May 2022 arXiv papers — page 127

Yiwen Xu, Liangtao Huang, Tiesong Zhao, Liqun Lin

The booming haptic data significantly improves the users'immersion during multimedia interaction. As a result, the study of Haptic,Audio-Visual Environment(HAVE)has attracted attentions of multimedia community. To realize such a system, a challenging tack is the synchronization of multiple sensorial signals that is critical to user experience. Despite of

Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan

Inverse problems and, in particular, inferring unknown or latent parameters from data are ubiquitous in engineering simulations. A predominant viewpoint in identifying unknown parameters is Bayesian inference where both prior information about the parameters and the information from the observations via likelihood evaluations are incorporated into the infere

Yu Hin Au

Let $s_d(n)$ be the number of distinct decompositions of the $d$-dimensional hypercube with $n$ rectangular regions that can be obtained via a sequence of splitting operations. We prove that the generating series $y = \sum_{n \geq 1} s_d(n)x^n$ satisfies the functional equation $x = \sum_{n\geq 1} μ_d(n)y^n$, where $μ_d(n)$ is the $d$-fold Dirichlet convolut

Asish K. Kundu, Tufan Roy, Santanu Pakhira, Ze-Bin Wu

Zintl compounds have been extensively studied for their outstanding thermoelectric properties, but their electronic structure remains largely unexplored. Here, we present a detailed investigation of the electronic structure of the isostructural thermopower materials YbMg$_2$Bi$_2$ and CaMg$_2$Bi$_2$ using angle-resolved photoemission spectroscopy (ARPES) and

Xiaojun Zhang, Weijun Cheng, Zhirui Gong, Taiyu Zheng

The giant atom system is a new paradigm in quantum optics, in which the traditional dipole approximation is not available. In this paper, we construct an artificial giant atom model by coupling a superconducting circuits to a transmission line by two coupling points. In the ultrastrong coupling regime, we show that the Lamb shift of the giant atom, which is

Victor Boussange, Sebastian Becker, Arnulf Jentzen, Benno Kuckuck

Nonlinear partial differential equations (PDEs) are used to model dynamical processes in a large number of scientific fields, ranging from finance to biology. In many applications standard local models are not sufficient to accurately account for certain non-local phenomena such as, e.g., interactions at a distance. In order to properly capture these phenome

Shashank Bhatnagar, Teresa Aruja, Vaishali Guleria

In present work we study the production of ground and excited charmonium pairs in $e^- e^+ \rightarrow Ψ(nS)+ χ_{cJ}(nP)$ for $J=0,1$ and $n=1,2$, through leading order (LO) tree-level diagrams $\sim O(α_{em} α_s)$, which proceed through exchange of a virtual photon and an internal gluon line connecting two quark lines (in the triangle quark loop part of the

Tosin Adewumi, Foteini Liwicki, Marcus Liwicki

We demonstrate, in this study, that an open-domain conversational system trained on idioms or figurative language generates more fitting responses to prompts containing idioms. Idioms are part of everyday speech in many languages, across many cultures, but they pose a great challenge for many Natural Language Processing (NLP) systems that involve tasks such

Shuming Jiao, Jiaxiang Li, Wei Huang, Zibang Zhang

Single-pixel imaging (SPI) is a novel optical imaging technique by replacing a two-dimensional pixelated sensor with a single-pixel detector and pattern illuminations. SPI have been extensively used for various tasks related to image acquisition and processing. In this work, a novel non-image-based task of playing Tic-Tac-Toe games interactively is merged in

Shu-Min Wu, Yu-Tong Cai, Wen-Jing Peng, Hao-Sheng Zeng

With the complexity of information tasks, the bipartite and tripartite entanglement can no longer meet our needs, and we need more entangled particles to process relativistic quantum information. In this paper, we study the genuine N-partite entanglement and distributed relationships for Dirac fields in the background of dilaton black holes. We present the g

Kazuki Hiroe

This note explains a construction of a Poisson manifold whose symplectic foliation describes a deformation of a moduli space of meromorphic connections with unramified irregular singularities. In particular, this deformation of the moduli space corresponds to the unfolding of irregular singularities of the meromorphic connections. This is an announcement of

Mikhail Nevskii

Let $Q_n=[0,1]^n$ be the unit cube in ${\mathbb R}^n$ and let $C(Q_n)$ be a space of continuous functions $f:Q_n\to{\mathbb R}$ with the norm $\|f\|_{C(Q_n)}:=\max_{x\in Q_n}|f(x)|.$ By $Π_1\left({\mathbb R}^n\right)$ denote a set of polynomials of degree $\leq 1$, i.e., a set of linear functions on ${\mathbb R}^n$. The interpolation projector $P:C(Q_n)\to Π

