May 2022 arXiv papers — page 16

Do-Myoung Lee, Yeachan Kim, Chang-gyun Seo

Deep neural networks (DNNs) have a high capacity to completely memorize noisy labels given sufficient training time, and its memorization, unfortunately, leads to performance degradation. Recently, virtual adversarial training (VAT) attracts attention as it could further improve the generalization of DNNs in semi-supervised learning. The driving force behind

Shaoshen Wang, Yanbin Liu, Ling Chen, Chengqi Zhang

Unsupervised anomaly detection (AD) is a challenging task in realistic applications. Recently, there is an increasing trend to detect anomalies with deep neural networks (DNN). However, most popular deep AD detectors cannot protect the network from learning contaminated information brought by anomalous data, resulting in unsatisfactory detection performance

Joseph Cho, Katrin Leschke, Yuta Ogata

We provide explicit parametrisations of all Darboux transforms of Delaunay surfaces. Using the Darboux transformation on a multiple cover, we obtain this way new closed CMC surfaces with dihedral symmetry. These can be used to construct closed same-lobed CMC multibubbletons by applying Bianchi permutability.

Mohamed Chabab, Samir Iraoui

In this work, we performed a detailed study of the fractional order phase transition (FPT) for several AdS black hole prototypes [1]. Our objective is to see whether the FPT 4/3 order at critical points reported in [2] is universal. Our analysis shows two remarkable features: Firstly, the FPT is located at 4/3 order only when the black hole possesses a spher

Walter Boscheri, Michael Dumbser, Elena Gaburro

We propose a new high order accurate nodal discontinuous Galerkin (DG) method for the solution of nonlinear hyperbolic systems of partial differential equations (PDE) on unstructured polygonal Voronoi meshes. Rather than using classical polynomials of degree N inside each element, in our new approach the discrete solution is represented by piecewise continuo

Arne Brataas

Spin transfer torque and spin pumping are central reciprocal phenomena in spintronics. These phenomena occur in hybrid systems of normal metals and magnets. Spin transfer is the conversion of spin currents in metals to a torque on the magnetization of magnets. Spin pumping is the emission of spin currents from precessing magnets. Here, we demonstrate a gener

A. Abraray, R. Pereira, K. Kaboutari, S. Maslovski

A reconfigurable microwave reflectarray metasurface (MS) is investigated for beamforming applications. The reflected beam direction is changed by applying external dc voltages, which create a reflection phase gradient on the structure. The studied MS comprises a chessboard-like array of metallic patches placed over a grounded dielectric slab with metallic vi

Markus Nöth

The method developed by Van Dijk, Nogami and Toyama for obtaining the time-evolved wave function of a decaying quantum system is generalized to potentials and initial wave functions of non-compact support. The long time asymptotic behavior is extracted and employed to predict the timescale for the onset of non-exponential decay. The method is illustrated wit

David Stenger, Maximilian Nitsch, Dirk Abel

The performance of a guidance, navigation and control (GNC) system of an autonomous underwater vehicle (AUV) heavily depends on the correct tuning of its parameters. Our objective is to automatically tune these parameters with respect to arbitrary high-level control objectives within different operational scenarios. In contrast to literature, an overall tuni

Yun-Fan Liu, Wei Dai, Ben-Wei Zhang, Enke Wang

When an energetic parton traverses the hot QCD medium it may suffer multiple scattering and lose its energy. The medium-induced gluon radiation for a massive quark will be suppressed relative to that of a light quark due to the dead-cone effect. The development of new declustering techniques of jet evolution makes a direct study of the dead-cone effect in th

Masahiro Fujii, Ryosuke Kutsuzawa, Yasunari Suzuki, Yoshifumi Nakata

Random dynamics in isolated quantum systems is of practical use in quantum information and is of theoretical interest in fundamental physics. Despite a large number of theoretical studies, it has not been addressed how random dynamics can be verified from experimental data. In this paper, based on an information-theoretic formulation of random dynamics, i.e.

