July 2022 arXiv papers — page 37

Xuqian Ren, Saihui Hou, Chunshui Cao, Xu Liu

Gait recognition is instrumental in crime prevention and social security, for it can be conducted at a long distance to figure out the identity of persons. However, existing datasets and methods cannot satisfactorily deal with the most challenging cloth-changing problem in practice. Specifically, the practical gait models are usually trained on automatically

Can Chen, Xi Chen, Chen Ma, Zixuan Liu

Bi-level optimization, especially the gradient-based category, has been widely used in the deep learning community including hyperparameter optimization and meta-knowledge extraction. Bi-level optimization embeds one problem within another and the gradient-based category solves the outer-level task by computing the hypergradient, which is much more efficient

Prasun Roy, Subhankar Ghosh, Saumik Bhattacharya, Umapada Pal

In computer vision, human pose synthesis and transfer deal with probabilistic image generation of a person in a previously unseen pose from an already available observation of that person. Though researchers have recently proposed several methods to achieve this task, most of these techniques derive the target pose directly from the desired target image on a

Jason Armitage, Leonardo Impett, Rico Sennrich

In a busy city street, a pedestrian surrounded by distractions can pick out a single sign if it is relevant to their route. Artificial agents in outdoor Vision-and-Language Navigation (VLN) are also confronted with detecting supervisory signal on environment features and location in inputs. To boost the prominence of relevant features in transformer-based ar

Praneeth Nemani, Satyanarayana Vollala

Semantic similarity analysis and modeling is a fundamentally acclaimed task in many pioneering applications of natural language processing today. Owing to the sensation of sequential pattern recognition, many neural networks like RNNs and LSTMs have achieved satisfactory results in semantic similarity modeling. However, these solutions are considered ineffic

Teruo Nagase, Akiko Shima

Charts are oriented labeled graphs in a disk. Any simple surface braid (2-dimensonal braid) can be described by using a chart. Also, a chart represents an oriented closed surface embedded in 4-space. In this paper, we investigate embedded surfaces in 4-space by using charts. Let $\Gamma$ be a chart, and we denote by $\Gamma_m$ the union of all the edges of l

Zahra Naderi, Seyed Pooya Shariatpanahi, Behnam Bahrak

Due to its minimal energy requirement the PoS consensus protocol has become an attractive alternative to PoW in modern cryptocurrencies. In this protocol the chance of being selected as a block proposer in each round is proportional to the current stake of any node. Thus, nodes with higher stakes will achieve more block rewards, resulting in the so-called ri

Soliman S M Aljarboa, Shah J Miah

Adopting a good health information system (HIS) is essential for providing high-quality healthcare. With rapid advances in technology in the healthcare industry in recent years, healthcare providers seek effective options to deal with numerous diseases and a growing number of patients, adopting advanced HIS such as for clinical decision support. While the cl

Shuai Shao, Markus Meister, Julijana Gjorgjieva

The efficient coding theory postulates that single cells in a neuronal population should be optimally configured to efficiently encode information about a stimulus subject to biophysical constraints. This poses the question of how multiple neurons that together represent a common stimulus should optimize their activation functions to provide the optimal stim

Chenyu Wu, Yufei Zhang

Flow topology optimization (ToOpt) based on Darcy's source term is widely used in the field of ToOpt. It has a high degree of freedom and requires no initial configuration, making it suitable for conceptual aerodynamic design. Two problems of ToOpt are addressed in this paper to apply the ToOpt method to high-Reynolds-number turbulent flow. First, the relati

Jiwoong Kim, Dongsung Bae, Kihyeon Cho, Junghwan Goh

We report the largest scale deep learning with High Performance Computing (HPC) to physics analysis with the CMS simulation data in proton-proton collisions at 13 TeV. We build a Convolutional Neural Network (CNN) model that takes low-level information as images considering the geometry of the CMS detector and use this model to discriminate \textit{R}-parity

Jonas Theiner, Ralph Ewerth

Sports field registration in broadcast videos is typically interpreted as the task of homography estimation, which provides a mapping between a planar field and the corresponding visible area of the image. In contrast to previous approaches, we consider the task as a camera calibration problem. First, we introduce a differentiable objective function that is

Triet H. M. Le

The thesis advances the field of software security by providing knowledge and automation support for software vulnerability assessment using data-driven approaches. Software vulnerability assessment provides important and multifaceted information to prevent and mitigate dangerous cyber-attacks in the wild. The key contributions include a systematisation of k

Sungha Choi, Seunghan Yang, Seokeon Choi, Sungrack Yun

This paper proposes a novel test-time adaptation strategy that adjusts the model pre-trained on the source domain using only unlabeled online data from the target domain to alleviate the performance degradation due to the distribution shift between the source and target domains. Adapting the entire model parameters using the unlabeled online data may be detr

