October 2023 arXiv papers — page 15

Zhi Qi

In this paper, on the complex field $\mathbb{C}$, we prove two integral formulae for the Hankel-Mellin transform and the double Fourier-Mellin transform of Bessel functions, both resulting the hypergeometric function. As two applications, we use the former integral formula to make explicit the spectral formula of Bruggeman and Motohashi for the fourth moment

Chao Huang

This paper studies multilateral matching in which agents may negotiate contracts within any coalition. We assume scale economies such that an agent substitutes some existing contracts with new ones only if the latter involve a set of partners that is weakly larger than the original. A weakly setwise stable (or setwise stable) outcome exists and can be found

Argyrios Loules, Nektarios Vlahakis

Relativistic shocks are present in all high-energy astrophysical processes involving relativistic plasma outflows interacting with their ambient medium. While a well understood process in the context of relativistic hydrodynamics and ideal magnetohydrodynamics, there is little to no understanding of their propagation in media with a finite electrical conduct

Tingting Wu, Zhiyan Du, Zhi Li, Feng-Lei Fan

Recovering clear images from blurry ones with an unknown blur kernel is a challenging problem. Deep image prior (DIP) proposes to use the deep network as a regularizer for a single image rather than as a supervised model, which achieves encouraging results in the nonblind deblurring problem. However, since the relationship between images and the network arch

Miriam Rengel, Jakob Adamczewski

The study of planetary atmospheres is crucial for understanding the origin, evolution, and processes that shape celestial bodies like planets, moons and comets. The interpretation of planetary spectra requires a detailed understanding of radiative transfer (RT) and its application through computational codes. With the advancement of observations, atmospheric

Andrea Gnoli, Giorgio Pontuale, Andrea Puglisi, Alberto Petri

It is well known that energy dissipation and finite size can deeply affect the dynamics of granular matter, often making usual hydrodynamic approaches problematic. Here we report on the experi-mental investigation of a small model system, made of ten beads constrained into a 1-d geometry by a narrow vertical pipe and shaken at the base by a piston excited by

Jakub Horsky, Andrew Wynn

We introduce Structure Informed Neural Networks (SINNs), a novel method for solving boundary observation problems involving PDEs. The SINN methodology is a data-driven framework for creating approximate solutions to internal variables on the interior of a domain, given only boundary data. The key idea is to use neural networks to identify a co-ordinate trans

Jonathan Schilhan, Thilo Weinert

We provide answers to a question brought up by Erd\H{o}s about the construction of Wetzel families in the absence of the continuum hypothesis - a Wetzel family is a family $\mathcal{F}$ of entire functions on the complex plane which pointwise assumes fewer than $\vert \mathcal{F} \vert$ values. To be more precise, we show that the existence of a Wetzel famil

Ahmad Abdi, Gérard Cornuéjols, Giacomo Zambelli

Let $D=(V,A)$ be a digraph. For an integer $k\geq 1$, a $k$-arc-connected flip is an arc subset of $D$ such that after reversing the arcs in it the digraph becomes (strongly) $k$-arc-connected. The first main result of this paper introduces a sufficient condition for the existence of a $k$-arc-connected flip that is also a submodular flow for a crossing subm

Astero Provata

When chaotic oscillators are coupled in complex networks a number of interesting synchronization phenomena emerge. Notable examples are the frequency and amplitude chimeras, chimera death states, solitary states as well as combinations of these. In a previous study [Journal of Physics: Complexity, 2020, 1(2), 025006], a toy model was introduced addressing po

Gouki Minegishi, Yusuke Iwasawa, Yutaka Matsuo

Grokking is an intriguing phenomenon of delayed generalization, where neural networks initially memorize training data with perfect accuracy but exhibit poor generalization, subsequently transitioning to a generalizing solution with continued training. While factors such as weight norms and sparsity have been proposed to explain this delayed generalization,

Dong Gaogao, Sun Nannan, Wang Fan

The rapid advancement of technology underscores the critical importance of robustness in complex network systems. This paper presents a framework for investigating the structural robustness of interconnected network models. This paper presents a framework for investigating the structural robustness of interconnected network models. In this context, we define

Jialin Yi

A Multi-Agent Cooperative Learning (MACL) system is an artificial intelligence (AI) system where multiple learning agents work together to complete a common task. Recent empirical success of MACL systems in various domains (e.g. traffic control, cloud computing, robotics) has sparked active research into the design and analysis of MACL systems for sequential

