July 2022 arXiv papers — page 86

Jooyeol Yun, Sanghyeon Lee, Minho Park, Jaegul Choo

Point-interactive image colorization aims to colorize grayscale images when a user provides the colors for specific locations. It is essential for point-interactive colorization methods to appropriately propagate user-provided colors (i.e., user hints) in the entire image to obtain a reasonably colorized image with minimal user effort. However, existing appr

A. Gogoi, J. C. Mandal

A simple HLLE-type scheme is proposed for all Mach number flows. In the proposed scheme, no extra wave structure is added in the HLLE scheme to resolve the shear wave while the contact wave is resolved by adding a wave structure similar to the HLLEM scheme. The resolution of the shear layers and the flow features at low Mach number are achieved by a velocity

Jinhua Zhu, Yingce Xia, Lijun Wu, Shufang Xie

Molecular representation learning has attracted much attention recently. A molecule can be viewed as a 2D graph with nodes/atoms connected by edges/bonds, and can also be represented by a 3D conformation with 3-dimensional coordinates of all atoms. We note that most previous work handles 2D and 3D information separately, while jointly leveraging these two so

Maciek Wielgus, Nicola Marchili, Ivan Marti-Vidal, Garrett K. Keating

The Event Horizon Telescope (EHT) observed the compact radio source, Sagittarius A* (Sgr A*), in the Galactic Center on 2017 April 5-11 in the 1.3 millimeter wavelength band. At the same time, interferometric array data from the Atacama Large Millimeter/submillimeter Array and the Submillimeter Array were collected, providing Sgr A* light curves simultaneous

Haozheng Zhang, Edmond S. L. Ho, Xiatian Zhang, Hubert P. H. Shum

Parkinson's disease (PD) is a progressive neurodegenerative disorder that results in a variety of motor dysfunction symptoms, including tremors, bradykinesia, rigidity and postural instability. The diagnosis of PD mainly relies on clinical experience rather than a definite medical test, and the diagnostic accuracy is only about 73-84% since it is challenged

Pengfei Chen, Xuehui Yu, Xumeng Han, Najmul Hassan

Object detection using single point supervision has received increasing attention over the years. However, the performance gap between point supervised object detection (PSOD) and bounding box supervised detection remains large. In this paper, we attribute such a large performance gap to the failure of generating high-quality proposal bags which are crucial

Nathaniel Capote-Robayna, Olga Matveeva, Valentyn S. Volkov, Pablo Alonso-González

Polaritons - hybrid light-mater excitations - are very appealing for the confinement of light at the nanoscale. Recently, different kinds of polaritons have been observed in thin slabs of van der Waals (vdW) materials, with particular interest focused on phonon polaritons (PhPs) - lattice vibrations coupled to electromagnetic fields in the mid-infrared spect

David Bruggemann, Christos Sakaridis, Prune Truong, Luc Van Gool

Due to the scarcity of dense pixel-level semantic annotations for images recorded in adverse visual conditions, there has been a keen interest in unsupervised domain adaptation (UDA) for the semantic segmentation of such images. UDA adapts models trained on normal conditions to the target adverse-condition domains. Meanwhile, multiple datasets with driving s

Jean-Pierre Magnot

We consider here the category of diffeological vector pseudo-bundles, and study a possible extension of classical differential geometric tools on finite dimensional vector bundles, namely, the group of automorphisms, the frame bundle, the space of connection 1-forms and the space of covariant derivatives. Substential distinctions are highlighted in this gene

Nandhinee PR, Harinath Krishnamoorthy, Koushik Srivatsan, Anil Goyal

In this paper, we propose DEXTER, an end to end system to extract information from tables present in medical health documents, such as electronic health records (EHR) and explanation of benefits (EOB). DEXTER consists of four sub-system stages: i) table detection ii) table type classification iii) cell detection; and iv) cell content extraction. We propose a

Neetu R R, Gourab Ghatak, Anand Srivastava, Vivek Ashok Bohara

We study an urban wireless network in which cache-enabled UAV-Access points (UAV-APs) and UAV-Base stations (UAV-BSs) are deployed to provide higher throughput and ad-hoc coverage to users on the ground. The cache-enabled UAV-APs route the user data to the core network via either terrestrial base stations (TBSs) or backhaul-enabled UAV-BSs through an xHaul l

Thijs Kooi

The idea of using computers to read medical scans was introduced as early as 1966. However, limits to machine learning technology meant progress was slow initially. The Alexnet breakthrough in 2012 sparked new interest in the topic, which resulted in the release of 100s of medical AI solutions on the market. In spite of success for some diseases and modaliti

