October 2022 arXiv papers — page 74

Haotian Ye, Xiaoyu Chen, Liwei Wang, Simon S. Du

Generalization in Reinforcement Learning (RL) aims to learn an agent during training that generalizes to the target environment. This paper studies RL generalization from a theoretical aspect: how much can we expect pre-training over training environments to be helpful? When the interaction with the target environment is not allowed, we certify that the best

Vivek Velivela, Chahat Raj, Muhammad Salman Tiwana, Raj Prasanna

Social media has been a powerful tool and an integral part of communication, especially during natural disasters. Social media platforms help nonprofits in effective disaster management by disseminating crucial information to various communities at the earliest. Besides spreading information to every corner of the world, various platforms incorporate many fe

Christiaan P. A. Van Buchem, Yamila Miguel, Mantas Zilinskas, Wim van Westrenen

To date, over 500 short-period rocky planets with equilibrium temperatures above 1500 K have been discovered. Such planets are expected to support magma oceans, providing a direct interface between the interior and the atmosphere. This provides a unique opportunity to gain insight into their interior compositions through atmospheric observations. A key proce

Yaming Yang, Ziyu Guan, Zhe Wang, Wei Zhao

Recent self-supervised pre-training methods on Heterogeneous Information Networks (HINs) have shown promising competitiveness over traditional semi-supervised Heterogeneous Graph Neural Networks (HGNNs). Unfortunately, their performance heavily depends on careful customization of various strategies for generating high-quality positive examples and negative e

Sultan Abulkhair, Peter A. Dowd, Chaoshui Xu

One of the most challenging aspects of multivariate geostatistics is dealing with complex relationships between variables. Geostatistical co-simulation and spatial decorrelation methods, commonly used for modelling multiple variables, are ineffective in the presence of multivariate complexities. On the other hand, multi-Gaussian transforms are designed to de

Cristian Axenie, Margherita Grossi

Existing traffic control systems only possess a local perspective over the multiple scales of traffic evolution, namely the intersection level, the corridor level, and the region level respectively. But luckily, despite its complex mechanics, traffic is described by various periodic phenomena. Workday flow distributions in the morning and evening commuting t

Emmanuelle Muhlethaler, Erez Posner, Moshe Bouhnik

Colonoscopy is the most common procedure for early detection and removal of polyps, a critical component of colorectal cancer prevention. Insufficient visual coverage of the colon surface during the procedure often results in missed polyps. To mitigate this issue, reconstructing the 3D surfaces of the colon in order to visualize the missing regions has been

Andrea P. Nagy

Here, we present a systematic study of 59 stripped-envelope supernovae (SESNe) (including Type IIb, Ib, Ic, and transitional events) to map a possible reason for the so-called mass-discrepancy problem. In this scenario, we assume the tension between the estimated ejected masses from early- and late-time light curves (LC) is due to approximations generally us

T. H. Phat, N. T. Anh, Toan T. Nguyen, H. V. Quyet

In this paper, we show that depending on the sign of the electric charge $Q$, the charged AdS black hole (BH) possesses two alternative facets when the cosmological constant is identified to the thermodynamic pressure $P$. It is discovered that: 1) the equation of state of BH corresponds to $Q>0$ and when $Q$ changes from $Q>0$ to $Q<0$ we obtain the equatio

Joachim Baumann, Christoph Heitz

Ensuring fairness of prediction-based decision making is based on statistical group fairness criteria. Which one of these criteria is the morally most appropriate one depends on the context, and its choice requires an ethical analysis. In this paper, we present a step-by-step procedure integrating three elements: (a) a framework for the moral assessment of w

Tim Graefnitz

In this note I will explain how relative/log Gromov-Witten invariants of pairs $(X,D)$ with very ample smooth anticanonical divisor $D$ can be computed using algebro-combinatorial objects called scattering diagrams. The underlying principle behind this computational method is a tropical correspondence theorem for non-toric cases, which I will explain briefly

Manoel Horta Ribeiro, Justin Cheng, Robert West

Online social media platforms use automated moderation systems to remove or reduce the visibility of rule-breaking content. While previous work has documented the importance of manual content moderation, the effects of automated content moderation remain largely unknown. Here, in a large study of Facebook comments (n=412M), we used a fuzzy regression discont

Dimitrios Tsitsokas, Anastasios Kouvelas, Nikolas Geroliminis

Traffic-responsive signal control is a cost-effective and easy-to-implement network management strategy with high potential in improving performance in congested networks with dynamic characteristics. Max Pressure (MP) distributed controller gained significant popularity due to its theoretically proven ability of queue stabilization and throughput maximizati

