March 2024 arXiv papers — page 97

Xue Bai, Tasmiah Haque, Sumit Mohan, Yuliang Cai

We propose a deep learning based novel prediction framework for enhanced bandwidth reduction in motion transfer enabled video applications such as video conferencing, virtual reality gaming and privacy preservation for patient health monitoring. To model complex motion, we use the First Order Motion Model (FOMM) that represents dynamic objects using learned

Bruno Colbois, Corentin Léna, Luigi Provenzano, Alessandro Savo

We consider the first eigenvalue of the magnetic Laplacian in a bounded and simply connected planar domain, with uniform magnetic field and Neumann boundary conditions. We investigate the reverse Faber-Krahn inequality conjectured by S. Fournais and B. Helffer, stating that this eigenvalue is maximized by the disk for a given area. Using the method of level

Fengran Mo, Bole Yi, Kelong Mao, Chen Qu

Conversational search provides a more convenient interface for users to search by allowing multi-turn interaction with the search engine. However, the effectiveness of the conversational dense retrieval methods is limited by the scarcity of training data required for their fine-tuning. Thus, generating more training conversational sessions with relevant labe

Hongrui Zheng, Zhijun Zhuang, Stephanie Wu, Shuo Yang

Generating competitive strategies and performing continuous motion planning simultaneously in an adversarial setting is a challenging problem. In addition, understanding the intent of other agents is crucial to deploying autonomous systems in adversarial multi-agent environments. Existing approaches either discretize agent action by grouping similar control

Seyedeh Baharan Khatami, Harsh Parikh, Haowei Chen, Sudeepa Roy

We address the challenge of inferring causal effects in social network data. This results in challenges due to interference -- where a unit's outcome is affected by neighbors' treatments -- and network-induced confounding factors. While there is extensive literature focusing on estimating causal effects in social network setups, a majority of them make prior

Haiyang Shi

Due to the heterogeneity of the global distribution of ecological and hydrological ground-truth observations, machine learning models can have limited adaptability when applied to unknown locations, which is referred to as weak extrapolability. Domain adaptation techniques have been widely used in machine learning domains such as image classification, which

Dong Won Lee, Hae Won Park, Yoon Kim, Cynthia Breazeal

We describe an approach for aligning an LLM-based dialogue agent based on global (i.e., dialogue-level) rewards, while also taking into account naturally-occurring multimodal signals. At a high level, our approach (dubbed GELI) learns a local, turn-level reward model by decomposing the human-provided Global Explicit (GE) session-level reward, using Local Imp

Chenxu Liu, Samuel A. Stein, Muqing Zheng, James Ang

Qubits are the fundamental building blocks of quantum information science and applications, whose concept is widely utilized in both quantum physics and quantum computation. While the significance of qubits and their implementation in physical devices have been extensively examined, now is the right time to revisit this understanding. In this paper, we intro

Bavesh Balaji, Jerrin Bright, Sirisha Rambhatla, Yuhao Chen

Unique player identification is a fundamental module in vision-driven sports analytics. Identifying players from broadcast videos can aid with various downstream tasks such as player assessment, in-game analysis, and broadcast production. However, automatic detection of jersey numbers using deep features is challenging primarily due to: a) motion blur, b) lo

Frank Ernesto Quintela Rodriguez

A self-consistent quadratic theory is presented to account for nonlinear contributions in quantum dynamics. Evolution equations are shown to depend on higher-order gradients of the Hamiltonian, which are incorporated via their equations of motion or through perturbative calculations. The dynamics is proven trace-preserving, with the Hamiltonian acting as a c

Antoine Poulin

In 2020, Calderoni, Marker, Motto Ros and Shani asked what the Borel complexity of the isomorphism relation of Archimedean orders on $\mathbb{Q}^n$ is. We answer this question by proving that the isomorphism relation of Archimedean orders on $\mathbb{Z}^n$ is not hyperfinite when $n \geq 3$ and not treeable when $n \geq 4$. As a corollary, we get that the is

Viktor Stasenko

The gravitational wave signals detected by the LIGO-Virgo-KAGRA collaboration can be explained by mergers of binary primordial black holes (PBHs) formed in the radiation dominated epoch. However, in early structures induced by the Poisson distribution of PBHs, a significant fraction of binaries are perturbed and avoid mergers. In addition, the internal dynam

