April 2024 arXiv papers — page 65

Minoru Hirose, Shingo Saito

It is known that the set of all nonnegative integers may be equipped with a total order that is chaotic in the sense that there is no monotone three-term arithmetic progressions. Such chaotic order must be so complicated that the resulting ordered set cannot be order isomorphic to the set of all nonnegative integers or the set of all integers with the standa

Xinxin Jiao, Liejun Wang, Yinfeng Yu

Speech emotion recognition is crucial in human-computer interaction, but extracting and using emotional cues from audio poses challenges. This paper introduces MFHCA, a novel method for Speech Emotion Recognition using Multi-Spatial Fusion and Hierarchical Cooperative Attention on spectrograms and raw audio. We employ the Multi-Spatial Fusion module (MF) to

Paweł Goldstein, Zofia Grochulska, Piotr Hajłasz

Cerf and Palais independently proved a remarkable result about extending diffeomorphisms defined on smooth balls in a manifold to global diffeomorphisms of the manifold onto itself. We explain Palais' argument and show how to extend it to the class of homeomorphisms and bi-Lipschitz homeomorphisms. While Palais' argument is surprising, it is elementary and s

Yaokun Su, Chen Li

The study of phonon dynamics is pivotal for understanding material properties, yet it faces challenges due to the irreversible information loss inherent in powder inelastic neutron scattering spectra and the limitations of traditional analysis methods. In this study, we present a machine learning framework designed to reveal obscured phonon dynamics from pow

Charith Chandra Sai Balne, Sreyoshi Bhaduri, Tamoghna Roy, Vinija Jain

The rise of deep learning has marked significant progress in fields such as computer vision, natural language processing, and medical imaging, primarily through the adaptation of pre-trained models for specific tasks. Traditional fine-tuning methods, involving adjustments to all parameters, face challenges due to high computational and memory demands. This h

Gensheng Pei, Yazhou Yao, Jianbo Jiao, Wenguan Wang

Conventional video object segmentation (VOS) methods usually necessitate a substantial volume of pixel-level annotated video data for fully supervised learning. In this paper, we present HVC, a \textbf{h}ybrid static-dynamic \textbf{v}isual \textbf{c}orrespondence framework for self-supervised VOS. HVC extracts pseudo-dynamic signals from static images, enab

Zachary Slepian, Jessica Chellino, Jiamin Hou

Recently isotropic basis functions of $N$ unit vector arguments were presented; these are of significant use in measuring the N-Point Correlation Functions (NPCFs) of galaxy clustering. Here we develop the generating function for these basis functions -- $i.e.$ that function which, expanded in a power series, has as its angular part the isotropic functions.

Tao Feng, Lizhen Qu, Zhuang Li, Haolan Zhan

Machine learning models have made incredible progress, but they still struggle when applied to examples from unseen domains. This study focuses on a specific problem of domain generalization, where a model is trained on one source domain and tested on multiple target domains that are unseen during training. We propose IMO: Invariant features Masks for Out-of

Lunjia Hu, Yifan Wu

Calibration allows predictions to be reliably interpreted as probabilities by decision makers. We propose a decision-theoretic calibration error, the Calibration Decision Loss (CDL), defined as the maximum improvement in decision payoff obtained by calibrating the predictions, where the maximum is over all payoff-bounded decision tasks. Vanishing CDL guarant

Shivam Nadimpalli, Shyamal Patel

We give a non-adaptive algorithm that makes $2^{\tilde{O}(\sqrt{k\log(1/\varepsilon_2 - \varepsilon_1)})}$ queries to a Boolean function $f:\{\pm 1\}^n \rightarrow \{\pm 1\}$ and distinguishes between $f$ being $\varepsilon_1$-close to some $k$-junta versus $\varepsilon_2$-far from every $k$-junta. At the heart of our algorithm is a local mean estimation pro

Zeyu Zhang, Xiaohe Bo, Chen Ma, Rui Li

Large language model (LLM) based agents have recently attracted much attention from the research and industry communities. Compared with original LLMs, LLM-based agents are featured in their self-evolving capability, which is the basis for solving real-world problems that need long-term and complex agent-environment interactions. The key component to support

Deddy Jobson, Eddy Hudson

Regression is typically treated as a curve-fitting process where the goal is to fit a prediction function to data. With the help of conditional generative adversarial networks, we propose to solve this age-old problem in a different way; we aim to learn a prediction function whose outputs, when paired with the corresponding inputs, are indistinguishable from