H. Lane, M. Songvilay, R. A. Ewings, C. Stock

RbFe$^{2+}$Fe$^{3+}$F$_{6}$ is an example of an antiferromagnet with charge ordering of the octahedrally coordinated Fe$^{2+}$ and Fe$^{3+}$ ions. As well as different spin values, Fe$^{2+}$ ($S=2$) and Fe$^{3+}$ ($S={5\over2}$) possess differing orbital ground states with Fe$^{2+}$ having an orbital degeneracy with an effective orbital angular momentum of $

Jieliang Hong, Leonid Mytnik

For a Dawson-Watanabe superprocess $X$ on $\mathbb{R}^d$, it is shown in Perkins (1990) that if the underlying spatial motion belongs to a certain class of L\'evy processes that admit jumps, then with probability one the closed support of $X_t$ is the whole space for almost all $t>0$ before extinction, the so-called ``instantaneous propagation'' property. In

Hancheng Zhong, Jiawei Yang, Zhengqing Ding, Mujie Rao

Highly compact lasers with ultra-low threshold and single-mode continuous wave (CW) operation have been a long sought-after component for photonic integrated circuits (PICs). Photonic bound states in the continuum (BICs), due to their excellent ability of trapping light and enhancing light-matter interaction, have been investigated in lasing configurations c

Yan Song, Si-Yuan Cui, Yong-Qiang Wang

We numerically construct the stationary solutions of $SU(2)$ Einstein-Yang-Mills theory in four dimensional anti-de Sitter spacetime. When the $t$ component of $SU(2)$ gauge field is taken to the only nonzero component, we construct a class of counterexamples to the weak cosmic censorship conjecture in Einstein-Maxwell theory. However, including a nonzero $\

François Roumestan, Amirhossein Ghazisaeidi, Jérémie Renaudier, Luis Trigo Vidarte

Quantum key distribution (QKD) enables the establishment of secret keys between users connected via a channel vulnerable to eavesdropping, with information-theoretic security, that is, independently of the power of a malevolent party. QKD systems based on the encoding of the key information on continuous variables (CV), such as the values of the quadrature c

Emiliano Merlin, Andrea Bonchi, Diego Paris, Davide Belfiori

We present the reduced images and multi-wavelength catalog of the first JWST NIRCam extra-galactic observations from the GLASS Early Release Science Program, obtained as coordinated parallels of the NIRISS observations of the Abell 2744 cluster. Images in seven bands (F090W, F115W, F150W, F200W, F277W, F356W, F444W) have been reduced using an augmented versi

Ilgiz Murzakhanov, Gururaj Mirle Vishwanath, Vemalaiah Kasi, Garima Prashal

Algorithms that adjust the reactive power injection of converter-connected RES to minimize losses may compromise the converters' fault-ride-through capability. This can become crucial for the reliable operation of the distribution grids, as they could lose valuable resources to support grid voltage at the time they need them the most. This paper explores how

Hongbin Xu, Weitao Chen, Yang Liu, Zhipeng Zhou

Significant progress has been witnessed in learning-based Multi-view Stereo (MVS) under supervised and unsupervised settings. To combine their respective merits in accuracy and completeness, meantime reducing the demand for expensive labeled data, this paper explores the problem of learning-based MVS in a semi-supervised setting that only a tiny part of the

J. Cooke, C. Angus, K. Auchettl, J. Bally

The Keck Wide-Field Imager (KWFI) is a proposed 1-degree diameter field of view UV-sensitive optical camera for Keck prime focus. KWFI will be the most powerful optical wide-field camera in the world and the only such 8m-class camera sensitive down to ~3000 A for the foreseeable future. Twenty science cases are described for KWFI compiled largely during 2019

Xiaoming Ren, Huifeng Zhu, Liuwei Wei, Minghui Wu

Recently Convolution-augmented Transformer (Conformer) has shown promising results in Automatic Speech Recognition (ASR), outperforming the previous best published Transformer Transducer. In this work, we believe that the output information of each block in the encoder and decoder is not completely inclusive, in other words, their output information may be c

Matteo Dora, Stéphane Jaffard, David Holcman

Wavelet quantile normalization (WQN) is a nonparametric algorithm designed to efficiently remove transient artifacts from single-channel EEG in real-time clinical monitoring. Today, EEG monitoring machines suspend their output when artifacts in the signal are detected. Removing unpredictable EEG artifacts would thus allow to improve the continuity of the mon

