October 2022 arXiv papers — page 23

Ottavio Fornieri, Heshou Zhang

Cosmic-ray (CR) diffusion is the result of the interaction of such charged particles against magnetic fluctuations. These fluctuations originate from large-scale turbulence cascading towards smaller spatial scales, decomposed into three different modes, as described by $magneto-hydro-dynamics$ (MHD) theory. As a consequence, the description of particle diffu

Sungjun Cho, Seonwoo Min, Jinwoo Kim, Moontae Lee

To overcome the quadratic cost of self-attention, recent works have proposed various sparse attention modules, most of which fall under one of two groups: 1) sparse attention under a hand-crafted patterns and 2) full attention followed by a sparse variant of softmax such as $\alpha$-entmax. Unfortunately, the first group lacks adaptability to data while the

Axel De Nardin, Pankaj Mishra, Gian Luca Foresti, Claudio Piciarelli

Image anomaly detection consists in detecting images or image portions that are visually different from the majority of the samples in a dataset. The task is of practical importance for various real-life applications like biomedical image analysis, visual inspection in industrial production, banking, traffic management, etc. Most of the current deep learning

Damian Owerko, Charilaos I. Kanatsoulis, Jennifer Bondarchuk, Donald J. Bucci

Multi-target tracking (MTT) is a classical signal processing task, where the goal is to estimate the states of an unknown number of moving targets from noisy sensor measurements. In this paper, we revisit MTT from a deep learning perspective and propose a convolutional neural network (CNN) architecture to tackle it. We represent the target states and sensor

Y. A. Malyshkin

In this paper, we prove the first-order convergence law for the uniform attachment random graph with almost all vertices having the same degree. In the considered model, vertices and edges are introduced recursively: at time $m+1$ we start with a complete graph on $m+1$ vertices. At step $n+1$ the vertex $n+1$ is introduced together with $m$ edges joining th

Enda Xiao, Chris A. Marianetti

Cubic phonon interactions are now regularly computed from first principles, and the quartic interactions have begun to receive more attention. Given this realistic anharmonic vibrational Hamiltonian, the classical phonon Green's function can be precisely measured using molecular dynamics, which can then be used to rigorously assess the range of validity for

Sergei A. Avdonin, Kira V. Khmelnytskaya, Vladislav V. Kravchenko

The problem of recovery of a potential on a quantum star graph from Weyl's matrix given at a finite number of points is considered. A method for its approximate solution is proposed. It consists in reducing the problem to a two-spectra inverse Sturm-Liouville problem on each edge with its posterior solution. The overall approach is based on Neumann series of

Gwendal Le Vaillant, Thierry Dutoit

Sound synthesizers are widespread in modern music production but they increasingly require expert skills to be mastered. This work focuses on interpolation between presets, i.e., sets of values of all sound synthesis parameters, to enable the intuitive creation of new sounds from existing ones. We introduce a bimodal auto-encoder neural network, which simult

A. Yu. Polyarush, S. A. Akimenko, A. V. Artamonov, V. N. Bychkov

The paper presents a measurement of the T-odd correlation in radiation decay \boldmath $K^+ \rightarrow \pi^{0} e^{+} \nu_{e} \gamma $ performed on the installation of the 101200 candidate events of the investigated decay were identified. Measured correlation $\xi_{\pi e \gamma}$ -is a mixed product of moments $e^{+}$, $\pi^{0}$, $\gamma$ in the kaon rest sy

Yu Ge, Maximilian Stark, Musa Furkan Keskin, Frank Hofmann

Radio positioning is an important part of joint communication and sensing in beyond 5G communication systems. Existing works mainly focus on the mmWave bands and under-utilize the sub-6 GHz bands, even though it is promising for accurate positioning, especially when the multipath is uncomplicated, and meaningful in several important use cases. In this paper,

Reo Yoneyama, Yi-Chiao Wu, Tomoki Toda

Our previous work, the unified source-filter GAN (uSFGAN) vocoder, introduced a novel architecture based on the source-filter theory into the parallel waveform generative adversarial network to achieve high voice quality and pitch controllability. However, the high temporal resolution inputs result in high computation costs. Although the HiFi-GAN vocoder ach

Friedemann Neuhaus, Matthias Schott, Chen Wang, Rainer Wanke

Several experiments have been proposed in the recent years to study the nature of tau neutrinos, in particular aiming for a first observation of tau anti-neutrinos, more stringent upper limit on its anomalous magnetic moment as well as new constrains on the strange-quark content of the nucleon. We propose here a new low-cost neutrino experiment at the CERN N