Szilvia Ujváry, Zsigmond Telek, Anna Kerekes, Anna Mészáros

Sharpness-aware minimization (SAM) aims to improve the generalisation of gradient-based learning by seeking out flat minima. In this work, we establish connections between SAM and Mean-Field Variational Inference (MFVI) of neural network parameters. We show that both these methods have interpretations as optimizing notions of flatness, and when using the rep

Muhammad Salman, Muhammad Ikram, Mohamed Ali Kaafar

The short message service (SMS) was introduced a generation ago to the mobile phone users. They make up the world's oldest large-scale network, with billions of users and therefore attracts a lot of fraud. Due to the convergence of mobile network with internet, SMS based scams can potentially compromise the security of internet services as well. In this stud

Tatsuya Hosoi

It is known that all $\tau$ functions of the Painlev\'{e} equations satisfy the fourth-order quadratic differential equation. Among them, for the III, V, and VI equations, it is possible to express the formal series solutions explicitly by using combinatorics. In this paper, we show the convergence of the formal series, including the solutions of more genera

Siyao Peng, Yang Janet Liu, Amir Zeldes

A lack of large-scale human-annotated data has hampered the hierarchical discourse parsing of Chinese. In this paper, we present GCDT, the largest hierarchical discourse treebank for Mandarin Chinese in the framework of Rhetorical Structure Theory (RST). GCDT covers over 60K tokens across five genres of freely available text, using the same relation inventor

Bradley E. Schaefer, Frederick M. Walter, Rebekah Hounsell, Yael Hillman

KT Eridani was a very fast nova in 2009 peaking at V=5.42 mag. We marshal large data sets of photometry to finally work out the nature of KT Eri. From the TESS light curve, as confirmed with our radial velocity curve, we find an orbital period of 2.61595 days. With our 272 spectral energy distributions from simultaneous BVRIJHK measures, the companion star h

Ye Tianyi

Communication in poor network environment is always a difficult problem, since troubles such as bit errors and packet loss may often occur. It is generally believed that it is impossible to transmit data both accurately and efficiently in this case. However, this paper provides a method to transmit data efficiently on the line where bit error may occur by ut

Lev Telyatnikov, Simone Scardapane

Missing data imputation (MDI) is crucial when dealing with tabular datasets across various domains. Autoencoders can be trained to reconstruct missing values, and graph autoencoders (GAE) can additionally consider similar patterns in the dataset when imputing new values for a given instance. However, previously proposed GAEs suffer from scalability issues, r

Mobin Ahmad, Mohammad Aamir Qayyoom

In this paper, we define and study CR-lightlike submanifolds of a golden semi-Riemannian manifold. We investigate some properties of geodesic CR-submanifolds of a golden semi-Riemannian manifold. Moreover, we obtain many interesting results for totally geodesic and totally umbilical CR-submanifolds on a golden Riemannian manifold. A non-trivial example of CR

Vladyslav Solohub

This qualification work studies methods of statistical analysis of global brands distributions and development process of information system which is represented by computer program. Algorithm of estimation of correspondance to distribution laws was shown. Correspondance of datasets (3) to Pareto Law and Zipf's Law were defined. Key words: analysis, method,

Viktoria Heimann, Andreas Spruck, André Kaup

High frame rates are desired in many fields of application. As in many cases the frame repetition rate of an already captured video has to be increased, frame rate up-conversion (FRUC) is of high interest. We conduct a motion compensated approach. From two neighboring frames, the motion is estimated and the neighboring pixels are shifted along the motion vec

Lukas Gonon

This article studies deep neural network expression rates for optimal stopping problems of discrete-time Markov processes on high-dimensional state spaces. A general framework is established in which the value function and continuation value of an optimal stopping problem can be approximated with error at most $\varepsilon$ by a deep ReLU neural network of s

Shirong Ma, Yinghui Li, Rongyi Sun, Qingyu Zhou

Chinese Grammatical Error Correction (CGEC) is both a challenging NLP task and a common application in human daily life. Recently, many data-driven approaches are proposed for the development of CGEC research. However, there are two major limitations in the CGEC field: First, the lack of high-quality annotated training corpora prevents the performance of exi

Sean Murphy, Leonardo Militano, Giovanni Toffetti, Remo Maurer

In this paper, we report on our use of cloud-robotics solutions to teach a Robotics Applications Programming course at Zurich University of Applied Sciences (ZHAW). The usage of Kubernetes based cloud computing environment combined with real robots -- turtlebots and Niryo arms -- allowed us to: 1) minimize the set up times required to provide a Robotic Opera

