July 2022 arXiv papers — page 142

Bohan Yang, Bo Lu, Wei Chen, Fangxun Zhong

Shape control of deformable objects is a challenging and important robotic problem. This paper proposes a model-free controller using novel 3D global deformation features based on modal analysis. Unlike most existing controllers using geometric features, our controller employs a physically-based deformation feature by decoupling 3D global deformation into lo

Andreas Mischok, Sabina Hillebrandt, Seonil Kwon, Malte C. Gather

Angle-independent, narrowband emission is required for many optoelectronic devices, ranging from high-definition displays to sensors. However, emerging materials for electroluminescent devices, such as organics and perovskites, show spectrally broad emission due to intrinsic disorder. Coupling this emission to an optical resonance reduces the linewidth, but

Sujan Pal, Jyotirmoy Poddar

The Central Sets Theorem near zero was originally proved by Hindman and Leader. Later a version of Central Sets Theorem was proved by De, Hindman and Strauss known to be the stronger Central Sets Theorem. Subsequently many other versions of Central Sets Theorem came, among which Dev Phulara proved the theorem for a sequence of central sets instead of taking

Florentin Coeurdoux, Nicolas Dobigeon, Pierre Chainais

Optimal transport (OT) provides effective tools for comparing and mapping probability measures. We propose to leverage the flexibility of neural networks to learn an approximate optimal transport map. More precisely, we present a new and original method to address the problem of transporting a finite set of samples associated with a first underlying unknown

Yair Neuman, Yochai Cohen

Buy low, sell high is one of the basic rules of thumb used in investment, although it is not considered to be a beneficial strategy. In this paper, we show how the appropriate permutation-based representation (i.e., the epistemic form) of a minute-by-minute trading time-series, alongside the use of a simple decision heuristic (i.e., the epistemic game), may

Zhenyu Kang, Changsheng You, Rui Zhang

Intelligent reflecting surface (IRS) has emerged as a promising technology to enhance the wireless communication network coverage and capacity by dynamically controlling the radio signal propagation environment. In contrast to the existing works that considered active or passive IRS only, we propose in this paper a new hybrid active-passive IRS architecture

Harun Al Rashid, Dheeraj Kumar Singh

In the half-filled one-orbital Hubbard model on a square lattice, we find pseduogap features in the form of two-peak structures associated with the momentum-resolved spectral function, which exists within the temperature window $T_N \lesssim T \lesssim T^*$. $T^*$ is the temperature below which there exists a well-formed dip in the density of state. Inside t

Fabian Küppers, Jonas Schneider, Anselm Haselhoff

Reliable spatial uncertainty evaluation of object detection models is of special interest and has been subject of recent work. In this work, we review the existing definitions for uncertainty calibration of probabilistic regression tasks. We inspect the calibration properties of common detection networks and extend state-of-the-art recalibration methods. Our

Ye Liu, Lingfeng Qiao, Di Yin, Zhuoxuan Jiang

Scene segmentation and classification (SSC) serve as a critical step towards the field of video structuring analysis. Intuitively, jointly learning of these two tasks can promote each other by sharing common information. However, scene segmentation concerns more on the local difference between adjacent shots while classification needs the global representati

Cinzia Casagrande

This note is a short survey on the Lefschetz defect, an invariant of smooth Fano varieties that has been recently introduced; it is related to the Picard number rho(X) of X, and to the Picard number of prime divisors in X. We explain the definition of the Lefschetz defect delta(X) and its origin, the known results - mainly on the case delta(X)>1, and several

Zhongxiang Chang, Yuning Chen, Zhongbao Zhou

A novel problem called satellite downlink scheduling problem (SDSP) under breakpoint resume mode (SDSP-BRM) is studied in our paper. Compared to the traditional SDSP where an imaging data has to be completely downloaded at one time, SDSP-BRM allows the data of an imaging data be broken into a number of pieces which can be downloaded in different playback win

Pritam Das, Najimuddin Khan

We consider a new physics model, where the Standard Model (SM) is extended by hyperchargeless $Y=0$ triplet fermions and Higgs triplet with hypercharge $Y=2$. The first two generation fermion triplets are even under the $Z_2$ transformation. In contrast, the third fermion triplet and scalar triplet are odd under the same $Z_2$ transformation. It is a unifyin

Chandler Squires, Annie Yun, Eshaan Nichani, Raj Agrawal

We consider the problem of learning the structure of a causal directed acyclic graph (DAG) model in the presence of latent variables. We define latent factor causal models (LFCMs) as a restriction on causal DAG models with latent variables, which are composed of clusters of observed variables that share the same latent parent and connections between these cl

