October 2024 arXiv papers — page 25

Dehao Xu, Simen T. Bootsma, Roberto Verzicco, Detlef Lohse

The presence of salt in seawater significantly affects the melt rate and morphological evolution of ice. This study investigates the melting process of a vertical cylinder in saline water using a combination of laboratory experiments and direct numerical simulations. The two-dimensional (2D) direct numerical simulations and 3D experiments achieve thermal Ray

Haowen Yao, Riddhiman Laha, Anirban Sinha, Jonas Hall

This paper is about generating motion plans for high degree-of-freedom systems that account for collisions along the entire body. A particular class of mathematical programs with complementarity constraints become useful in this regard. Optimization-based planners can tackle confined-space trajectory planning while being cognizant of robot constraints. Howev

Jorge Quesada, Zoe Fowler, Mohammad Alotaibi, Mohit Prabhushankar

The remarkable capabilities of the Segment Anything Model (SAM) for tackling image segmentation tasks in an intuitive and interactive manner has sparked interest in the design of effective visual prompts. Such interest has led to the creation of automated point prompt selection strategies, typically motivated from a feature extraction perspective. However, t

Hongsheng Dai, Xiequan Fan, Jianya Lu

In this paper, we study the self-normalized Cram\'er-type moderate deviation of the empirical measure of the stochastic gradient Langevin dynamics (SGLD). Consequently, we also derive the Berry-Esseen bound for SGLD. Our approach is by constructing a stochastic differential equation (SDE) to approximate the SGLD and then applying Stein's method as developed

Yaran Fan, Jamie Pool, Senja Filipi, Ross Cutler

Workplace meetings are vital to organizational collaboration, yet a large percentage of meetings are rated as ineffective. To help improve meeting effectiveness by understanding if the conversation is on topic, we create a comprehensive Topic-Conversation Relevance (TCR) dataset that covers a variety of domains and meeting styles. The TCR dataset includes 1,

Arezoo Borji, Gernot Kronreif, Bernhard Angermayr, Sepideh Hatamikia

Recent advances in machine learning are transforming medical image analysis, particularly in cancer detection and classification. Techniques such as deep learning, especially convolutional neural networks (CNNs) and vision transformers (ViTs), are now enabling the precise analysis of complex histopathological images, automating detection, and enhancing class

Spyridon Kantarelis, Konstantinos Thomas, Vassilis Lyberatos, Edmund Dervakos

Chord progressions encapsulate important information about music, pertaining to its structure and conveyed emotions. They serve as the backbone of musical composition, and in many cases, they are the sole information required for a musician to play along and follow the music. Despite their importance, chord progressions as a data domain remain underexplored.

Tseganesh Getachew Gebrehana, Hunduma Legesse Geleta

We investigate an extended version of Hilbert space of analytic functions called Hilbert space of complex-valued harmonic functions. It is found that functions in Hilbert space of complex-valued harmonic functions exhibit many properties analogous to its analytic counter part such as complex-valued harmonic function analogous of norm, equivalent norms, repro

Andreas Katsanikakis, Nikolaos Bekiaris-Liberis, Delphine Bresch-Pietri

We develop an input delay-compensating feedback law for linear switched systems with time-dependent switching. Because the future values of the switching signal, which are needed for constructing an exact predictor-feedback law, may be unavailable at current time, the key design challenge is how to construct a proper predictor state. We resolve this challeng

Teerath Kumar, Alessandra Mileo, Malika Bendechache

Data augmentation has become a pivotal tool in enhancing the performance of computer vision tasks, with the KeepOriginalAugment method emerging as a standout technique for its intelligent incorporation of salient regions within less prominent areas, enabling augmentation in both regions. Despite its success in image classification, its potential in addressin

Matteo Castagnola, Marcus T. Lexander, Henrik Koch

Experiments show that light-matter strong coupling affects chemical properties, though the underlying mechanism remains unclear. We present an ab initio quantum electrodynamics coupled cluster method for the collective strong coupling regime. The model accurately describes electronic and electron-photon correlation within a molecular subsystem, while a simpl

Lixiu Wu, Yuanrong Tang, Qisen Pan, Xianyang Zhan

Due to privacy concerns, open dialogue datasets for mental health are primarily generated through human or AI synthesis methods. However, the inherent implicit nature of psychological processes, particularly those of clients, poses challenges to the authenticity and diversity of synthetic data. In this paper, we propose ECAs (short for Embodied Conversationa

Mart Lubbers, Peter Achten

This note is meant to give people who are familiar with the functional programming language Haskell a concise overview of Clean language elements and how they differ from Haskell.

