May 2024 arXiv papers — page 43

Justin Carpentier, Louis Montaut, Quentin Le Lidec

Whether rigid or compliant, contact interactions are inherent to robot motions, enabling them to move or manipulate things. Contact interactions result from complex physical phenomena, that can be mathematically cast as Nonlinear Complementarity Problems (NCPs) in the context of rigid or compliant point contact interactions. Such a class of complementarity p

Neil Walkinshaw, Michael Foster, Jose Miguel Rojas, Robert M Hierons

Random testing approaches work by generating inputs at random, or by selecting inputs randomly from some pre-defined operational profile. One long-standing question that arises in this and other testing contexts is as follows: When can we stop testing? At what point can we be certain that executing further tests in this manner will not explore previously unt

Xiaopeng Ai, Boyang Chen, Christos Kassapoglou

Delamination is a critical mode of failure that occurs between plies in a composite laminate. The cohesive element, developed based on the cohesive zone model, is widely used for modeling delamination. However, standard cohesive elements suffer from a well-known limit on the mesh density-the element size must be much smaller than the cohesive zone size. This

Andrea Angiuli, Jean-Pierre Fouque, Mathieu Laurière, Mengrui Zhang

Mean Field Control Games (MFCG), introduced in [Angiuli et al., 2022a], represent competitive games between a large number of large collaborative groups of agents in the infinite limit of number and size of groups. In this paper, we prove the convergence of a three-timescale Reinforcement Q-Learning (RL) algorithm to solve MFCG in a model-free approach from

Weiquan Wang, Jun Xiao, Chunping Wang, Wei Liu

Continuous diffusion models have demonstrated their effectiveness in addressing the inherent uncertainty and indeterminacy in monocular 3D human pose estimation (HPE). Despite their strengths, the need for large search spaces and the corresponding demand for substantial training data make these models prone to generating biomechanically unrealistic poses. Th

Gianluca Fontanesi, Anna Guerra, Francesco Guidi, Juan A. Vásquez-Peralvo

In this paper, we consider a scenario with one UAV equipped with a ULA, which sends combined information and sensing signals to communicate with multiple GBS and, at the same time, senses potential targets placed within an interested area on the ground. We aim to jointly design the transmit beamforming with the GBS association to optimize communication perfo

Catharine W. K. Lo, José Francisco Rodrigues

We consider the one and the two obstacles problems for the nonlocal nonlinear anisotropic $g$-Laplacian $\mathcal{L}_g^s$, with $0<s<1$. We prove the strict T-monotonicity of $\mathcal{L}_g^s$ and we obtain the Lewy-Stampacchia inequalities. We consider the approximation of the solutions through semilinear problems, for which we prove a global $L^\infty$-est

Qi Wu, Yubo Zhao, Yifan Wang, Xinhang Liu

While previous approaches to 3D human motion generation have achieved notable success, they often rely on extensive training and are limited to specific tasks. To address these challenges, we introduce Motion-Agent, an efficient conversational framework designed for general human motion generation, editing, and understanding. Motion-Agent employs an open-sou

Abhinandan

For $p \geqslant 3$ and an unramified extension $F/\mathbb{Q}_p$ with perfect residue field, we define a syntomic complex with coefficients in a Wach module over a certain period ring for $F$. We show that our complex computes the crystalline part of the Galois cohomology (in the sense of Bloch and Kato) of the associated crystalline representation of the ab

David Cimasoni, Livio Ferretti, Jessica Liu

We show how the multivariable signature and Alexander polynomial of a colored link can be computed from a single symmetric matrix naturally defined from a colored link diagram. In the case of a single variable, it coincides with the matrix introduced by Kashaev in [arXiv:1801.04632], which was recently proven to compute the Levine-Tristram signature and the

Jia-Lun Li, Yu-Peng Yang, Shuang-Xi Yi, Jian-Ping Hu

As one of the most energetic and brightest events, gamma-ray bursts (GRBs) have been used as a standard candle for cosmological probe. Based on the relevant features of GRBs light curves, a plateau phase followed a decay phase, we obtain X-ray samples of 31 GRBs and optical samples of 50 GRBs, which are thought to be caused by the same physical mechanism. We

Xiaoqian Liu, Xingzhou Lou, Jianbin Jiao, Junge Zhang

Decision making demands intricate interplay between perception, memory, and reasoning to discern optimal policies. Conventional approaches to decision making face challenges related to low sample efficiency and poor generalization. In contrast, foundation models in language and vision have showcased rapid adaptation to diverse new tasks. Therefore, we advoca

