October 2022 arXiv papers — page 101

Yakov Bloch, Eliahu Cohen

The Cramer-Rao bound, satisfied by classical Fisher information, a key quantity in information theory, has been shown in different contexts to give rise to the Heisenberg uncertainty principle of quantum mechanics. In this paper, we show that the identification of the mean quantum potential, an important notion in Bohmian mechanics, with the Fisher informati

Dale Lawlor, Simon Hands, Seyong Kim, Jon-Ivar Skullerud

The infamous sign problem makes it impossible to probe dense (baryon density $\mu_B>0$) QCD at temperatures near or below the deconfinement threshold. As a workaround, one can explore QCD-like theories such as two-colour QCD (QC2D) which don't suffer from this sign problem but are qualitively similar to real QCD. Previous studies on smaller lattice volumes h

Ekaterina Dorzhieva, Ahmed Baza, Ayush Gupta, Aleksey Fedoseev

We propose a novel concept of augmented reality (AR) human-drone interaction driven by RL-based swarm behavior to achieve intuitive and immersive control of a swarm formation of unmanned aerial vehicles. The DroneARchery system developed by us allows the user to quickly deploy a swarm of drones, generating flight paths simulating archery. The haptic interfac

Anthony Hu, Gianluca Corrado, Nicolas Griffiths, Zak Murez

An accurate model of the environment and the dynamic agents acting in it offers great potential for improving motion planning. We present MILE: a Model-based Imitation LEarning approach to jointly learn a model of the world and a policy for autonomous driving. Our method leverages 3D geometry as an inductive bias and learns a highly compact latent space dire

Konstantinos Kanavouras, Andreas Makoto Hein, Maanasa Sachidanand

Space systems miniaturization has been increasingly popular for the past decades, with over 1600 CubeSats and 300 sub-CubeSat sized spacecraft estimated to have been launched since 1998. This trend towards decreasing size enables the execution of unprecedented missions in terms of quantity, cost and development time, allowing for massively distributed satell

Ana Wright

We call a knot $K$ a complete Alexander neighbor if every possible Alexander polynomial is realized by a knot one crossing change away from $K$. It is unknown whether there exists a complete Alexander neighbor with nontrivial Alexander polynomial. We eliminate infinite families of knots with nontrivial Alexander polynomial from having this property and discu

Matthew Dickson, Markus Heydenreich

We investigate a spatial random graph model whose vertices are given as a marked Poisson process on $\mathbb{R}^d$. Edges are inserted between any pair of points independently with probability depending on the spatial displacement of the two endpoints and on their marks. Upon variation of the Poisson density, a percolation phase transition occurs under mild

Ivan S. Gerasimov, Oleg V. Egorov, Tatiana A. Lozinskaya, Alexei V. Moiseev

Feedback from massive stars shapes the ISM and affects the evolution of galaxies, but its mechanisms acting at the small scales ($\sim 10$ pc) are still not well constrained observationally, especially in the low-metallicity environments. We present the analysis of the ionized gas (focusing on its kinematics, which were never studied before), and its connect

Erik C. Kool, Joel Johansson, Jesper Sollerman, Javier Moldón

Type Ia supernovae (SNe Ia) are thermonuclear explosions of degenerate white dwarf (WD) stars destabilized by mass accretion from a companion star, but the nature of their progenitors remains poorly understood. A way to discriminate between progenitor systems is through radio observations; a non-degenerate companion star is expected to lose material through

Fernando Lucatelli Nunes, Matthijs Vákár

We give a simple, direct and reusable logical relations technique for languages with term and type recursion and partially defined differentiable functions. We demonstrate it by working out the case of Automatic Differentiation (AD) correctness: namely, we present a correctness proof of a dual numbers style AD code transformation for realistic functional lan

Daniel Schalk, Bernd Bischl, David Rügamer

Various privacy-preserving frameworks that respect the individual's privacy in the analysis of data have been developed in recent years. However, available model classes such as simple statistics or generalized linear models lack the flexibility required for a good approximation of the underlying data-generating process in practice. In this paper, we propose

Gregory Gutin, Anders Yeo

A graph $H$ is a clique graph if $H$ is a vertex-disjoin union of cliques. Abu-Khzam (2017) introduced the $(a,d)$-{Cluster Editing} problem, where for fixed natural numbers $a,d$, given a graph $G$ and vertex-weights $a^*:\ V(G)\rightarrow \{0,1,\dots, a\}$ and $d^*{}:\ V(G)\rightarrow \{0,1,\dots, d\}$, we are to decide whether $G$ can be turned into a clu

