July 2022 arXiv papers — page 101

Kisun Lee, Julia Lindberg, Jose Israel Rodriguez

We implement a real polyhedral homotopy method using three functions. The first function provides a certificate that our real polyhedral homotopy is applicable to a given system; the second function generates binomial systems for a start system; the third function outputs target solutions from the start system obtained by the second function. This work reali

Tomas M. Bosschieter, Zifei Xu, Hui Lan, Benjamin J. Lengerich

Most pregnancies and births result in a good outcome, but complications are not uncommon and when they do occur, they can be associated with serious implications for mothers and babies. Predictive modeling has the potential to improve outcomes through better understanding of risk factors, heightened surveillance, and more timely and appropriate interventions

Jia Liu, Ran Cheng, Yaochu Jin

Deep neural networks have been found vulnerable to adversarial attacks, thus raising potentially concerns in security-sensitive contexts. To address this problem, recent research has investigated the adversarial robustness of deep neural networks from the architectural point of view. However, searching for architectures of deep neural networks is computation

Na Zhang, Yongguan Ke, Ling Lin, Li Zhang

We uncover the interaction-induced \emph{stable self-localization} of bosons in disorder-free superlattices. In these nonthermalized multi-particle states, one of the particles forms a superposition of multiple standing waves, so that it provides a quasirandom potential to localize the other particles. We derive effective Hamiltonians for self-localized stat

Jacob Pettine, Paolo Maioli, Fabrice Vallee, Natalia Del Fatti

Efficient excitation and harvesting of hot carriers from nanoscale metals is central to many emerging photochemical, photovoltaic, and ultrafast optoelectronic applications. Yet direct experimental evidence of the relevant femtosecond dynamics in ubiquitous tens-of-nanometer gold structures remains lacking, despite the rich interplay between interfacial and

Dipanjali Halder, V. S. Prasannaa, Rahul Maitra

In this paper, we have developed a unitary variant of a double exponential coupled cluster theory, which is capable of mimicking the effects of connected excitations of arbitrarily high rank, using only rank-one and rank-two parametrization of the wavefunction ansatz. While its implementation in a classical computer necessitates the construction of an effect

Junho Kim, Hojun Jang, Changwoon Choi, Young Min Kim

We present CPO, a fast and robust algorithm that localizes a 2D panorama with respect to a 3D point cloud of a scene possibly containing changes. To robustly handle scene changes, our approach deviates from conventional feature point matching, and focuses on the spatial context provided from panorama images. Specifically, we propose efficient color histogram

Connor J. Parde, Virginia E. Strehle, Vivekjyoti Banerjee, Ying Hu

Deep convolutional neural networks (DCNNs) have achieved human-level accuracy in face identification (Phillips et al., 2018), though it is unclear how accurately they discriminate highly-similar faces. Here, humans and a DCNN performed a challenging face-identity matching task that included identical twins. Participants (N=87) viewed pairs of face images of

Yung-Han Ho, Chih-Peng Chang, Peng-Yu Chen, Alessandro Gnutti

This paper presents an end-to-end learning-based video compression system, termed CANF-VC, based on conditional augmented normalizing flows (CANF). Most learned video compression systems adopt the same hybrid-based coding architecture as the traditional codecs. Recent research on conditional coding has shown the sub-optimality of the hybrid-based coding and

Pierre-Jean Barjhoux, Youssef Diouane, Stéphane Grihon, Joseph Morlier

In this paper, mixed categorical structural optimization problems are investigated. The aim is to minimize the weight of a truss structure with respect to cross-section areas, materials and cross-section type. The proposed methodology consists of using a bi-level decomposition involving two problems: master and slave. The master problem is formulated as a mi

Kai Yao, Penglei Gao, Xi Yang, Kaizhu Huang

Image outpainting, which is well studied with Convolution Neural Network (CNN) based framework, has recently drawn more attention in computer vision. However, CNNs rely on inherent inductive biases to achieve effective sample learning, which may degrade the performance ceiling. In this paper, motivated by the flexible self-attention mechanism with minimal in

Raymundo Bautista Ramos, Verónica Cifuentes Vargas

In this article we describe the Auslander-Reiten quiver for some posets with an involution, that we call types $\mathfrak{U}_n$ and $\mathfrak{U}_\infty$. These posets appear in the differentiation III of Zavadskij [12]. We follow the approach to classical Auslander-Reiten theory due to Auslander, Reiten and Smal\o{}[1]. For this purpose, we give a natural e