Dominik Czernia, Piotr Konieczny, Marcin Perzanowski, Dawid Pinkowicz

Molecular magnetism aims to design materials with unique properties at the molecular level, focusing on the systematic synthesis of new chemical compounds. In this paper, we propose an alternative route to engineer molecular magnetic materials through plasma irradiation. Our research indicates that the long-range magnetic order temperature in the three-dimen

F. A. Ivanyuk, C. Ishizuka, S. Chiba

We have generalized the four-dimensional Langevin approach used in our previous works for the description of fission process to the five-dimensional by considering the neck parameter $\eps$ in the two-center shell model shape parametrization as an independent dynamical variable. The calculated results for the mass distribution of fission fragments are in bet

András Csépai

We use a classifying space construction by Sz\H{u}cs and Terpai to extend Salomonsen's exact sequence from cobordism groups of immersions to cobordism groups of hyperplane projections of immersions with prescribed singularities. We apply this to obtain results on these cobordism groups in small and large codimensional cases.

Tackgeun You, Mijeong Kim, Jungtaek Kim, Bohyung Han

We propose a novel approach to learning the generative neural fields represented by linear combinations of implicit basis networks. Our algorithm learns basis networks in the form of implicit neural representations and their coefficients in a latent space by either conducting meta-learning or adopting auto-decoding paradigms. The proposed method easily enlar

Leah Chrestien, Tomás Pevný, Stefan Edelkamp, Antonín Komenda

In imitation learning for planning, parameters of heuristic functions are optimized against a set of solved problem instances. This work revisits the necessary and sufficient conditions of strictly optimally efficient heuristics for forward search algorithms, mainly A* and greedy best-first search, which expand only states on the returned optimal path. It th

Xuefeng Bai, Jialong Wu, Yulong Chen, Zhongqing Wang

Constituency parsing is a fundamental yet unsolved challenge in natural language processing. In this paper, we examine the potential of recent large language models (LLMs) to address this challenge. We reformat constituency parsing as a sequence-to-sequence generation problem and evaluate the performance of a diverse range of LLMs under zero-shot, few-shot,

Philipp Stangl, Christoph P. Neumann

We consider the problem of supply chain data visibility in a blockchain-enabled supply chain network. Existing methods typically record transactions happening in a supply chain on a single blockchain and are limited in their ability to deal with different levels of data visibility. To address this limitation, we present FoodFresh -- a multi-chain consortium

Mehdi Letafati, Samad Ali, Matti Latva-aho

In this paper, conditional denoising diffusion probabilistic models (DDPMs) are proposed to enhance the data transmission and reconstruction over wireless channels. The underlying mechanism of DDPM is to decompose the data generation process over the so-called "denoising" steps. Inspired by this, the key idea is to leverage the generative prior of diffusion

Amir Pakmehr, Andreas Aßmuth, Christoph P. Neumann, Gerald Pirkl

Security challenges for Cloud or Fog-based machine learning services pose several concerns. Securing the underlying Cloud or Fog services is essential, as successful attacks against these services, on which machine learning applications rely, can lead to significant impairments of these applications. Because the requirements for AI applications can also be d

Esperanza Maya-Barbecho, Samira Baid, José-Manuel Arias, José-Enrique García-Ramos

In this contribution, the shape coexistence phenomenon near the proton sub-shell closure at Z=40 is analyzed. Particular emphasis is placed on extracting the nuclear deformation values by examining experimental B(E2) transition rates and observing how the kinematic moment of inertia evolves in these nuclei. Based on the analysis of these two observables, we

Joseph C. Chapman, Muneer Alshowkan, Bing Qi, Nicholas A. Peters

The quantum digital signature protocol offers a replacement for most aspects of public-key digital signatures ubiquitous in today's digital world. A major advantage of a quantum-digital-signatures protocol is that it can have information-theoretic security, whereas public-key cryptography cannot. Here we demonstrate and characterize hardware to implement ent

Belhassen Dehman, Enrique Zuazua

The wave equation on a bounded domain of $\R^{n}$ with non homogeneous boundary Dirichlet data or sources supported on a subset of the boundary is considered. We analyze the problem of observing the source out of boundary measurements done away from its support. We first show that observability inequalities may not hold unless an infinite number of derivativ

Telikepalli Kavitha, Kazuhisa Makino, Ildikó Schlotter, Yu Yokoi

Our input is a directed, rooted graph $G = (V \cup \{r\},E)$ where each vertex in $V$ has a partial order preference over its incoming edges. The preferences of a vertex extend naturally to preferences over arborescences rooted at $r$. We seek a popular arborescence in $G$, i.e., one for which there is no "more popular" arborescence. Popular arborescences ha

