April 2024 arXiv papers — page 85

Harry Walsh, Abolfazl Ravanshad, Mariam Rahmani, Richard Bowden

Phonetic representations are used when recording spoken languages, but no equivalent exists for recording signed languages. As a result, linguists have proposed several annotation systems that operate on the gloss or sub-unit level; however, these resources are notably irregular and scarce. Sign Language Production (SLP) aims to automatically translate spoke

Ricardo Caldas, Juan Antonio Pinera Garcia, Matei Schiopu, Patrizio Pelliccione

Robotic systems are becoming pervasive and adopted in increasingly many domains, such as manufacturing, healthcare, and space exploration. To this end, engineering software has emerged as a crucial discipline for building maintainable and reusable robotic systems. The robotics software engineering research field has received increasing attention, fostering a

N. Sheremet, A. Chaikovskaia, D. Grosman, D. Karlovets

We explore elastic scattering of non-relativistic electrons in the form of standard Laguerre-Gaussian (sLG) and elegant Laguerre - Gaussian (eLG) packets on atomic targets in the generalized Born approximation and compare these results to the reference with Bessel-Gaussian (BG) packets. Scattering by hydrogen-like, iron, silver, and golden targets is conside

Denis Antipov, Aneta Neumann, Frank Neumann, Andrew M. Sutton

Diversity optimization is the class of optimization problems in which we aim to find a diverse set of good solutions. One of the frequently-used approaches to solve such problems is to use evolutionary algorithms that evolve a desired diverse population. This approach is called evolutionary diversity optimization (EDO). In this paper, we analyze EDO on a thr

Huapeng Gu, Xue-Bing Wu, Yuhan Wen, Qinchun Ma

NGC 4395 is a dwarf Seyfert 1 galaxy with a possible intermediate-mass black hole of several $\rm{10^4}$ solar masses in its center. As a well-studied object, its broad line region size has been measured via H$\rm{\alpha}$ time lag in numerous spectroscopic reverberation mapping (SRM) and narrow-band photometric reverberation mapping (PRM) campaigns. Here we

Alfred Geroldinger, Felix Gotti

We construct monoid algebras which satisfy the ascending chain condition on principal ideals and which have the property that every nonempty subset of $\mathbb{N}_{\ge 2}$ occurs as a length set.

Patrick R. Stollenwerk, Kevin G. Bailey, Daniel Koch, Peter Mueller

We demonstrate excitation of metastable krypton and xenon beams using a vacuum ultraviolet lamp and directly compare the performance of this method to metastable excitation based on a radiofrequency-driven plasma discharge. In our apparatus, lamp-based metastable excitation outperforms the plasma discharge across a wide range of beam flux values relevant for

Alexandre Quintart, Magnus Haw, Federico Semeraro

arcjetCV is an open-source Python software designed to automate time-resolved measurements of heatshield material recession and recession rates from arcjet test video footage. This new automated and accessible capability greatly exceeds previous manual extraction methods, enabling rapid and detailed characterization of material recession for any sample with

Igor Timoshuk, Egor Babaev

Two-band superconductors exhibit a distinct phase characterized by two correlation lengths, one smaller and the other larger than the magnetic field penetration length. This regime was coined type-1.5 superconductivity, with several unconventional properties, such as vortex clustering. However, a fully microscopic solution for vortex clusters has remained ch

Daming Li

Variational methods are highly valuable computational tools for solving high-dimensional quantum systems. In this paper, we explore the effectiveness of three variational methods: the density matrix renormalization group (DMRG), Boltzmann machine learning, and the variational quantum eigensolver (VQE). We apply these methods to two different quantum systems:

Cameron Wilson

We prove asymptotics for the density of everywhere locally soluble diagonal quadric surfaces parameterised by rational points on the split quadric surface $y_0y_1=y_2y_3$ which do not satisfy $-y_0y_1=\square$ nor $-y_0y_3=\square$.

