March 2023 arXiv papers — page 80

Yuntao Wang, Zirui Cheng, Xin Yi, Yan Kong

A computer vision system using low-resolution image sensors can provide intelligent services (e.g., activity recognition) but preserve unnecessary visual privacy information from the hardware level. However, preserving visual privacy and enabling accurate machine recognition have adversarial needs on image resolution. Modeling the trade-off of privacy preser

Youming Tao, Sijia Cui, Wenlu Xu, Haofei Yin

Both Byzantine resilience and communication efficiency have attracted tremendous attention recently for their significance in edge federated learning. However, most existing algorithms may fail when dealing with real-world irregular data that behaves in a heavy-tailed manner. To address this issue, we study the stochastic convex and non-convex optimization p

Rene Marczinzik

Let $A$ be an Iwanaga-Gorenstein ring. Enomoto conjectured that a self-orthogonal $A$-module has finite projective dimension. We prove this conjecture for $A$ having the property that every indecomposable non-projective maximal Cohen-Macaulay module is periodic. This answers a question of Enomoto and shows the conjecture for monomial quiver algebras and hype

Riccardo Checchin, Michael Ruderman, Roberto Oboe

In this paper, a controller design targeting the remotely operated hydraulic drive system is presented. A two-degrees-of-freedom PID position controller is used, which is designed so that to maximize the integral action under robust constraint. A linearized model of the system plant, affected by the parameters uncertainties such as variable communication tim

Ashish Seth, Mayur Hemani, Chirag Agarwal

Large pre-trained vision-language models (VLMs) reduce the time for developing predictive models for various vision-grounded language downstream tasks by providing rich, adaptable image and text representations. However, these models suffer from societal biases owing to the skewed distribution of various identity groups in the training data. These biases man

Yiran Ye, Thai Le, Dongwon Lee

Online texts with toxic content are a clear threat to the users on social media in particular and society in general. Although many platforms have adopted various measures (e.g., machine learning-based hate-speech detection systems) to diminish their effect, toxic content writers have also attempted to evade such measures by using cleverly modified toxic wor

Chuanjiao Zong

Protein sequence design is a challenging problem in protein engineering, which aims to discover novel proteins with useful biological functions. Directed evolution is a widely-used approach for protein sequence design, which mimics the evolution cycle in a laboratory environment and conducts an iterative protocol. However, the burden of laboratory experiment

Hao Zhang, Yeo Keat Ee, Basura Fernando

Visual abductive reasoning aims to make likely explanations for visual observations. We propose a simple yet effective Region Conditioned Adaptation, a hybrid parameter-efficient fine-tuning method that equips the frozen CLIP with the ability to infer explanations from local visual cues. We encode "local hints" and "global contexts" into visual prompts of th

Sajidha P, V. Vilfred Kamalappan, Julia K. Abraham

A bijective mapping $f: V(G) \rightarrow \left\{1,2,\ldots,n\right\}$ is called a \emph{Distance Magic Labeling (DML) of $G$} if ~ ${\sum_{v \in N(u)}} f(v) $ is a constant for all $u\in V(G)$ where $G$ is a simple graph of order $n$ and $N(u)$ = $\{v\in V(G):$ $uv\in E(G)\}$. Graph $G$ is called a \emph{Distance Magic Graph (DMG)} if it has a DML, otherwise

Sreerup Raychaudhuri

Indian scientists began to work on the theoretical aspects of LHC physics from the early 1980s, at the same time when the rest of the world started taking interest in this then-futuristic topic. From this point grew a whole school of collider phenomenologists, who now form a significant fraction of the Indian high-energy physics community. This article brief

Jingyi Hou, Zhen Dong, Jiayu Zhou, Zhijie Liu

Modern time series forecasting methods, such as Transformer and its variants, have shown strong ability in sequential data modeling. To achieve high performance, they usually rely on redundant or unexplainable structures to model complex relations between variables and tune the parameters with large-scale data. Many real-world data mining tasks, however, lac

Luca Capizzi, Viktor Eisler

We consider a free-fermion chain with a conformal defect that features an extended zero mode, and study the entanglement properties in its mixed ground state. The zero-mode induced degeneracy modifies the density of states in the single-particle entanglement spectrum, which can be calculated via the full counting statistics. For a homogeneous chain, the resu

Marlis Balkenhol

We generalise the notion of the Pseudo-Laplacian on a hyperbolic Riemann surface with one cusp, that was studied by Lax and Phillips and Colin de Verdi\`ere, by considering a boundary condition of Robin type for the constant term instead of the classical Dirichlet condition. The resulting family of Pseudo-Laplacians is a holomorphic family of unbounded opera