Chandrani Kumari, Rahul Siddharthan

We provide new algorithms for two tasks relating to heterogeneous tabular datasets: clustering, and synthetic data generation. Tabular datasets typically consist of heterogeneous data types (numerical, ordinal, categorical) in columns, but may also have hidden cluster structure in their rows: for example, they may be drawn from heterogeneous (geographical, s

Hangyu Wang, Jianghao Lin, Xiangyang Li, Bo Chen

Click-through rate (CTR) prediction plays as a core function module in various personalized online services. The traditional ID-based models for CTR prediction take as inputs the one-hot encoded ID features of tabular modality, which capture the collaborative signals via feature interaction modeling. But the one-hot encoding discards the semantic information

Pranay Kothari, Deepak Chopra, Manjot Singh, Shivam Bhardwaj

In today's world, secure and efficient biometric authentication is of keen importance. Traditional authentication methods are no longer considered reliable due to their susceptibility to cyber-attacks. Biometric authentication, particularly fingerprint authentication, has emerged as a promising alternative, but it raises concerns about the storage and use of

Dave B. H. Verweg, Bernard J. T. Jones, Rien van de Weygaert

The observation that accelerated cosmic expansion appears to start around the time that nonlinear cosmic structure is appearing seems like an extraordinary coincidence, unless the acceleration is somehow driven by the emergence of the structure. That has given rise to the controversial concept of a gravitational backreaction through which inhomogeneity becom

Maosheng Yang, Viacheslav Borovitskiy, Elvin Isufi

We propose principled Gaussian processes (GPs) for modeling functions defined over the edge set of a simplicial 2-complex, a structure similar to a graph in which edges may form triangular faces. This approach is intended for learning flow-type data on networks where edge flows can be characterized by the discrete divergence and curl. Drawing upon the Hodge

Ralf Graafe, Qutub Syed Sha, Florian Geissler, Michael Paulitsch

Transient or permanent faults in hardware can render the output of Neural Networks (NN) incorrect without user-specific traces of the error, i.e. silent data errors (SDE). On the other hand, modern NNs also possess an inherent redundancy that can tolerate specific faults. To establish a safety case, it is necessary to distinguish and quantify both types of c

Seppe Staelens, Gijs Nelemans

Context. The Astrophysical Gravitational Wave Background (AGWB) is a collective signal of astrophysical gravitational wave sources and is dominated by compact binaries. Its measurement is one of the science goals of current and future gravitational wave detectors. Aims. We aim to determine what population of compact binaries dominates the AGWB in the mHz ban

Jinsong Zhang, Lingfeng Gu, Yu-Kun Lai, Xueyang Wang

Group detection, especially for large-scale scenes, has many potential applications for public safety and smart cities. Existing methods fail to cope with frequent occlusions in large-scale scenes with multiple people, and are difficult to effectively utilize spatio-temporal information. In this paper, we propose an end-to-end framework,GroupTransformer, for

Ludovico Bruni Bruno, Matteo Semplice, Stefano Serra-Capizzano

Weights are geometrical degrees of freedom that allow to generalise Lagrangian finite elements. They are defined through integrals over specific supports, well understood in terms of differential forms and integration, and lie within the framework of finite element exterior calculus. In this work we exploit this formalism with the target of identifying suppo

Jeffrey W. Doser, Andrew O. Finley, Marc Kéry, Elise F. Zipkin

Numerous modeling techniques exist to estimate abundance of plant and wildlife species. These methods seek to estimate abundance while accounting for multiple complexities found in ecological data, such as observational biases, spatial autocorrelation, and species correlations. There is, however, a lack of user-friendly and computationally efficient software

Mariachiara Di Cosmo, Giovanna Migliorelli, Matteo Francioni, Andi Mucaj

This study explores the use of Federated Learning (FL) for stenosis detection in coronary angiography images (CA). Two heterogeneous datasets from two institutions were considered: Dataset 1 includes 1219 images from 200 patients, which we acquired at the Ospedale Riuniti of Ancona (Italy); Dataset 2 includes 7492 sequential images from 90 patients from a pr

Zhiwei Hao, Jianyuan Guo, Kai Han, Yehui Tang

Knowledge distillation~(KD) has proven to be a highly effective approach for enhancing model performance through a teacher-student training scheme. However, most existing distillation methods are designed under the assumption that the teacher and student models belong to the same model family, particularly the hint-based approaches. By using centered kernel

