March 2024 arXiv papers — page 142

Yasuko Kawahata

The efforts of this Note are aimed at understanding various phenomena in digital space that are incomplete and difficult to define, and to translate them into language from research fields that are based on existing large-scale experimental data. Information diffusion and user behavior patterns in digital space are often hard to intuitively capture, and the

Jinghan Huang, Qiufeng Chen, Yijun Bian, Pengli Zhu

Graph neural networks (GNNs) have proven effective in capturing relationships among nodes in a graph. This study introduces a novel perspective by considering a graph as a simplicial complex, encompassing nodes, edges, triangles, and $k$-simplices, enabling the definition of graph-structured data on any $k$-simplices. Our contribution is the Hodge-Laplacian

Junyoung Kim, Kyungsik Lee

We consider the chance-constrained binary knapsack problem (CKP), where the item weights are independent and normally distributed. We introduce a continuous relaxation for the CKP, represented as a non-convex optimization problem, which we call the non-convex relaxation. A comparative study shows that the non-convex relaxation provides an upper bound for the

Julian Frattini, Michael Unterkalmsteiner, Davide Fucci, Daniel Mendez

Tools constitute an essential contribution to natural language processing for requirements engineering (NLP4RE) research. They are executable instruments that make research usable and applicable in practice. In this chapter, we first introduce a systematic classification of NLP4RE tools to improve the understanding of their types and properties. Then, we ext

Jing Guo, Yuming Liu, Yu Ye

Let $G$ be a Brauer graph and $A$ the associated Brauer graph algebra. Denote by $gr(A)$ the graded algebra associated with the radical filtration of $A$. The question when $gr(A)$ is of finite representation type was answered in [9]. In the present paper, we characterize when $gr(A)$ is domestic in terms of the associated Brauer graph $G$.

Charlie Budd, Tom Vercauteren

Relative monocular depth, inferring depth up to shift and scale from a single image, is an active research topic. Recent deep learning models, trained on large and varied meta-datasets, now provide excellent performance in the domain of natural images. However, few datasets exist which provide ground truth depth for endoscopic images, making training such mo

Siyu Duan, Jun Wang, Qi Su

Cultural heritage serves as the enduring record of human thought and history. Despite significant efforts dedicated to the preservation of cultural relics, many ancient artefacts have been ravaged irreversibly by natural deterioration and human actions. Deep learning technology has emerged as a valuable tool for restoring various kinds of cultural heritages,

Jintao Huang, Yiu-Ming Cheung, Chi-Man Vong

Existing Partial Label Learning (PLL) methods posit that training and test data adhere to the same distribution, a premise that frequently does not hold in practical application where Out-of-Distribution (OOD) objects are present. We introduce the OODPLL paradigm to tackle this significant yet underexplored issue. And our newly proposed PLOOD framework enabl

Robert Graubohm, Marvin Loba, Marcus Nolte, Markus Maurer

Developers have to obtain a sound understanding of existing risk potentials already in the concept phase of driverless vehicles. Deductive as well as inductive SOTIF analyses of potential triggering conditions for hazardous behavior help to achieve this goal. In this regard, ISO 21448 suggests conducting a System-Theoretic Process Analysis (STPA). In this ar

Qilang Ye, Zitong Yu, Xin Liu

Audio-visual question answering (AVQA) requires reference to video content and auditory information, followed by correlating the question to predict the most precise answer. Although mining deeper layers of audio-visual information to interact with questions facilitates the multimodal fusion process, the redundancy of audio-visual parameters tends to reduce

Giulia Pagliaroli, Christoph A. Ternes

We discuss the possibility to observe neutrinos emitted from a failed core collapse Supernova in the various experiments at Laboratori Nazionali del Gran Sasso. We show that the veto regions of dark matter and neutrinoless double beta decay experiments can be used as a network of small detectors to measure Supernova neutrinos. In addition we show that this n

Yury Demidovich, Grigory Malinovsky, Peter Richtárik

In this study, we investigate stochastic optimization on Riemannian manifolds, focusing on the crucial variance reduction mechanism used in both Euclidean and Riemannian settings. Riemannian variance-reduced methods usually involve a double-loop structure, computing a full gradient at the start of each loop. Determining the optimal inner loop length is chall

Shunsuke Yasuki, Masato Taki

Recently, convolutional neural networks (CNNs) with large size kernels have attracted much attention in the computer vision field, following the success of the Vision Transformers. Large kernel CNNs have been reported to perform well in downstream vision tasks as well as in classification performance. The reason for the high-performance of large kernel CNNs