Swastik Kopparty, Harry Sha

We study the problem of partitioning the unit cube $[0,1]^n$ into $c$ parts so that each $d$-dimensional axis-parallel projection has small volume. This natural combinatorial/geometric question was first studied by Kopparty and Nagargoje [KN23] as a reformulation of the problem of determining the achievable parameters for seedless multimergers -- which extra

Sergey Kurapov, Maxim Davidovsky

The monography presents a new algorithm for finding the clique of maximal length in a nonseparable graph. The algorithm is based on the properties of the representation of a clique as a subset of the set of cycles with a length of three, the ring sum of which is an empty set. As a result of selecting the cycles of the length of three, two vectors are formed:

Ricardo Fraiman, Leonardo Moreno, Thomas Ransford

We show how a Cram\'er-Wold theorem for a family of multivariate probability distributions can be used to generate a similar theorem for mixtures (convex combinations) of distributions drawn from the same family. Using this abstract result, we establish a Cram\'er-Wold theorem for mixtures of multivariate Gaussian distributions. According to this theorem, tw

Linda Fernsel, Yannick Kalff, Katharina Simbeck

Audits contribute to the trustworthiness of Learning Analytics (LA) systems that integrate Artificial Intelligence (AI) and may be legally required in the future. We argue that the efficacy of an audit depends on the auditability of the audited system. Therefore, systems need to be designed with auditability in mind. We present a framework for assessing the

Chenbo Shi, Xin Gu, Shichen Liang, Jin Pan

This paper presents a novel and efficient method for characteristic mode decomposition in multi-structure systems. By leveraging the translation and rotation matrices of vector spherical wavefunctions, our approach enables the synthesis of a composite system's characteristic modes using independently computed simulations of its constituent structures. The co

Amir. M Mousavi Harris, Jamal Esmaily, Sajjad Zabbah, Reza Ebrahimpour

Everyday decisions often involve many different levels. What connects these higher and lower level decisions hierarchy to one another determines how the cause(s) of failures are interpreted. It is hypothesized that decision confidence guides the assignment of blame to the correct level of hierarchy but this hypothesis has only been tested by manipulation of

Barbara Gatti, Gioia Schulte

In the study of algebraic curves with many points over a finite field, a well known general problem is to understanding better the properties of $\mathbb{F}_{q^2}$-maximal curves whose genera fall in the higher part of the spectrum of the genera of all $\mathbb{F}_{q^2}$-maximal curves. This problem is still open for genera smaller than $ \lfloor \frac{1}{6}

Sun-Young Jeon, Sen Wang, Adam S. Wang, Garry E. Gold

Fluoroscopy is critical for real-time X-ray visualization in medical imaging. However, low-dose images are compromised by noise, potentially affecting diagnostic accuracy. Noise reduction is crucial for maintaining image quality, especially given such challenges as motion artifacts and the limited availability of clean data in medical imaging. To address the

Shourya Khanna, Jie Yu, Ronald Drimmel, Eloisa Poggio

We present an exploration of the Milky Way's structural parameters using an all-sky sample of RC giants to map the stellar density from the Galactic disc beyond 3 kpc. These evolved giants are considered to be standard candles due to their low intrinsic variance in their absolute luminosities, allowing us to estimate their distances with reasonable confidenc

Md Abu Ahammed Babu, Sushant Kumar Pandey, Darko Durisic, Ashok Chaitanya Koppisetty

Data leakage is a very common problem that is often overlooked during splitting data into train and test sets before training any ML/DL model. The model performance gets artificially inflated with the presence of data leakage during the evaluation phase which often leads the model to erroneous prediction on real-time deployment. However, detecting the presen

Chenbo Shi, Jin Pan, Xin Gu, Shichen Liang

This paper presents a computation method of generalized scattering matrix (GSM) based on integral equations and the method of moments (MoM), specifically designed for antennas excited through waveguide ports. By leveraging two distinct formulations -- magnetic-type and electric-type integral equations -- we establish concise algebraic relations linking the G

Andrew Marks, Dino Rossegger, Theodore Slaman

We show that if $E$ is a countable Borel equivalence relation on $\mathbb{R}^n$, then there is a closed subset $A \subset [0,1]^n$ of Hausdorff dimension $n$ so that $E \restriction A$ is smooth. More generally, if $\leq_Q$ is a locally countable Borel quasi-order on $2^{\omega}$ and $g$ is any gauge function of lower order than the identity, then there is a

Tomoya Nishida, Harsh Purohit, Kota Dohi, Takashi Endo

This paper proposes a framework of explaining anomalous machine sounds in the context of anomalous sound detection~(ASD). While ASD has been extensively explored, identifying how anomalous sounds differ from normal sounds is also beneficial for machine condition monitoring. However, existing sound difference captioning methods require anomalous sounds for tr