Martina Tsvetanova, Kai Sotthewes, Harold J. W. Zandvliet

We have derived exact expressions for the domain wall free energy along the three high-symmetry directions of a triangular lattice with anisotropic nearest-neighbor interactions. The triangular lattice undergoes an orderdisorder phase transition at a temperature Tc given by exp(-(e1+e2)/2kTc)+ exp(-(e2+e3)/2kTc)+ exp(-(e3+e1)/2kTc)= 1, where e1, e2, e3 are t

Peiying Zhang, Ning Chen, Shibao Li, Kim-Kwang Raymond Choo

Network Virtualization (NV) is an emerging network dynamic planning technique to overcome network rigidity. As its necessary challenge, Virtual Network Embedding (VNE) enhances the scalability and flexibility of the network by decoupling the resources and services of the underlying physical network. For the future multi-domain physical network modeling with

Geraldo F. Oliveira, Amirali Boroumand, Saugata Ghose, Juan Gómez-Luna

Today's computing systems require moving data back-and-forth between computing resources (e.g., CPUs, GPUs, accelerators) and off-chip main memory so that computation can take place on the data. Unfortunately, this data movement is a major bottleneck for system performance and energy consumption. One promising execution paradigm that alleviates the data move

James J Gugger, Nishant Sinha, Yiming Huang, Alexa Walter

The trajectory of an individual's recovery after traumatic brain injury (TBI) is heterogeneous, with complete recovery in some cases but persistent disability in others. We hypothesized that changes in structural brain network abnormalities guide the trajectory of an individual's recovery post-injury. Our objective was to characterize the variability in reco

Shijie Huang, Jinlong Lei, Yiguang Hong

No-regret learning has been widely used to compute a Nash equilibrium in two-person zero-sum games. However, there is still a lack of regret analysis for network stochastic zero-sum games, where players competing in two subnetworks only have access to some local information, and the cost functions include uncertainty. Such a game model can be found in securi

Guangji Chen, Qingqing Wu

In this paper, we develop a unified dynamic intelligent reflecting surface (IRS) beamforming framework to boost the sum computation rate of an IRS-aided mobile edge computing (MEC) system, where each device follows a binary offloading policy. Specifically, the task of each device has to be either executed locally or offloaded to MEC servers as a whole with t

Changyu Hou, Jun Wang, Yixuan Qiao, Peng Jiang

Large scale pre-training models have been widely used in named entity recognition (NER) tasks. However, model ensemble through parameter averaging or voting can not give full play to the differentiation advantages of different models, especially in the open domain. This paper describes our NER system in the SemEval 2022 task11: MultiCoNER. We proposed an eff

Zheng Xiong, Liangyu Chai, Wenxi Liu, Yongtuo Liu

Crowd image is arguably one of the most laborious data to annotate. In this paper, we devote to reduce the massive demand of densely labeled crowd data, and propose a novel weakly-supervised setting, in which we leverage the binary ranking of two images with high-contrast crowd counts as training guidance. To enable training under this new setting, we conver

H. Gacki, Ł. Stettner

In the paper we study a measure version of the evolutionary nonlinear Boltzmann-type equation in which we admit a random number of collisions of particles. We consider first a stationary model and use two methods to find its fixed points: the first based on Zolotarev seminorm and the second on Kantorovich-Rubinstein maximum principle. Then a dynamic version

Wamiq Reyaz Para, Paul Guerrero, Niloy Mitra, Peter Wonka

Scalable generation of furniture layouts is essential for many applications in virtual reality, augmented reality, game development and synthetic data generation. Many existing methods tackle this problem as a sequence generation problem which imposes a specific ordering on the elements of the layout making such methods impractical for interactive editing or

Yun-Hua Chen, Meng-Ge Qin

The inclusion of the $\rho-\omega$ mixing effect is essential for a precise description of the pion electromagnetic form factor in the $e^+e^- \rightarrow \pi^+\pi^-$ process, which quantifies the two-pion contribution to the anomalous magnetic moment of the muon $a_\mu$. In this paper, we analyse the momentum dependence of the $\rho-\omega$ mixing by consid

Allison Beemer, Altan Berdan Kilic, Alberto Ravagnani

We consider the problem of error control in a coded, multicast network, focusing on the scenario where the errors can occur only on a proper subset of the network edges. We model this problem via an adversarial noise, presenting a formal framework and a series of techniques to obtain upper and lower bounds on the network's (1-shot) capacity, improving on the

Anacé N. da Silva, R. Kishor Kumar, Ashton S. Bradley, Lauro Tomio

The dynamical vortex production, with a trap-confining time-dependent stirred potential, is studied by using mass-imbalanced cold-atom coupled Bose-Einstein condensates (BEC). The vortex formation is explored by considering that both coupled species are confined by a pancake-like harmonic trap, slightly modified elliptically by a time-dependent periodic pote

