March 2023 arXiv papers — page 92

Nafiseh Nikeghbal, Amir Hossein Kargaran, Abbas Heydarnoori, Hinrich Schütze

GitHub's issue reports provide developers with valuable information that is essential to the evolution of a software development project. Contributors can use these reports to perform software engineering tasks like submitting bugs, requesting features, and collaborating on ideas. In the initial versions of issue reports, there was no standard way of using t

J-L. Le Mouël, F. Lopes, V. Courtillot, D. Gibert

In the report he submitted to the Acad\'emie des Sciences, Poisson imagined a set of concentric spheres at the origin of the Earth's magnetic field. It may come as a surprise to many that Poisson as well as Gauss both considered the magnetic field to be constant. We propose in this study to test this surprising assertion for the first time evoked by Poisson

Yining Jiao, Carlton Zdanski, Julia Kimbell, Andrew Prince

Deep implicit functions (DIFs) have emerged as a powerful paradigm for many computer vision tasks such as 3D shape reconstruction, generation, registration, completion, editing, and understanding. However, given a set of 3D shapes with associated covariates there is at present no shape representation method which allows to precisely represent the shapes whil

Khondker Fariha Hossain, Sharif Amit Kamran, Alireza Tavakkoli, George Bebis

Accurately segmenting fluid in 3D optical coherence tomography (OCT) images is critical for detecting eye diseases but remains challenging. Traditional autoencoder-based methods struggle with resolution loss and information recovery. While transformer-based models improve segmentation, they arent optimized for 3D OCT volumes, which vary by vendor and extract

Lennart Jütte, Ning Wang, Bernhard Roth

Melanoma is the most lethal type of skin cancer. Patients are vulnerable to mental health illnesses which can reduce the effectiveness of the cancer treatment and the patients adherence to drug plans. It is crucial to preserve the mental health of patients while they are receiving treatment. However, current art therapy approaches are not personal and unique

P. V. Padmanabh, E. D. Barr, S. S. Sridhar, M. R. Rugel

Galactic plane radio surveys play a key role in improving our understanding of a wide range of astrophysical phenomena. Performing such a survey using the latest interferometric telescopes produces large data rates necessitating a shift towards fully or quasi-real-time data analysis with data being stored for only the time required to process them. We presen

Yi Xie, Huaidong Zhang, Xuemiao Xu, Jianqing Zhu

Previous Knowledge Distillation based efficient image retrieval methods employs a lightweight network as the student model for fast inference. However, the lightweight student model lacks adequate representation capacity for effective knowledge imitation during the most critical early training period, causing final performance degeneration. To tackle this is

Ruikai Chen, Sihem Mesnager

Planar functions, introduced by Dembowski and Ostrom, are functions from a finite field to itself that give rise to finite projective planes. They exist, however, only for finite fields of odd characteristics. They have attracted much attention in the last decade thanks to their interest in theory and those deep and various applications in many fields. This

V. V. Zavjalov

This text contains a collection of equations useful for understanding Nuclear Magnetic Resonance (NMR) experiments in superfluid $^3$He-B. This is a part of my notebook where I try to describe some parts of this sophisticated system.

Gustavo Rezende Silva, Darko Bozhinoski, Mario Garzon Oviedo, Mariano Ramírez Montero

Self-adaptation can be used in robotics to increase system robustness and reliability. This work describes the Metacontrol method for self-adaptation in robotics. Particularly, it details how the MROS (Metacontrol for ROS Systems) framework implements and packages Metacontrol, and it demonstrate how MROS can be applied in a navigation scenario where a mobile

Xiaoming Zhang, Weizhen Meng, Ying Liu, Xuefang Dai

Electrides are a unique class of electron-rich materials where excess electrons are localized in interstitial lattice sites as anions, leading to a range of unique properties and applications. While hundreds of electrides have been discovered in recent years, magnetic electrides have received limited attention, with few investigations into their fundamental

Ciara Byers, Shubhani Jain, Stefano Moretti, Emmanuel Olaiya

We investigate the possibility of detectable 2-Higgs Doublet Model (2HDM) type-II cross-sections at the High-Luminosity phase of the Large Hadron Collider (HL-LHC) for the production of the Standard Model (SM)-like Higgs boson ($h$) in association with a single top (anti)quark over the parameter space region corresponding to the so-called `wrong-sign solutio

Patrick Hemmer, Monika Westphal, Max Schemmer, Sebastian Vetter

Recent work has proposed artificial intelligence (AI) models that can learn to decide whether to make a prediction for an instance of a task or to delegate it to a human by considering both parties' capabilities. In simulations with synthetically generated or context-independent human predictions, delegation can help improve the performance of human-AI teams