Emanuel Laude, Panagiotis Patrinos

This paper studies a novel algorithm for nonconvex composite minimization which can be interpreted in terms of dual space nonlinear preconditioning for the classical proximal gradient method. The proposed scheme can be applied to additive composite minimization problems whose smooth part exhibits an anisotropic descent inequality relative to a reference func

Peng-Tao Wei, Jin-Yu Ni, Xia-Ming Zheng, Da-Yong Liu

Topological magnons in a one-dimensional (1D) ferromagnetic (FM) Su-Schrieffer-Heeger (SSH) model with anisotropic exchange interactions are investigated. Apart from the inter-cellular isotropic Heisenberg interaction, the intercellular anisotropic exchange interactions, i.e. Dzyaloshinskii-Moriya interaction (DMI) and pseudo-dipolar interaction (PDI), also

Hai-Jun Wu, Bing-Shi Yu, Jia-Qi Jiang, Chun-Yu Li

Orbital angular momentum (OAM) conservation plays an important role in shaping and controlling structured light with nonlinear optics. The OAM of a beam originating from three-wave mixing should be the sum or difference of the other two inputs because no light-matter OAM exchange occurs in parametric nonlinear interactions. Here, we report anomalous OAM cons

Ulku Meteriz-Yildiran, Necip Fazil Yildiran, Joongheon Kim, David Mohaisen

The extensive use of smartphones and wearable devices has facilitated many useful applications. For example, with Global Positioning System (GPS)-equipped smart and wearable devices, many applications can gather, process, and share rich metadata, such as geolocation, trajectories, elevation, and time. For example, fitness applications, such as Runkeeper and

Biagio Trimarchi, Lorenzo Gentilini, Fabrizio Schiano, Lorenzo Marconi

The presented paper tackles the problem of modeling an unknown function, and its first $r-1$ derivatives, out of scattered and poor-quality data. The considered setting embraces a large number of use cases addressed in the literature and fits especially well in the context of control barrier functions, where high-order derivatives of the safe set are require

Yun-Hin Chan, Edith C. -H. Ngai

Due to the rapid growth of IoT and artificial intelligence, deploying neural networks on IoT devices is becoming increasingly crucial for edge intelligence. Federated learning (FL) facilitates the management of edge devices to collaboratively train a shared model while maintaining training data local and private. However, a general assumption in FL is that a

Jiale Liu, Yu-Wei Zhan, Xin Luo, Zhen-Duo Chen

Recently, deep cross-modal hashing has gained increasing attention. However, in many practical cases, data are distributed and cannot be collected due to privacy concerns, which greatly reduces the cross-modal hashing performance on each client. And due to the problems of statistical heterogeneity, model heterogeneity, and forcing each client to accept the s

Zhaoxuan Zhu, Hepeng Yao, Laurent Sanchez-Palencia

Quantum simulation of quasicrystals in synthetic bosonic matter now paves the way to the exploration of these intriguing systems in wide parameter ranges. Yet thermal fluctuations in such systems compete with quantum coherence, and significantly affect the zero-temperature quantum phases. Here we determine the thermodynamic phase diagram of interacting boson

L. Magrini, C. Viscasillas Vazquez, L. Spina, S. Randich

The spatial distribution of elemental abundances and their time evolution are among the major constraints to disentangle the scenarios of formation and evolution of the Galaxy. We used the sample of open clusters available in the final release of the Gaia-ESO survey to trace the Galactic radial abundance and abundance to iron ratio gradients, and their time

Daniel Fink, Alison Johnston, Matt Strimas-Mackey, Tom Auer

1. Citizen and community-science (CS) datasets have great potential for estimating interannual patterns of population change given the large volumes of data collected globally every year. Yet, the flexible protocols that enable many CS projects to collect large volumes of data typically lack the structure necessary to keep consistent sampling across years. T

Bowen Shen, Zheng Lin, Yuanxin Liu, Zhengxiao Liu

Transformer-based pre-trained language models (PLMs) mostly suffer from excessive overhead despite their advanced capacity. For resource-constrained devices, there is an urgent need for a spatially and temporally efficient model which retains the major capacity of PLMs. However, existing statically compressed models are unaware of the diverse complexities be

M. G. Blyth, T. -S. Lin, D. Tseluiko

The transition to dripping in the gravity-driven flow of a liquid film under an inclined plate is investigated at zero Reynolds number. Computations are carried out on a periodic domain assuming either a fixed fluid volume or a fixed flow rate for a hierarchy of models: two lubrication models with either linearised curvature or full curvature (the LCM and FC

