December 2024 arXiv papers — page 109

Florian Millo, Rafael Lopes Seeger, Claude Chappert, Aurélie Solignac

We study the symmetry of the coupling between surface acoustic waves and ferromagnetic resonance in a thin magnetic film of CoFeB deposited on top of a piezoelectric Z-cut LiNbO3 substrate. We vary the orientation of the applied magnetic field with respect to the wavevector of the surface acoustic wave. Experiments indicate an unexpected 2-fold symmetry of t

Adesh Kadambi, José Zariffa

Wearable egocentric cameras and machine learning have the potential to provide clinicians with a more nuanced understanding of patient hand use at home after stroke and spinal cord injury (SCI). However, they require detailed contextual information (i.e., activities and object interactions) to effectively interpret metrics and meaningfully guide therapy plan

Alexander Borichev, Alexander Volberg

We prove here the concentration of measure inequality for Lipschitz function on the Hamming cube with values in any Banach spaces of finite cotype.

Jingshi Yao, Minghao Han, Xunyuan Yin

In this paper, we propose a Lyapunov-based reinforcement learning method for distributed control of nonlinear systems comprising interacting subsystems with guaranteed closed-loop stability. Specifically, we conduct a detailed stability analysis and derive sufficient conditions that ensure closed-loop stability under a model-free distributed control scheme b

Haoxian Ruan, Zhihua Xu, Zhijing Yang, Yongyi Lu

Multi-label recognition with partial labels (MLR-PL), in which only some labels are known while others are unknown for each image, is a practical task in computer vision, since collecting large-scale and complete multi-label datasets is difficult in real application scenarios. Recently, vision language models (e.g. CLIP) have demonstrated impressive transfer

Lars Becker, Joseph Slote, Alexander Volberg, Haonan Zhang

We prove bounds for the absolute sum of all level-$k$ Fourier coefficients for $(-1)^{p(x)}$, where polynomial $p:\mathbf{F}_2^n \to \mathbf{F}_2$ is of degree $1$ or degree $2$.

Nityananda Roy, Robert Dürr, Andreas Bück, S. Sundar

Generating an accurate solution of the Navier--Stokes equations using physics--informed neural networks (PINNs) for higher Reynolds numbers in the corners of a lid--driven cavity problem is challenging. In this paper, we improve the solution accuracy of the incompressible Navier--Stokes equations in the region near the walls significantly and generate accura

Victor Batyrev

We classify all smooth projective toric surfaces $S$ containing exactly one exceptional curve. We show that every such surface $S$ is isomorphic to either $\mathbb{F}_1$ or a surface $S_r$ defined by a rational number $r \in \mathbb{Q} \setminus \mathbb{Z}$ $(r >1)$. If $a:= [ r]$ then $S_r$ is obtained from the minimal desingularization of the weighted proj

Hai-Ming Xu, Qi Chen, Lei Wang, Lingqiao Liu

Recent advancements in Multimodal Large Language Models (MLLMs) have generated significant interest in their ability to autonomously interact with and interpret Graphical User Interfaces (GUIs). A major challenge in these systems is grounding-accurately identifying critical GUI components such as text or icons based on a GUI image and a corresponding text qu

Eugen J. Ionascu, Florian Luca, Thomas Merino

We find a nontrivial upper bound on the average value of the function M(n) which associates to every positive integer n the minimal Hamming weight of a multiple of n. Some new results about the equation M(n)=M(n') are given.

Christian Flores, Marcelo Contreras, Ichiro Macedo, Javier Andreu-Perez

Machine learning and deep learning advancements have boosted Brain-Computer Interface (BCI) performance, but their wide-scale applicability is limited due to factors like individual health, hardware variations, and cultural differences affecting neural data. Studies often focus on uniform single-site experiments in uniform settings, leading to high performan

Kai Gu, Yingping Liang, Jiaming Su, Peihan Sun

Colloidal synthesis of nanocrystals usually includes complex chemical reactions and multi-step crystallization processes. Despite the great success in the past 30 years, it remains challenging to clarify the correlations between synthetic parameters of chemical reaction and physical properties of nanocrystals. Here, we developed a deep learning-based nanocry

Edward Pearce-Crump, William J. Knottenbelt

Group equivariant neural networks are growing in importance owing to their ability to generalise well in applications where the data has known underlying symmetries. Recent characterisations of a class of these networks that use high-order tensor power spaces as their layers suggest that they have significant potential; however, their implementation remains