Panagiotis Tolias, Tobias Dornheim, Zhandos A. Moldabekov, Jan Vorberger

Nonlinear density response theory is revisited focusing on the harmonically perturbed finite temperature uniform electron gas. Within the non-interacting limit, brute force quantum kinetic theory calculations for the quadratic, cubic, quartic and quintic responses reveal a deep connection with the linear response. Careful analysis of the static long waveleng

Ludwig A. Hothorn, Mario Hasler

Most comparisons of treatments or doses against a control are performed by the original Dunnett single step procedure \cite{Dunnett1955} providing both adjusted p-values and simultaneous confidence intervals for differences to the control. Motivated by power arguments, unbalanced designs with higher sample size in the control are recommended. When higher var

R. Kieokaew, R. F. Pinto, E. Samara, C. Tao

Our current capability of space weather prediction in the Earth's radiation belts is limited to only an hour in advance using the real-time solar wind monitoring at the Lagrangian L1 point. To mitigate the impacts of space weather on telecommunication satellites, several frameworks were proposed to advance the lead time of the prediction. We develop a protot

Gustavo Rezende Silva, Juliane Päßler, Jeroen Zwanepol, Elvin Alberts

Once deployed in the real world, autonomous underwater vehicles (AUVs) are out of reach for human supervision yet need to take decisions to adapt to unstable and unpredictable environments. To facilitate research on self-adaptive AUVs, this paper presents SUAVE, an exemplar for two-layered system-level adaptation of AUVs, which clearly separates the applicat

Qiao Wu, Jiaqi Yang, Kun Sun, Chu'ai Zhang

3D single object tracking (SOT) is an indispensable part of automated driving. Existing approaches rely heavily on large, densely labeled datasets. However, annotating point clouds is both costly and time-consuming. Inspired by the great success of cycle tracking in unsupervised 2D SOT, we introduce the first semi-supervised approach to 3D SOT. Specifically,

Xiaoming Zhang, Tingli He, Ying Liu, Xuefang Dai

Real Chern insulators have attracted great interest, but so far, their material realization is limited to nonmagnetic crystals and to systems without spin-orbit coupling. Here, we reveal magnetic real Chern insulator (MRCI) state in a recently synthesized metal-organic framework material Co3(HITP)2. Its ground state with in-plane ferromagnetic ordering hosts

Rubén Martos

We introduce a K\"unneth class in the quantum equivariant setting inspired by the pioneer work by J. Chabert, H. Oyono-Oyono and S. Echterhoff, which allows to relate the quantum Baum-Connes property with the K\"unneth formula by generalising some key results of Chabert-Oyono-Oyono-Echterhoff to discrete quantum groups. Finally, we make the observation that

Viktor Andersson, Balázs Varga, Vincent Szolnoky, Andreas Syrén

In this work, a novel and model-based artificial neural network (ANN) training method is developed supported by optimal control theory. The method augments training labels in order to robustly guarantee training loss convergence and improve training convergence rate. Dynamic label augmentation is proposed within the framework of gradient descent training whe

Yuqian Zhao, Bing Sun, Kai Lin, Zhoujian Cao

Supermassive black holes at the center of each galaxy may be surrounded by dark matter. Such dark matter admits a spike structure and vanishes at a certain distance from the black hole. This dark matter will impact the spacetime near the black hole and the related ringing gravitational waves can show distinguished features of the black hole without dark matt

Mahshid Pournajar, Tero Mäkinen, Seyyed Ahmad Hosseini, Paolo Moretti

Quasi-brittle materials endowed with (statistically) self-similar hierarcical microstructures show distinct failure patterns that deviate from the standard scenario of damage accumulation followed by crack nucleation-and-growth. Here we study the failure of paper sheets with hierarchical slice patterns as well as non-hierarchical and unpatterned reference sa

Sangita Dutta, Prosenjit Kundu, Pitambar Khanra, Chittaranjan Hens

We propose a framework for achieving perfect synchronization in complex networks of Sakaguchi-Kuramoto oscillators in presence of higher order interactions (simplicial complexes) at a targeted point in the parameter space. It is achieved by using an analytically derived frequency set from the governing equations. The frequency set not only provides stable pe

Mingyue Zhao, Shang Zhao, Quan Quan, Li Fan

Airway segmentation, especially bronchioles segmentation, is an important but challenging task because distal bronchus are sparsely distributed and of a fine scale. Existing neural networks usually exploit sparse topology to learn the connectivity of bronchioles and inefficient shallow features to capture such high-frequency information, leading to the break

Andrey A. Dorogovtsev

In this article the construction of a stationary random knot is proposed. The corresponding smooth random curve has no self-intersections in deterministic moments of time and changes its topological type at random moments.