Lakshmi J. Naik, V. Sreekanth

We study the thermal dilepton and photon production from relativistic heavy ion collisions in presence of viscosities by employing the recently developed second order dissipative hydrodynamic formulation estimated within a quasiparticle description of thermal QCD (Quantum Chromo-Dynamics) medium. The sensitivity of shear and bulk viscous pressures to the tem

Filipe Chagas Ferraz

Since Shor's proposition of the method for factoring products of prime numbers using quantum computing, there has been a quest to implement efficient quantum arithmetic algorithms. These algorithms are capable of applying arithmetic operations simultaneously on large sets of values using quantum parallelism. Draper proposed an addition algorithm based on the

Tsubasa Harada, Toshiya Itoh, Shuichi Miyazaki

In the online facility assignment problem OFA(k,\ell), there exist k servers with a capacity \ell \geq 1 on a metric space and a request arrives one-by-one. The task of an online algorithm is to irrevocably match a current request with one of the servers with vacancies before the next request arrives. As special cases for OFA(k,\ell), we consider OFA(k,\ell)

Alexander Tumanov

We consider a problem whether a CR mapping of a generic manifold in complex space is uniquely determined by its finite jet at a point, which is referred to as finite jet determination. We derive the finite jet determination for CR mappings of smooth Levi nondegenerate manifolds of arbitrary codimension from the finite dimensionality of the algebras of infini

Linfeng Zhang, Xin Chen, Junbo Zhang, Runpei Dong

The success of deep learning is usually accompanied by the growth in neural network depth. However, the traditional training method only supervises the neural network at its last layer and propagates the supervision layer-by-layer, which leads to hardship in optimizing the intermediate layers. Recently, deep supervision has been proposed to add auxiliary cla

Zhang Kai, Gao Chuanhou

Order picking is the process of retrieving ordered products from storage locations in warehouses. In picker-to-parts order picking systems, two or more customer orders may be grouped and assigned to a single picker. Then routing decision regarding the visiting sequence of items during a picking tour must be made. (J.Won and S.Olafsson 2005) found that solvin

Zinnat Hassan, G. Mustafa, Joao R. L. Santos, P. K. Sahoo

An intriguing solution that appears in General Relativity (GR) but has not been observed so far is the wormhole. This exotic solution describes a topological bridge connecting two distinct universes or two different points in the same universe. It is known that the traversable wormhole solutions violate all the energy conditions in GR, resulting in their ins

Yunhan Huang, Tao Zhang, Quanyan Zhu

This paper aims to formulate and study the inverse problem of non-cooperative linear quadratic games: Given a profile of control strategies, find cost parameters for which this profile of control strategies is Nash. We formulate the problem as a leader-followers problem, where a leader aims to implant a desired profile of control strategies among selfish pla

Hamed Nilforoshan, Johann Gaebler, Ravi Shroff, Sharad Goel

Recent work highlights the role of causality in designing equitable decision-making algorithms. It is not immediately clear, however, how existing causal conceptions of fairness relate to one another, or what the consequences are of using these definitions as design principles. Here, we first assemble and categorize popular causal definitions of algorithmic

Tianyi Li

The graph-theoretical task of determining most likely inter-community edges based on disconnected subgraphs' intra-community connectivity is proposed. An algorithm is developed for this edge augmentation task, based on elevating the zero eigenvalues of graph's spectrum. Upper bounds for eigenvalue elevation amplitude and for the corresponding augmented edge

Zhou Kangneng, Zhu Xiaobin, Gao Daiheng, Lee Kai

Manipulating latent code in generative adversarial networks (GANs) for facial image synthesis mainly focuses on continuous attribute synthesis (e.g., age, pose and emotion), while discrete attribute synthesis (like face mask and eyeglasses) receives less attention. Directly applying existing works to facial discrete attributes may cause inaccurate results. I

Bo Lin, Feifei Gao, Yong Zhang, Chengkang Pan

Due to the short wavelength and large attenuation of millimeter-wave (mmWave), mmWave BSs are densely distributed and require beamforming with high directivity. When the user moves out of the coverage of the current BS or is severely blocked, the mmWave BS must be switched to ensure the communication quality. In this paper, we proposed a multi-camera view ba

Siddique Latif, Rajib Rana, Sara Khalifa, Raja Jurdak

Despite the recent progress in speech emotion recognition (SER), state-of-the-art systems lack generalisation across different conditions. A key underlying reason for poor generalisation is the scarcity of emotion datasets, which is a significant roadblock to designing robust machine learning (ML) models. Recent works in SER focus on utilising multitask lear