Marek Balcerzak, Jacek Hejduk, Artur Wachowicz

We prove that the lower density operator associated with the Baire category density points in the real line has Borel values of class $\pmb \Pi^0_3$ which is analogous to the measure case. We also introduce the notion of the Baire category density point of a subset with the Baire property of the Cantor space, and we prove that it generates a lower density op

Sweta Singh, Vaibhav Kulkarni, Mario Briggs, Deepak Mahajan

Directed Acyclic Graphs (DAGs) are commonly used in Databases and Big Data computational engines like Apache Spark for representing the execution plan of queries. We refer to such graphs as Query Directed Acyclic Graphs (QDAGs). This paper uses similarity hashing to arrive at a fingerprint such that the fingerprint embodies the compute requirements of the qu

Evan Caville, Wai Weng Lo, Siamak Layeghy, Marius Portmann

This paper investigates Graph Neural Networks (GNNs) application for self-supervised network intrusion and anomaly detection. GNNs are a deep learning approach for graph-based data that incorporate graph structures into learning to generalise graph representations and output embeddings. As network flows are naturally graph-based, GNNs are a suitable fit for

V. M. Braun, Yao Ji, Jakob Schoenleber

Deeply-virtual Compton scattering gives access to the generalized parton distributions that encode the information on the transverse position of quarks and gluons in the proton in dependence in their longitudinal momentum. In anticipation of the high-precision experimental data in a broad kinematic range from the Electron-Ion Collider, we have calculated the

Xingping Dong, Tianran Ouyang, Shengcai Liao, Bo Du

Most existing few-shot learning (FSL) methods require a large amount of labeled data in meta-training, which is a major limit. To reduce the requirement of labels, a semi-supervised meta-training (SSMT) setting has been proposed for FSL, which includes only a few labeled samples and numbers of unlabeled samples in base classes. However, existing methods unde

N. -E. Nèmec, A. I. Shapiro, E. Işık, K. Sowmya

Surfaces of the Sun and other cool stars are filled with magnetic fields, which are either seen as dark compact spots or more diffuse bright structures like faculae. Both hamper detection and characterisation of exoplanets, affecting stellar brightness and spectra, as well as transmission spectra. However, the expected facular and spot signals in stellar dat

Riccardo Giubilato, Wolfgang Stürzl, Armin Wedler, Rudolph Triebel

We present the DLR Planetary Stereo, Solid-State LiDAR, Inertial (S3LI) dataset, recorded on Mt. Etna, Sicily, an environment analogous to the Moon and Mars, using a hand-held sensor suite with attributes suitable for implementation on a space-like mobile rover. The environment is characterized by challenging conditions regarding both the visual and structur

Javier de la Rosa, Eduardo G. Ponferrada, Paulo Villegas, Pablo Gonzalez de Prado Salas

The pre-training of large language models usually requires massive amounts of resources, both in terms of computation and data. Frequently used web sources such as Common Crawl might contain enough noise to make this pre-training sub-optimal. In this work, we experiment with different sampling methods from the Spanish version of mC4, and present a novel data

Ernesto Estrada, Jesús Gómez-Gardeñes, Lucas Lacasa

Real-world networks are neither regular nor random, a fact elegantly explained by mechanisms such as the Watts-Strogatz or the Barabasi-Albert models, among others. Both mechanisms naturally create shortcuts and hubs, which while enhancing network's connectivity, also might yield several undesired navigational effects: they tend to be overused during geodesi

Andrea Asperti, Valerio Tonelli

Different encodings of datapoints in the latent space of latent-vector generative models may result in more or less effective and disentangled characterizations of the different explanatory factors of variation behind the data. Many works have been recently devoted to the explorationof the latent space of specific models, mostly focused on the study of how f

Christoph Reile, Mohak Chadha, Valentin Hauner, Anshul Jindal

Microservice architecture is the common choice for cloud applications these days since each individual microservice can be independently modified, replaced, and scaled. However, the complexity of microservice applications requires automated testing with a focus on the interactions between the services. While this is achievable with end-to-end tests, they are

Geethan Karunaratne, Michael Hersche, Jovin Langenegger, Giovanni Cherubini

Continually learning new classes from a few training examples without forgetting previous old classes demands a flexible architecture with an inevitably growing portion of storage, in which new examples and classes can be incrementally stored and efficiently retrieved. One viable architectural solution is to tightly couple a stationary deep neural network to

Aurélien Drezet

In this work we develop a time-symmetric soliton theory for quantum particles inspired from works by de Broglie and Bohm. We consider explicitly a non-linear Klein-Gordon theory leading to monopolar oscillating solitons. We show that the theory is able to reproduce the main results of the pilot-wave interpretation for non interacting particles in a external

André V. G. Cavalieri, Petrônio A. S. Nogueira

Reduced-order models were derived for plane Couette flow using Galerkin projection, with orthonormal basis functions taken as the leading controllability modes of the linearised Navier-Stokes system for a few low wavenumbers. Resulting Galerkin systems comprise ordinary differential equations, with a number of degrees of freedom ranging from 144 to 600, whic

Wontae Kim, Juha Kinnunen, Kristian Moring

We prove local higher integrability of the gradient of a weak solution to a degenerate parabolic double-phase system. This result comes with a reverse H\"older type estimate for the gradient. The proof is based on estimates in the intrinsic geometry and stopping time arguments.

