August 2024 arXiv papers — page 2

Yuxiang Guo, Faizan Siddiqui, Yang Zhao, Rama Chellappa

Predicting and reasoning how a video would make a human feel is crucial for developing socially intelligent systems. Although Multimodal Large Language Models (MLLMs) have shown impressive video understanding capabilities, they tend to focus more on the semantic content of videos, often overlooking emotional stimuli. Hence, most existing MLLMs fall short in

Bohao Zhang, Ram Vasudevan

Performing trajectory design for humanoid robots with high degrees of freedom is computationally challenging. The trajectory design process also often involves carefully selecting various hyperparameters and requires a good initial guess which can further complicate the development process. This work introduces a generalized gait optimization framework that

Pablo Dorta-González, Alexis Jorge López-Puig, María Isabel Dorta-González, Sara M. González-Betancor

The integration of generative artificial intelligence technology into research environments has become increasingly common in recent years, representing a significant shift in the way researchers approach their work. This paper seeks to explore the factors underlying the frequency of use of generative AI amongst researchers in their professional environments

Synim Selimi, Blerim Rexha, Kamer Vishi

The rapid evolution of the Internet, particularly the emergence of Web3, has transformed the ways people interact and share data. Web3, although still not well defined, is thought to be a return to the decentralization of corporations' power over user data. Despite the obsolescence of the idea of building systems to detect and prevent cyber intrusions, t

Ritwik Raj Saxena

Traditional medical basic sciences educational approaches follow a one-size-fits-all model, neglecting the diverse learning styles of individual students. I propose an intelligent AI companion which will fill this gap by providing on-the-fly solutions to students' questions in the context of not only USMLE Step 1 but also other similar examinations in ot

Eren Kurshan, Paul Franzon

3D integration offers key advantages in improving system performance and efficiency for the End-of-Scaling era. It enables the incorporation of heterogeneous system components and disparate technologies, eliminates off-chip communication constraints, reduces on-chip latency and total power dissipation. Moreover, AIs demand for increased computational power,

Shu Hu, George H. Chen

We propose a general approach for encouraging fairness in survival analysis models based on minimizing a worst-case error across all subpopulations that occur with at least a user-specified probability. This approach can be used to convert many existing survival analysis models into ones that simultaneously encourage fairness, without requiring the user to s

Faisal Zaki Roshan, Abhishek Ahuja, Fateme Rajabiyazdi

The healthcare system collects extensive data, encompassing patient administrative information, clinical measurements, and home-monitored health metrics. To support informed decision-making in patient care and treatment management, it is essential to review and analyze these diverse data sources. Data visualization is a promising solution to navigate healthc

A. Leone De Castris, C. Thomas

Governments, industry, and other actors involved in governing AI technologies around the world agree that, while AI offers tremendous promise to benefit the world, appropriate guardrails are required to mitigate risks. Global institutions, including the OECD, the G7, the G20, UNESCO, and the Council of Europe, have already started developing frameworks for e

Esam Ghaleb, Bulat Khaertdinov, Wim Pouw, Marlou Rasenberg

In face-to-face dialogues, the form-meaning relationship of co-speech gestures varies depending on contextual factors such as what the gestures refer to and the individual characteristics of speakers. These factors make co-speech gesture representation learning challenging. How can we learn meaningful gestures representations considering gestures' variab

Woon-Seng Gan, Santi Peksi, Chung Kwan Lai, Yen Theng Lee

This paper introduces a novel portable and scalable Active Noise Mitigation (PSANM) system designed to reduce low-frequency noise from construction machinery. The PSANM system consists of portable units with autonomous capabilities, optimized for stable performance within a specific power range. An adaptive control algorithm with a variable penalty factor pr

Anna-Maria Nau, Phillip Ditto, Dawnie Wolfe Steadman, Audris Mockus

Accurately assessing the postmortem interval (PMI) is an important task in forensic science. Some of the existing techniques use regression models that use a decomposition score to predict the PMI or accumulated degree days (ADD), however, the provided formulas are based on very small samples and the accuracy is low. With the advent of Big Data, much larger

Adrian Marius Dumitran, Adrian Catalin Badea, Stefan-Gabriel Muscalu

This study explores the performance of large language models (LLMs) in solving competitive programming problems from the Romanian Informatics Olympiad at the county level. Romania, a leading nation in computer science competitions, provides an ideal environment for evaluating LLM capabilities due to its rich history and stringent competition standards. We co