Quan Quan, Shuhan Huang, Kai-Yuan Cai

With the rapid development of robotics swarm technology, there are more tasks that require the swarm to pass through complicated environments safely and efficiently. Virtual tube technology is a novel way to achieve this goal. Virtual tubes are free spaces connecting two places that provide safety boundaries and direction of motion for swarm robotics. How to

Chenghao Xu, Malcolm Mielle, Antoine Laborde, Ali Waseem

Achieving the EU's climate neutrality goal requires retrofitting existing buildings to reduce energy use and emissions. A critical step in this process is the precise assessment of geometric building envelope characteristics to inform retrofitting decisions. Previous methods for estimating building characteristics, such as window-to-wall ratio, building foot

Tamir Bar-Tov, Rami Puzis, David Toubiana

Metabolite biosynthesis is regulated via metabolic pathways, which can be activated and deactivated within organisms. Understanding and identifying an organism's metabolic pathway network is a crucial aspect for various research fields, including crop and life stock breeding, pharmacology, and medicine. The problem of identifying whether a pathway is part of

Yue Chen, Jian Li

To incorporate the gravitational influence of Kuiper belt objects (KBOs) in planetary ephemerides, uniform-ring models are commonly employed. In this paper, for representing the KBO population residing in Neptune's 2:3 mean motion resonance (MMR), known as the Plutinos, we introduce a three-arc model by considering their resonant characteristics. Each `arc'

Ayush Singh, Mansi Gupta, Shivank Garg

Vision Language Models excel in handling a wide range of complex tasks, including Optical Character Recognition (OCR), Visual Question Answering (VQA), and advanced geometric reasoning. However, these models fail to perform well on low-level basic visual tasks which are especially easy for humans. Our goal in this work was to determine if these models are tr

X. Tong, A. Li, L. Lei, X. Hu

In this paper, we investigate symbol-level precoding (SLP) and efficient decoding techniques for downlink transmission, where we focus on scenarios where the base station (BS) transmits multiple QAM constellation streams to users equipped with multiple receive antennas. We begin by formulating a joint symbol-level transmit precoding and receive combining opt

Maria Anna Sisak

This submission is a PhD dissertation. Kapustin and Witten conjectured that there is a mirror symmetry relation between the hyperk\"ahler structures on certain Higgs bundle moduli spaces. As a consequence, they conjecture an equivalence between categories of BBB and BAA-branes. At the classical level, this mirror symmetry is given by T-duality between semi-f

Kun Song, Ruben Solozabal, Li hao, Lu Ren

Hyperbolic representation learning is well known for its ability to capture hierarchical information. However, the distance between samples from different levels of hierarchical classes can be required large. We reveal that the hyperbolic discriminant objective forces the backbone to capture this hierarchical information, which may inevitably increase the Li

David Acton, Owen Doyle, Michael P. Tuite

We consider real linear transformations between two inertial frames with constant relative speed $v$ in a $d$-dimensional spacetime where light moves with constant speed $c=1$ (for some chosen units) in all frames. For $d=2$ we show that the standard relative velocity formula holds and that any associated anisotropic conformal factor is multiplicative under

Olaf Parczyk, Christoph Spiegel

Graham, R\"odl, and Ruci\'nski originally posed the problem of determining the minimum number of monochromatic Schur triples that must appear in any 2-coloring of the first $n$ integers. This question was subsequently resolved independently by Datskovsky, Schoen, and Robertson and Zeilberger. Here we suggest studying a natural anti-Ramsey variant of this que

Shaokai Li, Yixuan Ji, Peng Song, Haoqin Sun

In this paper, we propose a novel deep inductive transfer learning framework, named feature distribution adaptation network, to tackle the challenging multi-modal speech emotion recognition problem. Our method aims to use deep transfer learning strategies to align visual and audio feature distributions to obtain consistent representation of emotion, thereby

Sina Jamalzadegan, Mohammadreza Zare, Micah J. Dickens, Florian Schenk

Liquid metals (LM) are emerging plasmonic nanomaterials with transformable surface plasmon resonances (SPR) due to their liquid-like deformability. This study delves into the plasmonic properties of LM nanoparticles, with a focus on EGaIn (eutectic gallium-indium)-based materials. Leveraging Finite-Difference Time-Domain (FDTD) simulations and experimental v