Claudio Cicconetti, Dario Sabella, Pietro Noviello, Gennaro Davide Paduanelli

The advent of distributed computing systems will offer great flexibility for application workloads, while also imposing more attention to security, where the future advent and adoption of quantum technology can introduce new security threats. For this reason, the Multi-access Edge Computing (MEC) working group at ETSI has recently started delving into securi

Ana Pérez-Neira, Marc Martinez-Gost, Alphan Şahin, Saeed Razavikia

Over-the-air computation (AirComp) leverages the signal-superposition characteristic of wireless multiple access channels to perform mathematical computations. Initially introduced to enhance communication reliability in interference channels and wireless sensor networks, AirComp has more recently found applications in task-oriented communications, like wire

Hongliu Cao

Text embedding methods have become increasingly popular in both industrial and academic fields due to their critical role in a variety of natural language processing tasks. The significance of universal text embeddings has been further highlighted with the rise of Large Language Models (LLMs) applications such as Retrieval-Augmented Systems (RAGs). While pre

Snehajit Misra, Nabanita Ray

In this article, we investigate the stability of syzygy bundles corresponding to ample and globally generated vector bundles on smooth irreducible projective surfaces.

Michael Joswig

The term "tropical convexity" was coined by Develin and Sturmfels who published a landmark paper with that title in 2004. However, the topic has much older roots and is deeply connected to linear and combinatorial optimization and other areas of mathematics. The purpose of this survey is to sketch how that article contributed to shaping the field of tropical

Yang Zhang, Mingying Li, Huilin Pan, Moyun Liu

Deep learning-based fault detection methods have achieved significant success. In visual fault detection of freight trains, there exists a large characteristic difference between inter-class components (scale variance) but intra-class on the contrary, which entails scale-awareness for detectors. Moreover, the design of task-specific networks heavily relies o

Xinyi Gao, Tong Chen, Wentao Zhang, Yayong Li

The burgeoning volume of graph data presents significant computational challenges in training graph neural networks (GNNs), critically impeding their efficiency in various applications. To tackle this challenge, graph condensation (GC) has emerged as a promising acceleration solution, focusing on the synthesis of a compact yet representative graph for effici

Quan Van Nguyen, Huy Quang Pham, Dan Quang Tran, Thang Kien-Bao Nguyen

Purpose: This study focuses on the development of automated text generation from radiology images, termed diagnostic captioning, to assist medical professionals in reducing clinical errors and improving productivity. The aim is to provide tools that enhance report quality and efficiency, which can significantly impact both clinical practice and deep learning

M. Cherniavskii, D. Gribanov, D. Malyshev, P. M. Pardalos

For integers $k,n \geq 0$ and a cost vector $c \in Z^n$, we study two fundamental integer linear programming (ILP) problems: \[ \text{(Standard Form)} \quad \max\bigl\{c^\top x \colon Ax = b,\ x \in Z^n_{\geq 0}\bigr\} \text{ with } A \in Z^{k \times n}, \text{rank}(A) = k, b \in Z^k, \] \[ \text{(Canonical Form)} \quad \max\bigl\{c^\top x \colon Ax \leq b,\

F. M. Maccagni, W. J. G. de Blok, P. E. Mancera Piña, R. Ragusa

We present the discovery of a low-mass gas-rich low-surface brightness galaxy in the Dorado Group, at a distance of 17.7 Mpc. Combining deep MeerKAT 21-cm observations from the MeerKAT HI Observations of Nearby Galactic Objects: Observing Southern Emitters (MHONGOOSE) survey with deep photometric images from the VST Early-type Galaxy Survey (VEGAS) we find a

Bruno Rando Forastier, Daniel Marín Pina, Mark Gieles, Simon Portegies Zwart

Dynamical interactions in star clusters are an efficient mechanism to produce the coalescing binary black holes (BBHs) that have been detected with gravitational waves (GWs). We want to understand how BBH coalescence can occur during - or after - binary-single interactions with different mass ratios. We perform gravitational scattering experiments of binary-

M. I. Ayzatsky

In this work we present a new approach in representation of wave fields in nonuniform 1-D multilayer medium. This approach is based on the use of a modified homogeneous basis. A new form of coupled equations for describing nonuniform one-directional photonic crystals is proposed. This description can be especially useful to study radiation that originates wh

Jinwoo Kim

This paper considers program synthesis in the context of computational hardness, asking the question: How hard is it to determine whether a given synthesis problem has a solution or not? To answer this question, this paper studies program synthesis for a basic imperative, Turing-complete language IMP, for which this paper proves that program synthesis is $\S