Jiashi Yang

This short note is concerned with the rotational invariance of the stored energy density in continuum physics as a scalar function of a few vectors. A simple derivation is presented for the determination of the general form of the energy density in the case of a two-dimensional space. It is also shown that the general form of the energy density so determined

Ibrahim Alshehri, Adnan Alshehri, Abdulrahman Almalki, Majed Bamardouf

The increasing complexity and scale of modern digital environments have exposed significant gaps in traditional cybersecurity penetration testing methods, which are often time-consuming, labor-intensive, and unable to rapidly adapt to emerging threats. There is a critical need for an automated solution that can efficiently identify and exploit vulnerabilitie

Ergon Cugler de Moraes Silva

Brazilian communities on Telegram have increasingly turned to apocalyptic and survivalist theories, especially in times of crisis such as the COVID-19 pandemic, where narratives of occultism and esotericism find fertile ground. Therefore, this study aims to address the research question: how are Brazilian conspiracy theory communities on apocalypse, survival

Fatemeh Chajaei, Hossein Bagheri

Climate models lack the necessary resolution for urban climate studies, requiring computationally intensive processes to estimate high resolution air temperatures. In contrast, Data-driven approaches offer faster and more accurate air temperature downscaling. This study presents a data-driven framework for downscaling air temperature using publicly available

Xiaojun Xiao, Sen Shen, Qiming Bao, Hongfei Rong

In fine-tuning large language models (LLMs), conserving computational resources while maintaining effectiveness and improving outcomes within the same computational constraints is crucial. The Low-Rank Adaptation (LoRA) strategy balances efficiency and performance in fine-tuning large models by reducing the number of trainable parameters and computational co

Kaihui Chen, Hao Yi, Qingyang Li, Tianyu Qi

Enhancing the conformity of large language models (LLMs) to human preferences remains an ongoing research challenge. Recently, offline approaches such as Direct Preference Optimization (DPO) have gained prominence as attractive options due to offering effective improvement in simple, efficient, and stable without interactions with reward models. However, the

Ergon Cugler de Moraes Silva

Interest in extraterrestrial phenomena and conspiracy theories involving UFOs and reptilians has been growing on Brazilian Telegram, especially in times of global uncertainty, such as during the COVID-19 pandemic. Therefore, this study aims to address the research question: how are Brazilian conspiracy theory communities on UFO, universe, reptilians and crea

Rajasekhar Anguluri, Anamitra Pal

Localizing sources of troublesome oscillations, particularly forced oscillations (FOs), in power systems has received considerable attention over the last few years. This is driven in part by the massive deployment of phasor measurement units (PMUs) that capture these oscillations when they occur; and in part by the increasing incidents of FOs due to malfunc

Yangfan Deng, Hamad Albidah, Ahmed Dallal, Jijun Yin

Sleep is crucial for human health, and EEG signals play a significant role in sleep research. Due to the high-dimensional nature of EEG signal data sequences, data visualization and clustering of different sleep stages have been challenges. To address these issues, we propose a two-stage hierarchical and explainable feature selection framework by incorporati

Lin Ge, Yang Xu, Jianing Chu, David Cramer

Today's top advertisers typically manage hundreds of campaigns simultaneously and consistently launch new ones throughout the year. A crucial challenge for marketing managers is determining the optimal allocation of limited budgets across various ad lines in each campaign to maximize cumulative returns, especially given the huge uncertainty in return out

Ivan Arraut, Enrique Arrieta-Diaz

The origins of neutrino masses is one of the biggest mysteries in modern physics since they are beyond the realm of the Standard Model. As massive particles, neutrinos undergo flavor oscillations throughout their propagation. In this paper we show that when a neutrino oscillates from a flavor state α to a flavor state \b{eta}, it follows three possible paths

Tomer Ezra

We study a variant of the single-choice prophet inequality problem where the decision-maker does not know the underlying distribution and has only access to a set of samples from the distributions. Rubinstein et al. [2020] showed that the optimal competitive-ratio of $\frac{1}{2}$ can surprisingly be obtained by observing a set of $n$ samples, one from each

Hanxin Zhu, Tianyu He, Anni Tang, Junliang Guo

Significant progress has been made in text-to-video generation through the use of powerful generative models and large-scale internet data. However, substantial challenges remain in precisely controlling individual concepts within the generated video, such as the motion and appearance of specific characters and the movement of viewpoints. In this work, we pr