Andriy Regeta

Let $Aut_{alg}(X)$ be the subgroup of the group of regular automorphisms $Aut(X)$ of an affine algebraic variety $X$ generated by all connected algebraic subgroups. We prove that if $dim X \ge 2$ and if $Aut_{alg}(X)$ is rich enough, $Aut_{alg}(X)$ is not linear, i.e., it cannot be embedded into $GL_n(K)$, where $K$ is an algebraically closed field of charac

Kamal Khemani, Shreesh Parvatikar, Pradeep Kumar

In the present work, the full spectrum $k$-distribution method (FSK) has been adopted to calculate the radiative heat transfer in the presence of participating gaseous medium within an enclosure. The spectral radiative properties of the gaseous medium is obtained from the HITEMP-2010 database. Further, radiative properties have been assembled into a monotoni

Guillaume Salha-Galvan

Graph autoencoders (GAE) and variational graph autoencoders (VGAE) emerged as two powerful groups of unsupervised node embedding methods, with various applications to graph-based machine learning problems such as link prediction and community detection. Nonetheless, at the beginning of this Ph.D. project, GAE and VGAE models were also suffering from key limi

Jian Ding, Hang Du

For two correlated graphs which are independently sub-sampled from a common Erd\H{o}s-R\'enyi graph $\mathbf{G}(n, p)$, we wish to recover their \emph{latent} vertex matching from the observation of these two graphs \emph{without labels}. When $p = n^{-\alpha+o(1)}$ for $\alpha\in (0, 1]$, we establish a sharp information-theoretic threshold for whether it i

Syeda Rabia Arshad, Syed Mujtaba Haider, Abdul Basit Mughal

The audio data is increasing day by day throughout the globe with the increase of telephonic conversations, video conferences and voice messages. This research provides a mechanism for identifying a speaker in an audio file, based on the human voice biometric features like pitch, amplitude, frequency etc. We proposed an unsupervised learning model where the

Sameea Naeem, Arif ur Rahman, Syed Mujtaba Haider, Abdul Basit Mughal

Finding similarities between two inter-language news articles is a challenging problem of Natural Language Processing (NLP). It is difficult to find similar news articles in a different language other than the native language of user, there is a need for a Machine Learning based automatic system to find the similarity between two inter-language news articles

Hila Katznelson, Saar Rahav

Exponential averages that appear in integral fluctuation theorems can be recast as a sum over moments of thermodynamic observables. We use two examples to show that such moment series can exhibit non-uniform convergence in certain singular limits. The first example is a simple model of a process with measurement and feedback. In this example, the limit of in

Geraldo F. Oliveira, Juan Gómez-Luna, Saugata Ghose, Onur Mutlu

The increasing prevalence and growing size of data in modern applications have led to high costs for computation in traditional processor-centric computing systems. Moving large volumes of data between memory devices (e.g., DRAM) and computing elements (e.g., CPUs, GPUs) across bandwidth-limited memory channels can consume more than 60% of the total energy i

Anastassia M. Makarieva, Andrei V. Nefiodov, Antonio Donato Nobre, Mara Baudena

The terrestrial water cycle links the soil and atmosphere moisture reservoirs through four fluxes: precipitation, evaporation, runoff, and atmospheric moisture convergence (net import of water vapor to balance runoff). Each of these processes is essential for human and ecosystem well-being. Predicting how the water cycle responds to changes in vegetation cov

Syed Zain Abbas, Arif ur Rahman, Abdul Basit Mughal, Syed Mujtaba Haider

There are several online newspapers in urdu but for the users it is difficult to find the content they are looking for because these most of them contain irrelevant data and most users did not get what they want to retrieve. Our proposed framework will help to predict Urdu news in the interests of users and reduce the users searching time for news. For this

Zhiyun Cheng

In this short note, we investigate the effect of region crossing change on planar trivalent graphs.

A. D. Dolgov

Astronomical data of the several recent years, which present an evidence in favour of abundant antimatter population in our Galaxy, Milky Way, are analysed. The data include: registration of gamma-rays with energy 0.511 MeV, which surely originate from electron-positron annihilation at rest, very large flux of anti-helium nuclei, discovered at AMS, and 14 st

Yanxin Song, Jianzong Wang, Tianbo Wu, Zhangcheng Huang

Facial micro-expressions recognition has attracted much attention recently. Micro-expressions have the characteristics of short duration and low intensity, and it is difficult to train a high-performance classifier with the limited number of existing micro-expressions. Therefore, recognizing micro-expressions is a challenge task. In this paper, we propose a