Benjamin Monnet, Christopher Madec, Valérie Vidal, Sylvain Joubaud

The rise of a single bubble confined between two vertical plates is investigated over a wide range of Reynolds numbers. In particular, we focus on the evolution of the bubble speed, aspect ratio and drag coefficient during the transition from the viscous to the inertial regime. For sufficiently large bubbles, a simple model based on power balance captures th

Prajval Kumar Murali, Cong Wang, Ravinder Dahiya, Mohsen Kaboli

Three-dimensional (3D) object recognition is crucial for intelligent autonomous agents such as autonomous vehicles and robots alike to operate effectively in unstructured environments. Most state-of-art approaches rely on relatively dense point clouds and performance drops significantly for sparse point clouds. Unsupervised domain adaption allows to minimise

Yaru Yu, Dewei Li, Dongya Zhao, Yugeng Xi

The research on sliding mode control strategy is generally based on the robust approach. The larger parameter space consideration will inevitably sacrifice part of the performance. Recently, the data-driven sliding mode control method attracts much attention and shows excellent benefits in the fact that data is introduced to compensate the controller. Nevert

Yi Liu

For any pseudo-Anosov automorphism on an orientable closed surface, an inquality is established bounding certain growth of virtual homological eigenvalues with the Weil--Petersson translation length. The new inquality fits nicely with other known inequalities due to Kojima and McShane, and due to Lê. The new quantity to be considered is the square sum of the

Mingchao Li, Kun Huang, Zetian Zhang, Xiao Ma

You can have your cake and eat it too. Microvessel segmentation in optical coherence tomography angiography (OCTA) images remains challenging. Skeleton-level segmentation shows clear topology but without diameter information, while pixel-level segmentation shows a clear caliber but low topology. To close this gap, we propose a novel label adversarial learnin

Yiqun Lin, Huifeng Yao, Zezhong Li, Guoyan Zheng

Segmentation of 3D knee MR images is important for the assessment of osteoarthritis. Like other medical data, the volume-wise labeling of knee MR images is expertise-demanded and time-consuming; hence semi-supervised learning (SSL), particularly barely-supervised learning, is highly desirable for training with insufficient labeled data. We observed that the

Andreas Athenodorou

We present recent results on the spectrum of a confining flux tube that is closed around a spatial torus as a function of its length as well as the spectrum of glueballs. The extraction of the spectra has been realized by simulating four dimensional $SU(N)$ gauge theories and performing measurements using lattice techniques. Regarding flux-tubes, we have per

Yaodong Wu, Jialiang Jiang, Jin Tang

We report dynamics of skyrmion bubbles driven by spin-transfer torque in achiral ferromagnetic nanostripes using micromagnetic simulations. In a three-dimensional uniaxial ferromagnet with a quality factor that is smaller than 1, the skyrmion bubble is forced to stay at the central nanostripe by a repulsive force from the geometry border. The coherent motion

Junghoon Kim, Seyyedali Hosseinalipour, Andrew C. Marcum, Taejoon Kim

Intelligent reflecting surfaces (IRS) consist of configurable meta-atoms, which can alter the wireless propagation environment through design of their reflection coefficients. We consider adaptive IRS control in the practical setting where (i) the IRS reflection coefficients are attained by adjusting tunable elements embedded in the meta-atoms, (ii) the IRS

Zunlei Feng, Tian Qiu, Sai Wu, Xiaotuan Jin

Deep learning has recently achieved remarkable performance in image classification tasks, which depends heavily on massive annotation. However, the classification mechanism of existing deep learning models seems to contrast to humans' recognition mechanism. With only a glance at an image of the object even unknown type, humans can quickly and precisely f

A. Shukla, S. Pandey, H. Pandey

We investigate the Li2CuSb full-Heusler alloy using the first-principles electronic structure calculations and propose the electrochemical lithiation in this alloy. Band structure calculations suggest the presence of metallic nature in this alloy contrary to half-metallic nature as predicted for most of the members of the full-Heusler alloy family. This allo

Liqun Lin, Zheng Wang, Jiachen He, Weiling Chen

In the video coding process, the perceived quality of a compressed video is evaluated by full-reference quality evaluation metrics. However, it is difficult to obtain reference videos with perfect quality. To solve this problem, it is critical to design no-reference compressed video quality assessment algorithms, which assists in measuring the quality of exp

Umair Shahzad

The increasing demand of large scale wind integration in the conventional power system brings a lot of challenges. One of them is the stability of the power system when subjected to a large disturbance, such as a fault. This paper proposes a probabilistic risk-based framework for computing a global instability index, incorporating angle, voltage, and frequen