Luca Bompani, Manuele Rusci, Daniele Palossi, Francesco Conti

This paper introduces Multi-Resolution Rescored Byte-Track (MR2-ByteTrack), a novel video object detection framework for ultra-low-power embedded processors. This method reduces the average compute load of an off-the-shelf Deep Neural Network (DNN) based object detector by up to 2.25$\times$ by alternating the processing of high-resolution images (320$\times

Stefan Steinerberger

We consider the problem of finding good low rank approximations of symmetric, positive-definite $A \in \mathbb{R}^{n \times n}$. Chen-Epperly-Tropp-Webber showed, among many other things, that the randomly pivoted partial Cholesky algorithm that chooses the $i-$th row with probability proportional to the diagonal entry $A_{ii}$ leads to a universal contracti

Ravshan Ashurov, Yusuf Fayziev, Muattar Khudoykulova

In recent years, the Boussinesq type fractional partial differential equation has attracted much attentions of researchers for its practical importance. In this paper we study a non-local problem for the Boussinesq type equation $D_t^\alpha u(t)+A D_t^\alpha u(t)+\nu^2A u(t)=0,\,\, 0< t< T,\,\, 1<\alpha<2,$ where $D_t^\alpha$ is the Caputo fractional derivat

Chandler Osborne, Samir Salim

The Sloan Digital Sky Survey (SDSS) was foundational to the study of galaxy evolution, having revealed the bimodality of galaxies and the relationship between their structure and star-forming activity. However, ground-based optical surveys like SDSS are limited in resolution and depth which may lead to biases or poor quality in the derived morphological prop

Tommaso Sorgente, Stefano Berrone, Silvia Biasotti, Gianmarco Manzini

We present an optimization procedure for generic polygonal or polyhedral meshes, tailored for the Virtual Element Method (VEM). Once the local quality of the mesh elements is analyzed through a quality indicator specific to the VEM, groups of elements are agglomerated to optimize the global mesh quality. The resulting discretization is significantly lighter:

Yue Wu, Yewen Fan, So Yeon Min, Shrimai Prabhumoye

We propose an intuitive LLM prompting framework (AgentKit) for multifunctional agents. AgentKit offers a unified framework for explicitly constructing a complex "thought process" from simple natural language prompts. The basic building block in AgentKit is a node, containing a natural language prompt for a specific subtask. The user then puts together chains

Claudia Ceci, Alessandra Cretarola

We investigate the optimal reinsurance problem in a risk model with jump clustering features. This modeling framework is inspired by the concept initially proposed in Dassios and Zhao (2011), combining Hawkes and Cox processes with shot noise intensity models. Specifically, these processes describe self-exciting and externally excited jumps in the claim arri

Tomasz Szydlo, Amadeusz Szabala, Nazar Kordiumov, Konrad Siuzdak

Internet of Things systems exists in various areas of our everyday life. For example, sensors installed in smart cities and homes are processed in edge and cloud computing centres providing several benefits that improve our lives. The place of data processing is related to the required system response times -- processing data closer to its source results in

Sofia Canevarolo, Loek van Vonderen, Nora Elisa Chisari

The distribution of masses of neutron stars, particularly the maximum mass value, is considered a probe of their formation, evolution and internal physics (i.e., equation of state). This mass distribution could in principle be inferred from the detection of gravitational waves from binary neutron star mergers. Using mock catalogues of $10^5$ dark sirens even

Andrei Martinez-Finkelshtein, Rafael Morales, Daniel Perales

We address the problem of the weak asymptotic behavior of zeros of families of generalized hypergeometric polynomials as their degree tends to infinity. The main tool is the representation of such polynomials as a finite free convolution of simpler elements; this representation is preserved in the asymptotic regime, so we can formally write the limit zero di

Saulo Albuquerque, Sebastian H. Völkel, Kostas D. Kokkotas

Wave equations with energy-dependent potentials appear in many areas of physics, ranging from nuclear physics to black hole perturbation theory. In this work, we use the semi-classical WKB method to first revisit the computation of bound states of potential wells and reflection/transmission coefficients in terms of the Bohr-Sommerfeld rule and the Gamow form

Jose M. Munoz, Silviu M. Udrescu, Ronald F. Garcia Ruiz

Numerous phenomenological nuclear models have been proposed to describe specific observables within different regions of the nuclear chart. However, developing a unified model that describes the complex behavior of all nuclei remains an open challenge. Here, we explore whether novel symbolic Machine Learning (ML) can rediscover traditional nuclear physics mo

Sinan Arda

Technological innovations have shown remarkable capabilities to benefit and harm society alike. AI constitutes a democratized sophisticated technology accessible to large parts of society, including malicious actors. This work proposes a taxonomy focusing on on (geo)political risks associated with AI. It identifies 12 risks in total divided into four categor

Hao-Wei Chen, Yu-Syuan Xu, Kelvin C. K. Chan, Hsien-Kai Kuo

Existing image restoration approaches typically employ extensive networks specifically trained for designated degradations. Despite being effective, such methods inevitably entail considerable storage costs and computational overheads due to the reliance on task-specific networks. In this work, we go beyond this well-established framework and exploit the inh