Lukasz Stettner

In this paper we consider impulse control of continuous time Markov processes with average cost per unit time functional. This problem is approximated using impulse control problems stopped at the first exit time from increasing sequence of open sets. We find solution to Bellman equation corresponding to the original problem and show that stopped impulse con

Hansoo Lee, Sangwook Lee, Youngji Koh, Uichin Lee

Prior HCI studies often analyzed smartphone app usage data for usability and user experience research purposes. App usage videos are often collected by a screen recording app in order to better analyze the app usage behaviors (e.g., app usage time, screen transition, and notification handling). However, it is difficult to analyze app usage videos along with

Adur Pastor Yabar, Andrés Asensio Ramos, Rafael Manso Sainz, Manuel Collados

We study the impact of the loss of axial symmetry around the optical axis on the polarimetric properties of a telescope with segmented primary mirror when each segment is present in a different aging stage. The different oxidation stage of each segment as they are substituted in time leads to non-negligible crosstalk terms. This effect is wavelength dependen

Lina Wu, Tianjun Li

We propose the generic no-scale inflation inspired from string theory compactifications. We consider the K\"ahler potentials with an inflaton field $\varphi$, as well as one, two, and three K\"ahler moduli. Also, we consider the renormalizable superpotential of $\varphi$ in general. We study the spectral index and tensor-to-scalar ratio in details, and find

P. O. Kazinski, T. V. Solovyev

The radiation of photons by electrons is investigated in the framework of quantum electrodynamics up to the second order in the coupling constant $e$. The $N$-particle, coherent, and thermal initial states are considered and the forms of the electron wave packets are taken into account. The explicit expressions for the intensity of radiation and the inclusiv

Rohit Mohan, Abhinav Valada

Amodal panoptic segmentation aims to connect the perception of the world to its cognitive understanding. It entails simultaneously predicting the semantic labels of visible scene regions and the entire shape of traffic participant instances, including regions that may be occluded. In this work, we formulate a proposal-free framework that tackles this task as

V. Jurdjevic, I. Markina, F. Silva Leite

The objective of the current paper is essentially twofold. Firstly, to make clear the difference between two notions of rolling a Riemannian manifold over another, using a language accessible to a wider audience, in particular to readers with interest in applications. Secondly, we concentrate on rolling an important class of Riemannian manifolds. In the firs

A S. Habibina, H. S. Ramadhan

We study the geodesics of $5d$ Reissner-Nordstrom and nonsingular black strings, and establish a rational bound orbit taxonomy for both massive as well as null test particles. For the timelike case, test particles with high energy (that would have made them plunge into or scatter off a black hole) could still form bound orbits around the black strings. We ca

Michelle Blom, Philip B. Stark, Peter J. Stuckey, Vanessa Teague

This paper explains the main principles and some of the technical details for auditing the scanning and digitisation of the Australian Senate ballot papers. We give a short summary of the motivation for auditing paper ballots, explain the necessary supporting steps for a rigorous and transparent audit, and suggest some statistical methods that would be appro

Diego García-Sepúlveda, Alfredo Guevara, Justin Kulp, Jingxiang Wu

We study the celestial description of the $O(N)$ sigma model in the large $N$ limit as introduced by Coleman, Jackiw and Politzer. Focusing on three dimensions, we analyze the implications of a UV complete, all-loop order 4-point amplitude of pions in terms of correlation functions defined on the celestial circle. We find these retain many key features from

Yong Chen, Yumin Cheng

The Berry-Ess\'{e}en upper bounds of moment estimators and least squares estimators of the mean and drift coefficients in Vasicek models driven by general Gaussian processes are studied. When studying the parameter estimation problem of Ornstein-Uhlenbeck (OU) process driven by fractional Brownian motion, the commonly used methods are mainly given by Kim and

Jean Dupuy, Adrien Guille, Julien Jacques

Networks of documents connected by hyperlinks, such as Wikipedia, are ubiquitous. Hyperlinks are inserted by the authors to enrich the text and facilitate the navigation through the network. However, authors tend to insert only a fraction of the relevant hyperlinks, mainly because this is a time consuming task. In this paper we address an annotation, which w

Jassem Abbasi, Pål Østebø Andersen

In recent years, the gap between Deep Learning (DL) methods and analytical or numerical approaches in scientific computing is tried to be filled by the evolution of Physics-Informed Neural Networks (PINNs). However, still, there are many complications in the training of PINNs and optimal interleaving of physical models. Here, we introduced the concept of Phy