Khanh Chau Le, Hoang Giang Bui

A formulation of the asymptotically exact first-order shear deformation theory for linear-elastic homogeneous plates in the rescaled coordinates and rotation angles is considered. This allows the development of its asymptotically accurate and shear-locking-free finite element implementation. As applications, numerical simulations are performed for circular a

Mohit, Ranjana Jain

In this article, we discuss the relationship between Birkhoff-James orthogonality of elementary tensors in the space $L^{p}(\mu)\otimes^{\Delta_{p}}X,\; (1\leq p<\infty)$ with the individual elements in their respective spaces, where $X$ is a Banach space whose norm is Fr$\acute{e}chet$ differentiable and $\Delta_{p}$ is the natural norm induced by $L^{p}(\m

R. James Cotton, Colleen Peyton

Easy access to precise 3D tracking of movement could benefit many aspects of rehabilitation. A challenge to achieving this goal is that while there are many datasets and pretrained algorithms for able-bodied adults, algorithms trained on these datasets often fail to generalize to clinical populations including people with disabilities, infants, and neonates.

Xin Wei, Xiande Zhang, Gennian Ge

Separating hash families are useful combinatorial structures which generalize several well-studied objects in cryptography and coding theory. Let $p_t(N, q)$ denote the maximum size of universe for a $t$-perfect hash family of length $N$ over an alphabet of size $q$. In this paper, we show that $q^{2-o(1)}<p_t(t, q)=o(q^2)$ for all $t\geq 3$, which answers a

Xintian Ren, Jun Wu, Hansong Xu, Qianqian Pan

Semantic communication has emerged as a new deep learning-based communication paradigm that drives the research of end-to-end data transmission in tasks like image classification, and image reconstruction. However, the security problem caused by semantic attacks has not been well explored, resulting in vulnerabilities within semantic communication systems ex

Z. Prudil, A. Kunder, I. Dekany, A. J Koch-Hansen

We present a new set of period-absolute magnitude-metallicity (PMZ) relations for single-mode RR Lyrae stars calibrated for the optical $G_{\rm BP}$, $V$, $G$, $G_{\rm RP}$, near-infrared $I$, $J$, $H$, and $K_{\rm s}$ passbands. We compiled a large dataset (over $100$ objects) of fundamental and first-overtone RR~Lyrae pulsators consisting of mean intensity

Xin Wei, Xiande Zhang, Gennian Ge

To prevent service time bottlenecks in distributed storage systems, the access balancing problem has been studied by designing almost supermagic edge labelings of certain graphs to balance the access requests to different servers. In this paper, we introduce the concept of robustness of edge labelings under limited-magnitude swaps, which is important for stu

Gökberk Özsoy, Luis Salamanca, Matthew Connelly, Raymond Hicks

In the current paper, we present the KG-FRUS dataset, comprised of more than 300,000 US government diplomatic documents encoded in a Knowledge Graph (KG). We leverage the data of the Foreign Relations of the United States (FRUS) (available as XML files) to extract information about the documents and the individuals and countries mentioned within them. We use

Sourav Bhattacharya, Nitin Joshi, Kinsuk Roy

We consider a massless and minimally coupled self interacting quantum scalar field in the inflationary de Sitter spacetime. The scalar potential is taken to be a hybrid, $V(\phi)= \lambda \phi^4/4!+\beta \phi^3/3!$ ($\lambda >0$). Compared to the earlier well studied $\beta=0$ case, the present potential has a rolling down effect due to the $\phi^3$ term, al

Anuj P. Lara, Ambaresh Sahoo, Samudra Roy

We investigate the dynamics of a spatial discrete soliton and the radiation families emitted by it inside a parity-time ($\mathcal{PT}$)-symmetric waveguide array with alternate gain-loss channels. A strong spatial soliton that evolves inside the waveguide array due to the balance between discrete diffraction and Kerr nonlinearity excites linear waves in the

Aleix Alcacer, Marina Martínez-Garcia, Irene Epifanio

The aim of ordinal classification is to predict the ordered labels of the output from a set of observed inputs. Interval-valued data refers to data in the form of intervals. For the first time, interval-valued data and interval-valued functional data are considered as inputs in an ordinal classification problem. Six ordinal classifiers for interval data and

Seongun Kim, Jaesik Choi

Deep policy networks enable robots to learn behaviors to solve various real-world complex tasks in an end-to-end fashion. However, they lack transparency to provide the reasons of actions. Thus, such a black-box model often results in low reliability and disruptive actions during the deployment of the robot in practice. To enhance its transparency, it is imp