Xinwei Fang, Radu Calinescu, Colin Paterson, Julie Wilson

Self-adaptive systems are expected to mitigate disruptions by continually adjusting their configuration and behaviour. This mitigation is often reactive. Typically, environmental or internal changes trigger a system response only after a violation of the system requirements. Despite a broad agreement that prevention is better than cure in self-adaptation, pr

Wan-Ping Nicole Chen, Yuan-chin Ivan Chang

As technology advanced, collecting data via automatic collection devices become popular, thus we commonly face data sets with lengthy variables, especially when these data sets are collected without specific research goals beforehand. It has been pointed out in the literature that the difficulty of high-dimensional classification problems is intrinsically ca

Xin Qu, Peng Xu, Rusong Li, Gang Li

The combination of density functional theory with dynamical mean-field theory (DFT+DMFT) has become a powerful first-principles approach to tackle strongly correlated materials in condensed matter physics. The wide use of this approach relies on robust and easy-to-use implementations, and its implementation in various numerical frameworks will increase its a

Alok C. Gupta, Pankaj Kushwaha, L. Carrasco, Haiguang Xu

We present the most extensive and well-sampled long-term multi-band near-infrared (NIR) temporal and spectral variability study of OJ 287, considered to be the best candidate binary supermassive black hole blazar. These observations were made between December 2007 and November 2021. The source underwent ~ 2 -- 2.5 magnitude variations in the J, H, and Ks NIR

Raffaele Soloperto, Ali Mesbah, Frank Allgöwer

In this paper, we propose a novel model predictive control (MPC) framework for output tracking that deals with partially unknown constraints. The MPC scheme optimizes over a learning and a backup trajectory. The learning trajectory aims to explore unknown and potentially unsafe areas, if and only if this might lead to a potential performance improvement. On

Thijs van Eeden, Aart Heijboer

The detection of astrophysical $ν_τ$ is an important verification of the observed flux of high-energy neutrinos. A flavour ratio of approximately $ν_{e} : ν_μ: ν_τ\approx 1 : 1 : 1$ is predicted for astrophysical neutrinos measured at Earth due to neutrino oscillations. On top of this, the $ν_τ$ offers a unique channel for neutrino astronomy due to absence o

Chao Li, Xiaojun Chen

We propose a group sparse optimization model for inpainting of a square-integrable isotropic random field on the unit sphere, where the field is represented by spherical harmonics with random complex coefficients. In the proposed optimization model, the variable is an infinite-dimensional complex vector and the objective function is a real-valued function de

Jingna Zhang, Jianfei Huang, Yifa Tang, Luis Vázquez

In this paper, a modified Euler-Maruyama (EM) method is constructed for a kind of multi-term Riemann-Liouville stochastic fractional differential equations and the strong convergence order min{1-α_m, 0.5} of the proposed method is proved with Riemann-Liouville fractional derivatives&#39; orders 0<α_1<α_2<...<α_m <1. Then, based on the sum-of-exponentials app

Tao Chen, Lei Wu, Lianping Wang, Shiyi Chen

The head-on collision of two identical droplets is investigated based on the BGK-Boltzmann equation. Gauss-Hermite quadratures with different degree of precision are used to solve the kinetic equation, so that the continuum (solution truncated at the Navier-Stokes order) and non-continuum (rarefied gas dynamics) solutions can be compared. When the kinetic eq

Zhaofeng Si, Honggang Qi, Xiaoyu Song

Convolutional neural networks are prevailing in deep learning tasks. However, they suffer from massive cost issues when working on mobile devices. Network pruning is an effective method of model compression to handle such problems. This paper presents a novel structured network pruning method with auxiliary gating structures which assigns importance marks to

João Bento Sousa, Ricardo Moreira, Vladimir Balayan, Pedro Saleiro

Concept-based explanations aims to fill the model interpretability gap for non-technical humans-in-the-loop. Previous work has focused on providing concepts for specific models (eg, neural networks) or data types (eg, images), and by either trying to extract concepts from an already trained network or training self-explainable models through multi-task learn

Kunni Lin, Jiawei Peng, Chao Xu, Feng Long Gu

The machine learning approaches are applied in the dynamical simulation of open quantum systems. The long short-term memory recurrent neural network (LSTM-RNN) models are used to simulate the long-time quantum dynamics, which are built based on the key information of the short-time evolution. We employ various hyperparameter optimization methods, including t

Akim Tsvigun, Artem Shelmanov, Gleb Kuzmin, Leonid Sanochkin

Active learning (AL) is a prominent technique for reducing the annotation effort required for training machine learning models. Deep learning offers a solution for several essential obstacles to deploying AL in practice but introduces many others. One of such problems is the excessive computational resources required to train an acquisition model and estimat