Jun Yu, Jichao Zhu, Wangyuan Zhu, Zhongpeng Cai

Emotional Reaction Intensity(ERI) estimation is an important task in multimodal scenarios, and has fundamental applications in medicine, safe driving and other fields. In this paper, we propose a solution to the ERI challenge of the fifth Affective Behavior Analysis in-the-wild(ABAW), a dual-branch based multi-output regression model. The spatial attention i

Run-Tian Li, Song Cheng, Yang-Yang Chen, Xi-Wen Guan

The dynamical structure factor (DSF) represents a measure of dynamical density-density correlations in a quantum many-body system. Due to the complexity of many-body correlations and quantum fluctuations in a system of an infinitely large Hilbert space, such kind of dynamical correlations often impose a big theoretical challenge. For one dimensional (1D) qua

Daniel Berwick-Evans

We construct a ${\rm KO}$-valued families index for a class of $1|1$-dimensional Euclidean field theories. This realizes a conjectured cocycle map in the Stolz--Teichner program. We further show that a bundle of spin manifolds leads to a family of partially-defined $1|1$-Euclidean field theories, yielding a cocycle refinement of the families analytic index.

Anna Scampicchio, Elena Arcari, Melanie N. Zeilinger

The effectiveness of non-parametric, kernel-based methods for function estimation comes at the price of high computational complexity, which hinders their applicability in adaptive, model-based control. Motivated by approximation techniques based on sparse spectrum Gaussian processes, we focus on models given by regularized trigonometric linear regression. T

Ziyad Benomar, Evgenii Chzhen, Nicolas Schreuder, Vianney Perchet

Consider a hiring process with candidates coming from different universities. It is easy to order candidates with the same background, yet it can be challenging to compare them otherwise. The latter case requires additional costly assessments, leading to a potentially high total cost for the hiring organization. Given an assigned budget, what would be an opt

George Kenison, Klara Nosan, Mahsa Shirmohammadi, James Worrell

Hypergeometric sequences are rational-valued sequences that satisfy first-order linear recurrence relations with polynomial coefficients; that is, a hypergeometric sequence $\langle u_n \rangle_{n=0}^{\infty}$ is one that satisfies a recurrence of the form $f(n)u_n = g(n)u_{n-1}$ where $f,g \in \mathbb{Z}[x]$. In this paper, we consider the Membership Proble

S. E. Derkachev, A. V. Ivanov, L. A. Shumilov

In the paper, we obtain an expression for a two-loop master-diagram by using the Mellin$-$Barnes transformation. In the two-dimensional case we managed to factorize the answer and write it as a bilinear combination of hypergeometric functions ${}_3F_2$.

Jayasmita Behera, Salil Bedkihal, Bijay Kumar Agarwalla, Malay Bandyopadhyay

We investigate the role of quantum coherence and higher harmonics resulting from multiple-path interference in nonlinear thermoelectricity in a two-terminal triangular triple-dot Aharonov-Bohm (AB) interferometer. We quantify the trade-off between efficiency and power in the nonlinear regime of our simple setup comprising three non-interacting quantum dots (

Audrey Bürki, Sylvain Madec

The picture-word interference paradigm (participants name target pictures while ignoring distractor words) is often used to model the planning processes involved in word production. The participants' naming times are delayed in the presence of a distractor (general interference). The size of this effect depends on the relationship between the target and dist

Aurélien Colin, Pierre Tandeo, Charles Peureux, Romain Husson

Synthetic Aperture Radar is known to be able to provide high-resolution estimates of surface wind speed. These estimates usually rely on a Geophysical Model Function (GMF) that has difficulties accounting for non-wind processes such as rain events. Convolutional neural network, on the other hand, have the capacity to use contextual information and have demon

Mingyang Song, Yang Zhang, Tunç O. Aydın, Elham Amin Mansour

Noise synthesis is a challenging low-level vision task aiming to generate realistic noise given a clean image along with the camera settings. To this end, we propose an effective generative model which utilizes clean features as guidance followed by noise injections into the network. Specifically, our generator follows a UNet-like structure with skip connect

Clara Stegehuis, Bert Zwart

We provide large deviations estimates for the upper tail of the number of triangles in scale-free inhomogeneous random graphs where the degrees have power law tails with index $-\alpha, \alpha \in (1,2)$. We show that upper tail probabilities for triangles undergo a phase transition. For $\alpha<4/3$, the upper tail is caused by many vertices of degree of or

