July 2023 arXiv papers — page 151

Yu-Bin Wang, Abdusattar Kurban, Xia Zhou, Yun-Wei Yu

FRB 180916.J0158+65 is a well-known repeating fast radio burst with a period ($16.35~\rm days$) and an active window ($5.0~\rm days$). We give out the statistical results of the dispersion measures and waiting times of bursts of FRB 180916.J0158+65. We find the dispersion measures at the different frequencies show a bimodal distribution. The peaking dispersi

Andris P. Stikuts, Abdelqader Zaben, Ivars Driķis, Māra Šmite

Effective mixing of fluids at the microfluidic scale is important for future applications in biology, medicine, and chemistry. A promising type of micromixers are magnetic filaments, which can be activated by an external magnetic field. However, there is a lack of research that combines experiments and numerical modelling of hydrodynamics around such filamen

Laixiang Qin, Chunlai Li, Yiqun Wei, Zhangwei Xu

We demonstrate an exotic doubled-channeled NT GAAFET (DC NT GAAFET) structure with Ion boost in comparison with NT GAAFET and NW GAAFET with the same footprint. Ion gains of 64.8% and 1.7 times have been obtained in DC NT GAAFET in compared with NT GAAFET and NW GAAFET. Ioff of DC NT GAAFET degrades by 61.8% than that of NT GAAFET, SS is almost comparable in

Hamza Kebiri, Ali Gholipour, Meritxell Bach Cuadra, Davood Karimi

The brain white matter consists of a set of tracts that connect distinct regions of the brain. Segmentation of these tracts is often needed for clinical and research studies. Diffusion-weighted MRI offers unique contrast to delineate these tracts. However, existing segmentation methods rely on intermediate computations such as tractography or estimation of f

Shiyu Liu, Shaogao Lv, Dun Zeng, Zenglin Xu

Federated learning is a decentralized and privacy-preserving technique that enables multiple clients to collaborate with a server to learn a global model without exposing their private data. However, the presence of statistical heterogeneity among clients poses a challenge, as the global model may struggle to perform well on each client's specific task.

Maria del Pilar Romero de la Rosa

We explore some convergence notions for set-convergence coming from modern summability methods. Specifically we will see the connections between Wijsman $f$-statistical convergence and Wijsman $f$-strong Cesàro convergence, when $f$ is a modulus function that induces a density in $\mathbb{N}$.

Christian Gerhards, Xinpeng Huang

Subspaces obtained by the orthogonal projection of locally supported square-integrable vector fields onto the Hardy spaces $H_+(\mathbb{S})$ and $H_-(\mathbb{S})$, respectively, play a role in various inverse potential field problems since they characterize the uniquely recoverable components of the underlying sources. Here, we consider approximation in thes

Jonas M. Schneider, Christoph Burkhardt, Thorsten Kleine

Nucleosynthetic isotope anomalies in meteorites allow distinguishing between the non-carbonaceous (NC) and carbonaceous (CC) meteorite reservoirs and show that correlated isotope anomalies exist in both reservoirs. It is debated, however, whether these anomalies reflect thermal processing of presolar dust in the disk or are primordial heterogeneities inherit

F. Conte, S. Massucco, F. Silvestro, D. Cirio

This paper describes an intelligent management algorithm for an aggregate of domestic electric water heaters called to provide a demand response service. This algorithm is developed using Model Predictive Control. The model of the entire aggregate is dynamically identified using a recursive polynomial model estimation technique. This allows the control to be

Ritika Singhal, N. Shravan Kumar

In this paper, we prove several versions of the classical Paley inequality for the Weyl transform. As an application, we discuss $L^p$-$L^q$ boundedness of the Weyl multipliers and prove a version of the Hörmander's multiplier theorem. We also prove Hardy-Littlewood inequality. Finally, we study vector-valued versions of these inequalities. In particular

P. Tozman, S. Isogami, I. Suzuki, A. Bolyachkin

Multi-level magnetic recording is a new concept for increasing the data storage capacity of hard disk drives. However, its implementation has been limited by a lack of suitable media capable of storing information at multiple levels. Herein, we overcome this problem by developing dual FePt-C nanogranular films separated by a Ru-C breaking layer with a cubic

Souayah Abdelkader, Mokretar Kraroubi Abderrahmene, Slimane Larabi

People with visual impairments face numerous challenges when interacting with their environment. Our objective is to develop a device that facilitates communication between individuals with visual impairments and their surroundings. The device will convert visual information into auditory feedback, enabling users to understand their environment in a way that

