February 2023 arXiv papers — page 4

Xu Zhang, Marcos M. Vasconcelos

Multi-agent systems often communicate over low-power shared wireless networks in unlicensed spectrum, prone to denial-of-service attacks. We consider the following scenario: multiple pairs of agents communicating strategically over shared communication networks in the presence of a jammer who may launch a denial-of-service. We cast this problem as a game bet

Simon Gottschalk, Endri Kacupaj, Sara Abdollahi, Diego Alves

Accessing and understanding contemporary and historical events of global impact such as the US elections and the Olympic Games is a major prerequisite for cross-lingual event analytics that investigate event causes, perception and consequences across country borders. In this paper, we present the Open Event Knowledge Graph (OEKG), a multilingual, event-centr

Robert C. Bird, Michael R. Tarbutt, Jeremy M. Hutson

We consider the magnetically tunable Feshbach resonances that may exist in ultracold mixtures of molecules in $^2\Sigma$ states and alkali-metal atoms. We focus on Rb+CaF as a prototype system. There are likely to be Feshbach resonances analogous to those between pairs of alkali-metal atoms. We investigate the patterns of near-threshold states and the resona

Giannis Fikioris, Éva Tardos

Bandits with Knapsacks (BwK), the generalization of the Bandits problem under global budget constraints, has received a lot of attention in recent years. Previous work has focused on one of the two extremes: Stochastic BwK where the rewards and consumptions of the resources of each round are sampled from an i.i.d. distribution, and Adversarial BwK where thes

Samyak Jain, Sravanti Addepalli, Pawan Sahu, Priyam Dey

Generalization of neural networks is crucial for deploying them safely in the real world. Common training strategies to improve generalization involve the use of data augmentations, ensembling and model averaging. In this work, we first establish a surprisingly simple but strong benchmark for generalization which utilizes diverse augmentations within a train

Dolores Bernenko, Sang Hoon Lee, Ludvig Lizana

Researchers developed chromosome capture methods such as Hi-C to better understand DNA's 3D folding in nuclei. The Hi-C method captures contact frequencies between DNA segment pairs across the genome. When analyzing Hi-C data sets, it is common to group these pairs using standard bioinformatics methods (e.g., PCA). Other approaches handle Hi-C data as weight

Bo Peng, Jun Hu, Jingtao Zhou, Xuan Gao

Recently, many works have been proposed to utilize the neural radiance field for novel view synthesis of human performers. However, most of these methods require hours of training, making them difficult for practical use. To address this challenging problem, we propose IntrinsicNGP, which can train from scratch and achieve high-fidelity results in few minute

Beiyan Cao, Changyang He, Muzhi Zhou, Mingming Fan

Understanding livestream platforms' accessibility challenges for minority groups, such as people with disabilities, is critical to increasing the diversity and inclusion of those platforms. While prior work investigated the experiences of streamers with vision or motor loss, little is known about the experiences of deaf or hard of hearing (DHH) streamers who

Ping Xi

We show that a double character sum, appearing in the work of Conrey-Iwaniec and Petrow-Young on Weyl bound for certain $L$-functions, is essentially a hypergeometric sum introduced by Katz. This produces a simple proof of the upper bound for this sum.

Holy Lovenia, Samuel Cahyawijaya, Pascale Fung

The demand for multimodal dialogue systems has been rising in various domains, emphasizing the importance of interpreting multimodal inputs from conversational and situational contexts. We explore three methods to tackle this problem and evaluate them on the largest situated dialogue dataset, SIMMC 2.1. Our best method, scene-dialogue alignment, improves the

Yimin Dai, Xian Shuai, Rui Tan, Guoliang Xing

Tracking interpersonal distances is essential for real-time social distancing management and {\em ex-post} contact tracing to prevent spreads of contagious diseases. Bluetooth neighbor discovery has been employed for such purposes in combating COVID-19, but does not provide satisfactory spatiotemporal resolutions. This paper presents ImmTrack, a system that

Taha Ceritli, Ghadeer O. Ghosheh, Vinod Kumar Chauhan, Tingting Zhu

Electronic Health Records (EHRs) contain sensitive patient information, which presents privacy concerns when sharing such data. Synthetic data generation is a promising solution to mitigate these risks, often relying on deep generative models such as Generative Adversarial Networks (GANs). However, recent studies have shown that diffusion models offer severa

Syu-Ning Johnn, Victor-Alexandru Darvariu, Julia Handl, Joerg Kalcsics

ALNS is a popular metaheuristic with renowned efficiency in solving combinatorial optimisation problems. However, despite 16 years of intensive research into ALNS, whether the embedded adaptive layer can efficiently select operators to improve the incumbent remains an open question. In this work, we formulate the choice of operators as a Markov Decision Proc

