March 2024 arXiv papers — page 84

Nikos Katzourakis, Roger Moser

We study variational problems for second order supremal functionals $\mathrm F_\infty(u)= \|F(\cdot,u,\mathrm D u,\mathrm{A}\!:\!\mathrm D^2u)\|_{\mathrm L^{\infty}(\Omega)}$, where $F$ satisfies certain natural assumptions, $\mathrm A$ is a positive matrix, and $\Omega \Subset \mathbb R^n$. Higher order problems are very novel in the Calculus of Variations

Shuaida He, Jiaqi Li, Xin Chen

The classification of random objects within metric spaces without a vector structure has attracted increasing attention. However, the complexity inherent in such non-Euclidean data often restricts existing models to handle only a limited number of features, leaving a gap in real-world applications. To address this, we propose a data-adaptive filtering proced

G. Somogyi, S. Van Thurenhout

We present the Feynman rules for leading-twist gauge-invariant quark and gluon operators with an arbitrary number of total derivatives and applicable to any order in perturbation theory. This generalizes previous results and constitutes a necessary ingredient in the computation of the matrix elements of the corresponding operators. The results are written in

Soumya Chakrabarti

Motivated by the notion that the mathematics of gravity can be reproduced from a statistical requirement of maximal entropy, we study the consequence of introducing an entropic source term in the Einstein-Hilbert action. For a spatially homogeneous cosmological system driven by this entropic source and enveloped by a time evolving apparent horizon, we formul

Georgia Acton, Michael Barnes, Sarah Newton, Hanne Thienpondt

Microinstabilities drive turbulent fluctuations in inhomogeneous, magnetized plasmas. In the context of magnetic confinement fusion devices, this leads to an enhanced transport of particles, momentum, and energy, thereby degrading confinement. In this work, we elaborate on the application of the adjoint method to efficiently determine the variation of linear

Haochen Wu, Liyang Lu, Zhaocheng Wang

Near-field communication comes to be an indispensable part of the future sixth generation (6G) communications at the arrival of the forth-coming deployment of extremely large-scale multiple-input-multiple-output (XL-MIMO) systems. Due to the huge array aperture and high-frequency bands, the electromagnetic radiation field is modeled by the spherical waves in

Valentina Shumovskaia, Mert Kayaalp, Ali H. Sayed

Non-Bayesian social learning is a framework for distributed hypothesis testing aimed at learning the true state of the environment. Traditionally, the agents are assumed to receive observations conditioned on the same true state, although it is also possible to examine the case of heterogeneous models across the graph. One important special case is when hete

Anurag Singh, Shivangi Aneja

With the increasing influence of social media, online misinformation has grown to become a societal issue. The motivation for our work comes from the threat caused by cheapfakes, where an unaltered image is described using a news caption in a new but false-context. The main challenge in detecting such out-of-context multimedia is the unavailability of large-

Rene Doyon

Detecting an atmosphere on nearby temperate planets is one of the most important scientific objectives of the Webb mission, an endeavour in practice limited to a handful of well-characterized planets: Trappist-1d, e, f, g, LHS1140b, and the mini-Neptune K2- 18b. The first 18 months of atmospheric characterization with JWST have confirmed both its power and v

Richard M. Höfer, Šárka Nečasová, Florian Oschmann

We consider the solutions $\rho_\varepsilon, \mathbf{u}_\varepsilon$ to the compressible Navier-Stokes equations (NSE) in a domain periodically perforated by holes of diameter $\varepsilon>0$. We focus on the case where the diameter of the holes is of the same order as the distance between neighboring holes. This is the same setting investigated in the paper

Lihua Dong, Shu Lin

It is commonly understood that the strong magnetic field produced in heavy ion collisions is short-lived. The electric conductivity of the quark-gluon plasma is unable to significantly extend the life time of magnetic field. We propose an alternative scenario to achieve this: with finite baryon density and spin polarization by the initial magnetic field, the

L. H. Carnevale, P. Deuar, Z. Che, P. E. Theodorakis

The breakup of liquid threads into droplets is crucial in various applications, such as nanoprinting, nanomanufacturing, and inkjet printing, where a detailed understanding of the thinning neck dynamics allows for a precise droplet control. Here, the role of surfactant in the breakup process is studied by many-body dissipative particle dynamics, in particula

Zhi-Jun Li, Ming-Kuan Yuan, Yun-Xuan Song, Yan-Gu Li

Modern particle physics experiments usually rely on highly complex and large-scale spectrometer devices. In high energy physics experiments, visualization helps detector design, data quality monitoring, offline data processing, and has great potential for improving physics analysis. In addition to the traditional physics data analysis based on statistical me