Stefano Biagi, Giulia Meglioli, Fabio Punzo

We study mixed local and nonlocal elliptic equation with a variable coefficient $ρ$. Under suitable assumptions on the behaviour at infinity of $ρ$, we obtain uniqueness of solutions belonging to certain weighted Lebsgue spaces, with a weight depending on the coefficient $ρ$. The hypothesis on $ρ$ is optimal; indeed, when it fails we get nonuniqueness of sol

Anita Dürr, Nicolas El Maalouly, Lasse Wulf

In 1982 Papadimitriou and Yannakakis introduced the Exact Matching problem, in which given a red and blue edge-colored graph $G$ and an integer $k$ one has to decide whether there exists a perfect matching in $G$ with exactly $k$ red edges. Even though a randomized polynomial-time algorithm for this problem was quickly found a few years later, it is still un

Mingfei Lu, Badong Chen

The generative autoencoders, such as the variational autoencoders or the adversarial autoencoders, have achieved great success in lots of real-world applications, including image generation, and signal communication. However, little concern has been devoted to their robustness during practical deployment. Due to the probabilistic latent structure, variationa

Mustafa Sencer Aydin, Igor Kukavica, Wojciech S. Ożański, Amjad Tuffaha

We consider the three-dimensional Euler equations in a domain with a free boundary with no surface tension. We construct unique local-in-time solutions in the Lagrangian setting for $u_0 \in H^{2.5+δ}$ such that the Rayleigh-Taylor condition holds and $\mathrm{curl}\,u_0 \in H^{2+δ}$ in an arbitrarily small neighborhood of the free boundary. We show that the

Shanqi Liu, Weiwei Liu, Wenzhou Chen, Guanzhong Tian

The field of cooperative multi-agent reinforcement learning (MARL) has seen widespread use in addressing complex coordination tasks. While value decomposition methods in MARL have been popular, they have limitations in solving tasks with non-monotonic returns, restricting their general application. Our work highlights the significance of joint intentions in

Asif Manzoor Hasan, Johan Larsson, Sergio Pirozzoli, Rene Pecnik

Accurately predicting drag and heat transfer for compressible high-speed flows is of utmost importance for a range of engineering applications. This requires the precise knowledge of the entire velocity and temperature profiles. A common approach is to use compressible velocity scaling laws (transformation), that inverse transform the velocity profile of an

Fabio Villa

EuPRAXIA@SPARC_LAB is a new multi-disciplinary user-facility that is currently under construction at the Laboratori Nazionali di Frascati of the INFN in the framework of the EuPRAXIA collaboration. The electron beam will be accelerated by an X-band normal conducting linac followed by a Plasma WakeField Acceleration (PWFA) stage. It will be characterized by a

Sascha Mücke, Thore Gerlach, Nico Piatkowski

Quadratic unconstrained binary optimization (QUBO) problems are well-studied, not least because they can be approached using contemporary quantum annealing or classical hardware acceleration. However, due to limited precision and hardware noise, the effective set of feasible parameter values is severely restricted. As a result, otherwise solvable problems be

Renato Ferreira Pinto

We study the connection between directed isoperimetric inequalities and monotonicity testing. In recent years, this connection has unlocked breakthroughs for testing monotonicity of functions defined on discrete domains. Inspired the rich history of isoperimetric inequalities in continuous settings, we propose that studying the relationship between directed

Irina Afanasieva, Valery Murzin, Valery Ardilanov, Nikolai Ivaschenko

Herein, we describe the design, implementation and operation principles of an astronomical camera system, based on a large-format CCD261-84 detector with an extremely thick 200 mkm substrate. The DINACON-V controller was used with the CCD to achieve high performance and low noise. The CCD system photometric characteristics are presented. A spatial autocorrel

Si Chen, Li-Chao Peng, Yong-Peng Guo, Xue-Mei Gu

In the quest to build general-purpose photonic quantum computers, fusion-based quantum computation has risen to prominence as a promising strategy. This model allows a ballistic construction of large cluster states which are universal for quantum computation, in a scalable and loss-tolerant way without feed-forward, by fusing many small n-photon entangled re

Guangrui Yang, Lihua Yang, Qing Zhang, Zhihua Yang

Recommendation algorithm plays an important role in recommendation system (RS), which predicts users' interests and preferences for some given items based on their known information. Recently, a recommendation algorithm based on the graph Laplacian regularization was proposed, which treats the prediction problem of the recommendation system as a reconstr