Yuanwei Li, Elizaveta Ivanova, Martins Bruveris

Automatic image anomaly detection is important for quality inspection in the manufacturing industry. The usual unsupervised anomaly detection approach is to train a model for each object class using a dataset of normal samples. However, a more realistic problem is zero-/few-shot anomaly detection where zero or only a few normal samples are available. This ma

Philippe Spalart, Kenneth Jansen, Gary Coleman

A pair of Direct Numerical Simulations is used to investigate curvature and pressure effects. One has a Gaussian test bump and a straight opposite wall, while the other has a straight test wall and a blowing/suction distribution on an opposite porous boundary, adjusted to produce the same pressure distribution. The calculation of the transpiration distributi

William Bjorndahl, Jack Easton, Austin Modoff, Eric C. Larson

Spiking neural networks (SNNs) are the third generation of neural networks that are biologically inspired to process data in a fashion that emulates the exchange of signals in the brain. Within the Computer Vision community SNNs have garnered significant attention due in large part to the availability of event-based sensors that produce a spatially resolved

Wenxuan Wang

Large language models (LLMs), such as ChatGPT, have rapidly penetrated into people's work and daily lives over the past few years, due to their extraordinary conversational skills and intelligence. ChatGPT has become the fastest-growing software in terms of user numbers in human history and become an important foundational model for the next generation o

S. Qi, H. Moore, N. Hogade, D. Milojicic

Serverless computing is an emerging cloud computing paradigm that can reduce costs for cloud providers and their customers. However, serverless cloud platforms have stringent performance requirements (due to the need to execute short duration functions in a timely manner) and a growing carbon footprint. Traditional carbon-reducing techniques such as shutting

Lynnyngs K. Arruda, Nikolai V. Chemetov, Fernanda Cipriano

This article studies the Stochastic Degasperis-Procesi (SDP) equation on $\mathbb{R}$ with an additive noise. Applying the kinetic theory, and considering the initial conditions in $L^2(\mathbb{R})\cap L^{2+δ}(\mathbb{R})$, for arbitrary small $δ>0$, we establish the existence of a global pathwise solution. Restricting to the particular case of zero noise, o

Fazle Rahat, M Shifat Hossain, Md Rubel Ahmed, Sumit Kumar Jha

Scaling laws dictate that the performance of AI models is proportional to the amount of available data. Data augmentation is a promising solution to expanding the dataset size. Traditional approaches focused on augmentation using rotation, translation, and resizing. Recent approaches use generative AI models to improve dataset diversity. However, the generat

Burak Kaya, Mahmut Kuzucuoğlu, Patrizia Longobardi, Mercede Maj

The structure of automorphism groups of $κ$-existentially closed groups are studied by Kaya-Kuzucuoğlu in 2022. It was proved that Aut(G) is the union of subgroups of level preserving automorphisms and $|Aut(G)|=2^κ$ whenever $κ$ is an inaccessible cardinal and $G$ is the unique $κ$-existentially closed group of cardinality $κ$. The cardinality of the automo

Jacqueline Lammert, Nicole Pfarr, Leonid Kuligin, Sonja Mathes

Rare gynecological tumors (RGTs) present major clinical challenges due to their low incidence and heterogeneity. The lack of clear guidelines leads to suboptimal management and poor prognosis. Molecular tumor boards accelerate access to effective therapies by tailoring treatment based on biomarkers, beyond cancer type. Unstructured data that requires manual

Shih-Yu Chang

This paper presents significant advancements in tensor analysis and the study of random walks on manifolds. It introduces new tensor inequalities derived using the Mond-Pecaric method, which enriches the existing mathematical tools for tensor analysis. This method, developed by mathematicians Mond and Pecaric, is a powerful technique for establishing inequal

Maximilian Fels, Lisa Hartung, Oren Louidor

This is the first in a series of two works which study the discrete Gaussian free field on the binary tree when all leaves are conditioned to be positive. In this work, we obtain sharp asymptotics for the probability of this "hard-wall constraint" event, and identify the repulsion profile followed by the field in order to achieve it. We also provide

Stefan Ivanov, Ivan Minchev, Marina Tchomakova

We consider certain fiber bundles over a paraquaternionic contact manifolds, called twistor and reflector spaces, and show that these carry an intrinsic geometric structure that is always integrable.

