May 2022 arXiv papers — page 69

Szymon Płotka, Michal K. Grzeszczyk, Robert Brawura-Biskupski-Samaha, Paweł Gutaj

Predicting fetal weight at birth is an important aspect of perinatal care, particularly in the context of antenatal management, which includes the planned timing and the mode of delivery. Accurate prediction of weight using prenatal ultrasound is challenging as it requires images of specific fetal body parts during advanced pregnancy which is difficult to ca

P. N. Fedorov, V. S. Akhmetov, A. B. Velichko, A. M. Dmytrenko

We present the results of a kinematic analysis of red giants and subgiants whose centroids are in the plane of our Galaxy. For this, the positions, parallaxes, proper motions, and radial velocities of these stars from the $Gaia$ EDR3 catalog were used. We applied two approaches to obtain kinematic parameters. The first approach -- solving the equations of th

Siyao Liu, Tong Wu, Yong Wang

In this paper, we generalize the results in [Y. Wang: Affine connections on singular warped products. Int. J. Geom. Methods Mod. Phys. 18(5), 2150076, (2021).] to singular multiply warped products and singular twisted products. We study singular multiply warped products and singular twisted products and their curvature with the semi-symmetric metric connecti

Cezar Sas, Andrea Capiluppi, Claudio Di Sipio, Juri Di Rocco

GitHub is the world's largest host of source code, with more than 150M repositories. However, most of these repositories are not labeled or inadequately so, making it harder for users to find relevant projects. There have been various proposals for software application domain classification over the past years. However, these approaches lack a well-defined t

Shalanika Dayarathna, Rajitha Senanayake, Jamie Evans

Focusing on the joint relay selection and power control problem with a view to maximizing the sum-rate, we propose a novel sub-optimal algorithm that iterates between relay selection and power control. The relay selection is performed by maximizing the minimum signal-to-interference-plus-noise-ratio (as opposed to maximizing the sum-rate) and the power contr

Ogul Esen, Miroslav Grmela, Michal Pavelka

The General Equation for Non-Equilibrium Reversible-Irreversible Coupling (GENERIC) provides structure of mesoscopic multiscale dynamics that guarantees emergence of equilibrium states. Similarly, a lift of the GENERIC structure to iterated cotangent bundles, called a rate GENERIC, guarantees emergence of the vector fields that generate the approach to equil

Ogul Esen, Miroslav Grmela, Michal Pavelka

This paper contains a fully geometric formulation of the General Equation for Non-Equilibrium Reversible-Irreversible Coupling (GENERIC). Although GENERIC, which is the sum of Hamiltonian mechanics and gradient dynamics, is a framework unifying a vast range of models in non-equilibrium thermodynamics, it has unclear geometric structure, due to the diverse ge

Ran Li, Chuan Huang, Xiaoqi Qin, Shengpei Jiang

We investigate the coexistence of task-oriented and data-oriented communications in a IoT system that shares a group of channels, and study the scheduling problem to jointly optimize the weighted age of incorrect information (AoII) and throughput, which are the performance metrics of the two types of communications, respectively. This problem is formulated a

Stylianos I. Venieris, Christos-Savvas Bouganis, Nicholas D. Lane

As the use of AI-powered applications widens across multiple domains, so do increase the computational demands. Primary driver of AI technology are the deep neural networks (DNNs). When focusing either on cloud-based systems that serve multiple AI queries from different users each with their own DNN model, or on mobile robots and smartphones employing pipeli

F. Lopes, V. Courtillot, D. Gibert, JL Le Mouël

The time series of northern hemisphere (NHSI) and southern hemisphere (SHSI) sea-ice extent are submitted to singular spectral analysis (SSA). The components are analyzed with Laplace's formulation of the Liouville-Euler system. As already shown in a previous work, the trends observed in the time series are quasi linear, decreasing for NHSI and increasing fo

Takashi Uneyama, Tatsuma Oishi, Takato Ishida, Yuya Doi

We derive the stress tensor of a rigid dumbbell by using the virtual work method. In the virtual work method, we virtually apply a small deformation to the system, and relate the change of the energy to the work done by the stress tensor. A rigid dumbbell consists of two particles connected by a rigid bond of which length is constant (the rigid constraint).

