November 2024 arXiv papers — page 14

Christian Homeyer, Christoph Schnörr

Moving object detection and segmentation from a single moving camera is a challenging task, requiring an understanding of recognition, motion and 3D geometry. Combining both recognition and reconstruction boils down to a fusion problem, where appearance and motion features need to be combined for classification and segmentation. In this paper, we present a n

Roberto Balestri

This study investigates ChatGPT-4o's multimodal content generation, highlighting significant disparities in its treatment of sexual content and nudity versus violent and drug-related themes. Detailed analysis reveals that ChatGPT-4o consistently censors sexual content and nudity, while showing leniency towards violence and drug use. Moreover, a pronounced ge

Zi-Qiang Yin, Zhi-Hao Liu, Jian Tang, Hui Jing

Quantum correlation of photons based on quantum interference, such as unconventional photon blockade (UPB), has been extensively studied for realizing single-photon sources in weak nonlinear regime. However, how to use this effect for other practical applications is rarely studied. Here, we propose schemes to realize sensitive sensing by the quantum correlat

Bernhard Klar, Bojana Milošević, Marko Obradović

This paper presents a comprehensive study of nonparametric estimation techniques on the circle using Fej\'er polynomials, which are analogues of Bernstein polynomials for periodic functions. Building upon Fej\'er's uniform approximation theorem, the paper introduces circular density and distribution function estimators based on Fej\'er kernels. It establishe

Harrison Nicholls, Tim Lichtenberg, Dan J. Bower, Raymond Pierrehumbert

Interactions between magma oceans and overlying atmospheres on young rocky planets leads to an evolving feedback of outgassing, greenhouse forcing, and mantle melt fraction. Previous studies have predominantly focused on the solidification of oxidized Earth-similar planets, but the diversity in mean density and irradiation observed in the low-mass exoplanet

Zhi-Xiang Tang, Xun-Wei Xu

Magnetic-free optomechanically induced nonreciprocity may stimulate a wide range of practical applications in quantum technologies. However, how to suppress the thermal noise flow from the mechanical reservoir is still a difficulty encountered in achieving optomechanically nonreciprocal effects on a few- and even single-photon level. Here, we show how to rea

V. A. Yerokhin, Z. Harman, C. H. Keitel

Numerical calculations of the electron self-energy without any expansion in the binding nuclear field are required in order to match the rapidly advancing precision of experimental spectroscopy. For the lightest elements, particularly hydrogen, these computations are complicated by large numerical cancellations and the slow convergence of the partial-wave ex

Peilin Tian, Hao Li

Simultaneous Localization and Mapping (SLAM) and Multi-Object Tracking (MOT) are pivotal tasks in the realm of autonomous driving, attracting considerable research attention. While SLAM endeavors to generate real-time maps and determine the vehicle's pose in unfamiliar settings, MOT focuses on the real-time identification and tracking of multiple dynamic obj

Batıkan Bora Ormancı, Phillip Swazinna, Steffen Udluft, Thomas A. Runkler

In this paper, we investigate offline reinforcement learning (RL) with the goal of training a single robust policy that generalizes effectively across environments with unseen dynamics. We propose a novel approach, Trajectory Encoding Augmentation (TEA), which extends the state space by integrating latent representations of environmental dynamics obtained fr

Margarita Miguelina Mieras, Tania Daiana Tobares, Ricardo Raúl Palma, Antonio José Ramirez-Pastor

This research presents the development of a new simulation model to determine the optimal order lot sizes in Material Requirements Planning, based on purchase volume and the temporal deterioration of items. The scientific novelty lies in the exhaustive enumeration of all supply strategies, considering when and how much raw material and/or inputs to acquire w

Eleftherios E. Vlahakis, Lars Lindemann, Pantelis Sopasakis, Dimos V. Dimarogonas

We address an optimal control problem for linear stochastic systems with unknown noise distributions and joint chance constraints using conformal prediction. Our approach involves designing a feedback controller to maintain an error system within a prediction region (PR). We define PRs as sublevel sets of a nonconformity score over error trajectories, enabli

Chengcai Tian, Florian Sedlmeir, Jervee Punzalan, Petra Becker

Lithium tetraborate (LB4) is a lithium borate compound and recently has shown renewed interest due to its exceptional linear and nonlinear optical properties. Its wide transparency range, spanning from 0.16$\mu m$ to 3.5$\mu m$, and low loss in the visible range make LB4 highly popular in applications of harmonics generation and deep ultraviolet radiation. A