Peng Zhang, Purnima P. Balakrishnan, Christopher Eckberg, Peng Deng

The quantum anomalous Hall (QAH) effect is characterized by a dissipationless chiral edge state with a quantized Hall resistance at zero magnetic field. Manipulating the QAH state is of great importance in both the understanding of topological quantum physics and the implementation of dissipationless electronics. Here, we realized the QAH effect in the magne

Jielian Lin, Aiping Huang, Keke Zhang, Xu Wang

Versatile Video Coding (VVC) has set a new milestone in high-efficiency video coding. In the standard encoder, the $λ$-domain rate control is incorporated for its high accuracy and good Rate-Distortion (RD) performance. In this paper, we formulate this task as a Nash equilibrium problem that effectively bargains between multiple agents, {\it i.e.}, Coding Tr

Yuefeng Tsai, Yicheng Hsu, Mingsian Bai

Distortion resulting from acoustic echo suppression (AES) is a common issue in full-duplex communication. To address the distortion problem, a multi-frame minimum variance distortionless response (MFMVDR) filtering technique is proposed. The MFMVDR filter with parameter estimation which was used in speech enhancement problems is extended in this study from a

Attila Maróti, Saveliy V. Skresanov

General bounds are presented for the diameters of orbital graphs of finite affine primitive permutation groups. For example, it is proved that the orbital diameter of a finite affine primitive permutation group with a nontrivial point stabilizer $ H \leq \mathrm{GL}(V) $, where the vector space $ V $ has dimension $ d $ over the prime field, can be bounded i

Surendra Singh Rathore, Balkrishna Mehta, Pradeep Kumar, Mohammad Asfer

The modeling of flow and heat transfer in porous media systems have always been a challenge and, the extended Darcy transport models for flow and equilibrium and non-equilibrium energy models for heat transfer are being used for macro-level analysis, however, the limitations of these models are subjected to porous geometry. The forced convective flow of an i

Rishi Sharma, Shreyansh Kulshreshtha, Manas Thakur

With the advent of multi-core systems, GPUs and FPGAs, loop parallelization has become a promising way to speed-up program execution. In order to stay up with time, various performance-oriented programming languages provide a multitude of constructs to allow programmers to write parallelizable loops. Correspondingly, researchers have developed techniques to

Xiaotian Pan, Bingzhe Hou

In this article, we focus on the left (translation) actions on noncommutative compact connected Lie groups ${\rm SU}(2) \times T^n$. We define the rotation vectors of the left actions induced by the elements in the maximal tori of ${\rm SU}(2) \times T^n$, and utilize rotation vectors to give the complete topologically conjugate classifications of left actio

Tiesong Zhao, Yuhang Huang, Weize Feng, Yiwen Xu

The ever-growing multimedia traffic has underscored the importance of effective multimedia codecs. Among them, the up-to-date lossy video coding standard, Versatile Video Coding (VVC), has been attracting attentions of video coding community. However, the gain of VVC is achieved at the cost of significant encoding complexity, which brings the need to realize

Abhradeep Roy, Varsha R. Chitnis, Alok C. Gupta, Paul J. Wiita

We present a long term optical $R$ band light curve analysis of the gravitationally lensed blazar AO 0235+164 in the time span 1982 - 2019. Several methods of analysis lead to the result that there is a periodicity of ~8.13 years present in these data. In addition, each of these five major flares are apparently double-peaked, with the secondary peak followin

Keke Zhang, Tiesong Zhao, Weiling Chen, Yuzhen Niu

The image Super-Resolution (SR) technique has greatly improved the visual quality of images by enhancing their resolutions. It also calls for an efficient SR Image Quality Assessment (SR-IQA) to evaluate those algorithms or their generated images. In this paper, we focus on the SR-IQA under deep learning and propose a Structure-and-Perception-based Quality E

Yanxiang Gong, Linjie Deng, Shuai Tao, Xinchen Lu

Recently, deep learning-based methods have reached an excellent performance on License Plate (LP) detection and recognition tasks. However, it is still challenging to build a robust model for Chinese LPs since there are not enough large and representative datasets. In this work, we propose a new dataset named Chinese Road Plate Dataset (CRPD) that contains m

Yanxun Ren, Lining Jiang

In this paper, we introduce and study a new generalized inverse, called ag-Drazin inverses in a Banach algebra $\mathcal{A}$ with unit $1$. An element $a\in\mathcal{A}$ is ag-Drazin invertible if there exists $x\in\mathcal{A}$ such that $ax=xa, \, xax=x \ {\rm and} \ a-axa\in\mathcal{A}^{acc}$, where $\mathcal{A}^{acc}\triangleq\{a\in\mathcal{A}: a-λ1 \ {\rm