Seong-A Park, Hyung-Chul Lee, Chul-Woo Jung, Hyun-Lim Yang

Attention mechanisms are widely used to dramatically improve deep learning model performance in various fields. However, their general ability to improve the performance of physiological signal deep learning model is immature. In this study, we experimentally analyze four attention mechanisms (e.g., squeeze-and-excitation, non-local, convolutional block atte

Elias Wirth, Hiroshi Kera, Sebastian Pokutta

The vanishing ideal of a set of points $X = \{\mathbf{x}_1, \ldots, \mathbf{x}_m\}\subseteq \mathbb{R}^n$ is the set of polynomials that evaluate to $0$ over all points $\mathbf{x} \in X$ and admits an efficient representation by a finite subset of generators. In practice, to accommodate noise in the data, algorithms that construct generators of the approxim

Johannes Wiesel, Erica Zhang

For probability measures $\mu,\nu$ and $\rho$ define the cost functionals \begin{align*} C(\mu,\rho):=\sup_{\pi\in \Pi(\mu,\rho)} \int \langle x,y\rangle\, \pi(dx,dy),\quad C(\nu,\rho):=\sup_{\pi\in \Pi(\nu,\rho)} \int \langle x,y\rangle\, \pi(dx,dy), \end{align*} where $\langle\cdot, \cdot\rangle$ denotes the scalar product and $\Pi(\cdot,\cdot)$ is the set

Milo Roucairol, Tristan Cazenave

We demonstrate how Monte Carlo Search (MCS) algorithms, namely Nested Monte Carlo Search (NMCS) and Nested Rollout Policy Adaptation (NRPA), can be used to build graphs and find counter-examples to spectral graph theory conjectures in minutes.

Vishnu Raj, Tianyu Cui, Markus Heinonen, Pekka Marttinen

Bayesian neural networks (BNNs) can account for both aleatoric and epistemic uncertainty. However, in BNNs the priors are often specified over the weights which rarely reflects true prior knowledge in large and complex neural network architectures. We present a simple approach to incorporate prior knowledge in BNNs based on external summary information about

Canran Li, Dongnan Liu, Haoran Li, Zheng Zhang

Unsupervised domain adaptation (UDA) methods have been broadly utilized to improve the models' adaptation ability in general computer vision. However, different from the natural images, there exist huge semantic gaps for the nuclei from different categories in histopathology images. It is still under-explored how could we build generalized UDA models for pre

Jian He, Jing He, Panyue Zhou

It was shown recently that an $n$-extension closed subcategory $\mathscr A$ of a Krull-Schmidt $(n+2)$-angulated category has a natural structure of an $n$-exangulated category. In this article, we prove that its idempotent completion $\widetilde{\mathscr A}$ admits an $n$-exangulated structure. It is not only a generalization of the main result of Lin, but

Zhe Chang, Xukun Zhang, Jing-Zhi Zhou

The cosmological background of higher order vector modes can be generated by the first order scalar perturbations. We investigate the second order and the third order vector modes systematically. The explicit expressions of two point functions $\langle V^{(n),\lambda}V^{(n),\lambda'} \rangle$$\left(n=2,3\right)$ and power spectra corresponded are presented.

Kaitao Meng, Qingqing Wu, Robert Schober, Wen Chen

Besides improving communication performance, intelligent reflecting surfaces (IRSs) are also promising enablers for achieving larger sensing coverage and enhanced sensing quality. Nevertheless, in the absence of a direct path between the base station (BS) and the targets, multi-target sensing is generally very difficult, since IRSs are incapable of proactive

K. Ram Prabhakar, Susmit Agrawal, R. Venkatesh Babu

We present a motion segmentation guided convolutional neural network (CNN) approach for high dynamic range (HDR) image deghosting. First, we segment the moving regions in the input sequence using a CNN. Then, we merge static and moving regions separately with different fusion networks and combine fused features to generate the final ghost-free HDR image. Our

Abhinav Dhawan, A. Bhattacharyay

In this paper we compare the Boltzmann distribution with a modified Boltzmann distribution, that results from an It\^o-process considering thermal equilibrium of a Brownian particle with coordinate dependent diffusion, in the light of an existing experiment. The experiment was reported in 1994 by Faucheux and Libchaber. The experiment made use of direct trac

Shahid Alam

The digital transformation has created a new digital space known as cyberspace. This new cyberspace has improved the workings of businesses, organizations, governments, society as a whole, and day to day life of an individual. With these improvements come new challenges, and one of the main challenges is security. The security of the new cyberspace is called