Zihua Zhao, Mengxi Chen, Tianjie Dai, Jiangchao Yao

Noisy correspondence that refers to mismatches in cross-modal data pairs, is prevalent on human-annotated or web-crawled datasets. Prior approaches to leverage such data mainly consider the application of uni-modal noisy label learning without amending the impact on both cross-modal and intra-modal geometrical structures in multimodal learning. Actually, we

Lingdi Meng, Shuo Tang, Zhi Hu, Guo-Li Wang

In this paper, we evaluate the electromagnetic and gravitational form factors as well as the corresponding generalized parton distributions of the electron using the Basis Light-front Quantization approach to QED. We compare our results with those from light-front perturbation theory. We adopt a novel basis with its scale depending on the constituents' longi

Wen Hanlin

In the Vision-and-Language Navigation (VLN) field, agents are tasked with navigating real-world scenes guided by linguistic instructions. Enabling the agent to adhere to instructions throughout the process of navigation represents a significant challenge within the domain of VLN. To address this challenge, common approaches often rely on encoders to explicit

Attilio Santocchia

Search for BSM phenomena is one of the fundamental goals of the LHC experiments. Many BSM models foresee long-lived particles which decay far from the production vertex and a big effort has been done both by the ATLAS and CMS collaborations to detect these long-lived particles. A specific, widely studied, example for such searches is made through the measure

Oleg Gutik

We find anti-isomorphic submonoids $\mathscr{C}_{+}(a,b)$ and $\mathscr{C}_{-}(a,b)$ of the bicyclic monoid $\mathscr{C}(a,b)$ with the following properties: every Hausdorff left-continuous (right-continuous) topology on $\mathscr{C}_{+}(a,b)$ ($\mathscr{C}_{-}(a,b)$) is discrete and there exists a compact Hausdorff topological monoid $S$ which contains $\ma

Giambattista Giacomin, Marco Zamparo

We focus on the localized phase of pinning models with i.i.d. site disorder on which we assume only that the moment generating function is bounded in a neighborhood of the origin. We develop quantitative correlation functions estimates for local observables that entail quantitative $C^\infty$ estimates on the free energy density, showing in particular that i

M. Firouzi Parizi, A. Alijani, M. A. Dehghan

Recently, frame multipliers, pair frames, and controlled frames have been investigated to improve the numerical efficiency of iterative algorithms for inverting the frame operator and other applications of frames. In this paper, the concept of biframe is introduced for a Hilbert space. A biframe is a pair of sequences in a Hilbert space that applies to an in

Ruike Wu, Yanrong Yang, Han Lin Shang, Huanjun Zhu

Robust estimation for modern portfolio selection on a large set of assets becomes more important due to large deviation of empirical inference on big data. We propose a distributionally robust methodology for high-dimensional mean-variance portfolio problem, aiming to select an optimal conservative portfolio allocation by taking distribution uncertainty into

Marc Michalke, Fin Gentzen, Admela Jukan, Kfir Toledo

In this paper, we conduct an experimental study to provide a general sense of the application response time implications that inter-cluster communication experiences at the edge at the example of a specific IoT-edge-cloud contiuum solution from the EU Project ICOS called ClusterLink. We create an environment to emulate different networking topologies that in

Emir Baysazan, Tolga Birkandan, Ismail Eyuphan Unver

Wave equations for some curved spacetimes may involve functions that prevent a solution in a closed form. In some cases, these functions can be eliminated by transformations and the solutions can be found analytically. In the cases where such transformations are not available, the infinite series expansions of these functions can be convoluted with the power

Abdul Qayyum, Moona Mazher, Angela Lee, Jose A Solis-Lemus

Unlike Right Atrium (RA), Left Atrium (LA) presents distinctive challenges, including much thinner myocardial walls, complex and irregular morphology, as well as diversity in individual's structure, making off-the-shelf methods designed for the Left Ventricle (LV) may not work in the context of the left atrium. To overcome aforementioned challenges, we are t

Robert Eymard, Thierry Gallouët, Raphaele Herbin

We consider a finite volume scheme with two-point flux approximation (TPFA) to approximate a Laplace problem when the solution exhibits no more regularity than belonging to $H^1_0(\Omega)$. We establish in this case some error bounds for both the solution and the approximation of the gradient component orthogonal to the mesh faces. This estimate is optimal,

Simone Bocca, Amarsanaa Ganbold, Tsolmon Zundui

Data reuse is fundamental for reducing the data integration effort required to build data supporting new applications, especially in data scarcity contexts. However, data reuse requires to deal with data heterogeneity, which is always present in data coming from different sources. Such heterogeneity appears at different levels, like the language used by the