Yanyan Li, Chenyu Lyu, Yan Di, Guangyao Zhai

During the Gaussian Splatting optimization process, the scene's geometry can gradually deteriorate if its structure is not deliberately preserved, especially in non-textured regions such as walls, ceilings, and furniture surfaces. This degradation significantly affects the rendering quality of novel views that deviate significantly from the viewpoints in the

Kevin Lin, Donald Brown, Sana Syed, Adam Greene

Eosinophilic Esophagitis (EoE) represents a challenging condition for medical providers today. The cause is currently unknown, the impact on a patient's daily life is significant, and it is increasing in prevalence. Traditional approaches for medical image diagnosis such as standard deep learning algorithms are limited by the relatively small amount of data

Yiran Wu, Tianwei Yue, Shaokun Zhang, Chi Wang

It is a notable trend to use Large Language Models (LLMs) to tackle complex tasks, e.g., tasks that require a sequence of actions and dynamic interaction with tools and external environments. In this paper, we propose StateFlow, a novel LLM-based task-solving paradigm that conceptualizes complex task-solving processes as state machines. In StateFlow, we dist

Yang Yang

Benchmark instances for the unbounded knapsack problem are typically generated according to specific criteria within a given constant range $R$, and these instances can be referred to as the unbounded knapsack problem with bounded coefficients (UKPB). In order to increase the difficulty of solving these instances, the knapsack capacity $C$ is usually set to

Lev Titarchuk, Elena Seifina

Precise measurements of black hole (BHs) masses are necessary to understand the coevolution of these sources and their host galaxies. Sometimes in the center of a galaxy there is not one, but two BHs. The BH duality of the quasar nucleus SDSS~J075217.84+193542.2 (herein SDSS~J0752) was recently proposed based on the observed strict periodicity of optical emi

Joseph Kapusta, Scott Pratt, Mayank Singh

Measurements of the dynamical correlations between neutral and charged kaons in central Pb-Pb collisions at $\sqrt{s_{NN}} = 2.76$ TeV by the ALICE Collaboration display anomalous behavior relative to conventional heavy-ion collision simulators. We consider other conventional statistical models, none of which can reproduce the magnitude and centrality depend

Igor Sterner, Weizhe Lin, Jinghong Chen, Bill Byrne

Two approaches have emerged to input images into large language models (LLMs). The first is to caption images into natural language. The second is to map image feature embeddings into the domain of the LLM and pass the mapped embeddings directly to the LLM. The majority of recent few-shot multimodal work reports performance using architectures that employ va

Jackob Black, Ryan Premo, Robert K. Goldberg, Trenton M. Ricks

Aerospace structures often experience high strain rate events such as ballistic impact, crash, or crush. A material model has been developed that enhances the capability to simulate the dynamic response of composite materials under these loading conditions. The material model has been implemented into the commercially available transient dynamic finite eleme

Stefania Russo

In this paper, we consider the Dirichlet problems with a widely degenerate equation. Through a well-known result by Talenti, we explicitly express the gradient of the solution $u_p$ outside the ball with a radius of $1$, if the datum $f$ is a non-negative radially decreasing function. This allows us to establish some sharp higher regularity results for the w

Daniel Enström, Viktor Kjellberg, Moa Johansson

Transformer language models are neural networks used for a wide variety of tasks concerning natural language, including some that also require logical reasoning. However, a transformer model may easily learn spurious patterns in the data, short-circuiting actual reasoning. In this paper we investigate to what extent transformers can be trained to a) approxim

M. Yunus Seker, Oliver Kroemer

Optimizing robotic action parameters is a significant challenge for manipulation tasks that demand high levels of precision and generalization. Using a model-based approach, the robot must quickly reason about the outcomes of different actions using a predictive model to find a set of parameters that will have the desired effect. The model may need to captur

Tiago M. Fernández-Caramés, Paula Fraga-Lamas

The Metaverse is a concept that proposes to immerse users into real-time rendered 3D content virtual worlds delivered through Extended Reality (XR) devices like Augmented and Mixed Reality (AR/MR) smart glasses and Virtual Reality (VR) headsets. When the Metaverse concept is applied to industrial environments, it is called Industrial Metaverse, a hybrid worl

Zichen Wu, Hsiu-Yuan Huang, Fanyi Qu, Yunfang Wu

Deep multimodal semantic understanding that goes beyond the mere superficial content relation mining has received increasing attention in the realm of artificial intelligence. The challenges of collecting and annotating high-quality multi-modal data have underscored the significance of few-shot learning. In this paper, we focus on two critical tasks under th