Hengkui Wu, Panpan Chi, Yongfeng Zhu, Liujiang Liu

For decades, researchers have developed task-specific models to address scientific challenges across diverse disciplines. Recently, large language models (LLMs) have shown enormous capabilities in handling general tasks; however, these models encounter difficulties in addressing real-world scientific problems, particularly in domains involving large-scale nu

P. Chatterjee, M. Nord, J. He, D. Meier

FeSn is a room-temperature antiferromagnet composed of alternating Fe3Sn kagome layers and honeycomb Sn layers. Its distinctive lattice allows the formation of linearly dispersing Dirac bands and topological flat bands in its electronic band structure, positioning FeSn as an ideal candidate for investigating the interplay between magnetism and topology. In t

Stephanie M. Brown, Badri Krishnan, Rahul Somasundaram, Ingo Tews

One of the main goals of gravitational-wave astrophysics is to study gravity in the strong-field regime and constrain deviations from general relativity (GR). Any such deviation affects not only binary dynamics and gravitational-wave emission but also the structure and tidal properties of compact objects. In the case of neutron stars, masses, radii, and tida

Alireza Faraji, Zahra Molaee, Ahmad Shirzad

General relativity contains 16 variables in the framework of ADM-Vielbein formalism which are 6 more than metric formalism. These variables emerge due to additional symmetry of Local Lorentz Transformations. In the framework of the Hamiltonian approach, it is expected to find first class constraints which generate this gauge symmetry. We introduce the comple

Yicheng Zhang, Zhen Qin, Zhaomin Wu, Jian Hou

Large language models (LLMs) are increasingly powering web-based applications, whose effectiveness relies on fine-tuning with large-scale instruction data. However, such data often contains valuable or sensitive information that limits its public sharing among business organizations. Federated learning (FL) enables collaborative fine-tuning of LLMs without a

Ilaria Andrei, Damianos Iosifidis, Laur Järv, Margus Saal

In metric-affine gravity, both the gravitational and matter actions depend not just on the metric, but also on the independent affine connection. Thus matter can be modeled as a hyperfluid, characterized by both the energy-momentum and hypermomentum tensors. The latter is defined as the variation of the matter action with respect to the connection and it enc

L. Ricci, B. Boccardi, J. Roeder, M. Perucho

The dynamic of relativistic jets in the inner parsec regions is deeply affected by the nature of the magnetic fields. The level of magnetization of the plasma, as well as the geometry of these fields on compact scales, have not yet been fully constrained. In this paper we employ multi-frequency and multi-epoch very long baseline interferometry observations o

Honghui Wang, Yifan Pu, Shiji Song, Gao Huang

Physics-informed neural networks (PINNs) have made significant strides in modeling dynamical systems governed by partial differential equations (PDEs). However, their generalization capabilities across varying scenarios remain limited. To overcome this limitation, we propose PIDO, a novel physics-informed neural PDE solver designed to generalize effectively

Navin Rajapriya, Kotaro Kawajiri

Developing environmentally sustainable refrigerants is critical for mitigating the impact of anthropogenic greenhouse gases on global warming. This study presents a predictive modeling framework to estimate the 100-year global warming potential (GWP 100) of single-component refrigerants using a fully connected neural network implemented on the Multi-Sigma pl

Swetha B, Susmitha NRK, Thirulogaveni J, Sruthi S

The evolving threat landscape in cybersecurity necessitates the adoption of advanced tools for effective vulnerability management. This paper presents a comprehensive comparative analysis of three widely used tools: Nessus, Acunetix, and Nikto. Each tool is assessed based on its detection accuracy, risk scoring using the Common Vulnerability Scoring System (

Alessandro Licciardi, Davide Carbone, Lamberto Rondoni, Alessandro Nagar

Gravitational waves, first predicted by Albert Einstein within the framework of general relativity, were confirmed in 2015 by the LIGO/Virgo collaboration, marking a pivotal breakthrough in astrophysics. Despite this achievement, a key challenge remains in distinguishing true gravitational wave signals from noise artifacts, or "glitches," which can distort d

Daewon Yoon, Hyeongseok Lee, Wonsik Shin, Sangyu Han

While text-to-video diffusion models have advanced significantly, creating coherent long-form content remains unreliable due to stochastic sampling artifacts. This necessitates generating multiple candidates, yet verifying them creates a severe bottleneck; manual review is unscalable, and existing automated metrics lack the adaptability and speed required fo

Maxim Dvornikov

We study neutrino oscillations in background matter within the quantum field theory formalism where neutrino mass eigenstates are virtual particles. In this case, neutrino mass eigenstates are mixed owing to the interaction with matter. Assuming that neutrinos are Majorana particles, we find the exact propagators for massive neutrinos accounting for the inte