Stefan Geiss, Xilin Zhou

Using the coupling method introduced in \cite{Geiss:Ylinen:21}, we investigate regularity properties of stochastic differential equations, where we consider the Lipschitz case in $\R^d$ and allow for H\"older continuity of the diffusion coefficient of scalar valued stochastic differential equations. Two cases of the coupling method are of special interest: T

Hasan Ozgur Cildiroglu, Oguz Yayla

The advent of quantum computing has profound implications for current technologies, offering advancements in optimization while posing significant threats to cryptographic algorithms. Public-key cryptosystems relying on prime factorization or discrete logarithms are particularly vulnerable, whereas block ciphers (BCs) remain secure through increased key leng

Jiaxu Li, Rui Li, Jianyu Qi, Songning Lai

2D images and 3D point clouds are foundational data types for multimedia applications, including real-time video analysis, augmented reality (AR), and 3D scene understanding. Class-incremental semantic segmentation (CSS) requires incrementally learning new semantic categories while retaining prior knowledge. Existing methods typically rely on computationally

V V Vlasyuk, I V Afanasieva, V I Ardilanov, V A Murzin

The development of technologies for creating various types of solid-state detectors for optical astronomy is reviewed. The principles of designing astronomical photodetecting systems with large-format sensors based on charge-coupled device (CCD) and complementary metal oxide semiconductor (CMOS) structures are analyzed. Examples of the most advanced projects

Hendrik Beukelman, Wilder C. Rodrigues

This study explores visual search asymmetry and the detection process between parallel and serial search strategies, building upon Treisman's Feature Integration Theory [3]. Our experiment examines how easy it is to locate an oblique line among vertical distractors versus a vertical line among oblique distractors, a framework previously validated by Treisman

Peter Fierlinger, Jie Sheng, Yevgeny V. Stadnik, Chuan-Yang Xing

We propose a novel detection method for axion dark matter using the Rabi oscillation of neutron spins in beam-based measurements. If axions couple to neutron spins, a background oscillating axion dark matter field would drive transitions between spin-up and spin-down neutron states in a magnetic field when the axion particle energy matches the energy gap bet

Dengyang Jiang, Haoyu Wang, Lei Zhang, Wei Wei

Pre-training backbone networks on a general annotated dataset (e.g., ImageNet) that comprises numerous manually collected images with category annotations has proven to be indispensable for enhancing the generalization capacity of downstream visual tasks. However, those manually collected images often exhibit bias, which is non-transferable across either cat

Youhui Yun, Zhizhen Zhou, Baoguo An, Zhixing Gao

Photomultiplier tubes (PMTs) are essential in xenon detectors like PandaX, LZ, and XENON experiments for dark matter searches and neutrino properties measurement. To minimize PMT-induced backgrounds, stringent requirements on PMT radioactivity are crucial. A novel 2-inch low-background R12699 PMT has been developed through a collaboration between the PandaX

Tim Zimmermann, David J. E. Marsh, Keir K. Rogers, Hans A. Winther

Fuzzy (wave) dark matter (FDM), the dynamical model underlying an ultralight bosonic dark matter species, produces a rich set of non-gravitational signatures that distinguishes it markedly from the phenomenologically related warm (particle) dark matter (WDM) scenario. The emergence of extended interference fringes hosted by cosmic filaments is one such pheno

Harsha Hutridurga, Krishan Kumar, Amiya K. Pani

In the first part of this paper, uniqueness of strong solution is established for the Vlasov-unsteady Stokes problem in 3D. The second part deals with a semi discrete scheme, which is based on the coupling of discontinuous Galerkin approximations for the Vlasov and the Stokes equations for the 2D problem. The proposed method is both mass and momentum conserv

Zongqian Wu, Baoduo Xu, Ruochen Cui, Mengmeng Zhan

Chain-of-thought (CoT) reasoning has emerged as an effective approach for activating latent capabilities in LLMs. Interestingly, we observe that both CoT reasoning and self-training share the core objective: iteratively leveraging model-generated information to progressively reduce prediction uncertainty. Building on this insight, we propose a novel CoT fram

Sharmin Akter

Chest radiography is climacteric in identifying different pulmonary diseases, yet radiologist workload and inefficiency can lead to misdiagnoses. Automatic, accurate, and efficient segmentation of lung from X-ray images of chest is paramount for early disease detection. This study develops a deep learning framework using a Pix2pix Generative Adversarial Netw

A. ud-Doula, J. O. Sundqvist, N. Narechania, D. Debnath

O-stars generally show clear signs of strong line-broadening (in addition to rotational broadening) in their photospheric absorption lines (typically referred to as 'macroturbulence'), believed to originate in a turbulent sub-surface zone associated with enhanced opacities due to recombination of iron-group elements (at T~ 150-200 kK). O-stars with detected