Qucheng Peng, Ce Zheng, Chen Chen

3D human pose data collected in controlled laboratory settings present challenges for pose estimators that generalize across diverse scenarios. To address this, domain generalization is employed. Current methodologies in domain generalization for 3D human pose estimation typically utilize adversarial training to generate synthetic poses for training. Nonethe

Kirill S. Evdokimov, Andrei Zeleneev

This paper considers nonparametric identification and estimation of the regression function when a covariate is mismeasured. The measurement error need not be classical. Employing the small measurement error approximation, we establish nonparametric identification under weak and easy-to-interpret conditions on the instrumental variable. The paper also provid

Azzurra Ciliberti

We express cluster variables of type $B_n$ and $C_n$ in terms of cluster variables of type $A_n$. Then we associate a cluster tilted bound symmetric quiver $Q$ of type $A_{2n-1}$ to any seed of a cluster algebra of type $B_n$ and $C_n$. Under this correspondence, cluster variables of type $B_n$ (resp. $C_n$) correspond to orthogonal (resp. symplectic) indeco

Yang Yang

As an important part of genetic algorithms (GAs), mutation operators is widely used in evolutionary algorithms to solve $\mathcal{NP}$-hard problems because it can increase the population diversity of individual. Due to limitations in mathematical tools, the mutation probability of the mutation operator is primarily empirically set in practical applications.

Ramón Bécar, P. A. González, Eleftherios Papantonopoulos, Yerko Vásquez

We consider massive scalar field perturbations in the background of black holes immersed in Chaplygin-like dark fluid (CDF), and we analyze the photon sphere modes, the de Sitter modes as well as the near extremal modes and discuss their dominance, by using the pseudospectral Chebyshev method and the third order Wentzel-Kramers-Brillouin approximation. We al

Jonathan W. P. Zajac, Praveen Muralikrishnan, Idris Tohidian, Xianci Zeng

Arginine has been a mainstay in biological formulation development for decades. To date, the way arginine modulates protein stability has been widely studied and debated. Here, we employed a hydrophobic polymer to decouple hydrophobic effects from other interactions relevant to protein folding. While existing hypotheses for the effects of arginine can genera

Steffen Hagedorn, Marcel Milich, Alexandru P. Condurache

Planning the trajectory of the controlled ego vehicle is a key challenge in automated driving. As for human drivers, predicting the motions of surrounding vehicles is important to plan the own actions. Recent motion prediction methods utilize equivariant neural networks to exploit geometric symmetries in the scene. However, no existing method combines motion

Tulasi Udupa A, Sushma Jayaram, Shreya Ganesh Hegde

The rapid development of computer network system brings both a great convenience and new security threats for users. Network security problem generally includes network system security and data security. Specifically, it refers to the reliability of network system, confidentiality, integrity and availability of data information in the system. This paper intr

Ido Cohen

This paper provides two algorithms to extract the governing equations of the dynamical system from samples, \acf{KR} and \acf{IKEA}. These algorithms extract a functionally independent set of Koopman Eigenfunctions. This kind of set is the most informative since it reveals the geometric structure of the dynamical system. Consequently, despite its finite card

Dongyu Wei, Liu Cao, Lyutianyang Zhang, Xiangyu Gao

The evolution of the IEEE 802.11 standards marks a significant throughput advancement in wireless access technologies, progressively increasing bandwidth capacities from 20 MHz in the IEEE 802.11a to up to 320 MHz in the latest IEEE 802.11be (Wi-Fi 7). However, the increased bandwidth capacities may not be well exploited due to inefficient bandwidth utilizat

Guohao Sun, Can Qin, Jiamian Wang, Zeyuan Chen

Recent advances in vision-language models have shown notable generalization in broad tasks through visual instruction tuning. However, bridging the gap between the pre-trained vision encoder and the large language models (LLMs) becomes the whole network's bottleneck. To improve cross-modality alignment, existing works usually consider more visual instruction

Matt Schmittle, Rohan Baijal, Brian Hou, Siddhartha Srinivasa

We focus on the problem of long-range dynamic replanning for off-road autonomous vehicles, where a robot plans paths through a previously unobserved environment while continuously receiving noisy local observations. An effective approach for planning under sensing uncertainty is determinization, where one converts a stochastic world into a deterministic one