Jaco du Toit, Herman Redelinghuys, Marcel Dunaiski

Hierarchical Text Classification (HTC) is a natural language processing task with the objective to classify text documents into a set of classes from a structured class hierarchy. Many HTC approaches have been proposed which attempt to leverage the class hierarchy information in various ways to improve classification performance. Machine learning-based class

Daniel Moreno-Garcia, Luis Guillermo Villanueva

Flexoelectricity is a property of all dielectric materials, where inhomogeneous strain induces electrical polarization. This effect becomes particularly prominent at the nanoscale where larger strain gradients can be obtained. While flexoelectric charges have been measured in mm-scale systems, direct measurements in nanoscale-thickness materials have not yet

Chung-Ting Tsai, Ching-Yun Ko, I-Hsin Chung, Yu-Chiang Frank Wang

The rapid advancement of generative models has introduced serious risks, including deepfake techniques for facial synthesis and editing. Traditional approaches rely on training classifiers and enhancing generalizability through various feature extraction techniques. Meanwhile, training-free detection methods address issues like limited data and overfitting b

Panchajanya Dey, Banibrata Mukhopadhyay

The exact theory of gravity in the strong field regime is still under debate. There are observations implying the need for modification to Einstein's gravity. On the other hand, the exact constituents of dark matter are also a big puzzle, where primordial black holes (PBHs) are argued to be a potential candidate. We explore Hawking radiation in a modified gr

Hyeon-Woo Jeong, Seong Jang, Sein Park, Kenji Watanabe

The topological properties of gapped graphene have been explored for valleytronics applications. Prior transport experiments indicated their topological nature through large nonlocal resistance in Hall-bar devices, but the origin of this resistance was unclear. This study focused on dual-gate bilayer graphene (BLG) devices with naturally cleaved edges, exami

Gwangoo Yeo, Jiin Kim, Yujeong Choi, Minsoo Rhu

NVIDIA's Multi-Instance GPU (MIG) is a feature that enables system designers to reconfigure one large GPU into multiple smaller GPU slices. This work characterizes this emerging GPU and evaluates its effectiveness in designing high-performance AI inference servers. Our study reveals that the data preprocessing stage of AI inference causes significant perform

Siqi Kou, Jiachun Jin, Zhihong Liu, Chang Liu

We introduce Orthus, an autoregressive (AR) transformer that excels in generating images given textual prompts, answering questions based on visual inputs, and even crafting lengthy image-text interleaved contents. Unlike prior arts on unified multimodal modeling, Orthus simultaneously copes with discrete text tokens and continuous image features under the A

Eduard Manziuk, Oleksander Barmak, Pavlo Radiuk, Vladislav Kuznetsov

This paper proposes a novel approach to semantic ontology alignment using contextual descriptors. A formalization was developed that enables the integration of essential and contextual descriptors to create a comprehensive knowledge model. The hierarchical structure of the semantic approach and the mathematical apparatus for analyzing potential conflicts bet

Julien Dudas, Baptiste Carles, Elie Gouzien, Julie Grollier

Quantum neural networks promise to extend the power of machine learning into the quantum domain, with potential applications ranging from automatic recognition of quantum states to the control of quantum devices. However, their physical implementation and training remain challenging. In particular, the backpropagation algorithm that underpins the efficiency

Matthieu Faitg, Azat M. Gainutdinov, Christoph Schweigert

Davydov-Yetter cohomology $H_{\mathrm{DY}}^{\bullet}(F)$ is associated to a monoidal functor $F: \mathcal{C} \to \mathcal{D}$ between $\Bbbk$-linear monoidal categories where $\Bbbk$ is a field, and its second degree classifies the infinitesimal deformations of the monoidal structure of $F$. Our main result states that if $F$ admits a right adjoint $R$, then

Yuxiang Liu, Ligong Wang

A graph $G$ is $F$-free if $G$ does not contain $F$ as a subgraph. Let $\mathcal{G}(m, F)$ denote the family of $F$-free graphs with $m$ edges and without isolated vertices. Let $S_{n,k}$ denote the graph obtained by joining every vertex of $K_{k}$ to $n-k$ isolated vertices and $S_{n,k}^{t}$ denote the graph obtained from $S_{n-t,k}$ by attaching $t$ pendan

Lei Zhou, Youwen Zhu, Qiao Xue, Ji Zhang

Recently, the enactment of ``right to be forgotten" laws and regulations has imposed new privacy requirements on federated learning (FL). Researchers aim to remove the influence of certain data from the trained model without training from scratch through federated unlearning (FU). While current FU research has shown progress in enhancing unlearning efficienc