V. Vilfred Kamalappan, Sajidha P

Let $G$ be a graph of order $n$ and $N = \{N(u_{i})\}^k_{i=1}$ be a sequence of neighbourhood(nbh)s in $G$ where $N(u)$ = $\{v\in V(G):$ $uv\in E(G)\}$. \emph{Nbh sequence graph $H$ of} $N$ in $G$ is defined as the union of all induced subgraphs of closed nbh $N[u_{i}]$ in $G$, $1 \leq i \leq k$, $k\in\mathbb{N}$. A labeling $f: V(G) \rightarrow \left\{1,2,\

Krzysztof Malarz

The site percolation problem is one of the core topics in statistical physics. Evaluation of the percolation threshold, which separates two phases (sometimes described as conducting and insulating), is useful for a range of problems from core condensed matter to interdisciplinary application of statistical physics in epidemiology or other transportation or c

Zeyu Shangguan, Mohammad Rostami

Conventional training of deep neural networks requires a large number of the annotated image which is a laborious and time-consuming task, particularly for rare objects. Few-shot object detection (FSOD) methods offer a remedy by realizing robust object detection using only a few training samples per class. An unexplored challenge for FSOD is that instances f

Tao Shu, Xinke Wang, Ruotong Wang, Chuang Chen

The continuous improvement of human-computer interaction technology makes it possible to compute emotions. In this paper, we introduce our submission to the CVPR 2023 Competition on Affective Behavior Analysis in-the-wild (ABAW). Sentiment analysis in human-computer interaction should, as far as possible Start with multiple dimensions, fill in the single imp

Junjie Ye, Xuanting Chen, Nuo Xu, Can Zu

GPT series models, such as GPT-3, CodeX, InstructGPT, ChatGPT, and so on, have gained considerable attention due to their exceptional natural language processing capabilities. However, despite the abundance of research on the difference in capabilities between GPT series models and fine-tuned models, there has been limited attention given to the evolution of

Yusuke Tsukamoto, Masahiro N. Machida, Shu-ichiro Inutsuka

We propose a new evolutionary process of protoplanetary disks "co-evolution of dust grains and protoplanetary disks", revealed by dust-gas two-fluid non-ideal magnetohydrodynamics simulations considering the growth of dust and associated changes in magnetic resistivity. We found that the dust growth significantly affects disk evolution by changing the coupli

Guojin Chen, Ziyang Yu, Hongduo Liu, Yuzhe Ma

With the feature size continuously shrinking in advanced technology nodes, mask optimization is increasingly crucial in the conventional design flow, accompanied by an explosive growth in prohibitive computational overhead in optical proximity correction (OPC) methods. Recently, inverse lithography technique (ILT) has drawn significant attention and is becom

Zhi Yin, Liang Zhao

It is well known that, under some assumptions, the limit distribution of random block matrices and their partial transposition converges to the distributions of random variables in some noncommutative probability space. Using free probability theory, we obtain the relation between the free cumulants of the corresponding random variables. As an application, w

Anton V. Proskurnikov, B. Ross Barmish

The takeoff point for this paper is the voluminous body of literature addressing recursive betting games with expected logarithmic growth of wealth being the performance criterion. Whereas almost all existing papers involve use of linear feedback, the use of nonlinear control is conspicuously absent. This is epitomized by the large subset of this literature

E. Savchenko, I. Khyzhniy, S. Uyutnov, M. Bludov

The effect of thermal treatment on relaxation phenomena in Kr matrices irradiated with a low energy electron beam has been studied. The experiments were performed employing measurements of the relaxation emissions from preliminary irradiated Kr samples - quench-condensed and annealed before exposure to an electron beam. Three emissions were monitored in corr

Zhenhang Pu, Hailong He, Licheng Luo, Qiyun Ma

Higher-order topological phases have raised widespread interest in recent years with the occurrence of the topological boundary states of dimension two or more less than that of the system bulk. The higher-order topological states have been verified in gapped phases, in a wide variety of systems, such as photonic and acoustic systems, and recently also obser

Jin Gao, Zhenyu Yu, Junda Zhang

We investigate heat kernel-based and other $p$-energy norms (1<p<\infty) on bounded and unbounded metric measure spaces, in particular, on nested fractals and their blowups. With the weak-monotonicity properties for these norms, we generalise the celebrated Bourgain-Brezis-Mironescu (BBM) type characterization for p\neq2. When there admits a heat kernel sati