Hetvi Waghela, Sneha Rakshit, Jaydip Sen

This paper introduces a novel adversarial attack method targeting text classification models, termed the Modified Word Saliency-based Adversarial At-tack (MWSAA). The technique builds upon the concept of word saliency to strategically perturb input texts, aiming to mislead classification models while preserving semantic coherence. By refining the traditional

Priyanshu Tyagi Rahul Nishant Priyadarshi

Computer networks have evolved into an essential component of modern society, facilitating the seamless sharing and dissemination of digital information. This paper explores the fundamental concepts of networking, focusing on the transformative impact of intranets and internets. Intranets, in particular, have emerged as indispensable tools for businesses, en

Marvin Anas Hahn, Kathlén Kohn, Orlando Marigliano, Tomas Pajdla

Rolling shutter (RS) cameras dominate consumer and smartphone markets. Several methods for computing the absolute pose of RS cameras have appeared in the last 20 years, but the relative pose problem has not been fully solved yet. We provide a unified theory for the important class of order-one rolling shutter (RS$_1$) cameras. These cameras generalize the pe

Jonathan Treviño-Marroquín

Limit and Pseudotopological spaces are two generalizations of topological spaces which are defined by indicating what filters converge under some axioms. In this article, we introduce covering spaces and set forth some necessary conditions for a construction for a universal covering space.

Ragav V, Jesher Joshua M, Syed Ibrahim S P

Auto manufacturers and research groups are working on autonomous driving for long period and achieved significant progress. Autonomous vehicles (AV) are expected to transform road traffic reduction from current conditions, avoiding accidents and congestion. As the implementation of an autonomous vehicle ecosystem includes complex automotive technology, ethic

Valeria Zelina Reyna Ortiz, Maciej Rybczynski, Zbigniew Wlodarczyk

It has been demonstrated that factorial moments analysis in dependence from the size of phase-space cells (when the latter is decreased but is still considerably large), exhibits sensitivity to particle bunching within a system situated in the two-dimensional cell. Based on recent findings concerning fluctuations in charge particle density observed in centra

Shujing Feng, Xin Jiang

Decentralized optimization algorithms have recently attracted increasing attention due to its wide applications in all areas of science and engineering. In these algorithms, a collection of agents collaborate to minimize the average of a set of heterogeneous cost functions in a decentralized manner. State-of-the-art decentralized algorithms like Gradient Tra

Asma Sattar, Georgios Deligiorgis, Marco Trincavelli, Davide Bacciu

Dynamic multi-relational graphs are an expressive relational representation for data enclosing entities and relations of different types, and where relationships are allowed to vary in time. Addressing predictive tasks over such data requires the ability to find structure embeddings that capture the diversity of the relationships involved, as well as their d

Jesher Joshua M, Ragav V, Syed Ibrahim S P

The maintenance, archiving and usage of the design drawings is cumbersome in physical form in different industries for longer period. It is hard to extract information by simple scanning of drawing sheets. Converting them to their digital formats such as Computer-Aided Design (CAD), with needed knowledge extraction can solve this problem. The conversion of t

Gopal-Krishna, Dusmanta Patra, Ravi Joshi

From a careful visual scrutiny of the radio structures of a well-defined sample of 2428 sources in the LoTSS DR2 survey made at 144 MHz with a 6" beam, we have selected a subset of 25 (i.e., 1%) sources showing highly unusual radio structures, not conforming to the prevalent radio morphological classification. Here we present and briefly discuss the basic pr

Siyuan Huang, Iaroslav Ponomarenko, Zhengkai Jiang, Xiaoqi Li

While the integration of Multi-modal Large Language Models (MLLMs) with robotic systems has significantly improved robots' ability to understand and execute natural language instructions, their performance in manipulation tasks remains limited due to a lack of robotics-specific knowledge. Conventional MLLMs are typically trained on generic image-text pairs,

Nirupam Dutta

This is evident that the controllable quantum systems can be the reliable building blocks for Quantum computation. In reality we are witnessing the progress towards making the idea tractable enough, though optimistic but the threshold is not very near to us. The dawn of quantum computation has begun. In the future, we hope to see a full fledged operationally

Yang Li, Zechen Tang, Zezhou Chen, Minghui Sun

Deep-learning density functional theory (DFT) shows great promise to significantly accelerate material discovery and potentially revolutionize materials research. However, current research in this field primarily relies on data-driven supervised learning, making the developments of neural networks and DFT isolated from each other. In this work, we present a