Adrien Gourgout, Arthur Marguerite, Benoît Fauqué, Kamran Behnia

Electron-electron collisions lead to a T-square component in the electrical resistivity of Fermi liquids. The case of liquid $^3$He illustrates that the \textit{thermal} resitivity of a Fermi liquid has a T-square term, expressed in m$\cdot$W$^{-1}$. Its natural units are $\hbar/k_FE_F^2$. Here, we present a high-resolution study of the thermal conductivity

Ross G. Shepherd, Edouard Boujo, Mathieu Sellier

We derive a generalised asymptotic model for the flow of a thin fluid film over an arbitrarily-parameterised non-axisymmetric curved substrate surface based on the lubrication approximation. In addition to surface tension, gravity, and centrifugal force, our model incorporates the effects of the Coriolis force and disjoining pressure, together with a non-uni

Qi Si, Zhi Xia Yang

Twin support vector machine (TSVM) is a very classical and practical classifier for pattern classification. However, the traditional TSVM has two limitations. Firstly, it uses the L_2-norm distance metric that leads to its sensitivity to outliers. Second, it needs to select the appropriate kernel function and the kernel parameters for nonlinear classificatio

Tien Rahayu Tulili, Ayushi Rastogi, Andrea Capiluppi

Collaborative software development happens in teams, that cooperate on shared artefacts, and discuss development on online platforms. Due to the complexity of development and the variety of teams, software components often act as effective containers for parallel work and teams. Past research has shown how communication between team members, especially in an

Hongtao Wang, Rongyu Feng, Liangyi Wu, Mutian Liu

In seismic exploration, identifying the first break (FB) is a critical component in establishing subsurface velocity models. Various automatic picking techniques based on deep neural networks have been developed to expedite this procedure. The most popular class is using semantic segmentation networks to pick on a shot gather called 2-dimensional (2-D) picki

Sergey Galkin, Jianxun Hu, Hiroshi Iritani, Huazhong Ke

We continue investigation of asymptotics of quantum differential equation for Fano manifolds, with a special regard to Gamma conjecture I and its underlying Conjecture $\mathcal{O}$. We introduce the A-model conifold value, a symplectic invariant of a Fano manifold, and propose modifications for Gamma conjecture I based on this new definition. We discuss an

Yuefeng Peng, Jaechul Roh, Subhransu Maji, Amir Houmansadr

We introduce One-Shot Label-Only (OSLO) membership inference attacks (MIAs), which accurately infer a given sample's membership in a target model's training set with high precision using just \emph{a single query}, where the target model only returns the predicted hard label. This is in contrast to state-of-the-art label-only attacks which require $\sim6000$

Michał Popławski

A finite family $\mathcal{F}=\{f_1,\ldots,f_n\}$ of continuous selfmaps of a given metric space $X$ is called an iterated function system (shortly IFS). In a case of contractive selfmaps of a complete metric space is well-known that IFS has an unique attractor \cite{Hu}. However, in \cite{LS} authors studied highly non-contractive IFSs, i.e. such families $\

Saurav Pandey, Abhishek Dhar, Anupam Kundu

We study the evolution of a classical harmonic chain with nearest-neighbor interactions starting from domain wall initial conditions. The initial state is taken to be either a product of two Gibbs Ensembles (GEs) with unequal temperatures on the two halves of the chain or a product of two Generalized Gibbs Ensembles (GGEs) with different parameters in the tw

Luca Capizzi, Jiaozi Wang, Xiansong Xu, Leonardo Mazza

The eigenstate thermalization hypothesis (ETH) describes the properties of diagonal and off-diagonal matrix elements of local operators in the eigenenergy basis. In this work, we propose a relation between (i) the singular behaviour of the off-diagonal part of ETH at small energy differences, and (ii) the smooth profile of the diagonal part of ETH as a funct

Marcin Płodzień, Jan Chwedeńczuk, Maciej Lewenstein

The standard way to generate many-body quantum correlations is via a dynamical protocol: an initial product state is transformed by interactions that generate non-classical correlations at later times. Here, we show that many-body Bell correlations are inherently present in the eigenstates of a variety of spin-1/2 chains. In particular, we show that the eige

Sven Teufel, Jörg Gamerdinger, Jan-Patrick Kirchner, Georg Volk

To ensure safe operation of autonomous vehicles in complex urban environments, complete perception of the environment is necessary. However, due to environmental conditions, sensor limitations, and occlusions, this is not always possible from a single point of view. To address this issue, collective perception is an effective method. Realistic and large-scal