Gia H. Ngo, Minh Nguyen, Nancy F. Chen, Mert R. Sabuncu

Neuroimaging studies are often limited by the number of subjects and cognitive processes that can be feasibly interrogated. However, a rapidly growing number of neuroscientific studies have collectively accumulated an extensive wealth of results. Digesting this growing literature and obtaining novel insights remains to be a major challenge, since existing me

Nils T. Basse

We have characterized a transition of turbulence intensity (TI) scaling for friction Reynolds numbers $Re_{\tau} \sim 10^4$ in the companion papers [Basse, N.T. Scaling of global properties of fluctuating and mean streamwise velocities in pipe flow: Characterization of a high Reynolds number transition region, Physics of Fluids, Volume 33, 065127 (2021)] and

Xinwei Sun, Xiangyu Zheng, Jim Weinstein

Causal decomposition has provided a powerful tool to analyze health disparity problems, by assessing the proportion of disparity caused by each mediator. However, most of these methods lack \emph{policy implications}, as they fail to account for all sources of disparities caused by the mediator. Besides, their estimations \emph{pre-specified} some covariates

Zhen Wang, Liu Liu, Yajing Kong, Jiaxian Guo

Online continual learning (online CL) studies the problem of learning sequential tasks from an online data stream without task boundaries, aiming to adapt to new data while alleviating catastrophic forgetting on the past tasks. This paper proposes a framework Contrastive Vision Transformer (CVT), which designs a focal contrastive learning strategy based on a

Zhong-Xue Gao, Tian-Tian Li, Han-Yu Jiang, Jun He

Calcium oscillation is an important calcium homeostasis, imbalance of which is the key mechanism of initiation and progression of many major diseases. The formation and maintenance of calcium homeostasis are closely related to the spatial distribution of calcium channels. In the current paper, a theoretical framework is established by abstracting the spatial

Quanshi Zhang, Xin Wang, Jie Ren, Xu Cheng

Although many methods have been proposed to enhance the transferability of adversarial perturbations, these methods are designed in a heuristic manner, and the essential mechanism for improving adversarial transferability is still unclear. This paper summarizes the common mechanism shared by twelve previous transferability-boosting methods in a unified view,

Emanuele Frittaion

We consider fragments of uniform reflection for formulas in the analytic hierarchy over theories of second order arithmetic. The main result is that for any second order arithmetic theory $T_0$ extending ${\sf RCA}_0$ and axiomatizable by a $\Pi^1_{k+2}$ sentence, and for any $n\geq k+1$, \[ T_0+ \mathrm{RFN}_{\varPi^1_{n+2}}(T) \ = \ T_0 + \mathrm{TI}_{\var

Yuki Miyazawa, Ryotaro Inoue, Hiroki Matsui, Gyohei Nomura

We report the realization of a Bose-Einstein condensate of europium atoms, which is a strongly dipolar species with unique properties, a highly symmetric $[\mathrm{Xe}]\ 4f^7 6s^2\ {}^8\mathrm{S}_{7/2}$ electronic ground state and a hyperfine structure. By means of evaporative cooling in a crossed optical dipole trap, we produced a condensate of ${}^{151}$Eu

Erika Cortese, Joshua Mornhinweg, Rupert Huber, Christoph Lange

The achievement of large values of the light-matter coupling in nanoengineered photonic structures can lead to multiple photonic resonances contributing to the final properties of the same hybrid polariton mode. We develop a general theory describing multi-mode light-matter coupling in systems of reduced dimensionality and we explore their novel phenomenolog

Xinyu Li

Machine sound classification has been one of the fundamental tasks of music technology. A major branch of sound classification is the classification of music genres. However, though covering most genres of music, existing music genre datasets often do not contain fine-grained labels that indicate the detailed sub-genres of music. In consideration of the cons

Pengfei Qiu, Yongqiang Lyu, Haixia Wang, Dongsheng Wang

Performance Monitor Unit (PMU) is a significant hardware module on the current processors, which counts the events launched by processor into a set of PMU counters. Ideally, the events triggered by instructions that are executed but the results are not successfully committed (transient execution) should not be recorded. However, in this study, we discover th

Jia-Qi Liu, Qian Gao, Zhen-Peng Hu

A sp2-sp3 hybrid carbon allotrope named HSH-carbon is proposed by the first-principles calculations. The structure of HSH-carbon can be regarded as a template polymerization of [1.1.1]propellane molecules in a hexagonal lattice, as well as, an AA stacking of recently reported HSH-C10 consisting of carbon trigonal bipyramids. Based on calculations, the stabil