S. Pirzada, Saleem Khan

Let $G$ be a simple graph with order $n$ and size $m$. The quantity $M_1(G)=\displaystyle\sum_{i=1}^{n}d^2_{v_i}$ is called the first Zagreb index of $G$, where $d_{v_i}$ is the degree of vertex $v_i$, for all $i=1,2,\dots,n$. The signless Laplacian matrix of a graph $G$ is $Q(G)=D(G)+A(G)$, where $A(G)$ and $D(G)$ denote, respectively, the adjacency and the

Larissa Fernanda Ferreira, Agustín Silvio Picco, Flávia Elisa Galdino, Lindomar Jose Calumby Albuquerque

Protein corona formation and nanoparticle aggregation have been heavily discussed over the last years since the lack of fine-mapping of these two combined effects has hindered the targeted delivery evolution and the personalized nanomedicine development. We present a multi-technique approach that combines Dynamic Light and Small-Angle X-ray Scattering techni

Aaron Potechin, Aaron Zhang

In this paper, we investigate the total coefficient size of Nullstellensatz proofs. We show that Nullstellensatz proofs of the pigeonhole principle on $n$ pigeons require total coefficient size $2^{Ω(n)}$ and that there exist Nullstellensatz proofs of the ordering principle on $n$ elements with total coefficient size $2^n - n$.

Mukesh Sharma, Tulika Maitra

Magnetic phase transitions have been explored in a superlattice formed by stacking monolayers of $\rm LaTiO_{3}$ and $\rm LaVO_{3}$ alternately, using ab-initio density functional theory (DFT) and Monte-Carlo (MC) simulations. DFT derived intra-layer and inter-layer exchange interaction parameters were used for the MC simulations on a Ising spin model Hamilt

Weiling Chen, Rongfu Lin, Honggang Liao, Tiesong Zhao

The widespread image applications have greatly promoted the vision-based tasks, in which the Image Quality Assessment (IQA) technique has become an increasingly significant issue. For user enjoyment in multimedia systems, the IQA exploits image fidelity and aesthetics to characterize user experience; while for other tasks such as popular object recognition,

Vincent Le Guen

This thesis tackles the subject of spatio-temporal forecasting with deep learning. The motivating application at Electricity de France (EDF) is short-term solar energy forecasting with fisheye images. We explore two main research directions for improving deep forecasting methods by injecting external physical knowledge. The first direction concerns the role

Tsubasa Ochiai, Marc Delcroix, Tomohiro Nakatani, Shoko Araki

Beamforming is a powerful tool designed to enhance speech signals from the direction of a target source. Computing the beamforming filter requires estimating spatial covariance matrices (SCMs) of the source and noise signals. Time-frequency masks are often used to compute these SCMs. Most studies of mask-based beamforming have assumed that the sources do not

Raja Solanki, P. K. Sahoo

Statefinder diagnostic is a convenient method that can differentiate between the various dark energy models. In this article, we analyze the statefinder parameters in symmetric teleparallel cosmology. The $f(Q)$ gravity theory is an alternative theory to GR, where gravitational interactions attribute to the non-metricity scalar $Q$. In the present work, we c

Maria Victorova, Heidi Hin Ting Lau, Timothy Tin-Yan Lee, David Navarro-Alarcon

Background: Ultrasound (US) imaging for scoliosis assessment is challenging for a non-experienced operator. The robotic scanning was developed to follow a spinal curvature with deep learning and apply consistent forces to the patient&#39; back. Methods: 23 scoliosis patients were scanned with US devices both, robotically and manually. Two human raters measur

Mahdis Ghodrati

For two symmetric strips with equal and finite size and in the background of several confining geometries, we numerically calculate the critical distance between these two mixed systems where the mutual information between them drops to zero and show that this quantity could be a useful correlation measure in probing the phase structures of holographic QCD m

Lukas von Koch, Peter Moeck

A Python program for calculating the metrics necessary to perform information-theory based symmetry classifications and quantifications of transmission electron diffraction spot patterns is introduced. It is the first of its kind, in that it implements objectivity into crystallographic symmetry classifications and quantifications of approximate zone axis pat

Qunsong Zeng, Jiawei Liu, Jun Lan, Yi Gong

To support emerging applications ranging from holographic communications to extended reality, next-generation mobile wireless communication systems require ultra-fast and energy-efficient (UFEE) baseband processors. Traditional complementary metal-oxide-semiconductor (CMOS)-based baseband processors face two challenges in transistor scaling and the von Neuma