Mikako Matsuura, Roger Wesson, Richard G. Arendt, Eli Dwek

At a distance of 50 kpc, Supernova 1987A is an ideal target to study how a young supernova (SN) evolves in time. Its equatorial ring, filled with material expelled from the progenitor star about 20,000 years ago, has been engulfed with SN blast waves. Shocks heat dust grains in the ring, emitting their energy at mid-infrared (IR) wavelengths We present groun

Ruimin Feng, Qing Wu, Yuyao Zhang, Hongjiang Wei

Parallel imaging is a widely-used technique to accelerate magnetic resonance imaging (MRI). However, current methods still perform poorly in reconstructing artifact-free MRI images from highly undersampled k-space data. Recently, implicit neural representation (INR) has emerged as a new deep learning paradigm for learning the internal continuity of an object

Marcin Marculewicz, Marek Nikolajuk, Agata Różańska

We study the origin of the anomalous deep absorption in a spectrum of the SDSS J110511.15+530806.5 distant quasar (z=1.929) obtained by the Sloan Digital Sky Survey in Data Release 7 of the optical catalog. We aim to estimate the velocity of absorbing material, and we show that this material considerably affects our measurements of the black hole (BH) mass i

Yueshen Wu, Qi Wang, Xiang Zhou, Jinghui Wang

Nonreciprocal charge transport phenomena are widely studied in two-dimensional superconductors, which demonstrate unidirectional-anisotropy magnetoresistances as a result of symmetry breaking. Here, we report a strong nonreciprocal transport phenomenon in superconducting CsV$_{3}$Sb$_{5}$ thin flakes. The second harmonic voltages, mainly originating from the

Xin Mao, Wenting Wang, Yuanbin Wu, Man Lan

Entity Alignment (EA) aims to find equivalent entity pairs between KGs, which is the core step of bridging and integrating multi-source KGs. In this paper, we argue that existing GNN-based EA methods inherit the inborn defects from their neural network lineage: weak scalability and poor interpretability. Inspired by recent studies, we reinvent the Label Prop

Takahiko Matsubara

In order to extract maximal information about cosmology from the large-scale structure of the Universe, one needs to use every bit of signal that can be observed. Beyond the spatial distributions of astronomical objects, the spatial correlations of tensor fields, such as galaxy spins and shapes, are ones of promising sources that can be accessed in the era o

Maren Pielka, Felix Rode, Lisa Pucknat, Tobias Deußer

We analyze two Natural Language Inference data sets with respect to their linguistic features. The goal is to identify those syntactic and semantic properties that are particularly hard to comprehend for a machine learning model. To this end, we also investigate the differences between a crowd-sourced, machine-translated data set (SNLI) and a collection of t

MohammadJavad Salehi, Antti Tölli

Multi-antenna coded caching (CC) techniques are considered viable options for achieving higher data rates in future networks, especially for the prominent use case of multimedia-driven applications. However, despite their information-theoretic analyses, which are thoroughly studied in the literature, the research on the finite-SNR performance of multi-antenn

Hui Cao, Wenlong Zou, Yinkun Wang, Ting Song

Since the 2004 DARPA Grand Challenge, the autonomous driving technology has witnessed nearly two decades of rapid development. Particularly, in recent years, with the application of new sensors and deep learning technologies extending to the autonomous field, the development of autonomous driving technology has continued to make breakthroughs. Thus, many car

Christian Palmroos, Jan Gieseler, Nina Dresing, Diana E. Morosan

Solar Energetic Particles (SEPs) are charged particles accelerated within the solar atmosphere or the interplanetary space by explosive phenomena such as solar flares or Coronal Mass Ejections (CMEs). Once injected into the interplanetary space, they can propagate towards Earth, causing space weather related phenomena. For their analysis, interplanetary in-s

Xinhan Di, Pengqian Yu

In real life, the decoration of 3D indoor scenes through designing furniture layout provides a rich experience for people. In this paper, we explore the furniture layout task as a Markov decision process (MDP) in virtual reality, which is solved by hierarchical reinforcement learning (HRL). The goal is to produce a proper two-furniture layout in the virtual

L. K. Duchaniya, B. Mishra, Jackson Levi Said

The Noether Symmetry approach is applied to study an extended teleparallel $f(T,\phi)$ gravity that contains the torsion scalar $T$ and the scalar field $\phi$ in the context of an Friedmann-Lema\^{i}tre-Robertson-Walker space-time. We investigate the Noether symmetry approach in $f(T,\phi)$ gravity formalism with the specific form of $f(T,\phi)$ and analyze

