May 2023 arXiv papers — page 184

Hao Cheng, Meng Zhang, Liangyou Li, Qun Liu

Utilizing pivot language effectively can significantly improve low-resource machine translation. Usually, the two translation models, source-pivot and pivot-target, are trained individually and do not utilize the limited (source, target) parallel data. This work proposes an end-to-end training method for the cascaded translation model and configures an impro

Ante Kapetanovic, Dragan Poljak, Kun Li

The lack of freely available standardized datasets represents an aggravating factor during the development and testing the performance of novel computational techniques in exposure assessment and dosimetry research. This hinders progress as researchers are required to generate numerical data (field, power and temperature distribution) anew using simulation s

Sameer Kumar Mallik, Roshan Padhan, Mousam Charan Sahu, Suman Roy

The demands of modern electronic components require advanced computing platforms for efficient information processing to realize in-memory operations with a high density of data storage capabilities towards developing alternatives to von Neumann architectures. Herein, we demonstrate the multifunctionality of monolayer MoS2 mem-transistors which can be used a

Yang Li

We study polarised degenerations of $n$-dimensional Calabi-Yau hypersurfaces $\{ F_0F_1\ldots F_m+tF=0\} $, where the essential skeleton has dimension $1\leq m\leq n-1$. We will describe the limiting behaviour of the Calabi-Yau potential at the $C^0$-level, in terms of an optimal transport problem, and in terms of non-archimedean potential theory.

Samuel N. Cohen, Eliana Fausti

We consider the problem of estimating the state of a continuous-time Markov chain from noisy observations. We show that the corresponding optimal filter is strictly contracting pathwise, when considered in the Hilbert projective space, and give explicit deterministic and pathwise rates of convergence. Using this, we provide alternative proofs of the robustne

Loris Bozzato, Thomas Eiter, Rafael Kiesel, Daria Stepanova

We present a continuation to our previous work, in which we developed the MR-CKR framework to reason with knowledge overriding across contexts organized in multi-relational hierarchies. Reasoning is realized via ASP with algebraic measures, allowing for flexible definitions of preferences. In this paper, we show how to apply our theoretical work to real auto

Robert Cameron, Manfred Schüssler

Theoretical models for the solar dynamo range from simple low-dimensional ``toy models'' to complex 3D-MHD simulations. Here we mainly discuss appproaches that are motivated and guided by solar (and stellar) observations. We give a brief overview of the evolution of solar dynamo models since 1950s, focussing upon the development of the Babcock-Leight

D. Parkison, M. A. Tunes, T. J. Nizolek, T. A. Saleh

The fabrication of bulk delta-phase Zirconium Hydride ($δ$-ZrH) using Zircaloy-4 as a precursor is herein reported. Characterization using electron-microscopy methods indicate that the fabricated material is of a single-phase. Sn-rich segregation zones have been observed to form as a direct result of the hydriding process. These findings experimentally valid

Ivan Fedioun

The solution of the two-fluids plane or axisymetric Poiseuille flow is derived analytically. Then, the conditions for the maximum flow rate of the most viscous fluid are analyzed in terms of fluids volume fractions. The axisymmetric case is totally analytical, whereas the plane one is not. In the axisymmetric case, it is shown that an optimum can be found on

Rémi Dulong, Quentin Acher, Baptiste Lepers, Valerio Schiavoni

Modern NVMM is closing the gap between DRAM and persistent storage, both in terms of performance and features. Having both byte addressability and persistence on the same device gives NVMM an unprecedented set of features, leading to the following question: How should we design an NVMM-based caching system to fully exploit its potential? We build two caching

Sanjay Somanath, Vasilis Naserentin, Orfeas Eleftheriou, Daniel Sjölie

The desired outcome for urban digital twins is an automatically generated detailed 3D model of a building from aerial imagery, footprints, LiDAR, or a fusion of these. Such 3D models have applications in architecture, civil engineering, urban planning, construction, real estate, GIS, and many others. Further, the visualization of large-scale data in conjunct

Jason Gibson, Bogdan Vlahov, David Fan, Patrick Spieler

Modeling dynamics is often the first step to making a vehicle autonomous. While on-road autonomous vehicles have been extensively studied, off-road vehicles pose many challenging modeling problems. An off-road vehicle encounters highly complex and difficult-to-model terrain/vehicle interactions, as well as having complex vehicle dynamics of its own. These co