Subrata Nandi, Srinivasan Krishnaswamy, Pinaki Mitra

In LFSR-based stream ciphers, the knowledge of the feedback equation of the LFSR plays a critical role in most attacks. In word-based stream ciphers such as those in the SNOW series, even if the feedback configuration is hidden, knowing the characteristic polynomial of the state transition matrix of the LFSR enables the attacker to create a feedback equation

Cornelis J. G. Mommers, Marc Vanderhaeghen

We propose a novel direct search experiment for X17 using the reaction $γD \to e^+ e^- pn$. X17 is a hypothetical particle conjectured by the ATOMKI collaboration to explain anomalous signals around 17 MeV in excited ${}^8$Be, ${}^4$He and ${}^{12}$C nuclear decays via internal pair creation. It has been subject to a global experimental and theoretical resea

A. V. Bobakov, A. V. Karpova, S. V. Zharikov, A. Yu. Kirichenko

We present the results of optical spectroscopy of stellar companions to three binary millisecond pulsars, PSRs J0621$+$2514, J2317$+$1439 and J2302$+$4442, obtained with the Gran Telescopio Canarias. The spectrum of the J0621$+$2514 companion shows a blue continuum and prominent Balmer absorption lines. The latter are also resolved in the spectrum of the J23

Federico Chiariotti

Mobile Edge Computing (MEC) is expected to play a significant role in the development of 6G networks, as new applications such as cooperative driving and eXtended Reality (XR) require both communication and computational resources from the network edge. However, the limited capabilities of edge servers may be strained to perform complex computational tasks w

Filip Cano Córdoba, Alexander Palmisano, Martin Fränzle, Roderick Bloem

Agents operating in physical environments need to be able to handle delays in the input and output signals since neither data transmission nor sensing or actuating the environment are instantaneous. Shields are correct-by-construction runtime enforcers that guarantee safe execution by correcting any action that may cause a violation of a formal safety specif

Alba Crescente

The coherent energy transfer between a quantum charger and a quantum battery is analyzed. In particular, we study how to improve the direct energy transfer by adding a photonic cavity as a mediator. We show that the additional degree of freedom given by the photons consistently improves the transfer performances, above all in the off-resonant case, where the

Jingwei Zhang, Han Shi, Jincheng Yu, Enze Xie

Generative models can be categorized into two types: explicit generative models that define explicit density forms and allow exact likelihood inference, such as score-based diffusion models (SDMs) and normalizing flows; implicit generative models that directly learn a transformation from the prior to the data distribution, such as generative adversarial nets

Zhi Zheng, Zhaopeng Qiu, Xiao Hu, Likang Wu

The rapid development of online recruitment services has encouraged the utilization of recommender systems to streamline the job seeking process. Predominantly, current job recommendations deploy either collaborative filtering or person-job matching strategies. However, these models tend to operate as "black-box" systems and lack the capacity to offe

Camille Laurent, Matthieu Léautaud

These notes are intended as an introduction to the question of unique continuation for the wave operator, and some of its applications. The general question is whether a solution to a wave equation in a domain, vanishing on a subdomain has to vanish everywhere. We state and prove two of the main results in the field. We first give a proof of the classical lo

Cees Diks, Bram Wouters

A novel method for noise reduction in the setting of curve time series with error contamination is proposed, based on extending the framework of functional principal component analysis (FPCA). We employ the underlying, finite-dimensional dynamics of the functional time series to separate the serially dependent dynamical part of the observed curves from the n

Tulasi Bharathi, Shailaja D Sharma, Nithin Nagaraj

Kolam is a ritual art form practised by people in South India and consists of rule-bound geometric patterns of dots and lines. Single loop Kolams are mathematical closed loop patterns drawn over a grid of dots and conforming to certain heuristics. In this work, we propose a novel encoding scheme where we map the angular movements of Kolam at lattice points i

Rouven Michels, Marius Ötting, Dimitris Karlis

The prevalent model by Dixon and Coles (1997) extends the double Poisson model where two independent Poisson distributions model the number of goals scored by each team by moving probabilities between the scores 0-0, 0-1, 1-0, and 1-1. We show that this is a special case of a multiplicative model known as the Sarmanov family. Based on this family, we create