Zhanjie Zhang, Quanwei Zhang, Huaizhong Lin, Wei Xing

Artistic style transfer aims to transfer the learned artistic style onto an arbitrary content image, generating artistic stylized images. Existing generative adversarial network-based methods fail to generate highly realistic stylized images and always introduce obvious artifacts and disharmonious patterns. Recently, large-scale pre-trained diffusion models

Ejiofor Oluomachi, Akinsola Ahmed, Wahab Ahmed, Edozie Samson

This article assesses the effectiveness of current cybersecurity regulations and policies in the United States amidst the escalating frequency and sophistication of cyber threats. The focus is on the comprehensive framework established by the U.S. government, with a spotlight on the National Institute of Standards and Technology (NIST) Cybersecurity Framewor

Meinolf Geck

These are expanded notes from graduate courses about Lie algebras and Chevalley groups held at the University of Stuttgart. In the 1950s Chevalley showed how linear groups over arbitrary fields could be obtained~ -- ~by a uniform procedure~ -- ~from the simple Lie algebras over $\C$ occurring in the Cartan--Killing classification. Together with subsequent va

Luís Atayde, Noemi Frusciante, Benjamin Bose, Santiago Casas

To fully exploit the data from next generation surveys, we need an accurate modelling of the matter power spectrum up to non-linear scales. Therefore in this work we present the halo model reaction framework for the Generalized Cubic Covariant Galileon (GCCG) model, a modified gravity model within the Horndeski class of theories which extends the cubic covar

Marcos Zampieri, Damith Premasiri, Tharindu Ranasinghe

The spread of various forms of offensive speech online is an important concern in social media. While platforms have been investing heavily in ways of coping with this problem, the question of privacy remains largely unaddressed. Models trained to detect offensive language on social media are trained and/or fine-tuned using large amounts of data often stored

Louveton Nicolas, McCall Rod, Engel Thomas

Multitasking with a touch screen user-interface while driving is known to impact negatively driving performance and safety. Literature shows that list scrolling interfaces generate more visual-manual distraction than structured menus and sequential navigation. Depth and breadth trade-offs for structured navigation have been studied. However, little is known

Carlo Alberto Mantica, Luca Guido Molinari

We introduce Sinyukov-like tensors, a special kind of conformal Killing tensors. In Robertson-Walker space-times they have the perfect-fluid form and only depend on two constants and the scale factor. They are the candidate for the dark term of the newly proposed Conformal Killing Gravity, by Harada. In addition to ordinary matter, the Friedmann equations co

Xiaoyan Zhou, Feiran Liang, Zhaojie Xie, Yang Lan

Package managers such as NPM, Maven, and PyPI play a pivotal role in open-source software (OSS) ecosystems, streamlining the distribution and management of various freely available packages. The fine-grained details within software packages can unveil potential risks within existing OSS ecosystems, offering valuable insights for detecting malicious packages.

Jilian Zhong, Xiaoyue Li

For open quantum systems,a short-time evolution is usually well described by the effective non-Hermitian Hamiltonians,while long-time dynamics requires the Lindblad master equation,in which the Liouvillian superoperators characterize the time evolution. In this paper, we constructed an open system by adding suitable gain and loss operators to the Chen insula

Arvindh Arun, Saurav Chhatani, Jisun An, Ponnurangam Kumaraguru

We investigate the impact of free speech and the relaxation of moderation on online social media platforms using Elon Musk's takeover of Twitter as a case study. By curating a dataset of over 10 million tweets, our study employs a novel framework combining content and network analysis. Our findings reveal a significant increase in the distribution of certain

Jonathan R. Stewart

Local dependence random graph models are a class of block models for network data which allow for dependence among edges under a local dependence assumption defined around the block structure of the network. Since being introduced by Schweinberger and Handcock (2015), research in the statistical network analysis and network science literatures have demonstra

Mgeni Makambi Mashauri, Alexandre Graell i Amat, Michael Lentmaier

A non-adaptive quantitative group testing (GT) scheme based on sparse codes-on-graphs in combination with low-complexity peeling decoding was introduced and analyzed by Karimi et al.. In this work, we propose a variant of this scheme based on low-density parity-check codes where the BCH codes at the constraint nodes are replaced by simple single parity-check

Vincent Mittag, Christian Strelow, Tobias Kipp, Alf Mews

Dual-emissive nanorods with fluorescence in both, the visible and infrared range are prepared by a combination of a CdSe-nanocrystal-seeded growth of CdS nanorods, and a successive partial Cd-to-Pb cation exchange. We show that the exchange reaction, which involves Pb halides in oleylamine, starts at the tip of the rods, leading to the formation of CdSe-dot/