Sashank Kaushik Sridhar, Sayan Ghosh, Avik Dutt

Topological effects manifest in a wide range of physical systems, such as solid crystals, acoustic waves, photonic materials and cold atoms. These effects are characterized by `topological invariants' which are typically integer-valued, and lead to robust quantized channels of transport in space, time, and other degrees of freedom. The temporal channel,

Tae Gab Ha, Seyun Kim

In this paper, we study the blow-up radial solution of fully parabolic system with higher dimensional two species Cauchy problem for some initial condition. In addition, we show that the set of positive radial functions in $L^{1}(\mathbb{R})\cap BUC(\mathbb{R}^{N}) \times L^{1}(\mathbb{R})\cap BUC(\mathbb{R}^{N}) \times W^{1,1}(\mathbb{R}^{N}) \cap W^{1,\inf

Tobias Heinrich, Hung-Tzu Chang, Sergey Zayko, Murat Sivis

We introduce a machine-learning-based approach to enhance the sensitivity of optical-extreme ultraviolet (XUV) transient absorption spectroscopy. A reference spectrum is used as input to a three-layer feed-forward neural network, allowing for an efficient elimination of source noise from measurement data. In pump-probe experiments using high-harmonic radiati

Yuxiang Nie, Heyan Huang, Wei Wei, Xian-Ling Mao

Annotating long-document question answering (long-document QA) pairs is time-consuming and expensive. To alleviate the problem, it might be possible to generate long-document QA pairs via unsupervised question answering (UQA) methods. However, existing UQA tasks are based on short documents, and can hardly incorporate long-range information. To tackle the pr

Evgeny I. Buchbinder, Benjamin J. Stone

We consider the analytic construction of three-point functions of conserved higher-spin supercurrents in three-dimensional $\mathcal{N}=1$ superconformal field theory which are Grassmann-odd in superspace. In particular, these include the three-point functions of the supercurrent and flavour currents, which contain the three-point functions of the energy-mom

Md. Fazlul Huq Khan, Md. Masum Billah

The purpose of this research is to examine the relationship between the Dhaka Stock exchange index return and macroeconomic variables such as exchange rate, inflation, money supply etc. The long-term relationship between macroeconomic variables and stock market returns has been analyzed by using the Johnson Cointegration test, Augmented Dicky Fuller (ADF) an

Ivone Amorim, Eva Maia, Pedro Barbosa, Isabel Praça

The use of Neural Networks (NNs) for sensitive data processing is becoming increasingly popular, raising concerns about data privacy and security. Homomorphic Encryption (HE) has the potential to be used as a solution to preserve data privacy in NN. This study provides a comprehensive analysis on the use of HE for NN training and classification, focusing on

Maryam Al-Yahyai, Fatma Al-Musalhi, Nasser Al-Salti, Ibrahim Elmojtaba

In this paper, we build a mathematical model for the dynamics of COVID-19 to assess the impact of placing healthy individuals in quarantine and isolating infected ones on the number of hospitalization and intensive care unit cases. The proposed model is fully analyzed in order to prove the positivity of solutions, to study the local and global stability of t

Timothy Castiglia, Yi Zhou, Shiqiang Wang, Swanand Kadhe

We propose LESS-VFL, a communication-efficient feature selection method for distributed systems with vertically partitioned data. We consider a system of a server and several parties with local datasets that share a sample ID space but have different feature sets. The parties wish to collaboratively train a model for a prediction task. As part of the trainin

Kai Xiong, Zhihong Wang, Supeng Leng, Jianhua He

Multi-robot system for manufacturing is an Industry Internet of Things (IIoT) paradigm with significant operational cost savings and productivity improvement, where Unmanned Aerial Vehicles (UAVs) are employed to control and implement collaborative productions without human intervention. This mission-critical system relies on 3-Dimension (3-D) scene recognit

Niklas Christoph Affolter

In this PhD thesis we develop the frame work of triple crossing diagram maps (TCD maps), which describes constrained configurations of points in projective spaces and discrete dynamics on these configurations. We are able to capture the constraints and dynamics of a large list of examples that occur in discrete differential geometry (DDG), discrete integrabl

Furkan Simsek, Brian Pfitzmann, Hendrik Raetz, Jona Otholt

Language identification describes the task of recognizing the language of written text in documents. This information is crucial because it can be used to support the analysis of a document's vocabulary and context. Supervised learning methods in recent years have advanced the task of language identification. However, these methods usually require large

Bo Hui, Da Yan, Xiaolong Ma, Wei-Shinn Ku

Lottery Ticket Hypothesis (LTH) claims the existence of a winning ticket (i.e., a properly pruned sub-network together with original weight initialization) that can achieve competitive performance to the original dense network. A recent work, called UGS, extended LTH to prune graph neural networks (GNNs) for effectively accelerating GNN inference. UGS simult

