January 2022 arXiv papers — page 24

Cui Datian, Zhong Sujuan, Song Kexing, Wang Xingxing

As one of the important methods for surface modification of materials and life extension of key components, cemented carbide brazing coatings are widely used in agricultural machinery, oil drilling, aerospace and other fields, it has also attracted the attention of scholars in the field of surface modification at home and abroad. Based on the research report

Wenxin Ding, Gautam Kamath, Weina Wang, Nihar B. Shah

Reviewers in peer review are often miscalibrated: they may be strict, lenient, extreme, moderate, etc. A number of algorithms have previously been proposed to calibrate reviews. Such attempts of calibration can however leak sensitive information about which reviewer reviewed which paper. In this paper, we identify this problem of calibration with privacy, an

Hong Xuan, Robert Pless

Pair-wise loss is an approach to metric learning that learns a semantic embedding by optimizing a loss function that encourages images from the same semantic class to be mapped closer than images from different classes. The literature reports a large and growing set of variations of the pair-wise loss strategies. Here we decompose the gradient of these loss

Ruxin Xu, Huiru Wang

Weighted twin support vector machines (WLTSVM) mines as much potential similarity information in samples as possible to improve the common short-coming of non-parallel plane classifiers. Compared with twin support vector machines (TWSVM), it reduces the time complexity by deleting the superfluous constraints using the inter-class K-Nearest Neighbor (KNN). Mu

Zhengyang Li, Yijia Tang, Jing Chen, Hao Wu

The quadratic Wasserstein metric has shown its power in measuring the difference between probability densities, which benefits optimization objective function with better convexity and is insensitive to data noise. Nevertheless, it is always an important question to make the seismic signals suitable for comparison using the quadratic Wasserstein metric. The

Harold D Chiang, Bruce E Hansen, Yuya Sasaki

We propose improved standard errors and an asymptotic distribution theory for two-way clustered panels. Our proposed estimator and theory allow for arbitrary serial dependence in the common time effects, which is excluded by existing two-way methods, including the popular two-way cluster standard errors of Cameron, Gelbach, and Miller (2011) and the cluster

Rahul Gopinath, Philipp Görz, Alex Groce

Fuzzing is one of the fastest growing fields in software testing. The idea behind fuzzing is to check the behavior of software against a large number of randomly generated inputs, trying to cover all interesting parts of the input space, while observing the tested software for anomalous behaviour. One of the biggest challenges facing fuzzer users is how to v

Enyu Shi, Jiayi Zhang, Shuaifei Chen, Jiakang Zheng

In future sixth-generation (6G) mobile networks, the Internet-of-Everything (IoE) is expected to provide extremely massive connectivity for small battery-powered devices. Indeed, massive devices with limited energy storage capacity impose persistent energy demand hindering the lifetime of communication networks. As a remedy, wireless energy transfer (WET) is

Xinyuan Zheng, Edo Waks

Photonics provide an efficient way to implement quantum walks, the quantum analogue of classical random walk that demonstrates rich physics with potential applications. However, most photonic quantum walks do not involve photon interactions, which limits their potential to explore strongly-correlated many-body physics of light. We propose a strongly interact

Shun Zhang, Tao Zhang, Zhili Chen, N. Xiong

The rapid development of mobile Internet and sharing economy brings the prosperity of Spatial Crowdsourcing (SC). SC applications assign various tasks according to reported location information of task's requesters and outsourced workers (such as DiDi, MeiTuan and Uber). However, SC-servers are often untrustworthy and the exposure of users' locations raises

Zhe Wang, Jiayi Zhang, Hien Quoc Ngo, Bo Ai

In this paper, we investigate a cell-free massive MIMO system with both access points and user equipments equipped with multiple antennas over the Weichselberger Rayleigh fading channel. We study the uplink spectral efficiency (SE) based on a two-layer decoding structure with maximum ratio (MR) or local minimum mean-square error (MMSE) combining applied in t

Tianyuan Xu, Lifeng Chen, Jifa Jiang

This paper studies limit measures of stationary measures of stochastic ordinary differential equations on the Euclidean space and tries to determine which invariant measures of an unperturbed system will survive. Under the assumption for SODEs to admit the Freidlin-Wentzell or Dembo-Zeitouni large deviations principle with weaker compactness condition, we pr

Jianping Cai, Ximeng Liu, Jiayin Li, Shuangyue Zhang

Starting from the local structures to study hierarchical trees is a common research method. However, the cumbersome analysis and description make the naive method challenging to adapt to the increasingly complex hierarchical tree problems. To improve the efficiency of hierarchical tree research, we propose an embeddable matrix representation for hierarchical

Jie Shao, Wei Yao, Peng Wan, Lei Luo

Registration of unmanned aerial vehicle laser scanning (ULS) and ground light detection and ranging (LiDAR) point clouds in forests is critical to create a detailed representation of a forest structure and an accurate inversion of forest parameters. However, forest occlusion poses challenges for marker-based registration methods, and some marker-free automat

