July 2023 arXiv papers — page 50

Pranab J. Deka, Ralf Kissmann, Lukas Einkemmer

Anisotropic diffusion is imperative in understanding cosmic ray diffusion across the Galaxy, the heliosphere, and the interplay of cosmic rays with the Galactic magnetic field. This diffusion term contributes to the highly stiff nature of the cosmic ray transport equation. To conduct numerical simulations of time-dependent cosmic ray transport, implicit inte

Ioannis Diamantis

In this paper we present two different ways for computing the Kauffman bracket skein module of $S^1\times S^2$, ${\rm KBSM}\left(S^1\times S^2\right)$, via braids. We first extend the universal Kauffman bracket type invariant $V$ for knots and links in the Solid Torus ST, which is obtained via a unique Markov trace constructed on the generalized Temperley-Li

Tianan Li, Zhehan Chen, Huan Liu, Chen Wang

Depth completion is crucial for many robotic tasks such as autonomous driving, 3-D reconstruction, and manipulation. Despite the significant progress, existing methods remain computationally intensive and often fail to meet the real-time requirements of low-power robotic platforms. Additionally, most methods are designed for opaque objects and struggle with

Dominic Breit, Prince Romeo Mensah, Sebastian Schwarzacher, Pei Su

We consider the interaction of a viscous incompressible fluid with a flexible shell in three space dimensions. The fluid is described by the three-dimensional incompressible Navier--Stokes equations in a domain that is changing in accordance with the motion of the structure. The displacement of the latter evolves along a visco-elastic shell equation. Both ar

Jürgen Struckmeier

Beam dynamics calculations that are based on the Vlasov equation do not permit the the treatment of stochastic phenomena such as intra-beam scattering. If the nature of the stochastic process can be regarded as a Markov process, we are allowed to use the Fokker-Planck equation to describe the change of the phase space volume the beam occupies. From the Fokke

Mohadese Karimi, Mohsen Amini, Morteza Soltani, Mozhgan Sadeghizadeh

The quantization of conductance in the presence of non-magnetic point defects is a consequence of topological protection and the spin-momentum locking of helical edge states in two-dimensional topological insulators. This protection ensures the absence of backscattering of helical edge modes in the quantum Hall phase of the system. However, our study focuses

Yongkun Du, Zhineng Chen, Caiyan Jia, Xiaoting Yin

Scene text recognition (STR) methods have struggled to attain high accuracy and fast inference speed. Autoregressive (AR)-based models implement the recognition in a character-by-character manner, showing superiority in accuracy but with slow inference speed. Alternatively, parallel decoding (PD)-based models infer all characters in a single decoding pass, o

Chiara Bigi, Sahar Pakdel, Michał J. Winiarski, Pasquale Orgiani

Intermetallics are an important playground to stabilize a large variety of physical phenomena, arising from their complex crystal structure. The ease of their chemical tuneabilty makes them suitable platforms to realize targeted electronic properties starting from the symmetries hidden in their unit cell. Here, we investigate the family of the recently disco

Jürgen Struckmeier, Ingo Hofmann

Charged particle beams that remain stationary while passing through a transport channel are represented by ``self-consistent'' phase space distributions. As the starting point, we assume the external focusing forces to act continuously on the beam. If Liouville's theorem applies, an infinite variety of self-consistent particle phase space distributions exist

Paraskevi Nousi, Loukia Avramelou, Georgios Rodinos, Maria Tzelepi

Financial portfolio management describes the task of distributing funds and conducting trading operations on a set of financial assets, such as stocks, index funds, foreign exchange or cryptocurrencies, aiming to maximize the profit while minimizing the loss incurred by said operations. Deep Learning (DL) methods have been consistently excelling at various t

Zijie Zeng, Lele Sha, Yuheng Li, Kaixun Yang

The recent large language models (LLMs), e.g., ChatGPT, have been able to generate human-like and fluent responses when provided with specific instructions. While admitting the convenience brought by technological advancement, educators also have concerns that students might leverage LLMs to complete their writing assignments and pass them off as their origi

Shicong Liu, Zhen Gao, Gaojie Chen, Yu Su

The Space-Air-Ground-Sea integrated network calls for more robust and secure transmission techniques against jamming. In this paper, we propose a textual semantic transmission framework for robust transmission, which utilizes the advanced natural language processing techniques to model and encode sentences. Specifically, the textual sentences are firstly spl