James R. Heselden, Gautham P. Das

Mapping is a time-consuming process for deploying robotic systems to new environments. The handling of maps is also risk-adverse when not managed effectively. We propose here, a standardised approach to handling such maps in a manner which focuses on the information contained wherein such as global location, object positions, topology, and occupancy. As part

Yiqing Shen, Outongyi Lv, Houying Zhu, Yu Guang Wang

Large language models (LLMs) have garnered considerable attention for their proficiency in tackling intricate tasks, particularly leveraging their capacities for zero-shot and in-context learning. However, their utility has been predominantly restricted to general tasks due to an absence of domain-specific knowledge. This constraint becomes particularly pert

Osmer Suárez-López, Andrés S. Villares, Wladimir E. Banda-Barragán

Galactic superbubbles are triggered by stellar feedback in the discs of star-forming galaxies. They are important in launching galactic winds, which play a key role in regulating the mass and energy exchange in galaxies. Observations can only reveal projected information and the 3D structure of such winds is quite complex. Therefore, numerical simulations ar

Sagarika Menon, Peter Moeck

The computer program "Histropy" is an interactive Python program for the quantification of selected features of two-dimensional (2D) images/patterns (in either JPG/JPEG, PNG, GIF, BMP, or baseline TIF/TIFF formats) using calculations based on the pixel intensities in this data, their histograms, and user-selected sections of those histograms. The histograms

Enze Jiang, Jishen Peng, Zheng Ma, Xiong-Bin Yan

In recent years we have witnessed a growth in mathematics for deep learning, which has been used to solve inverse problems of partial differential equations (PDEs). However, most deep learning-based inversion methods either require paired data or necessitate retraining neural networks for modifications in the conditions of the inverse problem, significantly

Ziad Ghanem, Casey Crane, Jingzhou Liu

In this paper, we prove a global bifurcation result for the existence of non-radial branches of solutions to the paramterized family of $\Gamma$-symmetric problems $-\Delta u=f(\alpha,z,u)$, $u|_{\partial D}=0$ on the unit disc $D:=\{z\in \mathbb{C} : |z|<1\}$ with $u(z)\in \mathbb{R}^k$, where $\mathbb{R}^k$ is an orthogonal $\Gamma$-representation, $f: \ma

Yazan H. Al-Badarneh, Mustafa K. Alshawaqfeh, Osamah S. Badarneh, Yazid M. Khattabi

We propose a reconfigurable intelligent surface (RIS)-assisted underlay spectrum sharing system, in which a RIS-assisted secondary network shares the spectrum licensed for a primary network. The secondary network consists of a secondary source (SS), an RIS, and a secondary destination (SD), operating in a Rician fading environment. We study the performance o

Qixuan Zhang, Zhifeng Wang, Yang Liu, Zhenyue Qin

In this paper, we present a novel benchmark for Emotion Recognition using facial landmarks extracted from realistic news videos. Traditional methods relying on RGB images are resource-intensive, whereas our approach with Facial Landmark Emotion Recognition (FLER) offers a simplified yet effective alternative. By leveraging Graph Neural Networks (GNNs) to ana

Zheng Wang, Shi-Hao Li, Kang-Ya Lu, Jian-Qing Sun

In this paper, we plan to show an eigenvalue algorithm for block Hessenberg matrices by using the idea of non-commutative integrable systems and matrix-valued orthogonal polynomials. We introduce adjacent families of matrix-valued $\theta$-deformed bi-orthogonal polynomials, and derive corresponding discrete non-commutative hungry Toda lattice from discrete

Romain Lacombe, Neal Vaidya

Recent advances in fast sampling methods for diffusion models have demonstrated significant potential to accelerate generation on image modalities. We apply these methods to 3-dimensional molecular conformations by building on the recently introduced GeoLDM equivariant latent diffusion model (Xu et al., 2023). We evaluate trade-offs between speed gains and q

Rahul Roy, Masato Takei, Hideki Tanemura

We show that two independent elephant random walks on the integer lattice $\mathbb{Z}$ meet each other finitely often or infinitely often depends on whether the memory parameter $p$ is strictly larger than $3/4$ or not. Asymptotic results for the distance between them are also obtained.