Shanqing Yu, Shihan Zhang, Jianlin Zhang, Jiajun Zhou

Entity alignment is the task of finding entities representing the same real-world object in two knowledge graphs(KGs). Cross-lingual knowledge graph entity alignment aims to discover the cross-lingual links in the multi-language KGs, which is of great significance to the NLP applications and multi-language KGs fusion. In the task of aligning cross-language k

Jianping He, Yushan Li, Lin Cai, Xinping Guan

Recent years have witnessed the fast advance of security research for networked dynamical system (NDS). Considering the latest inference attacks that enable stealthy and precise attacks into NDSs with observation-based learning, this article focuses on a new security aspect, i.e., how to protect control mechanism secrets from inference attacks, including sta

Zheng Chen, Jian Zhao, Mingyu Yang, Wengang Zhou

In this work, we are dedicated to multi-target active object tracking (AOT), where there are multiple targets as well as multiple cameras in the environment. The goal is maximize the overall target coverage of all cameras. Previous work makes a strong assumption that each camera is fixed in a location and only allowed to rotate, which limits its application.

Zijian Li, Ruichu Cai, Jiawei Chen, Yuguan Yan

Domain adaptation on time-series data is often encountered in the industry but received limited attention in academia. Most of the existing domain adaptation methods for time-series data borrow the ideas from the existing methods for non-time series data to extract the domain-invariant representation. However, two peculiar difficulties to time-series data ha

Hikaru Sasaki, Terushi Hirabayashi, Kaoru Kawabata, Takamitsu Matsubara

The environments of such large industrial machines as waste cranes in waste incineration plants are often weakly observable, where little information about the environmental state is contained in the observations due to technical difficulty or maintenance cost (e.g., no sensors for observing the state of the garbage to be handled). Based on the findings that

Ayon Ganguly, Debanjan Mitra, Debasis Kundu

Under adaptive progressive Type-II censoring schemes, order restricted inference based on competing risks data is discussed in this article. The latent failure lifetimes for the competing causes are assumed to follow Weibull distributions, with an order restriction on the scale parameters of the distributions. The practical implication of this order restrict

Yuzhu Li, Tairan Liu, Hatice Ceylan Koydemir, Hongda Wang

Early detection and identification of pathogenic bacteria such as Escherichia coli (E. coli) is an essential task for public health. The conventional culture-based methods for bacterial colony detection usually take >24 hours to get the final read-out. Here, we demonstrate a bacterial colony-forming-unit (CFU) detection system exploiting a thin-film-transist

Binghui Wang, Youqi Li, Pan Zhou

Graph neural networks (GNNs) have achieved state-of-the-art performance in many graph-based tasks such as node classification and graph classification. However, many recent works have demonstrated that an attacker can mislead GNN models by slightly perturbing the graph structure. Existing attacks to GNNs are either under the less practical threat model where

Shay Deutsch, Stefano Soatto

We introduce the Graph Sylvester Embedding (GSE), an unsupervised graph representation of local similarity, connectivity, and global structure. GSE uses the solution of the Sylvester equation to capture both network structure and neighborhood proximity in a single representation. Unlike embeddings based on the eigenvectors of the Laplacian, GSE incorporates

Mingyao Cui, Linglong Dai, Zhaocheng Wang, Shidong Zhou

Wideband extremely large-scale multiple-input-multiple-output (XL-MIMO) is a promising technique to achieve Tbps data rates in future 6G systems through beamforming and spatial multiplexing. Due to the extensive bandwidth and the huge number of antennas for wideband XL-MIMO, a significant near-field beam split effect will be induced, where beams at different

Ya-Li Zheng, Wen-Hui Ai

Let $ρ=(\frac{p}{q})^{\frac{1}{r}}<1$ for some $p,q,r\in\mathbb{N}$ with $(p,q)=1$ and $\mathcal{D}_{n}=\{0,1,\cdot\cdot\cdot,N_{n}-1\}$, where $N_{n}$ is prime for all $n\in\mathbb{N}$, and denote $M=\sup\{N_{n}:n=1,2,3,\ldots\}<\infty$. The associated Borel probability measure $$μ_{ρ,\{\mathcal{D}_{n}\}}=δ_{ρ\mathcal{D}_{1}}*δ_{ρ^{2}\mathcal{D}_{2}}*δ_{ρ^{

Yingrong Zhong, Yashuai Cao, Tiejun Lv

User-centric (UC) based cell-free (CF) structures can provide the benefits of coverage enhancement for millimeter wave (mmWave) multiple input multiple output (MIMO) systems, which is regarded as the key technology of the reliable and high-rate services. In this paper, we propose a new beam selection scheme and precoding algorithm for the UC CF mmWave MIMO s

Ajeet Kumar Dwivedi

The progression of innovation and technology and ease of inter-connectivity among networks has allowed us to evolve towards one of the promising areas, the Internet of Vehicles. Nowadays, modern vehicles are connected to a range of networks, including intra-vehicle networks and external networks. However, a primary challenge in the automotive industry is to