Johannes Hoster, Sara Al-Sayed, Felix Biessmann, Alexander Glaser

Satellite imagery is regarded as a great opportunity for citizen-based monitoring of activities of interest. Relevant imagery may however not be available at sufficiently high resolution, quality, or cadence -- let alone be uniformly accessible to open-source analysts. This limits an assessment of the true long-term potential of citizen-based monitoring of n

Christian Richter

A topological disc is called $n$-self-affine if it has a dissection into $n$ affine images of itself. It is called $n$-gc-self-affine if the dissection is obtained by successive glass-cuts, which are cuts along segments splitting one disc into two. For every $n \ge 2$, we characterize all $n$-gc-self-affine discs. All such discs turn out to be either triangl

Bowen Fang, Xu Chen, Xuan Di

This paper aims to develop a learning method for a special class of traveling salesman problems (TSP), namely, the pickup-and-delivery TSP (PDTSP), which finds the shortest tour along a sequence of one-to-one pickup-and-delivery nodes. One-to-one here means that the transported people or goods are associated with designated pairs of pickup and delivery nodes

Sunhao Dai, Chen Xu, Shicheng Xu, Liang Pang

With the rapid advancements of large language models (LLMs), information retrieval (IR) systems, such as search engines and recommender systems, have undergone a significant paradigm shift. This evolution, while heralding new opportunities, introduces emerging challenges, particularly in terms of biases and unfairness, which may threaten the information ecos

Hengyu Zhang, Junwei Pan, Dapeng Liu, Jie Jiang

Click-through rate (CTR) prediction tasks play a pivotal role in real-world applications, particularly in recommendation systems and online advertising. A significant research branch in this domain focuses on user behavior modeling. Current research predominantly centers on modeling co-occurrence relationships between the target item and items previously int

Roland Miyamoto

Using a Picard-like operator $T$, we prove that the iterative differential equation $-\gamma g' = g^{-1}$ with parameter $\gamma>0$ has a solution $g=h\colon[0,1]\to[0,1]$ for only one value $\gamma=\kappa\approx0.278877$, and that this solution $h$ is unique. As an even stronger result, we exhibit $h$ as the global limit of the operator $T$.

Panna Gehér, Arsenii Sagdeev, Géza Tóth

In Euclidean Ramsey Theory usually we are looking for monochromatic configurations in the Euclidean space, whose points are colored with a fixed number of colors. In the canonical version, the number of colors is arbitrary, and we are looking for an `unavoidable' set of colorings of a finite configuration, that is a set of colorings with the property that on

Will Johnson

Let $T$ be a theory with a definable topology. $T$ is t-minimal in the sense of Mathews if every definable set in one variable has finite boundary. If $T$ is t-minimal, we show that there is a good dimension theory for definable sets, satisfying properties similar to dp-rank in dp-minimal theories, with one key exception: the dimension of $\operatorname{dom}

Nello Bruscino

Due to its high mass top quarks decay before top-flavoured hadrons can be formed. This feature yields experimental access to the top quark polarization and production asymmetries. The large top quark sample moreover enables measurements of other properties, such as the W-boson branching ratios and helicity, and fragmentation functions of the bottom quarks. I

Anton Kullberg, Martin A. Skoglund, Isaac Skog, Gustaf Hendeby

Typical iterated filters, such as the iterated extended Kalman filter (IEKF), iterated unscented Kalman filter (IUKF), and iterated posterior linearization filter (IPLF), have been developed to improve the linearization point (or density) of the likelihood linearization in the well-known extended Kalman filter (EKF) and unscented Kalman filter (UKF). A short

Jonathan Eastoe, Grayson M. Noah, Debargha Dutta, Alessandro Rossi

Semiconductor integrated circuits operated at cryogenic temperature will play an essential role in quantum computing architectures. These can offer equivalent or superior performance to their room-temperature counterparts while enabling a scaling up of the total number of qubits under control. Silicon integrated circuits can be operated at a temperature stag

Yujia Hu, Yuntao Du, Zhikun Zhang, Ziquan Fang

Trajectory streams are being generated from location-aware devices, such as smartphones and in-vehicle navigation systems. Due to the sensitive nature of the location data, directly sharing user trajectories suffers from privacy leakage issues. Local differential privacy (LDP), which perturbs sensitive data on the user side before it is shared or analyzed, e