Sebastian Rickelhoff, Alexander Schnurr

When considering stochastic integration and the theory of stochastic differential equations, P. Protter's textbook \cite{protter} undoubtedly is a main piece of standard literature. Not only is it well-written, but it also contains various profound results regarding these fields. Unfortunately, Theorem 12 of Chapter V, which presents an equivalence to unifor

Hikaru Okuma, Yumiko Katayama, Fukunobu Kadowaki, Yuki Tokumoto

Epitaxial thin films of SrTaO$_3$ with thickness ($t$) smaller than 74 nm were successfully fabricated on an insulator (LaAlO$_3$)$_{0.3}$(Sr$_2$AlTaO$_6$)$_{0.7}$ substrate. Films with $t$ above 8.6 nm showed metallic conduction. Both conductivity and a mobility showed a decrease with increasing $t$ above 42 nm, suggesting the instability of thick SrTaO$_3$

Gerlind Plonka, Yannick Riebe

We propose a new fast algorithm for simultaneous recovery of the coil sensitivities and of the magnetization image from incomplete Fourier measurements in parallel MRI. Our approach is based on a parameter model for the coil sensitivities using bivariate trigonometric polynomials of small degree. The derived MOCCA algorithm has low computational complexity o

Petr Čoupek, Pavel Kříž, Bohdan Maslowski

In this paper, we study parameter identification for solutions to (possibly non-linear) SDEs driven by additive Rosenblatt process and singularity of the induced laws on the path space. We propose a joint estimator for the drift parameter, diffusion intensity, and Hurst index that can be computed from discrete-time observations with a bounded time horizon an

Denis Dresvyanskiy, Maxim Markitantov, Jiawei Yu, Peitong Li

As emotions play a central role in human communication, automatic emotion recognition has attracted increasing attention in the last two decades. While multimodal systems enjoy high performances on lab-controlled data, they are still far from providing ecological validity on non-lab-controlled, namely 'in-the-wild' data. This work investigates audiovisual de

F. Aharonian, F. Ait Benkhali, J. Aschersleben, H. Ashkar

The Crab Nebula is a unique laboratory for studying the acceleration of electrons and positrons through their non-thermal radiation. Observations of very-high-energy $\gamma$ rays from the Crab Nebula have provided important constraints for modelling its broadband emission. We present the first fully self-consistent analysis of the Crab Nebula's $\gamma$-ray

Tobias Doernbach

Top-down, user-centered thinking is not typically a strength of all students, especially tech-savvy computer science-related ones. We propose Human-Robot Interaction (HRI) introductory courses as a highly suitable opportunity to foster these important skills since the HRI discipline includes a focus on humans as users. Our HRI course therefore contains eleme

Simon Klüttermann, Jérôme Rutinowski, Anh Nguyen, Britta Grimme

In this contribution, we introduce a novel ensemble method for the re-identification of industrial entities, using images of chipwood pallets and galvanized metal plates as dataset examples. Our algorithms replace commonly used, complex siamese neural networks with an ensemble of simplified, rudimentary models, providing wider applicability, especially in ha

Rodrigo Laigner, Zhexiang Zhang, Yijian Liu, Leonardo Freitas Gomes

Microservice architectures have become a popular approach for designing scalable distributed applications. Despite their extensive use in industrial settings for over a decade, there is limited understanding of the data management challenges that arise in these applications. Consequently, it has been difficult to advance data system technologies that effecti

Mari-Liis Aru, Karina Mauco, Carlo F. Manara, Thomas J. Haworth

In the Orion Nebula Cluster (ONC), protoplanetary disks exhibit ionized gas clouds in the form of a striking teardrop shape as massive stars irradiate the disk material. We present the first spatially and spectrally resolved observations of 12 proplyds, using Integral Field Spectroscopy observations performed with the MUSE instrument in Narrow Field Mode (NF

Marc Carnovale, Jonathan M. Fraser, Ana E. de Orellana

The Fourier spectrum is a family of dimensions that interpolates between the Fourier and Hausdorff dimensions and are defined in terms of certain energies which capture Fourier decay. In this paper we obtain a convenient discrete representation of those energies using the Fourier coefficients. As an example application, we use this representation to establis

Yuehan Xu, Tao Wang, Peng Huang, Guihua Zeng

The integration of sensing and communication can achieve ubiquitous sensing while enabling ubiquitous communication. Within the gradually improving global communication, the integrated sensing and communication (ISAC) system based on optical fibers can accomplish various functionalities, such as urban structure imaging, seismic wave detection, and pipeline s