Sneha Kanchan, Jae Won Jang, Jun Yong Yoon, Bong Jun Choi

Federated Learning (FL) is a Machine Learning (ML) technique that aims to reduce the threats to user data privacy. Training is done using the raw data on the users' device, called clients, and only the training results, called gradients, are sent to the server to be aggregated and generate an updated model. However, we cannot assume that the server can be tr

Fei Hua, Yuwei Jin, Ang Li, Chenxu Liu

Near-term quantum systems tend to be noisy. Crosstalk noise has been recognized as one of several major types of noises in superconducting Noisy Intermediate-Scale Quantum (NISQ) devices. Crosstalk arises from the concurrent execution of two-qubit gates on nearby qubits, such as \texttt{CX}. It might significantly raise the error rate of gates in comparison

Thang Nguyen, Shi Wang

We consider a coarse version of the marked length spectrum rigidity: given a group with two left invariant metrics, if the marked length spectrum (the translation length function) under the two metrics are the same, then the two metrics are uniformly close. We prove the rigidity theorem for relatively hyperbolic groups. This generalizes a result of Fujiwara.

Vikram S Chundawat, Ayush K Tarun, Murari Mandal, Mukund Lahoti

Synthetic tabular data generation becomes crucial when real data is limited, expensive to collect, or simply cannot be used due to privacy concerns. However, producing good quality synthetic data is challenging. Several probabilistic, statistical, generative adversarial networks (GANs), and variational auto-encoder (VAEs) based approaches have been presented

Zhuohan Li, Gang Zhao, Yuqin Chen, Xilong Liang

As a typical data-driven method, deep learning becomes a natural choice for analysing astronomical data nowadays. In this study, we built a deep convolutional neural network to estimate basic stellar parameters $T\rm{_{eff}}$, log g, metallicity ([M/H] and [Fe/H]) and [$\alpha$/M] along with nine individual elemental abundances ([C/Fe], [N/Fe], [O/Fe], [Mg/F

Xubin Zhong, Changxing Ding, Zijian Li, Shaoli Huang

Human-Object Interaction (HOI) detection is a core task for high-level image understanding. Recently, Detection Transformer (DETR)-based HOI detectors have become popular due to their superior performance and efficient structure. However, these approaches typically adopt fixed HOI queries for all testing images, which is vulnerable to the location change of

Zhe Cheng, Jianbo Liang, Keisuke Kawamura, Hidetoshi Asamura

High thermal conductivity electronic materials are critical components for high-performance electronic and photonic devices as either active functional materials or thermal management materials. We report an isotropic high thermal conductivity over 500 W m-1K-1 at room temperature in high-quality wafer-scale cubic silicon carbide (3C-SiC) crystals, which is

Md Mahmudur Rahman, Sanjay Purushotham

Multi-state survival analysis (MSA) uses multi-state models for the analysis of time-to-event data. In medical applications, MSA can provide insights about the complex disease progression in patients. A key challenge in MSA is the accurate subject-specific prediction of multi-state model quantities such as transition probability and state occupation probabil

Ming Feng, Kele Xu, Nanhui Wu, Weiquan Huang

Despite remarkable efforts been made, the classification of gigapixels whole-slide image (WSI) is severely restrained from either the constrained computing resources for the whole slides, or limited utilizing of the knowledge from different scales. Moreover, most of the previous attempts lacked of the ability of uncertainty estimation. Generally, the patholo

Chao-Wei Huang, Shang-Chi Tsai, Yun-Nung Chen

Automatically classifying electronic health records (EHRs) into diagnostic codes has been challenging to the NLP community. State-of-the-art methods treated this problem as a multilabel classification problem and proposed various architectures to model this problem. However, these systems did not leverage the superb performance of pretrained language models,

Wanhua Li, Jiwen Lu, Abudukelimu Wuerkaixi, Jianjiang Feng

Different people age in different ways. Learning a personalized age estimator for each person is a promising direction for age estimation given that it better models the personalization of aging processes. However, most existing personalized methods suffer from the lack of large-scale datasets due to the high-level requirements: identity labels and enough sa

Farzad Omidi

In this paper, we investigate generalized volume-complexity $\mathcal{C}_{\rm gen}$ for a two-sided uncharged HV black brane in $d+2$ dimensions. This quantity which was recently introduced in [arXiv:2111.02429], is an extension of volume in the Complexity=Volume (CV) proposal, by adding higher curvature corrections with a coupling constant $\lambda$ to the