Y. Munro, C. Sarmiento, I. Bloch, G. Bourgne

In the context of abstract argumentation, we present the benefits of considering temporality, i.e. the order in which arguments are enunciated, as well as causality. We propose a formal method to rewrite the concepts of acyclic abstract argumentation frameworks into an action language, that allows us to model the evolution of the world, and to establish caus

Peter Coppens, Panagiotis Patrinos

We consider the worst-case expectation of a permutation invariant ambiguity set of discrete distributions as a proxy-cost for data-driven expected risk minimization. For this framework, we coin the term ordered risk minimization to highlight how results from order statistics inspired the proxy-cost. Specifically, we show how such costs serve as point-wise hi

G. Sun, H. Reimerdes, C. Theiler, B. P. Duval

Numerical simulations explore the possibility to test the tightly baffled, long-legged divertor (TBLLD) concept in a future upgrade of the Tokamak \`a configuration variable (TCV). The SOLPS-ITER code package is used to compare the exhaust performance of several TBLLD configurations with existing unbaffled and baffled TCV configurations. The TBLLDs feature a

Tyler Cassidy

Estimating model parameters is a crucial step in mathematical modelling and typically involves minimizing the disagreement between model predictions and experimental data. This calibration data can change throughout a study, particularly if modelling is performed simultaneously with the calibration experiments, or during an on-going public health crisis as i

Volodymyr A. Kuznietsov, Oleh Savchuk, Roman V. Poberezhnyuk, Volodymyr Vovchenko

Molecular dynamics simulations are performed for a finite non-relativistic system of particles with Lennard-Jones potential. We study the effect of liquid-gas mixed phase on particle number fluctuations in coordinate subspace. A metastable region of the mixed phase, the so-called nucleation region, is analyzed in terms of a non-interacting cluster model. Lar

Yuhang He, Irving Fang, Yiming Li, Rushi Bhavesh Shah

We propose DeepExplorer, a simple and lightweight metric-free exploration method for topological mapping of unknown environments. It performs task and motion planning (TAMP) entirely in image feature space. The task planner is a recurrent network using the latest image observation sequence to hallucinate a feature as the next-best exploration goal. The motio

Huabin Ge, Bobo Hua, Puchun Zhou

In [12], the existence of ideal circle patterns in Euclidean or hyperbolic background geometry under the combinatorial conditions was proved using flow approaches. It remains as an open problem for the spherical case. In this paper, we introduce a combinatorial geodesic curvature flow in spherical background geometry, which is analogous to the combinatorial

Rui-Yang Ju, Chih-Chia Chen, Jen-Shiun Chiang, Yu-Shian Lin

The Transformer-based method has demonstrated remarkable performance for image super-resolution in comparison to the method based on the convolutional neural networks (CNNs). However, using the self-attention mechanism like SwinIR (Image Restoration Using Swin Transformer) to extract feature information from images needs a significant amount of computational

Hiba Arnaout, Simon Razniewski, Jeff Z. Pan

In this paper, we release data about demographic information and outliers of communities of interest. Identified from Wiki-based sources, mainly Wikidata, the data covers 7.5k communities, such as members of the White House Coronavirus Task Force, and 345k subjects, e.g., Deborah Birx. We describe the statistical inference methodology adopted to mine such da

Kyubihn Lee, Nam Yul Yu

In edge intelligence, deep learning~(DL) models are deployed at an edge device and an edge server for data processing with low latency in the Internet of Things~(IoT). In this letter, we propose a new end-to-end learning-based wireless image recognition scheme using the PyramidNet in edge intelligence. We split the PyramidNet carefully into two parts for an

Zhongwei Qiu, Yang Qiansheng, Jian Wang, Haocheng Feng

Existing methods of multi-person video 3D human Pose and Shape Estimation (PSE) typically adopt a two-stage strategy, which first detects human instances in each frame and then performs single-person PSE with temporal model. However, the global spatio-temporal context among spatial instances can not be captured. In this paper, we propose a new end-to-end mul

A. Nikolaeva, O. Hryhorchak, V. Pastukhov

The ground state of spin-$1\over 2$ fermions with contact $s$-wave inter- and $p$-wave intra-species interactions is discussed. Particularly, we formulate the mean field scheme for calculating thermodynamic properties of the system in arbitrary dimension $D<2$ and discuss in detail the phase diagram in 1D case. Except clean phases with either singlet or trip