Md. Rayid Hasan Mojumder, Naruttam Kumar Roy

A Proportional- Integral- Derivative (PID) controller is required to bring a system back to the stable operating region as soon as possible following a disturbance or discrepancy. For successful operation of the PID controller, it is necessary to design the controller parameters in a manner that will render low optimization complexity, less memory for operat

Adilson Almeida, Nikolai V. Chemetov, Fernanda Cipriano

We study an optimal control problem with a quadratic cost functional for non-Newtonian fluids of differential type. More precisely, we consider the system governing the evolution of a second grade fluid filling a two-dimensional bounded domain, supplemented with a Navier slip boundary condition, and under certain assumptions on the size of the initial data a

Kristin Kliemt

This work provides a review of crystal growth, crystal structure, compositional details, magnetism, thermodynamic, and transport behavior in the family of the trigonal intermetallic systems Eu$T_2Pn_2$ ($T=$ Cd, Zn; $Pn=$ P, As, Sb; space group $P\overline{3}m1$, No.164). The physical properties observed in these materials, and how these change depending on

Sayan Rakshit, Hmrishav Bandyopadhyay, Nibaran Das, Biplab Banerjee

Catastrophic forgetting makes neural network models unstable when learning visual domains consecutively. The neural network model drifts to catastrophic forgetting-induced low performance of previously learnt domains when training with new domains. We illuminate this current neural network model weakness and develop a forgetting-resistant incremental learnin

Ryo Wakizaka, Yasunari Suzuki, Atsushi Igarashi

Fault-tolerant quantum computation using lattice surgery can be abstracted as operations on graphs, wherein each logical qubit corresponds to a vertex of the graph, and multi-qubit measurements are accomplished by connecting the vertices with paths between them. Operations attempting to connect vertices without a valid path will result in abnormal terminatio

Robert Lasarzik, Elisabetta Rocca, Riccarda Rossi

In this paper we investigate the existence of solutions and their weak-strong uniqueness property for a PDE system modelling damage in viscoelastic materials. In fact, we address two solution concepts, weak and strong solutions. For the former, we obtain a global-in-time existence result, but the highly nonlinear character of the system prevents us from prov

Angel Beshirov, Milena Dobreva, Dimitar Dimitrov, Momchil Hardalov

The digitization of historical documents is crucial for preserving the cultural heritage of the society. An important step in this process is converting scanned images to text using Optical Character Recognition (OCR), which can enable further search, information extraction, etc. Unfortunately, this is a hard problem as standard OCR tools are not tailored to

Romain Puech, Vincent Gouldieff

We consider the frequency estimation of periodic signals using noisy time-of-arrival (TOA) information with missing (sparse) data contaminated with outliers. We tackle the problem from a mathematical optimization standpoint, formulating it as a linear regression with an unknown increasing integer independent variable and outliers. Assuming an upper bound on

Yuga Iguchi, Toshihiro Yamada

We propose a straightforward and effective method for discretizing multi-dimensional diffusion processes as an extension of Milstein scheme. The new scheme is explicitly given and can be simulated using Gaussian variates, requiring the same number of random variables as Euler-Maruyama (EM) scheme. We show that the proposed scheme has a weak convergence rate

Tobias M. Schuett, Sophia A. Henneberg

The new class of compact quasi-axisymmetric stellarators with a wide range of field periods offers the unique potential to combine the advantages of the two leading magnetic confinement fusion devices, tokamaks and stellarators. Here we present the first numerical optimization of this class which has so far only been obtained analytically. Our approach finds

Lulu Fang, Carlos Gustavo Moreira, Yiwei Zhang

In 1928, Jarn\'ık \cite{Jar} obtained that the set of continued fractions with bounded coefficients has Hausdorff dimension one. Good \cite{Goo} observed a dimension drop phenomenon by proving that the Hausdorff dimension of the set of continued fractions whose coefficients tend to infinity is one-half. For the set of continued fractions whose coefficien

M. A. Reyes, C. Dalfó, M. A. Fiol

The chordal ring (CR) graphs are a well-known family of graphs used to model some interconnection networks for computer systems in which all nodes are in a cycle. Generalizing the CR graphs, in this paper, we introduce the families of chordal multi-ring (CMR), chordal ring mixed (CRM), and chordal multi-ring mixed (CMRM) graphs. In the case of mixed graphs,