Andrey A. Voronov, Marcos Cuervo Santos, Florian Bruckner, Dieter Suess

The inverse design approach in magnonics exploits the wave nature of magnons and machine learning to develop logical devices with functionalities that exceed the capabilities of analytical methods. While promising for analog, Boolean, and neuromorphic computing, current implementations face memory limitations that hinder the design of complex systems. This s

Feng Liu, Shiwei Zhang, Xiaofeng Wang, Yujie Wei

As a fundamental backbone for video generation, diffusion models are challenged by low inference speed due to the sequential nature of denoising. Previous methods speed up the models by caching and reusing model outputs at uniformly selected timesteps. However, such a strategy neglects the fact that differences among model outputs are not uniform across time

Shuo Xu, Haokai Ma, Yunshan Ma, Xiaohao Liu

Product bundling aims to organize a set of thematically related items into a combined bundle for shipment facilitation and item promotion. To increase the exposure of fresh or overstocked products, sellers typically bundle these items with popular products for inventory clearance. This specific task can be formulated as a long-tail product bundling scenario,

Xinran Wang, Haiwen Zhang, Baoteng Li, Kongming Liang

Object description plays an important role for visually impaired individuals to understand and compare the differences between objects. Recent multimodal large language models(MLLMs) exhibit powerful perceptual abilities and demonstrate impressive potential for generating object-centric descriptions. However, the descriptions generated by such models may sti

Xianhao Ye, Wenbo Wu, Carlos Allende Prieto, David S. Aguado

Gaia Bp/Rp spectra for over two hundred million stars have great potential for mapping metallicity across the Milky Way. We aim to construct an alternative catalog of atmospheric parameters from Gaia Bp/Rp spectra by fitting them with synthetic spectra based on model atmospheres, and provide corrections to the Bp/Rp fluxes according to stellar colors, magnit

Juan Eloy Ruiz-Castro, Hugo Alaín Zapata-Ceballos

A complex multi-state redundant system undergoing preventive maintenance and experiencing multiple events is being considered in a continuous time frame. The online unit is susceptible to various types of failures, both internal and external in nature, with multiple degradation levels present, both internally and externally. Random inspections are continuous

Jeongho Ju, Daeyoung Kim, SunYoung Park, Youngjune Kim

In this paper, we introduce an open-source Korean-English vision-language model (VLM), VARCO-VISION. We incorporate a step-by-step training strategy that allows a model learn both linguistic and visual information while preserving the backbone model's knowledge. Our model demonstrates outstanding performance in diverse settings requiring bilingual image-text

Zhongmiao Yan, Qi Wu, Songpengcheng Xia, Junyuan Deng

360-degree images offer a significantly wider field of view compared to traditional pinhole cameras, enabling sparse sampling and dense 3D reconstruction in low-texture environments. This makes them crucial for applications in VR, AR, and related fields. However, the inherent distortion caused by the wide field of view affects feature extraction and matching

Felicitas Hörmann, Hannes Bartz

Linearized Reed--Solomon (LRS) codes are sum-rank-metric codes that generalize both Reed--Solomon and Gabidulin codes. We study vertically and horizontally interleaved LRS (VILRS and HILRS) codes whose codewords consist of a fixed number of stacked or concatenated codewords of a chosen LRS code. Our unified presentation of results for horizontal and vertical

Stefano Crotti, Thomas Barthel, Alfredo Braunstein

We propose an analytic approach for the steady-state dynamics of Markov processes on locally tree-like graphs. It is based on time-translation invariant probability distributions for edge trajectories, which we encode in terms of infinite matrix products. For homogeneous ensembles on regular graphs, the distribution is parametrized by a single $d\times d\tim

Jason Li, Owen Li

We present a simple and faster algorithm for computing fair cuts on undirected graphs, a concept introduced in recent work of Li et al. (SODA 2023). Informally, for any parameter $\epsilon>0$, a $(1+\epsilon)$-fair $(s,t)$-cut is an $(s,t)$-cut such that there exists an $(s,t)$-flow that uses $1/(1+\epsilon)$ fraction of the capacity of every edge in the cut

Yusen Li, Kenneth Freeman, Helmut Jerjen

The Hercules kinematic group is a stellar anomaly structure observed in the solar neighbourhood (SNd). In the previous paper, we analysed chemical signatures and related the origin of this stellar population to the outer bar. Next to consider is how this alien population migrate out into the SNd. Often, this kinematic structure is associated with bar resonan

Sanjay Suryanarayanan, Haiyue Song, Mohammed Safi Ur Rahman Khan, Anoop Kunchukuttan