Rui Gong, Martin Danelljan, Han Sun, Julio Delgado Mangas

While originally designed for image generation, diffusion models have recently shown to provide excellent pretrained feature representations for semantic segmentation. Intrigued by this result, we set out to explore how well diffusion-pretrained representations generalize to new domains, a crucial ability for any representation. We find that diffusion-pretra

Tomer Cohen, Ariel Kulik, Hadas Shachnai

We study the uniform $2$-dimensional vector multiple knapsack (2VMK) problem, a natural variant of multiple knapsack arising in real-world applications such as virtual machine placement. The input for 2VMK is a set of items, each associated with a $2$-dimensional weight vector and a positive profit, along with $m$ $2$-dimensional bins of uniform (unit) capac

Gilles Aldon

Doing mathematics implies three levels of manipulation: manipulating the abstract, manipulating symbols and manipulating logic. Teaching mathematics therefore involves the teacher proposing situations in which pupils can explore a small part of mathematics through these manipulations. In doing so, the pupils work on both the heuristics enabling them to confr

Oubaïda Chouchane, Michele Panariello, Oualid Zari, Ismet Kerenciler

Over the last decade, the use of Automatic Speaker Verification (ASV) systems has become increasingly widespread in response to the growing need for secure and efficient identity verification methods. The voice data encompasses a wealth of personal information, which includes but is not limited to gender, age, health condition, stress levels, and geographica

Tanmay sahoo, Nil Kamal Hazra, Narayanaswamy Balakrishnan

Ordered random vectors are frequently encountered in many problems. The generalized order statistics (GOS) and sequential order statistics (SOS) are two general models for ordered random vectors. However, these two models do not capture the dependency structures that are present in the underlying random variables. In this paper, we study the developed sequen

Felix Burkhardt, Uwe Reichel, Florian Eyben, Björn Schuller

We introduce two rule-based models to modify the prosody of speech synthesis in order to modulate the emotion to be expressed. The prosody modulation is based on speech synthesis markup language (SSML) and can be used with any commercial speech synthesizer. The models as well as the optimization result are evaluated against human emotion annotations. Results

Slawomir Mianowski, Nicolas De Angelis, Kamil Brylew, Johannes Hulsman

POLAR-2, a plastic scintillator based Compton polarimeter, is currently under development and planned for a launch to the China Space Station in 2025. It is intended to shed a new light on our understanding of Gamma-Ray Bursts by performing high precision polarization measurements of their prompt emission. The instrument will be orbiting at an average altitu

Hejing Cao, Dongyan Zhao

Grammatical Error Correction (GEC) is the task of correcting errorful sentences into grammatically correct, semantically consistent, and coherent sentences. Popular GEC models either use large-scale synthetic corpora or use a large number of human-designed rules. The former is costly to train, while the latter requires quite a lot of human expertise. In rece

Shaogao Lv, Gang Wen, Shiyu Liu, Linsen Wei

To improve the robustness of graph neural networks (GNN), graph structure learning (GSL) has attracted great interest due to the pervasiveness of noise in graph data. Many approaches have been proposed for GSL to jointly learn a clean graph structure and corresponding representations. To extend the previous work, this paper proposes a novel regularized GSL a

Masayuki Asaoka, Taisuke Shibata

In this paper, we prove that if an area-preserving non-degenerate diffeomorphism on the open disk which extend smoothly to the boundary with non-degeneracy has at least 2 interior periodic points, then there are infinitely many positive hyperbolic periodic points on the interior. As an application, we prove that if a non-degenerate universally tight contact

Kim Cheng Sheang, Horacio Saggion

Text is by far the most ubiquitous source of knowledge and information and should be made easily accessible to as many people as possible; however, texts often contain complex words that hinder reading comprehension and accessibility. Therefore, suggesting simpler alternatives for complex words without compromising meaning would help convey the information t

Zhuoyang Liu, Huilin Xu, Feng Xu

Radar imaging is crucial in remote sensing and has many applications in detection and autonomous driving. However, the received radar signal for imaging is enormous and redundant, which degrades the speed of real-time radar quantitative imaging and leads to obstacles in the downlink applications. In this paper, we propose a physics-assisted deep learning met

Zichen Yang

In this paper, we study universal sums of triangular numbers and squares. Specifically, we prove that a sum of triangular numbers and squares is universal if and only if it represents $1,2,3,4,5,6,7,8,10,13,14,15,18,19,20,23,27,28,34,41,47$, and $48$.

