodic lattice with two energy bands. To do this, we write a generalized Rice-Mele model with two orbitals per unit cell, including all possible complex-valued long-range hoppings consistent with Hermicity. We then apply different forms of time-reversal, cha

Anthony Frion, Lucas Drumetz, Mauro Dalla Mura, Guillaume Tochon

Over the last few years, several works have proposed deep learning architectures to learn dynamical systems from observation data with no or little knowledge of the underlying physics. A line of work relies on learning representations where the dynamics of the underlying phenomenon can be described by a linear operator, based on the Koopman operator theory.

Dorian Le Peutrec, Laurent Michel, Boris Nectoux

In this work, we analyse the metastability of non-reversible diffusion processes $$dX_t=\boldsymbol{b}(X_t)dt+\sqrt h\,dB_t$$ on a bounded domain $\Omega$ when $\mathbf{b}$ admits the decomposition $\mathbf{b}=-(\nabla f+\mathbf{\ell})$ and $\nabla f \cdot \mathbf{\ell}=0$. In this setting, we first show that, when $h\to 0$, the principal eigenvalue of the g

Andrey Vayner, Nadia L. Zakamska, Yuzo Ishikawa, Swetha Sankar

Massive galaxies formed most actively at redshifts $z=1-3$ during the period known as `cosmic noon.' Here we present an emission-line study of an extremely red quasar SDSSJ165202.64+172852.3 host galaxy at $z=2.94$, based on observations with the Near Infrared Spectrograph (NIRSpec) integral field unit (IFU) on board JWST. We use standard emission-line diagn

F Osswald, E Traykov, T Durand, M Heine

A prototype of ion beam transport module has been developed at the Institut Pluridisciplinaire Hubert Curien (IPHC) and used as a test bed to investigate key issues related to the efficient transport of ion beams. This includes the reduction of the beam losses, the increase of the acceptance, and the definition of the instrumentation necessary to evaluate th

Cyprien Beaufort, Mar Bastero-Gil, Tiffany Luce, Daniel Santos

The decay of Axion-Like Particles (ALPs) trapped in the solar gravitational field would contribute to the observed solar X-ray flux, hence constraining ALP models. We improve by one order of magnitude the existing limits in the parameter space $(g_{a\gamma\gamma}, m)$ by considering ALPs production via photon coalescence. For $g_{ae} \neq 0$, we demonstrate

Christophe Raffalli

We propose a novel sufficient condition establishing that a piecewise affine variety has the same topology as a variety of the sphere $\mathbb{S}^n$ defined by positively homogeneous $C^1$ functions. This covers the case of $C^1$ varieties in the projective space $\mathbb{P}^n$. We prove that this condition is sufficient in the case of codimension one and ar

Zeina Al Masry, Romain Pic, Clément Dombry, Christine Devalland

Introduction: The Oncotype DX (ODX) test is a commercially available molecular test for breast cancer assay that provides prognostic and predictive breast cancer recurrence information for hormone positive, HER2-negative patients. The aim of this study is to propose a novel methodology to assist physicians in their decision-making. Methods: A retrospective s

Bo Qiang, Yiran Zhou, Yuheng Ding, Ningfeng Liu

Chemical reactions are the fundamental building blocks of drug design and organic chemistry research. In recent years, there has been a growing need for a large-scale deep-learning framework that can efficiently capture the basic rules of chemical reactions. In this paper, we have proposed a unified framework that addresses both the reaction representation l

Laurent Thomann, Nicolas Burq

In this note, we give an overview of some results obtained in [3]. This latter work is devoted to the study of the one-dimensional nonlinear Schr{\"o}dinger equation with random initial conditions. Namely, we describe the nonlinear evolution of Gaussian measures and we deduce global well-posedness and scattering results for the corresponding nonlinear Schr{\

Tommaso Flaminio, Sara Ugolini

The present paper investigates proof-theoretical and algebraic properties for the probability logic FP(L,L), meant for reasoning on the uncertainty of Lukasiewicz events. Methodologically speaking, we will consider a translation function between formulas of FP(L,L) to the propositional language of Lukasiewicz logic that allows us to apply the latter and the