Chuang Liu, Renren Jin, Yuqi Ren, Deyi Xiong

Chinese Large Language Models (LLMs) have recently demonstrated impressive capabilities across various NLP benchmarks and real-world applications. However, the existing benchmarks for comprehensively evaluating these LLMs are still insufficient, particularly in terms of measuring knowledge that LLMs capture. Current datasets collect questions from Chinese ex

Alice Damiano, Milena Valentini, Stefano Borgani, Luca Tornatore

We implement a sub-resolution prescription for the unresolved dynamical friction onto black holes (BHs) in the OpenGadget3 code. We carry out cosmological simulations of a volume of 16 cMpc3 and zoom-ins of a galaxy group and of a galaxy cluster. The advantages of our new technique are assessed in comparison to commonly adopted methods to hamper spurious BH

Catalina Vajiac, Arun Frey, Joachim Baumann, Abigail Smith

Rental assistance programs provide individuals with financial assistance to prevent housing instabilities caused by evictions and avert homelessness. Since these programs operate under resource constraints, they must decide who to prioritize. Typically, funding is distributed by a reactive or first-come-first serve allocation process that does not systematic

Peter Keller, Mert Ugurlu

The well-known Isothermal Theorem was introduced in a Nature Communications article in 2005 and has since contributed to the creation of the rich field of evolutionary graph theory. The theorem states under which conditions certain Moran-like processes on graphs ("spatial Moran Processes") have the same fixation probability as the classic one-dimensional Mor

Giacomo Morpurgo, Thierry Giamarchi

We study the competition between disorder and singlet superconductivity in a quasi-1d system. We investigate the applicability of the Anderson theorem, namely that time-reversal conserving (non-magnetic) disorder does not impact the critical temperature, by opposition to time-reversal breaking disorder (magnetic). To do so we examine a quasi-1d system of spi

F. Alemanno, P. Bernardini, A. Corvaglia, G. De Matteis

The KLOE electromagnetic calorimeter is expected to be reused in the Near Detector complex of the DUNE experiment at Fermilab. The possible substitution of traditional Photomultiplier Tubes (PMTs) with Silicon Photomultipliers (SiPMs) in the refurbished calorimeter is the object of this investigation. A block of the KLOE lead-scintillating fiber calorimeter

Victor Carbune, Hassan Mansoor, Fangyu Liu, Rahul Aralikatte

Vision-language models (VLMs) are achieving increasingly strong performance on multimodal tasks. However, reasoning capabilities remain limited particularly for smaller VLMs, while those of large-language models (LLMs) have seen numerous improvements. We propose a technique to transfer capabilities from LLMs to VLMs. On the recently introduced ChartQA, our m

Antonio Di Pasquale, Johanna Kristin Maria Becker, Andreas Martin Kettner, Mario Paolone

Recently, the authors of this paper proposed a method for the Harmonic Power-Flow (HPF) calculus in polyphase grids with widespread deployment of Converter-Interfaced Distributed Energy Resources (CIDERs). The HPF problem was formulated by integrating the hybrid nodal equations of the grid with a detailed representation of the CIDERs hardware, sensing, and c

Daniele Ferretti, Alessandro Teta

We study the Hamiltonian for a three-dimensional Bose gas of $N \geq 3$ spinless particles interacting via zero-range (also known as contact) interactions. Such interactions are encoded by (singular) boundary conditions imposed on the coincidence hyperplanes, i.e., when the coordinates of two particles coincide. It is well known that imposing the same kind o

Hiroki Ishizaka

In this study, we investigate a hybrid-type anisotropic weakly over-penalised symmetric interior penalty method for the Poisson equation on convex domains. Compared with the well-known hybrid discontinuous Galerkin methods, our approach is simple and easy to implement. Our primary contributions are the proposal of a new scheme and the demonstration of a proo

Subhransu Dhar, Teresa Liberto, Catherine Barentin, Thibaut Divoux

The dynamic yield stress associated with the flow cessation of cement pastes is measured using a rheometer equipped with various shear geometries such as vane, helical, sandblasted co-axial cylinders, and serrated parallel plates, as well as with the mini-cone spread test. Discrepancies in yield stress values are observed for cement pastes at various volume

Evgeny Kochurin

The dynamic conformal transformation method has been generalized for the first time to numerically simulate the capillary wave turbulence of a liquid surface in the plane symmetric anisotropic geometry. The model is strongly nonlinear and involves effects of surface tension, as well as energy dissipation and pumping. Simulation results have shown that the sy

Ilan Ben-Noah, Juan J. Hidalgo, Marco Dentz

Media classification and the construction of pore network models from binary images of porous media hinges on accurately characterizing the pore space. We present an efficient method for (i) locating critical points, that is, pore body and throat centers, and (ii) partitioning of the pore space using information on the curvature of the distance map (DM) of t

Nicolas Chenavier, David Coupier, Keenan Penner, Arnaud Rousselle

We consider a random growth model based on the IDLA protocol with sources in a hyperplane of $Z^d$ . We provide a stabilization result and a shape theorem generalizing [7] in any dimension by introducing new techniques leading to a rough global upper bound.