Shuyin Xia, Xinyu Lin, Guan Wang, De-Gang Chen

Optimization problems aim to find the optimal solution, which is becoming increasingly complex and difficult to solve. Traditional evolutionary optimization methods always overlook the granular characteristics of solution space. In the real scenario of numerous optimizations, the solution space is typically partitioned into sub-regions characterized by varyi

Hui-hui Miao, Yuri Igorevich Ozhigov

We introduce the association-dissociation model of neutral hydrogen molecule, which is a finite-dimensional cavity quantum electrodynamics model of chemistry with two two-level artificial atoms on quantum dots placed in optical cavities, based on the Tavis-Cummings-Hubbard model. The motion of the nuclei can be represented in quantum form. Electron spin tran

Sabri Bensid

In this paper, we consider the following free boundary problem $$ (P)\left\{\begin{array}{ll} \Delta u = \lambda \phi(x)\Sum_{i=1}^n H(u-\mu_i )& \quad \mbox{ in }\ \Omega=\Omega_2\setminus \overline{\Omega}_1, \\[0.3cm]u =0 &\quad \mbox{ on } \partial \Omega_2, \\[0.3cm]u =M &\quad \mbox{ on } \partial \Omega_1. \end{array} \right. $$ The domain $\Omega$ is

Shuxin Wang, Zhichao Zheng, Yanhui Gu, Junsheng Zhou

Single-branch object detection methods use shared features for localization and classification, yet the shared features are not fit for the two different tasks simultaneously. Multi-branch object detection methods usually use different features for localization and classification separately, ignoring the relevance between different tasks. Therefore, we propo

Michaela Brchnelova, Błażej Kuźma, Fan Zhang, Barbara Perri

Computational Fluid Dynamics (CFD)-based global solar coronal simulations are slowly making their way into the space weather modeling toolchains to replace the semi-empirical methods such as the Wang-Sheeley-Arge (WSA) model. However, since they are based on CFD, if the assumptions in them are too strong, these codes might experience issues with convergence

A. Zelenski, G. Atoian, E. Beebe, S. Ikeda

The proposed polarized $^3$He$^{++}$ acceleration in RHIC and the future Electron-Ion Collider will require about $2\times10^{11}$ ions in the source pulse. A new technique had been proposed for production of high intensity polarized $^3$He$^{++}$ ion beams. It is based on ionization and accumulation of the $^3$He gas (polarized by metastability-exchange opt

Alex Gaudio, Christos Faloutsos, Asim Smailagic, Pedro Costa

Is there an initialization for deep networks that requires no learning? ExplainFix adopts two design principles: the "fixed filters" principle that all spatial filter weights of convolutional neural networks can be fixed at initialization and never learned, and the "nimbleness" principle that only few network parameters suffice. We contribute (a) visual mode

Doosung Park

In the category of log schemes, it is unclear how to define the blow-ups for non-strict closed immersions. In this article, we introduce the notion of divided log spaces. We obtain the category of divided log spaces by locally inverting log blow-ups in the category of log schemes. We show that blow-ups exist for closed immersions of log smooth divided log sp

Yuhan Li, Yishun Dou, Xuanhong Chen, Bingbing Ni

We develop a generalized 3D shape generation prior model, tailored for multiple 3D tasks including unconditional shape generation, point cloud completion, and cross-modality shape generation, etc. On one hand, to precisely capture local fine detailed shape information, a vector quantized variational autoencoder (VQ-VAE) is utilized to index local geometry fr

N. Zhao, H. Ge, L. Zhou, Z. M. Song

In this paper, we investigate the low temperature magnetic properties of the rare-earth garnet compound Nd$_3$Ga$_5$O$_{12}$ in detail by means of magnetization, specific heat and magnetocaloric effect measurements. The magnetic thermal properties along with the crystal field calculations reveal that the Nd$^{3+}$ ions form into a frustrated hyper-kagome lat

Zheng Qin, Sanping Zhou, Le Wang, Jinghai Duan

The main challenge of Multi-Object Tracking~(MOT) lies in maintaining a continuous trajectory for each target. Existing methods often learn reliable motion patterns to match the same target between adjacent frames and discriminative appearance features to re-identify the lost targets after a long period. However, the reliability of motion prediction and the

Bouthaina Slika, Fadi Dornaika, Hamid Merdji, Karim Hammoudi

To develop generic and reliable approaches for diagnosing and assessing the severity of COVID-19 from chest X-rays (CXR), a large number of well-maintained COVID-19 datasets are needed. Existing severity quantification architectures require expensive training calculations to achieve the best results. For healthcare professionals to quickly and automatically