Soichiro Kumano, Hiroshi Kera, Toshihiko Yamasaki

Adversarial attacks have only focused on changing the predictions of the classifier, but their danger greatly depends on how the class is mistaken. For example, when an automatic driving system mistakes a Persian cat for a Siamese cat, it is hardly a problem. However, if it mistakes a cat for a 120km/h minimum speed sign, serious problems can arise. As a ste

Zi-Yang Lin, Jian-Bo Cheng, Shi-Lin Zhu

We use the leading order (LO) contact interactions and OPE potentials to investigate the newly observed double-charm state $T_{cc}^+$. The $DD\pi$ three-body effect is important in this system since the intermediate states can go on shell. We keep the dependence of the pion propagators on the center-of-mass energy, which results in a unitary cut of the OPE p

Giovanni S. Alberti, Matteo Santacesaria, Silvia Sciutto

In this work, we present and study Continuous Generative Neural Networks (CGNNs), namely, generative models in the continuous setting: the output of a CGNN belongs to an infinite-dimensional function space. The architecture is inspired by DCGAN, with one fully connected layer, several convolutional layers and nonlinear activation functions. In the continuous

Chun-Khiang Chua

We study the rates and direct CP violations of two-body baryonic $\bar B_{u,d,s}\to {{\rm\bf B}\overline{\rm\bf B}}'$ and $B^-_c\to{{\rm\bf B}\overline{\rm\bf B}}'$ decays, where the final state baryons include low-lying octet and decuplet baryons. We incorporate topological amplitude formalism and the factorization approach. Asymptotic relations at large $m

Ziquan Wei, Shenghua Cheng, Jing Cai, Shaoqun Zeng

Cervical glandular cell (GC) detection is a key step in computer-aided diagnosis for cervical adenocarcinomas screening. It is challenging to accurately recognize GCs in cervical smears in which squamous cells are the major. Widely existing Out-Of-Distribution (OOD) data in the entire smear leads decreasing reliability of machine learning system for GC detec

Xianliang Xu, Zhongyi Huang

The Wasserstein distance has been an attractive tool in many fields. But due to its high computational complexity and the phenomenon of the curse of dimensionality in empirical estimation, various extensions of the Wasserstein distance have been proposed to overcome the shortcomings such as the Sliced Wasserstein distance. It enjoys a low computational cost

Shangkun Sun, Yuanqi Chen, Yu Zhu, Guodong Guo

Optical flow estimation is a classical yet challenging task in computer vision. One of the essential factors in accurately predicting optical flow is to alleviate occlusions between frames. However, it is still a thorny problem for current top-performing optical flow estimation methods due to insufficient local evidence to model occluded areas. In this paper

Masahito Hayashi, Seunghoan Song

This paper unifiedly addresses two kinds of key quantum secure tasks, i.e., quantum versions of secret sharing (SS) and symmetric private information retrieval (SPIR) by using multi-target monotone span program (MMSP), which characterizes the classical linear protocols of SS and SPIR. SS has two quantum extensions; One is the classical-quantum (CQ) setting,

Yao Ding, Zhengyang Bai, Guoxiang Huang, Weibin Li

We investigate facilitation induced transparency (FIT) enabled by strong and long-range Rydberg atom interactions between two spatially separated optical channels. In this setting, the resonant two-photon excitation of Rydberg states in a target channel is conditioned by a single Rydberg excitation in a control channel. Through the contactless coupling enabl

Lingtong Kong, Boyuan Jiang, Donghao Luo, Wenqing Chu

Prevailing video frame interpolation algorithms, that generate the intermediate frames from consecutive inputs, typically rely on complex model architectures with heavy parameters or large delay, hindering them from diverse real-time applications. In this work, we devise an efficient encoder-decoder based network, termed IFRNet, for fast intermediate frame s

Kyung Geun Kim, Byeong Tak Lee

In this paper, we propose a novel graph-based data augmentation method that can generally be applied to medical waveform data with graph structures. In the process of recording medical waveform data, such as electrocardiogram (ECG) or electroencephalogram (EEG), angular perturbations between the measurement leads exist due to discrepancies in lead positions.

Animesh Pandey, Anurag Gupta

We derive two consequences of the distributional form of the stress equilibrium condition while incorporating piecewise smooth stress and body force fields with singular concentrations on an interface. First we obtain the local equilibrium conditions in the bulk and at the interface, the latter including conditions on the interfacial stress and stress dipole

Animesh Pandey, Anurag Gupta

Mechanical fields over thin elastic surfaces can develop singularities at isolated points and curves in response to constrained deformations (e.g., crumpling and folding of paper), singular body forces and couples, distributions of isolated defects (e.g., dislocations and disclinations), and singular metric anomaly fields (e.g., growth and thermal strains).