Clément Gaspard, Grégoire Passault, Mélodie Daniel, Olivier Ly

Designing a humanoid locomotion controller is challenging and classically split up in sub-problems. Footstep planning is one of those, where the sequence of footsteps is defined. Even in simpler environments, finding a minimal sequence, or even a feasible sequence, yields a complex optimization problem. In the literature, this problem is usually addressed by

Alexander Kolpakov, Aidan Rocke

In the present work we use maximum entropy methods to derive several theorems in probabilistic number theory, including a version of the Hardy-Ramanujan Theorem. We also provide a theoretical argument explaining the experimental observations of Yang-Hui He about the learnability of primes, and posit that the Erd\H{o}s-Kac law would very unlikely be discovere

Camila Fernández, Matías Pavez-Signé, Maya Stein

We study two variations of the Gyarfas--Lehel conjecture on the minimum number of monochromatic components needed to cover an edge-coloured complete bipartite graph. Specifically, we show the following. - For p>> (\log n/n)^{1/2}, w.h.p.~every 2-colouring of the random bipartite graph G~ G(n,n,p) admits a cover of all but O(1/p) vertices of G using at most t

Sumika Chauhan, Govind Vashishtha, Rajesh Kumar, Radoslaw Zimroz

The vibration analysis of the bearing is very crucial because of its non-stationary nature and low signal-to-noise ratio. Therefore, a novel scheme for detecting bearing defects is put forward based on the extraction of single-valued neutrosophic cross-entropy (SVNCE) to address this issue. Initially, the artificial hummingbird algorithm (AHA) is used to mak

Yazeed Alharbi, Peter Wonka

We present a novel, training-free approach for textual editing of real images using diffusion models. Unlike prior methods that rely on computationally expensive finetuning, our approach leverages LAtent SPatial Alignment (LASPA) to efficiently preserve image details. We demonstrate how the diffusion process is amenable to spatial guidance using a reference

Sheikh Zeeshan Basar, Satadal Ghosh

In any spacecraft landing mission, fuel-efficient precision soft landing while avoiding nearby hazardous terrain is of utmost importance. Very few existing literature have attempted addressing both the problems of precision soft landing and terrain avoidance simultaneously. To this end, an optimal terrain avoidance landing guidance (OTALG) was recently devel

Gulshan Yadav, RahulKumar Yadav, Mansi Viramgama, Mayank Viramgama

Traditional database management systems need help efficiently represent and querying the complex, high-dimensional data prevalent in modern applications. Vector databases offer a solution by storing data as numerical vectors within a multi-dimensional space. This enables similarity-based search and analysis, such as image retrieval, recommendation engine gen

Xiang Li, Zhenyu Li, Chen Shi, Yong Xu

The task of financial analysis primarily encompasses two key areas: stock trend prediction and the corresponding financial question answering. Currently, machine learning and deep learning algorithms (ML&DL) have been widely applied for stock trend predictions, leading to significant progress. However, these methods fail to provide reasons for predictions, l

Thomas Schneider, Pascal Schweitzer

The Weisfeiler-Leman (WL) algorithms form a family of incomplete approaches to the graph isomorphism problem. They recently found various applications in algorithmic group theory and machine learning. In fact, the algorithms form a parameterized family: for each $k \in \mathbb{N}$ there is a corresponding $k$-dimensional algorithm $\texttt{WLk}$. The algorit

Chengjie Wang, Wenbing Zhu, Bin-Bin Gao, Zhenye Gan

Industrial anomaly detection (IAD) has garnered significant attention and experienced rapid development. However, the recent development of IAD approach has encountered certain difficulties due to dataset limitations. On the one hand, most of the state-of-the-art methods have achieved saturation (over 99% in AUROC) on mainstream datasets such as MVTec, and t

Iyad Walwil, Olivier Fercoq

We optimize the running time of the primal-dual algorithms by optimizing their stopping criteria for solving convex optimization problems under affine equality constraints, which means terminating the algorithm earlier with fewer iterations. We study the relations between four stopping criteria and show under which conditions they are accurate to detect opti