Efstratios Stratoglou, Alexandre Anahory Simoes, Leonardo J. Colombo

We study the reduction by symmetry for optimality conditions in optimal control problems of left-invariant affine multi-agent control systems, with partial symmetry breaking cost functions for continuous-time and discrete-time systems. We recast the optimal control problem as a constrained variational problem with a partial symmetry breaking Lagrangian and o

Seok-Hyung Lee, Srikrishna Omkar, Yong Siah Teo, Hyunseok Jeong

Measurement-based quantum computing (MBQC) in linear optical systems is promising for near-future quantum computing architecture. However, the nondeterministic nature of entangling operations and photon losses hinder the large-scale generation of graph states and introduce logical errors. In this work, we propose a linear optical topological MBQC protocol em

Vincenzo Sapienza, Marco Miceli, Aya Bamba, Satoru Katsuda

Synchrotron X-ray emission in young supernova remnants (SNRs) is a powerful diagnostic tool to study the population of high energy electrons accelerated at the shock front and the acceleration process. We performed a spatially resolved spectral analysis of NuSTAR and XMM-Newton observations of the young Kepler's SNR, aiming to study in detail its non-thermal

Yifei He, Artur Podobas, Måns I. Andersson, Stefano Markidis

Discrete Fourier Transform (DFT) libraries are one of the most critical software components for scientific computing. Inspired by FFTW, a widely used library for DFT HPC calculations, we apply compiler technologies for the development of HPC Fourier transform libraries. In this work, we introduce FFTc, a domain-specific language, based on Multi-Level Interme

Jeshuren Chelladurai, Sudarsun Santhiappan, Balaraman Ravindran

Automated medical coding is a process of codifying clinical notes to appropriate diagnosis and procedure codes automatically from the standard taxonomies such as ICD (International Classification of Diseases) and CPT (Current Procedure Terminology). The manual coding process involves the identification of entities from the clinical notes followed by querying

Nils Jansen, Sebastian Junges, Joost-Pieter Katoen

This paper surveys the analysis of parametric Markov models whose transitions are labelled with functions over a finite set of parameters. These models are symbolic representations of uncountable many concrete probabilistic models, each obtained by instantiating the parameters. We consider various analysis problems for a given logical specification $\varphi$

Giovanni Nastasi, Vittorio Romano

Some properties of the electron-electron collision operator in graphene are analyzed along with the evaluation of collision rate. Monte Carlo simulations complete the study and highlight the non-negligible role of the electron-electron scattering for an accurate evaluation of the currents and, as a consequence, of the characteristic curves.

Qi Zhao, Shuchang Lyu, Wenpei Bai, Linghan Cai

Ovarian cancer is one of the most harmful gynecological diseases. Detecting ovarian tumors in early stage with computer-aided techniques can efficiently decrease the mortality rate. With the improvement of medical treatment standard, ultrasound images are widely applied in clinical treatment. However, recent notable methods mainly focus on single-modality ul

Deepak Raikwal, Sandhya Choubey, Monojit Ghosh

In this paper we study the synergy among the future accelerator (T2HK), future atmospheric (ICAL) and future reactor (JUNO) neutrino experiments to determine the neutrino mass ordering. T2HK can measure the mass ordering only for favorable values of $\delta_{\rm CP}$, whereas the mass ordering sensitivity of JUNO is dependent on the energy resolution. Our re

Jürgen Seiler, André Kaup

Image signals typically are defined on a rectangular two-dimensional grid. However, there exist scenarios where this is not fulfilled and where the image information only is available for a non-regular subset of pixel position. For processing, transmitting or displaying such an image signal, a re-sampling to a regular grid is required. Recently, Frequency Se

Chengye Yu, Deyou Chen, Chuanhong Gao

In this paper, we investigate the photon sphere, shadow radius and quasinormal modes of a $4$-dimensional black hole with a deficit solid angle and quintessence-like matter. We find that the radii of the photon sphere and shadow decrease with the decreases of the deficit solid angle and density of quintessence-like matter. The quasinormal modes are gotten by