Yi Yu, Yufei Wang, Wenhan Yang, Shijian Lu

Recent deep-learning-based compression methods have achieved superior performance compared with traditional approaches. However, deep learning models have proven to be vulnerable to backdoor attacks, where some specific trigger patterns added to the input can lead to malicious behavior of the models. In this paper, we present a novel backdoor attack with mul

Yohei Ema, Masashi Hazumi, Hideo Iizuka, Kyohei Mukaida

We point out that there is a stable configuration of metal plates where the Casimir force is vanishing in axion electrodynamics. We consider a concrete setup involving Weyl semimetals, which hosts an axion-like effect on the electromagnetism, towards the measurement of the axionic effect on the Casimir force. Our setup realizes zero Casimir force between met

Zsolt Baja, Tamás László

We consider numerical semigroups associated with normal weighted homogeneous surface singularities with rational homology sphere links. We say that a semigroup is representable if it can be realized in this way. In this article, we study the representability of flat semigroups and prove that a numerical semigroup is representable if and only if it can be wri

Xingyu Chen, Peixi Wu, Ge Li, Thomas H. Li

As a crucial infrastructure of intelligent mobile robots, LiDAR-Inertial odometry (LIO) provides the basic capability of state estimation by tracking LiDAR scans. The high-accuracy tracking generally involves the kNN search, which is used with minimizing the point-to-plane distance. The cost for this, however, is maintaining a large local map and performing

Chengzhi Wu, Junwei Zheng, Julius Pfrommer, Jürgen Beyerer

Point cloud sampling is a less explored research topic for this data representation. The most commonly used sampling methods are still classical random sampling and farthest point sampling. With the development of neural networks, various methods have been proposed to sample point clouds in a task-based learning manner. However, these methods are mostly gene

Grigory A. Starkov, Mikhail V. Fistul, Ilya M. Eremin

Motivated by the recent growing interest in the field of $\mathcal{P}\mathcal{T}$-symmetric Hamiltonian systems we theoretically study the emergency of singularities called Exceptional Points ($\textit{EP}$s) in the eigenspectrum of pseudo-Hermitian Hamiltonian as the strength of Hermiticity-breaking terms turns on. Using general symmetry arguments, we chara

Qisheng Yu, Jiawei Huang, Changming Ke, Zhuang Qian

Recent discovery of HfO2-based and nitride-based ferroelectrics that are compatible to the semiconductor manufacturing process have revitalized the field of ferroelectric-based nanoelectronics. Guided by a simple design principle of charge compensation and density functional theory calculations, we discover HfO2-like mixed-anion materials, TaON and NbON, can

Yite Wang, Jing Wu, Naira Hovakimyan, Ruoyu Sun

Over the past few years, there has been growing interest in developing larger and deeper neural networks, including deep generative models like generative adversarial networks (GANs). However, GANs typically come with high computational complexity, leading researchers to explore methods for reducing the training and inference costs. One such approach gaining

Denis Yagodkin, Elias Ankerhold, Abhijeet Kumar, Johanna Richter

Optically dark excitons determine a wide range of properties of photoexcited semiconductors yet are hard to access via conventional spectroscopies. Here, we develop a time-resolved ultrafast photocurrent technique (trPC) to probe the formation dynamics of optically dark excitons. The nonlinear nature of the trPC makes it particularly sensitive to the formati

Barbara Sylwester, Janusz Sylwester, Kenneth J. H. Phillips, Anna K. Kepa

We report on calcium abundance $A({\rm Ca})$ estimates during the decay phases of 194 solar X-ray flares using archived data from the Bent Crystal Spectrometer (BCS) on Solar Maximum Mission (operational 1980~--~1989). The abundances are derived from the ratio of the total calcium X-ray line emission in BCS channel~1 to that in neighboring continuum, with te

Jose Martinez-Castro, Cyrus F. Hirjibehedin, David Serrate

We reversibly switch the polar environment of an individual magnetic atom with an electric field to control the energy barrier for reversal of magnetization. By applying an electric field in the gap between the tip and sample of a scanning tunneling microscope, we induce bistable changes in the polarization of the region surrounding a chlorine vacancy in a m

Konstantinos Boutivas, Georgios Pastras, Nikolaos Tetradis

We study the entanglement entropy resulting from tracing out local degrees of freedom of a quantum scalar field in an expanding universe. It is known that when field modes become superhorizon during inflation they evolve to increasingly squeezed states. We argue that this causes the entanglement entropy to grow continuously as successive modes cross the hori