Shonkho Shuvro, Roopa Jayaramaiah, Rangarajan Muralidharan, Digbijoy N. Nath

We demonstrate active embedded microfluidic cooling in $\beta$-Ga$_2$O$_3$. We employ a cost-effective infra-red laser etch setup to achieve controlled etching of micro-channels in 500 um thick $\beta$-Ga$_2$O$_3$ substrate. The micro-channels are about 210 um deep and 340 um wide. Resistive heating is used as proof-of-concept. At a water flow rate of 50 ml/

Vanni Noferini, Paul Van Dooren

We define a compact local Smith-McMillan form of a rational matrix $R(\lambda)$ as the diagonal matrix whose diagonal elements are the nonzero entries of a local Smith-McMillan form of $R(\lambda)$. We show that a recursive rank search procedure, applied to a block-Toeplitz matrix built on the Laurent expansion of $R(\lambda)$ around an arbitrary complex poi

Stefano Vellucci, Michela Longhi, Alessio Monti, Mirko Barbuto

The beamforming capabilities of conformal cylindrical Huygens metasurface (HMS) coatings for linear antennas are assessed. It is shown that by engineering the phase-gradient profile of the HMS, the original omnidirectional radiation pattern of the linear antenna can be shaped to form multi- or single-beam configurations. A closed-form expression for the phas

Atefe Aghaei, Mohsen Ebrahimi Moghaddam

Purpose Predicting the progression of MCI to Alzheimer's disease is an important step in reducing the progression of the disease. Therefore, many methods have been introduced for this task based on deep learning. Among these approaches, the methods based on ROIs are in a good position in terms of accuracy and complexity. In these techniques, some specific pa

Suyun Jiang, Hong Liu, Nika Salia

The Erd\H{o}s-S\'os conjecture states that the maximum number of edges in an $n$-vertex graph without a given $k$-vertex tree is at most $\frac {n(k-2)}{2}$. Despite significant interest, the conjecture remains unsolved. Recently, Caro, Patk\'os, and Tuza considered this problem for host graphs that are connected. Settling a problem posed by them, for a $k$-

Jinyin Chen, Mingjun Li, Mingjun Li, Haibin Zheng

Federated learning (FL), an effective distributed machine learning framework, implements model training and meanwhile protects local data privacy. It has been applied to a broad variety of practice areas due to its great performance and appreciable profits. Who owns the model, and how to protect the copyright has become a real problem. Intuitively, the exist

Yang Su, Hui Zhou, Yansha Deng, Mischa Dohler

Cellular-connected unmanned aerial vehicle (UAV) swarm is a promising solution for diverse applications, including cargo delivery and traffic control. However, it is still challenging to communicate with and control the UAV swarm with high reliability, low latency, and high energy efficiency. In this paper, we propose a two-phase command and control (C&C) tr

Andrea Pasquale, Stavros Efthymiou, Sergi Ramos-Calderer, Jadwiga Wilkens

In this proceedings we present Qibocal, an open-source software package for calibration and characterization of quantum processing units (QPUs) based on the Qibo framework. Qibocal is specifically designed for self-hosted QPUs and provides the groundwork to easily develop, deploy and distribute characterization and calibration routines for all levels of hard

Xiaoqi Zhao, Youwei Pang, Lihe Zhang, Huchuan Lu

In many binary segmentation tasks, most CNNs-based methods use a U-shape encoder-decoder network as their basic structure. They ignore two key problems when the encoder exchanges information with the decoder: one is the lack of interference control mechanism between them, the other is without considering the disparity of the contributions from different enco

Zhen Han, Yue Feng, Mingming Sun

Recently, end-to-end trained models for multiple-choice commonsense question answering (QA) have delivered promising results. However, such question-answering systems cannot be directly applied in real-world scenarios where answer candidates are not provided. Hence, a new benchmark challenge set for open-ended commonsense reasoning (OpenCSR) has been recentl

Andrzej Pelc

Graph exploration is one of the fundamental tasks performed by a mobile agent in a graph. An $n$-node graph has unlabeled nodes, and all ports at any node of degree $d$ are arbitrarily numbered $0,\dots, d-1$. A mobile agent, initially situated at some starting node $v$, has to visit all nodes of the graph and stop. In the absence of any initial knowledge of

Yang Li, D. Mahinda Vilathgamuwa, Daniel E. Quevedo, Chih Feng Lee

In a dynamic distribution market environment, residential prosumers with solar power generation and battery energy storage devices can flexibly interact with the power grid via power exchange. Providing a schedule of this bidirectional power dispatch can facilitate the operational planning for the grid operator and bring additional benefits to the prosumers