Vivek Narayanaswamy, Yamen Mubarka, Rushil Anirudh, Deepta Rajan

We focus on the problem of producing well-calibrated out-of-distribution (OOD) detectors, in order to enable safe deployment of medical image classifiers. Motivated by the difficulty of curating suitable calibration datasets, synthetic augmentations have become highly prevalent for inlier/outlier specification. While there have been rapid advances in data au

Shuxin Li, Xinrun Wang, Youzhi Zhang, Jakub Cerny

Offline reinforcement learning (offline RL) is an emerging field that has recently begun gaining attention across various application domains due to its ability to learn strategies from earlier collected datasets. Offline RL proved very successful, paving a path to solving previously intractable real-world problems, and we aim to generalize this paradigm to

Chuan Yan, Tao Yang, Huazhen Fang

Limited information availability represents a fundamental challenge for control of multi-agent systems, since an agent often lacks sensing capabilities to measure certain states of its own and can exchange data only with its neighbors. The challenge becomes even greater when agents are governed by high-order dynamics. The present work is motivated to conduct

Tingting Bo, Shiqian Cao, Nan Mu, Ruixin Xu

The discovery of metals as catalytic centers for nitrogen reduction reactions has stimulated great enthusiasm for single-atom catalysts. However, the poor activity and low selectivity of available SACs are far away from the industrial requirement. Through the high throughout first principles calculations, the doping engineering can effectively regulate the N

Qin Liu, Meng Zheng, Benjamin Planche, Srikrishna Karanam

The goal of click-based interactive image segmentation is to obtain precise object segmentation masks with limited user interaction, i.e., by a minimal number of user clicks. Existing methods require users to provide all the clicks: by first inspecting the segmentation mask and then providing points on mislabeled regions, iteratively. We ask the question: ca

Yifei Huang, Liping Tong, Jie Yang

We consider constrained sampling problems in paid research studies or clinical trials. When qualified volunteers are more than the budget allowed, we recommend a D-optimal sampling strategy based on the optimal design theory and develop a constrained lift-one algorithm to find the optimal allocation. Unlike the literature which mainly deals with linear model

Xiuxing Li, Zhenyu Li, Zhengyan Zhang, Ning Liu

Entity linking aims to link ambiguous mentions to their corresponding entities in a knowledge base, which is significant and fundamental for various downstream applications, e.g., knowledge base completion, question answering, and information extraction. While great efforts have been devoted to this task, most of these studies follow the assumption that larg

Madeleine Woodburn, Wynita M. Griggs, Jakub Marecek, Robert N. Shorten

Over two thirds of women of all ages in the UK have experienced some form of sexual harassment in a public space. Recent tragic incidents involving female pedestrians have highlighted some of the personal safety issues that women still face in cities today. There exist many popular location-based safety applications as a result of this; however, these applic

Sairam Sri Vatsavai, Ishan G Thakkar

Photonic Microring Resonator (MRR) based hardware accelerators have been shown to provide disruptive speedup and energy-efficiency improvements for processing deep Convolutional Neural Networks (CNNs). However, previous MRR-based CNN accelerators fail to provide efficient adaptability for CNNs with mixed-sized tensors. One example of such CNNs is depthwise s

David Vizgan, A. Meredith Hughes, Evan S. Carter, Kevin M. Flaherty

Debris disks are scaled-up analogs of the Kuiper Belt in which dust is generated by collisions between planetesimals. In the "collisional cascade" model of debris disks, dust lost to radiation pressure and winds is constantly replenished by grinding collisions between planetesimals. The model assumes that collisions are destructive and involve large velociti

Rebecca Engelke, Hyobin Yoo, Stephen Carr, Kevin Xu

We present a general method to analyze the topological nature of the domain boundary connectivity that appeared in relaxed moir\'e superlattice patterns at the interface of 2-dimensional (2D) van der Waals (vdW) materials. At large enough moir\'e lengths, all moir\'e systems relax into commensurated 2D domains separated by networks of dislocation lines. The

Dan Mikulincer, Daniel Reichman

We study monotone neural networks with threshold gates where all the weights (other than the biases) are non-negative. We focus on the expressive power and efficiency of representation of such networks. Our first result establishes that every monotone function over $[0,1]^d$ can be approximated within arbitrarily small additive error by a depth-4 monotone ne

Zhen Rong

Extending previous results of Bourdon and Shapiro we characterize the hypercyclic and mixing composition operators $C_{\varphi}$ for the automorphisms of $\mathbb{D}$ on any of the spaces $H^{p}$ with $1\leqslant p<+\infty$.