Mining parallel document pairs for document-level machine translation (MT) remains challenging due to the limitations of existing Cross-Lingual Document Alignment (CLDA) techniques. Existing methods often rely on metadata such as URLs, which are scarce, or on pooled document representations that fail to capture fine-grained alignment cues. Moreover, the limi

Ryosuke Sakamoto

The concept of ``multi-microlocalization'' was introduced to extend the usual microlocal sheaf theory to a more general scope. This paper aims to further extend this theory by exploring advanced topics. One is a stalk formula for multi-microlocalized Hom functors and we compute some examples in multi-microlocal settings. Secondly we construct the Sato's tria

Bin Jiang

Beautimeter is a new tool powered by generative pre-trained transformer (GPT) technology, designed to evaluate architectural and urban beauty. Rooted in Christopher Alexander's theory of centers, this work builds on the idea that all environments possess, to varying degrees, an innate sense of life. Alexander identified 15 fundamental properties, such as lev

Dae-Young Yun, Hee-Youl Kwak, Yongjune Kim, Sang-Hyo Kim

In this paper, we propose a neural window decoder (NWD) for spatially coupled low-density parity-check (SC-LDPC) codes. The proposed NWD retains the conventional window decoder (WD) process but incorporates trainable neural weights. To train the weights of NWD, we introduce two novel training strategies. First, we restrict the loss function to target variabl

G. S. Bali, V. M. Braun, S. Bürger, M. Göckeler

We present updated results on the wave function normalization constants and the first moments of the light cone distribution amplitudes for the lowest-lying baryon octet. The analysis is carried out on a large number of $n_f=2+1$ lattice gauge ensembles, including ensembles at physical pion (and kaon) masses. These are spread across five different lattice sp

Batuhan Sariturk, Rabia Bayraktar, Merve Elmas Erdem

With the rise of online education platforms, there is a growing abundance of educational content across various domain. It can be difficult to navigate the numerous available resources to find the most suitable training, especially in domains that include many interconnected areas, such as ICT. In this study, we propose a domain-specific chatbot application

Conrad Borchers, Ryan S. Baker

Algorithmic bias continues to be a key concern of learning analytics. We study the statistical properties of the Absolute Between-ROC Area (ABROCA) metric. This fairness measure quantifies group-level differences in classifier performance through the absolute difference in ROC curves. ABROCA is particularly useful for detecting nuanced performance difference

Tilman Aleman, Arnold Reusken

We consider a setting in which an evolving surface is implicitly characterized as the zero level of a level set function. Such an implicit surface does not encode any information about the path of a single point on the evolving surface. In the literature different approaches for determining a velocity that induces corresponding paths of points on the surface

Valentina Astore, Martino Borello, Marco Calderini, Flavio Salizzoni

Rank-metric codes have been a central topic in coding theory due to their theoretical and practical significance, with applications in network coding, distributed storage, crisscross error correction, and post-quantum cryptography. Recent research has focused on constructing new families of rank-metric codes with distinct algebraic structures, emphasizing th

Masato Suzuki, Ken'ichiro Tanaka

We propose a quadrature-based formula for computing the exponential function of matrices with a non-oscillatory integral on an infinite interval and an oscillatory integral on a finite interval. In the literature, existing quadrature-based formulas are based on the inverse Laplace transform or the Fourier transform. We show these expressions are essentially

Yusen Li, Kenneth Freeman, Helmut Jerjen, Sven Buder

The Hercules kinematic group is a kinematic anomaly of stars observed in the solar neighbourhood (SNd). In this series of papers, we present a comprehensive study of this structure. This paper focuses on its chemical signatures over several groups of elements. The next paper discusses its kinematical properties. While studies suggested a non-native origin of

Daumantas Kojelis

We study the fluted fragment of first-order logic which is often viewed as a multi-variable non-guarded extension to various systems of description logics lacking role-inverses. In this paper we show that satisfiable fluted sentences (even under reasonable extensions) admit special kinds of ``nice'' models which we call globally/locally homogeneous. Homogene

Yuqian Fu, Runze Wang, Bin Ren, Guolei Sun

Bridging the gap between ego-centric and exo-centric views has been a long-standing question in computer vision. In this paper, we focus on the emerging Ego-Exo object correspondence task, which aims to understand object relations across ego-exo perspectives through segmentation. While numerous segmentation models have been proposed, most operate on a single

Ryotaku Suzuki, Shinya Tomizawa

We present a new non-BPS solution describing an asymptotically flat, stationary, bi-axisymmetric capped black hole in the bosonic sector of five-dimensional minimal supergravity. This solution describes a spherical black hole, while the exterior region of the horizon exhibits a non-trivial topology of $[{\mathbb R}^4 \# {\mathbb C}{\mathbb P}^2] \setminus {\