Cristina Improta

AI-based code generators have gained a fundamental role in assisting developers in writing software starting from natural language (NL). However, since these large language models are trained on massive volumes of data collected from unreliable online sources (e.g., GitHub, Hugging Face), AI models become an easy target for data poisoning attacks, in which a

Hanxiao Chen

Most computer vision applications aim to identify pixels in a scene and use them for diverse purposes. One intriguing application is car damage detection for insurance carriers which tends to detect all car damages by comparing both pre-trip and post-trip images, even requiring two components: (i) car damage detection; (ii) image alignment. Firstly, we imple

Nicolò Defenu, David Mukamel, Stefano Ruffo

Ensemble inequivalence, i.e. the possibility of observing different thermodynamic properties depending on the statistical ensemble which describes the system, is one of the hallmarks of long-range physics, which has been demonstrated in numerous classical systems. Here, an example of ensemble inequivalence of a long-range quantum ferromagnet is presented. Wh

Nikita Tsoy, Anna Mihalkova, Teodora Todorova, Nikola Konstantinov

Cross-silo federated learning (FL) allows data owners to train accurate machine learning models by benefiting from each others private datasets. Unfortunately, the model accuracy benefits of collaboration are often undermined by privacy defenses. Therefore, to incentivize client participation in privacy-sensitive domains, a FL protocol should strike a delica

Eva Fluck, Sandra Kiefer, Christoph Standke

Tangles were originally introduced as a concept to formalize regions of high connectivity in graphs. In recent years, they have also been discovered as a link between structural graph theory and data science: when interpreting similarity in data sets as connectivity between points, finding clusters in the data essentially amounts to finding tangles in the un

Yukimi Goto

We show that the $N$-electron Hamiltonian $H(N, Z)$ with the total nuclear charge $Z$ has no normalizable ground state if the ground state energy $E(N, Z)$ satisfies $E(N, Z)= E(N-1, Z)$ for $Z=N-1$. For anions $\mathrm{He}^-, \mathrm{Be}^-, \mathrm{N}^-, \mathrm{Ne}^-$, etc., many numerical results give strong evidence of the condition $E(N, Z)= E(N-1, Z)$.

Xinyuan Gao, Songlin Dong, Yuhang He, Xing Wei

In real-world applications, dynamic scenarios require the models to possess the capability to learn new tasks continuously without forgetting the old knowledge. Experience-Replay methods store a subset of the old images for joint training. In the scenario of more strict privacy protection, storing the old images becomes infeasible, which leads to a more seve

Essizewa Essowedeou Agate, Nyomboi Timothy, Ambassah O. Nathaniel, Ines Ngassam

Expansive soils such as Black Cotton Soils (BCS) present significant challenges for road subgrade construction due to their high plasticity, swelling potential, and low strength. This study explores a triphasic stabilization method using Bamboo Charcoal (BC), Quarry Dust (QD), and Lime (L) to enhance the engineering properties of BCS for rural road applicati

Jaewon Jung, Hongsun Jang, Jaeyong Song, Jinho Lee

Adversarial robustness of the neural network is a significant concern when it is applied to security-critical domains. In this situation, adversarial distillation is a promising option which aims to distill the robustness of the teacher network to improve the robustness of a small student network. Previous works pretrain the teacher network to make it robust

Panagiotis Charalampopoulos, Paweł Gawrychowski, Samah Ghazawi

A fundamental concept related to strings is that of repetitions. It has been extensively studied in many versions, from both purely combinatorial and algorithmic angles. One of the most basic questions is how many distinct squares, i.e., distinct strings of the form $UU$, a string of length $n$ can contain as fragments. It turns out that this is always $\mat

Ziqi Gao, Tao Feng, Jiaxuan You, Chenyi Zi

AlphaFold can be used for both single-chain and multi-chain protein structure prediction, while the latter becomes extremely challenging as the number of chains increases. In this work, by taking each chain as a node and assembly actions as edges, we show that an acyclic undirected connected graph can be used to predict the structure of multi-chain protein c

Chengjie Luo, Yicheng Qiang, David Zwicker

Phase separation, crucial for spatially segregating biomolecules in cells, is well-understood in the simple case of a few components with pairwise interactions. Yet, biological cells challenge the simple picture in at least two ways: First, biomolecules, like proteins and nucleic acids, exhibit complex, higher-order interactions, where a single molecule may

Kanad Sengupta, S. P. Dinesh, K. Muhammed Shafi, Soumya Asokan

For quantum computation using photons, performing deterministic quantum gate operations is a challenge due to the probabilistic nature of the photon-photon interaction. Encoding qubits in multiple degrees-of-freedom of photons and controlling operations between them is one of the promising ways to navigate the probabilistic behavior. Using single-photon disc