Baki Uzun, Shivam Pande, Gwendal Cachin-Bernard, Minh-Tan Pham

Regular patterns of vegetation are considered widespread landscapes, although their global extent has never been estimated. Among them, spotted landscapes are of particular interest in the context of climate change. Indeed, regularly spaced vegetation spots in semi-arid shrublands result from extreme resource depletion and prefigure catastrophic shift of the

Chen Chen, Emil Björnson, Carlo Fischione

Over-the-air computation (AirComp) is considered as a communication-efficient solution for data aggregation and distributed learning by exploiting the superposition properties of wireless multi-access channels. However, AirComp is significantly affected by the uneven signal attenuation experienced by different wireless devices. Recently, Cell-free Massive MI

C. Dalfó, M. A. Fiol

In this note, we give an infinite family of optimal graphs called $G^+(d,c)$. They are optimal in the sense that they have the maximum possible number of vertices for given a diameter $d$ and the so-called `outer multiset dimension' $c$. We provide their spectra, which have the property that their Laplacian eigenvalues are all different and integral. Fin

Aleksandr Bashkatov, Florian Bürkle, Çayan Demirkır, Wei Ding

Electrolytically generated gas bubbles can significantly hamper the overall electrolysis efficiency. Therefore it is crucial to understand their dynamics in order to optimise water electrolyzer systems. Here we demonstrate a distinct transport mechanism where coalescence with microbubbles drives electrolyte droplets, resulting from the fragmentation of the W

Oscar Nierstrasz, Andrei Chiş, Tudor Gîrba

Software systems should be explainable, that is, they should help us to answer questions while exploring, developing or using them. Textual documentation is a very weak form of explanation, since it is not causally connected to the code, so easily gets out of date. Tests, on the other hand, are causally connected to code, but they are also a weak form of exp

Shivam Pande, Baki Uzun, Florent Guiotte, Thomas Corpetti

In this study, we tackle the challenge of identifying plant species from ultra high resolution (UHR) remote sensing images. Our approach involves introducing an RGB remote sensing dataset, characterized by millimeter-level spatial resolution, meticulously curated through several field expeditions across a mountainous region in France covering various landsca

Dushyantha A Basnayaka

This paper, based on recent research, articulates the opportunities and challenges posed by an emerging area of study known as ``mediumband wireless communication'', which refers to digital radio-frequency (RF) wireless communication through mediumband channels. This class of channels that falls in the transitional region between the narrowband and b

Lemeng Zhao, Junjie Hu, Jianchao Bi, Yanbing Bai

In recent years, unmanned aerial vehicles (UAVs) have played an increasingly crucial role in supporting disaster emergency response efforts by analyzing aerial images. While current deep-learning models focus on improving accuracy, they often overlook the limited computing resources of UAVs. This study recognizes the imperative for real-time data processing

Iván M. Zerón, Jesús Algaba, José Manuel Míguez, Bruno Mendiboure

Averaged local bond order parameters based on spherical harmonics, also known as Lechner and Dellago order parameters, are routinely used to determine crystal structures in molecular simulations. Among different options, the combination of the $\overline{q}_{4}$ and $\overline{q}_{6}$ parameters is one of the best choices in the literature since allows one t

Yuji Hashimoto, Koji Nuida

It is known that any isogeny graph consisting of ordinary elliptic curves over $\mathbb{F}_q$ with $q = p$ or $p^2$ has a special structure, called a volcano graph. We have a bound $h < \log_2 \sqrt{4q}$ of a height $h$ of the $2$-volcano graph. In this paper, we improve the bound on a height of $2$-volcano graphs over $\mathbb{F}_q$. In case $q = p^2$, we s

Stephen E. Derenzo

The recent discovery that GaAs(Si,B) is a bright cryogenic scintillator with no apparent afterglow offers new opportunities for detecting rare, low-energy, electronic excitations from interacting dark matter. This paper presents Monte Carlo calculations of the scintillation photon detection efficiencies of optical cavities using three current cryogenic photo

Hendrik Bernd Zarucha, Peter Jung

It is known that sparse recovery is possible if the number of measurements is in the order of the sparsity, but the corresponding decoders either lack polynomial decoding time or robustness to noise. Commonly, decoders that rely on a null space property are being used. These achieve polynomial time decoding and are robust to additive noise but pay the price