Oleg Kurnosikov, Muriel Sicot, Emilie Gaudry, Danielle Pierre

A method for subsurface visualization and characterization of hidden subsurface nano-structures based on Scanning Tuneling Microscopy/Spectroscopy (STM/STS) has been developed. The nano-objects buried under a metal surface up to several tens of nanometers can be visualized through the metal surface and characterized with STM without destroying the sample. Th

Gu Zhang, Changki Hong, Tomer Alkalay, Vladimir Umansky

Despite its ubiquity in quantum computation and quantum information, a universally applicable definition of quantum entanglement remains elusive. The challenge is further accentuated when entanglement is associated with other key themes, e.g., quantum interference and quantum statistics. Here, we introduce two novel motifs that characterize the interplay of

Chun-Jie Yang, Qingjun Tong, Jun-Hong An

Cavity magnomechanics has become an ideal platform to explore macroscopic quantum effects. Bringing together magnons, phonons, and photons in a system, it opens many opportunities for quantum technologies. It was conventionally realized by an yttrium iron garnet, which exhibits a parametric magnon-phonon coupling $\hat{m}^\dag\hat{m}(\hat{b}^\dag+\hat{b})$,

Chenyang Li, Zhi-Qi Cheng, Jun-Yan He, Pengyu Li

Streaming perception is a critical task in autonomous driving that requires balancing the latency and accuracy of the autopilot system. However, current methods for streaming perception are limited as they only rely on the current and adjacent two frames to learn movement patterns. This restricts their ability to model complex scenes, often resulting in poor

A. Barcock, D. Cussans, D. Lindebaum, D. Newbold

The DUNE neutrino experiment far detector has a fiducial mass of 40 kt. The O(1M) readout channels are distributed over the four 10 kt modules and need to be synchronized with respect to each other to a precision of O(10 ns). The entire system needs to be synchronized with respect to GPS time to O(100 ns). The system needs to be reliable, simple and affordab

Abbas Gholami, Rupert Klein, Luigi Delle Site

In molecular simulation and fluid mechanics, the coupling of a particle domain with a continuum representation of its embedding environment is an ongoing challenge. In this work, we show a novel approach where the latest version of the adaptive resolution scheme (AdResS), with non-interacting tracers as particles reservoir, is combined with a fluctuating hyd

Gabriel Hartmann, Amos Azaria

In meta-reinforcement learning, an agent is trained in multiple different environments and attempts to learn a meta-policy that can efficiently adapt to a new environment. This paper presents RAMP, a Reinforcement learning Agent using Model Parameters that utilizes the idea that a neural network trained to predict environment dynamics encapsulates the enviro

Lifa Zhu, Changwei Lin, Chen Zheng, Ninghua Yang

Great progress has been made in point cloud classification with learning-based methods. However, complex scene and sensor inaccuracy in real-world application make point cloud data suffer from corruptions, such as occlusion, noise and outliers. In this work, we propose Point-Voxel based Adaptive (PV-Ada) feature abstraction for robust point cloud classificat

Felix Schur, Parnian Kassraie, Jonas Rothfuss, Andreas Krause

Machine learning algorithms are often repeatedly applied to problems with similar structure over and over again. We focus on solving a sequence of bandit optimization tasks and develop LIBO, an algorithm which adapts to the environment by learning from past experience and becomes more sample-efficient in the process. We assume a kernelized structure where th

Annika Briegleb, Mhd Modar Halimeh, Walter Kellermann

In conventional multichannel audio signal enhancement, spatial and spectral filtering are often performed sequentially. In contrast, it has been shown that for neural spatial filtering a joint approach of spectro-spatial filtering is more beneficial. In this contribution, we investigate the spatial filtering performed by such a time-varying spectro-spatial f

Jin-Peng Lan, Zhi-Qi Cheng, Jun-Yan He, Chenyang Li

Existing Visual Object Tracking (VOT) only takes the target area in the first frame as a template. This causes tracking to inevitably fail in fast-changing and crowded scenes, as it cannot account for changes in object appearance between frames. To this end, we revamped the tracking framework with Progressive Context Encoding Transformer Tracker (ProContEXT)

Na Zhang, Shan Jia, Siwei Lyu, Xin Li

The vulnerability of face recognition systems to morphing attacks has posed a serious security threat due to the wide adoption of face biometrics in the real world. Most existing morphing attack detection (MAD) methods require a large amount of training data and have only been tested on a few predefined attack models. The lack of good generalization properti

Isaac Goldbring, Bradd Hart

We introduce the notion of a Tsirelson pair of C*-algebras, which is a pair of C*-algebras for which the space of quantum strategies obtained by using states on the minimal tensor product of the pair and the space of quantum strategies obtained by using states on the maximal tensor product of the pair coincide. We exhibit a number of examples of such pairs t