Babar Ali, Zdeněk Kohout, Hugo Natal da Luz, Rudolf Sýkora

We report on measurements of 1 and 1.5 MeV monoenergetic electrons with a Timepix3-based detector using a 0.5 mm thick silicon sensor. A $^{90}$Sr $\beta$-emitting radioisotope was used as the source of electrons, and a monochromator equipped with an adjustable magnetic field was employed to only pass electrons of desired energy into the detector. We provide

Gangmin Son, Deok-Sun Lee, Kwang-Il Goh

We study the phase transitions in the simplicial Ising model on hypergraphs, in which the energy within each hyperedge (group) is lowered only when all the member spins are unanimously aligned. The Hamiltonian of the model is equivalent to a weighted sum of lower-order interactions, evoking an Ising model defined on a simplicial complex. Using the Landau fre

Tingting Ye, Yuxuan Xu, Guo Chen, Ming Li

Cubic gauche nitrogen (cg-N) with a three-dimensional network of N-N single bonds attracted lots of attentions in last decades, since it theoretically has five times larger energy than TNT. While, extreme environments of high pressure or plasma treatment were required in traditional routes. Quite recently, in vacuum or protective gas environments, a one-step

S. Aiello, A. Albert, A. R. Alhebsi, M. Alshamsi

KM3NeT/ORCA is an underwater neutrino telescope under construction in the Mediterranean Sea. Its primary scientific goal is to measure the atmospheric neutrino oscillation parameters and to determine the neutrino mass ordering. ORCA can constrain the oscillation parameters $\Delta m^{2}_{31}$ and $\theta_{23}$ by reconstructing the arrival direction and ener

Ganglin Tian, Camille Le Coz, Anastase Alexandre Charantonis, Alexis Tantet

Sub-seasonal wind speed forecasts provide valuable guidance for wind power system planning and operations, yet the forecast skills of surface winds decrease sharply after two weeks. However, large-scale variables exhibit greater predictability on this time scale. This study explores the potential of leveraging non-linear relationships between 500 hPa geopote

Marcel Pfeiffer, Félix Garmirian, Tobias Ott

Solving the Bhatnagar-Gross-Krook (BGK) equation with a stochastic particle approach enables efficient and flexible simulations of flows in the transition regime, between continuum and free molecular flow. However, the usual first-order operator splitting between particle movement and relaxation imposes restrictions on the time step, causing the computationa

Dazhuang Liu, Yanqi Qiao, Rui Wang, Kaitai Liang

Current black-box backdoor attacks in convolutional neural networks formulate attack objective(s) as single-objective optimization problems in single domain. Designing triggers in single domain harms semantics and trigger robustness as well as introduces visual and spectral anomaly. This work proposes a multi-objective black-box backdoor attack in dual domai

D. Jiménez-Galindo, P. Casaseca-de-la-Higuera, Luis M. San-José-Revuelta

The design of both FIR and IIR digital filters is a multi-variable optimization problem, where traditional algorithms fail to obtain optimal solutions. A modified Shuffled Frog Leaping Algorithm (SFLA) is here proposed for the design of FIR and IIR discrete-time filters as close as possible to the desired filter frequency response. This algorithm can be cons

Lucas M. Jordan, Thomas Rometsch

Context. Binary star systems allow us to study the planet formation process under extreme conditions. In the early stages, these systems contain a circumbinary disk and a disk around each star. To model the interactions between these disks in the frame of one of the stars, strong fictitious forces must be included in the simulations. The original Fargo and t

Lila Cadi Tazi, David Muñoz Ramo, Alex J. W. Thom

The measurement of scalar products between two vectors is a common task in scientific computing and, by extension, in quantum computing. In this work, we introduce two alternative quantum circuits for computing scalar products with phase information, combining the structure of the swap test, the vacuum test, and the Hadamard test. These novel frameworks, cal

Junwei Feng, Xueyan Fan, Yuyang Chen, Yi Li

Ensuring construction site safety requires accurate and real-time detection of workers' safety helmet use, despite challenges posed by cluttered environments, densely populated work areas, and hard-to-detect small or overlapping objects caused by building obstructions. This paper proposes a novel algorithm for safety helmet wearing detection, incorporating a

Manish Chaudhary, Rejish Nath, Weibin Li

Non-adiabatic processes near conical intersections are rooted in the stronger coupling between electronic and nuclear degrees of freedom. Using a system of two trapped Rydberg ions, their high polarizability and strong dipolar interactions allow to form a conical intersection, where dynamics takes place on a microsecond time scale. Rydberg lifetimes are typi