Tiziano Dalmonte, Andrea Mazzullo, Ana Ozaki, Nicolas Troquard

Modal logics are widely used in multi-agent systems to reason about actions, abilities, norms, or epistemic states. Combined with description logic languages, they are also a powerful tool to formalise modal aspects of ontology-based reasoning over an object domain. However, the standard relational semantics for modalities is known to validate principles dee

Kesong Wu, Xianbin Cao, Peng Yang, Zongyang Yu

This paper is concerned with the issue of improving video subscribers' quality of experience (QoE) by deploying a multi-unmanned aerial vehicle (UAV) network. Different from existing works, we characterize subscribers' QoE by video bitrates, latency, and frame freezing and propose to improve their QoE by energy-efficiently and dynamically optimizing the mult

Rui Meng, Fangzhou Zhu, Xiqi Cheng, Xiaodong Xu

The future 6G-enabled IoT will facilitate seamless global connectivity among ubiquitous wireless devices, but this advancement also introduces heightened security risks such as spoofing attacks. Physical-Layer Authentication (PLA) has emerged as a promising, inherently secure, and energy-efficient technique for authenticating IoT terminals. Nonetheless, the

Ziwei Zhu, Changhao Shan, Bihong Zhang, Jian Yu

Spoken languages show significant variation across mandarin and accent. Despite the high performance of mandarin automatic speech recognition (ASR), accent ASR is still a challenge task. In this paper, we introduce meta-learning techniques for fast accent domain expansion in mandarin speech recognition, which expands the field of accents without deterioratin

Nicolas Broutin, Jean-François Marckert

We give an explicit construction of the scaling limit of the minimum spanning tree of the complete graph. The limit object is described using a recursive construction involving the convex minorants of a Brownian motion with parabolic drift (and countably many i.i.d. uniform random variables); we call it the Brownian parabolic tree. Aside from the new represe

Richard Evan Schwartz

In this paper I will unite two games, symplectic billiards and tiling billiards. The new game is called symplectic tiling billiards. I will prove a result about periodic orbits of symplectic tiling billiards in a very special case and then show how this result combines with the construction in Thurston's paper {\it Shapes of Polyhedra\/} to give hyperbolic s

Takumi Maegawa

We recall the notion of twisted parametrized spectra defined by Douglas and provide a sufficient condition for an $\infty$-category of twisted parametrized module spectra to be untwisted over an even-periodic $E_2$-ring. It is an easy consequence of the universal property of Thom spectra. We also investigate a genuine equivariant generalization based on the

Daniel Hug, Rolf Schneider

Cauchy's surface area formula says that for a convex body $K$ in $n$-dimensional Euclidean space the mean value of the $(n-1)$-dimensional volumes of the orthogonal projections of $K$ to hyperplanes is a constant multiple of the surface area of $K$. We prove an analogous formula, with the volumes of the projections replaced by their moment vectors. This requ

Haonan Guo, Xin Su, Chen Wu, Bo Du

Buildings are the basic carrier of social production and human life; roads are the links that interconnect social networks. Building and road information has important application value in the frontier fields of regional coordinated development, disaster prevention, auto-driving, etc. Mapping buildings and roads from very high-resolution (VHR) remote sensing

Youzhi Liang, Wen Liang

The utilization of biometric authentication with pattern images is increasingly popular in compact Internet of Things (IoT) devices. However, the reliability of such systems can be compromised by image quality issues, particularly in the presence of high levels of noise. While state-of-the-art deep learning algorithms designed for generic image denoising hav

Huw Price

One of the basic principles of risk management is that we should always keep an eye on ways that things could go badly wrong, even if they seem unlikely. The more disastrous a potential failure, the more improbable it needs to be, before we can safely ignore it. This principle may seem obvious, but it is easily overlooked in public discourse about risk, even

Sachin Kadam, Dong In Kim

Vehicle count prediction is an important aspect of smart city traffic management. Most major roads are monitored by cameras with computing and transmitting capabilities. These cameras provide data to the central traffic controller (CTC), which is in charge of traffic control management. In this paper, we propose a joint CNN-LSTM-based semantic communication

Enda Hua, Liang Si, Kunjie Dai, Qing Wang

In transition-metal-oxide heterostructures, the anomalous Hall effect (AHE) is a powerful tool for detecting the magnetic state and revealing intriguing interfacial magnetic orderings. However, achieving a larger AHE at room temperature in oxide heterostructures is still challenging due to the dilemma of mutually strong spin-orbit coupling and magnetic excha