Isaac Goldbring, Bradd Hart

We survey the developments in the model theory of tracial von Neumann algebras that have taken place in the last fifteen years. We discuss the appropriate first-order language for axiomatizing this class as well as the subclass of II$_1$ factors. We discuss how model-theoretic ideas were used to settle a variety of questions around isomorphism of ultrapowers

Masud Chaichian, Amir Ghal'e, Markku Oksanen

The $R+R^2$ model of gravity with the corresponding shallow potential in the Einstein frame is consistent with the observations. Recently, many efforts have been made to generalize the $R+R^2$ (Starobinsky) model of inflation or use other shallow potentials to construct a model for the early Universe. We revise the question about the shallow potential. We pr

Mieczysław A. Kłopotek, Robert A. Kłopotek

The paper points at the grieving problems implied by the richness axiom in the Kleinberg's axiomatic system and suggests resolutions. The richness induces learnability problem in general and leads to conflicts with consistency axiom. As a resolution, learnability constraints and usage of centric consistency or restriction of the domain of considered clusteri

Evandro C. R. da Rosa, Claudio Lima

Quantum computing is an emerging paradigm that opens a new era for exponential computational speedup. Still, quantum computers have yet to be ready for commercial use. However, it is essential to train and qualify today the workforce that will develop quantum acceleration solutions to get the quantum advantage in the future. This tutorial gives a broad view

Enikő Zakar-Polyák, Marcell Nagy, Roland Molontay

Numerous network models have been investigated to gain insights into the origins of fractality. In this work, we introduce two novel network models, to better understand the growing mechanism and structural characteristics of fractal networks. The Repulsion Based Fractal Model (RBFM) is built on the well-known Song-Havlin-Makse (SHM) model, but in RBFM repul

Navid Kayhani, Angela Schoellig, Brenda McCabe

Tag-based visual-inertial localization is a lightweight method for enabling autonomous data collection missions of low-cost unmanned aerial vehicles (UAVs) in indoor construction environments. However, finding the optimal tag configuration (i.e., number, size, and location) on dynamic construction sites remains challenging. This paper proposes a perception-a

Alexander Felski, Alireza Beygi, S. P. Klevansky

We investigate the impact of non-Hermiticity on the thermodynamic properties of interacting fermions by examining bilinear extensions to the $3+1$ dimensional $SU(2)$-symmetric Nambu--Jona-Lasinio (NJL) model of quantum chromodynamics at finite temperature and chemical potential. The system is modified through the anti-$PT$-symmetric pseudoscalar bilinear $\

C. Quesne

By using a point canonical transformation starting from the constant-mass Schr\"odinger equation for the Morse potential, it is shown that a semi-infinite quantum well model with a non-rectangular profile associated with a position-dependent mass that becomes infinite for some negative value of the position, while going to a constant for a large positive val

Manish Verma, Rossitza Pentcheva

Using a combination of density functional theory calculations with an on-site Coulomb repulsion term (DFT+$U$) and Boltzmann transport theory within the constant relaxation time approximation, we explore the effect of oxygen vacancies on the electronic, magnetic, and thermoelectric properties in ultrathin (LaNiO$_{3-\delta}$)$_1$/(LaAlO$_{3}$)$_1$(001) super

Md Ferdous Pervej, Richeng Jin, Huaiyu Dai

This paper proposes a vehicular edge federated learning (VEFL) solution, where an edge server leverages highly mobile connected vehicles' (CVs') onboard central processing units (CPUs) and local datasets to train a global model. Convergence analysis reveals that the VEFL training loss depends on the successful receptions of the CVs' trained models over the i

Alejandro Gonzalez-Hevia, Daniel Gayo-Avello

Knowledge graphs have been adopted in many diverse fields for a variety of purposes. Most of those applications rely on valid and complete data to deliver their results, pressing the need to improve the quality of knowledge graphs. A number of solutions have been proposed to that end, ranging from rule-based approaches to the use of probabilistic methods, bu

Pan Wang, Jie Li, Jieru Chen, Lin Wang

In this paper, a convolutional sparse coding method based on global structure characteristics and spectral correlation is proposed for the reconstruction of compressive spectral images. The spectral data is regarded as the convolution sum of the convolution kernel and the corresponding coefficients, using the convolution kernel operates the global image info

Ekkasit Pinyoanuntapong, Ayman Ali, Pu Wang, Minwoo Lee

Most existing gait recognition methods are appearance-based, which rely on the silhouettes extracted from the video data of human walking activities. The less-investigated skeleton-based gait recognition methods directly learn the gait dynamics from 2D/3D human skeleton sequences, which are theoretically more robust solutions in the presence of appearance ch