Pierre J. Clavier, Loic Foissy, Diego A. López, Sylvie Paycha

The present exploratory paper deals with tensor products in the locality framework {developed in previous work}, a natural setting for an algebraic formulation of the locality principle in quantum field theory. Locality tensor products of locality vector spaces raise challenging questions, such as whether the locality tensor product of two locality vector sp

Yosuke Imamura

We investigate contributions of giant gravitons to the superconformal index. We concentrate on coincident giant gravitons wrapped around a single cycle, and each contribution is obtained by a certain variable change for fugacities from the index of the worldvolume theory on the giant gravitons. Because we treat the index as a series of fugacities and the var

Piotr Sierant, Maciej Lewenstein, Antonello Scardicchio

We perform a thorough and complete analysis of the Anderson localization transition on several models of random graphs with regular and random connectivity. The unprecedented precision and abundance of our exact diagonalization data (both spectra and eigenstates), together with new finite size scaling and statistical analysis of the graph ensembles, unveils

Binh T. Nguyen, Bertrand Thirion, Sylvain Arlot

Identifying the relevant variables for a classification model with correct confidence levels is a central but difficult task in high-dimension. Despite the core role of sparse logistic regression in statistics and machine learning, it still lacks a good solution for accurate inference in the regime where the number of features $p$ is as large as or larger th

Michael E. Sander, Pierre Ablin, Gabriel Peyré

Neural Ordinary Differential Equations (Neural ODEs) are the continuous analog of Residual Neural Networks (ResNets). We investigate whether the discrete dynamics defined by a ResNet are close to the continuous one of a Neural ODE. We first quantify the distance between the ResNet's hidden state trajectory and the solution of its corresponding Neural ODE. Ou

Eugene Chang, Paul Darcy, Kim-Kwang Raymond Choo, Nhien-An Le-Khac

Cryptocurrency has been (ab)used to purchase illicit goods and services such as drugs, weapons and child pornography (also referred to as child sexual abuse materials), and thus mobile devices (where cryptocurrency wallet applications are installed) are a potential source of evidence in a criminal investigation. Not surprisingly, there has been increased foc

Mohammad Sina Karvandi, MohammadHossein Gholamrezaei, Saleh Khalaj Monfared, Soroush Meghdadizanjani

Software analysis, debugging, and reverse engineering have a crucial impact in today's software industry. Efficient and stealthy debuggers are especially relevant for malware analysis. However, existing debugging platforms fail to address a transparent, effective, and high-performance low-level debugger due to their detectable fingerprints, complexity, and i

Ilana Bogod, Saar Rahav

The investigation of optimal processes has a long history in the field of thermodynamics. It is well known that finite-time processes that minimize dissipation often exhibit discontinuities. We use a combination of numerical and analytical approaches to study the driving cycle that maximizes the output in a simple model of a stochastic pump: a system driven

Angel Gómez Nicola, Andrea Vioque-Rodríguez

We revisit the most general effective lagrangian within Chiral Perturbation Theory at nonzero isospin chemical potential. In addition to the contributions already considered in the literature, we discuss the effects of new terms allowed by the symmetries, derived within the external source method including spurion fields, as well as of linear-field correctio

Yirmeyahu J. Kaminski, François Ollivier

We consider flat differential control systems for which there exist flat outputs that are part of the state variables and study them using Jacobi bound. We introduce a notion of saddle Jacobi bound for an ordinary differential system of $n$ equations in $n+m$ variables. Systems with saddle Jacobi number equal to $0$ generalize various notions of chained and

M. Furukawa, P. J. Morrison

Simulated annealing (SA) is a kind of relaxation method for finding equilibria of Hamiltonian systems. A set of evolution equations is solved with SA, which is derived from the original Hamiltonian system so that the energy of the system changes monotonically while preserving Casimir invariants inherent to noncanonical Hamiltonian systems. The energy extremu

Binyan Hu, Yu Sun, A. K. Qin

Deep neural networks (DNNs) often rely on massive labelled data for training, which is inaccessible in many applications. Data augmentation (DA) tackles data scarcity by creating new labelled data from available ones. Different DA methods have different mechanisms and therefore using their generated labelled data for DNN training may help improving DNN's gen

Masaki Kawamoto, Takuya Sato

We consider the Cauchy problem of a dissipative nonlinear Schr\"odinger equation with a time dependent harmonic potential. We find a critical situation that the $L^2$-norm of dissipative solutions decays or not and which is decided by a nonlinear power and time decay order of harmonic potential.