Bao Ting Zhu

On a microscopic scale, resistivity during electric conduction is caused by collisions of the free conduction electrons with the obstructing atoms or molecules of the conductor material, resulting in heat production. Based on this fundamental understanding, a hypothesis concerning a physical requirement of the superconductor material is proposed, which sugge

Takahiro Yabe

Decomposition algebras and axial decomposition algebras are classes of commutative nonassociative algebras which are generalizations of axial algebras. The classes decomposition algebras, axial decomposition al;gebras and non-primitive axial algebras also have univesal algebras. Furthermore, by using the existence of a universal algebra, 2-generated non-prim

Itai Benjamini, Hagai Helman Tov, Maksim Zhukovskii

We observe the outcome of the discrete time noisy voter model at a single vertex of a graph. We show that certain pairs of graphs can be distinguished by the frequency of repetitions in the sequence of observations. We prove that this statistic is asymptotically normal and that it distinguishes between (asymptotically) almost all pairs of finite graphs. We c

Wei Shen, Zelin Peng, Xuehui Wang, Huayu Wang

The rapid development of deep learning has made a great progress in image segmentation, one of the fundamental tasks of computer vision. However, the current segmentation algorithms mostly rely on the availability of pixel-level annotations, which are often expensive, tedious, and laborious. To alleviate this burden, the past years have witnessed an increasi

Chenggang Shan, Guan Wang, Yuanqing Xia, Yufeng Zhan

As Kubernetes becomes the infrastructure of the cloud-native era, the integration of workflow systems with Kubernetes is gaining more and more popularity. To our knowledge, workflow systems employ scheduling algorithms that optimize task execution order of workflow to improve performance and execution efficiency. However, due to its inherent scheduling mecha

Bao Chen, Bing Chen, Xinyi Zhu, Zhifei Yu

Nitrogen-vacancy (NV) centers in diamond are suitable sensors of high-sensitivity magnetometry which have attracted much interest in recent years. Here, we demonstrate sensitivity-enhanced ensembles magnetometry via adaptively complete transitions overlapping with a bias magnetic field equally projecting onto all existing NV orientations. Under such conditio

Oshri Naparstek, Ophir Azulai, Daniel Rotman, Yevgeny Burshtein

For digitizing or indexing physical documents, Optical Character Recognition (OCR), the process of extracting textual information from scanned documents, is a vital technology. When a document is visually damaged or contains non-textual elements, existing technologies can yield poor results, as erroneous detection results can greatly affect the quality of OC

Haoren Guo, Haiyue Zhu, Jiahui Wang, Vadakkepat Prahlad

Prediction of Remaining Useful Lifetime(RUL) in the modern manufacturing and automation workplace for machines and tools is essential in Industry 4.0. This is clearly evident as continuous tool wear, or worse, sudden machine breakdown will lead to various manufacturing failures which would clearly cause economic loss. With the availability of deep learning a

Jiahui Wang, Haiyue Zhu, Haoren Guo, Abdullah Al Mamun

3D part segmentation is an essential step in advanced CAM/CAD workflow. Precise 3D segmentation contributes to lower defective rate of work-pieces produced by the manufacturing equipment (such as computer controlled CNCs), thereby improving work efficiency and attaining the attendant economic benefits. A large class of existing works on 3D model segmentation

Nayana Shibu Deepthi

Let $G$ be a finite simple connected graph on the vertex set $V(G)=[d]=\{1,\dots ,d\}$, with edge set $E(G)=\{e_{1},\dots , e_{n}\}$. Let $K[\mathbf{t}]=K[t_{1},\dots , t_{d}]$ be the polynomial ring in $d$ variables over a field $K$. The edge ring of $G$ is the semigroup ring $K[G]$ generated by monomials $\mathbf{t}^{e}:=t_{i}t_{j}$, for $e=\{i,j\} \in E(G

Cheng Zou, Furong Xu, Meng Wang, Wen Li

Automatic snake species recognition is important because it has vast potential to help lower deaths and disabilities caused by snakebites. We introduce our solution in SnakeCLEF 2022 for fine-grained snake species recognition on a heavy long-tailed class distribution. First, a network architecture is designed to extract and fuse features from multiple modali

Vishnuram Arumugam, Heiko Dietrich, S. P. Glasby

Given a finite group $G$ acting on a set $X$ let $\delta_k(G,X)$ denote the proportion of elements in $G$ that have exactly $k$ fixed points in $X$. Let $\mathrm{S}_n$ denote the symmetric group acting on $[n]=\{1,2,\dots,n\}$. For $A\le\mathrm{S}_m$ and $B\le\mathrm{S}_n$, the permutational wreath product $A\wr B$ has two natural actions and we give formula