David Ackermann, Fabian Brinkmann, Stefan Weinzierl

We present a database of recordings and radiation patterns of individual notes for 41 modern and historical musical instruments, measured with a 32-channel spherical microphone array in anechoic conditions. In addition, directivities averaged in one-third octave bands have been calculated for each instrument, which are suitable for use in acoustic simulation

Florian Stadtmann, Adil Rasheed, Tore Rasmussen

In this work, a digital twin with standalone, descriptive, and predictive capabilities is created for an existing onshore wind farm located in complex terrain. A standalone digital twin is implemented with a virtual-reality-enabled 3D interface using openly available data on the turbines and their environment. Real SCADA data from the wind farm are used to e

Jun-Hao Cheng, Wen-Yu Zhang, Qiong Xiao, Jun-Gang Deng

In the present work, the influence of ultra-intense laser fields on the $α$ decay half-life of the deformed ground state even-even nucleus with the mass number $52 \leq Z \leq 118$ is systematically studied. The calculations show that the laser field changes the $α$ decay half-life by varying the $α$ decay penetration probability in a small range. Moreover,

Adam Ivankay, Mattia Rigotti, Pascal Frossard

Along with the successful deployment of deep neural networks in several application domains, the need to unravel the black-box nature of these networks has seen a significant increase recently. Several methods have been introduced to provide insight into the inference process of deep neural networks. However, most of these explainability methods have been sh

Qiqi Zhou, Yichen Zhu

The vision transformer is a model that breaks down each image into a sequence of tokens with a fixed length and processes them similarly to words in natural language processing. Although increasing the number of tokens typically results in better performance, it also leads to a considerable increase in computational cost. Motivated by the saying "A pictu

Mohan Zhou, Yalong Bai, Wei Zhang, Ting Yao

We introduce a new conversation head generation benchmark for synthesizing behaviors of a single interlocutor in a face-to-face conversation. The capability to automatically synthesize interlocutors which can participate in long and multi-turn conversations is vital and offer benefits for various applications, including digital humans, virtual agents, and so

Shintaro Nomura, Hideyuki Watanabe, Satoshi Kashiwaya

Near-field enhancement of the microwave field is applied for imaging high frequency radio field using a diamond chip with an $n$-doped isotopically purified diamond layer grown by microwave plasma assisted chemical vapor deposition. A short $π$ pulse length enables us to utilize a multipulse dynamic decoupling method for detection of radio frequency field at

Alafate Abulimiti

In this paper, we show that investigating the interaction of conversational type (often known as language game or speech genre) with the character types of the interlocutors is worthwhile. We present a method of calculating the decision making process for selecting dialogue moves that combines character type and conversational type. We also present a mathema

Fritjof Freise, Norbert Gaffke, Rainer Schwabe

Under a nonlinear regression model with univariate response an algorithm for the generation of sequential adaptive designs is studied. At each stage, the current design is augmented by adding $p$ design points where $p$ is the dimension of the parameter of the model. The augmenting $p$ points are such that, at the current parameter estimate, they constitute

Cai-Ying Shao, Yu Hu, Cheng-Gang Shao

Future space-based gravitational-wave detectors will detect gravitational waves with high sensitivity in the millihertz frequency band, which provides more opportunities to test theories of gravity than ground-based ones. The study of quasinormal modes (QNMs) and their application to testing gravity theories have been an important aspect in the field of grav

Christiaan Jacobs, Herman Kamper

Acoustic word embeddings (AWEs) are fixed-dimensional vector representations of speech segments that encode phonetic content so that different realisations of the same word have similar embeddings. In this paper we explore semantic AWE modelling. These AWEs should not only capture phonetics but also the meaning of a word (similar to textual word embeddings).

Belén Maté, Isabel Tanarro, Vicente Timón, José Cernicharo

Experimental and theoretical infrared spectra, between 4000-500 cm$^{-1}$ (2.5-20 microns), and infrared band strengths of two solid phases of indene, amorphous and crystalline, are given for the first time. The samples were generated via vapor deposition under high vacuum conditions on a cold surface. Density functional theory was employed for the calculati

Bulat Nasrulin, Georgy Ishmaev, Jérémie Decouchant, Johan Pouwelse

Possible manipulation of user transactions by miners in a permissionless blockchain systems is a growing concern. This problem is a pervasive and systemic issue, known as Miner Extractable Value (MEV), incurs highs costs on users of decentralised applications. Furthermore, transaction manipulations create other issues in blockchain systems such as congestion