Michele Correggi, Emanuela L. Giacomelli, Ayman Kachmar

It is a well known fact that the geometry of a superconducting sample influences the distribution of the surface superconductivity for strong applied magnetic fields. For instance, the presence of corners induces geometric terms described through effective models in sector-like regions. We study the connection between two effective models for the offset of s

Yassine Habchi, Hamza Kheddar, Yassine Himeur, Mohamed Chahine Ghanem

The growing interest in developing smart diagnostic systems to help medical experts process extensive data for treating incurable diseases has been notable. In particular, the challenge of identifying thyroid cancer (TC) has seen progress with the use of machine learning (ML) and big data analysis, incorporating Transformers to evaluate TC prognosis and dete

Michael Klaiber, Karen Z. Hatsagortsyan, Christoph H. Keitel

A relativistic analytical theory of strong field ionization applicable across the regimes of the deep-tunneling up to the over-barrier ionization (OTBI) is developed, incorporating the effects of the polarization of the atomic bound state and the Stark-shift in an ultrastrong laser field. The theory, in particular, addresses the order of magnitude discrepanc

Joshua Martinez, Boris Kovalerchuk

Interpretable interactive visual pattern discovery in lossless 3D visualization is a promising way to advance machine learning. It enables end users who are not data scientists to take control of the model development process as a self-service. It is conducted in 3D General Line Coordinates (GLC) visualization space, which preserves all n-D information in 3D

Yuxuan Zhang, Yiren Song, Jinpeng Yu, Han Pan

Currently, personalized image generation methods mostly require considerable time to finetune and often overfit the concept resulting in generated images that are similar to custom concepts but difficult to edit by prompts. We propose an effective and fast approach that could balance the text-image consistency and identity consistency of the generated image

Zhiqiang Zang, Aditya Thimmaiah, Milos Gligoric

We present JOG, a framework that facilitates developing Java JIT peephole optimizations alongside JIT tests. JOG enables developers to write a pattern, in Java itself, that specifies desired code transformations by writing code before and after the optimization, as well as any necessary preconditions. Such patterns can be written in the same way that tests o

Aykut Has, Beyhan Yılmaz

In this article, spherical indicatrices of a curve and helices are re-examined using both the algebraic structure and the geometric structure of non-Newtonian (multiplicative) Euclidean space. Indicatrices of a multiplicative curve on the multiplicative sphere in multiplicative space are obtained. In addition, multiplicative general helix, multiplicative sla

Zhiqiang Zang, Fu-Yao Yu, Aditya Thimmaiah, August Shi

We present LeJit, a template-based framework for testing Java just-in-time (JIT) compilers. Like recent template-based frameworks, LeJit executes a template -- a program with holes to be filled -- to generate concrete programs given as inputs to Java JIT compilers. LeJit automatically generates template programs from existing Java code by converting expressi

Simone Gargiulo, Ivan Madan, Benoit Truc, Paolo Usai

The excitation of the $^{181\text{m}}$Ta isomer in the laser-plasma scenario was claimed to have been observed more than two decades ago. However, the reported experimental findings - and the respective high excitation rate - were later questioned as they could not be reproduced theoretically. The controversy has remained open ever since. In this work, we re

Aykut Has, Beyhan Yılmaz

The aim of this article is to characterize pairs of curves within multiplicative (non-Newtonian) spaces. Specifically, we investigate how famous curve pairs such as Bertrand partner curves, Mannheim partner curves, which are prominent in differential geometry, are transformed under the influence of multiplicative analysis. By leveraging the relationships bet

Kazi Mehedi Mohammad, Asma Akter Akhi, Md. Kamrujjaman

This study focuses on the modeling, mathematical analysis, developing theories, and numerical simulation of Influenza virus transmission. We have proved the existence, uniqueness, positivity, and boundedness of the solutions. Also, investigate the qualitative behavior of the models and find the basic reproduction number $(\mathcal{R}_0)$ that guarantees the

Yuting Chen, Partha Lahiri, Nicola Salvati

Nested error regression models are commonly used to incorporate observational unit specific auxiliary variables to improve small area estimates. When the mean structure of this model is misspecified, there is generally an increase in the mean square prediction error (MSPE) of Empirical Best Linear Unbiased Predictors (EBLUP). Observed Best Prediction (OBP) m

Md. Ashraf Uddin, Sunil Aryal, Mohamed Reda Bouadjenek, Muna Al-Hawawreh

With the increased use of network technologies like Internet of Things (IoT) in many real-world applications, new types of cyberattacks have been emerging. To safeguard critical infrastructures from these emerging threats, it is crucial to deploy an Intrusion Detection System (IDS) that can detect different types of attacks accurately while minimizing false