Neha Gupta, Aditya Maheshwari

This paper introduces the Generalized Fractional Compound Poisson Process (GFCPP), which claims to be a unified fractional version of the compound Poisson process (CPP) that encompasses existing variations as special cases. We derive its distributional properties, generalized fractional differential equations, and martingale properties. Some results related

Kai Zhu, Ran Li, Xiaoyue Cao, Shengdong Lu

The second moment of the stellar velocity within the effective radius, denoted by $\sigma_{\rm e}^2$, is a crucial quantity in galaxy studies as it provides insight into galaxy properties and their mass distributions. However, large spectroscopic surveys typically do not measure $\sigma_{\rm e}$ directly, instead providing $\sigma_{\rm aper}$, the second mom

Sourendu Gupta

The spin polarization of heavy quarks in heavy-ion collisions at the LHC is estimated from effective field theories (EFTs). One EFT is similar to the HQET used at zero temperature. This gives a coupling of the heavy quark spin to colour and electromagnetic fields in heavy-ion collisions. The second EFT describes the interaction of heavy quarks and hydrodynam

Matthias Langer, Harald Woracek

We prove Abelian and Tauberian theorems for regularised Cauchy transforms of positive Borel measures on the real line whose distribution functions grow at most polynomially at infinity. In particular, we relate the asymptotics of the distribution functions to the asymptotics of the regularised Cauchy transform.

Gennaro Auricchio, Ruixiao Zhang, Jie Zhang, Xiaohao Cai

Due to the large number of submissions that more and more conferences experience, finding an automatized way to well distribute the submitted papers among reviewers has become necessary. We model the peer-reviewing matching problem as a {\it bilevel programming (BP)} formulation. Our model consists of a lower-level problem describing the reviewers' perspecti

Clément Berthiere, Bin Chen, Hongjie Chen

We study the reflected entropy in $(1+1)$--dimensional Lifshitz field theory whose groundstate is described by a quantum mechanical model. Starting from tripartite Lifshitz groundstates, both critical and gapped, we derive explicit formulas for the R\'enyi reflected entropies reduced to two adjacent or disjoint intervals, directly in the continuum. We show t

Feng Zhang, Hu Liu, Fengrong Zhu, Jacob Oloketuyi

Ground-based cosmic ray experiments detect cosmic ray mainly by measuring the longitudinal and lateral distribution of secondary particles produced in the extensive air shower (EAS). The EAS of cosmic ray in the knee energy region is simulated via CORSIKA software. Several simulation samples with different energy, composition and zenith angles were carried o

Yousseif Elshahawy, Yassine El Kheir, Shammur Absar Chowdhury, Ahmed Ali

We introduce MyVoice, a crowdsourcing platform designed to collect Arabic speech to enhance dialectal speech technologies. This platform offers an opportunity to design large dialectal speech datasets; and makes them publicly available. MyVoice allows contributors to select city/country-level fine-grained dialect and record the displayed utterances. Users ca

Enrico Barausse, Kallol Dey, Marco Crisostomi, Akshay Panayada

The recent evidence of a stochastic background of gravitational waves in the nHz band by pulsar-timing array (PTA) experiments has shed new light on the formation and evolution of massive black hole binaries with masses $\sim 10^8$--$10^9 M_\odot$. The PTA data are consistent with a population of such binaries merging efficiently after the coalescence of the

Xiangyu Lyu, En-Kun Li, Yi-Ming Hu

We present a Bayesian parameter estimation progress to infer the stellar mass binary black hole properties by TianQin, LISA, and TianQin+LISA.Two typical stellar mass black hole binary systems, GW150914 and GW190521 are chosen as the fiducial sources. In this work, we establish the ability of TianQin to infer the parameters of those systems and first apply t

Jongsu Kim

We make classifications of gradient Ricci solitons $(M, g, f)$ with harmonic Weyl curvature. As a local classification, we prove that the soliton metric $g$ is locally isometric to one of the following four types: an Einstein manifold, the Riemannian product of a Ricci flat manifold and an Einstein manifold, a warped product of $\mathbb{R}$ and an Einstein m

Zhihan Jiang, Handi Chen, Rui Zhou, Jing Deng

The correlation between children's personal and family characteristics (e.g., demographics and socioeconomic status) and their physical and mental health status has been extensively studied across various research domains, such as public health, medicine, and data science. Such studies can provide insights into the underlying factors affecting children's hea