Pintu Bhunia

Let $A=\begin{bmatrix} A_{ij} \end{bmatrix}$ be an $n\times n$ operator matrix, where each $A_{ij}$ is a bounded linear operator on a complex Hilbert space. Among other numerical radius bounds, we show that $w(A)\leq w(\hat{A})$, where $\hat{A}=\begin{bmatrix} \hat{a}_{ij} \end{bmatrix}$ is an $n\times n$ complex matrix, with $$\hat{a}_{ij}= \begin{cases} w(

Andrzej Pelc

The task of rendezvous (also called {\em gathering}) calls for a meeting of two or more mobile entities, starting from different positions in some environment. Those entities are called mobile agents or robots, and the environment can be a network modeled as a graph or a terrain in the plane, possibly with obstacles. The rendezvous problem has been studied i

Zhongying Deng, Shujun Wang, Angelica I Aviles-Rivero, Zoe Kourtzi

Alzheimer's disease progression prediction is critical for patients with early Mild Cognitive Impairment (MCI) to enable timely intervention and improve their quality of life. While existing progression prediction techniques demonstrate potential with multimodal data, they are highly limited by their reliance on labelled data and fail to account for a key el

Chunhe Xiong, Sunho Kim, Asutosh Kumar, Zeyu Chen

In this paper, we show that the minimal quantum discord over "cross-symmetric" state extensions is an entanglement monotone. In particular, we show that the minimal Bures distance of discord over cross-symmetric extensions is equivalent to the Bures distance of entanglement. At last, we refute a long-held but unstated convention that only contractive distanc

Chen Yang, Jiahao Mai, Xuan Cao, Aaron Burberry

Microbiome research is now moving beyond the compositional analysis of microbial taxa in a sample. Increasing evidence from large human microbiome studies suggests that functional consequences of changes in the intestinal microbiome may provide more power for studying their impact on inflammation and immune responses. Although 16S rRNA analysis is one of the

Vahidin Jeleskovic, David Alexander Behrens, Wolfgang Karl Härdle

Technology adoption research aims to determine the reasons why and how individuals, corporations, and industries start using new technology. Furthermore, technology adoption itself is decomposed into underlying sub-processes which are characterized by a finite number of sequential states in order to capture its evolutionary nature. Building upon that, in thi

Ning Zhang, Francesco Nex, George Vosselman, Norman Kerle

Autonomous navigation of drones using computer vision has achieved promising performance. Nano-sized drones based on edge computing platforms are lightweight, flexible, and cheap, thus suitable for exploring narrow spaces. However, due to their extremely limited computing power and storage, vision algorithms designed for high-performance GPU platforms cannot

Bochao Huang, Pin

Autonomous vehicles must be capable of handling the occlusion of the environment to ensure safe and efficient driving. In urban environment, occlusion often arises due to other vehicles obscuring the perception of the ego vehicle. Since the occlusion condition can impact the trajectories of vehicles, the behavior of other vehicles is helpful in making infere

Aleksandr Laptev, Vladimir Bataev, Igor Gitman, Boris Ginsburg

This paper presents a framework based on Weighted Finite-State Transducers (WFST) to simplify the development of modifications for RNN-Transducer (RNN-T) loss. Existing implementations of RNN-T use CUDA-related code, which is hard to extend and debug. WFSTs are easy to construct and extend, and allow debugging through visualization. We introduce two WFST-pow

Xiaoqi Zhao, Shijie Chang, Youwei Pang, Jiaxing Yang

Static and moving objects often occur in real-life videos. Most video object segmentation methods only focus on extracting and exploiting motion cues to perceive moving objects. Once faced with the frames of static objects, the moving object predictors may predict failed results caused by uncertain motion information, such as low-quality optical flow maps. B

Julien Siems, Maximilian Schambach, Sebastian Schulze, Johannes S. Otterbach

The COVID-19 pandemic has highlighted the importance of supply chains and the role of digital management to react to dynamic changes in the environment. In this work, we focus on developing dynamic inventory ordering policies for a multi-echelon, i.e. multi-stage, supply chain. Traditional inventory optimization methods aim to determine a static reordering p

Morten Haahr Kristensen, Peter Gorm Larsen

The game of chess is well-known and widely played all over the world. However, the rules for playing it are rather complex since there are different types of pieces and the ways they are allowed to move depend upon the type of the piece. In this paper we discuss alternative paradigms that can be used for modelling the rule of the chess game using VDM++ and s

Huanbin Chi, Feng Wang, Wenting Wang, Hui Deng

Studying open clusters (OCs) is essential for a comprehensive understanding of the structure and evolution of the Milky Way. Many previous studies have systematically searched for OCs near the solar system within 1.2 kpc or 20 degrees of galactic latitude. However, few studies searched for OCs at higher galactic latitudes and deeper distances. In this study,