Zhuoling Li, Zhan Qu, Yang Zhou, Jianzhuang Liu

As an inherently ill-posed problem, depth estimation from single images is the most challenging part of monocular 3D object detection (M3OD). Many existing methods rely on preconceived assumptions to bridge the missing spatial information in monocular images, and predict a sole depth value for every object of interest. However, these assumptions do not alway

Kosuke Kurosawa, Ryota Moriwaki, Hikaru Yabuta, Ko Ishibashi

Carbonaceous asteroids, including Ryugu and Bennu, which have been explored by the Hayabusa2 and OSIRIS-REx missions, were probably important carriers of volatiles to the inner Solar System. However, Ryugu has experienced significant volatile loss, possibly from hypervelocity impact heating. Here we present impact experiments at speeds comparable to those ex

Patrick Bieker

We define Drinfeld level structures for Drinfeld shtukas of any rank and show that their moduli spaces are regular and admit finite flat level maps. In particular, the moduli spaces of Drinfeld shtukas with Drinfeld $\Gamma_0(\mathfrak{p}^n)$-level structures provide a good integral model and relative compactification of the moduli space of shtukas with naiv

Edoardo Ghignone, Nicolas Baumann, Mike Boss, Michele Magno

Autonomous racing is becoming popular for academic and industry researchers as a test for general autonomous driving by pushing perception, planning, and control algorithms to their limits. While traditional control methods such as MPC are capable of generating an optimal control sequence at the edge of the vehicles physical controllability, these methods ar

Michael Sklar

This PhD thesis covers breakthroughs in several areas of adaptive experiment design: (i) (Chapter 2) Novel clinical trial designs and statistical methods in the era of precision medicine. (ii) (Chapter 3) Multi-armed bandit theory, with applications to learning healthcare systems and clinical trials. (iii) (Chapter 4) Bandit and covariate processes, with fin

Jungin Lee

In this paper, we study the distribution of the cokernel of a general random Hermitian matrix over the ring of integers $\mathcal{O}$ of a quadratic extension $K$ of $\mathbb{Q}_p$. For each positive integer $n$, let $X_n$ be a random $n \times n$ Hermitian matrix over $\mathcal{O}$ whose upper triangular entries are independent and their reductions are not

Roberto Grimaudo, Antonino Messina, Hiromichi Nakazato, Alessandro Sergi

The class of two-interacting-impurity spin-boson models with vanishing transverse fields on the spin-pair is studied. The model can be exactly mapped into two independent standard single-impurity spin-boson models where the role of the tunnelling parameter is played by the spin-spin coupling. The dynamics of the magnetization is analysed for different levels

Shiyu Li, Chia Wei Hsu

Metalenses -- flat lenses made with optical metasurfaces -- promise to enable thinner, cheaper, and better imaging systems. Achieving a sufficient angular field of view (FOV) is crucial toward that goal and requires a tailored incident-angle-dependent response. Here, we show that there is an intrinsic trade-off between achieving a desired broad-angle respons

Anthony Scemama, Andreas Savin

We like to attribute a number of electrons to spatial domains (atoms, bonds, ...). However, as a rule, the number of electrons in a spatial domain is not a sharp number. We thus study probabilities for having any number of electrons (between 0 and the total number of electrons in the system) in a given spatial domain. We show that by choosing a domain that m

Ed Bennett, Deog Ki Hong, Jong-Wan Lee, C. -J. David Lin

We study Yang-Mills lattice theories with $Sp(N_c)$ gauge group, with $N_c=2N$, for $N=1,\,\cdots,\,4$. We show that if we divide the renormalised couplings appearing in the Wilson flow by the quadratic Casimir $C_2(F)$ of the $Sp(N_c)$ group, then the resulting quantities display a good agreement among all values of $N_c$ considered, over a finite interval

Ming-Liang Zhang, Fei Yin, Yi-Han Hao, Cheng-Lin Liu

Geometry diagram parsing plays a key role in geometry problem solving, wherein the primitive extraction and relation parsing remain challenging due to the complex layout and between-primitive relationship. In this paper, we propose a powerful diagram parser based on deep learning and graph reasoning. Specifically, a modified instance segmentation method is p

Yizheng Hu, Zhihua Zhang

Cooperative multi-agent reinforcement learning (cMARL) has many real applications, but the policy trained by existing cMARL algorithms is not robust enough when deployed. There exist also many methods about adversarial attacks on the RL system, which implies that the RL system can suffer from adversarial attacks, but most of them focused on single agent RL.