Monika Gahalawat, Raul Fernandez Rojas, Tanaya Guha, Ramanathan Subramanian

While depression has been studied via multimodal non-verbal behavioural cues, head motion behaviour has not received much attention as a biomarker. This study demonstrates the utility of fundamental head-motion units, termed \emph{kinemes}, for depression detection by adopting two distinct approaches, and employing distinctive features: (a) discovering kinem

S. K. Verma, S. S. Mishra, N. K. Mukhopadhyay, T. P. Yadav

Magnesium hydride (MgH2) is the mostly used material for solid-state hydrogen storage. However, their slow kinetics and highly unfavorable thermodynamics make them unsuitable for the practical applications. The current study describes the unusual catalytic action of a new class of catalyst, a high-entropy alloy (HEA) of Al20Cr16Mn16Fe16Co16Ni16, on the de/re

Yiming Cui, Linjie Yang, Haichao Yu

Transformer-based detection and segmentation methods use a list of learned detection queries to retrieve information from the transformer network and learn to predict the location and category of one specific object from each query. We empirically find that random convex combinations of the learned queries are still good for the corresponding models. We then

Jayant Murthy, Richard C. Henry, James Overduin

We have modeled the diffuse background at the Galactic Poles in the far-ultraviolet (FUV: 1536 \AA) and the near-ultraviolet (NUV: 2316 \AA). The background is well-fit using a single-scattering dust model with an offset representing the extragalactic light plus any other contribution to the diffuse background. We have found a dust albedo of 0.35 -- 0.40 (FU

Ray Islam, Peter Sandborn

Prognostic and Health Management (PHM) has been widely applied to hardware systems in the electronics and non-electronics domains but has not been explored for software. While software does not decay over time, it can degrade over release cycles. Software health management is confined to diagnostic assessments that identify problems, whereas prognostic asses

Longxiang Zhang, Wenping Wang

Online streaming is an emerging market that address much attention. Assessing gaming skills from videos is an important task for streaming service providers to discover talented gamers. Service providers require the information to offer customized recommendation and service promotion to their customers. Meanwhile, this is also an important multi-modal machin

Marco Fabris, Giulio Fattore, Angelo Cenedese

This paper addresses the optimal time-invariant formation tracking problem with the aim of providing a distributed solution for multi-agent systems with second-order integrator dynamics. In the literature, most of the results related to multi-agent formation tracking do not consider energy issues while investigating distributed feedback control laws. In orde

Guan Shen, Jieru Zhao, Zeke Wang, Zhe Lin

Along with the fast evolution of deep neural networks, the hardware system is also developing rapidly. As a promising solution achieving high scalability and low manufacturing cost, multi-accelerator systems widely exist in data centers, cloud platforms, and SoCs. Thus, a challenging problem arises in multi-accelerator systems: selecting a proper combination

Marco Fabris, Marco D. Bellinazzi, Andrea Furlanetto, Angelo Cenedese

This paper deals with water management over open-channel networks (OCNs) subject to water height imbalance. The OCN is modeled by means of graph theoretic tools and a regulation scheme is designed basing on an outer reference generation loop for the whole OCN and a set of local controllers. Specifically, it is devised a fully distributed adaptive consensus-b

Yoshiki Masuyama, Natsuki Ueno, Nobutaka Ono

We propose an optimization-based method for reconstructing a time-domain signal from a low-dimensional spectral representation such as a mel-spectrogram. Phase reconstruction has been studied to reconstruct a time-domain signal from the full-band short-time Fourier transform (STFT) magnitude. The Griffin-Lim algorithm (GLA) has been widely used because it re

Yoshiki Masuyama, Xuankai Chang, Wangyou Zhang, Samuele Cornell

Neural speech separation has made remarkable progress and its integration with automatic speech recognition (ASR) is an important direction towards realizing multi-speaker ASR. This work provides an insightful investigation of speech separation in reverberant and noisy-reverberant scenarios as an ASR front-end. In detail, we explore multi-channel separation

Haruhi Mitani, Kin-ya Oda

There is renewed attention to whether we can observe the decoherence effect in neutrino oscillation due to the separation of wave packets with different masses in near-future experiments. As a contribution to this endeavor, we extend the existing formulation based on a single 1D Gaussian wave function to an amplitude between two distinct 3D Gaussian wave pac