Hongsun Jang, Jaeyong Song, Jaewon Jung, Jaeyoung Park

The recent huge advance of Large Language Models (LLMs) is mainly driven by the increase in the number of parameters. This has led to substantial memory capacity requirements, necessitating the use of dozens of GPUs just to meet the capacity. One popular solution to this is storage-offloaded training, which uses host memory and storage as an extended memory

Alexander Mang

A resolution $P$ of the counit of the Hopf $\ast$-algebra $\mathcal{O}(U_n^+)$ of representative functions on van Daele and Wang's free unitary quantum group $U_n^+$ in terms of free $\mathcal{O}(U_n^+)$-modules is computed for arbitrary $n$. A different such resolution was recently found by Baraquin, Franz, Gerhold, Kula and Tobolski. While theirs has desir

Massimo Fornasier, Lukang Sun

Consensus-based optimization (CBO) is an agent-based derivative-free method for non-smooth global optimization that has been introduced in 2017, leveraging a surprising interplay between stochastic exploration and Laplace principle. In addition to its versatility and effectiveness in handling high-dimensional, non-convex, and non-smooth optimization problems

Batuhan Cengiz, Mert Gulsen, Yusuf H. Sahin, Gozde Unal

Point clouds and meshes are widely used 3D data structures for many computer vision applications. While the meshes represent the surfaces of an object, point cloud represents sampled points from the surface which is also the output of modern sensors such as LiDAR and RGB-D cameras. Due to the wide application area of point clouds and the recent advancements

Yujuan Ding, Yunshan Ma, Wenqi Fan, Yige Yao

Fashion analysis refers to the process of examining and evaluating trends, styles, and elements within the fashion industry to understand and interpret its current state, generating fashion reports. It is traditionally performed by fashion professionals based on their expertise and experience, which requires high labour cost and may also produce biased resul

Che Liu, Zhongwei Wan, Cheng Ouyang, Anand Shah

Electrocardiograms (ECGs) are non-invasive diagnostic tools crucial for detecting cardiac arrhythmic diseases in clinical practice. While ECG Self-supervised Learning (eSSL) methods show promise in representation learning from unannotated ECG data, they often overlook the clinical knowledge that can be found in reports. This oversight and the requirement for

Henrique Jesus, Hugo Proença

Large vision models based in deep learning architectures have been consistently advancing the state-of-the-art in biometric recognition. However, three weaknesses are commonly reported for such kind of approaches: 1) their extreme demands in terms of learning data; 2) the difficulties in generalising between different domains; and 3) the lack of interpretabi

Anders Bredahl Kock, Rasmus Søndergaard Pedersen, Jesper Riis-Vestergaard Sørensen

Lasso-type estimators are routinely used to estimate high-dimensional time series models. The theoretical guarantees established for these estimators typically require the penalty level to be chosen in a suitable fashion often depending on unknown population quantities. Furthermore, the resulting estimates and the number of variables retained in the model de

Suryadev Pratap Singh, Mohammad Rafiuddin, Subham Banerjee, Sreenivas K R

We have explored the evening transition using data from eighty days of observations across two fog seasons at the Kempegowda International Airport, Bengaluru (KIAB). Through field experiments and simulations integrating aerosol interaction in a radiation-conduction model, we elucidate the impact of aerosols on longwave cooling of the Atmospheric Boundary Lay

Mohsen Alishahiha, Mohammad Javad Vasli

We study thermalization in closed non-integrable quantum systems using the Krylov basis. We demonstrate that for thermalization to occur, the matrix representation of typical local operators in the Krylov basis should exhibit a specific tridiagonal form with all other elements in the matrix are exponentially small, reminiscent of the eigenstate thermalizatio

L. Reynier, Bastien Di Pierro, Frédéric Alizard, Anne Cadiou

In the present study, the efficiency of preconditioners for solving linear systems associated with the discretized variable-density incompressible Navier-Stokes equations with semiimplicit second-order accuracy in time and spectral accuracy in space is investigated. The method, in which the inverse operator for the constant-density flow system acts as precon

Zhiyuan Zhai, Xiaojun Yuan, Xin Wang, Huiyuan Yang

To exploit unprecedented data generation in mobile edge networks, federated learning (FL) has emerged as a promising alternative to the conventional centralized machine learning (ML). However, there are some critical challenges for FL deployment. One major challenge called straggler issue severely limits FL's coverage where the device with the weakest channe