Zoubeir Mlika, Soumaya Cherkaoui

The interconnection of vehicles in the future fifth generation (5G) wireless ecosystem forms the so-called Internet of vehicles (IoV). IoV offers new kinds of applications requiring delay-sensitive, compute-intensive and bandwidth-hungry services. Mobile edge computing (MEC) and network slicing (NS) are two of the key enabler technologies in 5G networks that

Neha Deshpande, Nicholas Farris, Vidhur Kumar

Hate speech detection has become an important research topic within the past decade. More private corporations are needing to regulate user generated content on different platforms across the globe. In this paper, we introduce a study of multilingual hate speech classification. We compile a dataset of 11 languages and resolve different taxonomies by analyzin

Benjamin Harris, Yoshiki Oshima

Let $G$ be a real linear reductive group and let $H$ be a unimodular, locally algebraic subgroup. Let $\operatorname{supp} L^2(G/H)$ be the set of irreducible unitary representations of $G$ contributing to the decomposition of $L^2(G/H)$, namely the support of the Plancherel measure. In this paper, we will relate $\operatorname{supp} L^2(G/H)$ with the image

Qingkai Lu, Yifan Zhu, Liangjun Zhang

Excavation of irregular rigid objects in clutter, such as fragmented rocks and wood blocks, is very challenging due to their complex interaction dynamics and highly variable geometries. In this paper, we adopt reinforcement learning (RL) to tackle this challenge and learn policies to plan for a sequence of excavation trajectories for irregular rigid objects,

Lin Li, Chao Chen, Lei Pan, Leo Yu Zhang

Biometric authentication prospered because of its convenient use and security. Early generations of biometric mechanisms suffer from spoofing attacks. Recently, unobservable physiological signals (e.g., Electroencephalogram, Photoplethysmogram, Electrocardiogram) as biometrics offer a potential remedy to this problem. In particular, Photoplethysmogram (PPG)

Ziruo Yi, Ting Xiao, Kaz-Onyeakazi Ijeoma, Ratnam Cheran

Building predictive models for companies often relies on inference using historical data of companies in the same industry sector. However, companies are similar across a variety of dimensions that should be leveraged in relevant prediction problems. This is particularly true for large, complex organizations which may not be well defined by a single industry

Drake Austin, Paige Miesle, Deanna Sessions, Michael Motala

High throughput characterization and processing techniques are becoming increasingly necessary to navigate multivariable, data-driven design challenges for sensors and electronic devices. For two-dimensional materials, device performance is highly dependent upon a vast array of material properties including number of layers, lattice strain, carrier concentra

Ihsan Chaoubi, Camille Besse, Hélène Cossette, Marie-Pier Côté

Detailed information about individual claims are completely ignored when insurance claims data are aggregated and structured in development triangles for loss reserving. In the hope of extracting predictive power from the individual claims characteristics, researchers have recently proposed to move away from these macro-level methods in favor of micro-level

Ryan C. Terrien, Allison Keen, Katy Oda, Winter Parts

Accurate tracers of the stellar magnetic field and rotation are cornerstones for the study of M dwarfs and for reliable detection and characterization of their exoplanetary companions. Such measurements are particularly challenging for old, slowly rotating, fully convective M dwarfs. To explore the use of new activity and rotation tracers, we examined multi-

Xusheng Du, Yi He, Xi Yang, Chia-Ming Chang

3D modeling based on point clouds is an efficient way to reconstruct and create detailed 3D content. However, the geometric procedure may lose accuracy due to high redundancy and the absence of an explicit structure. In this work, we propose a human-in-the-loop sketch-based point cloud reconstruction framework to leverage users cognitive abilities in geometr

Andrea Bonilla-Barroso, J. Ballesteros-Paredes, Jesus Hernández, Luis Aguilar

Using numerical simulations of the formation and evolution of stellar clusters within molecular clouds, we show that the stars in clusters formed within collapsing molecular cloud clumps exhibit a constant velocity dispersion regardless of their mass, as expected in a violent relaxation processes. In contrast, clusters formed in turbulence-dominated environm

Dong Ma, Yang Chen

A time-varying microwave photonic filter (TV-MPF) based on stimulated Brillouin scattering (SBS) is proposed and utilized to suppress the in-band noise of broadband arbitrary microwave waveforms, thereby improving the signal-to-noise ratio (SNR). The filter-controlling signal is designed according to the signal to be filtered and drives the TV-MPF so that th

Zhengyu Huang, Haoran Xie, Tsukasa Fukusato

We propose an interactive 3D character modeling approach from orthographic drawings (e.g., front and side views) based on 2D-space annotations. First, the system builds partial correspondences between the input drawings and generates a base mesh with sweeping splines according to edge information in 2D images. Next, users annotates the desired parts on the i