Jürgen Seiler, André Kaup

This contribution introduces a novel signal extrapolation algorithm and its application to image error concealment. The signal extrapolation is carried out by iteratively generating a model of the signal suffering from distortion. Thereby, the model results from a weighted superposition of two-dimensional basis functions whereas in every iteration step a set

Weijian Chen, Yixin Cao, Fuli Feng, Xiangnan He

Knowledge Graphs (KGs) are becoming increasingly essential infrastructures in many applications while suffering from incompleteness issues. The KG completion task (KGC) automatically predicts missing facts based on an incomplete KG. However, existing methods perform unsatisfactorily in real-world scenarios. On the one hand, their performance will dramaticall

Jürgen Seiler, André Kaup

In the past years, video communication has found its application in an increasing number of environments. Unfortunately, some of them are error-prone and the risk of block losses caused by transmission errors is ubiquitous. To reduce the effects of these block losses, a new spatio-temporal error concealment algorithm is presented. The algorithm uses spatial

Meghna Asthana, William A. P. Smith, Patrik Huber

We propose to tackle the multiview photometric stereo problem using an extension of Neural Radiance Fields (NeRFs), conditioned on light source direction. The geometric part of our neural representation predicts surface normal direction, allowing us to reason about local surface reflectance. The appearance part of our neural representation is decomposed into

Zizhao He, Nan Li

Quasars can be used to measure baryon acoustic oscillations at high redshift, which are considered as direct tracers of the most distant large-scale structures in the Universe. It is fundamental to select quasars from observations before implementing the above research. This work focuses on creating a catalog of quasar candidates based on photometric data to

Vanni Noferini, Lauri Nyman, Javier Pérez, María C. Quintana

Zeros of rational transfer function matrices $R(\lambda)$ are the eigenvalues of associated polynomial system matrices $P(\lambda)$, under minimality conditions. In this paper we define a structured condition number for a simple eigenvalue $\lambda_0$ of a (locally) minimal polynomial system matrix $P(\lambda)$, which in turn is a simple zero $\lambda_0$ of

Luca Capizzi, Guido Giachetti, Alessandro Santini, Mario Collura

We study the dynamics of the quantum Dyson hierarchical model in its paramagnetic phase. An initial state made by a local excitation of the paramagnetic ground state is considered. We provide analytical predictions for its time evolution, solving the single-particle dynamics on a hierarchical network. A localization mechanism is found and the excitation rema

Alessandro Masullo, Toby Perrett, Tilo Burghardt, Ian Craddock

We propose a novel approach to multimodal sensor fusion for Ambient Assisted Living (AAL) which takes advantage of learning using privileged information (LUPI). We address two major shortcomings of standard multimodal approaches, limited area coverage and reduced reliability. Our new framework fuses the concept of modality hallucination with triplet learning

Somnath Dey, Supriya Sasmal, Saikat Mondal, Santosh Kumar

Amongst the derivatives of 4-biphenylcarboxylic acid and amino acid esters, the crystal structure of 4-biphenylcarboxy-(L)-phenylalaninate is unusual owing to its monoclinic symmetry within a pseudo-orthorhombic lattice. The distortion is described by disparate rotational property around the chiral centers ($\varphi_{\mathrm{chiral}}$ $\simeq$ -129 degrees a

Liat Cohen, Tal Grinshpoun, Gera Weiss

We present an efficient algorithm that, given a discrete random variable $X$ and a number $m$, computes a random variable whose support is of size at most $m$ and whose Kolmogorov distance from $X$ is minimal, also for the one-sided Kolmogorov approximation. We present some variants of the algorithm, analyse their correctness and computational complexity, an

Alexander Croy, Antonios Raptakis, David Bodesheim, Arezoo Dianat

Two-dimensional covalent organic frameworks (2D COFs) are an interesting class of 2D materials since their reticular synthesis allows the tailored design of structures and functionalities. For many of their applications the mechanical stability and performance is an important aspect. Here, we use a computational approach involving a density-functional based

Laurent Legrand, Pratika Dayal, Anne Hutter, Stefan Gottlöber

Using the ASTRAEUS (semi-numerical rAdiative tranSfer coupling of galaxy formaTion and Reionization in N-body dark matter simUlationS) framework, we explore the impact of environmental density and radiative feedback on the assembly of galaxies and their host halos during the Epoch of Reionization. The ASTRAEUS framework allows us to study the evolution of ga