Dror Kipnis, Yaniv Levy, Roee Diamant

Abundant in coastal areas, sea turtles are affected by high-intensity acoustic anthropogenic sounds. In this paper, we offer a pattern analysis-based detection approach to serve as a warning system for the existence of nearby sea turtles. We focus on the challenge of overcoming the low signal-to-clutter ratio (SCR) caused by reverberations. Assuming that, du

Alina Karakanta, François Buet, Mauro Cettolo, François Yvon

Subtitles appear on screen as short pieces of text, segmented based on formal constraints (length) and syntactic/semantic criteria. Subtitle segmentation can be evaluated with sequence segmentation metrics against a human reference. However, standard segmentation metrics cannot be applied when systems generate outputs different than the reference, e.g. with

Riccardo Campana

In-orbit background is an unavoidable feature of all space-borne X-ray detectors, and arises both from cosmic sources (diffuse or point-like) and from the interaction of the detectors themselves with the space environment (primary or secondary cosmic rays, geomagnetically trapped particles, activation of spacecraft structures). In this chapter the main backg

Samar Layek, Miguel Monteverde, Gastón Garbarino, Marie-Aude Méasson

Although progress with twisted graphene nano-devices is boosting the superconductivity that is the consequence of their Moir\'e flat electronic bands, the immense choice for future development is an obstacle for their optimisation. We report here that soft-chemistry deintercalation of KC$_8$ breaks down graphite stacking generating a strong disorder that inc

Subhayan Maity

The space-time of the Universe has been perturbed under a scalar field $\phi$ considering the minimum coupling between {\phi} and the background metric. The solutions of Einstein field equations have been obtained under perturbed geometry and the corresponding conservation equation shows the non-equilibrium thermodynamic prescription of the cosmic fluid. Fol

Andrea Cossu, Tinne Tuytelaars, Antonio Carta, Lucia Passaro

Pre-trained models are nowadays a fundamental component of machine learning research. In continual learning, they are commonly used to initialize the model before training on the stream of non-stationary data. However, pre-training is rarely applied during continual learning. We formalize and investigate the characteristics of the continual pre-training scen

J. G. Christy, Jason Kumar, Arvind Rajaraman

We consider the search for gamma-rays produced by the annihilation or decay of low-mass dark matter which couples to quarks. In this scenario, most of the photons are produced from the decays of $\pi^0$ or $\eta$ mesons. These decays produce distinctly different photon signatures due to the difference in meson mass. We assess the ability of the future MeV-ra

Alexis M. S. Smith, Szilard Csizmadia

K2-139 b is a warm Jupiter with an orbital period of 28.4 d, but only three transits of this system have previously been observed, in the long-cadence mode of K2, limiting the precision with which the orbital period can be determined, and future transits predicted. We report photometric observations of four transits of K2-139 b with ESA's CHaracterising ExOP

Guochao Sun

Originally proposed as a cosmological probe of the large-scale structure, line intensity mapping (LIM) also offers a unique window into the astrophysics of galaxy evolution. Adding to the astrophysical explorations of LIM technique that have traditionally focused on small, non-linear scales, we present a novel method to study the global star formation law us

Manu Lahariya, Farzaneh Karami, Chris Develder, Guillaume Crevecoeur

In energy intensive industrial systems, an evaporative cooling process may introduce operational flexibility. Such flexibility refers to a systems ability to deviate from its scheduled energy consumption. Identifying the flexibility, and therefore, designing control that ensures efficient and reliable operation presents a great challenge due to the inherentl

Michael Ruderman, Leonid Fridman

Standard problem of one-degree-of-freedom mechanical systems with Coulomb friction is revised for a relay-based feedback stabilization. It is recalled that such a system with Coulomb friction is asymptotically stabilizable via a relay-based output feedback, as formerly shown in [1]. Assuming an upper bounded Coulomb friction disturbance, a time-optimal gain

Arnab Dey, Yassine Ahmine, Andrew I. Comport

Neural scene representations, such as Neural Radiance Fields (NeRF), are based on training a multilayer perceptron (MLP) using a set of color images with known poses. An increasing number of devices now produce RGB-D(color + depth) information, which has been shown to be very important for a wide range of tasks. Therefore, the aim of this paper is to investi

Alberto Muñoz-Ortiz, Carlos Gómez-Rodríguez, David Vilares

We propose a morphology-based method for low-resource (LR) dependency parsing. We train a morphological inflector for target LR languages, and apply it to related rich-resource (RR) treebanks to create cross-lingual (x-inflected) treebanks that resemble the target LR language. We use such inflected treebanks to train parsers in zero- (training on x-inflected