Licheng Zhang, Shengxiang Lv, Yuanqiu Huang

The existence of Hamiltonian cycles in 1-planar graphs with higher connectivity has attracted considerable attention. Recently, the authors and Dong proved that 4-connected 1-planar chordal graphs are Hamiltonian-connected. In this paper, we investigate the non-Hamiltonicity of a broader class of graphs, specifically perfect graphs, under the constraint of 1

Danae Pla Karidi, Evaggelia Pitoura

Path-based explanations provide intrinsic insights into graph-based recommendation models. However, most previous work has focused on explaining an individual recommendation of an item to a user. In this paper, we propose summary explanations, i.e., explanations that highlight why a user or a group of users receive a set of item recommendations and why an it

Andrei Khrennikov, Masanao Ozawa, Felix Benninger, Oded Shor

The past few years have seen a surge in the application of quantum theory methodologies and quantum-like modeling in fields such as cognition, psychology, and decision-making. Despite the success of this approach in explaining various psychological phenomena such as order, conjunction, disjunction, and response replicability effects there remains a potential

Chunchao Fan, Xinyu Hu, Qizhong Lin, Xin Lu

We focus on two hypergraph Ramsey problems. First, we consider the Erd\H{o}s-Hajnal function $r_k(k+1,t;n)$. In 1972, Erd\H{o}s and Hajnal conjectured that the tower growth rate of $r_k(k+1,t;n)$ is $t-1$ for each $2\le t\le k$. To finish this conjecture, it remains to show that the tower growth rate of $r_4(5,4;n)$ is three. We prove a superexponential lowe

P. Maneesha, Koyal Suman Samantaray, Rakhi Saha, Rajashri Urkude

Materials with magnetoelectric coupling (MEC) between ferroic orders at room temperature are emerging field in modern technology and physics. BaTiO3 is a robust ferroelectric in which several doping has led to MEC. In Ca and Mn modified BaTiO3 has been study with a series of Ba(1-x)Ca(x)Ti(1-y)Mn(y)O3 (x=y= 0, 0.03, 0.06, 0.09), in this MEC was only observed

Sung-Hoon Lee, Ki-Ha Hong

Ionic conduction in crystalline solids is conventionally understood to proceed via atomic-scale defects such as vacancies or interstitials. Here, by addressing the long-standing structural ambiguity of high-temperature tetragonal tantalum pentoxide (H-Ta$_2$O$_5$), we identify a qualitatively different transport mechanism. Based on first-principles calculati

Zujin Wen, Jin-Long Huang, Oscar Dahlsten

We design a quantum version of neural networks with sinusoidal activation functions and compare its performance to the classical case. We create a general quantum sine circuit implementing a discretised sinusoidal activation function. Along the way, we define a classical discrete sinusoidal neural network. We build a quantum optimization algorithm around the

Jan Mateu Armengol, Cristina Carnerero, Clément Rames, Álvaro Criado

Air pollution is a pressing environmental risk to public health, particularly in cities where population density and pollution levels are high. Traditional methods for exposure analysis often rely on census data, but recent studies highlight the impact of daily mobility on individuals' exposure. Here, we develop a methodology to determine unprecedented pedes

Fuminori Tatsuoka, Tomohiro Sogabe, Tomoya Kemmochi, Shao-Liang Zhang

This note considers the computation of the logarithm of symmetric positive definite matrices using the Gauss--Legendre (GL) quadrature. The GL quadrature becomes slow when the condition number of the given matrix is large. In this note, we propose a technique dividing the matrix logarithm into two matrix logarithms, where the condition numbers of the divided

Chengkai Huang, Shoujin Wang, Xianzhi Wang, Lina Yao

Sequential recommendation aims to predict the next item which interests users via modeling their interest in items over time. Most of the existing works on sequential recommendation model users' dynamic interest in specific items while overlooking users' static interest revealed by some static attribute information of items, e.g., category, or brand. Moreove

Xudong Wang, Hongyang Du, Dusit Niyato, Lijie Zhou

In wireless networks, applying deep learning models to solve matching problems between different entities has become a mainstream and effective approach. However, the complex network topology in 6G multiple access presents significant challenges for the real-time performance and stability of matching generation. Generative artificial intelligence (GenAI) has

Georgios Mylonas, Athanasios Kalogeras, Sobah Abbas Petersen, Luis Muñoz

Smart cities have been a very active research area in the past 20 years, while continuously adapting to new technological advancements and keeping up with the times regarding sustainability and climate change. In this context, there have been numerous proposals to expand the scope of smart cities, focusing on resilience and sustainability, among other aspect