Leonid Mytnik, Johanna Weinberger

We consider the one-dimensional stochastic differential equation \begin{equation*} X_t = x_0 + L_t + \int_0^t μ(X_s)ds, \quad t \geq 0, \end{equation*} where $μ$ is a finite measure of Kato class $K_η$ with $η\in (0,α-1]$ and $(L_t)_{t \geq 0}$ is a symmetric $α$-stable process with $α\in (1,2)$. We derive weak and strong well posedness for this equation whe

Masafumi Udagawa, Hiroki Nakai, Chisa Hotta

Pinch point is a spectral discontinuity found in the neutron diffraction image of spin ice. Similar spectral singularity is commonly observed in a broad range of systems that have a close connection with flat bands. We focus on the electron flat band and its two topologically distinct classes of wavefunction: the compact localized state (CLS), and the non-co

Justus Isaiah Hibshman, Adnan Hoq, Tim Weninger

Real-world data is typically a noisy manifestation of a core pattern (schema), and the purpose of data mining algorithms is to uncover that pattern, thereby splitting (i.e. decomposing) the data into schema and noise. We introduce SCHENO, a principled evaluation metric for the goodness of a schema-noise decomposition of a graph. SCHENO captures how schematic

Jianwei Zhang

Motivated by multi-domain service function chain (SFC) orchestration, we define the shortest-longest path (SLP) problem, prove its hardness, and design an efficient fully polynomial time approximation scheme (FPTAS) using the dynamic programming (DP) and scaling and rounding (SR) techniques to compute an approximation solution with provable performance guara

Peter Schaumann, Martin Rempel, Ulrich Blahak, Volker Schmidt

Many post-processing methods improve forecasts at individual locations but remove their correlation structure, which is crucial for predicting larger-scale events like total precipitation amount over areas such as river catchments that are relevant for weather warnings and flood predictions. We propose a method to reintroduce spatial correlation into a post-

Jaehyun Koo

We present an $O(1)$-round fully-scalable deterministic massively parallel algorithm for computing the min-plus matrix multiplication of unit-Monge matrices. We use this to derive a $O(\log n)$-round fully-scalable massively parallel algorithm for solving the exact longest increasing subsequence (LIS) problem. For a fully-scalable MPC regime, this result sub

Jingbo Wang, Harshal D. Kaushik, Jie Zhang

The adoption of electric vehicles (EVs) represents a critical shift in personal mobility, fueled by policy support and advancements in automotive technology. However, the expansion of EVs for long-distance travel is hindered by charging time concerns, the sparse distribution of charging stations, and the worsening waiting times due to congestion. The main ob

Guillaume Bal, Jiming Yu

Atmospheric and oceanic mass transport near the equator display a well-studied asymmetry characterized by two modes moving eastward. This asymmetric edge transport is characteristic of interfaces separating two-dimensional topological insulators. The northern and southern hemispheres are insulating because of the presence of a Coriolis force parameter that v

Abhinau K. Venkataramanan, Cosmin Stejerean, Ioannis Katsavounidis, Hassene Tmar

The deep learning revolution has strongly impacted low-level image processing tasks such as style/domain transfer, enhancement/restoration, and visual quality assessments. Despite often being treated separately, the aforementioned tasks share a common theme of understanding, editing, or enhancing the appearance of input images without modifying the underlyin

Hajer Ben Amor, Noureddine Ghiloufi

In this paper, we introduce new spaces of holomorphic functions on the unit ball $\mathbb{B}_{n}$ of $\mathbb{C}^{n}$ generalizing the classical Bergman spaces. The main results include the properties of some operators and integrals representations such as Bergman-type projections, and Berezin transform.

Toai Luong, Steve Wise

Phase field crystal is a model used to describe the behavior of crystalline materials at the mesoscale. In this study, we investigate the well-posedness of a phase field crystal equation subject to a degenerate mobility $M(u)$ that equals zero for $u\leq 0$. First, we prove the existence of a weak solution to a phase field crystal equation with non-degenerat

Gayana Jayasinghe

We construct Witten instanton complexes for K\"ahler Hamiltonian Morse functions on stratified pseudomanifolds with wedge K\"ahler metrics satisfying a local conformally totally geodesic condition. We use this to extend Witten's holomorphic Morse inequalities for the $L^2$ cohomology of Dolbeault complexes, deriving versions for Poincar\'e Hodge polynomials,

Sergio Celani, Rafał Gruszczyński, Paula Menchón

Drawing on the classic paper by Chellas "Basic conditional logic" (1975), we propose a general algebraic framework for studying a binary operation of conditional that models universal features of the "if..., then..." connective as strictly related to the unary modal necessity operator. To this end, we introduce a variety of conditional algebras, and we devel

Haobo Yan, Chuan Liu, Liuming Liu, Yu Meng

Lattice QCD results for isospin $I=\frac{1}{2}$ $D\pi$ scattering are presented. Utilizing a series of $N_{\text{f}}=2+1$ Wilson-Clover ensembles with pion masses of $m_\pi \approx 132, 208, 305$ and $317$ MeV, various two-particle operators are constructed and the corresponding finite-volume spectra are determined. The $S$ and $P$-wave scattering phase shif