Pakorn Uttayopas, Xiaoxiao Cheng, Jonathan Eden, Etienne Burdet

Current robotic haptic object recognition relies on statistical measures derived from movement dependent interaction signals such as force, vibration or position. Mechanical properties that can be identified from these signals are intrinsic object properties that may yield a more robust object representation. Therefore, this paper proposes an object recognit

Wolfgang Lucha

Within the formalism of relativistic quantum field theory an adequate framework for the description of two-particle bound states, such as, for instance, all conventional (i.e., non-exotic) mesons, is provided by the Poincar\'e-covariant homogeneous Bethe-Salpeter equation. In applications, however, this approach usually proves to be rather involved, whence i

Jan von der Assen, Alberto Huertas Celdrán, Pedro Miguel Sánchez Sánchez, Jordan Cedeño

Malware affecting Internet of Things (IoT) devices is rapidly growing due to the relevance of this paradigm in real-world scenarios. Specialized literature has also detected a trend towards multi-purpose malware able to execute different malicious actions such as remote control, data leakage, encryption, or code hiding, among others. Protecting IoT devices a

Jagannath Das, Aman Kumar, Avijit Maity, Vikram Tripathi

A variety of analytical approaches have been developed for the study of quantum spin systems in two dimensions, the notable ones being spin-waves, slave boson/fermion parton constructions, and for lattices with one-to-one local correspondence of faces and vertices, the 2D Jordan-Wigner (JW) fermionization. Field-theoretically, JW fermionization is implemente

Ruizhe Li, Xin Chen

Cardiac Magnetic Resonance Imaging (MRI) plays an important role in the analysis of cardiac function. However, the acquisition is often accompanied by motion artefacts because of the difficulty of breath-hold, especially for acute symptoms patients. Therefore, it is essential to assess the quality of cardiac MRI for further analysis. Time-consuming manual-ba

Tairone Paiva Leão

The purpose of this monograph is to review the early theoretical basis of what is known today as soil physics and to serve as a textbook for intermediate porous media physics or transport in porous media graduate courses.

Tiantian He, Haicang Zhou, Yew-Soon Ong, Gao Cong

Graph attention networks (GATs) are powerful tools for analyzing graph data from various real-world scenarios. To learn representations for downstream tasks, GATs generally attend to all neighbors of the central node when aggregating the features. In this paper, we show that a large portion of the neighbors are irrelevant to the central nodes in many real-wo

Phillip Rieger, Torsten Krauß, Markus Miettinen, Alexandra Dmitrienko

Federated Learning (FL) is a promising approach enabling multiple clients to train Deep Neural Networks (DNNs) collaboratively without sharing their local training data. However, FL is susceptible to backdoor (or targeted poisoning) attacks. These attacks are initiated by malicious clients who seek to compromise the learning process by introducing specific b

Leonardos Pantiskas, Kees Verstoep, Mark Hoogendoorn, Henri Bal

In current research, machine and deep learning solutions for the classification of temporal data are shifting from single-channel datasets (univariate) to problems with multiple channels of information (multivariate). The majority of these works are focused on the method novelty and architecture, and the format of the input data is often treated implicitly.

Mohamed S. Elbakry

This thesis is concerned with data-aided (DA) scheme and CFO tracking for OFDM system. OFDM system model is developed first without CFO and then with CFO. The system performance is evaluated via simulation. The bit error rate (BER), constellation diagram, the phase output and phase error were taken as performance measures. The performance is evaluated for di

Pradeep Kumar Sahu, Nitin Gupta

In this paper, we study some properties and characterization of the general weighted cumulative past extropy (n-WCPJ). Many results including some bounds, inequalities, and effects of linear transformations are obtained. We study the characterization of n-WCPJ based on the largest order statistics. Conditional WCPJ and some of its properties are discussed.

F. El Ayachi, M. El Baz

A classification of multipartite entanglement in qubit systems is introduced for pure and mixed states. The classification is based on the robustness of the said entanglement against partial trace operation. Then we use current machine learning and deep learning techniques to automatically classify a random state of two, three and four qubits without the nee

Yevgeniya Filanova, Igor Pontes Duff, Pawan Goyal, Peter Benner

Model-order reduction techniques allow the construction of low-dimensional surrogate models that can accelerate engineering design processes. Often, these techniques are intrusive, meaning that they require direct access to underlying high-fidelity models. Accessing these models is laborious or may not even be possible in some cases. Therefore, there is an i