Yufan Liu, Jiajiong Cao, Bing Li, Weiming Hu

Transformer attracts much attention because of its ability to learn global relations and superior performance. In order to achieve higher performance, it is natural to distill complementary knowledge from Transformer to convolutional neural network (CNN). However, most existing knowledge distillation methods only consider homologous-architecture distillation

Narutaka Ozawa

The well-known theorem of Shalom--Vaserstein and Ershov--Jaikin-Zapirain states that the group $\mathrm{EL}_n(\mathcal{R})$, generated by elementary matrices over a finitely generated commutative ring $\mathcal{R}$, has Kazhdan's property (T) as soon as $n\geq3$. This is no longer true if the ring $\mathcal{R}$ is replaced by a commutative rng (a ring but wi

Ziqi Wang, Jialin Liu

Game consists of multiple types of content, while the harmony of different content types play an essential role in game design. However, most works on procedural content generation consider only one type of content at a time. In this paper, we propose and formulate online level generation from music, in a way of matching a level feature to a music feature in

Nengzheng Jin, Joanna Siebert, Dongfang Li, Qingcai Chen

Table Question Answering (Table QA) refers to providing precise answers from tables to answer a user's question. In recent years, there have been a lot of works on table QA, but there is a lack of comprehensive surveys on this research topic. Hence, we aim to provide an overview of available datasets and representative methods in table QA. We classify existi

Mahmood A. Al-Shareeda, Selvakumar Manickam

The emerging wireless communication technology known as vehicle ad hoc networks (VANETs) has the potential to both lower the risk of auto accidents caused by drivers and offer a wide range of entertainment amenities. The messages broadcast by a vehicle may be impacted by security threats due to the open-access nature of VANETs. Because of this, VANET is susc

Liangyu Chen, Huajia Wang

Mutual information serves as an important measure of correlation between subsystem components. In the framework of quantum field theories (QFTs) they have better regulated UV behavior than entanglement entropy, and thus provide more direct access to universal aspects of entanglement structures. In this paper, we study the linear responses under shape deforma

Haiqing Hao, Zhongwang Pang, Guan Wang, Bo Wang

The optical fiber network has become a worldwide infrastructure. In addition to the basic functions in telecommunication, its sensing ability has attracted more and more attention. In this paper, we discuss the risk of household fiber being used for eavesdropping and demonstrate its performance in the lab. Using a 3-meter tail fiber in front of the household

Fanyi Yang, Xiaoping Xie

We propose an unfitted finite element method for numerically solving the time-harmonic Maxwell equations on a smooth domain. The model problem involves a Lagrangian multiplier to relax the divergence constraint of the vector unknown. The embedded boundary of the domain is allowed to cut through the background mesh arbitrarily. The unfitted scheme is based on

Zhuochen Xiong

With the worldwide ravaging of the covid-19 epidemic, the traditional face-to-face education systems have been interrupted frequently. It is demanded to develop high-quality online education modalities. The webcasting based online classroom is one of the popular education modalities but suffers from poor teacher-student interactions and and low immersive lea

Yuchen Song, Danshi Wang, Qirui Fan, Xiaotian Jiang

We propose efficient modelling of optical fiber channel via NLSE-constrained physics-informed neural operator without reference solutions. This method can be easily scalable for distance, sequence length, launch power, and signal formats, and is implemented for ultra-fast simulations of 16-QAM signal transmission with ASE noise.

Lili Gui, Chuanshuo Wang, Fei Ding, Hao Chen

Wavelength-tunable vortex fiber lasers that could generate beams carrying orbital angular momentum (OAM) hold great interest in large-capacity optical communications. The wavelength tunability of conventional vortex fiber lasers is however limited by the range of 35 nm due to narrow bandwidth and/or insertion loss of mode conversion components. Optical metas

Zhang Jiayu

Virtual reality(VR) is a hot research topic, and it has been effectively applied in military, education and other fields. The application prospect of virtual reality in education is very broad. It can effectively reduce labor cost, resource consumption, stimulate students' interest in learning, and improve students' knowledge level. New energy vehicles have

Woorak Choi, Chang-Goo Kim, Aeree Chung

Ram pressure stripping (RPS) is a process that removes the interstellar medium (ISM) quickly, playing a vital role in galaxy evolution. Previous RPS studies have treated the ISM as single-phase or lack the resolution and physical processes to properly capture the full multiphase ISM. To improve this simplification, we introduce an inflowing, hot intracluster