Sung-Hoon Lee, Doohee Cho

Surface reconstruction plays a vital role in determining the surface electronic structure and chemistry of semiconductors and metal oxides. However, it has been commonly believed that surface reconstruction does not occur in van der Waals layered materials, as they do not undergo significant bond breaking during surface formation. In this study, we present e

Emilio Acampora, Raffaele Albanese, Roberto Ambrosino, Antonio Castaldo

The Divertor Tokamak Test (DTT) facility will be equipped with in-vessel divertor coils able to locally modify the flux surfaces in the divertor region. When the first DTT divertor had not been selected, four in-vessel divertor coils were considered, with 10 turns each, fed by independent 4-quadrant SCR (thyristor) 0.5 kV - 5 kA - power supplies. This config

Alberto Artoni, Paola F. Antonietti, Roberto Corradi, Ilario Mazzieri

We propose AeroSPEED, a solver based on the Spectral Element Method (SEM) that solves the aeroacoustic Lighthill's wave equation. First, the fluid solution is computed employing a cell centered Finite Volume method. Then, AeroSPEED maps the sound source coming from the flow solution onto the acoustic grid, where finally the Lighthill's wave equation is solve

Priyanka Garg, Vinod Kumar Bhardwaj, Anirudh Pradhan

In the present work, we have analyzed the behaviors of extension of generalized Barrow holographic dark energy(`BHDE'). A ``generalized BHDE model based on the particle and the future horizon using infrared cut-off" was proposed by Nojiri et al. (2022). In this work, we have reviewed the generalized BHDE extension under the assumption of a generalized HDE cu

Rabia Iqbal, Cuipo Jiang

For the Klein group $K$ and a positive integr $k$, irreducible modules of the orbifold vertex operator algebra $L_{\widehat{\mathfrak{sl}_2}}(k,0)^{K}$ have been classified and constructed in \cite{JWa}. In this paper, we determine completely the fusion rules of $L_{\widehat{\frak{sl}_2}}(k,0)^{K}$.

Ya-yuan Hu, Shu-hang Yuan

In order to reveal the coupling effect among the chemical activity and the hydraulic seepage as well as the mechanical properties, a constitutive theoretical framework considering the chemical activity for saturated porous media is derived from the mixture theory incorporated with the chemical thermodynamics. First, to highlight the important role of porosit

Dan Ben Ami, Kobi Cohen, Qing Zhao

Federated learning (FL) is an emerging machine learning (ML) paradigm used to train models across multiple nodes (i.e., clients) holding local data sets, without explicitly exchanging the data. It has attracted a growing interest in recent years due to its advantages in terms of privacy considerations, and communication resources. In FL, selected clients tra

Wuyuan Xie, Shukang Wang, Sukun Tian, Lirong Huang

Just noticeable difference (JND) refers to the maximum visual change that human eyes cannot perceive, and it has a wide range of applications in multimedia systems. However, most existing JND approaches only focus on a single modality, and rarely consider the complementary effects of multimodal information. In this article, we investigate the JND modeling fr

Liang Yan, Shengzhong Zhang, Bisheng Li, Menglin Yang

Class imbalance in graph data presents a significant challenge for effective node classification, particularly in semi-supervised scenarios. In this work, we formally introduce the concept of geometric imbalance, which captures how message passing on class-imbalanced graphs leads to geometric ambiguity among minority-class nodes in the riemannian manifold em

Mario Raciti, Giampaolo Bella

This paper questions how to approach threat modelling in the automotive domain at both an abstract level that features no domain-specific entities such as the CAN bus and, separately, at a detailed level. It addresses such questions by contributing a systematic method that is currently affected by the analyst's subjectivity because most of its inner operatio

Miaohui Wang, Zhuowei Xu, Mai Xu, Weisi Lin

Blind image quality assessment (BIQA) aims at automatically and accurately forecasting objective scores for visual signals, which has been widely used to monitor product and service quality in low-light applications, covering smartphone photography, video surveillance, autonomous driving, etc. Recent developments in this field are dominated by unimodal solut

Nan Hu, Yike Wu, Guilin Qi, Dehai Min

Large-scale pre-trained language models (PLMs) such as BERT have recently achieved great success and become a milestone in natural language processing (NLP). It is now the consensus of the NLP community to adopt PLMs as the backbone for downstream tasks. In recent works on knowledge graph question answering (KGQA), BERT or its variants have become necessary