Ben Eisner, Yi Yang, Todor Davchev, Mel Vecerik

Many robot manipulation tasks can be framed as geometric reasoning tasks, where an agent must be able to precisely manipulate an object into a position that satisfies the task from a set of initial conditions. Often, task success is defined based on the relationship between two objects - for instance, hanging a mug on a rack. In such cases, the solution shou

Oğuzhan Canpolat, A. Giray Yağlıkçı, Ataberk Olgun, İsmail Emir Yüksel

RowHammer is a major read disturbance mechanism in DRAM where repeatedly accessing (hammering) a row of DRAM cells (DRAM row) induces bitflips in other physically nearby DRAM rows. RowHammer solutions perform preventive actions (e.g., refresh neighbor rows of the hammered row) that mitigate such bitflips to preserve memory isolation, a fundamental building b

Kleopatra Markou, Dimitrios Tomaras, Vana Kalogeraki, Dimitrios Gunopulos

The imminent need to interpret the output of a Machine Learning model with counterfactual (CF) explanations - via small perturbations to the input - has been notable in the research community. Although the variety of CF examples is important, the aspect of them being feasible at the same time, does not necessarily apply in their entirety. This work uses diff

Zhepeng Wang, Yi Sheng, Nirajan Koirala, Kanad Basu

Benefiting from cloud computing, today's early-stage quantum computers can be remotely accessed via the cloud services, known as Quantum-as-a-Service (QaaS). However, it poses a high risk of data leakage in quantum machine learning (QML). To run a QML model with QaaS, users need to locally compile their quantum circuits including the subcircuit of data encod

Junyao Shi, Jianing Qian, Yecheng Jason Ma, Dinesh Jayaraman

There have recently been large advances both in pre-training visual representations for robotic control and segmenting unknown category objects in general images. To leverage these for improved robot learning, we propose $\textbf{POCR}$, a new framework for building pre-trained object-centric representations for robotic control. Building on theories of "what

Maxim Prasolov

Lavrentiev curves form a special class of rectifiable curves which includes cusp-free piecewise smooth curves. We call a Lavrentiev curve Legendrian if the integral of the contact form equals zero on any its subarc. We define Legendrian isotopies of such curves and prove that the equivalence classes of Legendrian Lavrentiev links with respect to Legendrian i

Jizhao Zang, Haixin Liu, Travis C. Briles, Scott B. Papp

Soliton microcombs provide a chip-based, octave-spanning source for self-referencing and optical metrology. We explore use of a silicon-nitride integrated photonics foundry to manufacture octave-spanning microcombs. By group-velocity dispersion engineering with the waveguide cross-section, we shape the soliton spectrum for dispersive-wave spectral enhancemen

Huandong Chen, Jayakanth Ravichandran

A home-built compact system that functions as both a transfer stage for deterministic transfer processes and a mask aligner for contact photolithography, is constructed. The precision translation sample stage and optical microscope are shared between the two modes. In the transfer mode, assisted by either an adhesive or a heating element, the setup has been

Wenqi Jia, Sian Jin, Jinzhen Wang, Wei Niu

The rapid expansion of computational capabilities and the ever-growing scale of modern HPC systems present formidable challenges in managing exascale scientific data. Faced with such vast datasets, traditional lossless compression techniques prove insufficient in reducing data size to a manageable level while preserving all information intact. In response, r

J. S. Builes, Cristian F. Coletti, Leon A. Valencia

In this paper, we study an analytically tractable SIS model with a non-linear incidence rate for the number of infectious individuals described through a stochastic differential equation (SDE). We guarantee the existence of a positive solution, and we study its regularity. We study the persistence and extinction regimes, and we give sufficient conditions und

Ehud Shapiro

We present an architectural alternative to global digital platforms termed grassroots, designed to serve the social, economic, civic, and political needs of local digital communities, as well as their federation. Grassroots platforms may offer local communities an alternative to global digital platforms while operating solely on the smartphones of their memb

Jingyi Liu, Yi Man, John H. Costello, Eva Kanso

Ciliated microorganisms near the base of the aquatic food chain either swim to encounter prey or attach at a substrate and generate feeding currents to capture passing particles. Here, we represent attached and swimming ciliates using a popular spherical model in viscous fluid with slip surface velocity that afford analytical expressions of ciliary flows. We

Subhrangsu Saha, John E. Dolbow, Oscar Lopez-Pamies

With the fundamental objective of establishing the universality of the Griffith energy competition to describe the growth of large cracks in solids \emph{not} just under monotonic but under general loading conditions, this paper puts forth a generalization of the classical Griffith energy competition in nominally elastic brittle materials to arbitrary \emph{