Haoze He, Daniel Kressner, Bor Plestenjak

It is well known that a family of $n\times n$ commuting matrices can be simultaneously triangularized by a unitary similarity transformation. The diagonal entries of the triangular matrices define the $n$ joint eigenvalues of the family. In this work, we consider the task of numerically computing approximations to such joint eigenvalues for a family of (near

Haonan Chang, Kowndinya Boyalakuntla, Yuhan Liu, Xinyu Zhang

Solving storage problem: where objects must be accurately placed into containers with precise orientations and positions, presents a distinct challenge that extends beyond traditional rearrangement tasks. These challenges are primarily due to the need for fine-grained 6D manipulation and the inherent multi-modality of solution spaces, where multiple viable g

Wanyu Bian

This paper introduces an optimal control framework to address the inverse problem using a learned regularizer, with applications in image reconstruction. We build upon the concept of Learnable Optimization Algorithms (LOA), which combine deep learning with traditional optimization schemes to improve convergence and stability in image reconstruction tasks suc

Zehao Zhou, Peng Huang, Tao Wang, Guihua Zeng

Modulators based on the Mach-Zehnder interferometer (MZI) structure are widely used in continuous-variable quantum key distribution (CVQKD) systems. MZI-based variable optical attenuator (VOA) and amplitude modulator can reshape the waveform and control the intensity of coherent state signal to realize secret key information modulation in CVQKD system. Howev

Helen S. Ansell, Chengling Li, Daniel M. Sussman

Observations of glassy dynamics in experiments on confluent cellular tissue have inspired a wealth of computational and theoretical research to model their emergent collective behavior. Initial studies of the physical properties of several geometric cell models, including vertex-type models, have highlighted anomalous sub-Arrhenius, or &#34;ultra-strong,&#34

Amir Noori, Babak Tavassoli, Alireza Fereidunian

Renewable prosumers face the complex challenge of balancing self-sufficiency with seamless grid and market integration. This paper introduces a novel prosumers network framework aimed at mitigating peak loads in Iran, particularly under the uncertainties inherent in renewable energy generation and demand. A cost-oriented integrated prediction and optimizatio

Vage Egiazarian, Denis Kuznedelev, Anton Voronov, Ruslan Svirschevski

Text-to-image diffusion models have emerged as a powerful framework for high-quality image generation given textual prompts. Their success has driven the rapid development of production-grade diffusion models that consistently increase in size and already contain billions of parameters. As a result, state-of-the-art text-to-image models are becoming less acc

M. R. Formica, E. Ostrovsky, L. Sirota

We offer in this short report the so-called adaptive functional smoothness estimation in the Hilbert space norm sense in the three classical problems of non-parametrical statistic: regression, density and spectral (density) function measurement (estimation).

Chia-Yu Hsu, Wenwen Li, Sizhe Wang

Research on geospatial foundation models (GFMs) has become a trending topic in geospatial artificial intelligence (AI) research due to their potential for achieving high generalizability and domain adaptability, reducing model training costs for individual researchers. Unlike large language models, such as ChatGPT, constructing visual foundation models for i

Shentong Mo, Haofan Wang

Visual sound localization is a typical and challenging problem that predicts the location of objects corresponding to the sound source in a video. Previous methods mainly used the audio-visual association between global audio and one-scale visual features to localize sounding objects in each image. Despite their promising performance, they omitted multi-scal

Vikram Sudarshan, Warren D. Seider

Previously, using forward-flux sampling (FFS) and machine learning (ML), we developed multivariate alarm systems to counter rare un-postulated abnormal events. Our alarm systems utilized ML-based predictive models to quantify committer probabilities as functions of key process variables (e.g., temperature, concentrations, and the like), with these data obtai

P. Swaathi, Sanjit Das, N. Nirmal Thyagu

The dynamics of inertial particles in fluid flows have been the focus of extensive research due to their relevance in a wide range of industrial and environmental processes. Earlier studies have examined the dynamics of aerosols and bubbles using the Maxey-Riley equation in some standard systems but their dynamics within the traveling wave flow remain unexpl

Tomasz Stanisz, Stanisław Drożdż, Jarosław Kwapień

As the recent studies indicate, the structure imposed onto written texts by the presence of punctuation develops patterns which reveal certain characteristics of universality. In particular, based on a large collection of classic literary works, it has been evidenced that the distances between consecutive punctuation marks, measured in terms of the number of