Umesh Garg

Giant resonances--highly collective, high-frequency oscillations of the atomic nucleus--are the focus of this chapter. We discuss the isoscalar excitations, where the protons and neutrons oscillate in phase, up to angular-momentum transfers $L$ = 3. The procedures of experiments and data analysis employed in extracting the strength distributions associated w

Jakob Robnik, Uroš Seljak

In many hypothesis testing applications, we have mixed priors, with well-motivated informative priors for some parameters but not for others. The Bayesian methodology uses the Bayes factor and is helpful for the informative priors, as it incorporates Occam's razor via multiplicity or trials factor in the Look Elsewhere Effect. However, if the prior is not kn

Wu Zhuofei, Stefania Bartoletti, Vincent Martinez, Alessandro Bazzi

A new backward compatible WiFi amendment is under development by the IEEE bd Task Group towards the so-called IEEE 802.11bd, which includes the possibility to transmit up to three repetitions of the same packet. This feature increases time diversity and enables the use of maximum ratio combining (MRC) at the receiver to improve the probability of correct dec

Hallowed O. Olaoluwa, Aminat O. Ige, Johnson O. Olaleru

The paper introduces the class of O-metric spaces, a novel generalization of metric-type spaces, classifying almost all possible metric types into upward and downward O-metrics. We list some topologies arising from O-metrics and discuss convergence, sequential continuity, first countability and T$_2$ separation. The topology of an O-metric space can be gener

Erzhong Xue, Zilong Wang, Jinjin Chai

The sequence pairs of length $2^{m}$ projected from complementary array pairs of Type-II of size $\mathbf{2}^{(m)}$ and mixed Type-II/III and of size $\mathbf{2}^{(m-1)}\times2$ are complementary sequence pairs Type-II and Type-III respectively. An exhaustive search for binary Type-II and Type-III complementary sequence pairs of small lengths $2^{m}$ ($m=1,2

Marco Barbera, Ugo Lo Cicero, Luisa Sciortino

Thin filters and gas tight windows are used in Space to protect sensitive X-ray detectors from out-of-band electromagnetic radiation, low-energy particles, and molecular contamination. Though very thin and made of light materials, filters are not fully transparent to X-rays. For this reason, they ultimately define the detector quantum efficiency at low energ

Jungha Kim, Minkyeong Song, Yeoeun Lee, Moonkyeong Jung

Commercial visual-inertial odometry (VIO) systems have been gaining attention as cost-effective, off-the-shelf six degrees of freedom (6-DoF) ego-motion tracking methods for estimating accurate and consistent camera pose data, in addition to their ability to operate without external localization from motion capture or global positioning systems. It is unclea

Tomek Kamiński, Mirek Schmidt, Marcin Hajduk, Aleksandra Kiljan

Context. Galactic red novae are thought to be produced in stellar mergers between non-compact stars, such as main-sequence stars and cool giants. They are hoped to help in explaining physical processes involved in common envelope evolution and stellar binary collisions. Aims. We investigate the presence of lithium in three best-observed Galactic red nova rem

D. Holmes, S. Molcho, R. Pandharipande, A. Pixton

Let $A=(a_1,\ldots, a_n)$ be a vector of integers which sum to $k(2g-2+n)$. The double ramification cycle $\mathsf{DR}_{g,A}\in \mathsf{CH}^g(\mathcal{M}_{g,n})$ on the moduli space of curves is the virtual class of an Abel-Jacobi locus of pointed curves $(C,x_1,\ldots,x_n)$ satisfying $$\mathcal{O}_C\Big(\sum_{i=1}^n a_i x_i\Big) \, \simeq\, \big(\omega^{\m

Risako Kikuchi, Takumi Funato, Ai Yamakage

Quantum transport for a spin-1 chiral fermion is studied within the self-consistent Born approximation. We find characteristic properties around zero energy, i.e., the peak structure of the density of states and significant suppression of electrical conductivity. These structures originate from the flat band and its interband effect.

Vicente Orts Mercadillo, Kai Chio Chan, Mario Caironi, Athanassia Athanassiou

There is growing interest in transitioning electronic components and circuitry from stiff and rigid substrates to more flexible and stretchable platforms, such as thin plastics, textiles, and foams. In parallel, the push for more sustainable, biocompatible, and cost-efficient conductive inks to coat these substrates, has led to the development of formulation

Martin Keller-Ressel, Stephanie Nargang

We introduce L-hydra (landmarked hyperbolic distance recovery and approximation), a method for embedding network- or distance-based data into hyperbolic space, which requires only the distance measurements to a few 'landmark nodes'. This landmark heuristic makes L-hydra applicable to large-scale graphs and improves upon previously introduced methods. As a ma