Wei Xiong, Peng-Cheng Li

Recent studies have shown that rotating black holes can undergo spontaneous scalarization, leading to deviations from general relativity in the strong-field regime. We present the first nonperturbative calculation of the quasinormal modes (QNMs) of scalarized Kerr black holes in Einstein-scalar-Gauss-Bonnet gravity, without assuming small spin or weak coupli

Xuanchi Guo, Anh Le-Tuan, Danh Le-Phuoc

This paper proposes the possibility of integrating Dynamic Knowledge Graph (DKG) with Software-Defined Networking (SDN). This new approach aims to assist the management and control capabilities of the swarm network. The DKG works as a unified network data view, capturing network information such as topology, flow rules, host information, switch information,

Minhyun Lee, Seungho Lee, Song Park, Dongyoon Han

Referring Image Segmentation (RIS) is an advanced vision-language task that involves identifying and segmenting objects within an image as described by free-form text descriptions. While previous studies focused on aligning visual and language features, exploring training techniques, such as data augmentation, remains underexplored. In this work, we explore

Shengjun Zhu, Siyu Liu, Yang Li, Qing Lei

Coronavirus Disease 2019 (COVID-19), which emerged in 2019, has caused millions of deaths worldwide. Although effective vaccines have been developed to mitigate severe symptoms, certain populations, particularly the elderly and those with comorbidities, remain at high risk for severe outcomes and increased mortality. Consequently, early identification of the

Sota Minewaki, Tomohiro Ohigashi, Takashi Sozu

Benchmark dose (BMD; a dose associated with a specified change in response) is used to determine the point of departure for the acceptable daily intake of substances for humans. Multiple dose-response relationship models are considered in the BMD method. Bayesian model averaging (BMA) is commonly used, where several models are averaged based on their posteri

Adrián Fidalgo-Díaz, Umberto Martínez-Peñas

The problem of distributed matrix multiplication with straggler tolerance over finite fields is considered, focusing on field sizes for which previous solutions were not applicable (for instance, the field of two elements). We employ Reed-Muller-type codes for explicitly constructing the desired algorithms and study their parameters by translating the proble

Yutong Zhang, Lixing Chen, Shenghong Li, Nan Cao

Large language models (LLMs) have demonstrated exceptional performance across a wide variety of domains. Nonetheless, generalist LLMs continue to fall short in reasoning tasks necessitating specialized knowledge. Prior investigations into specialized LLMs focused on domain-specific training, which entails substantial efforts in domain data acquisition and mo

André Milagre, Luís Lavoura

We consider an extension of the Standard Model with one or more scalar multiplets beyond the Higgs doublet $\Phi$. The additional scalar multiplets are supposed to carry arbitrary hypercharges. We prove that, in such a model, if the field configuration where only $\Phi$ has a nonzero vacuum expectation value (VEV) is a local minimum of the potential, then it

Tao Tang, Mengzhou Li, Bin Lao, Xuan Zheng

In Weyl semimetals, the nonlinear planar Hall effect (NPHE) and spin-orbit torque (SOT) are prominent manifestations of nonlinear and linear charge-spin conversion, respectively. However, simultaneous investigations of these phenomena within a single material system are scarce, limiting our understanding of their intrinsic connection and underlying mechanism

S. Ayaz, Gary P. Zank, Imran A. Khan, G. Li

The heating of the solar corona and solar wind, through suprathermal particles and kinetic Alfv\'en waves within the 0 - 10 $R_{\rm Sun}$ range, has been a subject of great interest for many decades. This study investigates the acceleration and heating of charged particles and the role of KAWs in the solar corona. We investigate how KAWs transport energy and

Biswanath Layek, Brijesh Kumar Saini, Deepthi Godaba Venkata

The basic framework of the superfluid vortex model for pulsar glitches, though, is well accepted; there is a lack of consensus on the possible trigger mechanism responsible for the simultaneous release of a large number ($\sim 10^{17}$) of superfluid vortices from the inner crust. Here, we propose a simple trigger mechanism to explain such catastrophic event

MinKyu Lee, Sangeek Hyun, Woojin Jun, Jae-Pil Heo

This work tackles the fidelity objective in the perceptual super-resolution~(SR). Specifically, we address the shortcomings of pixel-level $L_\text{p}$ loss ($\mathcal{L}_\text{pix}$) in the GAN-based SR framework. Since $L_\text{pix}$ is known to have a trade-off relationship against perceptual quality, prior methods often multiply a small scale factor or u