Masoud Mokhtari, Mobina Mahdavi, Hooman Vaseli, Christina Luong

The functional assessment of the left ventricle chamber of the heart requires detecting four landmark locations and measuring the internal dimension of the left ventricle and the approximate mass of the surrounding muscle. The key challenge of automating this task with machine learning is the sparsity of clinical labels, i.e., only a few landmark pixels in a

Jorge Garcia-Hernandez, Roy Brouwer

Water markets represent a policy tool that aims at finding efficient water allocations among competing users by promoting reallocations from low-value to high-value uses. In Canada, water markets have been discussed and implemented at the provincial level; however, at the national level a study about the economic benefits of its implementation is still lacki

Andrew Keith Wilkinson

Garbage disposal is a challenging problem throughout the developed world. In Cyprus, as elsewhere, illegal ``fly-tipping" is a significant issue, especially in rural areas where few legal garbage disposal options exist. However, there is a lack of studies that attempt to measure the scale of this problem, and few resources available to address it. A method o

Kohei Shinohara, Atsushi Togo, Hikaru Watanabe, Takuya Nomoto

A spin space group provides a suitable way to fully exploit the symmetry of a spin arrangement with a negligible spin-orbit coupling. There has been a growing interest in applying spin symmetry analysis with the spin space group in the field of magnetism. However, there is no established algorithm to search for spin symmetry operations of the spin space grou

Longfei Chen, He Wang, Yang Ouyang, Yang Zhou

The provision of fire services plays a vital role in ensuring the safety of residents' lives and property. The spatial layout of fire stations is closely linked to the efficiency of fire rescue operations. Traditional approaches have primarily relied on mathematical planning models to generate appropriate layouts by summarizing relevant evaluation criteria.

Nicholas Roberts, Xintong Li, Dyah Adila, Sonia Cromp

Machine learning models -- including prominent zero-shot models -- are often trained on datasets whose labels are only a small proportion of a larger label space. Such spaces are commonly equipped with a metric that relates the labels via distances between them. We propose a simple approach to exploit this information to adapt the trained model to reliably p

Zhihao Chen, Qi Gao, Yi Zhang, Hongming Shan

While various deep learning methods have been proposed for low-dose computed tomography (CT) denoising, most of them leverage the normal-dose CT images as the ground-truth to supervise the denoising process. These methods typically ignore the inherent correlation within a single CT image, especially the anatomical semantics of human tissues, and lack the int

Andrew T. Walter, Ankit Kumar, Panagiotis Manolios

Teaching college students how to write rigorous proofs is a critical objective in courses that introduce formal reasoning. Over the course of several years, we have developed a mechanically-checkable style of calculational reasoning that we used to teach over a thousand freshman-level undergraduate students how to reason about computation in our "Logic and C

Da-Chuan Lu, Meng Zeng, Yi-Zhuang You

The Fermi surface symmetric mass generation (SMG) is an intrinsically interaction-driven mechanism that opens an excitation gap on the Fermi surface without invoking symmetry-breaking or topological order. We explore this phenomenon within a bilayer square lattice model of spin-1/2 fermions, where the system can be tuned from a metallic Fermi liquid phase to

Syed Masood A. S. Bukhari, Li-Gang Wang

Some aspects of atom-field interactions in curved spacetime are reviewed. Of great interest are quantum radiative and entanglement processes arising out of Rindler and black hole spacetimes, which involve the role of Hawking-Unruh and dynamical Casimir effects. Most of the discussion surrounds the radiative part of interactions. For this, we specifically rea

Yuzhao Mao, Di Lu, Xiaojie Wang, Yang Zhang

This paper concentrates on the understanding of interlocutors' emotions evoked in conversational utterances. Previous studies in this literature mainly focus on more accurate emotional predictions, while ignoring model robustness when the local context is corrupted by adversarial attacks. To maintain robustness while ensuring accuracy, we propose an emotion

Haonan Guo, Bo Du, Chen Wu, Xin Su

The efficacy of building footprint segmentation from remotely sensed images has been hindered by model transfer effectiveness. Many existing building segmentation methods were developed upon the encoder-decoder architecture of U-Net, in which the encoder is finetuned from the newly developed backbone networks that are pre-trained on ImageNet. However, the he

Haoyue Bai, Ceyuan Yang, Yinghao Xu, S. -H. Gary Chan

Deep neural networks achieve superior performance for learning from independent and identically distributed (i.i.d.) data. However, their performance deteriorates significantly when handling out-of-distribution (OoD) data, where the training and test are drawn from different distributions. In this paper, we explore utilizing the generative models as a data a