M. Stein, V. Heesen, R. -J. Dettmar, Y. Stein

Galactic winds play a key role in regulating the evolution of galaxies over cosmic time. In recent years, the role of cosmic rays (CR) in the formation of the galactic wind has increasingly gained attention. Therefore, we use radio continuum data to analyse the cosmic ray transport in edge-on galaxies. Data from the LOFAR Two-metre Sky Survey (LoTSS) data re

Pavlo Bilous

The interplay of x-ray ionization and atomic and nuclear degrees of freedom is investigated theoretically in the process of laser-assisted nuclear excitation by electron capture. In the resonant process of nuclear excitation by electron capture, an incident electron recombines into a vacancy in the atomic shell with simultaneous nuclear excitation. Here we i

Liu Yang, Simon X. Yang, Yun Li, Yinzhi Lu

Traditional machine learning techniques have been widely used to establish the trust management systems. However, the scale of training dataset can significantly affect the security performances of the systems, while it is a great challenge to detect malicious nodes due to the absence of labeled data regarding novel attacks. To address this issue, this paper

Valentina De Romeri, Jacopo Nava, Miguel Puerta, Avelino Vicente

Scotogenic models constitute an appealing solution to the generation of neutrino masses and to the dark matter mystery. In this work we consider a version of the Scotogenic model that breaks lepton number spontaneously. At this scope, we extend the particle content of the Scotogenic model with an additional singlet scalar which acquires a non-zero vacuum exp

A. V. Baeva, I. V. Sokolov

Quantum measurement-induced gate based on entanglement with ideal cubic phase state used as a non-Gaussian resource is able to produce Shr\"odinger cat state in the form of two high fidelity ``copies'' of the target state on phase plane [N.I. Masalaeva, I.V. Sokolov, Phys. Lett. A 424, 127846 (2022)]. In this work we examine the effect of finite initial sque

Manuel Araújo

An $n$-sesquicategory is an $n$-globular set with strictly associative and unital composition and whiskering operations, which are however not required to satisfy the Godement interchange laws which hold in $n$-categories. In arXiv:2202.09293 we showed how these can be defined as algebras over a monad $T_n^{D^s}$ whose operations are simple string diagrams.

Matin Ansaripour, Shayan Talaei, Giorgi Nadiradze, Dan Alistarh

Distributed optimization is the standard way of speeding up machine learning training, and most of the research in the area focuses on distributed first-order, gradient-based methods. Yet, there are settings where some computationally-bounded nodes may not be able to implement first-order, gradient-based optimization, while they could still contribute to joi

Dong Wu, Chi Zhang, Xiaojing Tang, Xiangyu Hu

The total Lagrangian smoothed particle hydrodynamics (TL-SPH) for elastic solid dynamics suffers from hourglass modes which can grow and lead to the failure of simulation for problems with large deformation. To address this long-standing issue, we present an hourglass-free formulation based on volumetric-devioatric stress decomposition. Inspired by the fact

Peter Lippmann, Enrique Fita Sanmartín, Fred A. Hamprecht

Branched Optimal Transport (BOT) is a generalization of optimal transport in which transportation costs along an edge are subadditive. This subadditivity models an increase in transport efficiency when shipping mass along the same route, favoring branched transportation networks. We here study the NP-hard optimization of BOT networks connecting a finite numb

J. Otsuki, K. Yoshimi, Y. Nakanishi-Ohno, M. Sekania

Compton scattering is a well-established technique that can provide detailed information about electronic states in solids. Making use of the principle of tomography, it is possible to determine the Fermi surface from sets of Compton-scattering data with different scattering axes. Practical applications, however, are limited due to long acquisition time requ

Sachin Kumar, Vidhisha Balachandran, Lucille Njoo, Antonios Anastasopoulos

Recent advances in the capacity of large language models to generate human-like text have resulted in their increased adoption in user-facing settings. In parallel, these improvements have prompted a heated discourse around the risks of societal harms they introduce, whether inadvertent or malicious. Several studies have explored these harms and called for t

Dibyayan Chakraborty, L. Sunil Chandran, Sajith Padinhatteeri, Raji. R. Pillai

In this paper, we study the computational complexity of \textsc{$s$-Club Cluster Vertex Deletion}. Given a graph, \textsc{$s$-Club Cluster Vertex Deletion ($s$-CVD)} aims to delete the minimum number of vertices from the graph so that each connected component of the resulting graph has a diameter at most $s$. When $s=1$, the corresponding problem is popularl

Joaquim Gomis, Arnoldo Guerra, Narciso Román-Roy

The (pre)multisymplectic geometry of the De Donder--Weyl formalism for field theories is further developed for a variety of field theories including a scalar field theory from the canonical Klein-Gordon action, the electric and magnetic Carrollian scalar field theories, bosonic string theory from the Nambu-Goto action, and $2+1$ gravity as a Chern-Simons the