Kurt Liffman

Discs of gas and dust are ubiquitous around protostars. Hypothetical disc viscosity is thought to cause the gas and dust to accrete onto the star. Turbulence within the disc might be the source of this disc viscosity. However, observed protostellar disc turbulence often appears to be small and not always conducive to disc accretion. In addition, theories for

James C. Blakesley, Ruy S. Bonilla, Marina Freitag, Alex M. Ganose

Photovoltaics (PVs) are a critical technology for curbing growing levels of anthropogenic greenhouse gas emissions, and meeting increases in future demand for low-carbon electricity. In order to fulfil ambitions for net-zero carbon dioxide equivalent (CO₂eq) emissions worldwide, the global cumulative capacity of solar PVs must increase by an order

Intesaaf Ashraf, Stephane Dorbolo

This article experimentally investigates the exit dynamics of two different spheres i.e. a smooth sphere and a sphere with dimples at a constant speed. Employing high-speed experimental observations, the study investigates the key characteristic lengths and hydrodynamic forces between the sphere's surface and water. The experiments were performed at differen

Keisuke Hoshino, Hayato Nasu

We relativise double categories of relations to stable orthogonal factorisation systems. Furthermore, we present the characterisation of the relative double categories of relations in two ways. The first utilises a generalised comprehension scheme, and the second focuses on a specific class of vertical arrows defined solely double-categorically. We organise

Kyowoon Lee, Seongun Kim, Jaesik Choi

Diffusion-based planning has shown promising results in long-horizon, sparse-reward tasks by training trajectory diffusion models and conditioning the sampled trajectories using auxiliary guidance functions. However, due to their nature as generative models, diffusion models are not guaranteed to generate feasible plans, resulting in failed execution and pre

Chi Zhang, Wenbin Guo

In this paper, we establish the theory of nilpotent hypergroups and study some properties of nilpotent hypergroups and provided some structural characterizations of nilpotent hypergroups.

Włodzisław Duch

The complexity of cultures in the modern world is now beyond human comprehension. Cognitive sciences cast doubts on the traditional explanations based on mental models. The core subjects in humanities may lose their importance. Humanities have to adapt to the digital age. New, interdisciplinary branches of humanities emerge. Instant access to information wil

Seongun Kim, Kyowoon Lee, Jaesik Choi

Mutual information-based reinforcement learning (RL) has been proposed as a promising framework for retrieving complex skills autonomously without a task-oriented reward function through mutual information (MI) maximization or variational empowerment. However, learning complex skills is still challenging, due to the fact that the order of training skills can

Adara M. Blaga

We characterize the $2$-Killing vector fields on a multiply twisted product manifold, with a special view towards generalized spacetimes. More precisely, we determine the nonlinear differential equations that completely describe them and the twisted functions, give particular solutions, and construct examples.

Hiroyuki Tajima, Hajime Moriya, Wataru Horiuchi, Eiji Nakano

Neutron star observations, as well as experiments on neutron-rich nuclei, used to motivate one to look at degenerate nuclear matter from its extreme, namely, pure neutron matter. As an important next step, impurities and clusters in dilute neutron matter have attracted special attention. In this paper, we review in-medium properties of these objects on the b

F. F. Karpeshin

Experimental data on the muon-induced prompt fission are analyzed and compared to theory. Good agreement is observed for the 2p to 1s and 3d to 1s transitions. Anomalously big nonradiative width in the case of 3d to 1s transition is surprised. Ways of resolving this puzzle are discussed.

David Samuel

This paper explores the use of latent bootstrapping, an alternative self-supervision technique, for pretraining language models. Unlike the typical practice of using self-supervision on discrete subwords, latent bootstrapping leverages contextualized embeddings for a richer supervision signal. We conduct experiments to assess how effective this approach is f

Thomas Duguet, Andreas Ekström, Richard J. Furnstahl, Sebastian König

Eigenvector continuation is a computational method for parametric eigenvalue problems that uses subspace projection with a basis derived from eigenvector snapshots from different parameter sets. It is part of a broader class of subspace-projection techniques called reduced-basis methods. In this colloquium article, we present the development, theory, and app

Adrian Cosma, Emilian Radoi

Gait analysis is proven to be a reliable way to perform person identification without relying on subject cooperation. Walking is a biometric that does not significantly change in short periods of time and can be regarded as unique to each person. So far, the study of gait analysis focused mostly on identification and demographics estimation, without consider

Wei Liu, Jingzhi Yan, Guangcheng Xiao, Xiukun Li

Context. 1A 0535+262 is a high-mass X-ray binary that went into a giant X-ray outburst in 2020. During this event, the X-ray luminosity reached the highest value measured over the last 30 years. Aims. Our aim is to study the long-term variability of 1A 0535+262 before and after the 2020 major X-ray outburst and to uncover the mechanism that led to the X-ray