Wang Zhen, Dong Yunyun

Diffusion generative models are currently the most popular generative models. However, their underlying modeling process is quite complex, and starting directly with the seminal paper Denoising Diffusion Probability Model (DDPM) can be challenging. This paper aims to assist readers in building a foundational understanding of generative models by tracing the

Yixuan Liang, Yuncong Liu, Neng Wang, Hongyang Yang

Financial sentiment analysis is crucial for understanding the influence of news on stock prices. Recently, large language models (LLMs) have been widely adopted for this purpose due to their advanced text analysis capabilities. However, these models often only consider the news content itself, ignoring its dissemination, which hampers accurate prediction of

Jia Hu, Xuerun Yan, Tian Xu, Haoran Wang

Reinforcement Learning (RL) offers a promising solution to enable evolutionary automated driving. However, the conventional RL method is always concerned with risk performance. The updated policy may not obtain a performance enhancement, even leading to performance deterioration. To address this challenge, this research proposes a High Confidence Policy Impr

Ru Geng, Yixian Gao, Jian Zu, Hong-Kun Zhang

A deep understanding of the intricate interactions between particles within a system is a key approach to revealing the essential characteristics of the system, whether it is an in-depth analysis of molecular properties in the field of chemistry or the design of new materials for specific performance requirements in materials science. To this end, we propose

HyunJoong Kim, Jip Kim

To maintain frequency stability in decarbonized power systems, inertia services from synchronous generators (SGs) and inverter-based resources must be procured. However, designing an inertia-aware system operation poses significant challenges in considering the variability and uncertainty of renewable energy sources (RES) and adopting a remuneration method f

Shivani Kumawat, Chandan Kumar Vishwakarma, Mohd Zeeshan, Indranil Mal

Two-dimensional (2D) Janus materials hold a great importance in spintronic and valleytronic applications due to their unique lattice structures and emergent properties. They intrinsically exhibit both an in-plane inversion and out-of-plane mirror symmetry breakings, which offer a new degree of freedom to electrons in the material. One of the main limitations

Yanan Zhang, Dajun Su, Zhaoyang Shan, Yunshu Shi

LaNiGa2 is a time-reversal symmetry breaking superconductor with symmetry protected band crossings, making it an ideal platform for investigating the interplay between unconventional superconductivity and electronic structure topology. Here we present a transport study of LaNiGa2 under pressure. The application of pressure to LaNiGa2 induces a significant en

Sida Huang, Hongyuan Zhang, Xuelong Li

With the advancement of pre-trained vision-language (VL) models, enhancing the alignment between visual and linguistic modalities in downstream tasks has emerged as a critical challenge. Different from existing fine-tuning methods that add extra modules to these two modalities, we investigate whether the frozen model can be fine-tuned by customized noise. Ou

Lei Bi, Michael Fulham, Jinman Kim

Automatic skin lesion segmentation methods based on fully convolutional networks (FCNs) are regarded as the state-of-the-art for accuracy. When there are, however, insufficient training data to cover all the variations in skin lesions, where lesions from different patients may have major differences in size/shape/texture, these methods failed to segment the

Chao Min, Yadan Ding

We study the Hankel determinant and orthogonal polynomials with respect to the two-parameter weight function $$ w(x)=w(x;t_1, t_2):=\exp(-x^6-t_2 x^4-t_1 x^2),\qquad x\in\mathbb{R}, $$ with $t_1,\; t_2 \in \mathbb{R}$. This problem arises from the matrix model in 2D quantum gravity investigated by Fokas, Its and Kitaev [Commun. Math. Phys. \textbf{142} (1991

Jia Hu, Zhexi Lian, Haoran Wang, Zihan Zhang

Adaptive Cruise Control (ACC) systems have been widely commercialized in recent years. However, existing ACC systems remain vulnerable to close-range cut-ins, a behavior that resembles "road bullying". To address this issue, this research proposes an Anti-bullying Adaptive Cruise Control (AACC) approach, which is capable of proactively protecting right-of-wa

Yongchao Ye, Xinting Zhu, Xuejin Shen, Xiaoyu Chen

As Earth's orbital satellite population grows exponentially, effective space situational awareness becomes critical for collision prevention and sustainable operations. Current approaches to monitor satellite behaviors rely on expert knowledge and rule-based systems that scale poorly. Among essential monitoring tasks, satellite pattern-of-life (PoL) identifi

Sergei Masaev

The production system (multidimensional object) is considered as a dynamic system with discrete time. Formalized: space (state of the object, control actions, goals, observed values, analytical estimates). Analytical estimates of the state of a dynamic system are formed through the autocorrelation function. The autocorrelation function is calculated with the