Yiftach Halevy, Yali Cina, Omer Feldman, David Groswasser

Matter-wave interferometry plays a significant role in scientific research and technological applications. While position-momentum phase-space squeezing has been demonstrated to increase the coherence of atom sources by reducing momentum spread, we theoretically investigate the potential advantages of the opposite squeezing. As a case study, we analytically

M. Halilsoy, V. Memari

The spinning electromagnetic universe, known also as the Rotating Bertotti-Robinson(RBR) spacetime is considered as a model to represent our cosmos. The model derives from different physical considerations, such as colliding waves, throat region, and near horizon geometry of the Kerr-Newman black hole. Our interest is whether such a singularity-free spinning

Minh H. Vu, Daniel Edler, Carl Wibom, Tommy Löfstedt

Deep learning (DL) models require extensive data to achieve strong performance and generalization. Deep generative models (DGMs) offer a solution by synthesizing data. Yet current approaches for tabular data often fail to preserve feature correlations and distributions during training, struggle with multi-metric hyperparameter selection, and lack comprehensi

Cheng Zhang, Qi Zhang, Wei Zhong, Ming-Ming Du

Measurement-device-independent quantum secret sharing (MDI-QSS) can eliminate all the security loopholes associated with imperfect measurement devices and greatly enhance QS's security under practical experimental condition. MDI-QSS requires each communication user to send single photon to the measurement party for the coincident measurement. However, the un

Arle Lommel, Serge Gladkoff, Alan Melby, Sue Ellen Wright

The year 2024 marks the 10th anniversary of the Multidimensional Quality Metrics (MQM) framework for analytic translation quality evaluation. The MQM error typology has been widely used by practitioners in the translation and localization industry and has served as the basis for many derivative projects. The annual Conference on Machine Translation (WMT) sha

Olivier Golinelli

We study a tree coloring model introduced by Guidon (2018), initially based on an analogy with a remote control system of a rail yard, seen as switches on a binary tree. For a given binary tree, we formalize the constraints on the coloring, in particular the distribution of the nodes among colors. Following Guidon, we are interested in balanced colorings i.e

Louis Fournier, Adel Nabli, Masih Aminbeidokhti, Marco Pedersoli

The performance of deep neural networks is enhanced by ensemble methods, which average the output of several models. However, this comes at an increased cost at inference. Weight averaging methods aim at balancing the generalization of ensembling and the inference speed of a single model by averaging the parameters of an ensemble of models. Yet, naive averag

Pierre-François Marteau

We introduce and detail an atypical neural network architecture, called time elastic neural network (teNN), for multivariate time series classification. The novelty compared to classical neural network architecture is that it explicitly incorporates time warping ability, as well as a new way of considering attention. In addition, this architecture is capable

Anton Uranga, Elena Akhmatskaya, Dmitri Sokolovski

The analytical continuation of classical equations of motion to complex times suggests that a tunnelling particle spends in the barrier an imaginary duration $i|\mathcal T|$. Does this mean that it takes a finite time to tunnel, or should tunnelling be seen as an instantaneous process? It is well known that examination of the adiabatic limit in a small addit

Xiaolu Wang, Yuchang Sun, Hoi-To Wai, Jun Zhang

We consider the distributed learning problem with data dispersed across multiple workers under the orchestration of a central server. Asynchronous Stochastic Gradient Descent (SGD) has been widely explored in such a setting to reduce the synchronization overhead associated with parallelization. However, the performance of asynchronous SGD algorithms often de

Zhengchuan Chen, Kang Lang, Nikolaos Pappas, Howard H. Yang

Timely status updating is the premise of emerging interaction-based applications in the Internet of Things (IoT). Using redundant devices to update the status of interest is a promising method to improve the timeliness of information. However, parallel status updating leads to out-of-order arrivals at the monitor, significantly challenging timeliness analysi

Yuzi Yan, Jialian Li, Yipin Zhang, Dong Yan

This paper presents an in-depth examination of the evolution and interplay of cognitive and expressive capabilities in large language models (LLMs), with a specific focus on Baichuan-7B and Baichuan-33B, an advanced bilingual (Chinese and English) LLM series. We define and explore the model's cognitive and expressive capabilities through linear representatio

Gal Binyamini

We introduce the class of \emph{Log-Noetherian} (LN) functions. These are holomorphic solutions to algebraic differential equations (in several variables) with logarithmic singularities. We prove an upper bound on the number of solutions for systems of LN equations, resolving in particular Khovanskii's conjecture for Noetherian functions. Consequently, we sh

Yann Damour, Alejandro Gallo, Anthony Scemama

We introduce a novel algorithm that leverages stochastic sampling techniques to compute the perturbative triples correction in the coupled-cluster (CC) framework. By combining elements of randomness and determinism, our algorithm achieves a favorable balance between accuracy and computational cost. The main advantage of this algorithm is that it allows for t