Josua Sassen, Klaus Hildebrandt, Martin Rumpf, Benedikt Wirth

Parametrizations of data manifolds in shape spaces can be computed using the rich toolbox of Riemannian geometry. This, however, often comes with high computational costs, which raises the question if one can learn an efficient neural network approximation. We show that this is indeed possible for shape spaces with a special product structure, namely those s

Ziqin Feng, Naga Chandra Padmini Nukala

We examine the homotopy types of Vietoris-Rips complexes on certain finite metric spaces at scale $2$. We consider the collections of subsets of $[m]=\{1, 2, \ldots, m\}$ equipped with symmetric difference metric $d$, specifically, $\mathcal{F}^m_n$, $\mathcal{F}_n^m\cup \mathcal{F}^m_{n+1}$, $\mathcal{F}_n^m\cup \mathcal{F}^m_{n+2}$, and $\mathcal{F}_{\prec

Timo Speith, Julian Speith, Steffen Becker, Yixin Zou

In today's age of digital technology, ethical concerns regarding computing systems are increasing. While the focus of such concerns currently is on requirements for software, this article spotlights the hardware domain, specifically microchips. For example, the opaqueness of modern microchips raises security issues, as malicious actors can manipulate them, j

Nandita Khetan, Jeff Cooke, Marica Branchesi

Superluminous supernovae (SLSNe) have been detected to $z\sim4$ and can be detected to $z\gtrsim15$ using current and upcoming facilities. SLSNe are extremely UV luminous, and hence objects at $z\gtrsim7$ are detected exclusively via their rest-frame UV using optical and infrared facilities. SLSNe have great utility in multiple areas of stellar and galactic

Emanuel Carneiro, Friedrich Littmann

In this note we find optimal one-sided majorants of exponential type for the signum function subject to certain monotonicity conditions. As an application, we use these special functions to obtain a simple Fourier analysis proof of the (non-sharp) weighted Hilbert-Montgomery-Vaughan inequality.

T. D. Kitching, N. Tessore, P. L. Taylor

In this paper we show how response function corrections to shear measurements (e.g. as required by Metacalibration) propagate into cosmic shear power spectra. We investigate a 2-sphere pixel (also known as HEALpixel') correction and a forward-modelling approach using simple Gaussian simulations. In the 2-sphere pixel-correction approach we find a free parame

Alberto Fossà, Roberto Armellin, Emmanuel Delande, Matteo Losacco

This paper presents an algorithm for the preprocessing of observation data aimed at improving the robustness of orbit determination tools. Two objectives are fulfilled: obtain a refined solution to the initial orbit determination problem and detect possible outliers in the processed measurements. The uncertainty on the initial estimate is propagated forward

Han Wu, Ping Xi

We establish a Weyl-type subconvexity of $L(\tfrac{1}{2},f)$ for spherical Hilbert newforms $f$ with level ideal $\mathfrak{N}^2$, in which $\mathfrak{N}$ is required to be cube-free, and at any prime ideal $\mathfrak{p}$ with $\mathfrak{p}^2 \mid \mathfrak{N}$ the local representation generated by $f$ is not supercuspidal. The proof exploits a distributiona

Stein Tore Johansen, Bjørn Tore Løvfall, Tamara Rodriguez Duran, Josip Zoric

A methodology for building pragmatic physics based models (Zoric et al., 2015b) is here adapted to a use-case in the steel industry. The challenge is to predict the erosion of steel ladle linings, such that the model can support operators to decide if the lade lining can be used one more time or not. If the ladle has too thin lining 140 tons of hot liquid st

Lin Han, Shiyu Wang, Liangliang Shang, Bingfang Yang

Based on a simplified model including a singlet vector-like top quark $T$ with charge $|Q|=2/3$, we analyze the prospects of observing $T$ via the single $T$ production in the $tZ$ channel with $Z$ decaying to neutrinos at the hadron-hadron colliders. This simplified model only includes two free parameters, the coupling constant $g^*$ and the $T$ quark mass

Minchang Kim, Yongjin Yang, Jung Hyun Ryu, Taesup Kim

Sequential recommenders have made great strides in capturing a user's preferences. Nevertheless, the cold-start recommendation remains a fundamental challenge as they typically involve limited user-item interactions for personalization. Recently, gradient-based meta-learning approaches have emerged in the sequential recommendation field due to their fast ada