Rongvoram Nivesvivat

The Potts conformal field theory is an analytic continuation in the central charge of conformal field theory describing the critical two-dimensional $Q$-state Potts model. Four-point functions of the Potts conformal field theory are dictated by two constraints: the crossing-symmetry equation and $S_Q$ symmetry. We numerically solve the crossing-symmetry equa

Norbert Michael Mayer, Oliver Obst

This work joins aspects of reservoir optimization, information-theoretic optimal encoding, and at its center fractal analysis. We build on the observation that, due to the recursive nature of recurrent neural networks, input sequences appear as fractal patterns in their hidden state representation. These patterns have a fractal dimension that is lower than t

Gehui Shen, Shibo Jie, Ziheng Li, Zhi-Hong Deng

Continual learning requires the model to maintain the learned knowledge while learning from a non-i.i.d data stream continually. Due to the single-pass training setting, online continual learning is very challenging, but it is closer to the real-world scenarios where quick adaptation to new data is appealing. In this paper, we focus on online class-increment

Aymeric Roux, Jean-Paul Martishang, Michael Baudoin

The radiation force exerted on an object by an acoustic wave is a widely studied phenomenon since the early work of Rayleigh, Langevin and Brillouin and has led in the last decade to tremendous developments for acoustic micromanipulation. Despite extensive work on this phenomenon, the expressions of the acoustic radiation force applied on a particle have so

Guillaume Voisin, G Luth, I Cognard, P Freire

The strong equivalence principle is a cornerstone of general relativity, tested with exquisite accuracy in the Solar system. However, tests in the strong-field regime require a compact object. Currently, PSR J0337+1715 is the unique millisecond pulsar found in a triple stellar system, orbiting two white dwarfs within an area comparable to the orbit of the Ea

J Dubois, D Fraix-Burnet, J Moultaka, P Sharma

Aims. The present study aims at providing a deeper insight into the power and limitation of an unsupervised classification algorithm (called Fisher-EM) on spectra of galaxies. This algorithm uses a Gaussian mixture in a discriminative latent subspace. To this end, we investigate the capacity of this algorithm to segregate the physical parameters used to gene

Zhengqin Li, Jia Shi, Sai Bi, Rui Zhu

We present a method to edit complex indoor lighting from a single image with its predicted depth and light source segmentation masks. This is an extremely challenging problem that requires modeling complex light transport, and disentangling HDR lighting from material and geometry with only a partial LDR observation of the scene. We tackle this problem using

Yutong Wang, Clayton D. Scott

Recent research in the theory of overparametrized learning has sought to establish generalization guarantees in the interpolating regime. Such results have been established for a few common classes of methods, but so far not for ensemble methods. We devise an ensemble classification method that simultaneously interpolates the training data, and is consistent

Adam Rançon

We comment on J. Phys. Soc. Jpn. 91, 024001 (2022) by Masaki-Kato et al. and show that their results are in very good agreement with the semi-classical spin-wave approximation of Bose-Hubbard model in the hardcore limit. This allows for recovering the analytical formulae for both the s-wave scattering length and the Lee-Huang-Yang correction.

Irene Cavallari, Clara Grassi, Giovanni F. Gronchi, Giulio Baù

The concept of sphere of influence of a planet is useful in both the context of impact monitoring of asteroids with the Earth and of the design of interplanetary trajectories for spacecrafts. After reviewing the classical results, we propose a new definition for this sphere that depends on the position and velocity of the small body for given values of the J

Weifeng Lin, Nir Kampf, Jacob Klein

Boundary lubrication is associated with two sliding molecularly thin lubricated film-coated surfaces, where the energy dissipation occurs at the slip-plane between lubricated films. The hydration lubrication paradigm, which accounts for ultralow friction in aqueous media, has been extended to various systems, with phosphatidylcholine (PC) lipids recognized a

Arne Keller, Antonio Zelaquett Khoury, Nicolas Fabre, Maria Inès Amanti

Stimulated emission tomography is a powerful and successful technique to both improve the resolution and experimentally simplify the task of determining the modal properties of biphotons. In the present manuscript we provide a theoretical description of SET valid for any quadratic coupling regime between a non-linear medium and pump fields generating photons

Marc Schmitt

Our fast-paced digital economy shaped by global competition requires increased data-driven decision-making based on artificial intelligence (AI) and machine learning (ML). The benefits of deep learning (DL) are manifold, but it comes with limitations that have, so far, interfered with widespread industry adoption. This paper explains why DL, despite its popu