Mohammad Baradaran, Robert Bergevin

Multi-task learning based video anomaly detection methods combine multiple proxy tasks in different branches to detect video anomalies in different situations. Most existing methods either do not combine complementary tasks to effectively cover all motion patterns, or the class of the objects is not explicitly considered. To address the aforementioned shortc

Jonathan Ish-Horowicz, Sarah Filippi

The bacterial microbiome is increasingly being recognised as a key factor in human health, driven in large part by datasets collected using 16S rRNA (ribosomal ribonucleic acid) gene sequencing, which enable cost-effective quantification of the composition of an individual's bacterial community. One of the defining characteristics of 16S rRNA datasets is the

Marc Carrascosa-Zamacois, Giovanni Geraci, Lorenzo Galati-Giordano, Anders Jonsson

Will Wi-Fi 7, conceived to support extremely high throughput, also deliver consistently low delay? The best hope seems to lie in allowing next-generation devices to access multiple channels via multi-link operation (MLO). In this paper, we aim to advance the understanding of MLO, placing the spotlight on its packet delay performance. We show that MLO devices

Szymon Harabasz, Jędrzej Kołaś, Radosław Ryblewski, Wojciech Florkowski

A spheroidal model of the expansion of hadronic matter produced in heavy-ion collisions in the few-GeV energy regime is proposed. It constitutes an extension of the spherically symmetric Siemens-Rasmussen blast-wave model used in our previous works. The spheroidal form of the expansion, combined with a single-freeze-out scenario, allows for a significantly i

Floris van Doorn

We will discuss our experiences and design decisions obtained from building a formal library for the convolution of two functions. Convolution is a fundamental concept with applications throughout mathematics. We will focus on the design decisions we made to make the convolution general and easy to use, and the incorporation of this development in Lean's mat

Manuele Rusci, Marco Fariselli, Martin Croome, Francesco Paci

This paper presents an optimized methodology to design and deploy Speech Enhancement (SE) algorithms based on Recurrent Neural Networks (RNNs) on a state-of-the-art MicroController Unit (MCU), with 1+8 general-purpose RISC-V cores. To achieve low-latency execution, we propose an optimized software pipeline interleaving parallel computation of LSTM or GRU rec

Divyang G. Bhimani, Ramesh Manna, Fabio Nicola, Sundaram Thangavelu

We establish some fixed-time decay estimates in Lebesgue spaces for the fractional heat propagator $e^{-tH^{\beta}}$, $t, \beta>0$, associated with the harmonic oscillator $H=-\Delta + |x|^2$. We then prove some local and global wellposedness results for nonlinear fractional heat equations.

Subaveerapandiyan A, R Nandhakumar

Information and communication technology prompted the sharing of information over the world. For its impact on education the government and the authorities like the University Grants Commission in India have energized the higher education institutions in India to implement online education during the pandemic situation. This paper attempts to know the teachi

Vuong Bui

We prove an old conjecture of McMullen, Schneider and Shephard that every polytope with the generating property is strongly monotypic. The other direction is already known, which implies that strong monotypy and the generating property for polytopes are the same notion. A criterion for monotypic and strongly monotypic polytopes is also given.

Velko Vechev, Ronan Hinchet, Stelian Coros, Bernhard Thomaszewski

Garments with the ability to provide kinesthetic force-feedback on-demand can augment human capabilities in a non-obtrusive way, enabling numerous applications in VR haptics, motion assistance, and robotic control. However, designing such garments is a complex, and often manual task, particularly when the goal is to resist multiple motions with a single desi

John Stewart Fabila-Carrasco, Chao Tan, Javier Escudero

Using a graph-based approach, we propose a multiscale permutation entropy to explore the complexity of multivariate time series over multiple time scales. This multivariate multiscale permutation entropy (MPEG) incorporates the interaction between channels by constructing an underlying graph for each coarse-grained time series and then applying the recent pe

Wenliang Dai, Zihan Liu, Ziwei Ji, Dan Su

Large-scale vision-language pre-trained (VLP) models are prone to hallucinate non-existent visual objects when generating text based on visual information. In this paper, we systematically study the object hallucination problem from three aspects. First, we examine recent state-of-the-art VLP models, showing that they still hallucinate frequently, and models

Amani Abusafia, Abdallah Lakhdari, Athman Bouguettaya

We propose a novel service-based ecosystem to crowdsource wireless energy to charge IoT devices. We leverage the service paradigm to abstract wireless energy crowdsourcing from nearby IoT devices as energy services. The proposed energy services ecosystem offers convenient, ubiquitous, and cost-effective power access to charge IoT devices. We discuss the impa