Jie Gu

In this paper we demonstrate that the Stokes constants of unrefined free energies and the Stokes constants of Nekrasov-Shatashvili free energies of topological string on a non-compact Calabi-Yau threefold are identical, possibly up to a sign, for any Borel singularity which is not associated to a compact two-cycle that intersects only with non-compact four-c

Zheheng Luo, Lei Liu, Qianqian Xie, Sophia Ananiadou

Existing NTMs with contrastive learning suffer from the sample bias problem owing to the word frequency-based sampling strategy, which may result in false negative samples with similar semantics to the prototypes. In this paper, we aim to explore the efficient sampling strategy and contrastive learning in NTMs to address the aforementioned issue. We propose

Ian Heywood

MeerKAT imaging of the globular cluster 47 Tucanae (47 Tuc) reveals 1.28 GHz continuum emission at the locations of 20 known millisecond pulsars (MSPs). We use time series and spectral imaging to investigate the image-domain characteristics of the MSPs, and search for previously unknown sources of interest. The MSPs exhibit a range of differences in their te

Yan Chang, Yukun Guo, Tao Yin, Yue Zhao

In this paper, we study the inverse source problem for the biharmonic wave equation. Mathematically, we characterize the radiating sources and non-radiating sources at a fixed wavenumber. We show that a general source can be decomposed into a radiating source and a non-radiating source. The radiating source can be uniquely determined by Dirichlet boundary me

Fabio Sigrist

High-cardinality categorical variables are variables for which the number of different levels is large relative to the sample size of a data set, or in other words, there are few data points per level. Machine learning methods can have difficulties with high-cardinality variables. In this article, we empirically compare several versions of two of the most su

Soham Jana, Yury Polyanskiy, Anzo Teh, Yihong Wu

We consider the problem of empirical Bayes estimation for (multivariate) Poisson means. Existing solutions that have been shown theoretically optimal for minimizing the regret (excess risk over the Bayesian oracle that knows the prior) have several shortcomings. For example, the classical Robbins estimator does not retain the monotonicity property of the Bay

Talha Mushtaq, Peter Seiler, Maziar S. Hemati

In this note, we present an exact solution for the structured singular value (SSV) of rank-one complex matrices with repeated complex full-block uncertainty. A key step in the proof is the use of Von Neumman's trace inequality. Previous works provided exact solutions for rank-one SSV when the uncertainty contains repeated (real or complex) scalars and/or

Chen Yaling, Feng Zhang, Hu Liu, Fengrong Zhu

The knee of cosmic ray spectra reflects the maximum energy accelerated by galactic cosmic ray sources or the limit to the ability of galaxy to bind cosmic rays. The measuring of individual energy spectra is a crucial tool to ascertain the origin of the knee. The Extensive Air Shower of cosmic rays in the knee energy region is simulated via CORSIKA software.

Steve Hanneke, Shay Moran, Qian Zhang

We study universal rates for multiclass classification, establishing the optimal rates (up to log factors) for all hypothesis classes. This generalizes previous results on binary classification (Bousquet, Hanneke, Moran, van Handel, and Yehudayoff, 2021), and resolves an open question studied by Kalavasis, Velegkas, and Karbasi (2022) who handled the multicl

Omar Moured, Jiaming Zhang, Alina Roitberg, Thorsten Schwarz

The digitization of documents allows for wider accessibility and reproducibility. While automatic digitization of document layout and text content has been a long-standing focus of research, this problem in regard to graphical elements, such as statistical plots, has been under-explored. In this paper, we introduce the task of fine-grained visual understandi

Jingcheng Xie, Haifan Yin, Liangcheng Han

The array gain of a superdirective antenna array can be proportional to the square of the number of antennas. However, the realization of the so-called superdirectivity entails accurate calculation and application of the excitations. Moreover, the excitations require a large dynamic power range, especially when the antenna spacing is smaller. In this paper,

Fuchao Wei, Chenglong Bao, Yang Liu, Guangwen Yang

Anderson mixing (AM) is a classical method that can accelerate fixed-point iterations by exploring historical information. Despite the successful application of AM in scientific computing, the theoretical properties of AM are still under exploration. In this paper, we study the restarted version of the Type-I and Type-II AM methods, i.e., restarted AM. With

Hanzhang Xue, Hao Fu, Liang Xiao, Yiming Fan

For autonomous driving, traversability analysis is one of the most basic and essential tasks. In this paper, we propose a novel LiDAR-based terrain modeling approach, which could output stable, complete and accurate terrain models and traversability analysis results. As terrain is an inherent property of the environment that does not change with different vi