Albin Dahlin, Yiannis Karayiannidis

Motion planning methods like navigation functions and harmonic potential fields provide (almost) global convergence and are suitable for obstacle avoidance in dynamically changing environments due to their reactive nature. A common assumption in the control design is that the robot operates in a disjoint star world, i.e. all obstacles are strictly starshaped

Chunya Zou, Andi Han, Lequan Lin, Junbin Gao

In this paper, we propose a simple yet effective graph neural network for directed graphs (digraph) based on the classic Singular Value Decomposition (SVD), named SVD-GCN. The new graph neural network is built upon the graph SVD-framelet to better decompose graph signals on the SVD ``frequency'' bands. Further the new framelet SVD-GCN is also scaled up for l

Cedric Fraces Gasmi, Hamdi Tchelepi

We present a Parametrization of the Physics Informed Neural Network (P-PINN) approach to tackle the problem of uncertainty quantification in reservoir engineering problems. We demonstrate the approach with the immiscible two phase flow displacement (Buckley-Leverett problem) in heterogeneous porous medium. The reservoir properties (porosity, permeability) ar

Ziyue Wang

The dynamical evolution of spin of a massive probe fermion in a massless hot QED plasma at local equilibrium is investigated through the quantum kinetic theory. We consider the massive probe fermion undergoing 2-by-2 Coulomb scattering with the massless fermions in the medium. The axial kinetic equation is derived including the collision terms to the first o

Tsuneya Yoshida, Yasuhiro Hatsugai

In spite of extensive works on the non-Hermitian topology, correlations effects remain crucial questions. We hereby analyze correlated non-Hermitian systems with special emphasis on the one-dimensional point-gap topology. Specifically, our analysis elucidates that correlations result in reduction of the topological classification $\mathbb{Z}\times \mathbb{Z}

Ramansh Sharma, Varun Shankar

We present a new technique for the accelerated training of physics-informed neural networks (PINNs): discretely-trained PINNs (DT-PINNs). The repeated computation of partial derivative terms in the PINN loss functions via automatic differentiation during training is known to be computationally expensive, especially for higher-order derivatives. DT-PINNs are

Xiongfei Gui, Wenbin Fan, Jiace Sun, Yongle Li

The accurate and efficient calculation of the rate coefficients of chemical reactions is a key issue in the research of chemical dynamics. In this work, by applying the dimension-free ultra-stable Cayley propagator, the thermal rate coefficients of a prototypic high dimensional chemical reaction OH + CH4 -> H2O + CH3 in the temperature range of 200 K to 1500

Tariq Islam, Cheolhyeon Kwon

Device to Device (D2D) communication takes advantage of the proximity between the communicating devices in order to achieve efficient resource utilization, improved throughput and energy efficiency, simultaneous serviceability and reduced latency. One of the main characteristics of D2D communication is reuse of the frequency resource in order to improve spec

Jiayu Mao, Haibo Yang, Peiwen Qiu, Jia Liu

Over-the-air federated learning (OTA-FL) has emerged as an efficient mechanism that exploits the superposition property of the wireless medium and performs model aggregation for federated learning in the air. OTA-FL is naturally sensitive to wireless channel fading, which could significantly diminish its learning accuracy. To address this challenge, in this

Shuo Yang, Zeke Xie, Hanyu Peng, Min Xu

The great success of deep learning heavily relies on increasingly larger training data, which comes at a price of huge computational and infrastructural costs. This poses crucial questions that, do all training data contribute to model's performance? How much does each individual training sample or a sub-training-set affect the model's generalization, and ho

Zifeng Wang, Jimeng Sun

Tabular data (or tables) are the most widely used data format in machine learning (ML). However, ML models often assume the table structure keeps fixed in training and testing. Before ML modeling, heavy data cleaning is required to merge disparate tables with different columns. This preprocessing often incurs significant data waste (e.g., removing unmatched

Shih-Han Chan, Tsai-Lun Yang, Yun-Wei Chu, Chi-Yang Hsu

An engaging and provocative question can open up a great conversation. In this work, we explore a novel scenario: a conversation agent views a set of the user's photos (for example, from social media platforms) and asks an engaging question to initiate a conversation with the user. The existing vision-to-question models mostly generate tedious and obvious qu

Yan-Hong Yao, Xin-He Meng

The backreaction term ${\cal Q}_\CD$ and the averaged spatial Ricci scalar $\average{\CR}$ in the spatially averaged inhomogeneous Universe can be used to combine into effective perfect fluid energy density $\varrho_{\rm eff}^{\CD}$ and pressure $p_{\rm eff}^{\CD}$ that can be regarded as new effective sources for the backreaction effects. In order to model