Matthew R. Edwards, Nicholas M. Fasano, Andreas M. Giakas, Michelle M. Wang

High-intensity lasers require suppression of prepulses and other non-ideal temporal structure to avoid target disruption before the arrival of the main pulse. To address this, we demonstrate that ionization gratings act as a controllable optical switch for high-power light with a temporal contrast improvement of at least $3\times10^5$ and a switching time le

Miguel A. Porras

The recent paper Phys. Rev. X. 14, 011031 (https://doi.org/10.48550/arXiv.2307.01019) includes an appendix that casts doubts on the validity the theory of the transverse orbital angular momentum of spatiotemporal optical vortices (STOVs) in Prog. Electromagn. Res. 177, 95 (https://doi.org/10.48550/arXiv.2301.09105). The argumentation in that appendix mixes a

Lutao Jiang, Xu Zheng, Yuanhuiyi Lyu, Jiazhou Zhou

Text-to-3D synthesis has recently seen intriguing advances by combining the text-to-image priors with 3D representation methods, e.g., 3D Gaussian Splatting (3D GS), via Score Distillation Sampling (SDS). However, a hurdle of existing methods is the low efficiency, per-prompt optimization for a single 3D object. Therefore, it is imperative for a paradigm shi

Lihui Liu, Zihao Wang, Ruizhong Qiu, Yikun Ban

Despite the superb performance in many tasks, large language models (LLMs) bear the risk of generating hallucination or even wrong answers when confronted with tasks that demand the accuracy of knowledge. The issue becomes even more noticeable when addressing logic queries that require multiple logic reasoning steps. On the other hand, knowledge graph (KG) b

Xinyu Huang, Henrik Hellstrom, Carlo Fischione

This paper investigates over-the-air computation (AirComp) in the context of multiple-access time-varying multipath channels. We focus on a scenario where devices with high mobility transmit their sensing data to a fusion center (FC) for averaging. To combat the time-varying channel and Doppler effect, each device adopts orthogonal time frequency space (OTFS

Oscar Amador, Ignacio Soto, Maria Calderon, Manuel Urueña

This paper evaluates the performance of ETSI ITS Contention-Based Forwarding (CBF) and ETSI Simple GeoBroadcast forwarding while disseminating warning messages over a Geographical Area in highway and urban scenarios. Our experimental evaluation considers the complete ETSI ITS architecture including the Decentralized Congestion Control (DCC) mechanism. We pro

Jie Tang, Fei-Peng Tian, Boshi An, Jian Li

Depth completion aims to derive a dense depth map from sparse depth measurements with a synchronized color image. Current state-of-the-art (SOTA) methods are predominantly propagation-based, which work as an iterative refinement on the initial estimated dense depth. However, the initial depth estimations mostly result from direct applications of convolutiona

Grzegorz Rzadkowski

The paper deals with the comparison of the Gompertz function and the logistic function. We show that the Gompertz function can be approximated with high accuracy by a sum of three logistic functions (multilogistic function). Two of them are increasing and one is decreasing. We use second-order logistic wavelets to estimate the parameters of the multilogistic

Bishal Sonar, Ravi Srivastava

A signed graph product is defined for a new product, and initially the unsigned graph product's Laplacian spectrum and signless Laplacian spectrum are found. Next, for the signed graph product, the adjacency spectrum, Laplacian spectrum, and signless Laplacian spectrum are found. In the end, we determined the prerequisite for the signed graph product to be i

Christian Döding

The time-dependent Gross-Pitaevksii equation (GPE) is a nonlinear Schr\"odinger equation which is used in quantum physics to model the dynamics of Bose-Einstein condensates. In this work we consider numerical approximations of the GPE based on a multiscale approach known as the localized orthogonal decomposition. Combined with an energy preserving time integ

Romain Cosson, Laurent Massoulié

We consider metrical task systems on general metric spaces with $n$ points, and show that any fully randomized algorithm can be turned into a randomized algorithm that uses only $2\log n$ random bits, and achieves the same competitive ratio up to a factor $2$. This provides the first order-optimal barely random algorithms for metrical task systems, i.e., whi