I. Nolasco, S. Singh, E. Vidana-Villa, E. Grout

Few-shot sound event detection is the task of detecting sound events, despite having only a few labelled examples of the class of interest. This framework is particularly useful in bioacoustics, where often there is a need to annotate very long recordings but the expert annotator time is limited. This paper presents an overview of the second edition of the f

Naoki Kanda, Chihaya Abe, Shintaro Goto, Keigo Yamada

In this paper, we overview, evaluate, and demonstrate the sparse processing particle image velocimetry (SPPIV) as a real-time flow field estimation method using the particle image velocimetry (PIV), whereas SPPIV was previously proposed with its feasibility study and its real-time demonstration is conducted for the first time in this study. In the wind tunne

Marcelo De Martino, Volker Heiermann, Eric Opdam

Let $G$ be a split reductive group over a number field $F$. We consider the computation of the inner product of two $K$-spherical pseudo Eisenstein series of $G$ supported in $[T,\mathcal{O}(1)]$ by means of residues, following a classical approach initiated by Langlands. We show that only the singularities of the intertwining operators due to the poles of t

Pia Ammann, Rainer Kolisch, Maximilian Schiffer

This paper investigates a novel type of driver routing and scheduling problem motivated by a practical application in long-distance bus networks. A key difference from other crew scheduling problems is that drivers can be exchanged between buses at arbitrary intermediate stops en route such that our problem requires additional synchronization constraints. We

Marc Sher

This review considers models with extended Higgs sectors in which there are tree-level flavor-changing neutral currents (FCNC) mediated by scalars. After briefly reviewing models without tree-level FCNC, several models with such currents are discussed. A popular mass-matrix ansatz, in which the flavor-changing couplings are the geometric mean of the individu

Fei Yang

We prove the existence of rational maps having smooth degenerate Herman rings. This answers a question of Eremenko affirmatively. The proof is based on the construction of smooth Siegel disks by Avila, Buff and Ch\'{e}ritat as well as the classical Siegel-to-Herman quasiconformal surgery. A crucial ingredient in the proof is the surgery's continuity, which r

Miguel García García, Yannick Sauer, Tamara Watson, Siegfried Wahl

For decades, manufacturers have attempted to reduce or eliminate the optical aberrations that appear on the progressive addition lens' surfaces during manufacturing. Besides every effort made, some of these distortions are inevitable given how lenses are fabricated, where in fact, astigmatism appears on the surface and cannot be entirely removed or where non

Dan Zhu, Khai-Ming Wong, Guo-Quan Wong

We investigate further the properties of axially symmetric monopole-antimonopole pair in the standard Weinberg-Salam model. By using a novel data sampling approach, we have obtained and analyzed 300 numerical solutions corresponding to physical Higgs self-coupling $\beta=0.7782$ and the Weinberg angle $\tan\theta_W=0.5358$. We calculate the energy of these s

Mirko Agarla, Simone Bianco, Luigi Celona, Paolo Napoletano

Performance in Speech Emotion Recognition (SER) on a single language has increased greatly in the last few years thanks to the use of deep learning techniques. However, cross-lingual SER remains a challenge in real-world applications due to two main factors: the first is the big gap among the source and the target domain distributions; the second factor is t

Chen Chen, Yisen Wang, Honghua Chen, Xuefeng Yan

Semantic segmentation of point clouds, aiming to assign each point a semantic category, is critical to 3D scene understanding.Despite of significant advances in recent years, most of existing methods still suffer from either the object-level misclassification or the boundary-level ambiguity. In this paper, we present a robust semantic segmentation network by

Fabrizio Genovese, Fosco Loregian, Caterina Puca

In this work we show how FibLang, a category-theoretic framework concerned with the interplay between language and meaning, can be used to describe vocabulary acquisition, that is the process with which a speaker acquires new vocabulary (through experience or interaction). We model two different kinds of vocabulary acquisition, which we call 'by example' and

Hamidreza Dehghani, Andreas Zilian

The governing equations and numerical solution strategy to solve porohyperelastic problems as multiscale multiphysics media are provided in this contribution. The problem starts from formulating and non-dimensionalising a Fluid-Solid Interaction (FSI) problem using Arbitrary Lagrangian-Eulerian (ALE) technique at the pore level. The resultant ALE-FSI coupled

Zhaoyang Jia, Yan Lu, Houqiang Li

Video frame synthesis, which consists of interpolation and extrapolation, is an essential video processing technique that can be applied to various scenarios. However, most existing methods cannot handle small objects or large motion well, especially in high-resolution videos such as 4K videos. To eliminate such limitations, we introduce a neighbor correspon

Mine Uysal, Ilker Inam, Engin Ozkan

In this work, we define a new type of Eisenstein-like series by using Pell-Lucas numbers and call them the Pell-Lucas-Eisenstein Series. Firstly, we show that the Pell-Lucas-Eisenstein series are convergent on their domain. Afterwards we prove that they satisfy some certain functional equations. Proofs follows from some on calculations on Pell-Lucas numbers.