Thomas Hillebrandt, Heiko Will, Marcel Kyas

We introduce the Membership Degree Min-Max (MD-Min-Max) localisation algorithm as a precise and simple lateration algorithm for indoor localisation. MD-Min-Max is based on the well-known Min-Max algorithm that computes a bounding box to estimate the position. MD-Min-Max uses a Membership Function (MF) based on an estimated error distribution of the distance

Gaochen Dong, Wei Chen

With the popularity of the recent Transformer-based models represented by BERT, GPT-3 and ChatGPT, there has been state-of-the-art performance in a range of natural language processing tasks. However, the massive computations, huge memory footprint, and thus high latency of Transformer-based models is an inevitable challenge for the cloud with high real-time

Wei Jiang, Hans D. Schotten

This paper focuses on multi-user downlink signal transmission in a wireless system aided by multiple reconfigurable intelligent surfaces (RISs). In such a multi-RIS, multi-user, multi-antenna scenario, determining a set of RIS phase shifts to maximize the sum throughput becomes intractable. Hence, we propose a novel scheme that can substantially simplify the

Marta Lazzaretti, Zeljko Kereta, Luca Calatroni, Claudio Estatico

We consider a stochastic gradient descent (SGD) algorithm for solving linear inverse problems (e.g., CT image reconstruction) in the Banach space framework of variable exponent Lebesgue spaces $\ell^{(p_n)}(\mathbb{R})$. Such non-standard spaces have been recently proved to be the appropriate functional framework to enforce pixel-adaptive regularisation in s

Kunyang Han, Yong Liu, Jun Hao Liew, Henghui Ding

Recent advancements in pre-trained vision-language models, such as CLIP, have enabled the segmentation of arbitrary concepts solely from textual inputs, a process commonly referred to as open-vocabulary semantic segmentation (OVS). However, existing OVS techniques confront a fundamental challenge: the trained classifier tends to overfit on the base classes o

Julien Guénolé, Vincent Taupin, Maxime Vallet, Wenbo Yu

Complex intermetallic materials known as MAX phases exhibit exceptional properties from both metals and ceramics, largely thanks to their nanolayered structure. With high-resolution scanning transmission electron microscopy supported by atomistic modelling, we reveal atomic features of a nano-twist phase in the nanolayered \MAX. The rotated hexagonal single-

Dejun Luo

The limit resonant equation of the 3D rotating Navier-Stokes equations is obtained by taking large rotation limit. This equation has a nonlinear term with restricted interactions between Fourier modes, and thus it enjoys better regularity estimates than those of the classical 3D Navier-Stokes equations. Such estimates enable us to prove uniqueness of weak so

Ahmet Burak Yıldırım, Aykut Erbaş, Luca Biancofiore

We use non-equilibrium atomistic molecular dynamics simulations of unentangled melts of linear and star polymers ($\mathrm{C_{25}H_{52}}$) to study the steady-state viscoelastic response under confinement within nanoscale hematite $\left ( \mathrm{\alpha-Fe_2O_3} \right )$ channels. We report (i) the negative (positive) first (second) normal stress differenc

Kanchanok Kannee, Raula Gaikovina Kula, Supatsara Wattanakriengkrai, Kenichi Matsumoto

Using libraries in applications has helped developers reduce the costs of reinventing already existing code. However, an increase in diverse technology stacks and third-party library usage has led developers to inevitably switch technologies and search for similar libraries implemented in the new technology. To assist with searching for these replacement lib

Volodymyr Savchuk

The real options approach is now considered an effective alternative to the corporate DCF model for a feasibility study. The current paper offers a practical methodology employing binomial trees and real options techniques for evaluating investment projects. A general computation procedure is suggested for the decision tree with two active stages of real opt

Izabela Babiarz, Roman Pasechnik, Wolfgang Schäfer, Antoni Szczurek

We propose to study the structure of the enigmatic $\chi_{c1}(3872)$ axial vector meson through its $\gamma^*_L \gamma \to \chi_{c1}(3872)$ transition form factor. We derive a light-front wave function representation of the form factor for the lowest $c \bar c$ Fock-state. We found that the reduced width of the state is well within the current experimental b

Hao Liu, Xin Li, Mingming Gong, Bing Liu

Recently, Table Structure Recognition (TSR) task, aiming at identifying table structure into machine readable formats, has received increasing interest in the community. While impressive success, most single table component-based methods can not perform well on unregularized table cases distracted by not only complicated inner structure but also exterior cap