Tao Wang, Jie Lv, Haonan Tong, Changsheng You

In this paper, we study the codebook-based near-field beam training for intelligent reflecting surfaces (IRSs) aided wireless system. In the considered model, the near-field beam training is critical to focus signals at the location of user equipment (UE) to obtain prominent IRS array gain. However, existing codebook schemes cannot achieve low training overh

Biswajit Jana, Anirban Chatterjee, Kumar Ravi, Abhijit Bandyopadhyay

We considered non-minimally coupled curvature-matter models of gravity in a FRW universe filled with perfect fluid and investigated its cosmological implications in the light of Pantheon compilation of 1048 Supernovae Ia data points along with 54 data points from Observed Hubble Data. The non-minimal curvature-matter coupling has been introduced by adding a

Renaud Ferrand, Sébastien Galtier, Fouad Sahraoui, Christoph Federrath

The role of supersonic turbulence in structuring the interstellar medium (ISM) remains an unsettled question. Here, this problem is investigated using a newexact law of compressible isothermal hydrodynamic turbulence, which involves two-point correlations in physical space. The new law is shown to have a compact expression that contains a single flux term re

M. Sumetsky

An optical microresonator, which parameters are periodically modulated in time, can generate optical frequency comb (OFC) spectral resonances equally spaced by the modulation frequency. Significant recent progress in realization of OFC generators based on the modulation of microresonator parameters boosted interest to their further experimental development a

Francesca Larosa, Jaroslav Mysiak, Marco Molinari, Panagiotis Varelas

Innovation is a key component to equip our society with tools to adapt to new climatic conditions. The development of research-action interfaces shifts useful ideas into operationalized knowledge allowing innovation to flourish. In this paper we quantify the existing gap between climate research and innovation action in Europe using a novel framework that co

Guihua Zhang, Hanyu Li, Yimin Wei

Based on the column pivoted QR decomposition, we propose some randomized algorithms including pass-efficient ones for the generalized CUR decompositions of matrix pair and matrix triplet. Detailed error analyses of these algorithms are provided. Numerical experiments are given to test the proposed randomized algorithms.

Andrea Carron, Danilo Saccani, Lorenzo Fagiano, Melanie N. Zeilinger

In cooperative multi-agent robotic systems, coordination is necessary in order to complete a given task. Important examples include search and rescue, operations in hazardous environments, and environmental monitoring. Coordination, in turn, requires simultaneous satisfaction of safety critical constraints, in the form of state and input constraints, and a c

Margarida Romero, Laurent Heiser, Alexandre Lepage, Alexandre Lepage

As part of the Digital Working Group (GTnum) #Scol_IA "Renewal of digital practices and creative uses of digital and AI" we are pleased to present the white paper "Teaching and learning in the era of Artificial Intelligence, Acculturation, integration and creative uses of AI in education". The white paper edited by Margarida Romero, Laurent Heiser and Alexan

Hayato Morimura, Nicolò Sibilla, Peng Zhou

We prove one direction of homological mirror symmetry for complete intersections in algebraic tori, in all dimensions. The mirror geometry is not a space but a LG model, i.e. a pair given by a space and a regular function. We show that the Fukaya category of the complete intersection is equivalent to the category of matrix factorizations of the LG pair. Our

Mehran Hatamzadeh, Ali Sharifnezhad, Reza Hassannejad, Raphael Zory

Objective: The main goal of the athletes who undergo anterior cruciate ligament reconstruction (ACLR) surgery is a successful return-to-sport. At this stage, identifying muscular deficits becomes important. Hence, in this study, three discriminative features based on surface electromyographic signals (sEMG) acquired in a dynamic protocol are introduced to as

Marilena Crupi, Antonino Ficarra, Ernesto Lax

Let $K$ be a field, $V$ a finite dimensional $K$-vector space and $E$ the exterior algebra of $V$. We analyze iterated mapping cone over $E$. If $I$ is a monomial ideal of $E$ with linear quotients, we show that the mapping cone construction yields a minimal graded free resolution $F$ of $I$ via the Cartan complex. Moreover, we provide an explicit descriptio