Boujemaa Guermazi, Riadh Ksantini, Naimul Khan

Image segmentation is the foundation of several computer vision tasks, where pixel-wise knowledge is a prerequisite for achieving the desired target. Deep learning has shown promising performance in supervised image segmentation. However, supervised segmentation algorithms require a massive amount of data annotated at a pixel level, thus limiting their appli

Silvia Corbara, Alejandro Moreo

Authorship Verification (AV) is a text classification task concerned with inferring whether a candidate text has been written by one specific author or by someone else. It has been shown that many AV systems are vulnerable to adversarial attacks, where a malicious author actively tries to fool the classifier by either concealing their writing style, or by im

Tomasz Masłowski

The exact solution of the Wegner flow equation with the Mielke generator for $3\times 3$ Hermitian matrices is presented. The general solutions for $N\times N$ tridiagonal Hermitian matrices and partially for $4\times 4$ real symmetric matrices are also given.

Kwan Yun, Kwanggyoon Seo, Chang Wook Seo, Soyeon Yoon

Facial sketches are both a concise way of showing the identity of a person and a means to express artistic intention. While a few techniques have recently emerged that allow sketches to be extracted in different styles, they typically rely on a large amount of data that is difficult to obtain. Here, we propose StyleSketch, a method for extracting high-resolu

Yuji Hirono, Akinori Tanaka, Kenji Fukushima

Score-based diffusion models have proven effective in image generation and have gained widespread usage; however, the underlying factors contributing to the performance disparity between stochastic and deterministic (i.e., the probability flow ODEs) sampling schemes remain unclear. We introduce a novel formulation of diffusion models using Feynman's path int

Ziheng Chen, Yue Song, Yunmei Liu, Nicu Sebe

Manifold-valued measurements exist in numerous applications within computer vision and machine learning. Recent studies have extended Deep Neural Networks (DNNs) to manifolds, and concomitantly, normalization techniques have also been adapted to several manifolds, referred to as Riemannian normalization. Nonetheless, most of the existing Riemannian normaliza

Lie-Liang Yang

A conceptual example is first analyzed to show that efficient wireless communications is possible, when user equipment (UE) receiver, BS transmitter or/and the scatter (reflector) in wireless channels employ the required channel state information (CSI) to remove the randomness of signal phase. Then, the principles and optimization of three reflective intelli

Taha-Hossein Hejazi, Zahra Ghadimkhani, Arezoo Borji

Placing applications in mobile edge computing servers presents a complex challenge involving many servers, users, and their requests. Existing algorithms take a long time to solve high-dimensional problems with significant uncertainty scenarios. Therefore, an efficient approach is required to maximize the quality of service while considering all technical co

Yong-Kang Huang, Yue-Long Shen, Chao Wang, Yu-Ming Wang

We accomplish for the first time the next-to-leading-order computation of the weak annihilation contribution to the exclusive electroweak penguin decays $B \to \left \{K, \pi \right \} \ell^{+} \ell^{-}$ with an energetic light-flavour meson, which is an essential missing piece of the complete QCD correction to the matrix elements of hadronic operators in th

Lorenz Frühwirth, Manuel Hauke

Given a monotonically decreasing $\psi: \mathbb{N} \to [0,\infty)$, Khintchine's Theorem provides an efficient tool to decide whether, for almost every $\alpha \in \mathbb{R}$, there are infinitely many $(p,q) \in \mathbb{Z}^2$ such that $\left\lvert \alpha - \frac{p}{q}\right\rvert \leq \frac{\psi(q)}{q}$. The recent result of Koukoulopoulos and Maynard pro

Xi Chen, Haosen Yang, Huicong Zhang, Hongxun Yao

Source-free unsupervised domain adaptation (SFUDA) aims to enable the utilization of a pre-trained source model in an unlabeled target domain without access to source data. Self-training is a way to solve SFUDA, where confident target samples are iteratively selected as pseudo-labeled samples to guide target model learning. However, prior heuristic noisy pse

Agi Kurucz, Frank Wolter, Michael Zakharyaschev

As well known, weak K4 and the difference logic DL do not enjoy the Craig interpolation property. Our concern here is the problem of deciding whether any given implication does have an interpolant in these logics. We show that the nonexistence of an interpolant can always be witnessed by a pair of bisimilar models of polynomial size for DL and of triple-expo

Arezoo Borji, Taha-Hossein Hejazi, Abbas Seifi

Alzheimer's disease is a progressive neurodegenerative disorder that primarily affects cognitive functions such as memory, thinking, and behavior. In this disease, there is a critical phase, mild cognitive impairment, that is really important to be diagnosed early since some patients with progressive MCI will develop the disease. This study delves into the c