Mohammadreza Doostmohammadian, Hamid R. Rabiee

Recent studies in network science and control have shown a meaningful relationship between the epidemic processes (e.g., COVID-19 spread) and some network properties. This paper studies how such network properties, namely clustering coefficient and centrality measures (or node influence metrics), affect the spread of viruses and the growth of epidemics over

Giulio Mazzi, Daniele Meli, Alberto Castellini, Alessandro Farinelli

Partially Observable Monte Carlo Planning (POMCP) is an efficient solver for Partially Observable Markov Decision Processes (POMDPs). It allows scaling to large state spaces by computing an approximation of the optimal policy locally and online, using a Monte Carlo Tree Search based strategy. However, POMCP suffers from sparse reward function, namely, reward

Changqing Qiu, Fusheng Jin, Yining Zhang

Recently, the explanation of neural network models has garnered considerable research attention. In computer vision, CAM (Class Activation Map)-based methods and LRP (Layer-wise Relevance Propagation) method are two common explanation methods. However, since most CAM-based methods can only generate global weights, they can only generate coarse-grained explan

Zheng Yuan, Hongyi Yuan, Chuanqi Tan, Wei Wang

Large language models have emerged abilities including chain-of-thought to answer math word problems step by step. Solving math word problems not only requires abilities to disassemble problems via chain-of-thought but also needs to calculate arithmetic expressions correctly for each step. To the best of our knowledge, there is no work to focus on evaluating

Yaosen Chen, Han Yang, Yuexin Yang, Yuegen Liu

Video photorealistic style transfer is desired to generate videos with a similar photorealistic style to the style image while maintaining temporal consistency. However, existing methods obtain stylized video sequences by performing frame-by-frame photorealistic style transfer, which is inefficient and does not ensure the temporal consistency of the stylized

Ansgar Reiners, Fei Yan, Momo Ellwarth, Hans-Günter Ludwig

Line profiles from spatially unresolved stellar observations consist of a superposition of local line profiles that result from observing the stellar atmosphere under specific viewing angles. Line profile variability caused by stellar magnetic activity or planetary transit selectively varies the weight and/or shape of profiles at individual surface positions

Tianwei Liang

We develop a theory of perfect algebraic stacks that extend our theory of perfect algebraic spaces in arXiv:2303.07672, arXiv:2303.08502 to the setting of algebraic stacks. We prove several desired properties of perfect algebraic stacks. This extends some previous results of perfect schemes and perfect algebraic spaces, including the recent one developed by

Zhihao Zhao

We study affine Grassmannians for the exceptional group of type G_2. This group can be given as automorphisms of octonion algebras (or para-octonion algebras). By using this automorphism group, we consider all maximal parahoric subgroups in G_2, and give a description of affine Grassmannians for G_2 as functors classifying suitable orders in a fixed space.

Ana Lawry Aguila, James Chapman, Andre Altmann

One of the challenges of studying common neurological disorders is disease heterogeneity including differences in causes, neuroimaging characteristics, comorbidities, or genetic variation. Normative modelling has become a popular method for studying such cohorts where the 'normal' behaviour of a physiological system is modelled and can be used at subject lev

Shangfei Wang, Jiaqiang Wu, Feiyi Zheng, Xin Li

This paper introduces our method for the Emotional Reaction Intensity (ERI) Estimation Challenge, in CVPR 2023: 5th Workshop and Competition on Affective Behavior Analysis in-the-wild (ABAW). Based on the multimodal data provided by the originazers, we extract acoustic and visual features with different pretrained models. The multimodal features are mixed to

Imant Daunhawer, Alice Bizeul, Emanuele Palumbo, Alexander Marx

Contrastive learning is a cornerstone underlying recent progress in multi-view and multimodal learning, e.g., in representation learning with image/caption pairs. While its effectiveness is not yet fully understood, a line of recent work reveals that contrastive learning can invert the data generating process and recover ground truth latent factors shared be

Wei Jiang, Hans D. Schotten

Most prior works on intelligent reflecting surface (IRS) merely consider point-to-point communications, including a single user, for ease of analysis. Nevertheless, a practical wireless system needs to accommodate multiple users simultaneously. Due to the lack of frequency-selective reflection, namely the set of phase shifts cannot be different across freque

Hui Tang, Kui Jia

Deep learning in computer vision has achieved great success with the price of large-scale labeled training data. However, exhaustive data annotation is impracticable for each task of all domains of interest, due to high labor costs and unguaranteed labeling accuracy. Besides, the uncontrollable data collection process produces non-IID training and test data,