Oscar Agudelo, Bernhard Ruf, Carlos Velez

We study the {\it Hamiltonian elliptic system} \begin{eqnarray}\label{HS1-abstract} \left\{ \begin{aligned} -\Delta u & = \lambda |v|^{r-1}v +|v|^{p-1}v \qquad &\hbox{in} \ \ \Omega ,\\ -\Delta v & = \mu |u|^{s-1}u +|u|^{q-1}u \qquad &\hbox{in} \ \ \Omega ,\\ u &>0, \ v>0 \qquad \, &\hbox{in} \ \ \Omega ,\\ u &=v = 0 \qquad \quad &\hbox{on} \quad \partial \O

Sergei Masaev

The activity of a special economic zone is defined by a dynamic equation, taking into account the individual strategies of residents. At a given point in time, in respect to the resident enterprise of a special economic zone, a regime is introduced that limits the flow of resources by 80% (sanctions), forming an integral indicator for a comprehensive assessm

Lior Bar-Hillel, Yonatan Plotnik, Ohad Segal, Mordechai Segev

We predict the existence of surface plasmons polaritons at the interface between a metal and a periodically modulated dielectric medium, and find an unusual multi-branched dispersion curve of surface and bulk modes. The branches are separated by momentum gaps indicating intense amplification of modes, and display high and low group velocity ranging from zero

Yang Song, Liang Zhao, Shoudong Huang

Inconsistency issue is one crucial challenge for the performance of extended Kalman filter (EKF) based methods for state estimation problems, which is mainly affected by the discrepancy of observability between the EKF model and the underlying dynamic system. In this work, some sufficient and necessary conditions for observability maintenance are first prove

Lubomíra Regeciová, Konrad Jerzy Kapcia

The model of localized fermions on the triangular lattice is analyzed in means of the Monte Carlo simulations in the grand canonical ensemble. The Hamiltonian of the system has a form of the extended Hubbard model (at the atomic limit) with nearest-neighbor Ising-like magnetic $J$ interactions and onsite Coulomb $U$ interactions. The model is investigated fo

Yuyang Zhang, Kangjie Chen, Jiaxin Gao, Ronghao Cui

Recently, applications powered by Large Language Models (LLMs) have made significant strides in tackling complex tasks. By harnessing the advanced reasoning capabilities and extensive knowledge embedded in LLMs, these applications can generate detailed action plans that are subsequently executed by external tools. Furthermore, the integration of retrieval-au

T R Govindarajan

A novel proposal is made to account for the dark matter component of the Universe. Ultralight dark matter with mass $\leq {\cal{O}}(10^{-22})~eV$ is one of the strong candidates for the missing mass which aids the formation of galaxies as well as holding them together. They are also known as fuzzy dark matter(FDM) which will come under Cold Dark matter. The

Poulami Ghosh, Raj Dabre, Pushpak Bhattacharyya

Pre-trained language models (PLMs) are known to be susceptible to perturbations to the input text, but existing works do not explicitly focus on linguistically grounded attacks, which are subtle and more prevalent in nature. In this paper, we study whether PLMs are agnostic to linguistically grounded attacks or not. To this end, we offer the first study addr

Yuan Tian, Shuo Wang, Guangtao Zhai

Face de-identification (DeID) has been widely studied for common scenes, but remains under-researched for medical scenes, mostly due to the lack of large-scale patient face datasets. In this paper, we release MeMa, consisting of over 40,000 photo-realistic patient faces. MeMa is re-generated from massive real patient photos. By carefully modulating the gener

Zeyu Zhang, Jianxun Lian, Chen Ma, Yaning Qu

Trending topics have become a significant part of modern social media, attracting users to participate in discussions of breaking events. However, they also bring in a new channel for poisoning attacks, resulting in negative impacts on society. Therefore, it is urgent to study this critical problem and develop effective strategies for defense. In this paper,

BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson

We report an improved study of the semileptonic decay $D^0 \rightarrow \bar{K}^0\pi^-e^+\nu_{e}$ based on a sample of $7.9~\mathrm{fb}^{-1}$ of $e^+e^-$ annihilation data collected at a center-of-mass energy of 3.773~GeV with the BESIII detector at the BEPCII collider. The branching fraction of this decay is measured to be $\mathcal{B}(D^0\rightarrow \bar{K}

Ben De Bondt, Andreas Thom

We study isomorphisms between metric reduced products of symmetric groups with the normalized Hamming metric assuming the open coloring axiom $\mathsf{OCA}$ and Martin's axiom for $\sigma$-linked posets.