Nikolai Chemetov, Fernanda Cipriano

We consider a velocity tracking problem for stochastic Navier-Stokes equations in a 2D-bounded domain. The control acts on the boundary through an injection-suction device with uncertainty, which acts in accordance with the non-homogeneous Navier-slip boundary conditions. After establishing a suitable stability result for the solution of the stochastic state

Daniel Witschard, Ilir Jusufi, Andreas Kerren

Embeddings are powerful tools for transforming complex and unstructured data into numeric formats suitable for computational analysis tasks. In this work, we use multiple embeddings for similarity calculations to be applied in bibliometrics and scientometrics. We build a multivariate network (MVN) from a large set of scientific publications and explore an as

Jianli Zhang, YiQing Guo

&#34;PeVatrons&#34; refer to astrophysical sources capable of accelerating particles to energies around $10^{15}$ electron volts and higher, potentially contributing to the cosmic ray spectrum in the knee region. Recently, LHAASO has discovered a large number of PeVatrons, allowing us to investigate in greater depth the contributions of these sources to cosm

Wenqiang Li, Haohuang Wen, Zhiqiang Lin

In modern mobile devices, baseband is an integral component running on top of cellular processors to handle crucial radio communications. However, recent research reveals significant vulnerabilities in these basebands, posing serious security risks like remote code execution. Yet, effectively scrutinizing basebands remains a daunting task, as they run closed

Jacob Fein-Ashley, Rajgopal Kannan, Viktor Prasanna

Attention mechanisms are critically important in the advancement of synthetic aperture radar (SAR) automatic target recognition (ATR) systems. Traditional SAR ATR models often struggle with the noisy nature of the SAR data, frequently learning from background noise rather than the most relevant image features. Attention mechanisms address this limitation by

Adrien Morel, Quentin Demouron, Adrien Badel

In this article, we present an analysis of the effects of nonlinear circuits on bistable vibration energy harvesters. We begin by introducing an analytical model for bistable vibration energy harvesters and demonstrate that the impact of nonlinear circuits can be characterized by two factors: electrically-induced damping and electrically-induced stiffness. S

Alain Omont

The systematic analysis of the correlations between diffuse interstellar bands (DIBs) is extended to weak DIBs through the comprehensive catalogue of the Apache Peak Observatory (APO) of 559 DIBs in 25 lines of sight with diverse interstellar properties. The main results are the following: 1) An extension of the number of DIBs identified to be related to C2,

S. M. Mahdi Shahabi, Xiaonan Deng, Ahmad Qidan, Taisir Elgorashi

This paper investigates the integration of Open Radio Access Network (O-RAN) within non-terrestrial networks (NTN), and optimizing the dynamic functional split between Centralized Units (CU) and Distributed Units (DU) for enhanced energy efficiency in the network. We introduce a novel framework utilizing a Deep Q-Network (DQN)-based reinforcement learning ap

Andrei Chiş, Tudor Gîrba, Oscar Nierstrasz

Debugging is hard. Interactive debuggers are mostly the same. They show you a stack, a way to sample the state of the stack, and, if the debugger is live, a way to step through execution. The standard interactive debugger for a general-purpose programming language provided by a mainstream IDE mostly offers a low-level interface in terms of generic language c

Arash Kargar-Estahbanati, Bhargav Rallabandi

We study the lubricated contact of sliding soft surfaces that are locally patterned but globally cylindrical, held together under an external normal force. The local patterns represent either naturally occurring surface roughness or engineered surface textures. Three dimensionless parameters govern the system: a speed, and the amplitude and wavelength of the

Federico A. Rossi

We describe an example of an indefinite invariant Einstein metric on a solvmanifold which is not standard, and whose restriction on the nilradical is nondegenerate.

Wenjun Jiang, Xiaojun Yuan, Boyu Teng, Hao Wang

Channel knowledge map (CKM) is viewed as a digital twin of wireless channels, providing location-specific channel knowledge for environment-aware communications. A fundamental problem in CKM-assisted communications is how to construct the CKM efficiently. Current research focuses on interpolating or predicting channel knowledge based on error-free channel kn

Minori Shikauchi, Ryosuke Hirai, Ilya Mandel

We construct a semi-analytical model that describes the convective core mass evolution of massive stars experiencing mass loss during the main-sequence stage. We first conduct a suite of 1D stellar evolution calculations to build insight into how convective core masses behave under idealized mass loss. Based on these simulations, we find several universal re