Zexu Wang, Jiachi Chen, Yanlin Wang, Yu Zhang

Reentrancy vulnerability as one of the most notorious vulnerabilities, has been a prominent topic in smart contract security research. Research shows that existing vulnerability detection presents a range of challenges, especially as smart contracts continue to increase in complexity. Existing tools perform poorly in terms of efficiency and successful detect

Partha Nandi, Bibhas Ranjan Majhi

We introduce an innovative method to explore gravity's quantum aspects using a novel theoretical framework. Our model delves into gravity-induced entanglement (GIE) while sidestepping classical communication limitations imposed by the LOCC principle. Specifically, we connect a non-relativistic two-dimensional quantum oscillator detector with linearly polariz

Prateek, Pawan Wadhwani, Reshesh Kumar Pathak, Mayur Bhosale

Swarm robots, which are inspired from the way insects behave collectively in order to achieve a common goal, have become a major part of research with applications involving search and rescue, area exploration, surveillance etc. In this paper, we present a swarm of robots that do not require individual extrinsic sensors to sense the environment but instead u

Vincent Bouttier, Renaud Jardri, Sophie Deneve

Belief Propagation (BP) is a simple probabilistic inference algorithm, consisting of passing messages between nodes of a graph representing a probability distribution. Its analogy with a neural network suggests that it could have far-ranging applications for neuroscience and artificial intelligence. Unfortunately, it is only exact when applied to cycle-free

Vladimir Korviakov, Denis Koposov

Most of the computer vision architectures nowadays are built upon the well-known foundation operations: fully-connected layers, convolutions and multi-head self-attention blocks. In this paper we propose a novel foundation operation - NeoCell - which learns matrix patterns and performs patchwise matrix multiplications with the input data. The main advantages

Marie Dessard, Jean-Baptiste Manneville, Jean-François Berret

Cellular microrheology has shown that cancer cells with high metastatic potential are softer compared to non-tumorigenic normal cells. These findings rely on measuring the apparent Young modulus of whole cells using primarily atomic force microscopy. This study aims to explore whether alternative mechanical parameters have discriminating features with regard

Chun-Tse Chien, Rui-Yang Ju, Kuang-Yi Chou, Jen-Shiun Chiang

The introduction of YOLOv9, the latest version of the You Only Look Once (YOLO) series, has led to its widespread adoption across various scenarios. This paper is the first to apply the YOLOv9 algorithm model to the fracture detection task as computer-assisted diagnosis (CAD) to help radiologists and surgeons to interpret X-ray images. Specifically, this pap

M. D. Fajardo, J. Vidal-Nunez

In this paper we study how Lagrange duality is connected to optimization problems whose objective function is the difference of two convex functions, briefly called DC problems. We present two Lagrange dual problems, each of them obtained via a different approach. While one of the duals corresponds to the standard formulation of the Lagrange dual problem, th

Xiubo Zhang, Yujie He, Ye Li, Yan Li

In the context of changing travel behaviors and the expanding user base of Geographic Information System (GIS) services, conventional centralized architectures responsible for handling shortest distance queries are facing increasing challenges, such as heightened load pressure and longer response times. To mitigate these concerns, this study is the first to

Antonio Bianchi, Marco Bonura, Carlota P. A. Carlos, Stewart Leith

Niobium-coated copper radio-frequency cavities are cost-effective alternatives to bulk niobium cavities, given the lower material costs of copper substrates and their operation in liquid helium at around 4.2 K. However, these cavities historically exhibited a gradual degradation in performance with the accelerating field. This phenomenon, not yet fully under

Johann Cigler

Using a slightly generalized result of George Andrews and Jet Wimp this note gives a simple computational proof of some Hankel determinants of backwards shifts of convolution powers of Catalan numbers and obtains analogous results for Narayana polynomials.

Ziyi Huang

We give a functional equation for the refined Herglotz-Zagier function. It is analogous to a result in the theory of modular forms.

Robert V. Kohn, Raghavendra Venkatraman

We study certain "geometric-invariant resonant cavitie"' introduced by Liberal et. al in a 2016 Nature Comm. paper, modeled using the transverse magnetic reduction of Maxwell's equations. The cross-section consists of a dielectric inclusion surrounded by an "epsilon-near-zero" (ENZ) shell. When the shell has the right area, its interaction with the inclusion