Gyungmin Cho, Dohun Kim

Advancements in the implementation of quantum hardware have enabled the acquisition of data that are intractable for emulation with classical computers. The integration of classical machine learning (ML) algorithms with these data holds potential for unveiling obscure patterns. Although this hybrid approach extends the class of efficiently solvable problems

Xin Yu, Yuan-Chen Guo, Yangguang Li, Ding Liang

Text-to-3D generation has made remarkable progress recently, particularly with methods based on Score Distillation Sampling (SDS) that leverages pre-trained 2D diffusion models. While the usage of classifier-free guidance is well acknowledged to be crucial for successful optimization, it is considered an auxiliary trick rather than the most essential compone

Mosarof Sarkar, Shubh N. Singh

Let $X$ be a nonempty set and $\mathcal{P}=\{X_i\colon i\in I\}$ a partition of $X$. Denote by $T(X)$ the full transformation semigroup on $X$, and $T(X, \mathcal{P})$ the subsemigroup of $T(X)$ consisting of all transformations that preserve $\mathcal{P}$. For every subsemigroup $\mathbb{S}(I)$ of $T(I)$, let $T_{\mathbb{S}(I)}(X,\mathcal{P})$ be the semigr

Federico Rollo, Andrea Zunino, Nikolaos Tsagarakis, Enrico Mingo Hoffman

In today's Human-Robot Interaction (HRI) scenarios, a prevailing tendency exists to assume that the robot shall cooperate with the closest individual or that the scene involves merely a singular human actor. However, in realistic scenarios, such as shop floor operations, such an assumption may not hold and personalized target recognition by the robot in crow

Vishvesh Kumar, Michael Ruzhansky, Hong-Wei Zhang

Let $\Delta$ be the Laplace-Beltrami operator on a non-compact symmetric space of any rank, and denote the bottom of its $L^2$-spectrum as $-|\rho|^{2}$. In this paper, we provide a comprehensive characterization of both the sufficient and necessary conditions ensuring the validity of the Stein-Weiss inequality for the entire family of operators $\lbrace{(-\

Muhammad Yaqub, Feng Jinchao

Breast cancer (BC) significantly contributes to cancer-related mortality in women, underscoring the criticality of early detection for optimal patient outcomes. A mammography is a key tool for identifying and diagnosing breast abnormalities; however, accurately distinguishing malignant mass lesions remains challenging. To address this issue, we propose a nov

Minxing Zhang, Ning Yu, Rui Wen, Michael Backes

Generative models have demonstrated revolutionary success in various visual creation tasks, but in the meantime, they have been exposed to the threat of leaking private information of their training data. Several membership inference attacks (MIAs) have been proposed to exhibit the privacy vulnerability of generative models by classifying a query image as a

Juan Vidal Alegria, Joao Vieira, Fredrik Rusek

Reconfigurable surface (RS) has been shown to be an effective solution for improving wireless communication links in general multi-user multiple-input multiple-output (MU-MIMO) setting. Current research efforts have been largely directed towards the study of reconfigurable intelligent surface (RIS), which corresponds to an RS made of passive reconfigurable e

Samuel Lensgraf, Ankita Sarkar, Adithya Pediredla, Devin Balkcom

We present a scalable combined localization infrastructure deployment and task planning algorithm for underwater assembly. Infrastructure is autonomously modified to suit the needs of manipulation tasks based on an uncertainty model on the infrastructure's positional accuracy. Our uncertainty model can be combined with the noise characteristics from multiple

Elisa Cascina, Andrea Pellegrino, Lorenzo Tozzi

This work addresses the need for efficient waste sorting strategies in Materials Recovery Facilities to minimize the environmental impact of rising waste. We propose resource-constrained semantic segmentation models for segmenting recyclable waste in industrial settings. Our goal is to develop models that fit within a 10MB memory constraint, suitable for edg

Zehao Jin, Benjamin L. Davis

Our knowledge of supermassive black holes (SMBHs) and their relation to their host galaxies is still limited, and there are only around 150 SMBHs that have their masses directly measured and confirmed. Better black hole mass scaling relations will help us reveal the physics of black holes, as well as predict black hole masses that are not yet measured. Here,

Farzeen Munir, Shoaib Azam, Tomasz Kucner, Ville Kyrki

Object detection is a core component of perception systems, providing the ego vehicle with information about its surroundings to ensure safe route planning. While cameras and Lidar have significantly advanced perception systems, their performance can be limited in adverse weather conditions. In contrast, millimeter-wave technology enables radars to function