Nicola Cavallucci

We extend the classical Otal-Peign\'e's Theorem to the class of proper, Gromov-hyperbolic spaces that are line-convex. Namely, we prove that when a group acts discretely and virtually freely by isometries on a metric space in this class then its critical exponent equals the topological entropy of the geodesic flow of the quotient metric space. We also show e

Johan Ulander

We propose and analyse a boundary-preserving numerical scheme for the weak approximation for some stochastic partial differential equations (SPDEs) with bounded state-space. We impose regularity assumptions on the drift and diffusion coefficients only locally on the state-space. In particular, the drift and diffusion coefficients may be non-globally Lipschit

Yufei Wu, Yixuan Even Xu, Xuming Zhang, Duo Liu

Community engagement plays a critical role in anti-poaching efforts, yet existing mathematical models aimed at enhancing this engagement often overlook direct participation by community members as alternative patrollers. Unlike professional rangers, community members typically lack flexibility and experience, resulting in new challenges in optimizing patrol

Kefan Su, Yusen Huo, Zhilin Zhang, Shuai Dou

Decision-making in large-scale games is an essential research area in artificial intelligence (AI) with significant real-world impact. However, the limited access to realistic large-scale game environments has hindered research progress in this area. In this paper, we present AuctionNet, a benchmark for bid decision-making in large-scale ad auctions derived

Linda Hoyer

Let $n$ be a positive integer and $q$ be a power of an odd prime. We provide explicit formulas for calculating the orthogonal determinants $\det(\chi)$, where $\chi \in \mathrm{Irr}(\mathrm{GL}_n(q))$ is an orthogonal character of even degree. Moreover, we show that $\det(\chi)$ is "odd". This confirms a special case of a conjecture by Richard Parker.

Dáire Healy, Jonathan A. Tawn, Peter Thorne, Andrew Parnell

We analyse extreme daily minimum temperatures in winter months over the island of Ireland from 1950-2022. We model the marginal distributions of extreme winter minima using a generalised Pareto distribution (GPD), capturing temporal and spatial non-stationarities in the parameters of the GPD. We investigate two independent temporal non-stationarities in extr

M. Yazdani-Kachoei, B. Rabihavi, I. E. Brumboiu, S. Mehdi Vaez Allaei

While the effect of intrinsic defects on the electronic properties of half-Heusler compounds has been extensively discussed in literature, their effect on the lattice vibrations has received much less attention, due to the prohibitive computational demands. This may lead to an erroneous description of the lattice thermal conductivity, which plays a crucial r

Ulisse Munari

We propose that the drastic photometric and spectroscopic changes affecting the symbiotic star V694 Mon since 2018, are due to its transition from the accreting-only state to steady hydrogen-burning on the surface of the white dwarf, closely mimicking the pattern followed by V4368 Sgr. The phase of peak optical brightness and weakest emission lines has proba

Sertac Kilickaya, Mete Ahishali, Cansu Celebioglu, Fahad Sohrab

The frequent breakdowns and malfunctions of industrial equipment have driven increasing interest in utilizing cost-effective and easy-to-deploy sensors, such as microphones, for effective condition monitoring of machinery. Microphones offer a low-cost alternative to widely used condition monitoring sensors with their high bandwidth and capability to detect s

Matias Quiroz, Laleh Tafakori, Hans Manner

We investigate methods for forecasting multivariate realized covariances matrices applied to a set of 30 assets that were included in the DJ30 index at some point, including two novel methods that use existing (univariate) log of realized variance models that account for attenuation bias and time-varying parameters. We consider the implications of some model

Klaudiusz Czudek

It has been shown that in one dimension the environment viewed by the particle process (EVP process) in quasi periodic random environment is uniquely ergodic and mixing under mild additional assumptions. Here we construct an analytic quasi periodic environment on higher dimensional torus such that the EVP process is not uniquely ergodic. The stationary measu

Yichun Yang, Rong-Hua Li, Meihao Liao, Longlong Lin

Graph propagation (GP) computation plays a crucial role in graph data analysis, supporting various applications such as graph node similarity queries, graph node ranking, graph clustering, and graph neural networks. Existing methods, mainly relying on power iteration or push computation frameworks, often face challenges with slow convergence rates when appli

Animesh Sharma, Amita Das, G Ravindra Kumar

A new mechanism of enhanced laser energy absorption in plasma microglobules is demonstrated with the help of two-dimensional Particle-In-Cell (PIC) simulations. The mechanism relies on the excitation of surface and bulk waves and the occurrence of repeated collisions in the confines of the finite-sized microglobular target. The episodic increase in the avera