Bertrand Duplantier, Olivier Golinelli, Emmanuel Guitter

We study the statistics of Hamiltonian cycles on various families of bicolored random planar maps (with the spherical topology). These families fall into two groups corresponding to two distinct universality classes with respective central charges $c=-1$ and $c=-2$. The first group includes generic $p$-regular maps with vertices of fixed valency $p\geq 3$, w

Angelo Feraudo, Diana Andreea Popescu, Poonam Yadav, Richard Mortier

As the prevalence of Internet-of-Things (IoT) devices becomes more and more dominant, so too do the associated management and security challenges. One such challenge is the exploitation of vulnerable devices for recruitment into botnets, which can be used to carry out Distributed Denial-of-Service (DDoS) attacks. The recent Manufacturer Usage Description (MU

Ana Casimiro, Cesar Rodrigo

Associated to any affine space A endowed with a metric structure of arbitrary signature we consider the space of affine functionals operating on the space of quadratic functions of A. On this functional space we characterize a symmetric bilinear form derived from the metric structure in a functorial way. We explore the geometrical relations of the relevant o

Jeffrey A. Brock, Daan Swinkels, Bert Koopmans, Eric E. Fullerton

We have performed an experimental and modeling-based study of the spin-orbit torque-induced growth of magnetic stripe domains in heavy metal/ferromagnet thin-film heterostructures that possess chiral Néel-type domain walls due to an interfacial Dzyaloshinskii-Moriya interaction. In agreement with previous reports, the stripe domains stabilized in these syste

Ella Mara Schmidt, Paul Benjamin Klar, Yasar Krysiak, Petr Svora

Structure-property relationships in ordered materials have long been a core principle in materials design. However, the intentional introduction of disorder into materials provides structural flexibility and thus access to material properties that are not attainable in conventional, ordered materials. To understand disorder-property relationships, the disord

William P. Banner, Shima Bab Hadiashar, Grzegorz Mazur, Tim Menke

Model-based optimization, in concert with conventional black-box methods, can quickly solve large-scale combinatorial problems. Recently, quantum-inspired modeling schemes based on tensor networks have been developed which have the potential to better identify and represent correlations in datasets. Here, we use a quantum-inspired model-based optimization me

Daji Landis, Nikolaj I. Schwartzbach

We study an auction with $m$ identical items in a context where $n$ agents can arbitrarily commit to strategies. In general, such commitments non-trivially change the equilibria by inducing a metagame of choosing which strategies to commit to. In this model, we demonstrate a strategy that an attacker may commit to that ensures they receive one such item for

Nicola Galante

The recent results presented in arXiv:2202.05608 have led to significant developments in achieving stable approximations of Helmholtz solutions by plane wave superposition. The study shows that the numerical instability and ill-conditioning inherent in plane wave-based Trefftz methods can be effectively overcome with regularization techniques, provided there

Sara Gholampourkashi, Joanna E. Cygler, Bernie Lavigne, Emily Heath

Purpose: To validate the accuracy of 4D Monte Carlo (4DMC) simulations to calculate dose deliveries to a deforming anatomy in the presence of realistic respiratory motion traces. A previously developed deformable lung phantom comprising an elastic tumor was modified to enable programming of arbitrary motion profiles. 4D simulations of the dose delivered to t

Aaron D. Ratschow, Lisa S. Bauer, Pravash Bista, Stefan A. L. Weber

Charge separation at moving three-phase contact lines is observed in nature as well as technological processes. Despite the growing number of experimental investigations in recent years, the physical mechanism behind the charging remains obscure. Here we identify the origin of charge separation as the dewetting of the bound surface charge within the electric

Sofoklis Kyriakopoulos, Artur S. d'Avila Garcez

Despite the extensive investment and impressive recent progress at reasoning by similarity, deep learning continues to struggle with more complex forms of reasoning such as non-monotonic and commonsense reasoning. Non-monotonicity is a property of non-classical reasoning typically seen in commonsense reasoning, whereby a reasoning system is allowed (differen

Evripidis Bampis, Bruno Escoffier, Themis Gouleakis, Niklas Hahn

We study the Online Traveling Salesperson Problem (OLTSP) with predictions. In OLTSP, a sequence of initially unknown requests arrive over time at points (locations) of a metric space. The goal is, starting from a particular point of the metric space (the origin), to serve all these requests while minimizing the total time spent. The server moves with unit s