Shinhyung Yang, Jiun Jeong, Bernhard Scholz, Bernd Burgstaller

To conduct real-time analytics computations, big data stream processing engines are required to process unbounded data streams at millions of events per second. However, current streaming engines exhibit low throughput and high tuple processing latency. Performance engineering is complicated by the fact that streaming engines constitute complex distributed s

Sanku Satya Uday, Satti Thanuja Pavani, T. Jaya Lakshmi, Rohit Chivukula

Human Activity Recognition (HAR) describes the machines ability to recognize human actions. Nowadays, most people on earth are health conscious, so people are more interested in tracking their daily activities using Smartphones or Smart Watches, which can help them manage their daily routines in a healthy way. With this objective, Kaggle has conducted a comp

Zhengyuan Liu, Nancy F. Chen

Text style transfer is an important task in controllable language generation. Supervised approaches have pushed performance improvement on style-oriented rewriting such as formality conversion. However, challenges remain due to the scarcity of large-scale parallel data in many domains. While unsupervised approaches do not rely on annotated sentence pairs for

Tomoya Iwashita, Masaaki Nagao, Akira Yoshimori, Masahide Terazima

Yeh and Hummer's simplified estimation method has often been adopted to obtain diffusion coefficients for solute molecules using molecular dynamic simulation. However, the simplified formula is not necessarily valid when a small basic cell is used. Therefore, we conducted molecular dynamics simulations of aqueous protein solution to estimate the diffusion co

Hwanwoo Kim, Daniel Sanz-Alonso, Alexander Strang

This paper introduces a computational framework to incorporate flexible regularization techniques in ensemble Kalman methods for nonlinear inverse problems. The proposed methodology approximates the maximum a posteriori (MAP) estimate of a hierarchical Bayesian model characterized by a conditionally Gaussian prior and generalized gamma hyperpriors. Suitable

Ying-Jen Yang, Hong Qian

Maximum entropy principle identifies forces conjugated to observables and the thermodynamic relations between them, independent upon their underlying mechanistic details. For data about state distributions or transition statistics, the principle can be derived from limit theorems of infinite data sampling. This derivation reveals its empirical origin and cla

Xiaofan Cui, Al-Thaddeus Avestruz

Stability guarantees are critical for cycle-by-cycle controlled dc-dc converters in consumer electronics and energy storage systems. Traditional stability analysis on cycle-by-cycle dc-dc converters is incomplete because the inductor current ramps are considered fixed; but instead, inductor ramps are not fixed because they are dependent on the output voltage

Kento Akamatsu, Takuya Hirose, Nobuhito Maru

We discuss the gauge symmetry breaking of six dimensional theories in flux compactification with a magnetic flux background and a constant vacuum expectation value (VEV) for the scalar fields, which are zero modes of extra spatial components of the gauge field. Although the effective potential for the scalar fields are known not to be generated classically a

Zhuoyan Xu, Kris Sankaran

Spatially resolved transcriptomics (ST) measures gene expression along with the spatial coordinates of the measurements. The analysis of ST data involves significant computation complexity. In this work, we propose gene expression dimensionality reduction algorithm that retains spatial structure. We combine the wavelet transformation with matrix factorizatio

M. Stalport, J. -B. Delisle, S. Udry, E. C. Matthews

Over the past years, the amount of detected multi-planet systems significantly grew, an important sub-class of which being the compact configurations. A precise knowledge of them is crucial to understand the conditions with which planetary systems form and evolve. However, observations often leave these systems with large uncertainties, notably on the orbita

Akash Godbole, Steven A. Grosz, Karthik Nandakumar, Anil K. Jain

Fingerprint recognition systems have been deployed globally in numerous applications including personal devices, forensics, law enforcement, banking, and national identity systems. For these systems to be socially acceptable and trustworthy, it is critical that they perform equally well across different demographic groups. In this work, we propose a formal s

Georgios N. Tsigaridas, Aristides I. Kechriniotis, Christos A. Tsonos, Konstantinos K. Delibasis

In this work we show that Weyl particles can exist at different states in zero electromagnetic field, either as free particles, or at localized states described by a parameter with dimensions of mass. We also calculate the electromagnetic fields that should be applied in order to modify the localization of Weyl particles at a desired rate. It is shown that t