Rony Abecidan, Vincent Itier, Jérémie Boulanger, Patrick Bas

The proliferation of image manipulation for unethical purposes poses significant challenges in social networks. One particularly concerning method is Image Steganography, allowing individuals to hide illegal information in digital images without arousing suspicions. Such a technique pose severe security risks, making it crucial to develop effective steganaly

Mengtan Zhang, Yi Feng, Qijun Chen, Rui Fan

There has been a recent surge of interest in learning to perceive depth from monocular videos in an unsupervised fashion. A key challenge in this field is achieving robust and accurate depth estimation in challenging scenarios, particularly in regions with weak textures or where dynamic objects are present. This study makes three major contributions by delvi

Tiziana D'Alessandro, Cristina Carmona-Duarte, Claudio De Stefano, Moises Diaz

Alzheimer's disease is one of the most incisive illnesses among the neurodegenerative ones, and it causes a progressive decline in cognitive abilities that, in the worst cases, becomes severe enough to interfere with daily life. Currently, there is no cure, so an early diagnosis is strongly needed to try and slow its progression through medical treatments. H

Quirin Vogel

We prove a large deviation principle for deep neural networks with Gaussian weights and at most linearly growing activation functions, such as ReLU. This generalises earlier work, in which bounded and continuous activation functions were considered. In practice, linearly growing activation functions such as ReLU are most commonly used. We furthermore simplif

Pieter C. van der Kruit

Jacobus C. Kapteyn is regarded as one of the coryfees of the University of Groningen. Part of his legacy is two paintings of him by Dutch painter Jan Pieter Veth. One, showing him at his desk, decorates the Kapteyn Room in the Kapteyn Astronomical Institute, and the other one, displaying him in academic attire, is in the University's gallery of professors in

Justin Reverdi, Sixin Zhang, Saïd Aoues, Fabrice Gamboa

In Vapor Cycle Systems, the mass flow sensor playsa key role for different monitoring and control purposes. However,physical sensors can be inaccurate, heavy, cumbersome, expensive orhighly sensitive to vibrations, which is especially problematic whenembedded into an aircraft. The conception of a virtual sensor, basedon other standard sensors, is a good alte

Noriaki Kawaguchi

In [13], for any continuous self-map of a compact metric space with s-limit shadowing, by using a $G_\delta$-partition of the phase space, a global description of Li-Yorke type chaos (with respect to several particular Furstenberg families) is obtained. In this paper, we complement the results in [13] by some results concerning the s-limit shadowing and gene

Chen Zhang, Lecheng Jia, Wei Zhang, Ning Wen

The advent of modern data processing has led to an increasing tendency towards interdisciplinarity, which frequently involves the importation of different technical approaches. Consequently, there is an urgent need for a unified data control system to facilitate the integration of varying libraries. This integration is of profound significance in acceleratin

Robert Vertesi

Jet substructure in heavy-ion collisions is a rapidly evolving area with lots of intriguing new measurements. This contribution presents a selection of recent jet-substructure measurements from experiments at the LHC, in particular, soft-drop groomed radii of jets and reclustered large-radius jets from ATLAS, jet axis difference and generalized jet angularit

Junwen Qiu, Bohao Ma, Andre Milzarek

The stochastic gradient descent method with momentum (SGDM) is a common approach for solving large-scale and stochastic optimization problems. Despite its popularity, the convergence behavior of SGDM remains less understood in nonconvex scenarios. This is primarily due to the absence of a sufficient descent property and challenges in simultaneously controlli

Simon Vellas, Bill Psomas, Kalliopi Karadima, Dimitrios Danopoulos

Real-time analysis of Martian craters is crucial for mission-critical operations, including safe landings and geological exploration. This work leverages the latest breakthroughs for on-the-edge crater detection aboard spacecraft. We rigorously benchmark several YOLO networks using a Mars craters dataset, analyzing their performance on embedded systems with

Quentin Japhet, Dimitri Watel, Dominique Barth, Marc-Antoine Weisser

A line digraph $L(G) = (A, E)$ is the digraph constructed from the digraph $G = (V, A)$ such that there is an arc $(a,b)$ in $L(G)$ if the terminal node of $a$ in $G$ is the initial node of $b$. The maximum number of arcs in a line digraph with $m$ nodes is $(m/2)^2 + (m/2)$ if $m$ is even, and $((m - 1)/2)^2 + m - 1$ otherwise. For $m \geq 7$, there is only