Manuel Caceres

A minimum chain cover (MCC) of a $k$-width directed acyclic graph (DAG) $G = (V, E)$ is a set of $k$ chains (paths in the transitive closure) of $G$ such that every vertex appears in at least one chain in the cover. The state-of-the-art solutions for MCC run in time $\tilde{O}(k(|V|+|E|))$ [Mäkinen et at., TALG], $O(T_{MF}(|E|) + k|V|)$, $O(k^2|V| + |E|)$ [C

Albert Fert, Mairbek Chshiev, André Thiaville, Hongxin Yang

Since the early 1960's, the discovery of Dzyaloshinskii-Moriya interaction (DMI) helped to explain the physical mechanisms behind certain magnetic phenomena, such as net moment in antiferromagnets, or enhanced anisotropy field from heavy metals impurity in dilute Cu:Mn alloy. Since the researchers unveil the key role that DMI plays in stabilizing chiral

S. Saberi, G. Meschke, A. Vogel

Immersed finite element methods have been developed as a means to circumvent the costly mesh generation required in conventional finite element analysis. However, the numerical ill-conditioning of the resultant linear system of equations in such methods poses a challenge for iterative solvers. In this work, we focus on the finite cell method (FCM) with adapt

Ruochen Zhao, Shafiq Joty, Yongjie Wang, Tan Wang

The emergence of large-scale pretrained language models has posed unprecedented challenges in deriving explanations of why the model has made some predictions. Stemmed from the compositional nature of languages, spurious correlations have further undermined the trustworthiness of NLP systems, leading to unreliable model explanations that are merely correlate

Uche Oluku, Shaoming Cheng

The paper examines the effects of stringent land use regulations, measured using the Wharton Residential Land Use Regulatory Index (WRLURI), on employment growth during the period 2010-2020 in the Retail, Professional, and Information sectors across 878 local jurisdictions in the United States. All the local jurisdictions exist in both (2006 and 2018) waves

Sho Ejiri, Zsolt Patakfalvi

We prove the Demailly--Peternell--Schneider conjecture in positive characteristic: if $X$ is a smooth projective variety over an algebraically closed field of characteristic $p>0$ with $-K_X$ is nef, then the Albanese morphism $a: X \to A$ is surjective. We also show strengthenings either allowing mild singularities for $X$, or proving more special propertie

Xueguang Ma, Xinyu Zhang, Ronak Pradeep, Jimmy Lin

Supervised ranking methods based on bi-encoder or cross-encoder architectures have shown success in multi-stage text ranking tasks, but they require large amounts of relevance judgments as training data. In this work, we propose Listwise Reranker with a Large Language Model (LRL), which achieves strong reranking effectiveness without using any task-specific

Anja Barz, Chiara Hergl, Gerik Scheuermann

Higher-order tensors appear in various areas of mechanics as well as physics, medicine or earth sciences. As these tensors are highly complex, most are not well understood. Thus, the analysis and the visualization process form a highly challenging task. In order to solve this problem a suitable tensor decomposition for arbitrary tensors is desirable. Since m

Zhen Chen, Jianfeng Wang, Maurizio Brunetti, Francesco Belardo

A graph $G$ is divisible by a graph $H$ if the characteristic polynomial of $G$ is divisible by that of $H$. In this paper, a necessary and sufficient condition for recursive graphs to be divisible by a path is used to show that the H-shape graph $P_{2,2;n-4}^{2,n-7}$, known to be (for $n$ large enough) the minimizer of the spectral radius among the graphs o

Nabajeet Barman, Yuriy Reznik, Maria Martini

Over the years, many subjective and objective quality assessment datasets have been created and made available to the research community. However, there is no standard process for documenting the various aspects of the dataset, such as details about the source sequences, number of test subjects, test methodology, encoding settings, etc. Such information is o

Octavio M. Guilera, Pablo Benitez-Llambay, Marcelo M. Miller Bertolami, Martin E. Pessah

Disk solids are critical in many planet formation processes, however, their effect on planet migration remains largely unexplored. Here we assess for the first time this important issue by building on the systematic measurements of dust torques on an embedded planet by Benitez-Llambay & Pessah (2018). Adopting standard models for the gaseous disk and its sol

Zebin Ou, Yue Zhang

Robust loss functions are designed to combat the adverse impacts of label noise, whose robustness is typically supported by theoretical bounds agnostic to the training dynamics. However, these bounds may fail to characterize the empirical performance as it remains unclear why robust loss functions can underfit. We show that most loss functions can be rewritt