Sumin Huang, Jianguo Qian, Wei Wang

It is known that, for any $k$-list assignment $L$ of a graph $G$, the number of $L$-list colorings of $G$ is at least the number of the proper $k$-colorings of $G$ when $k>(m-1)/\ln(1+\sqrt{2})$. In this paper, we extend the Whitney's broken cycle theorem to $L$-colorings of signed graphs, by which we show that if $k> \binom{m}{3}+\binom{m}{4}+m-1$ then, for

Changnam An, Eunkyung Han, Dongmyeong Noh, Ohkyoon Kwon

We present an efficient framework of corpus for sign language translation. Aided with a simple but dramatic data augmentation technique, our method converts text into annotated forms with minimum information loss. Sign languages are composed of manual signals, non-manual signals, and iconic features. According to professional sign language interpreters, non-

Keigan Demaria, Björn C. P. Sturmberg, Brad Riley, Francis Markham

Remote communities in Australia face unique mobility challenges that stand to be further complicated by the transition from Internal Combustion Engine (ICE) vehicles to Electric Vehicles (EVs). EVs offer a range of advantages that include lower maintenance requirements and independence from costly, dangerous and polluting petroleum imports that have long bee

Blai Bonet, Hector Geffner

Consider the finite state graph that results from a simple, discrete, dynamical system in which an agent moves in a rectangular grid picking up and dropping packages. Can the state variables of the problem, namely, the agent location and the package locations, be recovered from the structure of the state graph alone without having access to information about

Min Zhang, Zhuang Zhao

In this paper, a simple fifth-order finite difference Hermite WENO (HWENO) scheme combined with limiter is proposed for one- and two- dimensional hyperbolic conservation laws. The fluxes in the governing equation are approximated by the nonlinear HWENO reconstruction which is the combination of a quintic polynomial with two quadratic polynomials, where the l

Justin Diamond

Ultimate Tic-Tac-Toe is a variant of the popular Tic-Tac-Toe game. Two players compete to win three aligned "fields," with each field constituting its own miniature tic-tac-toe game. Each move determines which field the next player must play in. Prior studies have shown that there exists a forced winning strategy for the first player, whereby they can win in

David M. Rosen

Convex (specifically semidefinite) relaxation provides a powerful approach to constructing robust machine perception systems, enabling the recovery of certifiably globally optimal solutions of challenging estimation problems in many practical settings. However, solving the large-scale semidefinite relaxations underpinning this approach remains a formidable c

Tao Liu, Xi Yang, Chenshu Chen

As a promising approach in model compression, knowledge distillation improves the performance of a compact model by transferring the knowledge from a cumbersome one. The kind of knowledge used to guide the training of the student is important. Previous distillation methods in semantic segmentation strive to extract various forms of knowledge from the feature

P. Gaete, J. A. Helayël-Neto

In this contribution, our efforts consist in presenting and discussing the status of a paper in progress we are working on to investigate how non-linear electromagnetic effects couple to the parameters that signal Lorentz-symmetry violation (LSV). Here, we realize LSV by means of a specific model, namely Carroll-Field-Jackiw's. We set the formulation by cons

Masato Tamura, Rahul Vishwakarma, Ravigopal Vennelakanti

This paper presents a novel framework for social group activity recognition. As an expanded task of group activity recognition, social group activity recognition requires recognizing multiple sub-group activities and identifying group members. Most existing methods tackle both tasks by refining region features and then summarizing them into activity features

Zehong Liao, Long Zhu, Jun Su, Cheng Li

The dynamics of the charge equilibration (CE) and the effects on the production of the neutron-rich isotopes around $N = 126$ in multinucleon transfer reactions are still not well understood. In this Letter, we investigate the mechanism of the CE from different viewpoints by using the extended version of the dinuclear system model (DNS-sysu) and the improved

Yiming Cui, Linjie Yang, Ding Liu

Object detection is a basic computer vision task to loccalize and categorize objects in a given image. Most state-of-the-art detection methods utilize a fixed number of proposals as an intermediate representation of object candidates, which is unable to adapt to different computational constraints during inference. In this paper, we propose a simple yet effe

C. A. Escobar, Román Linares

In this work the spontaneous symmetry breaking in certain nonlinear theories with second-class constraints is explored. Using the Dirac's method we perform an analysis of the constraints and the counting of the degrees of freedom. The corresponding effective Hamiltonian is constructed explicitly. It is shown that on the surfaces where the effective Hamiltoni