Sergio A. Ortega, Miguel A. Martin-Delgado

This work introduces a graph-phased Szegedy's quantum walk, which incorporates link phases and local arbitrary phase rotations (APR), unlocking new possibilities for quantum algorithm efficiency. We demonstrate how to adapt quantum circuits to these advancements, allowing phase patterns that ensure computational practicality. The graph-phased model broadens

Manh Hong Duong, The Anh Han

Uncertainty, characterised by randomness and stochasticity, is ubiquitous in applications of evolutionary game theory across various fields, including biology, economics and social sciences. The uncertainty may arise from various sources such as fluctuating environments, behavioural errors or incomplete information. Incorporating uncertainty into evolutionar

Martin Holler, Erion Morina

This paper addresses the problem of uniqueness in learning physical laws for systems of partial differential equations (PDEs). Contrary to most existing approaches, it considers a framework of structured model learning, where existing, approximately correct physical models are augmented with components that are learned from data. The main results of the pape

Ihab A. Satam, Róbert Szabolcsi

Brain computer interface (BCI) applications in robotics are becoming more famous and famous. People with disabilities are facing a real-time problem of doing simple activities such as grasping, handshaking etc. in order to aid with this problem, the use of brain signals to control actuators is showing a great importance. The Emotive Insight, a Brain-Computer

Chris Lam

Alternative data provides valuable insights for lenders to evaluate a borrower's creditworthiness, which could help expand credit access to underserved groups and lower costs for borrowers. But some forms of alternative data have historically been excluded from credit underwriting because it could act as an illegal proxy for a protected class like race or ge

Sajjad Maleki, Shijie Pan, Subhash Lakshminarayana, Charalambos Konstantinou

The growing penetration of IoT devices in power grids despite its benefits, raises cybersecurity concerns. In particular, load-altering attacks (LAAs) targeting high-wattage IoT-controllable load devices pose serious risks to grid stability and disrupt electricity markets. This paper provides a comprehensive review of LAAs, highlighting the threat model, ana

Oualid Bouabdillah

For a subset $E = \{\xi_1, ..., \xi_N\}$ of the unit circle $\mathbb{T}$, the notion of Ritt$_E$ operators on a Banach space and their functional calculus on generalized Stolz domains was developed and studied in arXiv:2203.05373. In this paper, we define a quadratic functional calculus for a Ritt$_E$ operator on $E_r$, by a decomposition of type Franks-McIn

Ozhan Genc, Marcos Jardim

We study rank 2 $h$-instanton sheaves on projective threefolds. We demonstrate that any orientable rank 2, non-locally free $h$-instanton sheaf with defect 0 on a threefold can be obtained as an elementary transformation of a locally free $h$-instanton sheaf. Our focus then shifts to ruled Fano threefolds of Picard rank 2 and index 1, of which there are five

Manish Patel, Amir Shee, Debasish Chaudhuri

We explore the dynamics of active elements performing persistent random motion with fluctuating active speed and in the presence of translational noise in a $d$-dimensional harmonic trap, modeling active speed generation through an Ornstein-Uhlenbeck process. Our approach employs an exact analytic method based on the Fokker-Planck equation to compute time-de

Marcin Płodzień, Sambunath Das, Maciej Lewenstein, Christina Psaroudaki

Extracting information from quantum many-body systems remains a key challenge in quantum technologies due to experimental limitations. In this work, we employ a single spin qubit to probe a strongly interacting system, creating an environment conducive to qubit decoherence. By focusing on the XXZ spin chain, we observe diverse dynamics in the qubit evolution

Markus Lepper, Baltasar Trancón y Widemann

The semantics of notation systems can naturally be meta-modelled as a network of transformations, starting with the syntactic elements of the notation and ending with the parameters of an execution. In this context, a digital encoding format for music notation can be seen as selecting a subset of the data nodes of this network for storage, leaving others to

Kremena Valkanova

We examine the effect of item arrangement on choices using a novel decision-making model based on the Markovian exploration of choice sets. This model is inspired by experimental evidence suggesting that the decision-making process involves sequential search through rapid stochastic pairwise comparisons. Our findings show that decision-makers following a rev

Kento Kawaharazuka, Shogo Makino, Kei Tsuzuki, Moritaka Onitsuka

To develop Musashi as a musculoskeletal humanoid platform to investigate learning control systems, we aimed for a body with flexible musculoskeletal structure, redundant sensors, and easily reconfigurable structure. For this purpose, we develop joint modules that can directly measure joint angles, muscle modules that can realize various muscle routes, and no

Frank Barrows, Ezio Iacocca, Francesco Caravelli

Random assemblies of magnetic nanowires represent a unique class of materials with promising applications in spintronics and information storage. These assemblies exhibit complex behavior due to the combination of magnetic dipolar interactions between the nanowires and electronic transport properties governed by tunneling barriers at magnetic tunnel junction