Weiyue Wu, Shaoshan Liu

Due to the cultural and governance differences of countries around the world, there currently exists a wide spectrum of AI regulation policy proposals that have created a chaos in the global AI regulatory space. Properly regulating AI technologies is extremely challenging, as it requires a delicate balance between legal restrictions and technological develop

Cong Wang, Yu-Ping Wang, Dinesh Manocha

We propose a novel method, LoLep, which regresses Locally-Learned planes from a single RGB image to represent scenes accurately, thus generating better novel views. Without the depth information, regressing appropriate plane locations is a challenging problem. To solve this issue, we pre-partition the disparity space into bins and design a disparity sampler

Masoud Zabihi, Yanyue Xie, Zhengang Li, Peiyan Dong

The production process of superconductive integrated circuits is complex and consumes significant amounts of resources and energy. Therefore, it is crucial to evaluate the environmental impact of this emerging technology. An attractive option for the next generation of superconductive technology is Adiabatic Quantum-Flux-Parametron (AQFP) devices. This study

Hong-Hai Nguyen, Ngumimi Karen Iyortsuun, Seungwon Kim, Hyung-Jeong Yang

The human brain remains continuously active, whether an individual is working or at rest. Mental activity is a daily process, and if the brain becomes excessively active, known as overload, it can adversely affect human health. Recently, advancements in early prediction of mental health conditions have emerged, aiming to prevent serious consequences and enha

K. Jeganathan, T. Harikrishnan, K. Prasanna Lakshmi, D. Nagarajan

This article deals with asynchronous server vacation and customer retrial facility in a multi-server queueing-inventory system. The Poisson process governs the arrival of a customer. The system is comprised of c identical servers, a finite-size waiting area, and a storage area containing S items. The service time is distributed exponentially. If each server

Zhirong Liu

In comparison to numerous enhanced sampling methods for equilbrium thermodynamics, accelerating simulations for kinetics and nonequilibrium statistics are relatively rare and less effective. Here we derive a time-reversal path sampling (tRPS) method based on the time reversibility to accelerate simulations for determining the transition rates between free-er

Yuchen Wu, Yuansong Xu, Shenghan Gao, Xingbo Wang

Livestream e-commerce integrates live streaming and online shopping, allowing viewers to make purchases while watching. However, effective marketing strategies remain a challenge due to limited empirical research and subjective biases from the absence of quantitative data. Current tools fail to capture the interdependence between live performances and feedba

Srivatsan Sridhar, Onur Ascigil, Navin Keizer, François Genon

The InterPlanetary File System (IPFS) is currently the largest decentralized storage solution in operation, with thousands of active participants and millions of daily content transfers. IPFS is used as remote data storage for numerous blockchain-based smart contracts, Non-Fungible Tokens (NFT), and decentralized applications. We present a content censorship

Yixin Li, Hongrong Qiu, Maolin Bo

Transition metal clusters have a broad spectrum of potential applications in electronic and magnetic devices owing to their unique properties. Protective shells such as fullerene C$_{80}$ can be introduced to improve their stability. In this study, we optimized five core shell structures, C$_{80}$+M$_{13}$ (V, Mn, Cr, Ni, Co), and calculated their electromag

Guangzhou Guo, Peng Wang, Houwen Wu, Haitang Yang

In this paper, we construct scalarized rotating black holes within the framework of Einstein-Maxwell-scalar models. These models incorporate non-minimal couplings that can induce tachyonic instabilities, leading to the spontaneous scalarization of Kerr-Newman (KN) black holes. By exploring the domain of existence, we observe that the presence of scalarized K

Junfeng Li, Changqing Yan

A traffic system is a random and complex large system, which is difficult to conduct repeated modelling and control research in a real traffic environment. With the development of automatic driving technology, the requirements for testing and evaluating the development of automatic driving technology are getting higher and higher, so the application of compu

Otto Romero

As is well known, we can average the eigenfunction $y^s$ of the hyperbolic Laplacian on the hyperbolic plane by $\Gamma$ a lattice in $\mathbf{SL}(2,\mathbb{R})$ to obtain an automorphic form, the non-holomorphic Eisenstein series $E_\mathfrak{a} (z,s)$. In this note, we choose a particular eigenfunction $y^s dx$ of the Hodge-Laplace operator for 1-forms on