Alexander Shan, John Bauer, Riley Carlson, Christopher Manning

The vast majority of the popular English named entity recognition (NER) datasets contain American or British English data, despite the existence of many global varieties of English. As such, it is unclear whether they generalize for analyzing use of English globally. To test this, we build a newswire dataset, the Worldwide English NER Dataset, to analyze NER

Kleice Silva, Ann Barcomb, Ronnie de Souza Santos

Background. Women bring unique problem-solving skills to software development, often favoring a holistic approach and attention to detail. In software testing, precision and attention to detail are essential as professionals explore system functionalities to identify defects. Recognizing the alignment between these skills and women's strengths can derive str

Maximilian W. Feil, Magdalena Weger, Hans Reisinger, Thomas Aichinger

Fully-processed SiC power metal-oxide-semiconductor field-effect transistors (MOSFETs) emit light during switching of the gate terminal, while both drain and source terminals are grounded. The emitted photons are caused by defect-assisted recombination of electrons and holes at the 4H-SiC/SiO$_2$ interface and can be detected through the SiC substrate. Here,

Ronnie de Souza Santos, Cleyton Magalhes, Robson Santons, Jorge Correia-Neto

Context. In the post-pandemic era, software professionals resist returning to office routines, favoring the flexibility gained from remote work. Hybrid work structures, then, become popular within software companies, allowing them to choose not to work in the office every day, preserving flexibility, and creating several benefits, including an increase in th

Tanmoy Biswas, Chandan Datta

We consider a three-stroke engine in the microscopic regime, where the working body of the engine is composed of a two-level system. The working body of the engine aims to withdraw heat from the hot heat bath, generate work, and discharge the surplus heat into the cold heat bath through the successive execution of three strokes. In this process, the interact

Abhinav Gupta, Radim Bartos

HTTP/3 marks a significant advancement in protocol development, utilizing QUIC as its underlying transport layer to exploit multiplexing capabilities and minimize head-of-line blocking. The introduction of the Extensible Prioritization Scheme (EPS) offers a signaling mechanism for controlling the order of resource delivery. In this study, we propose mappings

Nicholas Barth, George C. Privon, Rana Ezzeddine, Aaron S. Evans

Our understanding of early-type galaxies (ETGs) has grown in the past decade with the advance of full-spectrum fitting techniques used to infer the properties of the stellar populations that make-up the galaxy. We present ages, central velocity dispersions, and abundance ratios relative to Fe of C, N, O, Mg, Si, Ca, Ti, Cr, Mn, Co, Ni, Cu, Sr, Ba, and Eu, de

Giovanni Franzese, Ravi Prakash, Cosimo Della Santina, Jens Kober

Learning from Interactive Demonstrations has revolutionized the way non-expert humans teach robots. It is enough to kinesthetically move the robot around to teach pick-and-place, dressing, or cleaning policies. However, the main challenge is correctly generalizing to novel situations, e.g., different surfaces to clean or different arm postures to dress. This

Xiaolu Zhao, Ludivine Oruba, Danièle Hauser, Biao Zhang

We investigate the ocean wave field under Hurricane SAM (2021). Whilst measurements of waves under Tropical Cyclones (TCs) are rare, an unusually large number of quality in situ and remote measurements are available in that case. First, we highlight the good consistency between the wave spectra provided by the Surface Waves Investigation and Monitoring (SWIM

Hanjiang Hu, Jianglin Lan, Changliu Liu

Safe control of neural network dynamic models (NNDMs) is important to robotics and many applications. However, it remains challenging to compute an optimal safe control in real time for NNDM. To enable real-time computation, we propose to use a sound approximation of the NNDM in the control synthesis. In particular, we propose Bernstein over-approximated neu

Jingtian Shi, Nicolás Morales-Durán, Eslam Khalaf, Allan H. MacDonald

Topological flat moir\'e bands with nearly ideal quantum geometry have been identified in homobilayer transition metal dichalcogenide moir\'e superlattices, and are thought to be crucial for understanding the fractional Chern insulating states recently observed therein. Previous work proposed viewing the system using an adiabatic approximation that replaces

Michael Bidollahkhani, Julian M. Kunkel

The landscape of maintenance in distributed systems is rapidly evolving with the integration of Artificial Intelligence (AI). Also, as the complexity of computing continuum systems intensifies, the role of AI in predictive maintenance (Pd.M.) becomes increasingly pivotal. This paper presents a comprehensive survey of the current state of Pd.M. in the computi