Junbo Zhang, Weiwei Wan, Nobuyuki Tanaka, Miki Fujita

This paper presents a system integration approach for a 6-DoF (Degree of Freedom) collaborative robot to operate a pipette for liquid dispensing. Its technical development is threefold. First, we designed an end-effector for holding and triggering manual pipettes. Second, we took advantage of a collaborative robot to recognize labware poses and planned robot

Sungwook Choi, Sang Won Im, Ji-Hyeok Huh, Sungwon Kim

Identifying the three-dimensional (3D) crystal-plane and strain-field distributions of nanocrystals is essential for optical, catalytic, and electronic applications. Here, we developed a methodology for visualizing the 3D information of chiral gold nanoparticles with concave gap structures by Bragg coherent X-ray diffraction imaging. The distribution of the

Yogesh Kumar, Prince Sharma, V. P. S. Awana

Topological insulators are immensely investigated for their surface states related properties as these materials can be used for various spintronics, quantum computing, and optoelectronics applications. In this perspective, different thicknesses of bismuth selenide thin films are deposited on the 250 nm SiO2 substrate with the help of thermal deposition. The

Xiangri Lu

The confrontation of modern intelligence is to some extent a non-complete information confrontation, where neither side has access to sufficient information to detect the deployment status of the adversary, and then it is necessary for the intelligence to complete information retrieval adaptively and develop confrontation strategies in the confrontation envi

Jürgen Seiler, André Kaup

The prediction step is a very important part of hybrid video codecs for effectively compressing video sequences. While existing video codecs predict either in temporal or in spatial direction only, the compression efficiency can be increased by a combined spatio-temporal prediction. In this paper we propose an algorithm for reusing the H.264/AVC deblocking f

Sébastien Ollivier, Sheng Li, Yue Tang, Chayanika Chaudhuri

Edge computing is a popular target for accelerating machine learning algorithms supporting mobile devices without requiring the communication latencies to handle them in the cloud. Edge deployments of machine learning primarily consider traditional concerns such as SWaP constraints (Size, Weight, and Power) for their installations. However, such metrics are

Sixing Yan, William K. Cheung, Keith Chiu, Terence M. Tong

Automatic generation of medical reports from X-ray images can assist radiologists to perform the time-consuming and yet important reporting task. Yet, achieving clinically accurate generated reports remains challenging. Modeling the underlying abnormalities using the knowledge graph approach has been found promising in enhancing the clinical accuracy. In thi

Jürgen Seiler, André Kaup

In this contribution, a novel spatio-temporal prediction algorithm for video coding is introduced. This algorithm exploits temporal as well as spatial redundancies for effectively predicting the signal to be encoded. To achieve this, the algorithm operates in two stages. Initially, motion compensated prediction is applied on the block being encoded. Afterwar

Shunyu Yao, Howard Chen, John Yang, Karthik Narasimhan

Existing benchmarks for grounding language in interactive environments either lack real-world linguistic elements, or prove difficult to scale up due to substantial human involvement in the collection of data or feedback signals. To bridge this gap, we develop WebShop -- a simulated e-commerce website environment with $1.18$ million real-world products and $

Jürgen Seiler, André Kaup

The purpose of this paper is to introduce a very efficient algorithm for signal extrapolation. It can widely be used in many applications in image and video communication, e. g. for concealment of block errors caused by transmission errors or for prediction in video coding. The signal extrapolation is performed by extending a signal from a limited number of

Yuki Hashimoto, Akira Furui, Koji Shimatani, Maura Casadio

The assessment of general movements (GMs) in infants is a useful tool in the early diagnosis of neurodevelopmental disorders. However, its evaluation in clinical practice relies on visual inspection by experts, and an automated solution is eagerly awaited. Recently, video-based GMs classification has attracted attention, but this approach would be strongly a

Shin'ichiro Ando, Nagisa Hiroshima, Koji Ishiwata

We investigate the primordial curvature perturbation by the observation of dark matter substructure. Assuming a bump in the spectrum of the curvature perturbation in the wavenumber of k>1 Mpc^{-1}, we track the evolution of the host halo and subhalos in a semi-analytic way. Taking into account possible uncertainties in the evaluation of the tidal stripping e

Eugene P. W. Ang, Shan Lin, Rahul Ahuja, Nemath Ahmed

Existing evaluation metrics for Person Re-Identification (Person ReID) models focus on system-wide performance. However, our studies reveal weaknesses due to the uneven data distributions among cameras and different camera properties that expose the ReID system to exploitation. In this work, we raise the long-ignored ReID problem of camera performance imbala