Thomas Ehrhard, Aymeric Walch

We extend to general Cartesian categories the idea of Coherent Differentiation recently introduced by Ehrhard in the setting of categorical models of Linear Logic. The first ingredient is a summability structure which induces a partial left-additive structure on the category. Additional functoriality and naturality assumptions on this summability structure i

Lisa Balsollier, Frédéric Lavancier, Jean Salamero, Charles Kervrann

Generators of space-time dynamics in bioimaging have become essential to build ground truth datasets for image processing algorithm evaluation such as biomolecule detectors and trackers, as well as to generate training datasets for deep learning algorithms. In this contribution, we leverage a stochastic model, called birth-death-move (BDM) point process, in

Chengzhi Ma, Xi Yang, Jintao Wang, Guanghua Yang

Distributed Antenna Systems (DASs) employ multiple antenna arrays in remote radio units to achieve highly directional transmission and provide great coverage performance for future-generation networks. However, the utilization of active antenna arrays results in a significant increase in hardware costs and power consumption for DAS. To address these issues,

Yongshuai Huang, Ning Lu, Dapeng Chen, Yibo Li

Table structure recognition aims to extract the logical and physical structure of unstructured table images into a machine-readable format. The latest end-to-end image-to-text approaches simultaneously predict the two structures by two decoders, where the prediction of the physical structure (the bounding boxes of the cells) is based on the representation of

Dilpreet Kaur, Pushpendra Singh

Let $K = \mathbb{R}$ or $\mathbb{C}$ and $T_{n}$ denote the Takasaki quandle of order $n$. In this article we provide decomposition of quandle ring $K[T_n]$ as direct sum of right simple ideals. This decomposition is equivalent to decomposition of regular representation \cite{EM18} of Takasaki quandles.

Lorenzo Cazzella, Francesco Linsalata, Maurizio Magarini, Matteo Matteucci

Digital Twins (DTs) for physical wireless environments have been recently proposed as accurate virtual representations of the propagation environment that can enable multi-layer decisions at the physical communication equipment. At high-frequency bands, DTs can help to overcome the challenges emerging in high mobility conditions featuring vehicular environme

Shuangping Huang, Yu Luo, Zhenzhou Zhuang, Jin-Gang Yu

Despite the success of deep neural network (DNN) on sequential data (i.e., scene text and speech) recognition, it suffers from the over-confidence problem mainly due to overfitting in training with the cross-entropy loss, which may make the decision-making less reliable. Confidence calibration has been recently proposed as one effective solution to this prob

Jiaxing Guo, Xuening Zhu, Zixin Hu, Xiaoxi Hu

Protein-protein interactions are of great importance in biochemical processes. Accurate prediction of protein-protein interaction sites (PPIs) is crucial for our understanding of biological mechanism. Although numerous approaches have been developed recently and achieved gratifying results, there are still two limitations: (1) Most existing models have excav

Elena V. Epure, Romain Hennequin

We conducted a human subject study of named entity recognition on a noisy corpus of conversational music recommendation queries, with many irregular and novel named entities. We evaluated the human NER linguistic behaviour in these challenging conditions and compared it with the most common NER systems nowadays, fine-tuned transformers. Our goal was to learn

Haibo Li

The joint bidiagonalization (JBD) process iteratively reduces a matrix pair $\{A,L\}$ to two bidiagonal forms simultaneously, which can be used for computing a partial generalized singular value decomposition (GSVD) of $\{A,L\}$. The process has a nested inner-outer iteration structure, where the inner iteration usually can not be computed exactly. In this p

Zdravko Marinov, Rainer Stiefelhagen, Jens Kleesiek

Interactive segmentation reduces the annotation time of medical images and allows annotators to iteratively refine labels with corrective interactions, such as clicks. While existing interactive models transform clicks into user guidance signals, which are combined with images to form (image, guidance) pairs, the question of how to best represent the guidanc

Fangxia An, M. Vaccari, P. N. Best, E. F. Ocran

By combining high-sensitivity LOFAR 150MHz, uGMRT 400MHz and 1,250MHz, GMRT 610MHz, and VLA 5GHz data in the ELAIS-N1 field, we study the radio spectral properties of radio-detected star-forming galaxies (SFGs) at observer-frame frequencies of 150-5,000MHz. We select ~3,500 SFGs that have both LOFAR 150MHz and GMRT 610MHz detections, and obtain a median two-

Fernando Sancho de Salas, Alejandro Torres Sancho

We give a geometric interpretation of the Stanley--Reisner correspondence, extend it to schemes, and interpret it in terms of the field of one element.