Emmanuel Klinger, Tianhao Liu, Mikhail Padniuk, Martin Engler

Self-compensated comagnetometers, employing overlapping samples of spin-polarized alkali and noble gases (for example K-$^3$He) are promising sensors for exotic beyond-the-standard-model fields and high-precision metrology such as rotation sensing. When the comagnetometer operates in the so-called self-compensated regime, the effective field, originating fro

Jieyi Bi, Yining Ma, Jiahai Wang, Zhiguang Cao

Recent neural methods for vehicle routing problems always train and test the deep models on the same instance distribution (i.e., uniform). To tackle the consequent cross-distribution generalization concerns, we bring the knowledge distillation to this field and propose an Adaptive Multi-Distribution Knowledge Distillation (AMDKD) scheme for learning more ge

Dan Stowell, Caitlin Black, Florencia Noriega, Sarab S. Sethi

Acoustic data (sound recordings) are a vital source of evidence for detecting, counting, and distinguishing wildlife. This domain of "bioacoustics" has grown in the past decade due to the massive advances in signal processing and machine learning, recording devices, and the capacity of data processing and storage. Numerous research papers describe the use of

Qiangbo Zhang, Zeqing Yu, Xinyu Liu, Chang Wang

Traditional snapshot hyperspectral imaging systems generally require multiple refractive-optics-based elements to modulate light, resulting in bulky framework. In pursuit of a more compact form factor, a metasurface-based snapshot hyperspectral imaging system, which achieves joint optimization of metasurface and image processing, is proposed in this paper. T

A. Subaveerapandiyan, K. Yohapriya, Ghouse Modin Nabeesab Mamdapur

In this transformative world, changes are happening in all the fields, including scholarly communications are trending in the academic area of publication and access to the resources, especially emerging the wave of open access, open science and open research. The study aims to investigate the digital publishing behaviour of manuscript authors. This study ap

Jahnavi Yidavalapati, Priyanka Sinha, Subaveerapandiyan A

The study examined the research data management and related services offered by South Asian countries' academic libraries. Research applied quantitative approach and survey research design method were used for this study. The survey questionnaire was distributed randomly to academic library professionals in five countries: Afghanistan, Bangladesh, India, Pak

Ivan Novikov, Olga Kovalyova, Alexander Shapeev, Max Hodapp

In computational materials science, a common means for predicting macroscopic (e.g., mechanical) properties of an alloy is to define a model using combinations of descriptors that depend on some material properties (elastic constants, misfit volumes, etc.), representative for the macroscopic behavior. The material properties are usually computed using specia

Teresa Tschirner, Berengar Leikert, Felix Kern, Daniel Wolf

Linear magnetoresistance (LMR) is of particular interest for memory, electronics, and sensing applications, especially when it does not saturate over a wide range of magnetic fields. One of its principal origins is local mobility or density inhomogeneities, often structural, which in the Parish-Littlewood theory leads to an unsaturating LMR proportional to m

Patrick Dendorfer, Vladimir Yugay, Aljoša Ošep, Laura Leal-Taixé

Recent developments in monocular multi-object tracking have been very successful in tracking visible objects and bridging short occlusion gaps, mainly relying on data-driven appearance models. While we have significantly advanced short-term tracking performance, bridging longer occlusion gaps remains elusive: state-of-the-art object trackers only bridge less

Florian Sammüller, Daniel de las Heras, Matthias Schmidt

We investigate the stationary flow of a colloidal gel under an inhomogeneous external shear force using adaptive Brownian dynamics simulations. The interparticle forces are derived from the Stillinger-Weber potential, where the three-body term is tuned to enable network formation and gelation in equilibrium. When subjected to the shear force field, the syste

Pengcheng Zhu, Elizabeth H. Driscoll, Bo Dong, Roberto Sommerville

The ever-increasing number of spent lithium-ion batteries (LIBs) has presented a serious waste-management challenge. Aluminium and copper current collectors are important components in LIBs and take up a weight percentage of more than 15%. Direct reuse of current collectors can effectively reduce LIB waste and provide an alternative renewable source of alumi

Matthew Baas, Kevin Eloff, Herman Kamper

Diffusion models have shown exceptional scaling properties in the image synthesis domain, and initial attempts have shown similar benefits for applying diffusion to unconditional text synthesis. Denoising diffusion models attempt to iteratively refine a sampled noise signal until it resembles a coherent signal (such as an image or written sentence). In this