Gavin Ball, Jesse Madnick, Uwe Semmelmann

The homogeneous minimal hypersurfaces in $S^n$ have $g = 1,2,3,4$, or $6$ distinct (constant) principal curvatures. While the Morse index and nullity have been calculated for all such hypersurfaces having $g = 1,2,3$, it has remained an open problem to compute these quantities for any of those with $g = 4$ or $6$. In this paper, we calculate the Morse index

Vagrant Gautam, Miaoran Zhang, Dietrich Klakow

If a question cannot be answered with the available information, robust systems for question answering (QA) should know _not_ to answer. One way to build QA models that do this is with additional training data comprised of unanswerable questions, created either by employing annotators or through automated methods for unanswerable question generation. To show

Patric Feldmeier, Philipp Straubinger, Gordon Fraser

Games are usually created incrementally, requiring repeated testing of the same scenarios, which is a tedious and error-prone task for game developers. Therefore, we aim to alleviate this game testing process by encapsulating it into a game called Playtest, which transforms the tiring testing process into a competitive game with a purpose. Playtest automates

Atharva Bagul, Patrick Ogle, Robert Antonucci, Philip Maloney

The prototypical powerful FR \Romannum{2} radio galaxy Cygnus A fits extremely well into the quasar/radio galaxy unified model: high polarization with an angle almost perpendicular to the radio jet and polarized flux showing broad permitted lines. It has been claimed that ionized gas in the torus reveals a very clear torus shape via Bremmstrahlung emission.

Frida Viset, Rudy Helmons, Manon Kok

Accurately estimating the positions of multi-agent systems in indoor environments is challenging due to the lack of Global Navigation Satelite System (GNSS) signals. Noisy measurements of position and orientation can cause the integrated position estimate to drift without bound. Previous research has proposed using magnetic field simultaneous localization an

Paweł Pasteczka

We generalize the result of (Witkowski, 2014) which binds orders of homogeneous, symmetric means $M,N,K \colon\mathbb{R}_+^2 \to \mathbb{R}_+$ of power growth that satisfy the invariance equation $K(M(x,y),N(x,y))=K(x,y)$ to the broader class of means. Moreover, we define the lower- and the upper-order which gives us insight into the order of the solution of

Martina Matusko, Ivan Ryger, Gwenhaël Goavec-Merou, Jacques Millo

This article reports on the use of a Field Programmable Gate Array (FPGA) platform for local ultra-stable optical frequency distribution through a 90 m-long fiber network. This platform is used to implement a fully digital treatment of the Doppler-cancellation scheme required by fiber links to be able to distribute ultra-stable frequencies. We present a nove

M. Milanesio, L. Paolozzi, T. Moretti, R. Cardella

A monolithic silicon pixel prototype produced for the MONOLITH ERC Advanced project was irradiated with 70 MeV protons up to a fluence of 1 x 10^16 1 MeV n_eq/cm^2. The ASIC contains a matrix of hexagonal pixels with 100 {\mu}m pitch, readout by low-noise and very fast SiGe HBT frontend electronics. Wafers with 50 {\mu}m thick epilayer with a resistivity of

Daniele Baieri, Donato Crisostomi, Stefano Esposito, Filippo Maggioli

In this work, we introduce an efficient generation procedure to produce synthetic multi-modal datasets of fluid simulations. The procedure can reproduce the dynamics of fluid flows and allows for exploring and learning various properties of their complex behavior, from distinct perspectives and modalities. We employ our framework to generate a set of thought

LHCb collaboration, R. Aaij, A. S. W. Abdelmotteleb, C. Abellan Beteta

A search for $\textit{CP}$ violation in $D^{0} \rightarrow K_{S}^{0} K^{+} \pi^{-} $ and $D^{0} \rightarrow K_{S}^{0} K^{-} \pi^{+} $ decays is reported. The search is performed using an unbinned model-independent method known as the energy test that probes local $\textit{CP}$ violation in the phase space of the decays. The data analysed correspond to an int

Franc Forstneric

Let $X$ be a Stein manifold of dimension $n\ge 1$. Given a continuous positive increasing function $h$ on $\mathbb R_+=[0,\infty)$ with $\lim_{t\to\infty} h(t)=\infty$, we construct a proper holomorphic embedding $f=(z,w):X\hookrightarrow \mathbb C^{n+1}\times \mathbb C^n$ satisfying $|w(x)|<h(|z(x)|)$ for all $x\in X$. In particular, $f$ may be chosen such