Olalla A. Castro-Alvaredo, Lucía Santamaría-Sanz

In this short review we present the key definitions, ideas and techniques involved in the study of symmetry resolved entanglement measures, with a focus on the symmetry resolved entanglement entropy. In order to be able to define such entanglement measures, it is essential that the theory under study possess an internal symmetry. Then, symmetry resolved enta

A. D'Adamo, M. Roel-Lesur, L. Turmo-Vidal, M. M. Dehshibi

Changes in body perception influence behavior and emotion and can be induced through multisensory feedback. Auditory feedback to one's actions can trigger such alterations; however, it is unclear which individual factors modulate these effects. We employ and evaluate SoniWeight Shoes, a wearable device based on literature for altering one's weight perception

Zheyu Wu, Jiasheng Chen, Theodore. I. Weinberger, Andrej Cabala

The phase diagram of the heavy fermion compound UTe$_2$ contains multiple superconducting phases, several of which show characteristics of odd-parity pairing. We have investigated the pressure dependence of the superconducting transition in high-quality crystals of UTe$_2$ by tracking its signature in the magnetic susceptibility $\chi(T)$. A single, sharp su

Zeki Zeybek, Peter Schmelcher, Rick Mukherjee

The Bose-Hubbard model (BHM) has been widely explored to develop a profound understanding of the strongly correlated behavior of interacting bosons. Quantum simulators not only allow the exploration of the BHM but also extend it to models with interesting phenomena such as gapped phases with multiple orders and topological phases. In this work, an extended B

Niklas Vaara, Pekka Sangi, Miguel Bordallo López, Janne Heikkilä

Point clouds have been a recent interest for ray tracing-based radio channel characterization, as sensors such as RGB-D cameras and laser scanners can be utilized to generate an accurate virtual copy of a physical environment. In this paper, a novel ray launching algorithm is presented, which operates directly on noisy point clouds acquired from sensor data.

Arturo de Pablo, Fernando Quirós, Jorge Ruiz-Cases

We study the positivity and asymptotic behaviour of nonnegative solutions of a general nonlocal fast diffusion equation, \[\partial_t u + \mathcal{L}\varphi(u) = 0,\] and the interplay between these two properties. Here $\mathcal{L}$ is a stable-like operator and $\varphi$ is a singular nonlinearity. We start by analysing positivity by means of a weak Harnac

Axel Abels, Elias Fernandez Domingos, Ann Nowé, Tom Lenaerts

Individual and social biases undermine the effectiveness of human advisers by inducing judgment errors which can disadvantage protected groups. In this paper, we study the influence these biases can have in the pervasive problem of fake news by evaluating human participants' capacity to identify false headlines. By focusing on headlines involving sensitive c

Francesco Dell'Accio, Alvise Sommariva, Marco Vianello

Existence of sufficient conditions for unisolvence of Kansa unsymmetric collocation for PDEs is still an open problem. In this paper we make a first step in this direction, proving that unsymmetric collocation matrices with Thin-Plate Splines for the 2D Poisson equation are almost surely nonsingular, when the discretization points are chosen randomly on doma

Fatemeh Ahmadi, Mohamad Ebrahim Shiri, Behroz Bidabad, Maral Sedaghat

Automated feature extraction from MRI brain scans and diagnosis of Alzheimer's disease are ongoing challenges. With advances in 3D imaging technology, 3D data acquisition is becoming more viable and efficient than its 2D counterpart. Rather than using feature-based vectors, in this paper, for the first time, we suggest a pipeline to extract novel covariance-

Sebastian Bordt, Harsha Nori, Rich Caruana

While many have shown how Large Language Models (LLMs) can be applied to a diverse set of tasks, the critical issues of data contamination and memorization are often glossed over. In this work, we address this concern for tabular data. Starting with simple qualitative tests for whether an LLM knows the names and values of features, we introduce a variety of

Qirui Huang, Marc Syndicus, Jérôme Frisch, Christoph van Treeck

Accurate occupancy information helps to improve building energy efficiency and occupant comfort. Occupancy detection methods based on CO2 sensors have received attention due to their low cost and low intrusiveness. In naturally ventilated buildings, the accuracy of CO2-based occupancy detection is generally low in related studies due to the complex ventilati

Weiqing Luo, Chonggang Song, Lingling Yi, Gong Cheng

Combining semantic information with behavioral data is a crucial research area in recommender systems. A promising approach involves leveraging external knowledge to enrich behavioral-based recommender systems with abundant semantic information. However, this approach faces two primary challenges: denoising raw external knowledge and adapting semantic repres