Carl Hase

A growing empirical literature finds that firms pass the cost of minimum wage hikes onto consumers via higher retail prices. Yet, little is known about minimum wage effects on wholesale prices and whether retailers face a wholesale cost shock in addition to the labor cost shock. I exploit the vertically disintegrated market structure of Washington state's le

Brati Mondal, Pritam Goswami, Avisek Sharma, Buddhadeb Sau

In the field of distributed system, Arbitrary Pattern Formation (APF) problem is an extensively studied problem. The purpose of APF is to design an algorithm to move a swarm of robots to a particular position on an environment (discrete or continuous) such that the swarm can form a specific but arbitrary pattern given previously to every robot as an input. I

Shiyu Tian, Hongxin Wei, Yiqun Wang, Lei Feng

Partial-label learning (PLL) is an important weakly supervised learning problem, which allows each training example to have a candidate label set instead of a single ground-truth label. Identification-based methods have been widely explored to tackle label ambiguity issues in PLL, which regard the true label as a latent variable to be identified. However, id

Fei Wang, Feng-Dong Jia, Wei-Chen Liang, Xiao-Kang Li

Based on the Rb$^+$-Rb hybrid trap, we investigate the effect of ion-atom elastic collisions on the number and temperature of the remaining atoms. We measured the remaining atomic number and temperature as a function of the wavelength and intensity of the ionization laser, and whether the ion trap was turned on. Fittings with a single exponential decay funct

Jeong Hee Hong, Wojciech Szymanski

We construct an action of the Thompson group F on a compact space built from pairs of infinite, binary rooted trees. The action arises as an F-equivariant compactification of the action of F by translations on one of its homogeneous spaces, F/H_2, corresponding to a certain subgroup H_2 of F. The representation of F on the Hilbert space l^2(F/H_2) is faithfu

Qinchun Ma, Xue-Bing Wu, Huapeng Gu, Yuhan Wen

Broadband photometric reverberation mapping (PRM) have been investigated for AGNs in recent years, but mostly on accretion disk continuum RM. Due to the small fraction of broad emission lines in the broadband, PRM for emission lines is very challenging. Here we present an ICCF-Cut method for broadband PRM to obtain the H$\alpha$ broad line lag and apply it t

Yucheng Ding, Chaoyue Niu, Fan Wu, Shaojie Tang

Many large vision models have been deployed on the cloud for real-time services. Meanwhile, fresh samples are continuously generated on the served mobile device. How to leverage the device-side samples to improve the cloud-side large model becomes a practical requirement, but falls into the dilemma of no raw sample up-link and no large model down-link. Speci

Wei-Chen Liang, Feng-Dong Jia, Fei Wang, Xi Zhang

Polyatomic cations $^{87}$Rb$_M^+$ ($M$ = 2, 3,$\ldots$) have been produced by cascade two-body ion-atom reactive collisions in the two-step CW-laser photoionization of laser-cooled $^{87}$Rb atoms and accumulated in the ion trap. Using resonant-excitation mass spectrometry and resonant excitation-assisted time-of-flight mass spectrometry, we directly observ

Haoning Dang, Qilong Zhai, Zhongshu Zhao

In this paper, we present a conforming discontinuous Galerkin (CDG) finite element method for Brinkman equations. The velocity stabilizer is removed by employing the higher degree polynomials to compute the weak gradient. The theoretical analysis shows that the CDG method is actually stable and accurate for the Brinkman equations. Optimal order error estimat

Ruofan Wu, Jiawei Qiao, Mingzhe Wu, Wen Yu

We present neural frailty machine (NFM), a powerful and flexible neural modeling framework for survival regressions. The NFM framework utilizes the classical idea of multiplicative frailty in survival analysis to capture unobserved heterogeneity among individuals, at the same time being able to leverage the strong approximation power of neural architectures

Aris Tsirigotis, George Sarantoglou, Stavros Deligiannidis, Kostas Sozos

In this work we numerically analyze a passive photonic integrated neuromorphic accelerator based on hardware-friendly optical spectrum slicing nodes. The proposed scheme can act as a fully analogue convolutional layer, preprocessing information directly in the optical domain. The proposed scheme allows the extraction of meaningful spatio-temporal features fr

K. Morawetz

Consequences of the consistent exact solution of Einstein-Cartan equation on the time dependence of Hubble parameter are discussed. The torsion leads to a space and time dependent expansion parameter which results into nontrivial windows of Hubble parameter between diverging behaviour. Only one window shows a period of decreasing followed by increasing time

K. Yu. Osipenko

The paper concerns problems of the recovery of operators from noisy information in weighted $L_q$-spaces with homogeneous weights. A number of general theorems are proved and applied to finding exact constants in multidimensional Carlson type inequalities with several weights and problems of the recovery of differential operators from a noisy Fourier transfo