Zilu Guo, Qing Wang, Jun Du, Jia Pan

In this paper, we propose a variance-preserving interpolation framework to improve diffusion models for single-channel speech enhancement (SE) and automatic speech recognition (ASR). This new variance-preserving interpolation diffusion model (VPIDM) approach requires only 25 iterative steps and obviates the need for a corrector, an essential element in the e

Franca Corradini, Carlo Grigioni, Alessandro Antonucci, Jérôme Guzzi

Safe road crossing by autonomous wheelchairs can be affected by several environmental factors such as adverse weather conditions influencing the accuracy of artificial vision. Previous studies have addressed experimental evaluation of multi-sensor information fusion to support road-crossing decisions in autonomous wheelchairs. In this study, we focus on the

Davide Basso, Luca Bortolussi, Mirjana Videnovic-Misic, Husni Habal

This paper presents an artificial intelligence driven methodology to reduce the bottleneck often encountered in the analog ICs layout phase. We frame the floorplanning problem as a Markov Decision Process and leverage reinforcement learning for automatic placement generation under established topological constraints. Consequently, we introduce Steiner tree-b

Seung-Hyeon Hyeon

Let $K$ be a mixed-characteristic local field. For an integer $m \geq 0$, we denote by $K^m / K$ the maximal $m$-step solvable extension of $K$, and by $G_K^m$ the maximal $m$-step solvable quotient of the absolute Galois group $G_K$ of $K$. We regard $G_K$ and its quotients as filtered profinite groups via the respective upper-numbering ramification filtrat

Hugo Chambon, Didier Fraix-Burnet

We present the first unsupervised classification of spaxels in hyperspectral images of individual galaxies. Classes identify regions by spectral similarity and thus take all the information into account that is contained in the data cubes (spatial and spectral).We used Gaussian mixture models in a latent discriminant subspace to find clusters of spaxels. The

Thomas Britz, Himadri Shekhar Chakraborty, Tsuyoshi Miezaki

In this paper, we present the harmonic generalizations of well-known polynomials of codes over finite fields, namely the higher weight enumerators and the extended weight enumerators, and we derive the correspondences between these weight enumerators. Moreover, we present the harmonic generalization of Greene's Theorem for the higher (resp. extended) weight

Qian Wang, Abdelrahman Eldesokey, Mohit Mendiratta, Fangneng Zhan

We introduce the first zero-shot approach for Video Semantic Segmentation (VSS) based on pre-trained diffusion models. A growing research direction attempts to employ diffusion models to perform downstream vision tasks by exploiting their deep understanding of image semantics. Yet, the majority of these approaches have focused on image-related tasks like sem

Moein Khajehnejad, Forough Habibollahi, Aswin Paul, Adeel Razi

How do biological systems and machine learning algorithms compare in the number of samples required to show significant improvements in completing a task? We compared the learning efficiency of in vitro biological neural networks to the state-of-the-art deep reinforcement learning (RL) algorithms in a simplified simulation of the game `Pong'. Using DishBrain

Kuranage Roche Rayan Ranasinghe, Hyeon Seok Rou, Giuseppe Thadeu Freitas de Abreu, Takumi Takahashi

We propose new schemes for joint channel and data estimation (JCDE) and radar parameter estimation (RPE) in doubly-dispersive channels, such that integrated sensing and communications (ISAC) is enabled by user equipment (UE) independently performing JCDE, and base stations (BSs) performing RPE. The contributed JCDE and RPE schemes are designed for waveforms

Jian Xie, Zihao Huo, Xin Lu, Zuo Feng

Fractional Chern insulators (FCIs) showing a transport effect with fractionally quantized Hall plateaus emerging under zero magnetic field, provide a radically new opportunity to engineer topological quantum electronics. By construction of topological flat band with moire engineering, intrinsic FCIs have been observed in twisted MoTe2 system and rhombohedral

Catherine Bénéteau, Dmitry Khavinson, Daniel Seco

We give an example of a function $f$ non-vanishing in the closed bidisk and the affine polynomial minimizing the norm of $1-pf$ in the Hardy space of the bidisk among all affine polynomials $p$. We show that this polynomial vanishes inside the bidisk. This provides a counterexample to the weakest form of a conjecture due to Shanks that has been open since 19

Adeline Degremont, Catherine Bisquay, Pierre-Alain Jachiet

Introduction: The HAS conducted a study in 2018 using the French National Health Data System (SNDS) on the care pathway of patients with epilepsy. This study used 2 algorithms to identify patients with epilepsy, based on hospitalization for epilepsy, insurance for chronic severe epilepsy, and antiepileptic drug (AE) dispensing, with exclusion of AEs not spec