Ann-Kathrin Raab, Melvin Redon, Sylvianne Roscam Abbing, Yuman Fang

We perform an experimental two-color high-order harmonic generation study in argon with the fundamental of an ytterbium ultrashort pulse laser and its second harmonic. The intensity of the second harmonic and its phase relative to the fundamental are varied, in a large range compared to earlier works, while keeping the total intensity constant. We extract th

Tianshu Gao, Mengbin Ye, Robert Ackland

This paper uses a multi-layer network model to study deliberation in online discussion platforms, focusing on the Reddit platform. The model comprises two layers: a discussion layer, which represents the comment-to-comment replies as a hierarchical tree, and an actor layer, which represent the actor-to-actor reply interactions. The interlayer links represent

S. Benlenqwanssa, S. S. Krishtopenko, M. Meyer, B. Benhamou-Bui

We present a multi-probe transport analysis that effectively separates bulk and edge currents in large Hall bar devices with standard geometries. Applied to transport measurements on all possible four-probe configurations of six-probe Hall bar devices made of inverted three-layer InAs/GaInSb quantum wells (QWs), our analysis not only reveals the presence of

Yu-Qing Liu, Chen Zhao, Xiao-Yong Yan, Xiaoyue Hou

Rapid urbanization and growing vehicle ownership exacerbate traffic congestion and prolong commute times. We examine the self-organizing dynamics of residential choice via a hypothetical home-swapping process to mitigate peak-hour traffic congestion and carbon emissions. Specifically, we analyze over 400,000 trajectories from 9 days in a major Chinese city,

Olivier Graf, Gustav Holzegel

In this last part of the series we prove that the slow (inverse logarithmic) decay in time of solutions to the linearised Einstein equations on Schwarzschild-Anti-de Sitter backgrounds obtained in~\cite{Gra.Hol24,Gra.Hol24a} is in fact optimal by constructing quasimode solutions for the Teukolsky system. The main difficulties compared with the case of the sc

Huan-Chih Wang, Ja-Ling Wu

Face verification is a well-known image analysis application and is widely used to recognize individuals in contemporary society. However, most real-world recognition systems ignore the importance of protecting the identity-sensitive facial images that are used for verification. To address this problem, we investigate how to implement a secure face verificat

Chaitanya Kumar Konda, Vidyashankar. S, Ulavish. V. S, Sachin. A. M

Symmetric NACA airfoils tend to undergo abrupt stall characteristics at higher angle of attacks. The abrupt stall has deteriorating effect on lift as well as the efficiency of the airfoils. Abruptness in stall restricts the airfoil to operate only at lower angle of attacks. So, in order to improve the efficiency of airfoils at higher angle of attacks and mak

Wen-Dong Jiang, Chih-Yung Chang, Ssu-Chi Kuai, Diptendu Sinha Roy

The growing demand for intelligent security in consumer electronics, such as smart home cameras and personal monitoring systems, is often hindered by the high computational cost and large model sizes of advanced AI. These limitations prevent the effective deployment of real-time Video Anomaly Detection (VAD) on resource-constrained edge devices. To bridge th

Delano Oliveira, Reydne Santos, Benedito de Oliveira, Martin Monperrus

Motivation: Code understandability is crucial in software development, as developers spend 58% to 70% of their time reading source code. Improving it can improve productivity and reduce maintenance costs. Problem: Experimental studies often identify factors influencing code understandability in controlled settings but overlook real-world influences like proj

Weishi Chen, Pavel Mozgunov

The study of combinations of drugs/drug-schedules gained increasing attention in various therapeutic areas recently. In oncology, the aim of phase I combination clinical trial is to find the maximum tolerated combination (MTC). Many innovative designs were proposed, among which the Partial Ordering Continual Reassessment Method (POCRM) is increasingly applie

Martin Gjorgjevski, Nicolas Keriven, Simon Barthelmé, Yohann De Castro

Node regression consists in predicting the value of a graph label at a node, given observations at the other nodes. To gain some insight into the performance of various estimators for this task, we perform a theoretical study in a context where the graph is random. Specifically, we assume that the graph is generated by a Latent Position Model, where each nod

Peng-Cheng Hang, Liangjian Hu, Min-Jie Luo

In our recent work [SIGMA \textbf{20} (2024), 074, 13 pages], the leading behaviour of the Humbert function $\Psi_1[a,b;c,c';x,y]$ when $x\to\infty$ and $y\to +\infty$ has been derived in a direct and simple manner. In this paper, we obtain the complete asymptotics of $\Psi_1$ in the general case $x,y\to\infty$ along a new path. Indeed, our proof is based on