Jiaxin Wang, Yadi Wei, Fang-Wei Fu, Juan Li

Self-orthogonal codes are a significant class of linear codes in coding theory and have attracted a lot of attention. In \cite{HLL2023Te,LH2023Se}, $p$-ary self-orthogonal codes were constructed by using $p$-ary weakly regular bent functions, where $p$ is an odd prime. In \cite{WH2023Se}, two classes of non-degenerate quadratic forms were used to construct $

Carsten Carstensen, Benedikt Gräßle

The a posteriori error analysis of the classical Argyris finite element methods dates back to 1996, while the optimal convergence rates of associated adaptive finite element schemes are established only very recently in 2021. It took a long time to realise the necessity of an extension of the classical finite element spaces to make them hierarchical. This pa

Nalini Anantharaman, Laura Monk

Let $X$ be a closed, connected, oriented surface of genus $g$, with a hyperbolic metric chosen at random according to the Weil--Petersson measure on the moduli space of Riemannian metrics. Let $\lambda_1=\lambda_1(X)$ bethe first non-zero eigenvalue of the Laplacian on $X$ or, in other words, the spectral gap.In this paper we give a full road-map to prove th

Tommaso Grigoletto, Francesco Ticozzi

Leveraging an algebraic approach built on minimal realizations and conditional expectations in quantum probability, we propose a method to reduce the dimension of quantum filters in discrete-time, while maintaining the correct distributions on the measurement outcomes and the expectations of some relevant observable. The method is presented for general quant

Ziming Wang, Ziling Wang, Huaning Li, Lang Qin

Event cameras, with their high dynamic range and temporal resolution, are ideally suited for object detection, especially under scenarios with motion blur and challenging lighting conditions. However, while most existing approaches prioritize optimizing spatiotemporal representations with advanced detection backbones and early aggregation functions, the cruc

Jianjun Huang, Lixin Ye, Li Kang

In the Industrial Internet of Things (IoT), a large amount of data will be generated every day. Due to privacy and security issues, it is difficult to collect all these data together to train deep learning models, thus the federated learning, a distributed machine learning paradigm that protects data privacy, has been widely used in IoT. However, in practica

Marie Vernet, Stéphanie Ducrot, Yves Chaix

This systematic review aimed to examine the possible implication of visual-perceptual, visuo-attentional and oculomotor processing in the reading deficits frequently experienced by children with Neurofibromatosis type 1 (NF1), as previously shown in dyslexia. Using PRISMA methodological guidelines, we examined 49 studies; most of these reported visual-proces

Christian W. Frey

Industrial production processes, especially in the pharmaceutical industry, are complex systems that require continuous monitoring to ensure efficiency, product quality, and safety. This paper presents a hybrid unsupervised learning strategy (HULS) for monitoring complex industrial processes. Addressing the limitations of traditional Self-Organizing Maps (SO

Torben Teepe, Philipp Wolters, Johannes Gilg, Fabian Herzog

Taking advantage of multi-view aggregation presents a promising solution to tackle challenges such as occlusion and missed detection in multi-object tracking and detection. Recent advancements in multi-view detection and 3D object recognition have significantly improved performance by strategically projecting all views onto the ground plane and conducting de

Jun Yu, Jichao Zhu, Wangyuan Zhu

Compound Expression Recognition (CER) plays a crucial role in interpersonal interactions. Due to the existence of Compound Expressions , human emotional expressions are complex, requiring consideration of both local and global facial expressions to make judgments. In this paper, to address this issue, we propose a solution based on ensemble learning methods

Ioannis Krikidis, Abhishek Kumar Singh, Kyle Jamieson

Reconfigurable antenna multiple-input multiple-output (MIMO) is a promising technology for upcoming 6G communication systems. In this paper, we deal with the problem of configuration selection for reconfigurable antenna MIMO by leveraging Coherent Ising Machines (CIMs). By adopting the CIM as a heuristic solver for the Ising problem, the optimal antenna conf

Chaoqin Huang, Aofan Jiang, Jinghao Feng, Ya Zhang

Recent advancements in large-scale visual-language pre-trained models have led to significant progress in zero-/few-shot anomaly detection within natural image domains. However, the substantial domain divergence between natural and medical images limits the effectiveness of these methodologies in medical anomaly detection. This paper introduces a novel light

Daniele Corradetti

Generalized Hurwitz theorem states that there are fifteen composition algebras for any given field: seven unital, six para-unital, and two non-unital algebras. In this article we explore the recovery of such algebras from 3D Geometric Algebras. Different involutions, such as reversion, inversion, Clifford conjugation, and full grade inversion, are introduced