Julien Klaus, Niklas Merk, Konstantin Wiedom, Sören Laue

The Hessian of a differentiable convex function is positive semidefinite. Therefore, checking the Hessian of a given function is a natural approach to certify convexity. However, implementing this approach is not straightforward since it requires a representation of the Hessian that allows its analysis. Here, we implement this approach for a class of functio

Mirza M. Elahi, Yihang Zeng, Cory R. Dean, Avik W. Ghosh

Transport measurement of electron optics in monolayer graphene p-n junction devices has been traditionally studied with negative refraction and chiral transmission experiments in Hallbar magnetic focusing set-ups. We show direct signatures of Klein (monolayer) and anti-Klein (bilayer) tunneling with a circular 'edgeless' Corbino geometry made out of gated gr

Prodromos Boutis, Zisis Batzos, Konstantinos Konstantoudakis, Anastasios Dimou

Nowadays, the need for large amounts of carefully and complexly annotated data for the training of computer vision modules continues to grow. Furthermore, although the research community presents state of the art solutions to many problems, there exist special cases, such as the pose estimation and tracking of a glove-wearing hand, where the general approach

Oriane Blondel

In this short note, we prove that $v(-\epsilon)=-v(\epsilon)$. Here, $v(\epsilon)$ is the speed of a one-dimensional random walk in a dynamic \emph{reversible} random environment, that jumps to the right (resp. to the left) with probability $1/2+\epsilon$ (resp. $1/2-\epsilon$) if it stands on an occupied site, and vice-versa on an empty site. We work in any

Sebastian Scherer, Robin Schön, Rainer Lienhart

Semi-supervised learning (SSL) can reduce the need for large labelled datasets by incorporating unlabelled data into the training. This is particularly interesting for semantic segmentation, where labelling data is very costly and time-consuming. Current SSL approaches use an initially supervised trained model to generate predictions for unlabelled images, c

Hyunsik Jeon, Jun-Gi Jang, Taehun Kim, U Kang

How can we recommend existing bundles to users accurately? How can we generate new tailored bundles for users? Recommending a bundle, or a group of various items, has attracted widespread attention in e-commerce owing to the increased satisfaction of both users and providers. Bundle matching and bundle generation are two representative tasks in bundle recomm

Katia Colaneri, Alessandra Cretarola, Benedetta Salterini

We study the optimal investment and proportional reinsurance problem of an insurance company, whose investment preferences are described via a forward dynamic utility of exponential type in a stochastic factor model allowing for a possible dependence between the financial and insurance markets. Specifically, we assume that the asset price process dynamics an

Zikang Yuan, Fengtian Lang, Tianle Xu, Xin Yang

This paper proposes a novel LiDAR-Inertial odometry (LIO), named SR-LIO, based on an iterated extended Kalman filter (iEKF) framework. We adapt the sweep reconstruction method, which segments and reconstructs raw input sweeps from spinning LiDAR to obtain reconstructed sweeps with higher frequency. We found that such method can effectively reduce the time in

Elizabeth Cappellazzo, Tayyaba Zafar, Pablo Corcho-Caballero, David Alexander Kann

We modelled dust grain-size distributions for carbonaceous and silicates dust, as well as for free-flying iron nanoparticles in the environment of a $\gamma$-ray burst (GRB) afterglow, GRB 180325A. This GRB, at $z=2.2486$, has an unambiguous detection of the 2175 \r{A} extinction feature with $R_V=4.58$ and $A_V=1.58$. In addition to silicates, polycyclic ar

Sean Dewar

A homothetic packing of squares is any set of various-size squares with the same orientation where no two squares have overlapping interiors. If all $n$ squares have the same size then we can have up to roughly $4n$ contacts by arranging the squares in a grid formation. The maximum possible number of contacts for a set of $n$ squares will drop drastically, h

Yanchen Yang, Lijun Yun, Ruoyu Li, Feiyan Cheng

While the Vision Transformer has been used in gait recognition, its application in multi-view gait recognition is still limited. Different views significantly affect the extraction and identification accuracy of the characteristics of gait contour. To address this, this paper proposes a Siamese Mobile Vision Transformer (SMViT). This model not only focuses o

Magdalena Zioło, Piotr Bródka, Anna Spoz, Jarosław Jankowski

Growing awareness of the impact of business activity on the environment increases the pressure on governing bodies to address this issue. One possibility is to encourage or force the market into green behaviours. However, it is often hard to predict how different actions affect the market. Thus, to help with that, in this paper, we have proposed the green be