Xuewei Feng, Yuxiang Yang, Qi Li, Xingxiang Zhan

In this paper, we conduct an empirical study on remote DoS attacks targeting NAT networks. We show that Internet attackers operating outside local NAT networks can remotely identify a NAT device and subsequently terminate TCP connections initiated from the identified NAT device to external servers. Our attack involves two steps. First, we identify NAT device

Chuqiao Zhang, Crina Grosan, Dalia Chakrabarty

Patients who are undergoing physical rehabilitation, benefit from feedback that follows from reliable assessment of their cumulative performance attained at a given time. In this paper, we provide a method for the learning of the recovery trajectory of an individual patient, as they undertake exercises as part of their physical therapy towards recovery of th

Yuxuan Lin, Yang Chang, Xuan Tong, Jiawen Yu

In the advancement of industrial informatization, unsupervised anomaly detection technology effectively overcomes the scarcity of abnormal samples and significantly enhances the automation and reliability of smart manufacturing. As an important branch, industrial image anomaly detection focuses on automatically identifying visual anomalies in industrial scen

Dario Trevisan, Feng-Yu Wang, Jie-Xiang Zhu

We identify the leading term in the asymptotics of the quadratic Wasserstein distance between the invariant measure and empirical measures for diffusion processes on closed weighted four-dimensional Riemannian manifolds. Unlike results in lower dimensions, our analysis shows that this term depends solely on the Riemannian volume of the manifold, remaining un

Pranjal R. S., Elisabeth Krause, Klaus Dolag, Karim Benabed

Robust modeling of non-linear scales is critical for accurate cosmological inference in Stage IV surveys. For weak lensing analyses in particular, a key challenge arises from the incomplete understanding of how non-gravitational processes, such as supernovae and active galactic nuclei - collectively known as baryonic feedback - affect the matter distribution

Pasquale Caporaso, Giuseppe Bianchi, Francesco Quaglia

The demand for data protection measures against unauthorized changes or deletions is steadily increasing. These measures are essential for maintaining the integrity and accessibility of data, effectively guarding against threats like ransomware attacks that focus on encrypting large volumes of stored data, as well as insider threats that involve tampering wi

Sahil Jhawar, Thibeau Wouters, Peter T. H. Pang, Mattia Bulla

Kilonovae, possible electromagnetic counterparts to neutron star mergers, provide important information about high-energy transient phenomena and, in principle, also allow us to obtain information about the source properties responsible for powering the kilonova. Unfortunately, numerous uncertainties exist in kilonova modeling that, at the current stage, hin

Angus Crookes, Ben Yuen, Stephen M. Hanham, Angela Demetriadou

Multi-partite entanglement is fundamental to emerging quantum technologies such as quantum networks, which ultimately require devices with strong light-matter interactions and long coherence times. Here, we introduce nanobeam photonic crystal cavities combining both extreme quality factors ($\sim10^{7}$) with sub-wavelength field confinement to reach unprece

Herman Lassche, Michiel Overeem, Ayushi Rastogi

Companies support their customers using live chats and chatbots to gain their loyalty. AFAS is a Dutch company aiming to leverage the opportunity large language models (LLMs) offer to answer customer queries with minimal to no input from its customer support team. Adding to its complexity, it is unclear what makes a response correct, and that too in Dutch. F

David Dzsotjan, Atakan Coban, Christoph Hoyer, Stefan Küchemann

With the advent and development of real-world quantum technology applications, a practically-focused quantum education including student quantum experiments are gaining increasing importance in physics curricula. In this paper, using the DeFT framework, we present an analysis of the representations in our AR-enhanced quantum cryptography student experiment,

Matteo Cerruti

Blazars are the most common sources of $\gamma$-ray photons in the extragalactic sky. Their $\gamma$-ray light curves are characterized by bright flaring episodes, similarly to what is observed at longer wavelengths. These gamma-ray bursts from blazars (GRBBLs) have been extensively studied individually, but never in terms of a population. The goal of this w

Mohammad Parsa Rezaei, Grzegorz Kudra, Mojtaba Ghodsi, Jan Awrejcewicz

This paper addresses the challenges of the Euler-Bernoulli beam theory regarding shortening and stretching assumptions. Certain boundary conditions, such as a cantilever with a horizontal spring attached to its end, result in beams that partly shorten or stretch, depending on the spring stiffness. The traditional Euler-Bernoulli beam model may not accurately