Andréas Sundström, Mickael Grech, István Pusztai, Caterina Riconda

We present a scheme for amplifying an extreme-ultraviolet (XUV) seed isolated attosecond pulse via stimulated Raman scattering of a pulse-train pump. At sufficient seed and pump intensity, the amplification is nonlinear, and the amplitude of the seed pulse can reach that of the pump, one order of magnitude higher than the initial seed amplitude. In the linea

Serge Koutchmy

The main observations of 1761 by M. Lomonossov and those that followed are recalled by extending the discussion to other remarkable visual observations of the passages, then with more and more powerful imagers producing images in profusion. The modern treatment of parasitic effects is briefly recalled by focusing on the expert observation of 1761 which has r

Neelanjana Pal, Taylor T Johnson

This work in progress paper introduces robustness verification for autoencoder-based regression neural network (NN) models, following state-of-the-art approaches for robustness verification of image classification NNs. Despite the ongoing progress in developing verification methods for safety and robustness in various deep neural networks (DNNs), robustness

Stefan Schupp, Francesco Leofante, Leander Behr, Erika Ábrahám

A swarm robotic system consists of a team of robots performing cooperative tasks without any centralized coordination. In principle, swarms enable flexible and scalable solutions; however, designing individual control algorithms that can guarantee a required global behavior is difficult. Formal methods have been suggested by several researchers as a mean to

Luan V. Nguyen, Wesam Haddad, Taylor T. Johnson

Satisfiability Modulo Theories (SMT) solvers have been successfully applied to solve many problems in formal verification such as bounded model checking (BMC) for many classes of systems from integrated circuits to cyber-physical systems. Typically, BMC is performed by checking satisfiability of a possibly long, but quantifier-free formula. However, BMC prob

Xuan Guang, Yang Bai, Raymond W. Yeung

In this paper, we put forward secure network function computation over a directed acyclic network. In such a network, a sink node is required to compute with zero error a target function of which the inputs are generated as source messages at multiple source nodes, while a wiretapper, who can access any one but not more than one wiretap set in a given collec

Jirô Akahori, Ryuya Namba, Shunsuke Semba

The Sz\'asz-Mirakyan operator is known as a positive linear operator which uniformly approximates a certain class of continuous functions on the half line. The purpose of the present paper is to find out limiting behaviors of the iterates of the Sz\'asz-Mirakyan operator in a probabilistic point of view. We show that the iterates of the Sz\'asz-Mirakyan oper

Dominik Grundt, Sorin Liviu Jurj, Willem Hagemann, Paul Kröger

This paper presents an approach for verifying the behaviour of nonlinear Artificial Neural Networks (ANNs) found in cyber-physical safety-critical systems. We implement a dedicated interval constraint propagator for the sigmoid function into the SMT solver iSAT and compare this approach with a compositional approach encoding the sigmoid function by basic ari

Guimei Cao, Zhanzhan Cheng, Yunlu Xu, Duo Li

Expandable networks have demonstrated their advantages in dealing with catastrophic forgetting problem in incremental learning. Considering that different tasks may need different structures, recent methods design dynamic structures adapted to different tasks via sophisticated skills. Their routine is to search expandable structures first and then train on t

Yuki Fujimoto, Kenji Fukushima, Larry D. McLerran, Michal Praszalowicz

We discuss an interpretation that a peak in the sound velocity in neutron star matter, as suggested by the observational data, signifies strongly-coupled conformal matter. The normalized trace anomaly is a dimensionless measure of conformality leading to the derivative and the non-derivative contributions to the sound velocity. We find that the peak in the s

Zheng-Yuan Fang, Ya-Rong Wang, Cheng-Qun Pang

Mass spectra of quarkonium systems can be described by different phenomenological potentials. In the present work, the {\color{black}resonance} states of heavy quarkonium like ($c\bar{c}$ and $b\bar{b}$) are considered as the rovibrational states. We study a parameterized rovibrational model derived from the empirical solution of the nonrelativistic Schr\"{o

I. A. Golovchanskiy, N. N. Abramov, V. V. Ryazanov, A. A. Golubov

In this work, we study magnetization dynamics in superconductor-ferromagnet-superconductor thin-film structures. Results of the broad-band ferromagnetic resonance spectroscopy are reported for a large set of samples with varied thickness of both superconducting and ferromagnetic layers in a wide frequency, field, and temperature ranges. Experimentally the on