Annalisa Baldi, Francescopaolo Montefalcone

We define a BV -type space in the setting of Carnot groups (i.e., simply connected Lie groups with stratified nilpotent Lie algebra) that allows one to characterize all distributions F for which there exists a continuous horizontal vector field {\Phi}, vanishing at infinity, that solves the equation divH{\Phi} = F. This generalize to the setting of Carnot gr

Ch. Rab, M. Weber, T. Grassi, B. Ercolano

Winds in protoplanetary disks play an important role in their evolution and dispersal. However, what physical process is driving the winds is still unclear (i.e. magnetically vs thermally driven), and can only be understood by directly confronting theoretical models with observational data. We use hydrodynamic photoevaporative disk-wind models and post-proce

Wesley C. Campbell, Eric R. Hudson

We describe the encoding of multiple qubits per atom in trapped atom quantum processors and methods for performing both intra- and inter-atomic gates on participant qubits without disturbing the spectator qubits stored in the same atoms. We also introduce techniques for selective state preparation and measurement of individual qubits that leave the informati

Mahmut Can Bozyiğit, Murat Olgun, Mehmet Ünver

In this paper, we introduce the concept of circular Pythagorean fuzzy set (value) (C-PFS(V)) as a new generalization of both circular intuitionistic fuzzy sets (C-IFSs) proposed by Atannassov and Pythagorean fuzzy sets (PFSs) proposed by Yager. A circular Pythagorean fuzzy set is represented by a circle that represents the membership degree and the non-membe

el Houcein el Abdalaoui

We present a simple proof on the existence of $L^1$-flat analytic polynomials with coefficients $0,1$ on the circle and on the real line and we give an example of a conservative ergodic map and flow whose unitary operators admits a simple Lebesgue spectrum. Among other results, we obtain an answer to Bourgain's question on the supremum of $L^1$-norm of such

Leonie Basso, Zhao Ren, Wolfgang Nejdl

Atrial fibrillation (AF) is the most common cardiac arrhythmia and associated with a high risk for serious conditions like stroke. The use of wearable devices embedded with automatic and timely AF assessment from electrocardiograms (ECGs) has shown to be promising in preventing life-threatening situations. Although deep neural networks have demonstrated supe

Vittorio Lippi, Christoph Maurer, Thomas Mergner

Similarly to humans, humanoid robots require posture control and balance to walk and interact with the environment. In this work posture control in perturbed conditions is evaluated as a performance test for humanoid control. A specific performance indicator is proposed: the score is based on the comparison between the body sway of the tested humanoid standi

Hasna Nhaila, Asma Elmaizi, Elkebir Sarhrouni, Ahmed Hammouch

Band selection is a great challenging task in the classification of hyperspectral remotely sensed images HSI. This is resulting from its high spectral resolution, the many class outputs and the limited number of training samples. For this purpose, this paper introduces a new filter approach for dimension reduction and classification of hyperspectral images u

Tiancheng Hu, Manoel Horta Ribeiro, Robert West, Andreas Spitz

According to journalistic standards, direct quotes should be attributed to sources with objective quotatives such as "said" and "told", as nonobjective quotatives, like "argued" and "insisted" would influence the readers' perception of the quote and the quoted person. In this paper, we analyze the adherence to this journalistic norm to study trends in object

Jiwei Li, Liangliang Su, Lei Wu, Bin Zhu

The ionization signal provide an important avenue of detecting light dark matter. In this work, we consider the sub-GeV inelastic dark matter and use the non-relativistic effective field theory (NR-EFT) to derive the constraints on the spin-dependent DM-electron scattering and DM-nucleus Migdal scattering. Since the recoil electron spectrum of sub-GeV DM is

Samuel W. Yee, Joshua N. Winn, Joel D. Hartman, Luke G. Bouma

NASA's Transiting Exoplanet Survey Satellite (TESS) mission promises to improve our understanding of hot Jupiters by providing an all-sky, magnitude-limited sample of transiting hot Jupiters suitable for population studies. Assembling such a sample requires confirming hundreds of planet candidates with additional follow-up observations. Here, we present twen

Jiaxi Ying, José Vinícius de M. Cardoso, Daniel P. Palomar

We consider the problem of estimating (diagonally dominant) M-matrices as precision matrices in Gaussian graphical models. These models exhibit intriguing properties, such as the existence of the maximum likelihood estimator with merely two observations for M-matrices \citep{lauritzen2019maximum,slawski2015estimation} and even one observation for diagonally