Monica Barrera, Volker Springel, Simon White, César Hernández-Aguayo

Upcoming large galaxy surveys will subject the standard cosmological model, $\Lambda$CDM, to new precision tests. These can be tightened considerably if theoretical models of galaxy formation are available that can predict galaxy clustering and galaxy-galaxy lensing on the full range of measurable scales throughout volumes as large as those of the surveys an

Romain Thoreau, Laurent Risser, Véronique Achard, Béatrice Berthelot

The combination of machine learning models with physical models is a recent research path to learn robust data representations. In this paper, we introduce p$^3$VAE, a variational autoencoder that integrates prior physical knowledge about the latent factors of variation that are related to the data acquisition conditions. p$^3$VAE combines standard neural ne

Anna Vock, Tommy Nilsson

As the space industry continues its rapid development, humanity is poised to expand beyond Low Earth Orbit (LEO), seeking to establish permanent presence on the Moon and beyond. While space travel has traditionally been the domain of a small number of highly specialized professionals, a new era of human exploration, involving non-space actors and stakeholder

Stefan Veldsman

This is a survey of some of the consequences of the recently introduced congruences on the theory of connectednesses (radical classes) and disconnectednesses (semisimple classes) of graphs and topological spaces. In particular, it is shown that the connectednesses and disconnectednesses can be obtained as Hoehnke radicals and a connectedness has a characteri

Qiang Wang, Xinhui Hu, Ming Chen

In this work, we empirically confirm that non-autoregressive translation with an iterative refinement mechanism (IR-NAT) suffers from poor acceleration robustness because it is more sensitive to decoding batch size and computing device setting than autoregressive translation (AT). Inspired by it, we attempt to investigate how to combine the strengths of auto

Michael Innerberger, Ani Miraçi, Dirk Praetorius, Julian Streitberger

In this work, we formulate and analyze a geometric multigrid method for the iterative solution of the discrete systems arising from the finite element discretization of symmetric second-order linear elliptic diffusion problems. We show that the iterative solver contracts the algebraic error robustly with respect to the polynomial degree $p \ge 1$ and the (lo

Chi-Han Peng, Jiayao Zhang

We propose a novel approach to compute high-resolution (2048x1024 and higher) depths for panoramas that is significantly faster and qualitatively and qualitatively more accurate than the current state-of-the-art method (360MonoDepth). As traditional neural network-based methods have limitations in the output image sizes (up to 1024x512) due to GPU memory con

Rao Muhammad Umer, Christian Micheloni

The current existing deep image super-resolution methods usually assume that a Low Resolution (LR) image is bicubicly downscaled of a High Resolution (HR) image. However, such an ideal bicubic downsampling process is different from the real LR degradations, which usually come from complicated combinations of different degradation processes, such as camera bl

LHCb collaboration

A search for the baryon- and lepton-number violating decays $B^0\to p\mu^-$ and $B^0_s\to p\mu^-$ is performed at the LHCb experiment using data collected in proton-proton collisions at $\sqrt{s}$ = 7, 8 and 13 TeV, corresponding to integrated luminosities of 1, 2 and 6 fb$^{-1}$, respectively. No significant signal for $B^0\to p\mu^-$ and $B^0_s\to p\mu^-$

Martin Berggren

Shape calculus concerns the calculation of directional derivatives of some quantity of interest, typically expressed as an integral. This article introduces a type of shape calculus based on localized dilation of boundary faces through perturbations of a level-set function. The calculus is tailored for shape optimization problems where a partial differential

Jian-Tong Hou, Chang-Xu Yan, Chao-Yang Tan, Zhi-Qiang Li

We report a unified theory based on linear response, for analyzing the longitudinal optical conductivity (LOC) of materials with tilted Dirac cones. Depending on the tilt parameter $t$, the Dirac electrons have four phases: untilted, type-I, type-II, and type-III; the Dirac dispersion can be isotropic or anisotropic; the spatial dimension of the material can

Yingchun Guo, Huan He, Ye Zhu, Yang Yu

Domain generalization person re-identification (DG Re-ID) aims to directly deploy a model trained on the source domain to the unseen target domain with good generalization, which is a challenging problem and has practical value in a real-world deployment. In the existing DG Re-ID methods, invariant operations are effective in extracting domain generalization