Jiarui Jin, Xianyu Chen, Weinan Zhang, Yong Yu

A fundamental technique of recommender systems involves modeling user preferences, where queries and items are widely used as symbolic representations of user interests. Queries delineate user needs at an abstract level, providing a high-level description, whereas items operate on a more specific and concrete level, representing the granular facets of user p

Jen-Yuan Huang

Diffusion Probabilistic Models (DPMs) have demonstrated exceptional capability of generating high-quality and diverse images, but their practical application is hindered by the intensive computational cost during inference. The DPM generation process requires solving a Probability-Flow Ordinary Differential Equation (PF-ODE), which involves discretizing the

Pin-Yen Chiu, Dai-Jie Wu, Po-Hsun Chu, Chia-Hsuan Hsu

Kinship face synthesis is a challenging problem due to the scarcity and low quality of the available kinship data. Existing methods often struggle to generate descendants with both high diversity and fidelity while precisely controlling facial attributes such as age and gender. To address these issues, we propose the Style Latent Diffusion Transformer (Style

Jugal Rakesh Shah, Max Huisman, Devendra Deshmukh, Dag Hanstorp

Small droplets are irradiated with visible and infrared light in many natural and industrial environments. One of the simplest ways to describe their evaporation is the D$^2$-Law. It states that the evaporation rate is proportional to $t^{-1/2}$, and $R^{-1}$. However, models like the D$^2$-Law do not account for the volumetric heating of light and the effec

Zhengcong Fei, Di Qiu, Debang Li, Changqian Yu

This paper investigates a solution for enabling in-context capabilities of video diffusion transformers, with minimal tuning required for activation. Specifically, we propose a simple pipeline to leverage in-context generation: ($\textbf{i}$) concatenate videos along spacial or time dimension, ($\textbf{ii}$) jointly caption multi-scene video clips from one

Nilo Schwencke, Cyril Furtlehner

In the recent years, Physics Informed Neural Networks (PINNs) have received strong interest as a method to solve PDE driven systems, in particular for data assimilation purpose. This method is still in its infancy, with many shortcomings and failures that remain not properly understood. In this paper we propose a natural gradient approach to PINNs which cont

Ann Nedime Nese Rende, Tolga Yilmaz, Özgür Ulusoy

To observe how individual behavior shapes a larger community's actions, agent-based modeling and simulation (ABMS) has been widely adopted by researchers in social sciences, economics, and epidemiology. While simulations can be run on general-purpose ABMS frameworks, these tools are not specifically designed for social networks and, therefore, provide limite

Mattia Fanan, Davide Dalle Pezze, Emad Efatinasab, Ruggero Carli

Behavior-based Driver Identification is an emerging technology that recognizes drivers based on their unique driving behaviors, offering important applications such as vehicle theft prevention and personalized driving experiences. However, most studies fail to account for the real-world challenges of deploying Deep Learning models within vehicles. These chal

Prabhakar Palni, Amal Sarkar, Santosh K. Das, Anuraag Rathore

The second Hot QCD Matter 2024 conference at IIT Mandi focused on various ongoing topics in high-energy heavy-ion collisions, encompassing theoretical and experimental perspectives. This proceedings volume includes 19 contributions that collectively explore diverse aspects of the bulk properties of hot QCD matter. The topics encompass the dynamics of electro

Xin Liu, Yaran Chen, Haoran Li

Current advanced policy learning methodologies have demonstrated the ability to develop expert-level strategies when provided enough information. However, their requirements, including task-specific rewards, action-labeled expert trajectories, and huge environmental interactions, can be expensive or even unavailable in many scenarios. In contrast, humans can

Yan-Rong Li, Jian-Min Wang

The reverberation mapping (RM) technique has seen wide applications in probing geometry and kinematics of broad-line regions (BLRs) and measuring masses of supermassive black holes (SMBHs) in active galactic nuclei. However, the key quantities in RM analysis like emissivity, responsivity, transfer functions, and mean and root-mean-square (RMS) spectra are fr

Yucong Meng, Zhiwei Yang, Yonghong Shi, Zhijian Song

The accelerated MRI reconstruction process presents a challenging ill-posed inverse problem due to the extensive under-sampling in k-space. Recently, Vision Transformers (ViTs) have become the mainstream for this task, demonstrating substantial performance improvements. However, there are still three significant issues remain unaddressed: (1) ViTs struggle t