Martin Lara, Alessandro Masat, Camilla Colombo

A popular intermediary in the theory of artificial satellites is obtained after the elimination of parallactic terms from the J2-problem Hamiltonian. The resulting quasi-Keplerian system is in turn converted into the Kepler problem by a torsion. When this reduction process is applied to unbounded orbits the solution is made of Keplerian hyperbolae. For this

Lu Xia, Ali Shojaie

Regression analysis of correlated data, where multiple correlated responses are recorded on the same unit, is ubiquitous in many scientific areas. With the advent of new technologies, in particular high-throughput omics profiling assays, such correlated data increasingly consist of large number of variables compared with the available sample size. Motivated

Tao Zhang, Wu Huang

Few-shot learning performs classification tasks and regression tasks on scarce samples. As one of the most representative few-shot learning models, Prototypical Network represents each class as sample average, or a prototype, and measures the similarity of samples and prototypes by Euclidean distance. In this paper, we propose a framework of spectral filteri

Amartya Saha

The 3D Bondi-Metzner-Sachs (BMS$_3$) algebra that is the asymptotic symmetry algebra at null infinity of the $1+2$D asymptotically flat space-time is isomorphic to the $1+1$D Carrollian conformal algebra. Building on this connection, various preexisting results in the BMS$_3$-invariant field theories are reconsidered in light of a purely Carrollian perspecti

Zihang Xu, Zhenghua Xu, Shuo Zhang, Thomas Lukasiewicz

Deep learning based semi-supervised learning (SSL) methods have achieved strong performance in medical image segmentation, which can alleviate doctors' expensive annotation by utilizing a large amount of unlabeled data. Unlike most existing semi-supervised learning methods, adversarial training based methods distinguish samples from different sources by lear

Victor Muthama Musau, Carlo Gaetan, Paolo Girardi

Clustering has received much attention in Statistics and Machine learning with the aim of developing statistical models and autonomous algorithms which are capable of acquiring information from raw data in order to perform exploratory analysis.Several techniques have been developed to cluster sampled univariate vectors only considering the average value over

Yongcheng Jing, Yining Mao, Yiding Yang, Yibing Zhan

State-of-the-art parametric and non-parametric style transfer approaches are prone to either distorted local style patterns due to global statistics alignment, or unpleasing artifacts resulting from patch mismatching. In this paper, we study a novel semi-parametric neural style transfer framework that alleviates the deficiency of both parametric and non-para

Chaozheng Wang, Yuanhang Yang, Cuiyun Gao, Yun Peng

Pre-trained models have been shown effective in many code intelligence tasks. These models are pre-trained on large-scale unlabeled corpus and then fine-tuned in downstream tasks. However, as the inputs to pre-training and downstream tasks are in different forms, it is hard to fully explore the knowledge of pre-trained models. Besides, the performance of fin

Zhong Lin Wang

In classical electrodynamics, by motion for either the observer or the media, it always naturally assumed that the relative moving velocity is a constant along a straight line (e.g., in inertia reference frame), so that the electromagnetic behavior of charged particles in vacuum space can be easily described using special relativity. However, for engineering

Yifan Li, Haomiao Sun, Zhaori Liu, Hu Han

Affective behaviour analysis has aroused researchers' attention due to its broad applications. However, it is labor exhaustive to obtain accurate annotations for massive face images. Thus, we propose to utilize the prior facial information via Masked Auto-Encoder (MAE) pretrained on unlabeled face images. Furthermore, we combine MAE pretrained Vision Transfo

Zilong Li, Qi Gao, Yaping Wu, Chuang Niu

Metal implants and other high-density objects in patients introduce severe streaking artifacts in CT images, compromising image quality and diagnostic performance. Although various methods were developed for CT metal artifact reduction over the past decades, including the latest dual-domain deep networks, remaining metal artifacts are still clinically challe

Junwu Zhang, Mang Ye, Yao Yang

This paper studies a novel privacy-preserving anonymization problem for pedestrian images, which preserves personal identity information (PII) for authorized models and prevents PII from being recognized by third parties. Conventional anonymization methods unavoidably cause semantic information loss, leading to limited data utility. Besides, existing learned

Ezekiel Olayiwola Arogunjo, Olivia Nnadi, Joseph Olorunfemi Ojo

The power flow control of multi-active bridge converters requires a comprehensive steady-state analysis of the converter and the determination of conditions for zero voltage switching of all switching in the converter which result in minimum switching loss. This paper aims to model and carry out the power flow and Zero Voltage Switching (ZVS) analyses of Qua

Kazem Ardaneh, Mostafa Hassan, Benoit Morel, Remi Meyer

Second-harmonic emission at a frequency that is twice the laser frequency is an important diagnostic for nonlinear laser-plasma interaction. It is forbidden for centrosymmetric materials such as the bulk of sapphire. The symmetry, however, can be broken by dielectric discontinuities as a result of plasma generation inside a solid dielectric. In the present w