Liang Zhang, Anwen Hu, Qin Jin

English-based Vision-Language Pre-training (VLP) has achieved great success in various downstream tasks. Some efforts have been taken to generalize this success to non-English languages through Multilingual Vision-Language Pre-training (M-VLP). However, due to the large number of languages, M-VLP models often require huge computing resources and cannot be fl

Ayreena Bakhtawar, Jing Feng

Let $[a_1(x),a_2(x),\cdots,a_n(x),\cdots]$ be the continued fraction expansion of $x\in[0,1)$. In this paper, we study the increasing rate of the weighted product $a^{t_0}_n(x)a^{t_1}_{n+1}(x)\cdots a^{t_m}_{n+m}(x)$ ,where $t_i\in \mathbb{R}_+\ (0\leq i \leq m)$ are weights. More precisely, let $\varphi:\mathbb{N}\to\mathbb{R}_+$ be a function with $\varphi

Yu Wang

Let H be a finite-dimensional pointed Hopf algebra of rank one over an algebraically closed field of characteristic zero. In this paper we describe all annihilator ideals of indecomposable H-modules by generators. In particular, we give the classification of all ideals of finite-dimensional pointed Hopf algebra of rank one of nilpotent type over Klein 4-grou

Rza Mustafayev, Merve Yılmaz

In this paper, new equivalence theorems for the boundedness of the composition of a quasilinear operator $T$ with the Hardy and Copson operators in weighted Lebesgue spaces are proved. The usefulness of the obtained results is illustrated in the case of weighted Hardy-type and weighted iterated Hardy-type inequalities.

Kaspar Rosager Ludvigsen, Shishir Nagaraja, Angela Daly

Client-Side Scanning (CSS) see in the Child Sexual Abuse Material Detection (CSAMD) represent ubiquitous mass scanning. Apple proposed to scan their systems for such imagery. CSAMD was since pushed back, but the European Union decided to propose forced CSS to combat and prevent child sexual abuse and weaken encryption. CSS is mass surveillance of personal pr

K. M. Rajwade, M. C. Bezuidenhout, M. Caleb, L. N. Driessen

We report on the discovery and localization of fast radio bursts (FRBs) from the MeerTRAP project, a commensal fast radio transient-detection programme at MeerKAT in South Africa. Our hybrid approach combines a coherent search with an average field-of-view of 0.4 $\rm deg^{2}$ with an incoherent search utilizing a field-of-view of $\sim$1.27 $\rm deg^{2}$ (b

Hiroyuki Hata, Daichi Takeda, Jojiro Yoshinaka

The $KBc$ algebra is a subalgebra that has been used to construct classical solutions in Witten's open string field theory, such as the tachyon vacuum solution. The main purpose of this paper is to give various operator sets that satisfy the $KBc$ algebra. In addition, since those sets can contain matter operators arbitrarily, we can reproduce the KOS and th

Florian Joseph Baader, Philipp Althaus, André Bardow, Manuel Dahmen

Volatile electricity prices make demand response (DR) attractive for processes that can modulate their production rate. However, if nonlinear dynamic processes must be scheduled simultaneously with their local multi-energy system, the resulting scheduling optimization problems often cannot be solved in real time. For single-input single-output processes, the

B. Barsbay, K. Azizi, H. Sundu

The spectroscopic parameters of the heavy-light hybrid mesons with different spin-parities and different quark contents are investigated in the framework of the QCD sum rule method. The mass and current coupling of these states are calculated by taking into account the quark, gluon and mixed vacuum condensates up to dimension 10. The obtained results are com

Yuxuan Liu, Zhuo-Yu Xian, Cheng Peng, Yi Ling

We construct three models to describe the scenario where two eternal black holes are separated by a flat space, and can eventually be entangled by exchanging radiations. In the doubly holographic setup, we compute the entanglement entropy and the mutual information among the subsystems and obtain the dynamic phase structure of the entanglement. The formation

Wen Wang, Wanli Ni, Hui Tian, Zhaohui Yang

This paper investigates the use of the reconfigurable dual-functional surface to guarantee the full-space secure transmission in non-orthogonal multiple access (NOMA) networks. In the presence of eavesdroppers, the downlink communication from the base station to the legitimate users is safeguarded by the simultaneously transmitting and reflecting reconfigura