Sajjan Sheoran, Saswata Bhattacharya

Magnetism-driven nonrelativistic spin splittings (NRSS) are promising for highly efficient spintronics applications. Although 2D centrosymmetric (in four-dimensional spacetime) antiferromagnets are abundant, they have not received extensive research attention owing to symmetry-forbidden spin polarization and magnetization. Here, we demonstrate a paradigm to

Dang Minh Nguyen, Chenfei Wang, Yan Shen, Yifan Zeng

Graph Neural Network (GNN) is the trending solution for item retrieval in recommendation problems. Most recent reports, however, focus heavily on new model architectures. This may bring some gaps when applying GNN in the industrial setup, where, besides the model, constructing the graph and handling data sparsity also play critical roles in the overall succe

Shuaibing Luo, Eskil Rydhe

This paper studies the function spaces $\mathcal{D}(\mu)$ by Richter and Aleman, and $\mathcal{D}_{\vec{\mu}}$ by the second author. It is known that the forward shift $M_z$ is bounded and expansive on $\mathcal{D}(\mu)$, and therefore $\mathcal{D}(\mu)$ coincides with a de~Branges--Rovnyak space $\mathcal{H}[B]$. We show that such a $B$ is rational if and o

Navodini Wijethilake, Steve Connor, Anna Oviedova, Rebecca Burger

Vestibular Schwannoma is a benign brain tumour that grows from one of the balance nerves. Patients may be treated by surgery, radiosurgery or with a conservative "wait-and-scan" strategy. Clinicians typically use manually extracted linear measurements to aid clinical decision making. This work aims to automate and improve this process by using deep learning

Qun Ren, Yuxin Lang, Yuqi Ja, Xia Xiao

The combination of surface coils and metamaterials remarkably enhance magnetic resonance imaging (MRI) performance for significant local staging flexibility. However, due to the coupling in between, impeded signal-to-noise ratio (SNR) and low-contrast resolution, further hamper the future growth in clinical MRI. In this paper, we propose a high-Q metasurface

Ahmad-Reza Ehyaei, Golnoosh Farnadi, Samira Samadi

Despite the essential need for comprehensive considerations in responsible AI, factors like robustness, fairness, and causality are often studied in isolation. Adversarial perturbation, used to identify vulnerabilities in models, and individual fairness, aiming for equitable treatment of similar individuals, despite initial differences, both depend on metric

Bernardo Fichera, Viacheslav Borovitskiy, Andreas Krause, Aude Billard

Gaussian process regression is widely used because of its ability to provide well-calibrated uncertainty estimates and handle small or sparse datasets. However, it struggles with high-dimensional data. One possible way to scale this technique to higher dimensions is to leverage the implicit low-dimensional manifold upon which the data actually lies, as postu

Alejandro Perez

A brief overview of the discovery that macroscopic black holes are thermodynamical systems is presented. They satisfy the laws of thermodynamics and are associated with a temperature and an entropy equal to one quarter of their horizon area in Planck units. They emit black body radiation and slowly evaporate as a consequence of Heisenberg's uncertainty princ

Zhenyu Wang, Selase Kwame Mantey, Xin Zhang

The jacket substructure is a critical component of the offshore wind turbine (OWT) that is the interface between the transition piece at the top and the grouted connection. This paper presents a comprehensive study on the optimization of a jacket substructure to achieve greater cost efficiency while maintain acceptable structural performance. A fast parametr

Hiroki Takizawa

The game of Othello is one of the world's most complex and popular games that has yet to be computationally solved. Othello has roughly ten octodecillion (10 to the 58th power) possible game records and ten octillion (10 to the 28th power) possible game positions. The challenge of solving Othello, determining the outcome of a game with no mistake made by eit

Sohail Farhangi

We show that for any locally compact second countable group $G$ and any continuous positive definite function $\phi:G\rightarrow\mathbb{C}$, there exists an ergodic measure preserving system $(X,\mathscr{B},\mu,\{T_g\}_{g \in G})$ and a function $f \in L^2(X,\mu)$ for which $\phi(g) = \langle T_gf,f\rangle$. We also show that if $G$ is a countably infinite a

Teodora Pandeva, Patrick Forré, Aaditya Ramdas, Shubhanshu Shekhar

We propose a general framework for constructing powerful, sequential hypothesis tests for a large class of nonparametric testing problems. The null hypothesis for these problems is defined in an abstract form using the action of two known operators on the data distribution. This abstraction allows for a unified treatment of several classical tasks, such as t