Daniel Dörfler

This article is concerned with the approximation of unbounded convex sets by polyhedra. While there is an abundance of literature investigating this task for compact sets, results on the unbounded case are scarce. We first point out the connections between existing results before introducing a new notion of polyhedral approximation called ($\varepsilon,\delt

Cristobal Laporte, Nora Locht, Antonio D. Pereira, Frank Saueressig

Wetterich's equation provides a powerful tool for investigating the existence and universal properties of renormalization group fixed points exhibiting quantum scale invariance. Motivated by recent works on asymptotically safe scalar-tensor theories, we develop a novel approximation scheme which projects the functional renormalization group equation onto fun

Zhang XueGuang, Zhao YuanBo

In the Letter, an interesting method is proposed to estimate size of narrow emission lines regions (NLRs) of a Type-2 AGN SDSS J083823.91+490241.1 (=SDSS J0838) at a redshift of 0.101, by comparing spectroscopic properties through the SDSS fiber (MJD=51873) (diameter of 3 arcseconds) and through the eBOSS fiber (MJD=55277) (diameter of 2 arcseconds). After s

Md. Riad Kasem, Hiroto Arima, Yoichi Ikeda, Aichi Yamashita

We synthesized a new high-entropy-alloy-type (HEA-type) superconductor (Fe,Co,Ni,Cu,Ga)Zr2 with a Tc of 2.9 K. The EDX analyses revealed that the actual composition of the transition-metal site (Tr-site) is Tr = Fe0.18Co0.18Ni0.16Cu0.25Ga0.23, which gives the configurational entropy of mixing {\Delta}Smix = 1.60R for the Tr site. Neutron powder diffraction r

Stephen L. H. Lau, Edwin K. P. Chong

Single-pixel imaging (SPI) is a novel imaging technique whose working principle is based on the compressive sensing (CS) theory. In SPI, data is obtained through a series of compressive measurements and the corresponding image is reconstructed. Typically, the reconstruction algorithm such as basis pursuit relies on the sparsity assumption in images. However,

Izaak Neri

We consider the problem of estimating the mean entropy production rate in a nonequilibrium process from the measurements of first-passage quantities associated with a single current. For first-passage processes with large thresholds, Refs. [1, 2] identified a ratio of first-passage observables - involving the mean first-passage time, the splitting probabilit

Zhanzhan Cheng, Peng Zhang, Can Li, Qiao Liang

Recently, automatically extracting information from visually rich documents (e.g., tickets and resumes) has become a hot and vital research topic due to its widespread commercial value. Most existing methods divide this task into two subparts: the text reading part for obtaining the plain text from the original document images and the information extraction

Yuefeng Yang, Xuanlong Ma, Qing Zeng

A subset $C$ of the vertex set of a graph $\Gamma$ is called a perfect code of $\Gamma$ if every vertex of $\Gamma$ is at distance no more than one to exactly one vertex in $C$. In this paper, we classify all connected quintic Cayley graphs on abelian groups that admit a perfect code, and determine completely all perfect codes of such graphs.

Yu-Liang Fang, Jun-Long Zhao, Dong-Xu Chen, Yan-Hui Zhou

In the past years, many efforts have been made to study various noteworthy phenomena in both parity-time ($\mathcal{PT}$) and anti-parity-time ($\mathcal{APT}$) symmetric systems. However, entanglement dynamics in $\mathcal{APT}$-symmetric systems has not previously been investigated in both theory and experiments. Here, we investigate the entanglement evolu

Natalia Slusarz, Ekaterina Komendantskaya, Matthew L. Daggitt, Robert Stewart

The rising popularity of neural networks (NNs) in recent years and their increasing prevalence in real-world applications have drawn attention to the importance of their verification. While verification is known to be computationally difficult theoretically, many techniques have been proposed for solving it in practice. It has been observed in the literature

Shuai Fu, Zheyi Ding, Yongjie Zhang, Xiaoping Zhang

Solar energetic particles (SEPs) associated with flares and/or coronal mass ejection (CME)-driven shocks can impose acute radiation hazards to space explorations. To measure energetic particles in near-Mars space, the Mars Energetic Particle Analyzer (MEPA) instrument onboard China's Tianwen-1 (TW-1) mission was designed. Here, we report the first MEPA measu

Marianne Akian, Stephane Gaubert, Louis Rowen

Hyperfields and systems are two algebraic frameworks which have been developed to provide a unified approach to classical and tropical structures. All hyperfields, and more generally hyperrings, can be represented by systems. Conversely, we show that the systems arising in this way, called {\it hypersystems}, are characterized by certain elimination axioms.