Jungsoo Lee, Jeonghoon Park, Daeyoung Kim, Juyoung Lee

In image classification, "debiasing" aims to train a classifier to be less susceptible to dataset bias, the strong correlation between peripheral attributes of data samples and a target class. For example, even if the frog class in the dataset mainly consists of frog images with a swamp background (i.e., bias-aligned samples), a debiased classifier should be

Ruixing Zhang, Liangzhe Han, Boyi Liu, Jiayuan Zeng

Recent years have witnessed a rapid growth of applying deep spatiotemporal methods in traffic forecasting. However, the prediction of origin-destination (OD) demands is still a challenging problem since the number of OD pairs is usually quadratic to the number of stations. In this case, most of the existing spatiotemporal methods fail to handle spatial relat

Shuyin Xia, Jiang Xie, Guoyin Wang

Existing clustering methods are based on a single granularity of information, such as the distance and density of each data. This most fine-grained based approach is usually inefficient and susceptible to noise. Inspired by adaptive process of granular-ball division and differentiation, we present a novel clustering approach that retains the speed and effici

Zhenwei Tang, Shichao Pei, Xi Peng, Fuzhen Zhuang

Many ontologies, i.e., Description Logic (DL) knowledge bases, have been developed to provide rich knowledge about various domains. An ontology consists of an ABox, i.e., assertion axioms between two entities or between a concept and an entity, and a TBox, i.e., terminology axioms between two concepts. Neural logical reasoning (NLR) is a fundamental task to

Chinmay Maheshwari, Manxi Wu, Druv Pai, Shankar Sastry

We study a multi-agent reinforcement learning dynamics, and analyze its asymptotic behavior in infinite-horizon discounted Markov potential games. We focus on the independent and decentralized setting, where players do not know the game parameters, and cannot communicate or coordinate. In each stage, players update their estimate of Q-function that evaluates

Tao Huang, Yuan Zhang, Shan You, Fei Wang

Distilling from the feature maps can be fairly effective for dense prediction tasks since both the feature discriminability and localization priors can be well transferred. However, not every pixel contributes equally to the performance, and a good student should learn from what really matters to the teacher. In this paper, we introduce a learnable embedding

M. Ilyas, A. R. Athar, Asma Bibi

The purpose of this paper is to study charged compact stars using extended gravitational theory, also known as $f(\mathcal{R}, \mathcal{G}, \mathcal{T})$ gravity. Alternatively, this theory is also called $f(\mathcal{R}, \mathcal{T}, \mathcal{G})$ gravity. The symbols $\mathcal{R}, \mathcal{G}$, and $\mathcal{T}$ denote the Ricci Scalar, the Gauss-Bonnet inv

Yu. Volkotrub, R. Skibiński, J. Golak, H. Witała

We employ two models of the nucleon-nucleon force: the OPE-Gaussian as well as the chiral N4LO and N4LO+ interactions with semilocal regularization in momentum space to study correlations among two-nucleon and three-nucleon elastic scattering observables. These models contain a number of free parameters whose values and covariance matrices are evaluated from

Gábor Péter, László Deák, Gyula Gróf, Bálint Kiss

The motivation and research design for repeating the EPF experiments are described in the paper.

Aritra Hazra

Component-based design paradigm is of paramount importance due to prolific growth in the complexity of modern-day systems. Since the components are developed primarily by multi-party vendors and often assembled to realize the overall system, it is an onus of the designer to certify both the functional and non-functional requirements of such systems. Several

Hunsoo Song, Jinha Jung

Despite the substantial demand for high-quality, large-area building maps, no established open-source workflow for generating 2D and 3D maps currently exists. This study introduces an automated, open-source workflow for large-scale 2D and 3D building mapping utilizing airborne LiDAR data. Uniquely, our workflow operates entirely unsupervised, eliminating the

Shahar Kvatinsky

Memristive technologies are attractive candidates to replace conventional memory technologies, and can also be used to perform logic and arithmetic operations using a technique called 'stateful logic.' Combining data storage and computation in the memory array enables a novel non-von Neumann architecture, where both the operations are performed within a memr

Han Wu, Haochen Tan, Mingjie Zhan, Gangming Zhao

Existing dialogue modeling methods have achieved promising performance on various dialogue tasks with the aid of Transformer and the large-scale pre-trained language models. However, some recent studies revealed that the context representations produced by these methods suffer the problem of anisotropy. In this paper, we find that the generated representatio