Yuan Liao, Jorge Gil, Sonia Yeh, Rafael H. M. Pereira

Socio-spatial segregation is the physical separation of different social, economic, or demographic groups within a geographic space, often resulting in unequal access to resources, services, and opportunities. The literature has traditionally focused on residential segregation, examining how individuals' residential locations are distributed differently acro

Elnara Kadyrgali, Adilet Yerkin, Yerdauit Torekhan, Pakizar Shamoi

Social activities often done in groups include watching television or movies. Choosing a film that appeals to the emotional inclinations of a varied group can be tricky. One of the most difficult aspects of making group movie suggestions is achieving agreement among members. At the same time, emotion is the most important component that connects the film and

Zixing Wang, Yongkang Huo, Fulvio Forni

We consider the design of a new class of passive iFIR controllers given by the parallel action of an integrator and a finite impulse response filter. iFIRs are more expressive than PID controllers but retain their features and simplicity. The paper provides a model-free data-driven design for passive iFIR controllers based on virtual reference feedback tunin

Patrick Hippold, Maren Scheel, Ludovic Renson, Malte Krack

Phase-locked loops are commonly used for shaker-based backbone tracking of nonlinear structures. The state of the art is to tune the control parameters by trial and error. In the present work, an approach is proposed to make backbone tracking much more robust and faster. A simple PI controller is proposed, and closed-form expressions for the gains are provid

Nick van Nielen, Fons Verbeek, Lu Cao

In biology, arborized structures are well represented and typically complex for visualization and analysis. In order to have a profound understanding of the topology of arborized 3D biological model, higher level abstraction is needed. We aim at constructing an abstraction of arborized 3D biological model to an L-system that provides a generalized formalizat

Junpeng Zhou, Xiying Yuan

An $r$-uniform hypergraph ($r$-graph for short) is linear if any two edges intersect at most one vertex. Let $\mathcal{F}$ be a given family of $r$-graphs. An $r$-graph $H$ is called $\mathcal{F}$-free if $H$ does not contain any member of $\mathcal{F}$ as a subgraph. The Tur\'{a}n number of $\mathcal{F}$ is the maximum number of edges in any $\mathcal{F}$-f

Balint Gyevnar, Stephanie Droop, Tadeg Quillien, Shay B. Cohen

It is often argued that effective human-centered explainable artificial intelligence (XAI) should resemble human reasoning. However, empirical investigations of how concepts from cognitive science can aid the design of XAI are lacking. Based on insights from cognitive science, we propose a framework of explanatory modes to analyze how people frame explanatio

Neelotpal Majumdar, Lutz Hofmann

Aggregated flexibilities or PQ-capabilities (active and reactive power capabilities) are termed in literature as Feasible Operating Regions (FORs). The FORs from underlying active distribution grids can effectively contribute to the operational management at the HV grid level. The HV buses are allocated aggregated FORs from the underlying MV grids, which are

Nicholas Carlini, Daniel Paleka, Krishnamurthy Dj Dvijotham, Thomas Steinke

We introduce the first model-stealing attack that extracts precise, nontrivial information from black-box production language models like OpenAI's ChatGPT or Google's PaLM-2. Specifically, our attack recovers the embedding projection layer (up to symmetries) of a transformer model, given typical API access. For under \$20 USD, our attack extracts the entire

Hector Zenil, Luan Carlos de Sena Monteiro

In many communication contexts, the capabilities of the involved actors cannot be known beforehand, whether it is a cell, a plant, an insect, or even a life form unknown to Earth. Regardless of the recipient, the message space and time scale could be too fast, too slow, too large, or too small and may never be decoded. Therefore, it pays to devise a way to e

Adrian Kailus, Dustin Kern, Christoph Krauß

Electric Vehicles (EVs) are more and more charged at public Charge Points (CPs) using Plug-and-Charge (PnC) protocols such as the ISO 15118 standard which eliminates user interaction for authentication and authorization. Currently, this requires a rather complex Public Key Infrastructure (PKI) and enables driver tracking via the included unique identifiers.

Georgios Tsoumplekas, Vladislav Li, Ilias Siniosoglou, Vasileios Argyriou

In the ever-evolving era of Artificial Intelligence (AI), model performance has constituted a key metric driving innovation, leading to an exponential growth in model size and complexity. However, sustainability and energy efficiency have been critical requirements during deployment in contemporary industrial settings, necessitating the use of data-efficient

M. Kumar, A. Nowzari, A. R. Persson, S. Jeppesen

We demonstrate experimentally non-equilibrium transport in unipolar quasi-1D hot electron devices reaching ballistic limit. The devices are realized with heterostructure engineering in nanowires to obtain dopant- and dislocation-free 1D-epitaxy and flexible bandgap engineering. We show experimentally the control of hot electron injection with a graded conduc