Jia Li, Yin Chen, Xuesong Zhang, Jiantao Nie

In this paper, we present our advanced solutions to the two sub-challenges of Affective Behavior Analysis in the wild (ABAW) 2023: the Emotional Reaction Intensity (ERI) Estimation Challenge and Expression (Expr) Classification Challenge. ABAW 2023 aims to tackle the challenge of affective behavior analysis in natural contexts, with the ultimate goal of crea

Yuu Hariya

Let $B=\{ B_{t}\} _{t\ge 0}$ be a one-dimensional standard Brownian motion. As an application of a recent result of ours on exponential functionals of Brownian motion, we show in this paper that, for every fixed $t>0$, the process given by \begin{align*} B_{s}-B_{t}-\Bigl| B_{t}+\max _{0\le u\le s}B_{u}-\max _{s\le u\le t}B_{u} \Bigr| +\Bigl| \max _{0\le u\l

Andrey V. Savchenko

In this article, the results of our team for the fifth Affective Behavior Analysis in-the-wild (ABAW) competition are presented. The usage of the pre-trained convolutional networks from the EmotiEffNet family for frame-level feature extraction is studied. In particular, we propose an ensemble of a multi-layered perceptron and the LightAutoML-based classifier

Loizos Hadjiloizou, Evagoras Makridis, Themistoklis Charalambous, Kyriakos M. Deliparaschos

We present a multisensor fusion framework for the onboard real-time navigation of a quadrotor in an indoor environment. The framework integrates sensor readings from an Inertial Measurement Unit (IMU), a camera-based object detection algorithm, and an Ultra-WideBand (UWB) localisation system. Often the sensor readings are not always readily available, leadin

Silvia Bonfanti, Roberto Guerra, Rene Alvarez-Donado, Pawel Sobkowicz

High Entropy Alloys (HEAs) are designed by mixing multiple metallic species in nearly the same amount to obtain crystalline or amorphous materials with exceptional mechanical properties. Here we use molecular dynamics simulations to investigate the role of positional and compositional disorder in determining the low-frequency vibrational properties of CrMnFe

Longjun Xiang, Hao Jin, Jian Wang

The DC photocurrent can detect the topology and geometry of quantum materials without inversion symmetry. Herein, we propose that the DC shot noise (DSN), as the fluctuation of photocurrent operator, can also be a diagnostic of quantum materials. Particularly, we develop the quantum theory for DSNs in gapped systems and identify the shift and injection DSNs

Laurence Barker

A pointed $p$-group is a pointed group $P_\gamma$ such that $P$ is a $p$-group. We parameterize the pointed $p$-groups on a group algebra or on a block algebra of a group algebra. The parameterization involves $p$-subgroups and irreducible characters of centralizers of $p$-subgroups.

Ziyang Zhang, Liuwei An, Zishun Cui, Ao xu

In this paper, we present our solutions for the 5th Workshop and Competition on Affective Behavior Analysis in-the-wild (ABAW), which includes four sub-challenges of Valence-Arousal (VA) Estimation, Expression (Expr) Classification, Action Unit (AU) Detection and Emotional Reaction Intensity (ERI) Estimation. The 5th ABAW competition focuses on facial affect

Panu Lahti

We investigate a version of Alberti's rank one theorem in Ahlfors regular metric spaces, as well as a connection with quasiconformal mappings. More precisely, we give a proof of the rank one theorem that partially follows along the usual steps, but the most crucial step consists in showing for $f\in BV(X;Y)$ that at $\Vert Df\Vert^s$-a.e. $x\in X$, the mappi

Kiyu Fukui, Yasuyuki Kato, Yukitoshi Motome

The Kitaev model, which hosts a quantum spin liquid (QSL) in the ground state, was originally defined on a two-dimensional honeycomb lattice, but can be straightforwardly extended to any tricoordinate lattices in any spatial dimensions. In particular, the three-dimensional (3D) extensions are of interest as a realization of 3D QSLs, and some materials like $

B Dioum, S Srivastava, M Karpiński, G Patera

Broadband temporal modes of pulsed optical fields have been recently recognized as very promising for photonic quantum information processing and time-frequency metrology. Exploiting their full potential demands efficient and flexible tools for their manipulation. Among the tools demonstrated surprisingly the most basic, a single-mode temporal filter, is mis

Naoki Hayashi, Yoshihide Sawada

Concept bottleneck model (CBM) is a ubiquitous method that can interpret neural networks using concepts. In CBM, concepts are inserted between the output layer and the last intermediate layer as observable values. This helps in understanding the reason behind the outputs generated by the neural networks: the weights corresponding to the concepts from the las