Xiang Li, Jinglu Wang, Xiaohao Xu, Xiao Li

Referring Video Object Segmentation (R-VOS) is a challenging task that aims to segment an object in a video based on a linguistic expression. Most existing R-VOS methods have a critical assumption: the object referred to must appear in the video. This assumption, which we refer to as semantic consensus, is often violated in real-world scenarios, where the ex

Raghvendra Posti, Abhishek Kumar, Dhananjay Tiwari, Debangsu Roy

Application of sufficient lateral current to a heavy metal (HM) can switch the perpendicular magnetization orientation of adjacent ferromagnetic layer (FM) through spin-orbit torques (SOTs). The choice of the HM and its arrangement plays a major role for the SOT induced magnetization switching in magnetic heterostructures. Here, in asymmetric Pt/Co/Pt hetero

Fernando Giner

The study of IR evaluation metrics through axiomatic analysis enables a better understanding of their numerical properties. Some works have modelled the effectiveness of retrieval metrics with axioms that capture desirable properties on the set of rankings of documents. This paper formally explores the effect of these ranking axioms on the numerical values o

Anupam Singh

Dark Energy is the largest fraction of the energy density of our Universe - yet it remains one of the enduring enigmas of our times. Here we show that Dark Energy can be used to solve 2 tantalizing mysteries of the observable universe. We build on existing models of Dark Energy linked to neutrino masses. In these models Dark Energy can undergo Phase Transiti

Jiahang Zhang, Lilang Lin, Zejia Fan, Wenjing Wang

Deep learning has become a powerful tool for Mars exploration. Mars terrain semantic segmentation is an important Martian vision task, which is the base of rover autonomous planning and safe driving. However, there is a lack of sufficient detailed and high-confidence data annotations, which are exactly required by most deep learning methods to obtain a good

Jiahao Liang, Weihong Deng

With the emergence of GAN, face forgery technologies have been heavily abused. Achieving accurate face forgery detection is imminent. Inspired by remote photoplethysmography (rPPG) that PPG signal corresponds to the periodic change of skin color caused by heartbeat in face videos, we observe that despite the inevitable loss of PPG signal during the forgery p

Tao Li, Xinsheng Wang, Qicong Xie, Zhichao Wang

Cross-speaker emotion transfer speech synthesis aims to synthesize emotional speech for a target speaker by transferring the emotion from reference speech recorded by another (source) speaker. In this task, extracting speaker-independent emotion embedding from reference speech plays an important role. However, the emotional information conveyed by such emoti

Xiaoyu Wang, Xiangyu Kong, Xiulian Peng, Yan Lu

In this paper we propose a multi-modal multi-correlation learning framework targeting at the task of audio-visual speech separation. Although previous efforts have been extensively put on combining audio and visual modalities, most of them solely adopt a straightforward concatenation of audio and visual features. To exploit the real useful information behind

Tao Gong, Benjamin Spreng, Miguel Camacho, Inigo Liberal

Casimir forces between charge-neutral bodies originate from quantum vacuum fluctuations of electromagnetic fields, which exhibit a critical dependence on material's electromagnetic properties. Over the years, in-situ modulation of material's optical properties has been enabled through various means and has been widely exploited in a plethora of applications

Hsuan-Jui Su, Jia-You Liou, I-Chun Lin, Yi-Hsin Chen

We provide a universal discussion of the interplay between Rydberg-state electromagnetically induced transparency (EIT) and optical pumping (OP) in a thermal Rb87 medium. By pumping the population to one single Hyperfine/Zeeman state, we can enhance the interaction strength and, in principle, amplify the EIT peak. According to our measurements, the EIT peak

Ivan P. Shestakov

We prove that for every natural number n there exists a natural number N(n) such that every multilinear skew-symmetric polynomial on N(n) or more variables which vanishes in the free associative algebra vanishes as well in any n-generated alternative algebra over a field of characteristic 0. Before this was proved only for a series of such polynomials constr

Belle Collaboration, S. Choudhury, S. Sandilya, K. Trabelsi

We measure the ratio of branching fractions for the $\Upsilon (4S)$ decays to $B^+B^-$ and $B^0\bar{B}{}^0$ using $B^+ \rightarrow J/\psi(\ell\ell) K^+$ and $B^0 \rightarrow J/\psi(\ell\ell) K^0$ samples, where $J/\psi(\ell\ell)$ stands for $J/\psi \to \ell^+\ell^-$ ($\ell = e$ or $\mu$), with $711$ fb$^{-1}$ of data collected at the $\Upsilon(4S)$ resonance

Huimin Chen, Fengran Mo, Yanhao Wang, Cen Chen

As privacy issues are receiving increasing attention within the Natural Language Processing (NLP) community, numerous methods have been proposed to sanitize texts subject to differential privacy. However, the state-of-the-art text sanitization mechanisms based on metric local differential privacy (MLDP) do not apply to non-metric semantic similarity measures