Felipe S. Abrahão, Santiago Hernández-Orozco, Narsis A. Kiani, Jesper Tegnér

We prove the full equivalence between Assembly Theory (AT) and Shannon Entropy via a method based upon the principles of statistical compression renamed `assembly index' that belongs to the LZ family of popular compression algorithms (ZIP, GZIP, JPEG). Such popular algorithms have been shown to empirically reproduce the results of AT, results that have also

M. H. Anikina, V. A. Nikitin, V. C. Rikhvitsky

In the theory of electroweak interactions, there is no prohibition on the existence of particles with a mass other than that of an electron, muon and tauon. The task is to search for a new particle in the mass range of 2-100 MeV. The search was performed using the photo material of the 2-m propane bubble chamber. The chamber has been exposed in a 10 GeV prot

M. S. Gabor, M. Belmeguenai, I. M. Miron

We investigate the origin of spin-orbit torques (SOTs) in archetypical Pt/Co/MgO thin films structures by performing harmonic Hall measurements. The behaviour of the damping like (DL) effective field ($h_{DL}$) with varying the Pt layer thickness and the Co layer thickness indicates that bulk spin-Hall effect (SHE) in Pt is mainly responsible for DL-SOT. The

Ikuya Kaneko

We establish the prime geodesic theorem for the Picard orbifold $\mathrm{PSL}_{2}(\mathbb{Z}[i]) \backslash \mathbb{H}^{3}$, wherein the error term shrinks proportionally to improvements in the subconvex exponent for quadratic Dirichlet $L$-functions over $\mathbb{Q}(i)$. Our result sheds light on a venerable conjecture by attaining an unconditional exponent

Alejandro Martín-Crespo, Alejandro Hernández-Serrano, Óscar Izquierdo-Monge, Paula Peña-Carro

In the recent years, the interest in electric direct current (DC) technologies (such as converters, batteries, electric vehicles, etc.) is increasing due to its potential on energy efficiency and sustainability. However, the vast majority of electric systems and networks are based on alternating current (AC), as they also have certain advantages regarding co

Yassine El Maazouz, Paul Alexander Helminck, Felix Röhrle, Pedro Souza

We study the topology of the moduli space of unramified $\mathbb{Z}/p$-covers of tropical curves of genus $g \geq 2$, where $p$ is a prime number. We use recent techniques by Chan--Galatius--Payne to identify contractible subcomplexes of the moduli space. We then use this contractibility result to show that this moduli space is simply connected. In the case

Stefan Schoder, Florian Kraxberger

Room acoustic simulations at low frequencies often face significant uncertainties of material parameters and boundary conditions due to absorbing material. We discuss the application of Physics-Informed Neural Networks (PINNs) to solve the (forward) Helmholtz equation in three dimensions (3D), employing mini-batch stochastic gradient descent with periodic re

Adele Veschetti, Richard Bubel, Reiner Hähnle

Smart contracts codify real-world transactions and automatically execute the terms of the contract when predefined conditions are met. This paper proposes SmartML, a modeling language for smart contracts that is platform independent and easy to comprehend. We detail its formal semantics and type system with a focus on its role in addressing security vulnerab

Bianca-Cerasela-Zelia Blaga, Sergiu Nedevschi

Humans use UAVs to monitor changes in forest environments since they are lightweight and provide a large variety of surveillance data. However, their information does not present enough details for understanding the scene which is needed to assess the degree of deforestation. Deep learning algorithms must be trained on large amounts of data to output accurat

Josh Shelton, Paul Milewski, Philippe H. Trinh

We develop a time-dependent conformal method to study the effect of viscosity on steep surface waves. When the effect of surface tension is included, numerical solutions are found that contain highly oscillatory parasitic capillary ripples. These small amplitude ripples are associated with the high curvature at the crest of the underlying viscous-gravity wav

Hien Thanh Doan, Minsoo Kim, Keunju Song, Hongseok Kim

In recent years, there has been a significant focus on advancing the next generation of power systems. Despite these efforts, persistent challenges revolve around addressing the operational impact of uncertainty on predicted data, especially concerning economic dispatch and optimal power flow. To tackle these challenges, we introduce a stochastic day-ahead s

Josep M. Miret, Jordi Pujolàs, Nicolas Thériault

We give a characterization of the codomain $[\ell]E(k)$ of the multiplication-by-$\ell$ map $[\ell]$ in the case of elliptic curves over a field $k$ of characteristic $\ne 2,3$ with $\ell$-torsion $E[\ell]=\langle W_1,W_2 \rangle$ fully defined over $k$, for primes $\ell$ different from the characteristic. We show that a point $Q\in E(k)$ lies in $[\ell]E(k)