Wanli Shi, Hongchang Gao, Bin Gu

Zeroth-order (ZO) method has been shown to be a powerful method for solving the optimization problem where explicit expression of the gradients is difficult or infeasible to obtain. Recently, due to the practical value of the constrained problems, a lot of ZO Frank-Wolfe or projected ZO methods have been proposed. However, in many applications, we may have a

Hanyang Wang, Hao Zhou, Sibo Cheng

Despite the success of various methods in addressing the issue of spatial reconstruction of dynamical systems with sparse observations, spatio-temporal prediction for sparse fields remains a challenge. Existing Kriging-based frameworks for spatio-temporal sparse field prediction fail to meet the accuracy and inference time required for nonlinear dynamic pred

Tanya Berry, Jaime M. Moya, David Smiadak, Scott B. Lee

While $\sim$30% of materials are reported to be topological, topological insulators are rare. Magnetic topological insulators (MTI) are even harder to find. Identifying crystallographic features that can host the coexistence of a topological insulating phase with magnetic order is vital for finding intrinsic MTI materials. Thus far, most materials that are i

Federico Castelletti, Laura Ferrini

Quantifying causal effects of exposures on outcomes, such as a treatment and a disease respectively, is a crucial issue in medical science for the administration of effective therapies. Importantly, any related causal analysis should account for all those variables, e.g. clinical features, that can act as risk factors involved in the occurrence of a disease.

Bruce T. Tsurutani, Abhijit Sen, Rajkumar Hajra, Gurbax S. Lakhina

Updated summaries of the August 1972 and March 1989 space weather events have been constructed. The features of these two events are compared to the Carrington 1859 event and a few other major space weather events. It is concluded that solar active regions release energy in a variety of forms (X-rays, EUV photons, visible light, coronal mass ejection (CME) p

Geoffrey Stewart Morrison

Fingerprint examiners appear to be reluctant to adopt probabilistic reasoning, statistical models, and empirical validation. The rate of adoption of the likelihood-ratio framework by fingerprint practitioners appears to be near zero. A factor in the reluctance to adopt the likelihood-ratio framework may be a perception that it would require a radical change

Zhenhao Cai, Eviatar B. Procaccia, Yuan Zhang

We study the harmonic measure (i.e. the limit of the hitting distribution of a simple random walk starting from a distant point) on three canonical two-dimensional lattices: the square lattice $\mathbb{Z}^2$, the triangular lattice $\mathscr{T}$ and the hexagonal lattice $\mathscr{H}$. In particular, for the least positive value of the harmonic measure of an

Jialiang Wang, Yan Xia, Ye Yuan

A second-order-based latent factor (SLF) analysis model demonstrates superior performance in graph representation learning, particularly for high-dimensional and incomplete (HDI) interaction data, by incorporating the curvature information of the loss landscape. However, its objective function is commonly bi-linear and non-convex, causing the SLF model to su

I. de Rodrigo, A. Sanchez-Cuadrado, J. Boal, A. J. Lopez-Lopez

This paper introduces the MERIT Dataset, a multimodal (text + image + layout) fully labeled dataset within the context of school reports. Comprising over 400 labels and 33k samples, the MERIT Dataset is a valuable resource for training models in demanding Visually-rich Document Understanding (VrDU) tasks. By its nature (student grade reports), the MERIT Data

Delia Ionescu-Kruse, Rossen Ivanov

We consider the two-dimensional water-wave problem with a general non-zero vorticity field in a fluid volume with a flat bed and a free surface. The nonlinear equations of motion for the chosen surface and volume variables are expressed with the aid of the Dirichlet-Neumann operator and the Green function of the Laplace operator in the fluid domain. Moreover

Daniel García Rasines, Roi Naveiro, David Ríos Insua, Simón Rodríguez Santana

Pricing decisions stand out as one of the most critical tasks a company faces, particularly in today&#39;s digital economy. As with other business decision-making problems, pricing unfolds in a highly competitive and uncertain environment. Traditional analyses in this area have heavily relied on game theory and its variants. However, an important drawback of

Apurba Das, Ramkrishna Mandal

A quasi-twilled associative algebra is an associative algebra $\mathbb{A}$ whose underlying vector space has a decomposition $\mathbb{A} = A \oplus B$ such that $B \subset \mathbb{A}$ is a subalgebra. In the first part of this paper, we give the Maurer-Cartan characterization and introduce the cohomology of a quasi-twilled associative algebra. In a quasi-twi