Anbang Wu, Hezi Zhang, Gushu Li, Alireza Shabani

Distributed quantum computing (DQC) is a promising approach to extending the computational power of near-term quantum devices. However, the non-local quantum communication between quantum devices is much more expensive and error-prone than the local quantum communication within each quantum device. Previous work on the DQC communication optimization focus on

Hansi Yang, Yongqi Zhang, Quanming Yao

Scoring function (SF) measures the plausibility of triplets in knowledge graphs. Different scoring functions can lead to huge differences in link prediction performances on different knowledge graphs. In this report, we describe a weird scoring function found by random search on the open graph benchmark (OGB). This scoring function, called AutoWeird, only us

Ezekiel Olayiwola Arogunjo, Joseph Olorunfemi Ojo

This paper aims at analyzing the effect of the zero dynamics of the Dual Active Bridge Isolated Bidirectional dc-dc converter (DAB) on the dynamics of the complete DAB system. It also explains its influence on controller design for the DAB system. In carrying out these analyses, the state space model of the DAB, as well as the first harmonic approximation (F

Takahiro Morishita, Massimo Stiavelli

This paper highlights initial photometric analyses of JWST NIRCam imaging data in the sightline of SMACS0723, aiming to identify galaxies at redshift $z>7$. By applying a conservative Lyman-break selection followed by photometric redshift analysis and visual inspection, we identify four F090W-dropout and two F150W-dropout sources, three of which were recentl

Haibo Shen, Yihao Luo, Xiang Cao, Liangqi Zhang

As the third generation of neural networks, spiking neural networks (SNNs) are dedicated to exploring more insightful neural mechanisms to achieve near-biological intelligence. Intuitively, biomimetic mechanisms are crucial to understanding and improving SNNs. For example, the associative long-term potentiation (ALTP) phenomenon suggests that in addition to

Abhijith Thoopul Anantharanga, Mohammad Saber Hashemi, Azadeh Sheidaei

Liquid metals (LM) are embedded in an elastomer matrix to obtain soft composites with unique thermal, dielectric, and mechanical properties. They have applications in soft robotics, biomedical engineering, and wearable electronics. By linking the structure to the properties of these materials, it is possible to perform material design rationally. Liquid-meta

Wenda Chu

We study the robust principal component analysis (RPCA) problem in a distributed setting. The goal of RPCA is to find an underlying low-rank estimation for a raw data matrix when the data matrix is subject to the corruption of gross sparse errors. Previous studies have developed RPCA algorithms that provide stable solutions with fast convergence. However, th

Bhan Lam, Kenneth Ooi, Zhen-Ting Ong, Karn N. Watcharasupat

To increase the availability and adoption of the soundscape standard, a low-cost calibration procedure for reproduction of audio stimuli over headphones was proposed as part of the global ``Soundscape Attributes Translation Project'' (SATP) for validating ISO/TS~12913-2:2018 perceived affective quality (PAQ) attribute translations. A previous preliminary stu

Jiaxin Wang, Zexia Shi, Yadi Wei, Fang-Wei Fu

Linear codes with a few weights are an important class of codes in coding theory and have attracted a lot of attention. In this paper, we present several constructions of $q$-ary linear codes with two or three weights from vectorial dual-bent functions, where $q$ is a power of an odd prime $p$. The weight distributions of the constructed $q$-ary linear codes

Cheyne Weis, Michel Fruchart, Ryo Hanai, Kyle Kawagoe

We study a class of bifurcations generically occurring in dynamical systems with non-mutual couplings ranging from models of coupled neurons to predator-prey systems and non-linear oscillators. In these bifurcations, extended attractors such as limit cycles, limit tori, and strange attractors merge and split in a similar way as fixed points in a pitchfork bi

BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson

Based on a data sample of $(448.1\pm2.9)\times10^6$ $\psi(3686)$ events collected with the BESIII detector at the BEPCII collider, the branching fraction of $\psi(3686)\rightarrow\Lambda\bar{\Lambda}\omega$ is measured to be $\rm (3.30\pm0.34(stat.)\pm0.29(syst.))\times10^{-5}$ for the first time. In addition, the $\Lambda\omega$ (or $\bar{\Lambda}\omega$) i

Devojyoti Kansabanik

Imaging the low-frequency radio Sun is an intrinsically challenging problem. Meter-wavelength solar emission spans angular scales from a few arcminutes to a few degrees. These emissions show temporal and spectral variability on a sub-second and sub-MHz scales. The brightness temperature of these emissions also varies by many orders of magnitude, which requir