Francesco Binucci, Paolo Banelli, Paolo Di Lorenzo, Sergio Barbarossa

Edge Learning (EL) pushes the computational resources toward the edge of 5G/6G network to assist mobile users requesting delay-sensitive and energy-aware intelligent services. A common challenge in running inference tasks from remote is to extract and transmit only the features that are most significant for the inference task. From this perspective, EL can b

Nicholas Meadows, Xiaoyan Li, Nathaniel D Osgood

The growing complexity of decision-making in public health and health care has motivated an increasing use of mathematical modeling. An important line of health modeling is based on stock & flow diagrams. Such modeling elevates transparency across the interdisciplinary teams responsible for most impactful models, but existing tools suffer from a number of sh

Shyan Akmal, Ce Jin

Our work concerns algorithms for an unweighted variant of Maximum Flow. In the All-Pairs Connectivity (APC) problem, we are given a graph $G$ on $n$ vertices and $m$ edges, and are tasked with computing the maximum number of edge-disjoint paths from $s$ to $t$ (equivalently, the size of a minimum $(s,t)$-cut) in $G$, for all pairs of vertices $(s,t)$. Althou

Younès Rabii, Michael Cook

Although procedural generation is popular among game developers, academic research on the topic has primarily focused on new applications, with some research into empirical analysis. In this paper we relate theoretical work in information theory to the generation of content for games. We prove that there is a relationship between the Kolomogorov complexity o

Roberto Alicandro, Lucia De Luca, Mariapia Palombaro, Marcello Ponsiglione

We propose nonlinear semi-discrete and discrete models for the elastic energy induced by a finite systems of edge dislocations in two dimensions. Within the dilute regime, we analyze the asymptotic behavior of the nonlinear elastic energy, as the core-radius (in the semi-discrete model) and the lattice spacing (in the purely discrete one) vanish. Our analysi

Bahri Batuhan Bilecen, Mustafa Ayazoglu

We propose a real-time and lightweight single-image super-resolution (SR) network named Bicubic++. Despite using spatial dimensions of the input image across the whole network, Bicubic++ first learns quick reversible downgraded and lower resolution features of the image in order to decrease the number of computations. We also construct a training pipeline, w

Kuang-Hao, Liu

This works explores the correlation between channels in reconfigurable intelligent surface (RIS)-aided communication systems. In this type of system, an RIS made up of many passive elements with adjustable phases reflects the transmitter's signal to the receiver. Since the transmitter-RIS link may be shared by multiple receivers, the cascade channels of

Weicong Chen, Chao-Kai Wen, Xiao Li, Michail Matthaiou

Reconfigurable intelligent surfaces (RISs) represent a pioneering technology to realize smart electromagnetic environments by reshaping the wireless channel. \textcolor[rgb]{0,0,0}{Jointly designing the transceiver and RIS relies on the channel state information (CSI), whose feedback has not been investigated in multi-RIS-assisted frequency division duplexin

Shuxian Quan, Ling Chen, Siyao Wu, Baocheng Zhang

Vectorial polarized fields of light has been applied to detect the rotational velocity by the rotational Doppler effect, but the measurement was made for the rotation of a single-particle system. When the rotational surface is rough, the scattered vectorial Doppler signal spectrum is complex. In this paper, we make the complex spectrum analyses using orbital

Honoka Shiratori, Hiroaki Shinkawa, André Röhm, Nicolas Chauvet

Collective decision-making is crucial to information and communication systems. Decision conflicts among agents hinder the maximization of potential utilities of the entire system. Quantum processes can realize conflict-free joint decisions among two agents using the entanglement of photons or quantum interference of orbital angular momentum (OAM). However,

Zhen Wei, Pascal Fua, Michaël Bauerheim

We propose two deep learning models that fully automate shape parameterization for aerodynamic shape optimization. Both models are optimized to parameterize via deep geometric learning to embed human prior knowledge into learned geometric patterns, eliminating the need for further handcrafting. The Latent Space Model (LSM) learns a low-dimensional latent rep

Andrew Granville

How does the mathematical community accept that a given proof is correct? Is objective verification based on explicit axioms feasible, or must the reviewer's experiences and prejudices necessarily come into play? Can automated provers avoid mistakes (as well as experiences and prejudices) to provide objective verification? And can an automated prover&#39

Cheng Li, Ze-Chun Hu, Qian-Qian Zhou

Let $B(n,p)$ denote a binomial random variable with parameters $n$ and $p$. Chvátal's theorem says that for any fixed $n\geq 2$, as $m$ ranges over $\{0,\ldots,n\}$, the probability $q_m:=P(B(n,m/n)\leq m)$ is the smallest when $m$ is closest to $\frac{2n}{3}$. Motivated by this theorem, we consider the minimum value problem on the probability that a ran