Kazuro Furukawa, Mitsuo Akemoto, Dai Arakawa, Yoshio Arakida

KEK electron positron injector LINAC initiated the injection operation into Photon Factory (PF) light source in 1982. Since then for 39 years, it has served for multiple projects, namely, TRISTAN, PF-AR, KEKB, and SuperKEKB. Its total operation time has accumulated 200 thousand hours on May 7, 2020. We are extremely proud of the achievement following continu

D. C. Cavanagh, Daniel F. Agterberg, P. M. R. Brydon

We study the influence of symmetry-breaking perturbations on superconductivity in multiorbital materials, with a particular focus on an external magnetic field. We introduce the field-fitness function which characterizes the pair-breaking effects of the perturbation on a given superconducting state. For even parity superconductors we find that this field-fit

Davide Belli, Debasmit Das, Bence Major, Fatih Porikli

Face authentication systems require a robust anti-spoofing module as they can be deceived by fabricating spoof images of authorized users. Most recent face anti-spoofing methods rely on optimized architectures and training objectives to alleviate the distribution shift between train and test users. However, in real online scenarios, past data from a user con

Xueying Zhan, Zeyu Dai, Qingzhong Wang, Qing Li

Pool-based Active Learning (AL) has achieved great success in minimizing labeling cost by sequentially selecting informative unlabeled samples from a large unlabeled data pool and querying their labels from oracle/annotators. However, existing AL sampling strategies might not work well in out-of-distribution (OOD) data scenarios, where the unlabeled data poo

Houquan Zhou, Shenghua Liu, Danai Koutra, Huawei Shen

Graph representation learning plays an important role in many graph mining applications, but learning embeddings of large-scale graphs remains a problem. Recent works try to improve scalability via graph summarization -- i.e., they learn embeddings on a smaller summary graph, and then restore the node embeddings of the original graph. However, all existing w

Jiashu Wu

Over the past decades, researchers had put lots of effort investigating ranking techniques used to rank query results retrieved during information retrieval, or to rank the recommended products in recommender systems. In this project, we aim to investigate searching, ranking, as well as recommendation techniques to help to realize a university academia searc

Jinho Lee, Sungwoo Park, Jungyu Ahn, Jonghun Kwak

Recently, the application of advanced machine learning methods for asset management has become one of the most intriguing topics. Unfortunately, the application of these methods, such as deep neural networks, is difficult due to the data shortage problem. To address this issue, we propose a novel approach using neural networks to construct a portfolio of exc

Tianping Zhang, Yizhuo Zhang, Wei Cao, Jiang Bian

Multivariate time series forecasting has seen widely ranging applications in various domains, including finance, traffic, energy, and healthcare. To capture the sophisticated temporal patterns, plenty of research studies designed complex neural network architectures based on many variants of RNNs, GNNs, and Transformers. However, complex models are often com

Kailong Yang, Zehua Zhao

In this paper, we prove scattering asymptotics for the 2D (discrete dimension) cubic resonant system. This scattering result was used in Zhao \cite{Z1} as an assumption to obtain the scattering for cubic NLS on $\mathbb{R}^2\times \mathbb{T}^2$ in $H^1$ space. Moreover, the 1D analogue is proved in Yang-Zhao \cite{YZ}. Though the scheme is also tightly based

Renjun Duan, Dongcheng Yang, Hongjun Yu

Although the compressible fluid limit of the Boltzmann equation with cutoff has been well investigated in [6] and [13], it still remains largely open to obtain analogous results in case of the angular non-cutoff or even in the grazing limit which gives the Landau equation, essentially due to the velocity diffusion effect of collision operator such that $L^\i

Sandy Ardianto, Hsueh-Ming Hang, Wen-Huang Cheng

We design a fast car detection and tracking algorithm for traffic monitoring fisheye video mounted on crossroads. We use ICIP 2020 VIP Cup dataset and adopt YOLOv5 as the object detection base model. The nighttime video of this dataset is very challenging, and the detection accuracy (AP50) of the base model is about 54%. We design a reliable car detection an

YuanDong Wang, ZhiFan Zhang, Zhen-Gang Zhu, Gang Su

It is known that intrinsic currents in magnetic metals often appear in the direction perpendicular to the external field for linear and nonlinear responses. Distinct from three kinds of known nonlinear currents, namely, the Drude contribution, the Berry curvature dipole induced current and the Berry connection polarization induced current, here we report a i