Shubhankar Singh, Anirudh Pupneja, Shivaansh Mital, Cheril Shah

The use of Natural Language Processing (NLP) for Automated Essay Scoring (AES) has been well explored in the English language, with benchmark models exhibiting performance comparable to human scorers. However, AES in Hindi and other low-resource languages remains unexplored. In this study, we reproduce and compare state-of-the-art methods for AES in the Hind

N. K. Dulaev, M. Y. Kaygorodov, A. V. Malyshev, I. I. Tupitsyn

For heliumlike uranium, the energies of the singly-excited $1sns$, $1snp$, and $1snd$ states with $n\leq 4$ and the probabilities of the one-photon $1s3d\to 1s2p$, $1s3p\to 1s2s$, $1s3p\to 1s2p$ and $1s4d\to 1s2p$ transitions are evaluated. The calculations are performed within the Breit approximation using the configuration-interaction method in the basis o

Kevin Mitchell, Khaled Kassem, Chaitanya Kaul, Valentin Kapitany

For widespread adoption, public security and surveillance systems must be accurate, portable, compact, and real-time, without impeding the privacy of the individuals being observed. Current systems broadly fall into two categories -- image-based which are accurate, but lack privacy, and RF signal-based, which preserve privacy but lack portability, compactnes

Yooyoung Lee, Craig Greenberg, Eliot Godard, Asad A. Butt

In 2022, the U.S. National Institute of Standards and Technology (NIST) conducted the latest Language Recognition Evaluation (LRE) in an ongoing series administered by NIST since 1996 to foster research in language recognition and to measure state-of-the-art technology. Similar to previous LREs, LRE22 focused on conversational telephone speech (CTS) and broa

Riade Benbaki, Wenyu Chen, Xiang Meng, Hussein Hazimeh

The sheer size of modern neural networks makes model serving a serious computational challenge. A popular class of compression techniques overcomes this challenge by pruning or sparsifying the weights of pretrained networks. While useful, these techniques often face serious tradeoffs between computational requirements and compression quality. In this work, w

Luís Cruz-Filipe, Fabrizio Montesi

Choreographic programming is a paradigm where developers write the global specification (called choreography) of a communicating system, and then a correct-by-construction distributed implementation is compiled automatically. Unfortunately, it is possible to write choreographies that cannot be compiled, because of issues related to an agreement property know

Stein Tore Johansen, Bjørn Tore Løvfall, Tamara Rodriguez Duran

In this paper we develop a physics-based model for the erosion of lining in steel ladles. The model predicts the temperature evolution in the liquid slag, steel, refractory bricks and outer steel casing. The flows of slag and steel is due to forced convection by inert gas injection, vacuum treatment (extreme bubble expansion), natural convection and waves ca

M. Salman Shaukat, J. -C. Põder, Sebastian Bader, Thomas Kirste

Artificial intelligence (AI) based assistive systems, so called intelligent assistive technology (IAT) are becoming increasingly ubiquitous by each day. IAT helps people in improving their quality of life by providing intelligent assistance based on the provided data. A few examples of such IATs include self-driving cars, robot assistants and smart-health ma

F. H. Kamin, Z. Abuali, H. Ness, S. Salimi

We present an analysis of the availability and maximum extractable work of quantum batteries in the presence of charge and/or heat steady-state currents. Quantum batteries are modelled as non-interacting open quantum systems (mesoscopic systems) strongly coupled to two thermal and particle reservoirs within the framework of non-equilibrium Green's function t

Tyler Cody, Laura Freeman

Machine learning models are increasingly used in practice. However, many machine learning methods are sensitive to test or operational data that is dissimilar to training data. Out-of-distribution (OOD) data is known to increase the probability of error and research into metrics that identify what dissimilarities in data affect model performance is on-going.

Yuriy Yerin, Stefan-Ludwig Drechsler, Mario Cuoco, Caterina Petrillo

It is well-established that multicomponent superconductors can host different nonstandard phenomena such as broken-time reversal symmetry (BTRS) states, exotic Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) phases, the fractional Josephson effect as well as plenty of topological defects like phase solitons, domain walls and unusual vortex structures. We show that i

Christian Zingg, Alexander von Gernler, Carsten Arzig, Frank Schweitzer

The functional interaction structure of a team captures the preferences with which members of different roles interact. This paper presents a data-driven approach to detect the functional interaction structure for software development teams from traces team members leave on development platforms during their daily work. Our approach considers differences in

Wendi Xu

In this paper, we consider the Schr\"odinger type equation $-\Delta u+V(x)u=f(x,u)$ on the lattice graph $\mathbb{Z}^{N}$ with indefinite variational functional, where $-\Delta$ is the discrete Laplacian. Specifically, we assume that $V(x)$ and $f(x,u)$ are periodic in $x$, $f$ satisfies some growth condition and 0 lies in a spectral gap of $(-\Delta + V)$.