Mayusree Das, Banibrata Mukhopadhyay

The existence of massive white dwarfs (WDs) containing more than Chandrasekhar's maximum mass has been suggested via the detection of peculiar type Ia Supernovae. It had been crucial to directly detect those 'super' (more massive)-Chandrasekhar WDs to confirm their existence. The WD's small size and cold internal environment have been a great disadvantage fo

Philipp Wiesner, Dennis Grinwald, Philipp Weiß, Patrick Wilhelm

The energy demand of modern cloud services, particularly those related to generative AI, is increasing at an unprecedented pace. To date, carbon-aware computing strategies have primarily focused on batch process scheduling or geo-distributed load balancing. However, such approaches are not applicable to services that require constant availability at specific

Suliman Khan, Edwin R. van Dam

We obtain a bound on the girth g of a quaternion unit gain graph in terms of the rank r of its adjacency matrix. In particular, we show that g <= r + 2 and characterize all quaternion unit gain graphs for which g = r+2. This extends corresponding results for (ordinary) graphs, signed graphs, and complex unit gain graphs.

Umberto Casti, Sandro Zampieri

In this paper, we propose control-theoretic methods as tools for the design of online optimization algorithms that are able to address dynamic, noisy, and partially uncertain time-varying quadratic objective functions. Our approach introduces two algorithms specifically tailored for scenarios where the cost function follows a stochastic linear model. The fir

Niklas Christoph Affolter, Felix Dellinger, Christian Müller, Denis Polly

S-embeddings were introduced by Chelkak as a tool to study the conformal invariance of the thermodynamic limit of the Ising model. Moreover, Chelkak, Laslier and Russkikh introduced a lift of s-embeddings to Lorentz space, and showed that in the limit the lift converges to a maximal surface. They posed the question whether there are s-embeddings that lift to

Noureddine Djama

This study proposes a new fundamental formula that describes in a more coherent way, the rise and fall of liquids in capillaries. The variation of the contact angle classically associated with these phenomena appears to be the indirect result of a more authentic physical parameter, which we call the apparent capillary range. This range depends on factors exp

Giulio Ferri, Enzo Marino

We present a novel formulation for the dynamics of geometrically exact Timoshenko beams and beam structures made of viscoelastic material featuring complex, arbitrarily curved initial geometries. An $\textrm{SO}(3)$-consistent and second-order accurate time integration scheme for accelerations, velocities and rate-dependent viscoelastic strain measures is ad

James A. Monro, Andrew M. Kingston, David M. Paganin

Ghost projection is the reversed process of computational classical ghost imaging that allows any desired image to be synthesized using a linear combination of illuminating patterns. Typically, physical attenuating masks are used to produce these illuminating patterns. A mask-free alternative form of ghost projection is explored here, where the illuminations

K. D. Duan, H. B. Zhang, X. L. Shang

The finite-temperature phase structures for neutron-proton superfluidity in asymmetric nuclear matter are investigated, with a particular focus on the angular dependence of the pairing gap induced by the $^3SD_1$ $NN$ interaction. This angular dependence of the pairing gap results in the Cooper pair momentum in the Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) sta

Nicola Fanelli, Gennaro Vessio, Giovanna Castellano

Inpainting focuses on filling missing or corrupted regions of an image to blend seamlessly with its surrounding content and style. While conditional diffusion models have proven effective for text-guided inpainting, we introduce the novel task of multi-mask inpainting, where multiple regions are simultaneously inpainted using distinct prompts. Furthermore, w

Safa Ben Atitallah, Chaima Ben Rabah, Maha Driss, Wadii Boulila

The abundance of complex and interconnected healthcare data offers numerous opportunities to improve prediction, diagnosis, and treatment. Graph-structured data, which includes entities and their relationships, is well-suited for capturing complex connections. Effectively utilizing this data often requires strong and efficient learning algorithms, especially

Sara Logsdon, Arya Maheshwari, István Miklós, Angelina Zhang

We present a dichotomy theorem on the parameterized complexity of the 3-uniform hypergraphicality problem. Given $0<c_1\le c_2 < 1$, the parameterized 3-uniform Hypergraphic Degree Sequence problem, $3uni-HDS_{c_1,c_2}$, considers degree sequences $D$ of length $n$ such that all degrees are between $c_1 {n-1 \choose 2}$ and $c_2 {n-1\choose 2}$ and it asks i

Gayatri Mohan, Nashiba Parbin, Umananda Dev Goswami

In this work, gravitational lensing in the weak and strong field limits is investigated for black hole spacetime within the framework of Hu-Sawicki $f(R)$ gravity. We employ the Ishihara et al. approach for weak lensing and adopt Bozza's method for strong lensing to explore the impact of Hu-Sawicki model parameters on lensing phenomenon. The deflection angle