Jan Philipp Bange, Paul Werner, David Schmitt, Wiebke Bennecke

The energy landscape of optical excitations in mono- and few-layer transition metal dichalcogenides (TMDs) is dominated by optically bright and dark excitons. These excitons can be fully localized within a single TMD layer, or the electron- and the hole-component of the exciton can be charge-separated over multiple TMD layers. Such intra- or interlayer excit

Maria Camisassa, Santiago Torres, Mark Hollands, Detlev Koester

The ESA Gaia space mission has revealed a bifurcation of the white dwarf (WD) sequence on the color magnitude diagram in two branches: A and B. While the A branch consists mostly of WDs with H-rich atmospheres, the B branch is not completely understood. Although invoked to be populated mainly by He-rich WDs, the B branch overlaps a $\sim 0.8M_\odot$ evolutio

Gayatri Singh, Kavita Dorai, Arvind

We experimentally demonstrate the transfer of an unknown single-qubit state from Alice to Bob via a two-step discrete-time quantum random walk on a cycle with four vertices on a four-qubit nuclear magnetic resonance quantum processor. The qubits with Alice and Bob are used as coin qubits and the walk is carried out on in a two-qubit `Gaming Arena'. In th

Domenic Rosati

Communication of scientific findings to the public is important for keeping non-experts informed of developments such as life-saving medical treatments. However, generating readable lay summaries from scientific documents is challenging, and currently, these summaries suffer from critical factual errors. One popular intervention for improving factuality is u

Andrea Ramazzina, Mario Bijelic, Stefanie Walz, Alessandro Sanvito

Vision in adverse weather conditions, whether it be snow, rain, or fog is challenging. In these scenarios, scattering and attenuation severly degrades image quality. Handling such inclement weather conditions, however, is essential to operate autonomous vehicles, drones and robotic applications where human performance is impeded the most. A large body of wor

Mohamed El Alami

Given a Fano variety $Y$ and a simple normal crossings divisor $D\subseteq Y$ which is anti-canonical, we prove a formula relating counts of discs with boundary on a Lagrangian $L\subseteq Y\backslash D$ to counts of rational curves in $Y$, under suitable positivity assumptions on $L$. This formula seriously constrains the topology of $L$ in many examples. O

Bing'er Jiang, Erik Ekstedt, Gabriel Skantze

Filled pauses (or fillers), such as "uh" and "um", are frequent in spontaneous speech and can serve as a turn-holding cue for the listener, indicating that the current speaker is not done yet. In this paper, we use the recently proposed Voice Activity Projection (VAP) model, which is a deep learning model trained to predict the dynamics of co

Chaobing Zheng, Jun Jiang, Wenjian Ying, Shiqian Wu

It is challenging to remove rain-steaks from a single rainy image because the rain steaks are spatially varying in the rainy image. Although the CNN based methods have reported promising performance recently, there are still some defects, such as data dependency and insufficient interpretation. A single image deraining algorithm based on the combination of d

Yufei Guo, Weihang Peng, Yuanpei Chen, Liwen Zhang

Emerged as a biology-inspired method, Spiking Neural Networks (SNNs) mimic the spiking nature of brain neurons and have received lots of research attention. SNNs deal with binary spikes as their activation and therefore derive extreme energy efficiency on hardware. However, it also leads to an intrinsic obstacle that training SNNs from scratch requires a re-

Gerhard Rein

We review stability and instability results for self-gravitating matter distributions, where the matter model is a collisionless gas as described by the Vlasov equation. The focus is on the general relativistic situation, i.e., on steady states of the Einstein-Vlasov system and their stability properties. In order to put things into perspective we include th

Carl Chalmers, Paul Fergus, Serge Wich, Steven N Longmore

Birds are important indicators for monitoring both biodiversity and habitat health; they also play a crucial role in ecosystem management. Decline in bird populations can result in reduced eco-system services, including seed dispersal, pollination and pest control. Accurate and long-term monitoring of birds to identify species of concern while measuring the

Christos Vasileiou, Josiah W. Smith, Shiva Thiagarajan, Matthew Nigh

In this paper, we introduce an innovative super resolution approach to emerging modes of near-field synthetic aperture radar (SAR) imaging. Recent research extends convolutional neural network (CNN) architectures from the optical to the electromagnetic domain to achieve super resolution on images generated from radar signaling. Specifically, near-field synth