Tao Xing, Nicolas Vernier, Xueying Y. Zhang, Y. G. Zhang

We present here a statistical study of the transit time required for a magnetic domain wall to go through a small laser spot focused on 2D magnetic thin film. The domain wall velocity deduced this way is in good agreement with the other ways used to measure this parameter. But, the main fact is that the transit time is not a reproducible parameter, we have o

Paolo Lisca, Andrea Parma

We complete the classification of the smooth, closed, oriented 4-manifolds having Euler characteristic less than four and a horizontal handlebody decomposition of genus one. We use the classification result to find a large family of rational homology ball smoothings of cyclic quotient singularities which can be smoothly embedded into the complex projective p

Kensaku Takai, Youhei Yamaji, Fakher F. Assaad, Masatoshi Imada

Metallic states near the Mott insulator show a variety of quantum phases including various magnetic, charge ordered states and high-temperature superconductivity in various transition metal oxides and organic solids. The emergence of a variety of phases and their competitions are likely intimately associated with quantum transitions between the electron-corr

Bengisu Guresti, Abdullah Vanlioglu, Nazim Kemal Ure

Achieving and maintaining cooperation between agents to accomplish a common objective is one of the central goals of Multi-Agent Reinforcement Learning (MARL). Nevertheless in many real-world scenarios, separately trained and specialized agents are deployed into a shared environment, or the environment requires multiple objectives to be achieved by different

Zhijie Shen, Wu Guo, Bin Gu

In this paper, we propose a language-universal adapter learning framework based on a pre-trained model for end-to-end multilingual automatic speech recognition (ASR). For acoustic modeling, the wav2vec 2.0 pre-trained model is fine-tuned by inserting language-specific and language-universal adapters. An online knowledge distillation is then used to enable th

Yijia Zhou, Kyle A. Gallivan, Adrian Barbu

Clustering is a widely used technique with a long and rich history in a variety of areas. However, most existing algorithms do not scale well to large datasets, or are missing theoretical guarantees of convergence. This paper introduces a provably robust clustering algorithm based on loss minimization that performs well on Gaussian mixture models with outlie

Alexander C. Murph, Jan Hannig, Jonathan P. Williams

Fiducial inference was introduced in the first half of the 20th century by Fisher (1935) as a means to get a posterior-like distribution for a parameter without having to arbitrarily define a prior. While the method originally fell out of favor due to non-exactness issues in multivariate cases, the method has garnered renewed interest in the last decade. Thi

Dianwen Ng, Ruixi Zhang, Jia Qi Yip, Zhao Yang

Existing self-supervised pre-trained speech models have offered an effective way to leverage massive unannotated corpora to build good automatic speech recognition (ASR). However, many current models are trained on a clean corpus from a single source, which tends to do poorly when noise is present during testing. Nonetheless, it is crucial to overcome the ad

Shanshan Wang, Michael Schreckenberg, Thomas Guhr

Traffic systems can operate in different modes. In a previous work, we identified these modes as different quasi-stationary states in the correlation structure. Here, we analyze the transitions between such quasi-stationary states, i.e., how the system changes its operational mode. In the longer run this might be helpful to forecast the time evolution of cor

Junwei Zheng, Jiaming Zhang, Kailun Yang, Kunyu Peng

People with Visual Impairments (PVI) typically recognize objects through haptic perception. Knowing objects and materials before touching is desired by the target users but under-explored in the field of human-centered robotics. To fill this gap, in this work, a wearable vision-based robotic system, MateRobot, is established for PVI to recognize materials an

Hao Peng, Cheng Qian, Dandan Zhao, Ming Zhong

Hypergraph networks are closer to real life because they can reflect higher-order interactions, so researchers have begun using them to build models for real-world networks. The mean-field approach is the current tool for studying the percolation problem on hypergraph networks. However, we found that when there is a loop in the hypergraph network, the calcul

Christophe Charlier, Jonatan Lenells

In a recent paper, we developed an inverse scattering approach to the Boussinesq equation in the case when no solitons are present. In this paper, we extend this approach to include solutions with solitons.