Meng Jiang, Yi Jing Yu, Qing Zhao, Jianqiang Li

Cognitive Behavioral Therapy (CBT) is an effective technique for addressing the irrational thoughts stemming from mental illnesses, but it necessitates precise identification of cognitive pathways to be successfully implemented in patient care. In current society, individuals frequently express negative emotions on social media on specific topics, often exhi

Arieh Iserles, Georg Maierhofer

The efficient approximation of highly oscillatory integrals plays an important role in a wide range of applications. Whilst traditional quadrature becomes prohibitively expensive in the high-frequency regime, Levin methods provide a way to approximate these integrals in many settings at uniform cost. In this work, we present an accelerated version of Levin m

Jin Wang, JinFei Wang, Shuying Dai, Jiqiang Yu

Automated dialogue systems are important applications of artificial intelligence, and traditional systems struggle to understand user emotions and provide empathetic feedback. This study integrates emotional intelligence technology into automated dialogue systems and creates a dialogue generation model with emotional intelligence through deep learning and na

Daniel P. Hogan, Andrea Brennen

Wargames are a powerful tool for understanding and rehearsing real-world decision making. Automated play of wargames using artificial intelligence (AI) enables possibilities beyond those of human-conducted games, such as playing the game many times over to see a range of possible outcomes. There are two categories of wargames: quantitative games, with discre

Jihu Lei

This study investigates the efficient strategies for supply chain network optimization, specifically aimed at reducing industrial carbon emissions. Amidst escalating concerns about global climate change, industry sectors are motivated to counteract the negative environmental implications of their supply chain networks. This paper introduces a novel framework

Carlos Olarte, Elaine Pimentel

Similar to modal connectives, the exponential ! in intuitionistic linear logic (ILL) is not canonical, in the sense that if $i\not= j$ then $!^i F\not\equiv !^j F$. Intuitively, this means that we can mark the exponential with labels taken from a set I organized in a pre-order $\preceq$, obtaining (possibly infinitely-many) exponentials ($!^i$ for $i\in I$).

Nadir Samos Sáenz de Buruaga, Rafał Bistroń, Marcin Rudziński, Rodrigo Miguel Chinita Pereira

We present a comprehensive analysis of fidelity decay and error accumulation in faulty quantum circuit models. Our work devises an analytical bound for the average fidelity between desired and faulty output states, accounting for errors that may arise during the implementation of two-qubit gates and multi-qubit permutations. It is shown that fidelity decays

Zhuoya Geng, Jianmei Chen, Wanqiang Zhu

Unmanned boats, while navigating at sea, utilize active compensation systems to mitigate wave disturbances experienced by onboard instruments and equipment. However, there exists a lag in the measurement of unmanned boat attitudes, thus introducing unmanned boat motion attitude prediction to compensate for the lag in the signal acquisition process. This pape

T. -L. Pham, M. Guerboub, S. D. Wansi Wendj, A. Bouzid

Solid-state electrolytes mark a significant leap forward in the field of electrochemical energy storage, offering improved safety and efficiency compared to conventional liquid electrolytes. Among these, antiperovskite electrolytes, particularly those based on Li and Na, have emerged as promising candidates due to their superior ionic conductivity and straig

Zi-Qiang Chen, Long-Bin Chen, Cong-Feng Qiao, Ruilin Zhu

Recently, the ATLAS and CMS collaborations jointly announced the first evidence of the rare Higgs boson decay channel $H\to Z\gamma$, with a ratio of $2.2\pm 0.7$ times the leading order standard model (SM) prediction. In order to face this challenge, it is urgent to produce an even more accurate calculation within the SM. To this end, we calculate in this p

Nora Bauer, Kübra Yeter-Aydeniz, Elias Kokkas, George Siopsis

The rapid development of neutral atom quantum hardware provides a unique opportunity to design hardware-centered algorithms for solving real-world problems aimed at establishing quantum utility. In this work, we study the performance of two such algorithms on solving MaxCut problem for various weighted graphs. The first method uses a state-of-the-art machine

Kristian Börger, Alexander Belt, Lukas Arnold

In performance-based fire safety design, ensuring safe egress, e.g. by visibility of safety signs, is a crucial safety goal. Compliance with the building requirements is often demonstrated by simulations of smoke spread. Numerical models like the Fire Dynamics Simulator generally compute visibility as a local quantity using the light extinction coefficient,

Jonathan R. Stewart

One of the first steps in applications of statistical network analysis is frequently to produce summary charts of important features of the network. Many of these features take the form of sequences of graph statistics counting the number of realized events in the network, examples of which include the degree distribution, as well as the edgewise shared part