Man Jia, Wei Li, Su-Yan Pei, Xin-Yao Du

In this paper, we solve the complete Salpeter equation and use the obtained relativistic wave function to calculate the strong and radiative electromagnetic decays of the ${D^*}$ meson. { We obtain the results $\Gamma(D^{*}(2007)^{0}\to D^{0}\pi^{0})=34.6~\rm{keV}$ and $\Gamma(D^{*}(2007)^{0}\rightarrow D^{0}\gamma)=19.4~\rm{keV}$, and the estimated full wid

Abdullah Al Mamun, Abdul Hasib, Abu Salyh Muhammad Mussa, Rakib Hossen

Due to more population congestion and car ownership, the provision of parking spaces for vehicles is becoming a crucial factor. This paper aims to present a novel Internet of Things (IoT)--based smart car parking system that can effectively manage these problems with the help of sensor technology and automation. Infrared (IR) sensors, DHT22 sensors, MQ-2 gas

Ziqi Zhao, Peijia Xie, Max Q. -H. Meng

Wheeled robots are highly efficient in human living environments. However, conventional wheeled designs, limited by degrees of freedom, struggle to meet varying footprint needs and achieve omnidirectional mobility. This paper proposes a novel robot drive model inspired by human movements, termed as the Omni Differential Drive (ODD). The ODD model innovativel

Xuan Mao, Yuxiang Li

This paper is concerned with a three-component chemotaxis model accounting for indirect signal production,reading as $u_t = \nabla\cdot(\nabla u - u\nabla v)$,$v_t = \Delta v - v + w$ and $0 = \Delta w - w + u$,posed in a ball of $\mathbb R^n$ with $n\geq5$,subject to homogeneous Neumann boundary conditions.The system is a Nagai-type variant of its fully par

Ashutosh Tripathi, Alok C. Gupta, Krista Lynne Smith, Paul J. Wiita

We examine lengthy radio light curves of the flat spectrum radio galaxy 3C 454.3 for possible quasi-periodic oscillations (QPOs). The data used in this work were collected at five radio frequencies, 4.8, 8.0, 14.5, 22.0, and 37.0 GHz between 1979--2013 as observed at the University of Michigan Radio Astronomical Observatory, Crimean Astrophysical Observatory

Qiyu Liu, Siyuan Han, Jianwei Liao, Jin Li

Compressing integer keys is a fundamental operation among multiple communities, such as database management (DB), information retrieval (IR), and high-performance computing (HPC). Recent advances in \emph{learned indexes} have inspired the development of \emph{learned compressors}, which leverage simple yet compact machine learning (ML) models to compress la

Alexis L. Quintana

Low-density and unbound stellar groups, OB associations have been historically delineated through their bright and massive members. They have been analysed for decades, but the arrival of Hipparcos, and more recently of Gaia led to a change of paradigm by allowing the identification of more reliable members using parallaxes and proper motions. This renewed i

Saksham Singh Kushwaha, Yapeng Tian

Recent advances in audio generation have focused on text-to-audio (T2A) and video-to-audio (V2A) tasks. However, T2A or V2A methods cannot generate holistic sounds (onscreen and off-screen). This is because T2A cannot generate sounds aligning with onscreen objects, while V2A cannot generate semantically complete (offscreen sounds missing). In this work, we a

Zeinab Dehghan, Manfried Faber

Color confinement is a fundamental phenomenon in quantum chromodynamics. In this work, the mechanisms underlying color confinement are investigated in detail, with a particular focus on the role of non-perturbative phenomena such as center vortices and monopoles in the QCD vacuum. By exploring lattice QCD approaches, including the Maximal Center Gauge and ce

Karan Dogra, Alok C. Gupta, C. M. Raiteri, M. Villata

Due to its peculiar and highly variable nature, the blazar 3C 454.3 has been extensively monitored by the WEBT team. Here, we present for the first time these long-term optical flux and color variability results using data acquired in B, V, R, and I bands over a time span of $\sim$ 2 decades. We include data from WEBT collaborators and public archives such a

Jurica Runtas, Tomislav Petkovic

Deep neural networks (DNNs) are a contemporary solution for semantic segmentation and are usually trained to operate on a predefined closed set of classes. In open-set environments, it is possible to encounter semantically unknown objects or anomalies. Road driving is an example of such an environment in which, from a safety standpoint, it is important to en

Matthias Aschenbrenner, Lou van den Dries, Joris van der Hoeven

We study relative differential closure in the context of Hardy fields. Using our earlier work on algebraic differential equations over Hardy fields, this leads to a proof of a conjecture of Boshernitzan (1981): the intersection of all maximal analytic Hardy fields agrees with that of all maximal Hardy fields. We also generalize a key ingredient in the proof,