L. Linan, F. Regnault, B. Perri, M. Brchnelova

The aim of this paper is to demonstrate the possible use of the new coronal model COCONUT to compute a detailed representation of a numerical CME at 0.1~AU, after its injection at the solar surface and propagation in a realistic solar wind, as derived from observed magnetograms. We present the implementation and propagation of modified Titov-Démoulin (TDm) f

Richard Pates

The cyclic feedback interconnection of $n$ subsystems is the basic building block of control theory. Many robust stability tools have been developed for this interconnection. Two notable examples are the small gain theorem and the Secant Criterion. Both of these conditions guarantee stability if an inequality involving the geometric mean of a set of subsyste

Stephen Kerby, Abraham D. Falcone

Recent works have developed samples of blazars from among the Fermi-LAT unassociated sources via machine learning comparisons with known blazar samples. Continued analysis of these new blazars tests the predictions of the blazar sequence and enables more flux-complete samples of blazars as a population. Using Fermi, Swift, WISE, and archival radio data, we c

Maloy Kumar Devnath, Avijoy Chakma, Mohammad Saeid Anwar, Emon Dey

Due to its light and weather-independent sensing, millimeter-wave (MMW) radar is essential in smart environments. Intelligent vehicle systems and industry-grade MMW radars have integrated such capabilities. Industry-grade MMW radars are expensive and hard to get for community-purpose smart environment applications. However, commercially available MMW radars

Orestis Papakyriakopoulos, Alice Xiang

Speech AI Technologies are largely trained on publicly available datasets or by the massive web-crawling of speech. In both cases, data acquisition focuses on minimizing collection effort, without necessarily taking the data subjects' protection or user needs into consideration. This results to models that are not robust when used on users who deviate fr

Fabian Immel, Richard Fehler, Mohammad M. Ghanaat, Florian Ries

High Definition (HD) maps are necessary for many applications of automated driving (AD), but their manual creation and maintenance is very costly. Vehicle fleet data from series production vehicles can be used to automatically generate HD maps, but the data is often incomplete and noisy. We propose a system for the generation of HD maps from vehicle fleet da

Rushrukh Rayan, Cogan Shimizu, Pascal Hitzler

We present an ontology design pattern for modeling Names as part of Roles, to capture scenarios where an Agent performs different Roles using different Names associated with the different Roles. Examples of an Agent performing a Role using different Names are rather ubiquitous, e.g., authors who write under different pseudonyms, or different legal names for

Przemysław Koprowski

Polynomial factorization and root finding are among the most standard themes of computational mathematics. Yet still, little has been done for polynomials over quaternion algebras, with the single exception of Hamiltonian quaternions for which there are known numerical methods for polynomial root approximation. The sole purpose of the present paper is to pre

Xin Pan, Shuang-Liang Li, Xinwu Cao

After the first quasi-periodic eruptions (QPEs, GSN069) was reported in 2019, four other sources have been identified as QPEs or its candidate. However, the physics behind QPEs is still unclear so far, though several models have been proposed. Pan et al. (2022) proposed an instability model for the accretion disk with magnetically driven outflows in the firs

M. A. Moreno-Frías, J. C. Rosales

In this work we will introduce the concept of ratio-covariety, as a nonempty family $\mathscr{R}$ of numerical semigroups verifying certain properties. This concept will allow us to: \begin{enumerate} \item Describe an algorithmic process to compute $\mathscr{R}.$ \item Prove the existence of the smallest element of $\sR$ that contains a set of positive inte

Subash Adhikari, William H. Matthaeus, Tulasi N. Parashar, Michael A. Shay

In this study we explore the statistics of pressure fluctuations in kinetic collisionless turbulence. A 2.5D kinetic particle-in-cell (PIC) simulation of decaying turbulence is used to investigate pressure balance via the evolution of thermal and magnetic pressure in a plasma with beta of order unity. We also discuss the behavior of thermal, magnetic and tot

Christopher D. P. Duffy, Gregoire Canchon, Thomas J. Haworth, Edward Gillen

Here we discuss the feasibility of photosynthesis on Earth-like rocky planets in close orbit around ultra-cool red dwarf stars. Stars of this type have very limited emission in the \textit{photosynthetically active} region of the spectrum ($400 - 700$ nm), suggesting that they may not be able to support oxygenic photosynthesis. However, photoautotrophs on Ea

Zhengru Ren

Backstepping is a mature and powerful Lyapunov-based design approach for a specific set of systems. Throughout the development over three decades, innovative theories and practices have extended backstepping to stabilization and tracking problems for nonlinear systems with growing complexity. The attractions of the backstepping-like approach are the recursiv