Zelin Xu, Yichen Zhang, Ke Chen, Kui Jia

The challenges of learning a robust 6D pose function lie in 1) severe occlusion and 2) systematic noises in depth images. Inspired by the success of point-pair features, the goal of this paper is to recover the 6D pose of an object instance segmented from RGB-D images by locally matching pairs of oriented points between the model and camera space. To this en

Claudio Corianò, Mario Cretì, Stefano Lionetti, Matteo Maria Maglio

The possibility of evading Lovelock&#39;s theorem at $d=4$, via a singular redefinition of the dimensionless coupling of the Gauss-Bonnet term, has been extensively discussed in the cosmological context. The term is added as a quadratic contribution of the curvature tensor to the Einstein-Hilbert action, originating theories of &#34;Einstein Gauss-Bonnet&#34

Zhipeng Zhang, Xinglin Hou, Kai Niu, Zhongzhen Huang

Recently, online shopping has gradually become a common way of shopping for people all over the world. Wonderful merchandise advertisements often attract more people to buy. These advertisements properly integrate multimodal multi-structured information of commodities, such as visual spatial information and fine-grained structure information. However, tradit

Zhenyu Liu, Zhi Ding

Accurate downlink channel state information (CSI) is vital to achieving high spectrum efficiency in massive MIMO systems. Existing works on the deep learning (DL) model for CSI feedback have shown efficient compression and recovery in frequency division duplex (FDD) systems. However, practical DL networks require sizeable wireless CSI datasets during trainin

Yashraj Narang, Kier Storey, Iretiayo Akinola, Miles Macklin

Robotic assembly is one of the oldest and most challenging applications of robotics. In other areas of robotics, such as perception and grasping, simulation has rapidly accelerated research progress, particularly when combined with modern deep learning. However, accurately, efficiently, and robustly simulating the range of contact-rich interactions in assemb

ZeGuo Wang, ShiJie Wei, Gui-Lu Long, Lajos Hanzo

We propose a variational quantum attack algorithm (VQAA) for classical AES-like symmetric cryptography, as exemplified the simplified-data encryption standard (S-DES). In the VQAA, the known ciphertext is encoded as the ground state of a Hamiltonian that is constructed through a regular graph, and the ground state can be found using a variational approach. W

Hao Deng, Zhijun Song, Ran Gao, Tian Xia

Dielectric loss is one of the major decoherence sources of superconducting qubits. Contemporary high-coherence superconducting qubits are formed by material systems mostly consisting of superconducting films on substrate with low dielectric loss, where the loss mainly originates from the surfaces and interfaces. Among the multiple candidates for material sys

Yuhan Xie, Kexin Jiang, Zhiyong Zhang, Shaolong Chen

Medical image segmentation based on deep learning is often faced with the problems of insufficient datasets and long time-consuming labeling. In this paper, we introduce the self-supervised method MAE(Masked Autoencoders) into knee joint images to provide a good initial weight for the segmentation model and improve the adaptability of the model to small data

Xiaoqian Xu, Pengxu Wei, Weikai Chen, Mingzhi Mao

Due to the sophisticated imaging process, an identical scene captured by different cameras could exhibit distinct imaging patterns, introducing distinct proficiency among the super-resolution (SR) models trained on images from different devices. In this paper, we investigate a novel and practical task coded cross-device SR, which strives to adapt a real-worl

Shih Yu Chang

In this work, we extend double tensor integrals (DTI) from our previous work to parametrization double tensors integrals (PDTI) by applying integral kernel transform bounds to upper bound PDTI norm and establishing a new perturbation formula. Besides, the convergence property of random PDTI is investigated and this property is utilized to characterize the re

Pedro F. Proença, Jeff Delaune, Roland Brockers

The next generation of Mars rotorcrafts requires on-board autonomous hazard avoidance landing. To this end, this work proposes a system that performs continuous multi-resolution height map reconstruction and safe landing spot detection. Structure-from-Motion measurements are aggregated in a pyramid structure using a novel Optimal Mixture of Gaussians formula

M. K. Gupta, Suman Sharma

Recently, we have studied the Finsler space with h-Matsumoto change and found Cartan connection for the transformed space [2]. In this paper, we have discussed certain geometrical properties of the hypersurface of a Finsler space for the h-Matsumoto change.