Xing-Yan Fan, Xiang-Ru Xie, Sheng-Ming Li, Jing-Ling Chen

As the simplest atom in nature, the hydrogen atom has been explored thoroughly from the perspective of non-relativistic quantum mechanics to relativistic quantum mechanics. Among the research on hydrogen atom, its energy level is the most basic, which can be obtained more conveniently predicated on the $SO(4)$ symmetry than the wave-equation resolution. More

Sizheng Cao, Xian-Hui Ge

This study explores the intricate real-time dynamics of a non-Hermitian system composed of two interconnected Sachdev-Ye-Kitaev (SYK) models. A central finding reveals that an excitation initially localized in the right SYK subsystem can be efficiently transmitted to the left subsystem subsequent to the characteristic scrambling time, a phenomenon facilitate

Annapurna Vadaparty, Daniel Zingaro, David H. Smith, Mounika Padala

The recent, widespread availability of Large Language Models (LLMs) like ChatGPT and GitHub Copilot may impact introductory programming courses (CS1) both in terms of what should be taught and how to teach it. Indeed, recent research has shown that LLMs are capable of solving the majority of the assignments and exams we previously used in CS1. In addition, p

Boran Wang

This work proposes a novel adaptive linearized alternating direction multiplier method (LADMM) to convex optimization, which improves the convergence rate of the LADMM-based algorithm by adjusting step-size iteratively.The innovation of this method is to utilize the information of the current iteration point to adaptively select the appropriate parameters, t

Robin Prinja, Peter Jordan, Florent Margnat

A noise modelling approach is proposed for bluff body wakes such as flow over a cylinder, where the primary noise source comprises large-scale coherent structures such as the vortex shedding flow feature. This phenomenon leads to Aeolian tones in the far-field, and is inherent in wake flows across a range of Reynolds numbers (Re), from low-Re to high-Re turb

Songze Li, Mingzhe Liu, Mengqi Chen

The rapid development of large machine learning (ML) models requires a massive amount of training data, resulting in booming demands of data sharing and trading through data markets. Traditional centralized data markets suffer from low level of security, and emerging decentralized platforms are faced with efficiency and privacy challenges. In this paper, we

Andre Opris, Duc-Cuong Dang, Frank Neumann, Dirk Sudholt

NSGA-II and NSGA-III are two of the most popular evolutionary multi-objective algorithms used in practice. While NSGA-II is used for few objectives such as 2 and 3, NSGA-III is designed to deal with a larger number of objectives. In a recent breakthrough, Wietheger and Doerr (IJCAI 2023) gave the first runtime analysis for NSGA-III on the 3-objective OneMinM

Tuomo Lehtonen, Anna Rapberger, Francesca Toni, Markus Ulbricht

Most existing computational tools for assumption-based argumentation (ABA) focus on so-called flat frameworks, disregarding the more general case. In this paper, we study an instantiation-based approach for reasoning in possibly non-flat ABA. We make use of a semantics-preserving translation between ABA and bipolar argumentation frameworks (BAFs). By utilizi

Rainis Haller, Jaan Kristjan Kaasik, Andre Ostrak

We address some open problems concerning Banach spaces of real-valued Lipschitz functions. Specifically, we prove that the diameter two properties differ from their weak-star counterparts in these spaces. In particular, we establish the existence of dual Banach spaces lacking the symmetric strong diameter two property but possessing its weak-star counterpart

Minh Tran, Sang Truong, Arthur F. A. Fernandes, Michael T. Kidd

In the food industry, assessing the quality of poultry carcasses during processing is a crucial step. This study proposes an effective approach for automating the assessment of carcass quality without requiring skilled labor or inspector involvement. The proposed system is based on machine learning (ML) and computer vision (CV) techniques, enabling automated

Tanzina Taher Ifty, Saleh Ahmed Shafin, Shoeb Mohammad Shahriar, Tashfia Towhid

Lung diseases remain a critical global health concern, and it's crucial to have accurate and quick ways to diagnose them. This work focuses on classifying different lung diseases into five groups: viral pneumonia, bacterial pneumonia, COVID, tuberculosis, and normal lungs. Employing advanced deep learning techniques, we explore a diverse range of models incl

Xiaoqing Chen

Matern correlation is of pivotal importance in spatial statistics and machine learning. This paper serves as a panoramic primer for this correlation with an emphasis on the exposition of its changing behavior and smoothness properties in response to the change of its two parameters. Such exposition is achieved through a series of simulation studies, the use