Raphaël Ollando, Seung Yeob Shin, Lionel C. Briand

Software-defined networks (SDN) enable flexible and effective communication systems that are managed by centralized software controllers. However, such a controller can undermine the underlying communication network of an SDN-based system and thus must be carefully tested. When an SDN-based system fails, in order to address such a failure, engineers need to

Frank Yannick Massoda Tchoussi, Francesco Finazzi

Smartphone-based earthquake early warning systems (EEWS) are emerging as a complementary solution to classic EEWS based on expensive scientific-grade instruments. Smartphone-based systems, however, are characterized by a highly dynamic network geometry and by noisy measurements. Thus the need to control the probability of false alarm and the probability of m

Adam Hutchinson, Silvia Dalla, Timo Laitinen, Charlotte O. G. Waterfall

Corotation of particle-filled magnetic flux tubes is generally thought to have a minor influence on the time-intensity profiles of gradual Solar Energetic Particle (SEP) events. For this reason many models solve the focussed transport equation within the corotating frame, thus neglecting corotation effects. We study the effects of corotation on gradual SEP i

Zichao Meng, Ye Guo, Wenjun Tang, Hongbin Sun

This paper proposes a nonparametric multivariate density forecast model based on deep learning. It not only offers the whole marginal distribution of each random variable in forecasting targets, but also reveals the future correlation between them. Differing from existing multivariate density forecast models, the proposed method requires no a priori hypothes

Amanda Bertsch, Graham Neubig, Matthew R. Gormley

In this work, we define a new style transfer task: perspective shift, which reframes a dialogue from informal first person to a formal third person rephrasing of the text. This task requires challenging coreference resolution, emotion attribution, and interpretation of informal text. We explore several baseline approaches and discuss further directions on th

Hengwei Zhao, Yanfei Zhong, Xinyu Wang, Hong Shu

Hyperspectral imagery (HSI) one-class classification is aimed at identifying a single target class from the HSI by using only knowing positive data, which can significantly reduce the requirements for annotation. However, when one-class classification meets HSI, it is difficult for classifiers to find a balance between the overfitting and underfitting of pos

K. Mojsilovic, N. Bozovic, S. Stojanovic, L. Damjanovic-Vasilic

The preparation and properties of zeolite-containing oxide coatings obtained by plasma electrolytic oxidation are investigated and discussed. Pure and Ce-exchanged natural (clinoptilolite) and synthetic (13X) zeolites are immobilized on aluminum support from silicate-based electrolyte. Obtained coatings are characterized with respect to their morphology, pha

Lukas Koch

This pre-print has now been superseded by arXiv:2305.19934 and will not be published. We prove that for convex vectorial functionals with (p,q)-growth the Lavrentiev phenomenon does not occur up to the boundary when (p,q) are suitably restricted. Under minimal assumptions on the regularity of the domain and the boundary data, we obtain results for autonomous

Aleksandr S. Baburin, Dmitriy O. Moskalev, Evgeniy S. Lotkov, Olga S. Sorokina

High-quality factor plasmonic devices are crucial components in the fields of nanophotonics, quantum computing and sensing. The majority of these devices are required to be fabricated on non-lattice matched or transparent amorphous substrates. Plasmonic devices quality factor is mainly defined by ohmic losses, scattering losses at grain boundaries, and in-pl

Takaaki Saeki, Heiga Zen, Zhehuai Chen, Nobuyuki Morioka

This paper proposes Virtuoso, a massively multilingual speech-text joint semi-supervised learning framework for text-to-speech synthesis (TTS) models. Existing multilingual TTS typically supports tens of languages, which are a small fraction of the thousands of languages in the world. One difficulty to scale multilingual TTS to hundreds of languages is colle

Varun Mandalapu, Lujie Karen Chen, Sushruta Shetty, Zhiyuan Chen

In recent years, there is a lot of interest in modeling students' digital traces in Learning Management System (LMS) to understand students' learning behavior patterns including aspects of meta-cognition and self-regulation, with the ultimate goal to turn those insights into actionable information to support students to improve their learning outcomes. In ac

Viktoria Heimann, Andreas Spruck, André Kaup

Neural networks became the standard technique for image classification throughout the last years. They are extracting image features from a large number of images in a training phase. In a following test phase, the network is applied to the problem it was trained for and its performance is measured. In this paper, we focus on image classification. The amount

M. Serdechnova, C. Blawert, S. Karpushenkov, L. Karpushenkava

Recently the successful formation of PEO coatings on zinc in a phosphate aluminate electrolyte was shown. The produced composite coatings contain various mixtures of ZnO and ZnAl$_2$O$_4$. In frame of the current study, the properties of the formed coatings including adhesion/cohesion, wear, corrosion and photocatalytic activity were analysed to identify pos