Georg Kruse, Dominik Happel, Stefan Ditze, Stefan Ehrlich

The optimization of electrical circuits is a difficult and time-consuming process performed by experts, but also increasingly by sophisticated algorithms. In this paper, a reinforcement learning (RL) approach is adapted to optimize a LLC converter at multiple operation points corresponding to different output powers at high converter efficiency at different

José D. Guimarães, James Lim, Mikhail I. Vasilevskiy, Susana F. Huelga

Quantum systems are inherently open and susceptible to environmental noise, which can have both detrimental and beneficial effects on their dynamics. This phenomenon has been observed in bio-molecular systems, where noise enables novel functionalities, making the simulation of their dynamics a crucial target for digital and analog quantum simulation. Neverth

Helen Shao, Natalí S. M de Santi, Francisco Villaescusa-Navarro, Romain Teyssier

We discover analytic equations that can infer the value of $\Omega_{\rm m}$ from the positions and velocity moduli of halo and galaxy catalogues. The equations are derived by combining a tailored graph neural network (GNN) architecture with symbolic regression. We first train the GNN on dark matter halos from Gadget N-body simulations to perform field-level

Maria Laura Piscopo

We present the theoretical status of the lifetimes of weakly decaying heavy hadrons containing a bottom or a charm quark, and discuss the current predictions, based on the framework of the Heavy Quark Expansion (HQE), for both mesons and baryons. Potential improvements to reduce the theoretical uncertainties are also highlighted.

Hao Ren, Shoudong Han, Huilin Ding, Ziwen Zhang

Discriminative representation is essential to keep a unique identifier for each target in Multiple object tracking (MOT). Some recent MOT methods extract features of the bounding box region or the center point as identity embeddings. However, when targets are occluded, these coarse-grained global representations become unreliable. To this end, we propose exp

D. Harutyunyan, T. Mengesha, H. Mikayelyan, J. M. Scott

This work establishes fractional analogues of Korn's first and second inequalities for vector fields in fractional Sobolev spaces defined over a bounded domain. The validity of the inequalities require no additional boundary condition, extending existing fractional Korn's inequalities that are only applicable for Sobolev vector fields satisfying zero Dirichl

Michal Pluhacek, Simon Garnier, Andreagiovanni Reina

Collective intelligence and autonomy of robot swarms can be improved by enabling the individual robots to become aware they are the constituent units of a larger whole and what is their role. In this study, we present an algorithm to enable positional self-awareness in a swarm of minimalistic error-prone robots which can only locally broadcast messages and e

Willem A. Baan

This paper presents an overview of methods for mitigating radio frequency interference (RFI) in radio science data. The primary purpose of mitigation is to assist observatories to take useful data outside frequency bands allocated to the Science Services (RAS and EESS): mitigation should not be needed within Passive bands. Mitigation methods may be introduce

Michaela Borzechowski, Simon Weber

Klaus showed that the Oriented Matroid Complementarity Problem (OMCP) can be solved by a reduction to the problem of sink-finding in a unique sink orientation (USO) if the input is promised to be given by a non-degenerate extension of a P-matroid. In this paper, we investigate the effect of degeneracy on this reduction. On the one hand, this understanding of

Cinzia Di Giorgio, Elena Blundo, Julien Basset, Giorgio Pettinari

We implemented radio frequency-assisted electrostatic force microscopy (RF-EFM) to investigate the electric field response of biaxially strained molybdenum disulfide (MoS2) monolayers (MLs) in the form of mesoscopic bubbles, produced via hydrogen (H)-ion irradiation of the bulk crystal. MoS2 ML, a semiconducting transition metal dichalcogenide, has recently

Giorgio Nicoletti

This Thesis explores how tools from Statistical Physics and Information Theory can help us describe and understand complex systems. In the first part, we study the interplay between internal interactions, environmental changes, and effective representations of complex stochastic systems. We model the environment as an unobserved stochastic process and invest

Onur Danaci, Wenlei Zhang, Robert Coleman, William Djakam

The ability to prepare systems in specific target states through quantum engineering is essential for realizing the new technologies promised by a second quantum revolution. Here, we recast the fundamental problem of state preparation in high-dimensional Hilbert spaces as ManQala, a quantum game inspired by the West African sowing game mancala. Motivated by

Kai Zhai, Qiang Nie, Bo Ouyang, Xiang Li

2D-to-3D human pose lifting is fundamental for 3D human pose estimation (HPE), for which graph convolutional networks (GCNs) have proven inherently suitable for modeling the human skeletal topology. However, the current GCN-based 3D HPE methods update the node features by aggregating their neighbors' information without considering the interaction of joints

Jürgen Groß, Annette Möller

In this note, we reconsider Cohen's effect size measure $f^2$ under linear mixed models and demonstrate its application by employing an artificially generated data set. It is shown how $f^2$ can be computed with the statistical software environment R using lme4 without the need for specification and computation of a coefficient of determination.