Xiao-Bin Qiang, Z. Z. Du, Hai-Zhou Lu, X. C. Xie

The Wiedemann-Franz law and Mott relation are textbook paradigms on the ratios of the thermal and thermoelectric conductivities to electrical conductivity, respectively. Deviations from them usually reveal insights for intriguing phases of matter. The recent topological kagome magnets TbMn$_6$Sn$_6$ and Mn$_3$Ge show confusingly opposite derivations in the H

Francesco Linsalata, Eugenio Moro, Maurizio Magarini, Umberto Spagnolini

Advances in the automotive industry and the ever-increasing demand for Connected and Autonomous Vehicles (CAVs) are pushing for a new epoch of networked wireless systems. Vehicular communications, or Vehicle-to-Everything (V2X), are expected to be among the main actors of the future beyond 5G and 6G networks. However, the challenging application requirements

Jie Zhang, Chen Chen, Weiming Zhuang, Lingjuan Lv

This paper focuses on an under-explored yet important problem: Federated Class-Continual Learning (FCCL), where new classes are dynamically added in federated learning. Existing FCCL works suffer from various limitations, such as requiring additional datasets or storing the private data from previous tasks. In response, we first demonstrate that non-IID data

E. Petri, R. Postoyan, D. Astolfi, D. Nesic

Various methods are nowadays available to design observers for broad classes of systems, where the primary focus is on establishing the convergence of the estimated states. Nevertheless, the question of the tuning of the observer to achieve satisfactory estimation performance remains largely open. In this context, we present a general design framework for th

Linh Anh Nguyen

The problem of minimizing finite fuzzy interpretations in fuzzy description logics (FDLs) is worth studying. For example, the structure of a fuzzy/weighted social network can be treated as a fuzzy interpretation in FDLs, where actors are individuals and actions are roles. Minimizing the structure of a fuzzy/weighted social network makes it more compact, thus

Tim Puphal, Raphael Wenzel, Benedict Flade, Malte Probst

Self-driving cars face complex driving situations with a large amount of agents when moving in crowded cities. However, some of the agents are actually not influencing the behavior of the self-driving car. Filtering out unimportant agents would inherently simplify the behavior or motion planning task for the system. The planning system can then focus on fewe

Luis Aragón-Muñoz, Hernando Quevedo

The influence of a curved spacetime $M$ on the physical behavior of an ideal gas of $N$ particles is analyzed by considering the phase space of the system as a region of the cotangent bundle $T^{*}M^{N}$ and using Souriau's Lie group {thermodynamics} to define the corresponding probability distribution function. While the construction of the phase space resp

Can Cui, Ziye Jia, Chao Dong, Zhuang Ling

Multi-access edge computing (MEC) is regarded as a promising technology in the sixth-generation communication. However, the antenna gain is always affected by the environment when unmanned aerial vehicles (UAVs) are served as MEC platforms, resulting in unexpected channel errors. In order to deal with the problem and reduce the power consumption in the UAV-b

Talia Fernós, David Futer, Mark Hagen

A finite-dimensional CAT(0) cube complex $X$ is equipped with several well-studied boundaries. These include the Tits boundary (which depends on the CAT(0) metric), the Roller boundary (which depends only on the combinatorial structure), and the simplicial boundary (which also depends only on the combinatorial structure). We use a partial order on a certain

Mohammad Hasan Ahmadilivani, Mahdi Taheri, Jaan Raik, Masoud Daneshtalab

Deep Neural Networks (DNNs) and their accelerators are being deployed ever more frequently in safety-critical applications leading to increasing reliability concerns. A traditional and accurate method for assessing DNNs' reliability has been resorting to fault injection, which, however, suffers from prohibitive time complexity. While analytical and hybrid fa