Haoyi Xiu, Xin Liu, Weimin Wang, Kyoung-Sook Kim

Modeling the local surface geometry is challenging in 3D point cloud understanding due to the lack of connectivity information. Most prior works model local geometry using various convolution operations. We observe that the convolution can be equivalently decomposed as a weighted combination of a local and a global component. With this observation, we explic

Yusuke Tanaka, Yuki Shirai, Xuan Lin, Alexander Schperberg

This paper introduces SCALER, a quadrupedal robot that demonstrates climbing on bouldering walls, overhangs, ceilings and trotting on the ground. SCALER is one of the first high-degrees of freedom four-limbed robots that can free-climb under the Earth's gravity and one of the most mechanically efficient quadrupeds on the ground. Where other state-of-the-art

Ahmed M. G. Ahmed, Alle Adjiri, Solomon Manukure

We aim to present and analyze a nonlinear nonlocal reverse-spacetime fifth-order scalar Sasa-Satsuma equation, based on a nonlocal $5 \times 5$ matrix AKNS spectral problem. Starting from a nonlocal matrix AKNS spectral problem, local and nonlocal symmetry relations are derived from a group of rotations. A kind of Riemann-Hilbert problem is formulated, which

Wendi Zuo, Xinmin Hou

Clustering by fast search and find of density peaks (DPC) (Since, 2014) has been proven to be a promising clustering approach that efficiently discovers the centers of clusters by finding the density peaks. The accuracy of DPC depends on the cutoff distance ($d_c$), the cluster number ($k$) and the selection of the centers of clusters. Moreover, the final al

Xuan Zhao, Ziyan Li, Xiaoli Li

In this work, fourth-order compact block-centered finite difference (CBCFD) schemes combined with the Crank-Nicolson discretization are constructed and analyzed for solving parabolic integro-differential type non-Fickian flows in one-dimensional and two-dimensional cases. Stability analyses of the constructed schemes are derived rigorously. We also obtain th

William M. Campbell, Serge Galliou, Michael E. Tobar, Maxim Goryachev

We investigate the electromechanical properties of quartz bulk acoustic wave resonators at extreme cryogenic temperatures. By applying a DC bias voltage, we demonstrate broad frequency tuning of high-Q phonon modes in a quartz bulk acoustic wave cavity at cryogenic temperatures of 4 K and 20 mK. More than 100 line-widths of tuning of the resonance peak witho

Pengcheng Zuo, Dong Ma, Yang Chen

A photonics-based short-time Fourier transform (STFT) system is proposed and experimentally demonstrated based on stimulated Brillouin scattering (SBS) without using high-frequency electronic devices and equipment. The wavelength of a distributed feedback laser diode is periodically swept by using a low-speed periodic sawtooth/triangular driving current. The

M. Sharif, Shazmeena Iltaf

This paper investigates the behavior of anisotropic static spheres that are constructed by employing a minimal geometric deformation in the framework of $f(R,T^{2})$ gravity ($T^{2}=T_{\zeta\nu}T^{\zeta\nu}$, $R$ is the Ricci scalar and $T_{\zeta\nu}$ is the energy-momentum tensor). We consider a spherical setup with two sources: seed and additional. It is a

Haoyi Xiu, Xin Liu, Weimin Wang, Kyoung-Sook Kim

Learning point clouds is challenging due to the lack of connectivity information, i.e., edges. Although existing edge-aware methods can improve the performance by modeling edges, how edges contribute to the improvement is unclear. In this study, we propose a method that automatically learns to enhance/suppress edges while keeping the its working mechanism cl

Yuhang Wang, Guiyu Cao, Liang Pan

High-order gas-kinetic scheme (HGKS) has become a workable tool for the direct numerical simulation (DNS) of turbulence. In this paper, to accelerate the computation, HGKS is implemented with the graphical processing unit (GPU) using the compute unified device architecture (CUDA). To conduct the much large-scale DNS of turbulence, HGKS also be further upgrad

Chang Liu, Gang Yang, Shuo Wang, Hangxu Wang

Existing RGB-D SOD methods mainly rely on a symmetric two-stream CNN-based network to extract RGB and depth channel features separately. However, there are two problems with the symmetric conventional network structure: first, the ability of CNN in learning global contexts is limited; second, the symmetric two-stream structure ignores the inherent difference

Alessandra Carneiro, Lorena Nascimento, Mauricio Noernberg, Carmem Hara

Portuguese man-of-war (PMW) is a gelatinous organism with long tentacles capable of causing severe burns, thus leading to negative impacts on human activities, such as tourism and fishing. There is a lack of information about the spatio-temporal dynamics of this species. Therefore, the use of alternative methods for collecting data can contribute to their mo