Weichan Liu, Mengke Qi, Xin Zhang

In this paper, we introduce the notion of 2-boundary planar graphs. A graph is 2-boundary planar if it has an embedding in the plane so that all vertices lie on the boundary of at most two faces and no edges are crossed. A proper coloring of a graph is odd if every non-isolated vertex has some color that appears an odd number of times on its neighborhood. Pe

Wei Guo, Chuan Huang, Xiaoqi Qin, Lian Yang

Federated learning (FL) has been recognized as a promising distributed learning paradigm to support intelligent applications at the wireless edge, where a global model is trained iteratively through the collaboration of the edge devices without sharing their data. However, due to the relatively large communication cost between the devices and parameter serve

Yafei Ou, Prasoon Ambalathankandy, Ryunosuke Furuya, Seiya Kawada

Rheumatoid arthritis (RA) is a chronic autoimmune disease that primarily affects peripheral synovial joints, like fingers, wrist and feet. Radiology plays a critical role in the diagnosis and monitoring of RA. Limited by the current spatial resolution of radiographic imaging, joint space narrowing (JSN) progression of RA with the same reason above can be les

Prakhar Gupta, Harsh Jhamtani, Jeffrey P. Bigham

Target-guided response generation enables dialogue systems to smoothly transition a conversation from a dialogue context toward a target sentence. Such control is useful for designing dialogue systems that direct a conversation toward specific goals, such as creating non-obtrusive recommendations or introducing new topics in the conversation. In this paper,

Shiva Kazemi Taskou, Mehdi Rasti, Pedro H. J. Nardelli

Many of the key enabling technologies of the fifth-generation (5G), such as network slicing, spectrum sharing, and federated learning, rely on a centralized authority. This may lead to pitfalls in terms of security or single point of failure. Distributed ledger technology, specifically blockchain, is currently employed by different applications related to th

Yuan Gao, Jian-Guo Liu

Chemical reactions can be modeled by a random time-changed Poisson process on countable states. The macroscopic behaviors, such as large fluctuations, can be studied via the WKB reformulation. The WKB reformulation for the backward equation is Varadhan's discrete nonlinear semigroup and is also a monotone scheme that approximates the limiting first-order Ham

Jack Hall

Let $X$ be an algebraic stack with quasi-affine diagonal of finite type over a field $k$ of characteristic $0$. We extend the well-known equivalence $\mathsf{D}^+(\mathsf{QCoh}(X)) \simeq \mathsf{D}_{\mathrm{qc}}^+(X)$ to unbounded derived categories. We also prove that if $X$ is smooth over $k$, then $\mathsf{D}_{\mathrm{qc}}(X)$ is compactly generated. We

Mohammadreza Iman, John A. Miller, Khaled Rasheed, Robert M. Branch

Deep transfer learning techniques try to tackle the limitations of deep learning, the dependency on extensive training data and the training costs, by reusing obtained knowledge. However, the current DTL techniques suffer from either catastrophic forgetting dilemma (losing the previously obtained knowledge) or overly biased pre-trained models (harder to adap

Sofia Di Gennaro, Yen Chin Ong

Barrow proposed that the area law of the entropy associated with a horizon might receive a "fractal correction" due to quantum gravitational effects -- in place of $S\propto A$, we have instead $S\propto A^{1+\delta/2}$, where $0\leqslant \delta \leqslant 1$ measures the deviation from the standard area law ($\delta=0$). Based on black hole thermodynamics, w

Hongxin Wei, Renchunzi Xie, Hao Cheng, Lei Feng

Detecting out-of-distribution inputs is critical for safe deployment of machine learning models in the real world. However, neural networks are known to suffer from the overconfidence issue, where they produce abnormally high confidence for both in- and out-of-distribution inputs. In this work, we show that this issue can be mitigated through Logit Normaliza

Charles K. C. Lieou, Takeshi Egami

Slow relaxation and plastic deformation in disordered materials such as metallic glasses and supercooled liquids occur at dynamical heterogeneities, or neighboring particles that rearrange in a correlated, cooperative manner. Dynamical heterogeneities have historically been described by a four-point, time-dependent density correlation function $\chi_4 (r, t)

Richa Sharma, Stefan Boettcher

We study transport within a spatially heterogeneous one-dimensional quantum walk with a combination of hierarchical and random barriers. Recent renormalization group calculations for a spatially disordered quantum walk with a regular hierarchy of barriers alone have shown a gradual decrease in transport but no localization for increasing (but finite) barrier