Alice Marcotte, François Gallaire, Alessandro Bongarzone

We study the free surface response in a cylindrical container undergoing an elliptic periodic orbit. For small forcing amplitudes and deep liquid layers, we quantify the effect of orbit's aspect ratio onto the surface dynamics in the vicinity of the fluid system's lowest natural frequency. We provide experimental evidences of the existence of a frequency ran

Minghao Zhou, Hong Wang, Qian Zhao, Yuexiang Li

Click-based interactive segmentation (IS) aims to extract the target objects under user interaction. For this task, most of the current deep learning (DL)-based methods mainly follow the general pipelines of semantic segmentation. Albeit achieving promising performance, they do not fully and explicitly utilize and propagate the click information, inevitably

Alejandro A. Hnilo

A new definition of "Realism" is proposed: it is that a gedanken "spectrograph" of hidden variables behaves as an actual (say, wavelength) spectrograph. The question is: does this definition allow, by itself, the derivation of Bell's inequalities? If it were, then such a spectrograph would be impossible, for Bell's inequalities are observed to be violated. I

Kamel-Eddine Harabi, Clement Turck, Marie Drouhin, Adrien Renaudineau

We present an integrated circuit fabricated in a process co-integrating CMOS and hafnium-oxide memristor technology, which provides a prototyping platform for projects involving memristors. Our circuit includes the periphery circuitry for using memristors within digital circuits, as well as an analog mode with direct access to memristors. The platform allows

Giorgos Armeniakos, Georgios Zervakis, Dimitrios Soudris, Mehdi B. Tahoori

Printed Electronics (PE) exhibits on-demand, extremely low-cost hardware due to its additive manufacturing process, enabling machine learning (ML) applications for domains that feature ultra-low cost, conformity, and non-toxicity requirements that silicon-based systems cannot deliver. Nevertheless, large feature sizes in PE prohibit the realization of comple

Willem A. Baan, Axel Jessner, Jaap Steenge

This paper presents an observing methodology for calibrated measurements of radio interference levels and compare these with threshold interference limits that have been established for interference entering the bands allocated to the Radio Astronomy Service. The measurement time and bandwidth intervals for these observations may be commensurate with the tim

Markus Eisenbach, Jannik Lübberstedt, Dustin Aganian, Horst-Michael Gross

Person re-identification plays a key role in applications where a mobile robot needs to track its users over a long period of time, even if they are partially unobserved for some time, in order to follow them or be available on demand. In this context, deep-learning based real-time feature extraction on a mobile robot is often performed on special-purpose de

Giuseppe Toscani, Mattia Zanella

Owing to the analogies between the problem of wealth redistribution with taxation in a multi-agent society, we introduce and discuss a kinetic model describing the statistical distributions in time of the sizes of groups of biological systems with prey-predator dynamic. While the evolution of the mean values is shown to be driven by a classical Lotka-Volterr

Irene Martín-Morató, Manu Harju, Paul Ahokas, Annamaria Mesaros

In this paper, we study the use of soft labels to train a system for sound event detection (SED). Soft labels can result from annotations which account for human uncertainty about categories, or emerge as a natural representation of multiple opinions in annotation. Converting annotations to hard labels results in unambiguous categories for training, at the c

Sk Aziz, Arindam Ghosh, Om Prakash

In this paper, we mainly prove some results on the additivity of maps over rings under certain conditions. First, we discuss a special case of MARTINDALE III's theorem of \cite{1969M} as a bijective map $\varphi$ over a ring $R$ with a non-trivial idempotent satisfying $\varphi(ab)=\varphi(a)\varphi(b)$ for all $a, b\in R$, is additive. Then we prove that a

Yang Zhai, Zhi-Wei Liu, Dong Yue, Songlin Hu

This paper studies the distributed multi-agent resilient optimization problem under the f-total Byzantine attacks. Compared with the previous work on Byzantineresilient multi-agent exact optimization problems, we do not require the communication topology to be fully connected. Under the redundancy of cost functions, we propose the distributed comparative gra

Sotiris Papatheodorou, Nils Funk, Dimos Tzoumanikas, Christopher Choi

Exploration of unknown space with an autonomous mobile robot is a well-studied problem. In this work we broaden the scope of exploration, moving beyond the pure geometric goal of uncovering as much free space as possible. We believe that for many practical applications, exploration should be contextualised with semantic and object-level understanding of the