Zhizhong Huang, Junping Zhang, Hongming Shan

Learning from noisy data is a challenging task that significantly degenerates the model performance. In this paper, we present TCL, a novel twin contrastive learning model to learn robust representations and handle noisy labels for classification. Specifically, we construct a Gaussian mixture model (GMM) over the representations by injecting the supervised m

Yiyuan Chen, Z. Z. Du, Hai-Zhou Lu, X. C. Xie

Using a pure electric current to control kagome noncollinear antiferromagnets is promising in information storage and processing, but a full description is still lacking, in particular, on intrinsic (i.e., no external magnetic fields or external spin currents) spin-orbit torques. In this work, we self-consistently describe the relations among the electronic

Shahnawaz A. Adil, Özgür Akarsu, Mohammad Malekjani, Eoin Ó Colgáin

Hubble constant $H_0$ and weighted amplitude of matter fluctuations $S_8$ determinations are biased to higher and lower values, respectively, in the late Universe with respect to early Universe values inferred by the Planck collaboration within flat $\Lambda$CDM cosmology. If these anomalies are physical, i.e. not due to systematics, they naively suggest tha

Feiyang Tang, Bjarte M. Østvold

The rise of mobile apps has brought greater convenience and customization for users. However, many apps use analytics services to collect a wide range of user interaction data purportedly to improve their service, while presenting app users with vague or incomplete information about this collection in their privacy policies. Typically, such policies neglect

Zhao-Yi Yan, Zhan Hou, Fan Wu, Ruiting Zhao

Two-dimensional materials-based field-effect transistors (2DM-FETs) exhibit both ambipolar and unipolar transport types. To physically and compactly cover both cases, we put forward a quasi-Fermi-level phase space (QFLPS) approach to model the ambipolar effect in our previous work. This work aims to further improve the QFLPS model's numerical aspect so that

Jiahao Xie, Wei Xu, Dingkang Liang, Zhanyu Ma

Crowd counting is a challenging task due to the heavy occlusions, scales, and density variations. Existing methods handle these challenges effectively while ignoring low-resolution (LR) circumstances. The LR circumstances weaken the counting performance deeply for two crucial reasons: 1) limited detail information; 2) overlapping head regions accumulate in d

Zhihao Zhang, Junming Duan, Huazhong Tang

This paper proposes high-order accurate well-balanced (WB) energy stable (ES) adaptive moving mesh finite difference schemes for the shallow water equations (SWEs) with non-flat bottom topography. To enable the construction of the ES schemes on moving meshes, a reformulation of the SWEs is introduced, with the bottom topography as an additional conservative

Jonathan Wagner, Reshef Meir

We present a strategy-proof public goods budgeting mechanism where agents determine both the total volume of expanses and the specific allocation. It is constructed as a modification of VCG to a less typical environment, namely where we do not assume quasi-linear utilities nor direct revelation. We further show that under plausible assumptions it satisfies s

Huyile Liang, Yaling Wang, Yi Wang

The divisibility and congruence of usual and generalized central trinomial coefficients have been extensively investigated. The present paper is devoted to analytic properties of these numbers. We show that usual central trinomial polynomials $T_n(x)$ have only real roots, and roots of $T_n(x)$ interlace those of $T_{n+1}(x)$, as well as those of $T_{n+2}(x)

Vítězslav Kala, Tomáš Kepka, Miroslav Korbelář

It is well known that the full matrix ring over a skew-field is a simple ring. We generalize this theorem to the case of semirings. We characterize the case when the matrix semiring $\mathbf{M}_n(S)$, of all $n\times n$ matrices over a semiring $S$, is congruence-simple, provided that either $S$ has a multiplicatively absorbing element or $S$ is commutative

Kira Maag, Tobias Riedlinger

In recent years, deep neural networks have defined the state-of-the-art in semantic segmentation where their predictions are constrained to a predefined set of semantic classes. They are to be deployed in applications such as automated driving, although their categorically confined expressive power runs contrary to such open world scenarios. Thus, the detect