Zheyan Jin, Shiqi Chen, Huajun Feng, Zhihai Xu

We present an image dehazing algorithm with high quality, wide application, and no data training or prior needed. We analyze the defects of the original dehazing model, and propose a new and reliable dehazing reconstruction and dehazing model based on the combination of optical scattering model and computer graphics lighting rendering model. Based on the new

Xiaoyang Lyu, Peng Dai, Zizhang Li, Dongyu Yan

Implicit neural rendering, which uses signed distance function (SDF) representation with geometric priors (such as depth or surface normal), has led to impressive progress in the surface reconstruction of large-scale scenes. However, applying this method to reconstruct a room-level scene from images may miss structures in low-intensity areas or small and thi

Hyung-Joo Moon, Chan-Byoung Chae, Mohamed-Slim Alouini

In this correspondence, we propose a diversity-achieving retroreflector-based fine tracking system for free-space optical (FSO) communications. We show that multiple retroreflectors deployed around the communication telescope at the aerial vehicle save the payload capacity and enhance the outage performance of the fine tracking system. Through the analysis o

Avirup Mukherjee, Kousshik Murali, Shivam Kumar Jha, Niloy Ganguly

Passwords are the most common mechanism for authenticating users online. However, studies have shown that users find it difficult to create and manage secure passwords. To that end, passphrases are often recommended as a usable alternative to passwords, which would potentially be easy to remember and hard to guess. However, as we show, user-chosen passphrase

Pawan Kumar, Dalton J. E. Harvie

The wetting behaviour of surfaces is important for various applications like super-hydrophobic surfaces, enhanced oil recovery, mining of metal ores and anti-icing surfaces etc. For rough surfaces, which are the rule rather than the exception, designing textured surfaces that have wetting properties tailored to suit these applications generally involves eith

Ryota Yamamuro, Kei E. I. Tanaka, Satoshi Okuzumi

Typical accretion disks around massive protostars are hot enough for water ice to sublimate. We here propose to utilize the massive protostellar disks for investigating the collisional evolution of silicate grains with no ice mantle, which is an essential process for the formation of rocky planetesimals in protoplanetary disks around lower-mass stars. We for

Klaus M. Miller, Bernd Skiera

In recent years, European regulators have debated restricting the time an online tracker can track a user to protect consumer privacy better. Despite the significance of these debates, there has been a noticeable absence of any comprehensive cost-benefit analysis. This article fills this gap on the cost side by suggesting an approach to estimate the economic

Athanassios Tzouvaras

We present a formalization of collections that Cornelius Castoriadis calls ``magmas'', especially the property which mainly characterizes them and distinguishes them from the usual cantorian sets. It is the property of their elements to {\em depend} on other elements, either in a one-way or a two-way manner, so that one cannot occur in a collection without t

Shangfei Wang, Yanan Chang, Yi Wu, Xiangyu Miao

Facial affective behavior analysis is important for human-computer interaction. 5th ABAW competition includes three challenges from Aff-Wild2 database. Three common facial affective analysis tasks are involved, i.e. valence-arousal estimation, expression classification, action unit recognition. For the three challenges, we construct three different models to

Lea Bold, Hannes Eschmann, Mario Rosenfelder, Henrik Ebel

Data-driven surrogate models of dynamical systems based on the extended dynamic mode decomposition are nowadays well-established and widespread in applications. Further, for non-holonomic systems exhibiting a multiplicative coupling between states and controls, the usage of bi-linear surrogate models has proven beneficial. However, an in-depth analysis of th

Buyang Li, Weifeng Qiu, Yupei Xie, Wenshan Yu

The weak maximum principle of the isoparametric finite element method is proved for the Poisson equation under the Dirichlet boundary condition in a (possibly concave) curvilinear polyhedral domain with edge openings smaller than $\pi$, which include smooth domains and smooth deformations of convex polyhedra. The proof relies on the analysis of a dual ellipt

Hiroshi Noguchi, Nikhil Walani, Marino Arroyo

The Bin/amphiphysin/Rvs (BAR) superfamily proteins have a crescent binding domain and bend biomembranes along the domain axis. However, their anisotropic bending rigidities and spontaneous curvatures have not been experimentally determined. Here, we estimated these values from the bound protein densities on tethered vesicles using a mean-field theory of anis

Sho Komukai, Satoshi Hattori, Bernard Rachet

In epidemiology research with cancer registry data, it is often of primary interest to make inference on cancer death, not overall survival. Since cause of death is not easy to collect or is not necessarily reliable in cancer registries, some special methodologies have been introduced and widely used by using the concepts of the relative survival ratio and t