Behnam Mohammadi, Elnaz Amirkhanlou

The most precise measurement of the $CP$ asymmetry in the decay $B^-\rightarrow D_s^-D^0$ has been reported by LHCb collaboration with the value of $(-0.4\pm0.5\pm0.5)\%$. In this study, the $CP$ violation in the decay $B^-\rightarrow D_s^-D^0$ has been calculated under the factorization approach. This decay mode includes current-current tree and penguin dia

Igor Zingman, Birgit Stierstorfer, Charlotte Lempp, Fabian Heinemann

We present a system for anomaly detection in histopathological images. In histology, normal samples are usually abundant, whereas anomalous (pathological) cases are scarce or not available. Under such settings, one-class classifiers trained on healthy data can detect out-of-distribution anomalous samples. Such approaches combined with pre-trained Convolution

Maryse Ernzer, Manel Bosch Aguilera, Matteo Brunelli, Gian-Luca Schmid

Feedback is a powerful and ubiquitous technique both in classical and quantum system control. Its standard implementation relies on measuring the state of a system, processing the classical signal, and feeding it back to the system. In quantum physics, however, measurements not only read out the state of the system but also modify it irreversibly. Coherent f

Flavio Bombacigno, Fabio Moretti, Simon Boudet, Gonzalo J. Olmo

We discuss how tensor polarizations of gravitational waves can suffer Landau damping in the presence of velocity birefringence, when parity symmetry is explicitly broken. In particular, we analyze the role of the Nieh-Yan and Chern-Simons terms in modified theories of gravity, showing how the gravitational perturbation in collisionless media can be character

Chiara Amorino, Arturo Jaramillo, Mark Podolskij

We present a novel theoretical result on estimation of local time and occupation time measure of an {\alpha}-stable L\'evy process with {\alpha} in (1, 2). Our approach is based upon computing the conditional expectation of the desired quantities given high frequency data, which is an L^2-optimal statistic by construction. We prove the corresponding stable c

Kevin G. Hare, Nikita Sidorov

Let $C$ be the classical middle third Cantor set. It is well known that $C+C = [0,2]$ (Steinhaus, 1917). (Here $+$ denotes the Minkowski sum.) Let $U$ be the set of $z \in [0,2]$ which have a unique representation as $z = x + y$ with $x, y \in C$ (the set of uniqueness). It isn't difficult to show that $\dim_H U = \log(2) / \log(3)$ and $U$ essentially looks

Berk Kaya, Suryansh Kumar, Carlos Oliveira, Vittorio Ferrari

Multi-view photometric stereo (MVPS) is a preferred method for detailed and precise 3D acquisition of an object from images. Although popular methods for MVPS can provide outstanding results, they are often complex to execute and limited to isotropic material objects. To address such limitations, we present a simple, practical approach to MVPS, which works w

Na Yan, Kezhi Wang, Kangda Zhi, Cunhua Pan

In this paper, a novel secure and private over-the-air federated learning (SP-OTA-FL) framework is studied where noise is employed to protect data privacy and system security. Specifically, the privacy leakage of user data and the security level of the system are measured by differential privacy (DP) and mean square error security (MSE-security), respectivel

Nisha Shahi, Ajit K. Jena, Gaurav K. Shukla, Vishal Kumar

Spin gapless semiconductors exhibit a finite band gap for one spin channel and closed gap for other spin channel, emerged as a new state of magnetic materials with a great potential for spintronic applications. The first experimental evidence for the spin gapless semiconducting behavior was observed in an inverse Heusler compound Mn2CoAl. Here, we report a d

Marco Caliari, Fabio Cassini, Franco Zivcovich

We present a method for computing actions of the exponential-like $\varphi$-functions for a Kronecker sum $K$ of $d$ arbitrary matrices $A_\mu$. It is based on the approximation of the integral representation of the $\varphi$-functions by Gaussian quadrature formulas combined with a scaling and squaring technique. The resulting algorithm, which we call PHIKS

Bálint Z. Téglásy, Sokratis Katsikas

National or international maritime authorities are used to handle requests for licenses for all kinds of marine activities. These licenses constitute authorizations limited in time and space, but there is no technical security service to check for the authorization of a wide range of marine assets. We have noted secure AIS solutions suitable for more or less

Daniel Rodriguez, Michael N. Stavropoulos, Petronio A. S. Nogueira, Daniel Edgington-Mitchell

Linear stability theory (LST) is often used to model the large-scale flow structures in the turbulent mixing region and near pressure field of high-speed jets. For perfectly-expanded single round jets, these models predict the dominance of $m=0$ and $m = 1$ helical modes for the lower frequency range, in agreement with empirical data. When LST is applied to