Yitong Li, Igor Yakushev, Dennis M. Hedderich, Christian Wachinger

Positron emission tomography (PET) is a well-established functional imaging technique for diagnosing brain disorders. However, PET's high costs and radiation exposure limit its widespread use. In contrast, magnetic resonance imaging (MRI) does not have these limitations. Although it also captures neurodegenerative changes, MRI is a less sensitive diagnostic

Shao-Jun Zhang

The Comisso-Asenjo mechanism is a novel mechanism proposed recently to extract energy from black holes through magnetic reconnection of the surrounding charged plasma, in which the magnetic field plays a crucial role. In this work, we revisit this process by taking into account the backreaction of the magnetic field on the black hole's geometry. We employ th

Janis Zenkner, Lukas Dierkes, Tobias Sesterhenn, Chrisitan Bartelt

LambdaBeam is a state-of-the-art, execution-guided algorithm for program synthesis that utilizes higher-order functions, lambda functions, and iterative loops within a Domain-Specific Language (DSL). LambdaBeam generates each program from scratch but does not take advantage of the frequent recurrence of program blocks or subprograms commonly found in specifi

Fengfan Zhou, Qianyu Zhou, Hefei Ling, Xuequan Lu

Adversarial attacks on Face Recognition (FR) systems have demonstrated significant effectiveness against standalone FR models. However, their practicality diminishes in complete FR systems that incorporate Face Anti-Spoofing (FAS) models, as these models can detect and mitigate a substantial number of adversarial examples. To address this critical yet under-

Amit Chakraborty, Dilip Kumar Ghosh, Najimuddin Khan, Stefano Moretti

We establish the possibility of having a pseudo-Nambu-Goldstone boson (pNGB) Dark Matter (DM) candidate in the inspired Froggatt-Nielsen Singlet Model (iFNSM) wherein a direct connection exists between the DM mass and new flavon symmetry-breaking scale. We find a considerable allowed region of parameter space for the ensuing pseudoscalar DM, which is depende

Olivier Golinelli

We study a tree coloring model introduced by Guidon (2018), initially based on an analogy with a remote control system of a rail yard, seen as a switch tree. For a given rooted tree, we formalize the constraints on the coloring, in particular on the minimum number of colors, and on the distribution of the nodes among colors. We show that the sequence $(a_1,a

Sara Roosta, Marcus Elstner, Weiwei Xie

Organic semiconductors (OSCs) have received much attention as promising materials for electronic devices. In this study, we investigate the impact of halogen groups on the charge transport properties of n-type OSC-6,13 bis ((triisopropylsilyl) ethynyl)-5,7,12,14-tetraazapentacene (TIPS-TAP). The computed mobilities for TAPs substituted with F and Cl exhibit

Laurent Busé, Pablo Mazón

We provide effective methods to construct and manipulate trilinear birational maps $\phi:(\mathbb{P}^1)^3\dashrightarrow \mathbb{P}^3$ by establishing a novel connection between birationality and tensor rank. These yield four families of nonlinear birational transformations between 3D spaces that can be operated with enough flexibility for applications in co

Laura Angeloni, Danilo Costarelli, Chiara Darielli

In this paper we introduce a new family of Bernstein-type exponential polynomials on the hypercube $[0, 1]^d$ and study their approximation properties. Such operators fix a multidimensional version of the exponential function and its square. In particular, we prove uniform convergence, by means of two different approaches, as well as a quantitative estimate

Zhenyang Li, Yangyang Guo, Kejie Wang, Xiaolin Chen

Visual Commonsense Reasoning (VCR) calls for explanatory reasoning behind question answering over visual scenes. To achieve this goal, a model is required to provide an acceptable rationale as the reason for the predicted answers. Progress on the benchmark dataset stems largely from the recent advancement of Vision-Language Transformers (VL Transformers). Th

Xun Liang, Simin Niu, Zhiyu li, Sensen Zhang

Retrieval-Augmented Generation (RAG) offers a cost-effective approach to injecting real-time knowledge into large language models (LLMs). Nevertheless, constructing and validating high-quality knowledge repositories require considerable effort. We propose a pre-retrieval framework named Pseudo-Graph Retrieval-Augmented Generation (PG-RAG), which conceptualiz

Richard Elvira, Juan D. Tardós, José M. M. Montiel

Monocular visual simultaneous localization and mapping (V-SLAM) is nowadays an irreplaceable tool in mobile robotics and augmented reality, where it performs robustly. However, human colonoscopies pose formidable challenges like occlusions, blur, light changes, lack of texture, deformation, water jets or tool interaction, which result in very frequent tracki