Katsuhiro Ota, Masahiro Sanka

Let $k \geq 2$ be an integer. We say that a graph $G$ is $(K_2 \cup kK_1)$-free if it does not contain $K_2 \cup kK_1$ as an induced subgraph. Recently, Shi and Shan conjectured that every $1$-tough and $2k$-connected $(K_2 \cup kK_1)$-free graph is hamiltonian. In this paper, we solve this conjecture by proving the statement; every $1$-tough and $k$-connect

Zheng Gao, Lianyi He, Huaisong Zhao, Shi-Guo Peng

We theoretically calculate the density dynamic structure factor of one-dimensional Fermi superfluid with Raman-type spin-orbit coupling, and analyze its main dynamical character during phase transition between Bardeen-Cooper-Schrieffer superfluid and topological superfluid. Our theoretical results display four kinds of single-particle excitations induced by

Hongsen Peng, Meixia Tao

This paper investigates the effective capacity of a point-to-point ultra-reliable low latency communication (URLLC) transmission over multiple parallel sub-channels at finite blocklength (FBL) with imperfect channel state information (CSI). Based on reasonable assumptions and approximations, we derive the effective capacity as a function of the pilot length,

Chen-Yun Lin, Christina Sormani

We present an overview of the history of the heat kernel and eigenfunctions on Riemannian manifolds and how the theory has lead to modern methods of analyzing high dimensional data via eigenmaps and other spectral embeddings. We begin with Varadhan's Theorem relating the heat kernel to the distance function on a Riemannian manifold. We then review various th

Ron Ofir, Thomas Kriecherbauer, Lars Grüne, Michael Margaliot

The ribosome flow model (RFM) is a phenomenological model for the flow of particles along a 1D chain of $n$ sites. It has been extensively used to study ribosome flow along the mRNA molecule during translation. When the transition rates along the chain are time-varying and jointly $T$-periodic the RFM entrains, i.e., every trajectory of the RFM converges to

Takahiro Toizumi, Koichi Takahashi, Masato Tsukada

This paper proposes an efficient iris localization method without using iris segmentation and circle fitting. Conventional iris localization methods first extract iris regions by using semantic segmentation methods such as U-Net. Afterward, the inner and outer iris circles are localized using the traditional circle fitting algorithm. However, this approach r

Yuming Wang, Xianyong Bai, Changyong Chen, Linjie Chen

Solar Ring (SOR) is a proposed space science mission to monitor and study the Sun and inner heliosphere from a full 360{\deg} perspective in the ecliptic plane. It will deploy three 120{\deg}-separated spacecraft on the 1-AU orbit. The first spacecraft, S1, locates 30{\deg} upstream of the Earth, the second, S2, 90{\deg} downstream, and the third, S3, comple

Jian-Gang Kong, Ke-Lin Zhao, Jian Li, Qing-Xu Li

Supervised machine learning algorithms, such as graph neural networks (GNN), have successfully predicted material properties. However, the superior performance of GNN usually relies on end-to-end learning on large material datasets, which may lose the physical insight of multi-scale information about materials. And the process of labeling data consumes many

Ziyi Gong, Liang Wu, Zaichen Zhang, Jian Dang

The reconfigurable intelligent surface (RIS) has drawn considerable attention for its ability to enhance the performance of not only the wireless communication but also the indoor localization with low-cost. This paper investigates the performance limits of the RIS-based near-field localization in the asynchronous scenario, and analyzes the impact of each pa

Takato Yamazaki, Katsumasa Yoshikawa, Toshiki Kawamoto, Masaya Ohagi

This paper describes our system submitted to Dialogue Robot Competition 2022. Our proposed system is a combined model of rule-based and generation-based dialog systems. The system utilizes HyperCLOVA, a Japanese foundation model, not only to generate responses but also summarization, search information, etc. We also used our original speech recognition syste

Debarati Bhattacharya, Nidhi Tiwari, P. S. R. Krishna, Dibyendu Bhattacharyya

Thin film metallic glasses undergoing devitrification can form partially crystallized or fully crystallized materials with novel structural and magnetic properties. The development of desired and tunable properties of such systems drives the need to understand the mechanism of their thermal evolution at the atomic level. Co-sputtered amorphous Ni-Zr alloy th

Dharam Vir Ahluwalia, Cheng-Yang Lee

By exploiting the freedom in defining the dual of spinors, we report an unexpected theoretical discovery of a quantum field theory of spin-half bosons. It fulfils Dirac's 1969-70 observation that "there must be boson variables connected with electrons." The theory is local, Lorentz-invariant, and has a positive-definite Hamiltonian. We formulate the unitarit