H. Almazán, L. Bernard, A. Blanchet, A. Bonhomme

Anomalies in past neutrino measurements have led to the discovery that these particles have non-zero mass and oscillate between their three flavors when they propagate. In the 2010's, similar anomalies observed in the antineutrino spectra emitted by nuclear reactors have triggered the hypothesis of the existence of a supplementary neutrino state that would b

Swaroop Mishra, Bhavdeep Singh Sachdeva, Chitta Baral

Pretrained Transformers (PT) have been shown to improve Out of Distribution (OOD) robustness than traditional models such as Bag of Words (BOW), LSTMs, Convolutional Neural Networks (CNN) powered by Word2Vec and Glove embeddings. How does the robustness comparison hold in a real world setting where some part of the dataset can be noisy? Do PT also provide mo

Stephanie Holly, Robin Heel, Denis Katic, Leopold Schoeffl

Anomaly detection in large industrial cooling systems is very challenging due to the high data dimensionality, inconsistent sensor recordings, and lack of labels. The state of the art for automated anomaly detection in these systems typically relies on expert knowledge and thresholds. However, data is viewed isolated and complex, multivariate relationships a

Jorge Lauret, Cynthia E. Will

The third real de Rham cohomology of compact homogeneous spaces is studied. Given $M=G/K$ with $G$ compact semisimple, we first show that each bi-invariant symmetric bilinear form $Q$ on $\mathfrak{g}$ such that $Q|_{\mathfrak{k}\times\mathfrak{k}}=0$ naturally defines a $G$-invariant closed $3$-form $H_Q$ on $M$, which plays the role of the so called Cartan

Álvaro García López

A derivation of pilot waves from electrodynamic self-interactions is presented. For this purpose, we abandon the current paradigm that describes electrodynamic bodies as point masses. Beginning with the Li\'enard-Wiechert potentials, and assuming that inertia has an electromagnetic origin, the equation of motion of a nonlinear time-delayed oscillator is obta

Jun Zhang, Shuyang Jiang, Jiangtao Feng, Lin Zheng

Transformer has achieved remarkable success in language, image, and speech processing. Recently, various efficient attention architectures have been proposed to improve transformer's efficiency while largely preserving its efficacy, especially in modeling long sequences. A widely-used benchmark to test these efficient methods' capability on long-range modeli

Ge Fan, Chaoyun Zhang, Kai Wang, Junyang Chen

Industrial recommender systems usually employ multi-source data to improve the recommendation quality, while effectively sharing information between different data sources remain a challenge. In this paper, we introduce a novel Multi-View Approach with Hybrid Attentive Networks (MV-HAN) for contents retrieval at the matching stage of recommender systems. The

Mugdim Bublin, Franz Werner, Andrea Kerschbaumer, Gernot Korak

Dysgraphia, a handwriting learning disability, has a serious negative impact on children's academic results, daily life and overall wellbeing. Early detection of dysgraphia allows for an early start of a targeted intervention. Several studies have investigated dysgraphia detection by machine learning algorithms using a digital tablet. However, these studies

Alejandro Sánchez de Miguel, Sara Krupansky

Using the SNPP-VIIRS/DNB and the DMSP-OLS it is possible to have an idea of the evolution of the light pollution until the LEDs started to appear massively. Another of the issues of dealing with these two datasets is the different time of acquisition. In general this means that countries get dimmer late at night, although that is not always true. A counterex

Stone Tao, Xiaochen Li, Tongzhou Mu, Zhiao Huang

Training long-horizon robotic policies in complex physical environments is essential for many applications, such as robotic manipulation. However, learning a policy that can generalize to unseen tasks is challenging. In this work, we propose to achieve one-shot task generalization by decoupling plan generation and plan execution. Specifically, our method sol

Roland Bacher

Every odd prime number p can be written in exactly (p + 1)/2 ways as a sum ab+cd of two ordered products ab and cd such that min(a, b) > max(c, d). An easy corollary is a proof of Fermat's Theorem expressing primes in 1 + 4N as sums of two squares.