H. C. Das

This thesis explores the effects of dark matter (DM) on neutron stars (NSs) using the relativistic mean-field (RMF) model. The effects of DM on NS properties, including the mass-radius relation, the moment of inertia, and tidal deformability, are calculated by varying its fraction. The study found that the EOS becomes softer with increasing DM momentum, and

Josiah Smith, Murat Torlak

In this article, we introduce a novel algorithm for efficient near-field synthetic aperture radar (SAR) imaging for irregular scanning geometries. With the emergence of fifth-generation (5G) millimeter-wave (mmWave) devices, near-field SAR imaging is no longer confined to laboratory environments. Recent advances in positioning technology have attracted signi

Tarek Stolz, István Koren, Liam Tirpitz, Sandra Geisler

With the increasing prevalence of IoT environments, the demand for processing massive distributed data streams has become a critical challenge. Data Stream Processing on the Edge (DSPoE) systems have emerged as a solution to address this challenge, but they often struggle to cope with the heterogeneity of hardware and platforms. To address this issue, we pro

Ahmed N. Ahmed, Siegfried Mercelis, Ali Anwar

In the domain of intelligent transportation systems (ITS), collaborative perception has emerged as a promising approach to overcome the limitations of individual perception by enabling multiple agents to exchange information, thus enhancing their situational awareness. Collaborative perception overcomes the limitations of individual sensors, allowing connect

Kairui Guo, Adrian Cheng, Yaqi Li, Jun Li

This paper aims to develop a new human-machine interface to improve rehabilitation performance from the perspective of both the user (patient) and the machine (robot) by introducing the co-adaption techniques via model-based reinforcement learning. Previous studies focus more on robot assistance, i.e., to improve the control strategy so as to fulfill the obj

Jan Grošelj, Hendrik Speleers

The space of $C^1$ cubic Clough-Tocher splines is a classical finite element approximation space over triangulations for solving partial differential equations. However, for such a space there is no B-spline basis available, which is a preferred choice in computer aided geometric design and isogeometric analysis. A B-spline basis is a locally supported basis

Jan Dreier, Robert Ganian, Thekla Hamm

Courcelle's theorem and its adaptations to cliquewidth have shaped the field of exact parameterized algorithms and are widely considered the archetype of algorithmic meta-theorems. In the past decade, there has been growing interest in developing parameterized approximation algorithms for problems which are not captured by Courcelle's theorem and, in

Zeinab Sadjadi, Heiko Rieger

Many biological active agents respond to gradients of environmental cues by redirecting their motion. Besides the well-studied prominent examples such as photo- and chemotaxis, there has been considerable recent interest in topotaxis, i.e.\ the ability to sense and follow topographic environmental cues. We numerically investigate the topotaxis of active agen

Ermes Franch, Philippe Gaborit, Chunlei Li

In this paper we generalize the notion of low-rank parity check (LRPC) codes by introducing a bilinear product over F^m q based on a generic 3-tensor in Fq^mxmxm, where Fq is the finite field with q elements. The generalized LRPC codes are Fq -linear codes in general and a particular choice of the 3-tensor corresponds to the original Fqm -linear LRPC codes.

Marc Carrascosa, Giovanni Geraci, Edward Knightly, Boris Bellalta

In this article, we investigate the real-world capability of the multi-link operation (MLO) framework -- one of the key MAC-layer features included in the IEEE 802.11be amendment -- by using a large dataset containing 5 GHz spectrum occupancy measurements on multiple channels. Our results show that when both available links are often busy, as is the case in

Vadim A. Bednyakov

In the paper expressions are obtained for the event rates expected in experiments aimed at direct detection of dark matter (DM) particles. These expressions allow one to estimate the rates taking into account simultaneously elastic (coherent) and inelastic (incoherent) channels of DM particle interaction with nuclei. The nonzero nuclear excitation energies a

Dennis Trautwein, Moritz Schubotz, Bela Gipp

It allows any two parties that are either both on the same network or connected via the internet to transfer the contents of a file based on a particular sequence of words. Peer discovery happens via multicast DNS if both peers are on the same network or via entries in the distributed hash table (DHT) of the InterPlanetary File-System (IPFS) if both peers ar

Said Fahlaoui, Hakim Monaim

In this paper, we present the general one-dimensional Clifford Fourier Transform. We derive fundamental properties: Plancherel theorem, reconstruction and convolution formulas. Additionally, we provide an application to probability theory illustrating results by examples.