Orcun Cetintas, Tim Meinhardt, Guillem Brasó, Laura Leal-Taixé

Increasing the annotation efficiency of trajectory annotations from videos has the potential to enable the next generation of data-hungry tracking algorithms to thrive on large-scale datasets. Despite the importance of this task, there are currently very few works exploring how to efficiently label tracking datasets comprehensively. In this work, we introduc

Daniel Spitz

Many homogeneous, four-dimensional space-time geometries can be considered within real projective geometry, which yields a mathematically well-defined framework for their deformations and limits without the appearance of singularities. Focussing on generalized unitary transformation behavior, projective quantum fields can be axiomatically introduced, which t

Dihui Wang, Heng Ban, Puqing Jiang

While high-throughput (HT) computations have streamlined the discovery of promising new materials, experimental characterization remains challenging and time-consuming. One significant bottleneck is the lack of an HT thermal characterization technique capable of analyzing advanced materials exhibiting varying surface roughness and in-plane anisotropy. To tac

Bin Chen, Yuefeng Liu, Boyang Yu

In this study, we explore the correlation functions of thin-shell operators, represented semiclassically by a homogeneous, thin interface of dust particles. Employing the monodromy method, we successfully compute the contribution from the Virasoro vacuum block and present the monodromy equation in a closed form without assuming the probe limit. Although an a

Haojian Huang

The accurate wind speed series forecast is very pivotal to security of grid dispatching and the application of wind power. Nevertheless, on account of their nonlinear and non-stationary nature, their short-term forecast is extremely challenging. Therefore, this dissertation raises one short-term wind speed forecast pattern on the foundation of attention with

Shneha Biswas, Souren Adhikary, Sudipta Dutta

Within the first principle calculations, we propose a boron and nitrogen cluster incorporated graphene system for efficient valley polarization. The broken spatial inversion symmetry results in high Berry curvature at K and K' valleys of the hexagonal Brillouin zone in this semiconducting system. The consideration of excitonic quasiparticles within GW approx

Hoa T. Nguyen, Prabhakar Krishnan, Dilip Krishnaswamy, Muhammad Usman

Quantum cloud computing is an emerging paradigm of computing that empowers quantum applications and their deployment on quantum computing resources without the need for a specialized environment to host and operate physical quantum computers. This paper reviews recent advances, identifies open problems, and proposes future directions in quantum cloud computi

Vincent Cartillier, Grant Schindler, Irfan Essa

We present SLAIM - Simultaneous Localization and Implicit Mapping. We propose a novel coarse-to-fine tracking model tailored for Neural Radiance Field SLAM (NeRF-SLAM) to achieve state-of-the-art tracking performance. Notably, existing NeRF-SLAM systems consistently exhibit inferior tracking performance compared to traditional SLAM algorithms. NeRF-SLAM meth

Louis H. Marting, Kenichi Karatsu, Akira Endo, Jochem J. A. Baselmans

Many superconducting on-chip filter-banks suffer from poor coupling to the detectors behind each filter. This is a problem intrinsic to the commonly used half wavelength filter, which has a maximum theoretical coupling of 50 %. In this paper we introduce a phase coherent filter, called a directional filter, which has a theoretical coupling of 100 %. In order

Zihan Cao, Xiao Wu, Liang-Jian Deng

Recent diffusion probabilistic models (DPM) in the field of pansharpening have been gradually gaining attention and have achieved state-of-the-art (SOTA) performance. In this paper, we identify shortcomings in directly applying DPMs to the task of pansharpening as an inverse problem: 1) initiating sampling directly from Gaussian noise neglects the low-resolu

Yueqiang Hu, Yi Zhang, Yuting Jiang, Quan Wang

Metasurfaces composed of anisotropic subwavelength structures provide an ultrathin platform for a compact, real-time polarimeter. However, applications in polychromatic scenes are restricted by the limited operating bandwidths and degraded imaging quality due to the loss of spectral information. Here, we demonstrated full-color polarization imaging based on

Achintya Low, Tushar Kanti Bhowmik, Susanta Ghosh, Setti Thirupathaiah

We report the magnetic and magnetotransport properties and electronic band structure of the kagome Dirac semimetal HoMn$_6$Ge$_6$. Temperature-dependent electrical resistivity demonstrates various magnetic-transition-driven anomalies. Notably, a crossover from negative to positive magnetoresistance (MR) is observed at around 150 K. While the linear nonsatura

Raymundo Albert, Cecilia G. Galarza

The matrix pencil method (MPM) is a well-known technique for estimating the parameters of exponentially damped sinusoids in noise by solving a generalized eigenvalue problem. However, in several cases, this is an ill-conditioned problem whose solution is highly biased under small perturbations. When the estimation is performed to classify the observed signal