Kunihiko Yamauchi, Ikutaro Hamada

The microscopic mechanism of the hydrogen-induced metal-insulator transition in SmNiO$_3$ is clarified by means of density-functional theory with the Hubbard U correction. While 100% of hydrogen doping per Ni atom has been supposed to be responsible for the metal-insulator transition, we found that 50% of hydrogen doping results in an outstandingly stable at

P. Diego-Palazuelos, E. Martínez-González, P. Vielva, R. B. Barreiro

The polarization of the cosmic microwave background (CMB) can be used to search for parity-violating processes like that predicted by a Chern-Simons coupling to a light pseudoscalar field. Such an interaction rotates $E$ modes into $B$ modes in the observed CMB signal by an effect known as cosmic birefringence. Even though isotropic birefringence can be conf

Venkatesh Thirugnana Sambandham, Konstantin Kirchheim, Sayan Mukhopadhaya, Frank Ortmeier

Landsat-8 (NASA) and Sentinel-2 (ESA) are two prominent multi-spectral imaging satellite projects that provide publicly available data. The multi-spectral imaging sensors of the satellites capture images of the earth's surface in the visible and infrared region of the electromagnetic spectrum. Since the majority of the earth's surface is constantly covered w

Shridhar Velhal, Krishna Kishore VS, Suresh Sundaram

In this paper, a non-iterative spatio-temporal multi-task assignment approach is used for playing piano music by a team of robots. This paper considers the piano playing problem, in which an algorithm needs to compute the trajectories for a dynamically sized team of robots who will play the musical notes by traveling through the specific locations associated

Yejin Bang, Tiezheng Yu, Andrea Madotto, Zhaojiang Lin

Many NLP classification tasks, such as sexism/racism detection or toxicity detection, are based on human values. Yet, human values can vary under diverse cultural conditions. Therefore, we introduce a framework for value-aligned classification that performs prediction based on explicitly written human values in the command. Along with the task, we propose a

Yan Chen, Tao Li

We study Nash equilibria learning of a general-sum stochastic game with an unknown transition probability density function. Agents take actions at the current environment state and their joint action influences the transition of the environment state and their immediate rewards. Each agent only observes the environment state and its own immediate reward and

Daiheng Gao, Yuliang Xiu, Kailin Li, Lixin Yang

Hand, the bearer of human productivity and intelligence, is receiving much attention due to the recent fever of digital twins. Among different hand morphable models, MANO has been widely used in vision and graphics community. However, MANO disregards textures and accessories, which largely limits its power to synthesize photorealistic hand data. In this pape

Bastien Richard, Bruno Bonté, Olivier Barreteau, Isabelle Braud

There has been little exploration of the explicit simulation of the set of options of actors in agent-based models and its evolution over time. This study proposes to use affordances as intermediate entities between agents' environment and agent actions. We illustrated the approach on a typical gravity-fed network in the South-East of France to explore how t

Julie Gerlings, Ioanna Constantiou

Banks hold a societal responsibility and regulatory requirements to mitigate the risk of financial crimes. Risk mitigation primarily happens through monitoring customer activity through Transaction Monitoring (TM). Recently, Machine Learning (ML) has been proposed to identify suspicious customer behavior, which raises complex socio-technical implications aro

Yusuke Nomura, Ryosuke Akashi

Density functional theory (DFT) is an essential building block for modern theoretical physics, chemistry, and engineering, especially those concerning electronic properties. Through decades of development, various program packages for first-principles electronic structure calculation are now available. Their sophisticated interfaces allow users to apply DFT

Van-Anh Nguyen, Khanh Pham Dinh, Long Tung Vuong, Thanh-Toan Do

Recently vision transformers (ViT) have been applied successfully for various tasks in computer vision. However, important questions such as why they work or how they behave still remain largely unknown. In this paper, we propose an effective visualization technique, to assist us in exposing the information carried in neurons and feature embeddings across th

Zahra Askarpour, Mohsen Farokhnezhad, Fahimeh norouzi, Mahdi Esmaeilzadeh

By using non-equilibrium Green's function (NEGF) method and tight-binding (TB) approximation, we investigated a perfect control on spin transport in a zigzag $\alpha^{\prime}$-boron nanoribbon ($\alpha^{\prime}$-BNR) as the must semi-conducting structure of borophene. It has been found that when an $\alpha^{\prime}$-BNR is exposed to an out-of-plane exchange

Christian Kanzow, Theresa Lechner

Optimization problems with composite functions consist of an objective function which is the sum of a smooth and a (convex) nonsmooth term. This particular structure is exploited by the class of proximal gradient methods and some of their generalizations like proximal Newton and quasi-Newton methods. In this paper, we propose a regularized proximal quasi-New

Luigi Forcella, Xiao Luo, Tao Yang, Xiaolong Yang

We study standing waves for a system of nonlinear Schr\"odinger equations with three waves interaction arising as a model for the Raman amplification in a plasma. We consider the mass-critical and mass-supercritical regimes, and we prove existence of ground states along with a synchronized mass collapse behavior. In addition, we show that the set of ground s