Xueshuo Xie, Haoxu Wang, Zhaolong Jian, Tao Li

Edge intelligence enables resource-demanding Deep Neural Network (DNN) inference without transferring original data, addressing concerns about data privacy in consumer Internet of Things (IoT) devices. For privacy-sensitive applications, deploying models in hardware-isolated trusted execution environments (TEEs) becomes essential. However, the limited secure

Irene Perez-Salesa, Rodrigo Aldana-Lopez, Carlos Sagues

Event-triggering mechanisms (ETM) have been developed for consensus problems to reduce communication while ensuring performance guarantees, but their design has grown increasingly complex by incorporating the agent's local and neighbor information. This typically results in ad-hoc solutions, which may only work for the consensus protocol under consideration.

Zhichao Feng, Junjiie Xie, Kaiyuan Li, Yu Qin

In the recommender system of Meituan Waimai, we are dealing with ever-lengthening user behavior sequences, which pose an increasing challenge to modeling user preference effectively. Existing sequential recommendation models often fail to capture long-term dependencies or are too complex, complicating the fulfillment of Meituan Waimai's unique business needs

Francesco Bonacina, Olivier Lopez, Maud Thomas

This paper proposes a regression tree procedure to estimate conditional copulas. The associated algorithm determines classes of observations based on covariate values and fits a simple parametric copula model on each class. The association parameter changes from one class to another, allowing for non-linearity in the dependence structure modeling. It also al

Mateusz Gabor, Rafal Zdunek, Agnieszka Wylomanska, Radoslaw Zimroz

Local damage of bearings can be detected as a weak cyclic and impulsive component in a highly noisy measured signal. A key problem is how to extract the signal of interest (SOI) from the raw signal, i.e., how to identify and design an optimal filter. To tackle this problem, we propose to use stochastic sampled orthogonal non-negative matrix factorization for

Mirza Alim Mutasodirin, Radityo Eko Prasojo, Achmad F. Abka, Hanif Rasyidi

Many NLP researchers rely on free computational services, such as Google Colab, to fine-tune their Transformer models, causing a limitation for hyperparameter optimization (HPO) in long-text classification due to the method having quadratic complexity and needing a bigger resource. In Indonesian, only a few works were found on long-text classification using

Raghavendra Selvan, Bob Pepin, Christian Igel, Gabrielle Samuel

The recent advances in deep learning (DL) have been accelerated by access to large-scale data and compute. These large-scale resources have been used to train progressively larger models which are resource intensive in terms of compute, data, energy, and carbon emissions. These costs are becoming a new type of entry barrier to researchers and practitioners w

S. Mildiner Moraga, E. Aarts

Hidden Markov models (HMMs) are probabilistic methods in which observations are seen as realizations of a latent Markov process with discrete states that switch over time. Moving beyond standard statistical tests, HMMs offer a statistical environment to optimally exploit the information present in multivariate time series, uncovering the latent dynamics that

O. S. Awolude, H. Don, E. Cator

There are many methods to estimate the quasi-stationary infected fraction of the SIS process on (random) graphs. A challenge is to adequately incorporate correlations, which is especially important in sparse graphs. Methods typically are either significantly biased in sparse graphs, or computationally very demanding already for small network sizes. The forme

Kaile Du, Yifan Zhou, Fan Lyu, Yuyang Li

The partial label challenge in Multi-Label Class-Incremental Learning (MLCIL) arises when only the new classes are labeled during training, while past and future labels remain unavailable. This issue leads to a proliferation of false-positive errors due to erroneously high confidence multi-label predictions, exacerbating catastrophic forgetting within the di

Kayn A. Forbes

It has recently been established that a linearly-polarized optical vortex possesses spin angular momentum density in the direction of propagation (longitudinal spin) under tight-focusing. The helicity of light has long been associated with longitudinal spin angular momentum. Here we show that the longitudinal spin density of linearly-polarized vortices is an

Benoît Gaudeul, Hélène Hivert

In this paper, we introduce a framework for the discretization of a class of constrained Hamilton-Jacobi equations, a system coupling a Hamilton-Jacobi equation with a Lagrange multiplier determined by the constraint. The equation is non-local, and the constraint has bounded variations. We show that, under a set of general hypothesis, the approximation obtai

Zhigang Chen, Benjia Zhou, Jun Li, Jun Wan

Previous Sign Language Translation (SLT) methods achieve superior performance by relying on gloss annotations. However, labeling high-quality glosses is a labor-intensive task, which limits the further development of SLT. Although some approaches work towards gloss-free SLT through jointly training the visual encoder and translation network, these efforts st

Debadri Bhattacharjee, Pradip Kumar Chattopadhyay

In this article we propose a new class of isotropic strange star using Buchdahl-I metric ansatz in the context of MIT bag model equation of state considering of non-zero strange quark mass $(m_{s})$ in the framework of modified $f(R,T)$ theory of gravity. The barotropic form of MIT bag model equation of state and a specific class of $f(R,T)$ model, {\it viz.