Lizhi Xin, Kevin Xin, Houwen Xin

Based on Darwin's natural selection, we developed "machine scientists" to discover the laws of nature by learning from raw data. "Machine scientists" construct physical theories by applying a logic tree (state Decision Tree) and a value tree (observation Function Tree); the logical tree determines the state of the entity, and the value tree determines the ab

Senen R. Nasyrov, Giang V. Nguyen

In this paper, we focus on studying the distortion of the exterior conformal modulus of a quadrilateral of sufficiently arbitrary form under the stretching map along the abscissa axis with coefficient $H\to\infty$. By using the properties of quasiconformal transformations and taking into account some facts from the theory of elliptic integrals, we confirm th

Pengfei Wang, Zhaoxiang Zhang, Zhen Lei, Lei Zhang

The goal of domain generalization (DG) is to enhance the generalization capability of the model learned from a source domain to other unseen domains. The recently developed Sharpness-Aware Minimization (SAM) method aims to achieve this goal by minimizing the sharpness measure of the loss landscape. Though SAM and its variants have demonstrated impressive DG

Shaobo Zhang, Zengli Ba, Denghui Ning, Nianfu Zhai

Among the four fundamental forces, only gravity does not couple to particle spins according to the general theory of relativity. We test this principle by searching for an anomalous scalar coupling between the neutron spin and the Earth gravity on the ground. We develop an atomic gas comagnetometer to measure the ratio of nuclear spin-precession frequencies

Guan-Ting Lin, Qingming Tang, Chieh-Chi Kao, Viktor Rozgic

Acoustic Event Classification (AEC) has been widely used in devices such as smart speakers and mobile phones for home safety or accessibility support. As AEC models run on more and more devices with diverse computation resource constraints, it became increasingly expensive to develop models that are tuned to achieve optimal accuracy/computation trade-off for

Jemal Rogava, Zurab Vashakidze

This paper considers the Cauchy problem for the nonlinear dynamic string equation of Kirchhoff-type with time-varying coefficients. The objective of this work is to develop a time domain discretization algorithm capable of approximating a solution to this initial-boundary value problem. To this end, a symmetric three-layer semi-discrete scheme is employed wi

Ziyang Ye, Haiyang Yu, Bin Li

Heatmap-based methods play an important role in anatomical landmark detection. However, most current heatmap-based methods assume that the distributions of all landmarks are the same and the distribution of each landmark is isotropic, which may not be in line with reality. For example, the landmark on the jaw is more likely to be located along the edge and l

Merab Gogberashvili

According to the Einstein hole argument, vacuum metric solutions are equivalent only if they correspond to the same energy--momentum tensor in the source region. In this paper it is shown that singular coordinates that are used to show Schwarzschild geodesics completeness, introduce the fictive delta-like sources at the horizon. Then, metric tensors obtained

Irina Bobrova, Vladimir Sokolov

We find all non-abelian generalizations of $\text{P}_1 - \text{P}_6$ Painlev\'e systems such that the corresponding autonomous system obtained by freezing the independent variable is integrable. All these systems have isomonodromic Lax representations.

Boyan Wan, Yifei Shi, Kai Xu

Most learning-based approaches to category-level 6D pose estimation are design around normalized object coordinate space (NOCS). While being successful, NOCS-based methods become inaccurate and less robust when handling objects of a category containing significant intra-category shape variations. This is because the object coordinates induced by global and r

Yufang Cui, Anders Lindquist

In a series of fundamental papers BK Ghosh reduced the simultaneous stabilization problem to a NevanlinnaPick interpolation problem. In this paper we generalize some of these results allowing for derivative constraints. Moreover, we apply a method based on a Riccati-type matrix equation, called the Covariance Extension Equation, which provides a parameteriza

Jiayang Bai, Zhen He, Shan Yang, Jie Guo

Predicting panoramic indoor lighting from a single perspective image is a fundamental but highly ill-posed problem in computer vision and graphics. To achieve locale-aware and robust prediction, this problem can be decomposed into three sub-tasks: depth-based image warping, panorama inpainting and high-dynamic-range (HDR) reconstruction, among which the succ

Thanh Vu, Baochen Sun, Bodi Yuan, Alex Ngai

The success of data mixing augmentations in image classification tasks has been well-received. However, these techniques cannot be readily applied to object detection due to challenges such as spatial misalignment, foreground/background distinction, and plurality of instances. To tackle these issues, we first introduce a novel conceptual framework called Sup