Oscar Bouverot-Dupuis

An XXZ spin chain at zero magnetization is subject to spatially correlated baths acting as dissipation. We show that the low-energy excitations of this model are described by a dissipative sine-Gordon field theory, i.e. a sine-Gordon action with an additional long-range interaction emerging from dissipation. The field theory is then exactly mapped onto a gen

Kevin Murzyn, Maarten L. S. van der Geest, Leo Guery, Zhonghui Nie

Nonlinear optical microscopy provides elegant means for label-free imaging of biological samples and condensed matter systems. The widespread areas of application could even be increased if resolution was improved, which is currently limited by the famous Abbe diffraction limit. Super-resolution techniques can break the diffraction limit but rely on fluoresc

Tunc Alkanat, Erkut Akdag, Egor Bondarev, Peter H. N. De With

Temporal localization of driving actions plays a crucial role in advanced driver-assistance systems and naturalistic driving studies. However, this is a challenging task due to strict requirements for robustness, reliability and accurate localization. In this work, we focus on improving the overall performance by efficiently utilizing video action recognitio

Thomas A. Courtade

Three equivalent characterizations of probability measures through independence criteria are given. These characterizations lead to a family of Brascamp--Lieb-type inequalities for relative entropy, determine equilibrium states and sharp rates of convergence for certain linear Boltzmann-type dynamics, and unify an assortment of $L^2$ inequalities in probabil

I. Piantschitsch, J. Terradas, E. Soubrie, S. G. Heinemann

The geometry of a coronal hole (CH) affects the density profile of the reflected part of an incoming global coronal wave (CW). In this study, we perform for the first time magnetohydrodynamic (MHD) simulations of fast-mode MHD waves interacting with CHs of different geometries, such as circular, elliptic, convex, and concave shapes. We analyse the influence

M. Kupper, J. M. Zapata

In decision-making, maxitive functions are used for worst-case and best-case evaluations. Maxitivity gives rise to a rich structure that is well-studied in the context of the pointwise order. In this article, we investigate maxitivity with respect to general preorders and provide a representation theorem for such functions. The results are illustrated for di

Willem Diepeveen

Data sets tend to live in low-dimensional non-linear subspaces. Ideal data analysis tools for such data sets should therefore account for such non-linear geometry. The symmetric Riemannian geometry setting can be suitable for a variety of reasons. First, it comes with a rich mathematical structure to account for a wide range of non-linear geometries that has

Jiageng Wu, Xian Wu, Yefeng Zheng, Jie Yang

With appropriate data selection and training techniques, Large Language Models (LLMs) have demonstrated exceptional success in various medical examinations and multiple-choice questions. However, the application of LLMs in medical dialogue generation-a task more closely aligned with actual medical practice-has been less explored. This gap is attributed to th

Hong Sun, Ziqiang Li, Lei Liu, Bin Li

The proliferation of malicious deepfake applications has ignited substantial public apprehension, casting a shadow of doubt upon the integrity of digital media. Despite the development of proficient deepfake detection mechanisms, they persistently demonstrate pronounced vulnerability to an array of attacks. It is noteworthy that the pre-existing repertoire o

Jiageng WU, Xian Wu, Jie Yang

Clinical reasoning refers to the cognitive process that physicians employ in evaluating and managing patients. This process typically involves suggesting necessary examinations, diagnosing patients' diseases, and deciding on appropriate therapies, etc. Accurate clinical reasoning requires extensive medical knowledge and rich clinical experience, setting a hi

P. S. Ardra, R. Krithika, Saket Saurabh, Roohani Sharma

An edge-colored graph is said to be balanced if it has an equal number of edges of each color. Given a graph $G$ whose edges are colored using two colors and a positive integer $k$, the objective in the Edge Balanced Connected Subgraph problem is to determine if $G$ has a balanced connected subgraph containing at least $k$ edges. We first show that this prob

Elisabeth Kirsten, Annalina Buckmann, Abraham Mhaidli, Steffen Becker

Qualitative data analysis provides insight into the underlying perceptions and experiences within unstructured data. However, the time-consuming nature of the coding process, especially for larger datasets, calls for innovative approaches, such as the integration of Large Language Models (LLMs). This short paper presents initial findings from a study investi

Fengda Zhang, Qianpei He, Kun Kuang, Jiashuo Liu

Facial Attribute Classification (FAC) holds substantial promise in widespread applications. However, FAC models trained by traditional methodologies can be unfair by exhibiting accuracy inconsistencies across varied data subpopulations. This unfairness is largely attributed to bias in data, where some spurious attributes (e.g., Male) statistically correlate