Igor Kotelnikov

The MHD stabilization of ``rigid'' flute and ballooning modes with azimuthal number $m = 1$ in an axisymmetric mirror trap by means of a perfectly conducting lateral wall is studied both in the presence and in the absence of the end MHD anchors. Numerical calculations were carried out for an anisotropic plasma created by injection of a beam of neutral atoms

A. Del Popolo, Man Ho Chan

In this paper, we extend our previous study \cite{DelPopolo2021} on the Lemaitre-Tolman (LT) model showing how the prediction of the model changes when the equation of state parameter ($w$) of dark energy is modified. In the previous study, it was considered that dark energy was merely constituted by the cosmological constant. In this paper, as in the previo

Alain Blaustein

This work tackles the diffusive limit for the Vlasov-Poisson-Fokker-Planck model. We derive a priori estimates which hold without restriction on the phase-space dimension and propose a strong convergence result in a L2 space. Furthermore, we strengthen previous results by obtaining an explicit convergence rate arbitrarily close to the (formal) optimal rate,

Vladimir Pastukhov

In this paper we integrate isotonic regression with Stone's cross-validation-based method to estimate a distribution with a general countable support with a partial order relation defined on it. We prove that the estimator is strongly consistent for any underlying distribution, derive its rate of convergence, and in the case of one-dimensional support we obt

Lingxiao Huang, Shaofeng H. -C. Jiang, Jianing Lou, Xuan Wu

We consider robust clustering problems in $\mathbb{R}^d$, specifically $k$-clustering problems (e.g., $k$-Median and $k$-Means with $m$ outliers, where the cost for a given center set $C \subset \mathbb{R}^d$ aggregates the distances from $C$ to all but the furthest $m$ data points, instead of all points as in classical clustering. We focus on the $\epsilon$

Sebastiano Cantalupo

I describe the design and implementation of a series of university MSc courses in Switzerland and in Italy on the topic of Cosmic Structure Formation whose goal has been to provide to the students a formative experience using interwoven research practice and fundamental scientific content. The course educational framework, which is based on the ISEE Inquiry

Youjia Zhang, Soyun Choi, Sungeun Hong

Crowd counting research has made significant advancements in real-world applications, but it remains a formidable challenge in cross-modal settings. Most existing methods rely solely on the optical features of RGB images, ignoring the feasibility of other modalities such as thermal and depth images. The inherently significant differences between the differen

Zhenpeng Yao, Yanwei Lum, Andrew Johnston, Luis Martin Mejia-Mendoza

Transitioning from fossil fuels to renewable energy sources is a critical global challenge; it demands advances at the levels of materials, devices, and systems for the efficient harvesting, storage, conversion, and management of renewable energy. Researchers globally have begun incorporating machine learning (ML) techniques with the aim of accelerating thes

Haode Yan, Sihem Mesnager, Xiantong Tan

Only three classes of Almost Perfect Nonlinear (for short, APN) power functions over odd characteristic finite fields have been investigated in the literature, and their differential spectra were determined. The differential uniformity of the power function $F(x)=x^{\frac{p^{n}-3}{2}}$ over the finite field $F_{p^n}$ of order $p^n$ (where $p$ is an odd prime

Nikolaus Umlauf, Nadja Klein

Random forests are an ensemble method relevant for many problems, such as regression or classification. They are popular due to their good predictive performance (compared to, e.g., decision trees) requiring only minimal tuning of hyperparameters. They are built via aggregation of multiple regression trees during training and are usually calculated recursive

Théo Dumont, Théo Lacombe, François-Xavier Vialard

The Gromov--Wasserstein problem is a non-convex optimization problem over the polytope of transportation plans between two probability measures supported on two spaces, each equipped with a cost function evaluating similarities between points. Akin to the standard optimal transportation problem, it is natural to ask for conditions guaranteeing some structure

Vladimir Dzhunushaliev, Vladimir Folomeev

Using the Radon-Nikodym theorem concerning the relation between any two measures, as well as the methods employed in loop quantum gravity, it is shown that, in gravitation, one can quantize any measure which is not even associated with metric. We have considered the simplest case where the proportionality coefficient between two operators of measure (the Rad

Juan M. Cornejo, Michael Kinyon, Hanamantagouda P. Sankappanavar

In 1973, Katri\v{n}\'{a}k proved that regular double $p$-algebras can be regarded as (regular) double Heyting algebras by ingeniously constructing binary terms for the Heying implication and its dual in terms of pseudocomplement and its dual. In this paper we prove a converse to the Katri\v{n}\'{a}k's theorem, in the sense that in the variety RDPCH of regula