Anna Silnova, Niko Brümmer, Albert Swart, Lukáš Burget

In speaker recognition, where speech segments are mapped to embeddings on the unit hypersphere, two scoring back-ends are commonly used, namely cosine scoring and PLDA. We have recently proposed PSDA, an analog to PLDA that uses Von Mises-Fisher distributions instead of Gaussians. In this paper, we present toroidal PSDA (T-PSDA). It extends PSDA with the abi

Mahmut Elbistan, Efe Hamamci, Dieter Van den Bleeken, Utku Zorba

Expanding General Relativity in the inverse speed of light, 1/c, leads to a nonrelativistic gravitational theory that extends the Post-Newtonian expansion by the inclusion of additional strong gravitational potentials. This theory has a fully covariant formulation in the language of Newton-Cartan geometry but we revisit it here in a 3+1 formulation. The appr

Frank Elson, Debarchan Das, Gediminas Simutis, Ola Kenji Forslund

For quantum systems or materials, a common procedure for probing their behaviour is to tune electronic/magnetic properties using external parameters, e.g. temperature, magnetic field or pressure. Pressure application as an external stimuli is a widely used tool, where the sample in question is inserted into a pressure cell providing a hydrostatic pressure co

Giulia Cavicchioni, Alessio Meneghetti

In this work, we determine new linear equations for the weight distribution of linear codes over finite chain rings. The identities are determined by counting the number of some special submatrices of the parity-check matrix of the code. Thanks to these relations we are able to compute the full weight distribution of codes with small Singleton defects, such

Yuri Kanno, Muneki Yasuda

An extreme learning machine (ELM) is a three-layered feed-forward neural network having untrained parameters, which are randomly determined before training. Inspired by the idea of ELM, a probabilistic untrained layer called a probabilistic-ELM (PELM) layer is proposed, and it is combined with a discriminative restricted Boltzmann machine (DRBM), which is a

Fitash Ul Haq, Donghwan Shin, Lionel Briand

Deep Neural Networks (DNNs) have been widely used to perform real-world tasks in cyber-physical systems such as Autonomous Driving Systems (ADS). Ensuring the correct behavior of such DNN-Enabled Systems (DES) is a crucial topic. Online testing is one of the promising modes for testing such systems with their application environments (simulated or real) in a

Saeedeh Sadeghian

We investigate the Hamilton-Jacobi equation of a probe particle moving on d-dimensional generalized Lense-Thirring metric. This space-time is different from the slowly rotating Myers-Perry black hole at second order in rotation parameters. We show that the dynamics of the probe particle along the time-like geodesic of the generalized Lense-Thirring space-tim

Jørgen Jensen Farner, Ola Huse Ramstad, Stefano Nichele, Kristine Heiney

We propose a novel local learning rule for spiking neural networks in which spike propagation times undergo activity-dependent plasticity. Our plasticity rule aligns pre-synaptic spike times to produce a stronger and more rapid response. Inputs are encoded by latency coding and outputs decoded by matching similar patterns of output spiking activity. We demon

Matan Karo, Arie Yeredor, Itshak Lapidot

Anti-spoofing is the task of speech authentication. That is, identifying genuine human speech compared to spoofed speech. The main focus of this paper is to suggest new representations for genuine and spoofed speech, based on the probability mass function (PMF) estimation of the audio waveforms' amplitude. We introduce a new feature extraction method for spe

Willem Boon, Marjolein Dijkstra, René van Roij

While important for many industrial applications, chemical reactions responsible for charging of solids in water are often poorly understood. We theoretically investigate the charging kinetics of solid-liquid interfaces, and find that the time-dependent equilibration of surface charge contains key information not only on the reaction mechanism, but also on t

Teven Le Scao, Thomas Wang, Daniel Hesslow, Lucile Saulnier

The crystallization of modeling methods around the Transformer architecture has been a boon for practitioners. Simple, well-motivated architectural variations can transfer across tasks and scale, increasing the impact of modeling research. However, with the emergence of state-of-the-art 100B+ parameters models, large language models are increasingly expensiv

Florian Frick, Samuel Murray, Steven Simon, Laura Stemmler

The classical Ham Sandwich theorem states that any $d$ point sets in $\mathbb{R}^d$ can be simultaneously bisected by a single affine hyperplane. A generalization of Dolnikov asserts that any $d$ families of pairwise intersecting compact, convex sets in $\mathbb{R}^d$ admit a common hyperplane transversal. We extend Dolnikov's theorem by showing that familie