Oleg K. Sheinman

Sets of points giving spectral curves can be regarded as phase coordinates of Hitchin systems. We address the problem of finding out trajectories of Hitchin systems in those coordinates. The problem is being solved for the systems with structure groups $SO(4)$ and $SL(2)$ on genus 2 curves. Our method is a transfer of straight line windings of fibers of the

Abhinau K. Venkataramanan, Cosmin Stejerean, Ioannis Katsavounidis, Hassene Tmar

High Dynamic Range (HDR) videos have enjoyed a surge in popularity in recent years due to their ability to represent a wider range of contrast and color than Standard Dynamic Range (SDR) videos. Although HDR video capture has seen increasing popularity because of recent flagship mobile phones such as Apple iPhones, Google Pixels, and Samsung Galaxy phones, a

I. Wojciechowska, A. Dyrdal

We consider the anomalous, spin, valley, and valley spin Hall effects in a pristine ex-so-tic graphene-based van-der-Waals (vdW) heterostructure consisting of a bilayer graphene (BLG) between semiconducting van-der-Waals material with strong SOC (e.g., WS$_2$) and ferromagnetic and insulating vdW material (e.g. Cr$_2$Ge$_2$Te$_6$). Reducing the effective Ham

Jose Cribeiro-Ramallo, Vadim Arzamasov, Federico Matteucci, Denis Wambold

Outlier detection in high-dimensional tabular data is an important task in data mining, essential for many downstream tasks and applications. Existing unsupervised outlier detection algorithms face one or more problems, including inlier assumption (IA), curse of dimensionality (CD), and multiple views (MV). To address these issues, we introduce Generative Su

Alexander Fominyh

The paper explores the differential inclusion of a special form. It is supposed that the support function of the set in the right-hand side of an inclusion may contain the sum of the maximum and the minimum of the finite number of continuously differentiable (in phase coordinates) functions. It is required to find a trajectory that would satisfy differential

Erdem Sucu

The impact of the Generalized Uncertainty Principle (GUP) on Hawking particle emission in a rotating linear dilaton black hole (RLDBH) spacetime is examined in this thesis. The concerned study presents a thermal emission model for black holes (BHs) that incorporates the influence of gravitational lens particles through GUP during the quantum tunneling proces

Jeremy Speth, Nathan Vance, Patrick Flynn, Adam Czajka

Subtle periodic signals, such as blood volume pulse and respiration, can be extracted from RGB video, enabling noncontact health monitoring at low cost. Advancements in remote pulse estimation -- or remote photoplethysmography (rPPG) -- are currently driven by deep learning solutions. However, modern approaches are trained and evaluated on benchmark datasets

Safinaz Salem

We propose an interpretation for the cosmological constant problem based on modeling the universe as a 3-brane embedded in the bulk of 5-dimensional supergravity with hypermultiplets. When solving the modified Friedmann equations the complex structure moduli of the Calabi-Yau manifold cancel the large value of the vacuum energy density on the brane, wherein

Istvan Racz, Gabor Zsolt Toth

The late-time behaviour of the solutions of the Fackerell-Ipser equation (which is a wave equation for the spin-zero component of the electromagnetic field strength tensor) on the closure of the domain of outer communication of sub-extremal Kerr spacetime is studied numerically. Within the Kerr family, the case of Schwarzschild background is also considered.

Bernhard Haeupler, D Ellis Hershkowitz, Zihan Tan

Expander decompositions form the basis of one of the most flexible paradigms for close-to-linear-time graph algorithms. Length-constrained expander decompositions generalize this paradigm to better work for problems with lengths, distances and costs. Roughly, an $(h,s)$-length $\phi$-expander decomposition is a small collection of length increases to a graph

Sanghyun Son, Matheus Gadelha, Yang Zhou, Zexiang Xu

We present a differentiable representation, DMesh, for general 3D triangular meshes. DMesh considers both the geometry and connectivity information of a mesh. In our design, we first get a set of convex tetrahedra that compactly tessellates the domain based on Weighted Delaunay Triangulation (WDT), and select triangular faces on the tetrahedra to define the

Ganesh Sistu, Senthil Yogamani

Object detection is a mature problem in autonomous driving with pedestrian detection being one of the first deployed algorithms. It has been comprehensively studied in the literature. However, object detection is relatively less explored for fisheye cameras used for surround-view near field sensing. The standard bounding box representation fails in fisheye c

Kevin L. Chen, Falco J. Bargagli-Stoffi, Raphael C. Kim, Lucas R. F. Henneman

Pollution from coal-fired power plants has been linked to substantial health and mortality burdens in the US. In recent decades, federal regulatory policies have spurred efforts to curb emissions through various actions, such as the installation of emissions control technologies on power plants. However, assessing the health impacts of these measures, partic