Tom Vander Aa, Tom Haber, Thomas J. Ashby, Roel Wuyts

With their widespread availability, FPGA-based accelerators cards have become an alternative to GPUs and CPUs to accelerate computing in applications with certain requirements (like energy efficiency) or properties (like fixed-point computations). In this paper we show results and experiences from mapping an industrial application used for drug discovery on

Bernhard Reinke

This paper discusses iterated monodromy groups for transcendental functions. We show that for every post-singularly finite entire transcendental function, the iterated monodromy action can be described by bounded activity automata of a special form, called "dendroid automata". In particular, we conclude that the iterated monodromy group of a post-singularly

Pavel Ludvík

We study the mappings of the first resolvable class defined by G. Koumoullis as a valuable tool to address the point of continuity property in the non-metrizable setting. First, we investigate the distance of a general mapping to the family of mappings of the first resolvable class via the \emph{fragmentability} quantity. We partially generalize papers of B.

Ulf Lindström, Özgür Sarıoğlu

We consider $f(R)$ gravity and Born-Infeld-Einstein (BIE) gravity in formulations where the metric and connection are treated independently and integrate out the metric to find the corresponding models solely in terms of the connection, the archetypical treatment being that of Eddington-Schr\"odinger (ES) duality between cosmological Einstein and Eddington t

Jongjin Kim, Hyunsik Jeon, Jaeri Lee, U Kang

When recommending personalized top-$k$ items to users, how can we recommend the items diversely to them while satisfying their needs? Aggregately diversified recommender systems aim to recommend a variety of items across whole users without sacrificing the recommendation accuracy. They increase the exposure opportunities of various items, which in turn incre

Bernard Bercu, Michel Bonnefont, Adrien Richou

The goal of this paper is to go further in the analysis of the behavior of the number of descents in a random permutation. Via two different approaches relying on a suitable martingale decomposition or on the Irwin-Hall distribution, we prove that the number of descents satisfies a sharp large deviation principle. A very precise concentration inequality invo

Jagdish Chandra Vyas, Alice-Agnes Gabriel, Thomas Ulrich, Paul Martin Mai

Frictional heat during earthquake rupture raises the pressure of fault zone fluids and affects the rupture process and its seismic radiation. Here, we investigate the role of two key parameters governing thermal-pressurization of pore fluids -- hydraulic diffusivity and shear-zone half-width -- on earthquake rupture dynamics, kinematic source properties and

Peiwei Yu, Xingyu Guo

We derive the relativistic quantum kinetic equation for massless fermions with vector and axial vector interaction using the Wigner function formalism. The vector and axial vector currents are self-consistently treated with corresponding constraint equations. The kinetic equations are derived and the condition for equilibrium is discussed up to the first ord

Haitao Huang, Qinqin Yang, Jiechao Wang, Pujie Zhang

Objective: Bloch simulation constitutes an essential part of magnetic resonance imaging (MRI) development. However, even with the graphics processing unit (GPU) acceleration, the heavy computational load remains a major challenge, especially in large-scale, high-accuracy simulation scenarios. This work aims to develop a deep learning-based simulator to accel

Mengmeng Jing, Xiantong Zhen, Jingjing Li, Cees G. M. Snoek

We aim for source-free domain adaptation, where the task is to deploy a model pre-trained on source domains to target domains. The challenges stem from the distribution shift from the source to the target domain, coupled with the unavailability of any source data and labeled target data for optimization. Rather than fine-tuning the model by updating the para

Shaurya Kaushal, Sauro Succi, Santosh Ansumali

We revisit force evaluation methodologies on rigid solid particles suspended in a viscous fluid and simulated via lattice Boltzmann method (LBM). We point out the non-commutativity of streaming and collision operators in the force evaluation procedure and provide a theoretical explanation for this observation. Based on this analysis, we propose a discrete fo

David Ziemkiewicz, Karol Karpiński, Sylwia Zielińska - Raczyńska

We investigate the imaging properties of copper-based superlens surrounded by copper oxide (Cu$_2$O). A subwavelength image resolution of the order $\lambda/9$ is demonstrated theoretically and verified in numerical simulations. It is shown that the existence of excitons in Cu$_2$O influence the static and dynamical optical properties of the lens. In particu

Bowen Xing, Ivor W. Tsang

Recent graph-based models for joint multiple intent detection and slot filling have obtained promising results through modeling the guidance from the prediction of intents to the decoding of slot filling. However, existing methods (1) only model the \textit{unidirectional guidance} from intent to slot; (2) adopt \textit{homogeneous graphs} to model the inter