Desi R. Ivanova, Joel Jennings, Cheng Zhang, Adam Foster

The real-world testing of decisions made using causal machine learning models is an essential prerequisite for their successful application. We focus on evaluating and improving contextual treatment assignment decisions: these are personalised treatments applied to e.g. customers, each with their own contextual information, with the aim of maximising a rewar

Khoi-Nguyen C. Mac, Minh N. Do, Minh P. Vo

Adaptive sampling that exploits the spatiotemporal redundancy in videos is critical for always-on action recognition on wearable devices with limited computing and battery resources. The commonly used fixed sampling strategy is not context-aware and may under-sample the visual content, and thus adversely impacts both computation efficiency and accuracy. Insp

Zhe Wang, Fan Zhang, Wenan Guo

Using Quantum Monte Carlo simulations, we study the spin-1/2 Heisenberg model on a two-dimensional lattice formed by coupling diagonal ladders. The model hosts an antiferromagnetic N\'eel phase, a rung singlet product phase, and a topological none trivial Haldane phase, separated by two quantum phase transitions. We show that the two quantum critical points

Md Mahmudur Rahman, Sanjay Purushotham

Survival analysis, time-to-event analysis, is an important problem in healthcare since it has a wide-ranging impact on patients and palliative care. Many survival analysis methods have assumed that the survival data is centrally available either from one medical center or by data sharing from multi-centers. However, the sensitivity of the patient attributes

Nei Lopes, Daniel Reyes, Natanael C. Costa, Mucio A. Continentino

The appearance of an incommensurate charge density wave vector $\textbf{Q} = (Q_x,Q_y)$ on multiband intermetallic systems presenting commensurate charge density wave (CDW) and superconductivity (SC) orders is investigated. We consider a two-band model in a square lattice, where the bands have distinct effective masses. The incommensurate CDW (inCDW) and CDW

Chan Park

We lay a theoretical foundation in the observation of gravitational waves (GWs) by electromagnetic waves (EMWs) performing a full electromagnetic analysis without any optical approximation. For that, the perturbation of plane EMWs is obtained by solving the perturbed Maxwell equation with GWs in the Minkowski background spacetime. In a GW detector using the

Meiyu Zhi

In this paper, we develop a robust, efficient visual SLAM system that utilizes spatial inhibition of low threshold, baseline lines, and closed-loop keyframe features. Using ORB-SLAM2, our methods include stereo matching, frame tracking, local bundle adjustment, and line and point global bundle adjustment. In particular, we contribute re-projection in line wi

Johnatan Cardona Jiménez, María I. Ardila, J. S. Rudas, Cesar A. Isaza M.

Responding to the current urgent need for low carbon emissions and high efficiency in manufacturing processes, the relationships between three different machining factors (depth of cut, feed rate, and spindle rate) on power consumption and surface finish (roughness) were analysed by applying a Bayesian seemingly unrelated regressions (SUR) model. For the ana

Qingci An, Yannis Kevrekidis, Fei Lu, Mauro Maggioni

We investigate the unsupervised learning of non-invertible observation functions in nonlinear state-space models. Assuming abundant data of the observation process along with the distribution of the state process, we introduce a nonparametric generalized moment method to estimate the observation function via constrained regression. The major challenge comes

Ji-Hoon Kim, Yeo-Reum Park, Jaeyoung Do, Soo-Young Ji

K-nearest neighbor search is one of the fundamental tasks in various applications and the hierarchical navigable small world (HNSW) has recently drawn attention in large-scale cloud services, as it easily scales up the database while offering fast search. On the other hand, a computational storage device (CSD) that combines programmable logic and storage mod

Xiangyu Li, Xinyu Wang, Tingli Kong, Junhao Zheng

This survey presents a comprehensive study of recent advances in block-chain technologies, focusing on how issues that affecting the enterprise adoption were progressively addressed from the original Bitcoin system to Ethereum, to Solana etc. Key issues preventing the wide adoption are scala-bility and performance, while recent advances in Solana has clearly

Scott Beliveau, Jerry Ma

The USPTO disseminates one of the largest publicly accessible repositories of scientific, technical, and commercial data worldwide. USPTO data has historically seen frequent use in fields such as patent analytics, economics, and prosecution & litigation tools. This article highlights an emerging class of usecases directed to the research, development, and ap

Tao Wang, Xiansheng Cai, Kun Chen, Boris V. Svistunov

We address the outstanding problem of electron pairing in the presence of strong Coulomb repulsion at small to moderate values of the Coulomb parameter, $r_s \lesssim 2$, and demonstrate that the pseudopotential framework is fundamentally biased and uncontrolled. Instead, one has to break the net result into two distinctively different effects: the Fermi liq