Takami Tohyama, Hiroki Maeda, Kenji Tsutsui, Shigetoshi Sota

Recent angle-resolved photoemission spectroscopy (ARPES) for a newly discovered doped one-dimensional (1D) Mott insulator Ba$_{2-x}$Sr$_x$CuO$_{3+\delta}$ proposed the presence of attractive charge interactions between neighboring sites if an 1D Hubbard model is employed to describe the material. On the other hand, long-range repulsive charge interactions we

Meghana Tedla, Shubham Kulkarni, Karthik Vaidhyanathan

The sustainability of Machine Learning-Enabled Systems (MLS), particularly with regard to energy efficiency, is an important challenge in their development and deployment. Self-adaptation techniques, recognized for their potential in energy savings within software systems, have yet to be extensively explored in Machine Learning-Enabled Systems (MLS), where r

Amir Esmaeili, Abderrahmen Mtibaa

The rapid advancement of autonomous driving technology is accompanied by substantial challenges, particularly the reliance on remote task execution without ensuring a reliable and accurate returned results. This reliance on external compute servers, which may be malicious or rogue, represents a major security threat. While researchers have been exploring ver

Xiangliang Kong, Chen Wang, Yiwei Zhang

Batch codes are a type of codes specifically designed for coded distributed storage systems and private information retrieval protocols. These codes have got much attention in recent years due to their ability to enable efficient and secure storage in distributed systems. In this paper, we study an array code version of the batch codes, which is called the \

James Weichert, Chinecherem Dimobi

As large language models (LLMs) become increasingly commonplace, concern about distinguishing between human and AI text increases as well. The growing power of these models is of particular concern to teachers, who may worry that students will use LLMs to write school assignments. Facing a technology with which they are unfamiliar, teachers may turn to publi

Théo Delemazure, Dominik Peters

Instant Runoff Voting (IRV) is used in elections for many political offices around the world. It allows voters to specify their preferences among candidates as a ranking. We identify a generalization of the rule, called Approval-IRV, that allows voters more freedom by allowing them to give equal preference to several candidates. Such weak orders are a more e

Arnab Kumar Maity, Satrajit Roy Chowdhury, Ray Li, Lada Markovtsova

Oncology drug development starts with a dose escalation phase to find the maximal tolerable dose (MTD). Dose limiting toxicity (DLT) is the primary endpoint for dose escalation phase. Traditionally, model-based dose escalation trial designs recommend a dose for escalation based on an assumed dose-DLT relationship. Pharmacokinetic (PK) data are often availabl

Fabio Bagagiolo, Stefan Moreti

In this article we deal with the Cauchy problem for the quasi-linear scalar conservation law \[u_t+ {\cal F}(u)_t+u_x=0,\] where ${\cal F}$ is a specific hysteresis operator, namely the Play operator. Hysteresis models a rate-independent memory relationship between the input $u$ and its output. Its presence in the partial differential equation gives a partic

Fabian Wein, Julian Mirbach, Aniket Angre, Jannis Greifenstein

A novel approach for creating tool paths for continuous carbon fiber-reinforced thermoplastic 3D printing is introduced. The aim is to enable load-bearing connections while avoiding non-manufacturable crossings of paths by generating layer specific patterns. We require a graph representation of the structural design with given desired continuous fiber connec

Daniel Cebrián-Lacasa, Pedro Parra-Rivas, Daniel Ruiz-Reynés, Lendert Gelens

The FitzHugh-Nagumo equation, originally conceived in neuroscience during the 1960s, became a key model providing a simplified view of excitable neuron cell behavior. Its applicability, however, extends beyond neuroscience into fields like cardiac physiology, cell division, population dynamics, electronics, and other natural phenomena. In this review spannin

Jia-Hui Zhang, Feng Mei, Liantuan Xiao, Suotang Jia

Local density of states (LDOS) is emerging as powerful means of exploring synthetic topological phases. However, the current LDOS detection method remains rare and merely works for static situations. Here, we introduce a generic dynamical method to detect both the static and Floquet LDOS, based on an elegant connection between dynamics of chiral density and

Laura Lopez-Honorez

The redshifted 21cm signal from the Cosmic Dawn is expected to provide unprecedented insights into early Universe astrophysics and cosmology. Here, we briefly summarize how decaying dark matter can heat the intergalactic medium before the first galaxies, leaving a distinctive imprint on the 21cm power spectrum. We discuss the first Fisher matrix forecasts on