Nir Shlezinger, Ivan V. Bajic

Artificial intelligence (AI) technologies, and particularly deep learning systems, are traditionally the domain of large-scale cloud servers, which have access to high computational and energy resources. Nonetheless, in Internet-of-Things (IoT) networks, the interface with the real-world is carried out using edge devices that are limited in hardware and can

Ryosuke Nakahama

Let $(G,G_1)=(G,(G^\sigma)_0)$ be a symmetric pair of holomorphic type, and we consider a pair of Hermitian symmetric spaces $D_1=G_1/K_1\subset D=G/K$, realized as bounded symmetric domains in complex vector spaces ${\mathfrak p}^+_1:=({\mathfrak p}^+)^\sigma\subset{\mathfrak p}^+$ respectively. Then the universal covering group $\widetilde{G}$ of $G$ acts

Hamza Reza Pavel, Abhishek Santra, Sharma Chakravarthy

Centrality measures for simple graphs are well-defined and several main-memory algorithms exist for each. Simple graphs are not adequate for modeling complex data sets with multiple entities and relationships. Multilayer networks (MLNs) have been shown to be better suited, but there are very few algorithms for centrality computation directly on MLNs. They ar

Hamza Reza Pavel, Abhishek Santra, Sharma Chakravarthy

Centrality measures for simple graphs/networks are well-defined and each has numerous main-memory algorithms. However, for modeling complex data sets with multiple types of entities and relationships, simple graphs are not ideal. Multilayer networks (or MLNs) have been proposed for modeling them and have been shown to be better suited in many ways. Since the

Zhiwu Qing, Shiwei Zhang, Ziyuan Huang, Xiang Wang

Standard approaches for video recognition usually operate on the full input videos, which is inefficient due to the widely present spatio-temporal redundancy in videos. Recent progress in masked video modelling, i.e., VideoMAE, has shown the ability of vanilla Vision Transformers (ViT) to complement spatio-temporal contexts given only limited visual contents

Haibo Shen, Yihao Luo, Xiang Cao, Liangqi Zhang

Neuromorphic vision sensors (event cameras) are inherently suitable for spiking neural networks (SNNs) and provide novel neuromorphic vision data for this biomimetic model. Due to the spatiotemporal characteristics, novel data augmentations are required to process the unconventional visual signals of these cameras. In this paper, we propose a novel Event Spa

Wenlei Chen, Patrick L. Kelly, Tommaso Treu, Xin Wang

We report the discovery of an extremely magnified star at redshift $z=2.65$ in James Webb Space Telescope (JWST) NIRISS pre-imaging of the Abell 2744 galaxy-cluster field. The star's background host galaxy lies on a fold caustic of the foreground lens, and the cluster creates a pair of images of the region close to the lensed star. We identified the bright t

Hongyin Chen, Yuxuan Lu, Yukun Cheng

With the development of blockchain applications, the requirements for file storage in blockchain are increasing rapidly. Many protocols, including Filecoin, Arweave, and Sia, have been proposed to provide scalable decentralized file storage for blockchain applications. However, the reliability is not well promised by existing protocols. Inspired by the idea

Rahul Vaze, Jayakrishnan Nair

A two-sided matching system is considered, where servers are assumed to arrive at a fixed rate, while the arrival rate of customers is modulated via a price-control mechanism. We analyse a loss model, wherein customers who are not served immediately upon arrival get blocked, as well as a queueing model, wherein customers wait in a queue until they receive se

Wonjin Jang, Jehyun Kim, Jaemin Park, Gyeonghun Kim

Multielectron semiconductor quantum dots (QDs) provide a novel platform to study the role of Coulomb correlations in finite quantum systems and their impact on many-body energy spectra. An example is the formation of interaction-driven, spatially localized electron states of Wigner molecules (WMs). Although Wigner molecularization has been confirmed by real-

Moirangthem Biken Singh, Ajay Pratap

This paper proposes Federated Learning (FL) based smart healthcare system where Medical Centers (MCs) train the local model using the data collected from patients and send the model weights to the miners in a blockchain-based robust framework without sharing raw data, keeping privacy preservation into deliberation. We formulate an optimization problem by max

George A. Elliott, Yasuhiko Sato

In order to realize all possible KMS-bundles on the Jiang-Su algebra, we introduce a class of C*-algebras which we call rationally approximately finite dimensional (RAF). Using these, we show that for a given proper simplex bundle $(S, \pi)$ with a singleton ${\pi}^{-1}(\{0\})$ and a unital separable monotracial C*-algebra $A$ absorbing the Jiang-Su algebra