Mateusz Gabor, Rafal Zdunek, Radoslaw Zimroz, Jacek Wodecki

In this study, a novel non-negative tensor factorization (NTF)-based method for vibration-based local damage detection in rolling element bearings is proposed. As the diagnostic signal registered from a faulty machine is non-stationary, the time-frequency method is frequently used as a primary decomposition technique. It is proposed here to extract multi-lin

Md Ashiqur Rahman, Robert Joseph George, Mogab Elleithy, Daniel Leibovici

Existing neural operator architectures face challenges when solving multiphysics problems with coupled partial differential equations (PDEs) due to complex geometries, interactions between physical variables, and the limited amounts of high-resolution training data. To address these issues, we propose Codomain Attention Neural Operator (CoDA-NO), which token

Dongyang Xu, Haokun Li, Qingfan Wang, Ziying Song

End-to-end autonomous driving has witnessed remarkable progress. However, the extensive deployment of autonomous vehicles has yet to be realized, primarily due to 1) inefficient multi-modal environment perception: how to integrate data from multi-modal sensors more efficiently; 2) non-human-like scene understanding: how to effectively locate and predict crit

Thomas Apel, Mariano Mateos, Arnd Rösch

The article examines a linear-quadratic Neumann control problem that is governed by a non-coercive elliptic equation. Due to the non-self-adjoint nature of the linear control-to-state operator, it is necessary to independently study both the state and adjoint state equations. The article establishes the existence and uniqueness of solutions for both equation

Seongbo Ha, Jiung Yeon, Hyeonwoo Yu

Simultaneous Localization and Mapping (SLAM) with dense representation plays a key role in robotics, Virtual Reality (VR), and Augmented Reality (AR) applications. Recent advancements in dense representation SLAM have highlighted the potential of leveraging neural scene representation and 3D Gaussian representation for high-fidelity spatial representation. I

Yichen Wang, Mengyu Cao, Zequn Lv, Mei Lu

Let $t,q$ and $n$ be positive integers. Write $[q] = \{1,2,\ldots,q\}$. The generalized Hamming graph $H(t,q,n)$ is the graph whose vertex set is the cartesian product of $n$ copies of $[q]$ ($q\ge 2$), where two vertices are adjacent if their Hamming distance is at most $t$. In particular, $H(1,q,n)$ is the well-known Hamming graph and $H(1,2,n)$ is the hyp

Somnath Maity, Ryusuke Hamazaki

We propose a construction of kinetically constrained models using the Markovian quantum dynamics under strong dissipation. Engineering the Gorini-Kossakowski-Sudarshan-Lindblad (GKSL) equation through classical noise, we show that strong dissipation leads to the emergent decoherence-free subspaces, within which constrained quantum many-body unitary dynamics

Mateusz Gabor, Rafal Zdunek, Radoslaw Zimroz, Agnieszka Wylomanska

Time-frequency representation (TFR) is often used for non-stationary signal analysis. The most intuitive and interpretable TFR is the spectrogram. Recently, a concept of non-negative matrix factorization (NMF) has been successfully applied to local damage detection in rolling elements of bearings via spectrogram factorization. NMF applied to the spectrogram

Of Maminiaina, M. Koko, J. J. Rajaonarison, R. Razafindrakoto

From 1994, we began to use ELISA (Enzyme Linked Immunosorbent Assay) in the diagnosis of PCP. This is aELISA for capturing antigens (PACE) possibly contained in the samples. The advantage of this test comes from the fact that it is completelyindependent of cell cultures. In addition, it is fast: the result can be obtained in less than 36 hours. A study of it

Bryn Davies, Silvio Barandun, Erik Orvehed Hiltunen, Richard V. Craster

We illuminate the fundamental mechanism responsible for the transition between the non-Hermitian skin effect and defect-induced localization in the bulk. We study a Hamiltonian with non-reciprocal couplings that exhibits the skin effect (the localization of all eigenvectors at one edge) and add an on-site defect in the center. Using a two-scale asymptotic me