Jiale Zhang, Bin Chen, Sijie Yu, Hui Tian

Extreme-ultraviolet late phase (ELP) refers to the second extreme-ultraviolet (EUV) radiation enhancement observed in certain solar flares, which usually occurs tens of minutes to several hours after the peak of soft X-ray emission. The coronal loop system that hosts the ELP emission is often different from the main flaring arcade, and the enhanced EUV emiss

Mingyang Guo, Hongliang Lu, Xinxin Ma, Xiao Ma

Let $n,m$ be integers such that $1\leq m\leq (n-2)/2$ and let $[n]=\{1,\ldots,n\}$. Let $\mathcal{G}=\{G_1,\ldots,G_{m+1}\}$ be a family of graphs on the same vertex set $[n]$. In this paper, we prove that if for any $i\in [m+1]$, the spectral radius of $G_i$ is not less than $\max\{2m,\frac{1}{2}(m-1+\sqrt{(m-1)^2+4m(n-m)})\}$, then $\mathcal{G}$ admits a r

Yongheng Zhou, Kaiyue He, Huamin Hu, Gang Ouyang

Magneto-optical effect has been widely used in light modulation, optical sensing and information storage. Recently discovered two-dimensional (2D) van der Waals layered magnets are considered as promising platforms for investigating novel magneto-optical phenomena and devices, due to the long-range magnetic ordering down to atomically-thin thickness, rich sp

Vir Pathak

This is a survey on some topics in Lattice based cryptography and Homomorphic Encryption. In particular, we define some lattice problems, LWE and RLWE, and state the reductions given by Regev and Peikert. We also give a full treatment of the recent CKKS homomorphic encryption scheme and give some worked out examples.

Yair A. G. Fosado, Jamieson Howard, Simon Weir, Agnes Noy

In spite of the nanoscale and single-molecule insights into how nucleoid associated proteins (NAPs) interact with DNA, their role in modulating the mesoscale viscoelasticity of the entangled genome in vivo has been overlooked so far. By combining microrheology and molecular dynamics simulation we find that the important NAP called Integration Host Factor (IH

Qiang Zheng, Xiaoguang Yin, Dongxiao Zhang

The Li-ion battery is a complex physicochemical system that generally takes applied current as input and terminal voltage as output. The mappings from current to voltage can be described by several kinds of models, such as accurate but inefficient physics-based models, and efficient but sometimes inaccurate equivalent circuit and black-box models. To realize

Thomas Sharland

In this article we provide a combinatorial sufficient (and conjecturally, necessary) condition (called $\alpha$-symmetry) for the mating of two postcritically finite polynomials in $\mathcal{S}_1$ to be obstructed. To do this, we study the rotation sets associated to the parameter limbs in the connectedness locus of $\mathcal{S}_1$, which allows us to determ

Sarah S. Ji, Benjamin B. Chu, Hua Zhou, Kenneth Lange

Copulas, generalized estimating equations, and generalized linear mixed models promote the analysis of grouped data where non-normal responses are correlated. Unfortunately, parameter estimation remains challenging in these three frameworks. Based on prior work of Tonda, we derive a new class of probability density functions that allow explicit calculation o

S. Allak

Studying Ultraluminous X-ray sources (ULXs) in the optical wavelengths provides important clues about the accretion mechanisms and the evolutionary processes of X-ray binary systems. In this study, three (C1, C2, and C3) possible optical counterparts were identified for well-known neutron star (NS) candidate M51 ULX-8 through advanced astrometry based on the

Ellen M. Considine, Danielle Braun, Leila Kamareddine, Rachel C. Nethery

Environmental Protection Agency (EPA) air quality (AQ) monitors, the gold standard for measuring air pollutants, are sparsely positioned across the US due to their costliness. Low-cost sensors (LCS) are increasingly being used by the public to fill in the gaps in AQ monitoring; however, LCS are not as accurate as EPA monitors. In this work, we investigate fa

Daniel López Garcia

We consider the rational map $F$ defined by the quotient of products of lines in general position and we study the monodromy problem and tangential center-focus problem for the fibration associated with $F$. Thus, we study the submodule of the 1-homology group of a regular fiber of $F$ generated by the orbit of the monodromy action on a vanishing cycle. More

M. Aloisio, S. L. de Carvalho, C. R. de Oliveira, E. Souza

We prove sharp estimates on the time-average behavior of the squared absolute value of the Fourier transform of some absolutely continuous measures that may have power-law singularities, in the sense that their Radon-Nikodym derivatives diverge with a power-law order. We also discuss an application to spectral measures of finite-rank perturbations of the dis

Zhirui Li, Jesus Arroyo, Konstantinos Pantazis, Vince Lyzinski

Given a collection of vertex-aligned networks and an additional label-shuffled network, we propose procedures for leveraging the signal in the vertex-aligned collection to recover the labels of the shuffled network. We consider matching the shuffled network to averages of the networks in the vertex-aligned collection at different levels of granularity. We de