Teng Sun, Wenjie Wang, Liqiang Jing, Yiran Cui

Existing studies on multimodal sentiment analysis heavily rely on textual modality and unavoidably induce the spurious correlations between textual words and sentiment labels. This greatly hinders the model generalization ability. To address this problem, we define the task of out-of-distribution (OOD) multimodal sentiment analysis. This task aims to estimat

Haiquan Wang, Menghao Su, Ran Zhao, Xiaobin Xu

Due to the rapid increase of air cargo and postal transport volume, an efficient automated multi-dimensional warehouse with elevating transfer vehicles (ETVs) should be established and an effective scheduling strategy should be designed for improving the cargo handling efficiency. In this paper, artificial bee colony algorithm, which possesses strong global

Filip Najman, Petar Orlić

In this paper we determine the $\mathbb Q$-gonalities of the modular curves $X_0(N)$ for all $N<145$. We determine the $\mathbb C$-gonality of many of these curves and the $\mathbb Q$-gonalities and $\mathbb C$-gonalities for many larger values of $N$. Using these results and some further work, we determine all the modular curves $X_0(N)$ of gonality $4$, $5

Zheng Tong, Tao Ma, Ju Huyan, Weiguang Zhang

Pavement damage segmentation has benefited enormously from deep learning. % and large-scale datasets. However, few current public datasets limit the potential exploration of deep learning in the application of pavement damage segmentation. To address this problem, this study has proposed Pavementscapes, a large-scale dataset to develop and evaluate methods f

Prasita Mukherjee, Haoteng Yin, Susheel Suresh, Tiark Rompf

Model Checking is widely applied in verifying the correctness of complex and concurrent systems against a specification. Pure symbolic approaches while popular, still suffer from the state space explosion problem that makes them impractical for large scale systems and/or specifications. In this paper, we propose to use graph representation learning (GRL) for

Branislav Dimitrijevic, Zijia Zhong, Liuhui Zhao, Dejan Besenski

The connected vehicle data (CVD) is one of the most promising emerging mobility data that greatly increases the ability to effectively monitor transportation system performance. A commercial vehicle trajectory dataset was evaluated for market penetration and coverage to establish whether it represents a sufficient sample of the vehicle volumes across the sta

Michael Filaseta

This paper addresses the factorization of polynomials of the form $F(x) = f_{0}(x) + f_{1}(x) x^{n} + \cdots + f_{r-1}(x) x^{(r-1)n} + f_{r}(x) x^{rn}$ where $r$ is a fixed positive integer and the $f_{j}(x)$ are fixed polynomials in $\mathbb Z[x]$ for $0 \le j \le r$. We provide an efficient method for showing that for $n$ sufficiently large and reasonable

Ermal Rrapaj, Kenneth S. McElvain, Chia Cheng Chang, Yantao Wu

We study the gate-based implementation of the binary reflected Gray code (BRGC) and binary code of the unitary time evolution operator due to the Laplacian discretized on a lattice with periodic boundary conditions. We find that the resulting Trotter error is independent of system size for a fixed lattice spacing through the Baker-Campbell-Hausdorff formula.

Jan Strappa, Paola Caymes-Scutari, Germán Bianchini

Wildfires are a highly prevalent multi-causal environmental phenomenon. The impact of this phenomenon includes human losses, environmental damage and high economic costs. To mitigate these effects, several computer simulation systems have been developed in order to predict fire behavior based on a set of input parameters, also called a scenario (wind speed a

Yang Zhao, Yongan Zhang, Yonggan Fu, Xu Ouyang

This work presents the first silicon-validated dedicated EGM-to-ECG (G2C) processor, dubbed e-G2C, featuring continuous lightweight anomaly detection, event-driven coarse/precise conversion, and on-chip adaptation. e-G2C utilizes neural network (NN) based G2C conversion and integrates 1) an architecture supporting anomaly detection and coarse/precise convers

Shi-Yao Hou, Zipeng Wu, Jinfeng Zeng, Ningping Cao

Inferring a quantum system from incomplete information is a common problem in many aspects of quantum information science and applications, where the principle of maximum entropy (MaxEnt) plays an important role. The quantum state compatibility problem asks whether there exists a density matrix $\rho$ compatible with some given measurement results. Such a co

Euiyong Park

In the paper, we prove that there exists a braid group action on the extended crystal $\widehat{B}(\infty)$ of finite type. The extended crystal $\widehat{B}(\infty)$ and its braid group action are investigated from the viewpoint of crystal similarity. We then interpret the braid group action on $\widehat{B}(\infty)$ in the Hernandez-Leclerc category $\maths