Xianfu Wang, Ziyuan Wang

We propose a Bregman inertial forward-reflected-backward (BiFRB) method for nonconvex composite problems. Our analysis relies on a novel approach that imposes general conditions on implicit merit function parameters, which yields a stepsize condition that is independent of inertial parameters. In turn, a question of Malitsky and Tam regarding whether FRB can

Darko Stosic, Dusan Stosic, Tatijana Stosic, Borko Stosic

A novel heuristic approach is proposed here for time series data analysis, dubbed Generalized weighted permutation entropy, which amalgamates and generalizes beyond their original scope two well established data analysis methods: Permutation entropy, and Weighted permutation entropy. The method introduces a scaling parameter to discern the disorder and compl

Haotao Wang, Junyuan Hong, Jiayu Zhou, Zhangyang Wang

Increasing concerns have been raised on deep learning fairness in recent years. Existing fairness-aware machine learning methods mainly focus on the fairness of in-distribution data. However, in real-world applications, it is common to have distribution shift between the training and test data. In this paper, we first show that the fairness achieved by exist

Chang Liu, Yugong Luo, Pengfei Li, Chunhui Xing

Vehicle platoon often face the problem of lack of scalability of maneuvers in practical applications. Once a new scenario is added, the original program may no longer be available. To deal with this problem, this paper introduces a two-dimensional maneuver management framework with a fault-tolerant mechanism on the basis of the proposed hierarchical architec

Zhibo Yang, Sounak Mondal, Seoyoung Ahn, Gregory Zelinsky

The prediction of human gaze behavior is important for building human-computer interactive systems that can anticipate a user's attention. Computer vision models have been developed to predict the fixations made by people as they search for target objects. But what about when the image has no target? Equally important is to know how people search when they c

Fu-Tsun Wei

The aim of this paper is to determine all algebraic relations among various special gamma values over function fields, and prove a Chowla-Selberg-type formula for quasi-periods of CM abelian $t$-modules. Our results are based on the intrinsic relations between gamma values in question and periods of CM dual $t$-motives, which are interpreted in terms of thei

Tianlong Chen, Peihao Wang, Zhiwen Fan, Zhangyang Wang

Neural Radiance Field (NeRF) regresses a neural parameterized scene by differentially rendering multi-view images with ground-truth supervision. However, when interpolating novel views, NeRF often yields inconsistent and visually non-smooth geometric results, which we consider as a generalization gap between seen and unseen views. Recent advances in convolut

Ming-Jian Gao, Hong Wu, Jun-Hong An

Hosting unique drumhead surface states enclosed by nodal lines, topological nodal-line semimetals exhibit novel transport phenomena. Thus, the exploration of topological semimetals with different nodal-line structures has attracted much attention. In this paper, we first find a second-order nodal line semimetal (SONLS), which has coexisting hinge Fermi arcs

Ling Liu, Yingqi Tian, Chungen Liu

Water autoionization plays a critical role in determining pH and properties of various chemical and biological processes occurring in the water mediated environment. The strikingly unsymmetrical potential energy surface of the dissociation process poses a great challenge to the mechanistic study. Here, we demonstrate that reliable sampling of the ionization

H. Blas, J. J. Monsalve, R. Quicaño, J. R. V. Pereira

A two-dimensional field theory of a fermion chirally coupled to Toda field plus a scalar self-coupling potential is considered. Using techniques of integrable systems we obtain analytical zero modes, in-gap states and bound states in the continuum (BIC) for topological configurations of the scalar field. Fermion-soliton duality mappings are uncovered for the

Haotao Wang, Aston Zhang, Yi Zhu, Shuai Zheng

Existing out-of-distribution (OOD) detection methods are typically benchmarked on training sets with balanced class distributions. However, in real-world applications, it is common for the training sets to have long-tailed distributions. In this work, we first demonstrate that existing OOD detection methods commonly suffer from significant performance degrad

Munsi Afif Aziz, Bishwajit Prasad Gond, Srijita Nandi, Soujanya Ray

Quantum cryptography was proposed as a counter to the capacity of quantum computers to break classical cryptosystems. A broad subclass of quantum cryptography, called quantum key distribution (QKD), relies on quantum mechanical process for secure distribution of the keys. Quantum channels are inherently noisy, and therefore these protocols will be susceptibl

Danpeng Chen, Shuai Wang, Weijian Xie, Shangjin Zhai

In this paper, we propose a tightly-coupled SLAM system fused with RGB, Depth, IMU and structured plane information. Traditional sparse points based SLAM systems always maintain a mass of map points to model the environment. Huge number of map points bring us a high computational complexity, making it difficult to be deployed on mobile devices. On the other