Tao Zhou, Alexandre Reinhardt, Marie Bousquet, Joel Eymery

Surface acoustic wave devices are key components for processing radio frequency signals in wireless communication because these devices offer simultaneously high performance, compact size and low cost. The optimization of the device structure requires a quantitative understanding of energy conversion and loss mechanisms. Stroboscopic full-field diffraction x

Jiajian Luo, Jaeho Lee

Thermoelectric coolers (TECs) offer a promising solution for direct cooling of local hotspots and active thermal management in advanced electronic systems. However, TECs present significant trade-offs among spatial cooling, heating and power consumption. The optimization of TECs requires extensive simulations, which are impractical for managing actual system

Sefika Efeoglu

Ontology matching is defined as finding a relationship or correspondence between two or more entities in two or more ontologies. To solve the interoperability problem of the domain ontologies, semantically similar entities in these ontologies must be found and aligned before merging them. GraphMatcher, developed in this study, is an ontology matching system

Afzal Ahmad, Daniel Bonilla Licea, Giuseppe Silano, Tomas Baca

This article presents Persistence Administered Collective Navigation (PACNav) as an approach for achieving decentralized collective navigation of Unmanned Aerial Vehicle (UAV) swarms. The technique is inspired by the flocking and collective navigation behavior observed in natural swarms, such as cattle herds, bird flocks, and even large groups of humans. PAC

Sefika Efeoglu, Adrian Paschke

Information resources such as newspapers have produced unstructured text data in various languages related to the corona outbreak since December 2019. Analyzing these unstructured texts is time-consuming without representing them in a structured format; therefore, representing them in a structured format is crucial. An information extraction pipeline with es

Sefika Efeoglu

Representing unstructured data in a structured form is most significant for information system management to analyze and interpret it. To do this, the unstructured data might be converted into Knowledge Graphs, by leveraging an information extraction pipeline whose main tasks are named entity recognition and relation extraction. This thesis aims to develop a

Zahra Rezaei, Aboozar Ghaffary

The explanation of the muon anomalous magnetic moment ($\mu$-AMM) requires new physics beyond the Standard Model. In this work, we investigate the effects of noncommutative space-time on the $\mu$-AMM within the Seiberg-Witten map framework, analyzing both tree-level and loop-level diagrams. Additionally, we examine the $\mu$-AMM by studying the scattering c

Baoru Huang, Yida Wang, Anh Nguyen, Daniel Elson

In surgical oncology, screening colonoscopy plays a pivotal role in providing diagnostic assistance, such as biopsy, and facilitating surgical navigation, particularly in polyp detection. Computer-assisted endoscopic surgery has recently gained attention and amalgamated various 3D computer vision techniques, including camera localization, depth estimation, s

Farid Behrouzi, Zahra Naghavi

Let $G$ be a countable discrete group that act minimally on a compact Hausdorff space $X$ by homeomorphisms. Our goal is to establish the equivalence between the faithfulness of the action of $G$ on the generalized Furstenberg boundary $\partial_F(G, X)$ and a weakened version of the generalized Powers' averaging property. This result provides valuable insig

Naotaka Kajino, Ryosuke Shimizu

We construct good $p$-energy forms on metric measure spaces as pointwise subsequential limits of Besov-type $p$-energy functionals under certain geometric/analytic conditions. Such forms are often called Korevaar-Schoen $p$-energy forms in the literature. As an advantage of our approach, the associated $p$-energy measures are obtained and investigated. We al

Yuang Liu, Zhiheng Qiu, Xiaokai Qin

Transformer has been applied in the field of computer vision due to its excellent performance in natural language processing, surpassing traditional convolutional neural networks and achieving new state-of-the-art. ViT divides an image into several local patches, known as "visual sentences". However, the information contained in the image is vast and complex

Jan Peszek, Rémy Rodiac

We study the mean-field limits of critical points of interaction energies with Coulombian singularity. An important feature of our setting is that we allow interaction between particles of opposite signs. Particles of opposite signs attract each other whereas particles of the same signs repel each other. In 2D, we prove that the associated empirical measures

Irina Rudenko, Andrey Rudenko, Achim J. Lilienthal, Kai O. Arras

Social robots, owing to their embodied physical presence in human spaces and the ability to directly interact with the users and their environment, have a great potential to support children in various activities in education, healthcare and daily life. Child-Robot Interaction (CRI), as any domain involving children, inevitably faces the major challenge of d