Alexandre Jaoui, Shan Jiang, Xiaokang Li, Yasuhide Tomioka

Crystals and glasses differ by the amplitude and the temperature dependence of their thermal conductivity. However, there are crystals known to display glass-like thermal conductivity. Here, we show that EuTiO$_3$, a quantum paraelectric known to order antiferromagnetically at 5.5 K, is one such system. The temperature dependence of resistivity and Seebeck c

Mathias Anselmann, Markus Bause, Nils Margenberg, Pavel Shamko

We present benchmark computations of dynamic poroelasticity modeling fluid flow in deformable porous media by a coupled hyperbolic-parabolic system of partial differential equations. A challenging benchmark setting and goal quantities of physical interest for this problem are proposed. Computations performed by space-time finite element approximations with c

Simran Kumari, Susenjit Ghosh, Ashish R. Hota, Siddhartha Mukhopadhyay

Current research on energy related problems such as eco-routing, eco-driving and range prediction for electric vehicles (EVs) primarily considers the effect of longitudinal dynamics on EV energy consumption. However, real-world driving includes longitudinal as well as lateral motion. Therefore, it is important to understand the effects of lateral dynamics on

Jaydip Sen, Subhasis Dasgupta

This chapter introduces the concept of adversarial attacks on image classification models built on convolutional neural networks (CNN). CNNs are very popular deep-learning models which are used in image classification tasks. However, very powerful and pre-trained CNN models working very accurately on image datasets for image classification tasks may perform

Deepanway Ghosal, Yew Ken Chia, Navonil Majumder, Soujanya Poria

Recently, the release of INSTRUCTEVAL has provided valuable insights into the performance of large language models (LLMs) that utilize encoder-decoder or decoder-only architecture. Interestingly, despite being introduced four years ago, T5-based LLMs, such as FLAN-T5, continue to outperform the latest decoder-based LLMs, such as LLAMA and VICUNA, on tasks th

K. Luijken, A. Lohmann, U. Alter, J. Claramunt Gonzalez

Results of simulation studies evaluating the performance of statistical methods are often considered actionable and thus can have a major impact on the way empirical research is implemented. However, so far there is limited evidence about the reproducibility and replicability of statistical simulation studies. Therefore, eight highly cited statistical simula

Noé Tits, Zoé Broisson

In this paper, we present a solution for providing personalized and instant feedback to English learners through a mobile application, called Flowchase, that is connected to a speech technology able to segment and analyze speech segmental and supra-segmental features. The speech processing pipeline receives linguistic information corresponding to an utteranc

Jianming Huang, Yu Hua

Extended Asynchronous DRAM Refresh (eADR) proposed by Intel extends the persistence domain from the Non-Volatile Memory (NVM) to CPU caches and offers the persistence guarantee. Due to allowing lazy persistence and decreasing the amounts of instructions, eADR-based NVM systems significantly improve performance. Existing designs however fail to provide effici

Mingjian Tuo, Xingpeng Li, Tianxia Zhao

Power flow analysis plays a crucial role in examining the electricity flow within a power system network. By performing power flow calculations, the system's steady-state variables, including voltage magnitude, phase angle at each bus, active/reactive power flow across branches, can be determined. While the widely used DC power flow model offers speed an

Takahiro Inayama

For a continuous function, we prove that the function is pluriharmonic if and only if the equality part of the optimal Ohsawa--Takegoshi $L^2$-extension theorem is satisfied with respect to the metric having the function as a weight. This partially resolves the conjecture proposed by the author.

Li Mingcong, Zhao Zhenming

Dispersion is an important factor of optical materials. Due to the effect of techniques and equipment in the manufacturing process of optical materials, the inhomogeneity of the material may be caused. In this paper, microsphere optical media are used to replace the inhomogeneous zones, and Huygens'principle is used to study the dispersion caused by the

Jie Fu, Junyu Gao, Changsheng Xu

Weakly-supervised audio-visual video parsing (WS-AVVP) aims to localize the temporal extents of audio, visual and audio-visual event instances as well as identify the corresponding event categories with only video-level category labels for training. Most previous methods pay much attention to refining the supervision for each modality or extracting fruitful

Yiyao Zhou, Qianggang Wang, Yuan Chi, Jianquan Liao

Optimal power flow (OPF) is a fundamental tool for analyzing the characteristics of bipolar DC distribution network (DCDN). However, existing OPF models face challenges in reflecting the power distribution and exchange of bipolar DCDN directly since its decision variables are voltage and current. This paper addresses this issue by establishing a convex OPF m