Guilherme Ferraz de Arruda, Yamir Moreno

In this paper we formalize, using the Nyquist-Shannon theorem, a fundamental temporal resolution limit for numerical experiments in complex systems. A consequence of this limit is aliasing, the introduction of spurious frequencies due to sampling. By imposing these limits on the uncertainty principle in harmonic analysis, we show that by increasing the sampl

Qingyuan Zhou, Roland R. Netz, Benjamin A. Dalton

The mean first-passage time (MFPT) is one standard measure for the reaction time in thermally activated barrier-crossing processes. While the relationship between MFPTs and phenomenological rate coefficients is known for systems that satisfy Markovian dynamics, it is not clear how to interpret MFPTs for experimental and simulation time-series data generated

L. W. Guo, C. M. Wang

We explore the thermoelectric transport properties of a coexistence topological semimetal, characterized by the presence of both a pair of Weyl points and a nodal ring in the quantum limit. This system gives rise to complex Landau bands when subjected to a magnetic field aligned with the direction connecting two Weyl points. In the longitudinal configuration

Emanuel Milman

We study isoperimetric inequalities on "slabs", namely weighted Riemannian manifolds obtained as the product of the uniform measure on a finite length interval with a codimension-one base. As our two main applications, we consider the case when the base is the flat torus $\mathbb{R}^2 / 2 \mathbb{Z}^2$ and the standard Gaussian measure in $\mathbb{R}^{n-1}$.

Alexander H. Berger, Laurin Lux, Suprosanna Shit, Ivan Ezhov

Direct image-to-graph transformation is a challenging task that involves solving object detection and relationship prediction in a single model. Due to this task's complexity, large training datasets are rare in many domains, making the training of deep-learning methods challenging. This data sparsity necessitates transfer learning strategies akin to the sta

Fudong Ge, Yiwei Zhang, Shuhan Shen, Yue Wang

In this paper, we propose a new image-based visual place recognition (VPR) framework by exploiting the structural cues in bird's-eye view (BEV) from a single monocular camera. The motivation arises from two key observations about place recognition methods based on both appearance and structure: 1) For the methods relying on LiDAR sensors, the integration of

E. Filandri, M. Viviani

We study dark matter, assumed to be composed by weak interacting massive particles (WIMPs), scattering off ${}^2$H and ${}^4$He nuclei. In order to parameterize the WIMP-nucleon interaction the chiral effective field theory approach is used. Considering only interactions invariant under parity, charge conjugation and time reversal, we examine five interactio

I. Calvo-Almazán, V. Chamard, T. Grünewald, M. Allain

This work proposes an innovative approach to improve Bragg coherent diffraction imaging (BCDI) microscopy applied to time evolving crystals and/or non-homogeneous crystalline strain fields, identified as two major limitations of BCDI microscopy. Speckle BCDI (spBCDI), introduced here, rests on the ability of a strongly non-uniform illumination to induce a co

Xiaohan Jia, Xuwen Zhang

In this paper, we prove the quantitative version of the Alexandrov theorem for capillary hypersurfaces in the half-space, which generalizes Julin-Niinikoski's result to the capillary case. The proof is based on the quantitative analysis of the Montiel-Ros-type argument carried out in our joint works with Wang-Xia.

Xinghui Liu, Kaili Chang, Jiarong Guo, Mengfei Xue

Plasmonic devices, with their ultra-high integration density and data-carrying capacity comparable to optical devices, are currently a hot topic in the field of nanophotonic devices. Photodetectors, non-volatile memories, and ultra-compact lasers based on plasmons in low-dimensional materials are emerging at a rapid pace. However, the narrow optical response

Paul Francis, David Wagner

The purpose of anonymizing structured data is to protect the privacy of individuals in the data while retaining the statistical properties of the data. There is a large body of work that examines anonymization vulnerabilities. Focusing on strong anonymization mechanisms, this paper examines a number of prominent attack papers and finds several problems, all

Souptik Chakraborty

Given $N\geq 3,$ we consider the critical Hardy-Sobolev equation $-\Delta u-\frac{\gamma}{|x|^2}u=\frac{|u|^{2^*(s)-2}u}{|x|^s}$ in $\mathbb{R}^N\setminus \{0\},$ where $0<\gamma<\gamma_{H}:=\left(\frac{N-2}{2}\right)^2,\,s\in (0,2)$ and $2^*(s)=\frac{2(N-s)}{(N-2)}.$ We prove a stability estimate for the corresponding Hardy-Sobolev inequality in the spirit