Haonan Guo, Bo Du, Chen Wu, Chengxi Han

Change detection (CD) is an important yet challenging task in the Earth observation field for monitoring Earth surface dynamics. The advent of deep learning techniques has recently propelled automatic CD into a technological revolution. Nevertheless, deep learning-based CD methods are still plagued by two primary issues: 1) insufficient temporal relationship

Yuncheng You, Junyi Tu

A new mathematical model of memristive neural networks described by the partly diffusive reaction-diffusion equations with weak synaptic coupling is proposed and investigated. Under rather general conditions it is proved that there exists an absorbing set showing the dissipative dynamics of the solution semiflow in the energy space and multiple ultimate boun

Baochen Yan, Jiahe Lan, Zheng Yan

Voice Recognition Systems (VRSs) employ deep learning for speech recognition and speaker recognition. They have been widely deployed in various real-world applications, from intelligent voice assistance to telephony surveillance and biometric authentication. However, prior research has revealed the vulnerability of VRSs to backdoor attacks, which pose a sign

Haiyan Huang, Qing Liu, Wenhui Zhang, Yajiang Chen

By numerically solving the Bogoliubov-de Gennes equations, we report a novel $\pi$-type vortex state whose order parameter near the core undergoes an extraordinary $\pi$-phase change for a quantum-confined extreme type-II $s$-wave superconductor. Its supercurrent behaves as the cube of the radial coordinate near the core, and its local density of states spec

Zui Tao, Wenjin Zhao, Bowen Shen, Patrick Knüppel

The electron's kinetic energy plays a pivotal role in magnetism. While virtual electron hopping promotes antiferromagnetism in an insulator, the real process usually favors ferromagnetism. But in kinetically frustrated systems, such as hole doped triangular lattice Mott insulators, real hopping has been shown to favor antiferromagnetism. Kinetic frustration

Dong-Dong Hou, Tian-Tian Zheng, Rui-Rui Guo

We construct four infinite families of chiral $3$-polytopes of type $\{4, 8\}$, with $1024m^4$, $2048m^4$, $4096m^4$ and $8192m^4$ automorphisms for every positive integer $m$, respectively. The automorphism groups of these polytopes are solvable groups, and when $m$ is a power of $2$, they provide examples with automorphism groups of order $2^n$ where $n \g

Forrest McKee, David Noever

The paper applies reinforcement learning to novel Internet of Thing configurations. Our analysis of inaudible attacks on voice-activated devices confirms the alarming risk factor of 7.6 out of 10, underlining significant security vulnerabilities scored independently by NIST National Vulnerability Database (NVD). Our baseline network model showcases a scenari

Zeyuan He, Simon D. Guest

This note is a complete library of symbolic parametrized expressions for both real and complexified configuration spaces of a planar 4-bar linkage. Building upon the previous work from Izmestiev (2015), this library expands on the expressions by incorporating all four rotational angles across all possible linkage length choices, along with the polynomial rel

Shoken Kaneko, Ramani Duraiswami

A generalization of a recently introduced recursive numerical method for the exact evaluation of integrals of regular solid harmonics and their normal derivatives over simplex elements in $\mathbb{R}^3$ is presented. The original Quadrature to Expansion (Q2X) method achieves optimal per-element asymptotic complexity, however, it considered only constant dens

Alexei A. Deriglazov

Equations of a rotating body with one point constrained to move freely on a plane (dancing top) are deduced from the Lagrangian variational problem. They formally look like the Euler-Poisson equations of a heavy body with fixed point, immersed in a fictitious gravity field. Using this analogy, we have found examples of analytical solutions for the case of a

Stan Alama, Lia Bronsard, Silas Vriend

In this article we consider the isoperimetric problem for partitioning the plane into three disjoint domains, one having unit area and the remaining two having infinite area. We show that the only solution, up to rigid motions of the plane, is a lens cluster consisting of circular arcs containing the finite area region, attached to a single axis, with two tr

Yang Ouyang, Yuchen Wu, He Wang, Chenyang Zhang

Simulation-based Medical Education (SBME) has been developed as a cost-effective means of enhancing the diagnostic skills of novice physicians and interns, thereby mitigating the need for resource-intensive mentor-apprentice training. However, feedback provided in most SBME is often directed towards improving the operational proficiency of learners, rather t

Jiaqi Luo, Shixin Xu

Deep learning models have become popular in the analysis of tabular data, as they address the limitations of decision trees and enable valuable applications like semi-supervised learning, online learning, and transfer learning. However, these deep-learning approaches often encounter a trade-off. On one hand, they can be computationally expensive when dealing