Anqi Mao, Mehryar Mohri, Yutao Zhong

We introduce a novel framework of ranking with abstention, where the learner can abstain from making prediction at some limited cost $c$. We present a extensive theoretical analysis of this framework including a series of $H$-consistency bounds for both the family of linear functions and that of neural networks with one hidden-layer. These theoretical guaran

Ali Shoker, Fernando Alves, Paulo Esteves-Verissimo

Over-the-Air (OTA) software updates are becoming essential for electric/electronic vehicle architectures in order to reduce recalls amid the increasing software bugs and vulnerabilities. Current OTA update architectures rely heavily on direct cellular repository-to-vehicle links, which makes the repository a communication bottleneck, and increases the cellul

Xiang Li, Huan Liang, Shaozhuang Xu, Dunyan Yan

In this paper, we will prove the sharp bounds of various operators in mixed radial angular spaces on Heisenberg groups. It mainly includes the boundedness of linear transformation eigenvalue operator in mixed radial angular space; Sharp Bounds of Hilbert Operator and Hardy-Littlewood-P$\acute{o}$lya Operator in mixed radial-angular space

Takashi Nakamura, Masatoshi Suzuki

We show that central zeros of $L$-functions in the Selberg class have a probabilistic interpretation by stating an equivalence condition of the Riemann hypothesis for the $L$-functions in terms of infinitely divisible distributions.

Lin Sui, Fangzhou Mu, Yin Li

This report describes our submission to the Ego4D Moment Queries Challenge 2023. Our submission extends ActionFormer, a latest method for temporal action localization. Our extension combines an improved ground-truth assignment strategy during training and a refined version of SoftNMS at inference time. Our solution is ranked 2nd on the public leaderboard wit

Runa Bhaumik, Jonathan Stange

Background: Reliable prediction of clinical progression over time can improve the outcomes of depression. Little work has been done integrating various risk factors for depression, to determine the combinations of factors with the greatest utility for identifying which individuals are at the greatest risk. Method: This study demonstrates that data-driven mac

Manuel Lafond, Weidong Luo

For a graph class $\mathcal{G}$, we define the $\mathcal{G}$-modular cardinality of a graph $G$ as the minimum size of a vertex partition of $G$ into modules that each induces a graph in $\mathcal{G}$. This generalizes other module-based graph parameters such as neighborhood diversity and iterated type partition. Moreover, if $\mathcal{G}$ has bounded modula

Lingyong Zeng, Zequan Wang, Jing Song, Gaoting Lin

High-entropy ceramics (HECs) are solid solutions of inorganic compounds with one or more Wyckoff sites shared by equal or near-equal atomic ratios of multi-principal elements. Material design and property tailoring possibilities emerge from this new class of materials. Here, we report the discovery of superconductivity around 2.35 K and topological propertie

Mingchuan Tian, Wilson Weixun Lu, Kelvin Weng Chiong Foong, Eugene Loh

Objectives: This research introduces a novel area-preserving Generative Adversarial Networks (GAN) inversion technique for effectively de-identifying dental patient images. This innovative method addresses privacy concerns while preserving key dental features, thereby generating valuable resources for dental education and research. Methods: We enhanced the e

Dollaya Hirunyasiri, Danielle R. Thomas, Jionghao Lin, Kenneth R. Koedinger

Research suggests that providing specific and timely feedback to human tutors enhances their performance. However, it presents challenges due to the time-consuming nature of assessing tutor performance by human evaluators. Large language models, such as the AI-chatbot ChatGPT, hold potential for offering constructive feedback to tutors in practical settings.

Herbert Palme, Dominik C. Hezel, Denton S. Ebel

One of the major unresolved problems in cosmochemistry is the origin of chondrules, once molten, spherical silicate droplets with diameters of 0.2 to 2 mm. Chondrules are an essential component of primitive meteorites and perhaps of all early solar system materials including the terrestrial planets. Numerous hypotheses have been proposed for their origin. Ma

Michael Greenberg, Denton S. Ebel

The Stardust mission captured comet Wild 2 particles in aerogel at 6.1 km/sec. We performed high resolution three-dimensional imaging and X-ray fluorescence mapping of whole cometary tracks in aerogel. We present the results of a survey of track structures using Laser Scanning Confocal Microscopy, including measurements of track volumes, entry hole size and