Ana Caraiani, Matthew Emerton, Toby Gee, David Savitt

In a previous article we introduced various moduli stacks of two-dimensional tamely potentially Barsotti-Tate representations of the absolute Galois group of a p-adic local field, as well as related moduli stacks of Breuil-Kisin modules with descent data. We study the irreducible components of these stacks, establishing in particular that the components of t

Yuma Sugahara, Akio K. Inoue, Yoshinobu Fudamoto, Takuya Hashimoto

We present photoionization modeling of galaxy populations at $z\sim0$, $2$, and $> 6$ to bridge optical and far-infrared (FIR) emission-line diagrams. We collect galaxies with measurements of optical and/or FIR ([O III] 88 $\mathrm{\mu m}$ and [C II] 158 $\mathrm{\mu m}$) emission line fluxes and plot them on the [O III]$\lambda5007/\mathrm{H\beta}$--[N II]$

Ana Caraiani, Matthew Emerton, Toby Gee, David Savitt

We establish a geometrisation of the Breuil-M\'ezard conjecture for potentially Barsotti-Tate representations, as well as of the weight part of Serre's conjecture, for moduli stacks of two-dimensional mod p representations of the absolute Galois group of a p-adic local field.

Mourad Oudich, Nikhil JRK Gerard, Yuanchen Deng, Yun Jing

In solid state physics, a bandgap (BG) refers to a range of energies where no electronic states can exist. This concept was extended to classical waves, spawning the entire fields of photonic and phononic crystals where BGs are frequency (or wavelength) intervals where wave propagation is prohibited. For elastic waves, BGs are found in periodically alternati

Ian Williams, Adnan Khan, Matthew McQuinn

Where the cosmic baryons lie in and around galactic dark matter halos is only weakly constrained. We develop a method to quickly paint on models for their distribution. Our approach uses the statistical advantages of $N$-body simulations, while painting on the profile of gas around individual halos in ways that can be motivated by semi-analytic models or zoo

Q. -H. Ren, T. Suzuki, T. Kanai, J. Itatani

We investigate the nonequilibrium electronic structure of 1T-TaS2 by time- and angle-resolved photoemission spectroscopy. We observe that strong photoexcitation induces the collapse of the Mott gap, leading to the photo-induced metallic phase. It is also found that the oscillation of photoemission intensity occurs as a result of the excitations of coherent p

Hanqing Chao, Jiajin Zhang, Pingkun Yan

Regression plays an essential role in many medical imaging applications for estimating various clinical risk or measurement scores. While training strategies and loss functions have been studied for the deep neural networks in medical image classification tasks, options for regression tasks are very limited. One of the key challenges is that the high-dimensi

Yu Liu, Can Li, Fu-Hua Xue, Ying Wang

Quantum spins, referred to the spin operator preserved by full SU(2) symmetry in the absence of the magnetic anistropy, have been proposed to host exotic interactions with superconductivity4. However, spin orbit coupling and crystal field splitting normally cause a significant magnetic anisotropy for d/f-shell spins on surfaces6,9, breaking SU(2) symmetry an

Ramya Cuduvally, Richard J. H. Morris, Giel Oosterbos, Piero Ferrari

A major challenge for Atom Probe Tomography (APT) quantification is the inability to decouple ions which possess the same mass/charge-state ($m/n$) ratio but a different mass. For example, $^{75}{\rm{As}}^{+}$ and $^{75}{\rm{As}}{_2}^{2+}$ at ~75 Da or $^{14}{\rm{N}}^+$ and $^{28}{\rm{Si}}^{2+}$ at ~14 Da, cannot be differentiated without the additional know

Matteo Gori, Roberto Franzosi, Giulio Pettini, Marco Pettini

The investigation of the Hamiltonian dynamical counterpart of phase transitions, combined with the Riemannian geometrization of Hamiltonian dynamics, has led to a preliminary formulation of a differential-topological theory of phase transitions. In fact, in correspondence of a phase transition there are peculiar geometrical changes of the mechanical manifold

Salvatore Torquato, Haina Wang

The determination of the pair potential $v({\bf r})$ that accurately yields an equilibrium state at positive temperature $T$ with a prescribed pair correlation function $g_2({\bf r})$ or corresponding structure factor $S({\bf k})$ in $d$-dimensional Euclidean space $\mathbb{R}^d$ is an outstanding inverse statistical mechanics problem with far-reaching impli