Siddhanth Raja Sindhupathiraja, A K M Amanat Ullah, William Delamare, Khalad Hasan

Teleportation, a widely-used locomotion technique in Virtual Reality (VR), allows instantaneous movement within VR environments. Enhanced hand tracking in modern VR headsets has popularized hands-only teleportation methods, which eliminate the need for physical controllers. However, these techniques have not fully explored the potential of bi-manual input, w

Chenru Duan, Guan-Horng Liu, Yuanqi Du, Tianrong Chen

Transition states (TSs) are transient structures that are key in understanding reaction mechanisms and designing catalysts but challenging to be captured in experiments. Alternatively, many optimization algorithms have been developed to search for TSs computationally. Yet the cost of these algorithms driven by quantum chemistry methods (usually density funct

Zaid Ahsan, Harry Dankowicz, Christian Kuehn

This paper presents a new boundary-value problem formulation for quantifying uncertainty induced by the presence of small Brownian noise near transversally stable periodic orbits (limit cycles) and quasiperiodic invariant tori of the deterministic dynamical systems obtained in the absence of noise. The formulation uses adjoints to construct a continuous fami

Zeinali Hossein, Lee Kong Aik, Alam Jahangir, Burget Lukas

This document outlines the Text-dependent Speaker Verification (TdSV) Challenge 2024, which centers on analyzing and exploring novel approaches for text-dependent speaker verification. The primary goal of this challenge is to motive participants to develop single yet competitive systems, conduct thorough analyses, and explore innovative concepts such as mult

Xian-Jin Li

In this paper, a positive operator is given. It is shown that the product of this positive operator and the convolution operator is a trace class Hilbert-Schmidt integral operator and has nonnegative eigenvalues. A formula is given for the trace of this product operator. It seems that this product operator is the closest trace class integral operator which h

Harshvardhan J. Pandit, Beatriz Esteves, Georg P. Krog, Paul Ryan

The Data Privacy Vocabulary (DPV), developed by the W3C Data Privacy Vocabularies and Controls Community Group (DPVCG), enables the creation of machine-readable, interoperable, and standards-based representations for describing the processing of personal data. The group has also published extensions to the DPV to describe specific applications to support leg

Yuheng Ji, Yue Liu, Zhicheng Zhang, Zhao Zhang

Vision-Language Models (VLMs) play a crucial role in the advancement of Artificial General Intelligence (AGI). As AGI rapidly evolves, addressing security concerns has emerged as one of the most significant challenges for VLMs. In this paper, we present extensive experiments that expose the vulnerabilities of conventional adaptation methods for VLMs, highlig

Somayeh Ashofteh, Moharram N. Iradmusa

A derangement $k$-representation of a graph $G$ is a map $\pi$ of $V(G)$ to the symmetric group $S_k$, such that for any two vertices $v$ and $u$ of $V(G)$, $v $ and $u$ are adjacent if and only if $\pi(v)(i) \neq \pi(u)(i)$ for each $i \in \{1,2,3,\ldots,k\}$. The derangement representation number of $G$ denoted by $drn(G)$, is the minimum of $k$ such that

Utsav Singh, Wesley A. Suttle, Brian M. Sadler, Vinay P. Namboodiri

In this work, we introduce PIPER: Primitive-Informed Preference-based Hierarchical reinforcement learning via Hindsight Relabeling, a novel approach that leverages preference-based learning to learn a reward model, and subsequently uses this reward model to relabel higher-level replay buffers. Since this reward is unaffected by lower primitive behavior, our

Mohammad Al-Ramahi, Izzat Alsmadi, Abdullah Wahbeh

The wealth of information available through the Internet and social media is unprecedented. Within computing fields, websites such as Stack Overflow are considered important sources for users seeking solutions to their computing and programming issues. However, like other social media platforms, Stack Overflow contains a mixture of relevant and irrelevant in

Harshal D. Kaushik, Roshni Anna Jacob, Souma Chowdhury, Jie Zhang

Optimal decision-making is key to efficient allocation and scheduling of repair resources (e.g., crews) to service affected nodes of large power grid networks. Traditional manual restoration methods are inadequate for modern smart grids sprawling across vast territories, compounded by the unpredictable nature of damage and disruptions in power and transporta

Michael Duchesne, Kaiwen Zhang, Chamseddine Talhi

Federated Learning (FL) has emerged as a prominent privacy-preserving technique for enabling use cases like confidential clinical machine learning. FL operates by aggregating models trained by remote devices which owns the data. Thus, FL enables the training of powerful global models using crowd-sourced data from a large number of learners, without compromis