Xiaoping Zhai

This paper presents a global stability result on perturbations near a background magnetic field to the 2D incompressible magnetohydrodynamic (MHD) equations with only magnetic diffusion on the periodic domain. The stability result provides a significant example for the stabilizing effects of the magnetic field on electrically conducting fluids. In addition,

J. S. C. Prentice

We study error propagation in both an explicit and an implicit method for solving Volterra integro-differential equations. We determine the relationship between local and global errors. We derive upper bounds for the global error, and show that the global order for both methods is expected to be first-order. A few numerical examples illustrate our results.

Jixia Gao, Haipeng Qu

Assume G is a nilpotent group of class > 3 in which every proper subgroup has class at most 3. In this note, we give the exact upper bound of class of G.

Mohammad Samiul Arshad, William J. Beksi

Accurate reconstruction of both the geometric and topological details of a 3D object from a single 2D image embodies a fundamental challenge in computer vision. Existing explicit/implicit solutions to this problem struggle to recover self-occluded geometry and/or faithfully reconstruct topological shape structures. To resolve this dilemma, we introduce LIST,

F. Fung, E. Rosenfeld, J. D. Schaefer, A. Kabcenell

Solid state spin qubits are promising candidates for quantum information processing, but controlled interactions and entanglement in large, multi-qubit systems are currently difficult to achieve. We describe a method for programmable control of multi-qubit spin systems, in which individual nitrogen-vacancy (NV) centers in diamond nanopillars are coupled to m

David M T Kuo

In this study, we investigate the charge transport properties of semiconducting armchair graphene nanoribbons (AGNRs) and heterostructures through their topological states (TSs), with a specific focus on the Coulomb blockade region. Our approach employs a two-site Hubbard model that takes into account both intra- and inter-site Coulomb interactions. Using th

Wenlong Liu, Xiangliang Kong, Fan Guo, Lulu Zhao

Ground level enhancements (GLEs) are extreme solar energetic particle (SEP) events that are of particular importance in space weather. In solar cycle 24, two GLEs were recorded on 2012 May 17 (GLE 71) and 2017 September 10 (GLE 72), respectively, by a range of advanced modern instruments. Here we conduct a comparative analysis of the two events by focusing o

Nikodem Popławski

We consider gravitational collapse of a sphere of a fluid with torsion generated by spin, which forms a black hole. We use the Tolman metric and the Einstein$-$Cartan field equations with a relativistic spin fluid as a source. We show that gravitational repulsion of torsion prevents a singularity, replacing it with a nonsingular bounce. Quantum particle crea

Zhengbing He, Mirco Nanni, Luca Pappalardo, Paolo Santi

It is commonly expected that drivers maintain a driving speed that is lower than or around the posted speed limit, as failure to obey may result in safety risks and fines. By taking randomly selected road segments as examples, this study compares the percentages of speeding vehicles in five countries worldwide, namely, two European countries (Germany and Ita

Weicheng Xue, Shaohong Jia, Hongyu Wang, Zhe Chen

This study explores the noise reduction achieved by airfoils with serrated trailing edges in a low turbulence wind tunnel, focusing on acoustic spectral characteristics and wake flow field measurements. We analyze the effects of various factors, including Reynolds number, angle of attack, serration parameters, and model type, on sound power levels and far-fi

Bo Yang, Zhihao Zhang Kirisame Marisa, Kai Shi

The Java and Scala community has built a very successful big data ecosystem. However, most of neural networks running on it are modeled in dynamically typed programming languages. These dynamically typed deep learning frameworks treat neural networks as differentiable expressions that contain many trainable variable, and perform automatic differentiation on

Brian Hopkins, Aram Tangboonduangjit

In 2013, Joerg Arndt recorded that the Fibonacci numbers count integer compositions where the first part is greater than the second, the third part is greater than the fourth, etc. We provide a new combinatorial proof that verifies his observation using compositions with only odd parts as studied by De Morgan. We generalize the descent condition to establish

Daniel Huybrechts

The surface of lines in a cubic fourfold intersecting a fixed line splits motivically into two parts, one of which resembles a K3 surface. We define the analogue of the Beauville-Voisin class and study the push-forward map to the Fano variety of all lines with respect to the natural splitting of the Bloch-Beilinson filtration introduced by Mingmin Shen and C