Masahiro Watari

In the present paper, we show that the motivic Hilbert zeta function for a curve singularity yields the generating functions for Euler numbers of punctual Hilbert schemes when any punctual Hilbert scheme admits an affine cell decomposition. This fact allows us to derive the relations among the motivic Hilbert zeta function and other invariants such as the ge

Yuexiao Ma, Huixia Li, Xiawu Zheng, Feng Ling

The significant resource requirements associated with Large-scale Language Models (LLMs) have generated considerable interest in the development of techniques aimed at compressing and accelerating neural networks. Among these techniques, Post-Training Quantization (PTQ) has emerged as a subject of considerable interest due to its noteworthy compression effic

Ying Chen, Yong Liu, Kai Wu, Qiang Nie

Deep learning-based image matching methods play a crucial role in computer vision, yet they often suffer from substantial computational demands. To tackle this challenge, we present HCPM, an efficient and detector-free local feature-matching method that employs hierarchical pruning to optimize the matching pipeline. In contrast to recent detector-free method

Zean Bao, Maobin Lu, Fang Deng, Jie Chen

In this paper, we investigate the attitude tracking problem of uncertain flexible spacecraft systems subject to external disturbances. In sharp contrast to existing results, the dynamics of flexible spacecraft systems and external disturbances are allowed to be unknown. To deal with the challenges by these unknown factors, we develop a class of nonlinear int

Zhenyuan Li, Yangyang Wei, Xiangmin Shen, Lingzhi Wang

Recent research in both academia and industry has validated the effectiveness of provenance graph-based detection for advanced cyber attack detection and investigation. However, analyzing large-scale provenance graphs often results in substantial overhead. To improve performance, existing detection systems implement various optimization strategies. Yet, as s

Huan Qing

Community detection in multi-layer networks is a crucial problem in network analysis. In this paper, we analyze the performance of two spectral clustering algorithms for community detection within the framework of the multi-layer degree-corrected stochastic block model (MLDCSBM) framework. One algorithm is based on the sum of adjacency matrices, while the ot

Yue Shi, Paul D. Stevenson, Nobuo Hinohara

This work presents a computer program that performs symmetry-unrestricted 3D nuclear time-dependent density function theory (DFT) calculations. The program features the augmented Lagrangian constraint in the static calculation. This allows for the calculation of the potential energy surface. In addition, the code includes the full energy density functionals

Mohamad M Nasr-Azadani, Jean-Luc Chatelain

This paper reviews Trustworthy Artificial Intelligence (TAI) and its various definitions. Considering the principles respected in any society, TAI is often characterized by a few attributes, some of which have led to confusion in regulatory or engineering contexts. We argue against using terms such as Responsible or Ethical AI as substitutes for TAI. And to

Yuanjiong Ying, Xian Huang, Wei Dong

Comprehensive perception of human beings is the prerequisite to ensure the safety of human-robot interaction. Currently, prevailing visual sensing approach typically involves a single static camera, resulting in a restricted and occluded field of view. In our work, we develop an active vision system using multiple cameras to dynamically capture multi-source

Michael Lackner, Behrus Puladi, Jens Kleesiek, Jan Egger

In traumatic medical emergencies, the patients heavily depend on cranioplasty - the craft of neurocranial repair using cranial implants. Despite the improvements made in recent years, the design of a patient-specific implant (PSI) is among the most complex, expensive, and least automated tasks in cranioplasty. Further research in this area is needed. Therefo

Hongjia Zhai, Hai Li, Xingrui Yang, Gan Huang

In this paper, we introduce Vox-Fusion++, a multi-maps-based robust dense tracking and mapping system that seamlessly fuses neural implicit representations with traditional volumetric fusion techniques. Building upon the concept of implicit mapping and positioning systems, our approach extends its applicability to real-world scenarios. Our system employs a v

Shuo Sun, Malcolm Mielle, Achim J. Lilienthal, Martin Magnusson

We propose a dense RGBD SLAM system based on 3D Gaussian Splatting that provides metrically accurate pose tracking and visually realistic reconstruction. To this end, we first propose a Gaussian densification strategy based on the rendering loss to map unobserved areas and refine reobserved areas. Second, we introduce extra regularization parameters to allev

Jiazhou Zhou, Xu Zheng, Yuanhuiyi Lyu, Lin Wang

Event cameras have recently been shown beneficial for practical vision tasks, such as action recognition, thanks to their high temporal resolution, power efficiency, and reduced privacy concerns. However, current research is hindered by 1) the difficulty in processing events because of their prolonged duration and dynamic actions with complex and ambiguous s