Jiayi Guo, Irene Martínez, Gonçalo Correia, Bart van Arem

Bathtub models are used to study urban traffic within a certain area. They do not require to take into account the detailed network topology. The emergence of different bathtub models has raised the question of which model can provide more robust and accurate results under different demand scenarios and network properties. This paper presents a comparative s

Chengze Du, Zhiwei Yu, Xiangyu Wang

Network tomography plays a crucial role in assessing the operational status of internal links within networks through end-to-end path-level measurements, independently of cooperation from the network infrastructure. However, the accuracy of performance inference in internal network links heavily relies on comprehensive end-to-end path performance data. Most

Yang Yang, Wenjuan Xi, Luping Zhou, Jinhui Tang

Vision-language retrieval aims to search for similar instances in one modality based on queries from another modality. The primary objective is to learn cross-modal matching representations in a latent common space. Actually, the assumption underlying cross-modal matching is modal balance, where each modality contains sufficient information to represent the

Andre Berger, Arman Rouhani, Marc Schröder

This paper studies a scheduling problem in a parallel machine setting, where each machine must adhere to a predetermined fixed order for processing the jobs. Given $n$ jobs, each with processing times and deadlines, we aim to minimize the number of machines while ensuring deadlines are met and the fixed order is maintained. We show that the first-fit algorit

Yu Rong, Hong-Xin Zhang, Cheng Cheng, Qi Guo

By analyzing data from DESI Legacy Imaging Survey of the dwarf galaxies in the Arecibo Legacy Fast Alfa Survey, we have identified five ultra-diffuse galaxies (UDGs) featuring central pseudo-bulges. These UDGs display blue pseudo-bulges with S\'ersic indices $n<2.5$ and effective radii spanning 300-700 pc, along with bluer thin stellar disks exhibiting low s

Kaito Tanaka, Benjamin Tan, Brian Wong

Vision-Language Models (VLMs) have emerged as key enablers for multimodal tasks, but their reliance on separate visual encoders introduces challenges in efficiency, scalability, and modality alignment. To address these limitations, we propose MUDAIF (Multimodal Unified Decoder with Adaptive Input Fusion), a decoder-only vision-language model that seamlessly

Srilagna Sahoo, Abin Varghese, Aniket Sadashiva, Mayank Goyal

Neuromorphic in-memory computing requires area-efficient architecture for seamless and low latency parallel processing of large volumes of data. Here, we report a compact, vertically integrated/stratified field-effect transistor (VSFET) consisting of a 2D non-ferroelectric MoS$_2$ FET channel stacked on a 2D ferroelectric In$_2$Se$_3$ FET channel. Electrosta

Nethmi S. Hewawiththi, M. Mahesha Viduranga, Vanodhya G. Warnasooriya, Tharindu Fernando

Unmanned aerial vehicle-assisted disaster recovery missions have been promoted recently due to their reliability and flexibility. Machine learning algorithms running onboard significantly enhance the utility of UAVs by enabling real-time data processing and efficient decision-making, despite being in a resource-constrained environment. However, the limited b

Mohit Yadav, Tapomoy Guha Sarkar

We propose the HI 21-cm power spectrum from the post-reionization epoch as a probe of a cosmological model with decaying dark matter particles. The unstable particles are assumed to undergo a 2-body decay into a massless and massive daughter. We assume that a fraction $f$ of the total dark matter budget to be unstable and quantify the decay using the life ti

Hanwei Fan, Ya Wang, Sicheng Li, Tingyuan Liang

With the continuous advancement of processors, modern micro-architecture designs have become increasingly complex. The vast design space presents significant challenges for human designers, making design space exploration (DSE) algorithms a significant tool for $\mu$-arch design. In recent years, efforts have been made in the development of DSE algorithms, a

Kwangmin Lee, Sewon Park, Seongmin Kim, Jaeyong Lee

We study Bayesian inference in the spiked covariance model, where a small number of spiked eigenvalues dominate the spectrum. Our goal is to infer the spiked eigenvalues, their corresponding eigenvectors, and the number of spikes, providing a Bayesian solution to principal component analysis with uncertainty quantification. We place an inverse-Wishart prior

Wenwen Zuo, Alok C. Gupta, Minfeng Gu, Mauri J. Valtonen

Using nearly simultaneous radio, near-infrared, optical, and ultraviolet data collected since 2009, we constructed 106 spectral energy distributions (SEDs) of the blazar OJ 287. These SEDs were well-fitted by a log-parabolic model. By classifying the data into `flare' and `quiescent' segments, we found that the median flux at peak frequency of the SEDs durin