Haitao Li, Jia Chen, Weihang Su, Qingyao Ai

This paper describes the approach of the THUIR team at the WSDM Cup 2023 Pre-training for Web Search task. This task requires the participant to rank the relevant documents for each query. We propose a new data pre-processing method and conduct pre-training and fine-tuning with the processed data. Moreover, we extract statistical, axiomatic, and semantic fea

Janez Bonca, Marcin Mierzejewski

We discuss the interplay between many-body localization and spin-symmetry. To this end, we study the time evolution of several observables in the anisotropic t-J model. Like the Hubbard chain, the studied model contains charge and spin degrees of freedom, yet it has smaller Hilbert space and thus allows for numerical studies of larger systems. We compare the

Sai Prathyush Katragadda, Tyler Cody, Peter Beling, Laura Freeman

Active learning is a practical field of machine learning that automates the process of selecting which data to label. Current methods are effective in reducing the burden of data labeling but are heavily model-reliant. This has led to the inability of sampled data to be transferred to new models as well as issues with sampling bias. Both issues are of crucia

Songpei Xu, Chaitanya Kaul, Xuri Ge, Roderick Murray-Smith

This paper presents a new continuous interaction strategy with visual feedback of hand pose and mid-air gesture recognition and control for a smart music speaker, which utilizes only 2 video frames to recognize gestures. Frame-based hand pose features from MediaPipe Hands, containing 21 landmarks, are embedded into a 2 dimensional pose space by an autoencode

Bai Xue

In this paper we propose sufficient conditions to synthesizing reach-avoid controllers for deterministic systems modelled by ordinary differential equations and stochastic systems modeled by stochastic differential equations based on the notion of control guidance-barrier functions. We begin with considering deterministic systems. Given an open safe set, a t

Shujie Hu, Xurong Xie, Zengrui Jin, Mengzhe Geng

Automatic recognition of disordered and elderly speech remains a highly challenging task to date due to the difficulty in collecting such data in large quantities. This paper explores a series of approaches to integrate domain adapted SSL pre-trained models into TDNN and Conformer ASR systems for dysarthric and elderly speech recognition: a) input feature fu

Kosuke Ikeya, Koki Ho

As many satellite constellations are proposed, deployed, and operated, their maintenance becomes increasingly important to provide satisfactory services; therefore, on-orbit refueling to spacecraft has become one of the most promising technologies for realizing more sustainable space development. This paper develops an analytical model to examine two types o

Hong Sun, Yanping Chen, Xuan Zhao

In this paper, a temporal nonuniform $L1$ type difference scheme is built up for the time fractional diffusion-wave equation with the help of the order reduction technique. The unconditional convergence of the nonuniform difference scheme is proved rigorously in $L^2$ norm. Our main tool is the discrete complementary convolution kernels with respect to the c

Tomer Solberg

We consider a simple theory of N free fermions in d dimensions with O\left(N\right) or U\left(N\right) symmetry. The singlet sector of this theory is expected from holography to be dual to the notoriously complicated Vasiliev gravity. By defining bilocal fields we find an explicit holographic mapping between the two theories, similar to what was done previou

Remi Tailleux

Explicit expressions of the 3D velocity field in terms of the conserved quantities of ideal fluid thermocline theory, namely Bernoulli function, density, and potential vorticity, are generalised here to a compressible ocean with a realistic nonlinear equation of state. The most general such expression is the `inactive wind' solution, an exact nonlinear solut

Leonardo Colzani, Bianca M. Gariboldi, Alessandro Monguzzi

Given an irrational vector $\alpha$ in $\mathbb{R}^{d}$, a continuous function $f(x)$ on the torus $\mathbb{T}^{d}$ and suitable weights $\Phi(N,n)$ such that $\sum_{n=-\infty}^{+\infty}\Phi(N,n)=1$, we estimate the speed of convergence to the integral $\int_{\mathbb{T}^{d}}f(y)dy$ of the weighted sum $\sum_{n=-\infty}^{+\infty}\Phi(N,n) f(x+n\alpha)$ as $N\

E. A. Maletskii, I. A. Iakovlev, V. V. Mazurenko

A rich variety of non-equilibrium dynamical phenomena and processes unambiguously calls for the development of general numerical techniques to probe and estimate a complex interplay between spatial and temporal degrees of freedom in many-body systems of completely different nature. In this work we provide a solution to this problem by adopting a structural c

Axi Niu, Pei Wang, Yu Zhu, Jinqiu Sun

Recently, many works have designed wider and deeper networks to achieve higher image super-resolution performance. Despite their outstanding performance, they still suffer from high computational resources, preventing them from directly applying to embedded devices. To reduce the computation resources and maintain performance, we propose a novel Ghost Residu