Simon Wattana Campbell

In this PhD thesis we investigate stellar evolution and nucleosynthesis in the low- and extremely-low metallicity regime - including models of stars with a pure Big Bang composition (i.e. $\rm{Z} = 0$). The metallicity range of the extremely metal-poor (EMP) models calculated is $-6.5 < \rm{[Fe/H]} < -3.0$, with a mass range $0.85 < \rm{M} < 3.0~\rm{M}_{\odo

I. Dankovsky, S. Ramazanov, E. Babichev, D. Gorbunov

We study domain walls (DWs) arising in field theories where $Z_2$-symmetry is spontaneously broken by a scalar expectation value decreasing proportionally to the Universe temperature. The energy density of such melting DWs redshifts sufficiently fast not to overclose the Universe. For the first time, evolution of melting DWs and the resulting gravitational w

Suhang Wu, Jialong Tang, Baosong Yang, Ante Wang

RALMs (Retrieval-Augmented Language Models) broaden their knowledge scope by incorporating external textual resources. However, the multilingual nature of global knowledge necessitates RALMs to handle diverse languages, a topic that has received limited research focus. In this work, we propose \textit{Futurepedia}, a carefully crafted benchmark containing pa

Yang Zhou, Tan Li Hui Faith, Yanyu Xu, Sicong Leng

Medical Vision-Language Pretraining (MedVLP) shows promise in learning generalizable and transferable visual representations from paired and unpaired medical images and reports. MedVLP can provide useful features to downstream tasks and facilitate adapting task-specific models to new setups using fewer examples. However, existing MedVLP methods often differ

Guan-Yan Yang, Yi-Heng Ko, Farn Wang, Kuo-Hui Yeh

Our work explores the utilization of deep learning, specifically leveraging the CodeBERT model, to enhance code security testing for Python applications by detecting SQL injection vulnerabilities. Unlike traditional security testing methods that may be slow and error-prone, our approach transforms source code into vector representations and trains a Long Sho

Hongtao Huang, Chengkai Huang, Tong Yu, Xiaojun Chang

Recent advancements in diffusion models have shown promising results in sequential recommendation (SR). Existing approaches predominantly rely on implicit conditional diffusion models, which compress user behaviors into a single representation during the forward diffusion process. While effective to some extent, this oversimplification often leads to the los

Kendong Liu, Zhiyu Zhu, Chuanhao Li, Hui Liu

In this paper, we make the first attempt to align diffusion models for image inpainting with human aesthetic standards via a reinforcement learning framework, significantly improving the quality and visual appeal of inpainted images. Specifically, instead of directly measuring the divergence with paired images, we train a reward model with the dataset we con

Yutao Mou, Shikun Zhang, Wei Ye

Ensuring the safety of large language model (LLM) applications is essential for developing trustworthy artificial intelligence. Current LLM safety benchmarks have two limitations. First, they focus solely on either discriminative or generative evaluation paradigms while ignoring their interconnection. Second, they rely on standardized inputs, overlooking the

Dat Nguyen, Marcella Astrid, Enjie Ghorbel, Djamila Aouada

Recently, Vision Transformers (ViTs) have achieved unprecedented effectiveness in the general domain of image classification. Nonetheless, these models remain underexplored in the field of deepfake detection, given their lower performance as compared to Convolution Neural Networks (CNNs) in that specific context. In this paper, we start by investigating why

Jun Jiang, Peng-Cheng Lu, Zong-Guo Si, Han Zhang

We study the next-to-leading order (NLO) electroweak (EW) corrections to the $\gamma \gamma \to \tau^+ \tau^-$ process in Pb-Pb ultraperipheral collision (UPC). We find that the EW correction $\delta \sigma_{\mathrm{EW}}$ decreases the total cross section $\sigma_{\mathrm{NLO}} = \sigma_{\mathrm{LO}} + \delta \sigma_{\mathrm{EW}}$ by -3\% at Pb-Pb center-of-

Mikael Mortensen

This paper describes a fast algorithm for transforming Legendre coefficients into Chebyshev coefficients, and vice versa. The algorithm is based on the fast multipole method and is similar to the approach described by Alpert and Rokhlin [SIAM J. Sci. Comput., 12 (1991)]. The main difference is that we utilise a modal Galerkin approach with Chebyshev basis fu

Rafael S. de Souza, Luis G. Dahmer-Hahn, Shiyin Shen, Ana L. Chies-Santos

We present capivara, a fast and scalable spectral-based segmentation package designed to study astrophysical properties within distinct structural components of galaxies. This spectro-segmentation code for integral field unit (IFU) data provides a holistic view of galactic structure, moving beyond conventional radial gradients and the bulge-plus-disk dichoto