Hasna Nhaila, Asma Elmaizi, Elkebir Sarhrouni, Ahmed Hammouch

Nowadays, the hyperspectral remote sensing imagery HSI becomes an important tool to observe the Earth's surface, detect the climatic changes and many other applications. The classification of HSI is one of the most challenging tasks due to the large amount of spectral information and the presence of redundant and irrelevant bands. Although great progresses h

Diego Ulisse Pizzagalli, Rolf Krause

Images conveniently capture the result of physical processes, representing rich source of information for data driven medicine, engineering, and science. The modeling of an image as a graph allows the application of graph-based algorithms for content analysis. Amongst these, one of the most used is the Dijkstra Single Source Shortest Path algorithm (DSSSP),

Bin Han, Dennis Krummacker, Qiuheng Zhou, Hans D. Schotten

Enabled by the emerging industrial agent (IA) technology, swarm intelligence (SI) is envisaged to play an important role in future industrial Internet of Things (IIoT) that is shaped by Sixth Generation (6G) mobile communications and digital twin (DT). However, its fragility against data injection attack may halt it from practical deployment. In this paper w

Jingyi li, Weiping tu, Li xiao

Voice conversion (VC) can be achieved by first extracting source content information and target speaker information, and then reconstructing waveform with these information. However, current approaches normally either extract dirty content information with speaker information leaked in, or demand a large amount of annotated data for training. Besides, the qu

I. L. Bartolom/'e, L. Errico, V. Fernandez, M. Matera

A theoretical model for two new tellurite-sulfates, namely Na$_2$Cu$_5$(TeO$_3$)(SO$_4$)$_3$(OH)$_4$ and K$_2$Cu$_5$(TeO$_3$)(SO$_4$)$_3$ (OH)$_4$ is determined to be compatible with ab-initio calculations. The results obtained in this work show that some previous speculations in the literature about the couplings are correct, obtaining a model with a mixtur

Jun-Cheng Chin, Tyler Cultice, Himanshu Thapliyal

Additive Manufacturing (AM) is gaining renewed popularity and attention due to low-cost fabrication systems proliferating the market. Current communication protocols used in AM limit the connection flexibility between the control board and peripherals; they are often complex in their wiring and thus restrict their avenue of expansion. Thus, the Controller Ar

Zhongzhan Huang, Senwei Liang, Mingfu Liang, Liang Lin

The self-attention mechanism has emerged as a critical component for improving the performance of various backbone neural networks. However, current mainstream approaches individually incorporate newly designed self-attention modules (SAMs) into each layer of the network for granted without fully exploiting their parameters' potential. This leads to suboptim

ATLAS Collaboration

A search for the pair-production of vector-like quarks optimized for decays into a $Z$ boson and a third-generation Standard Model quark is presented, using the full Run 2 dataset corresponding to 139 fb$^{-1}$ of $pp$ collisions at $\sqrt{s}=13$ TeV, collected in 2015-2018 with the ATLAS detector at the Large Hadron Collider. The targeted final state is cha

Luca Nicoli, Tommaso Giovannini, Chiara Cappelli

The performance of different Quantum Mechanics/Molecular Mechanics embedding models to compute vacuo-to-water solvatochromic shifts are investigated. In particular, both non-polarizable and polarizable approaches are analyzed and computed results as compared to reference experimental data. We show that none of the approaches outperforms the others and that e

Yi-Xiao Tao, Qi Chen

Unifying relations of amplitudes are elegant results in flat spacetime, but the research on these in (A)dS case is not very rich. In this paper, we discuss a type of unifying relations in (A)dS by using Berends-Giele currents. By taking the flat limit, we also get a semi-on-shell way to prove the unifying relations in the flat case. We also discuss the appli

Vincenzo Perri, Luka V. Petrović, Ingo Scholtes

Many network analysis and graph learning techniques are based on models of random walks which require to infer transition matrices that formalize the underlying stochastic process in an observed graph. For weighted graphs, it is common to estimate the entries of such transition matrices based on the relative weights of edges. However, we are often confronted

Wilson Jallet, Antoine Bambade, Nicolas Mansard, Justin Carpentier

Trajectory optimization is an efficient approach for solving optimal control problems for complex robotic systems. It relies on two key components: first the transcription into a sparse nonlinear program, and second the corresponding solver to iteratively compute its solution. On one hand, differential dynamic programming (DDP) provides an efficient approach

M. Iskin

We consider a weakly-interacting Bose-Einstein condensate (BEC) that is loaded into an optical lattice with a two-point basis, and described by a two-band Bose-Hubbard model with generic one-body and two-body terms. By first projecting the system to the lower Bloch band and then applying the Bogoliubov approximation to the resultant Hamiltonian, we show that