Xiaoya Chen, Jingkuan Song, Pengpeng Zeng, Lianli Gao

Video captioning is a challenging task that necessitates a thorough comprehension of visual scenes. Existing methods follow a typical one-to-one mapping, which concentrates on a limited sample space while ignoring the intrinsic semantic associations between samples, resulting in rigid and uninformative expressions. To address this issue, we propose a novel a

Wei Guo, Ran Li, Chuan Huang, Xiaoqi Qin

This paper studies the joint device selection and power control scheme for wireless federated learning (FL), considering both the downlink and uplink communications between the parameter server (PS) and the terminal devices. In each round of model training, the PS first broadcasts the global model to the terminal devices in an analog fashion, and then the te

Mike He Zhu, Léna Néhale Ezzine, Dianbo Liu, Yoshua Bengio

Federated learning is a distributed machine learning approach which enables a shared server model to learn by aggregating the locally-computed parameter updates with the training data from spatially-distributed client silos. Though successfully possessing advantages in both scale and privacy, federated learning is hurt by domain shift problems, where the lea

Dickson Y. B. Annor, Michael S. Payne

For an arrangement of $n$ lines in the real projective plane, we denote by $f$ the number of regions into which the real projective plane is divided by the lines. Using Bojanowski's inequality, we establish a new lower bound for $f$. In particular, we show that if no more than $\frac{2}{3}n$ lines intersect at any point, then $f \ge \frac{1}{6}n^{2}$

Yuichi Sano

While classical money can be copied, it is impossible to copy quantum money in principle, with only the bank that issues it knowing how to generate it, meaning only the bank can make exact copies. Not all reliable banks, such as central banks, will issue quantum money, so there is the possibility that untrustworthy banks are distributing fake or multiple cop

Cristian Ahumada, Claudio Gutierrez, Antonios Anastasopoulos

Mapuzugun is the language of the Mapuche people. Due to political and historical reasons, its number of speakers has decreased and the language has been excluded from the educational system in Chile and Argentina. For this reason, it is very important to support the revitalization of the Mapuzugun in all spaces and media of society. In this work we present a

Taichi Tanaka, Isao Nambu, Yoshiko Maruyama, Yasuhiro Wada

Many researchers have used machine learning models to control artificial hands, walking aids, assistance suits, etc., using the biological signal of electromyography (EMG). The use of such devices requires high classification accuracy of machine learning models. One method for improving the classification performance of machine learning models is normalizati

Saleh Naghdi, Thomas Quella, Charles D. Hill

By the standard second law of thermodynamics, heat spontaneously flows from a hotter body to a colder body. However, quantum systems in which quantum correlations play a prominent role can exhibit a non-classical reversal of such heat flow. We propose a quantum system consisting of a chain of qubits, each in local Gibbs states, where only adjacent qubits are

Minh Tran, Viet-Khoa Vo-Ho, Ngan T. H. Le

Convolutional Neural Networks (CNNs) have achieved promising results in medical image segmentation. However, CNNs require lots of training data and are incapable of handling pose and deformation of objects. Furthermore, their pooling layers tend to discard important information such as positions as well as CNNs are sensitive to rotation and affine transforma

Isamu Iwanari

We prove a generalization of Bogomolov-Tian-Todorov theorem to Calabi-Yau categories.

Xing Liu

We consider the time discretization of fractional stochastic wave equation with Gaussian noise, which is negatively correlated. Major obstacles to design and analyze time discretization of stochastic wave equation come from the approximation of stochastic convolution with respect to fractional Brownian motion. Firstly, we discuss the smoothing properties of

Amirhossein Farzam, Parham Moradi, Saeedeh Mohammadi, Zahra Padar

For Iranians and the Iranian diaspora, the Farsi Twittersphere provides an important alternative to state media and an outlet for political discourse. But this understudied online space has become an opinion manipulation battleground, with diverse actors using inauthentic accounts to advance their goals and shape online narratives. Examining trending discuss

Pride Kavumba, Ryo Takahashi, Yusuke Oda

Finetuning large pre-trained language models with a task-specific head has advanced the state-of-the-art on many natural language understanding benchmarks. However, models with a task-specific head require a lot of training data, making them susceptible to learning and exploiting dataset-specific superficial cues that do not generalize to other datasets. Pro

Hongsheng Hu

A Coxeter group admits infinite-dimensional irreducible complex representations if and only if it is not finite or affine. In this paper, we provide a construction of some of those representations for certain Coxeter groups using some topological information of the corresponding Coxeter graphs.