Bhavya Goyal, Jean-François Lalonde, Yin Li, Mohit Gupta

Scene inference under low-light is a challenging problem due to severe noise in the captured images. One way to reduce noise is to use longer exposure during the capture. However, in the presence of motion (scene or camera motion), longer exposures lead to motion blur, resulting in loss of image information. This creates a trade-off between these two kinds o

Weihai Zhang, Liqiang Yao

This paper studies finite-time stability and instability theorems in probability sense for stochastic nonlinear systems. Firstly, a new sufficient condition is proposed to guarantee that the considered system has a global solution. Secondly, we propose improved finite-time stability and instability criteria that relax the constraints on $\mathcal {L}V$ (the

Junyuan Wang, Lin Dai, Lu Yang, Bo Bai

By moving to millimeter wave (mmWave) frequencies, base stations (BSs) will be densely deployed to provide seamless coverage in sixth generation (6G) mobile communication systems, which, unfortunately, leads to severe cell-edge problem. In addition, with massive multiple-input-multiple-output (MIMO) antenna arrays employed at BSs, the beamspace channel is sp

Ali Siahkoohi, Gabrio Rizzuti, Rafael Orozco, Felix J. Herrmann

Bayesian inference for high-dimensional inverse problems is computationally costly and requires selecting a suitable prior distribution. Amortized variational inference addresses these challenges via a neural network that approximates the posterior distribution not only for one instance of data, but a distribution of data pertaining to a specific inverse pro

Yongchao Chen, Qing-Jie Li, Alex O'Brien, Yang Yang

Ion beam plays a pivotal role in ion implantations and the fabrication of nanostructures. However, there lacks a quantitative model to describe the residual stresses associated with the ion-beam radiation. Radiation-induced residual stress/transformation strain have been mostly recognized in the hydrostatic sub strain space. Here, we use molecular dynamics (

Xian Wei, Jiajia Menga, Sujie Ma, Yanchun Li

Once the magnesium alloy was implanted in the body, it was immediately covered with plasma proteins. The coated alloy surface promoted the adsorption and growth of osteoblasts. Herein, in vitro biological reactions of the ZK60 and AZ31 magnesium alloys were analyzed with and without plasma proteins incubation. The plasma proteins adsorbed on the magnesium al

C. J. Tablada, T. L. T. da Silveira, R. J. Cintra, F. M. Bayer

In this paper, two 8-point multiplication-free DCT approximations based on the Chen's factorization are proposed and their fast algorithms are also derived. Both transformations are assessed in terms of computational cost, error energy, and coding gain. Experiments with a JPEG-like image compression scheme are performed and results are compared with competin

Yong Huang, Aderon Huang, Wei Zhu, Yanming Fang

Fine-Grained Visual Classification (FGVC) is a longstanding and fundamental problem in computer vision and pattern recognition, and underpins a diverse set of real-world applications. This paper describes our contribution at SnakeCLEF2022 with FGVC. Firstly, we design a strong multimodal backbone to utilize various meta-information to assist in fine-grained

Sergio Correia, Stephan Luck, Emil Verner

We study the impact of non-pharmaceutical interventions (NPIs) on mortality and economic activity across U.S. cities during the 1918 Flu Pandemic. The combination of fast and stringent NPIs reduced peak mortality by 50% and cumulative excess mortality by 24% to 34%. However, while the pandemic itself was associated with short-run economic disruptions, we fin

Litao Yu, Jian Zhang, Mohammed Bennamoun, Xiaojun Chang

Concrete workability measure is mostly determined based on subjective assessment of a certified assessor with visual inspections. The potential human error in measuring the workability and the resulting unnecessary adjustments for the workability is a major challenge faced by the construction industry, leading to significant costs, material waste and delay.

D. Achour, T. Tiaiba

The objective of this study is to advance the theory concerning positive summing operators. Our focus lies in examining the space of positive strongly p-summable sequences and the space of positive unconditionally p-summable sequences. We utilize these in conjunction with the Banach lattice of positive weakly p-summable sequences to present and characterize

Philippe Brax, Anne-Christine Davis, Benjamin Elder

We compute bounds on screened scalar field theories from hydrogen-like systems. New light scalar fields generically have a direct coupling to matter. Such a coupling is strongly constrained by myriad experimental measurements. However, certain theories possess a {\it screening mechanism} that allows the effects of this coupling to weaken dynamically, and to

C. S. Ng

A new model, inspired by the structure of galactic disks, for three-dimensional Bernstein-Greene-Kruskal (BGK) modes in a plasma with a uniform finite background magnetic field is presented. These modes are exact nonlinear solutions of the steady-state Vlasov equation, with an electric potential and a magnetic potential perturbation localized in all three sp