Hamed Aslani, Davod Khojasteh Salkuyeh

This paper deals with solving a class of three-by-three block saddle point problems. The systems are solved by preconditioning techniques. Based on an iterative method, we construct a block upper triangular preconditioner. The convergence of the presented method is studied in details. Finally, some numerical experiments are given to demonstrate the superiori

Zoubeir Mlika, Soumaya Cherkaoui

This paper studies the multi-agent resource allocation problem in vehicular networks using non-orthogonal multiple access (NOMA) and network slicing. To ensure heterogeneous service requirements for different vehicles, we propose a network slicing architecture. We focus on a non-cellular network scenario where vehicles communicate by the broadcast approach v

Oleksandr Chapurin, Andrei Smolyakov, Gerjan Hagelaar, Jean-Pierre Boeuf

Low-frequency axial oscillations (5-50 kHz) stand out as a pervasive feature observed in many types of Hall thrusters. While it is widely recognized that the ionization effects play the central role in this mode, as manifested via the large scale oscillations of neutral and plasma density, the exact mechanism(s) of the instabilities remain unclear. To gain f

Zudi Lin, Prateek Garg, Atmadeep Banerjee, Salma Abdel Magid

Image super-resolution (SR) is a fast-moving field with novel architectures attracting the spotlight. However, most SR models were optimized with dated training strategies. In this work, we revisit the popular RCAN model and examine the effect of different training options in SR. Surprisingly (or perhaps as expected), we show that RCAN can outperform or matc

Jiaohao Weng, Chao Zhang, Xi Yang, Haoran Xie

With the emergence of large-scale open online courses and online academic conferences, it has become increasingly feasible and convenient to access online educational resources. However, it is time consuming and challenging to effectively retrieve and present numerous lecture videos for common users. In this work, we propose a hierarchical visual interface f

Zhiyi Fan, Kei Yagyu

We investigate CP violating 2 Higgs doublet models as an effective theory emerging from models with an $SU(3)_L \otimes U(1)_X$ gauge symmetry. Because of the extension of the electroweak symmetry, a characteristic structure of Yukawa interactions appears with new CP violating phases at the electroweak scale. In this scenario, the charged Higgs boson loop pr

Adam V. Bruce, Shuanglong Liu, James N. Fry, Hai-Ping Cheng

In certain configurations, the aromatic properties of benzene ring structured molecules allow for unpaired, reactive valence electrons (known as radicals). Clar's goblets are such molecules. With an even number of unpaired radicals, these nanographenes are topologically frustrated hydrocarbons in which pi-bonding network and topology of edges give rise to th

Jessica Yao, Amani Abusafia, Abdallah Lakhdari, Athman Bouguettaya

Wireless energy sharing is a novel convenient alternative to charge IoT devices. In this demo paper, we present a peer-to-peer wireless energy sharing platform. The platform enables users to exchange energy wirelessly with nearby IoT devices. The energy sharing platform allows IoT users to send and receive energy wirelessly. The platform consists of (i) a mo

Ernie Croot, Hamed Mousavi, Maxie Schmidt

We show that for every $r \geq 1$, and all $r$ distinct (sufficiently large) primes $p_1,..., p_r > p_0(r)$, there exist infinitely many integers $n$ such that ${2n \choose n}$ is divisible by these primes to only low multiplicity. From a theorem of Kummer, an upper bound for the number of times that a prime $p_j$ can divide ${2n \choose n}$ is $1+\log n / \

Yasuhiro Wakabayashi

The purpose of the present paper is to make a mathematical study of the differences and relations among possible structures inherent in an object, as well as of the whole structure constituted by them (i.e., the structure of structures), against the background of the structuralism by Claude L\'{e}vi-Strauss and others. Our discussion focuses on Blanchard's c

Assaf Bar-Natan, Advay Goel, Brendan Halstead, Paul Hamrick

In this paper, we study the relationship between the mapping class group of an infinite-type surface and the simultaneous flip graph, a variant of the flip graph for infinite-type surfaces defined by Fossas and Parlier. We show that the extended mapping class group is isomorphic to a proper subgroup of the automorphism group of the flip graph, unlike in the

Afaf Taik, Zoubeir Mlika, Soumaya Cherkaoui

Federated Learning (FL) is expected to play a prominent role for privacy-preserving machine learning (ML) in autonomous vehicles. FL involves the collaborative training of a single ML model among edge devices on their distributed datasets while keeping data locally. While FL requires less communication compared to classical distributed learning, it remains h

Grant A. Riley, Justin M. Shaw, Thomas J. Silva, Hans T. Nembach

The exchange interaction in ferromagnetic ultra-thin films is a critical parameter in magnetization-based storage and logic devices, yet the accurate measurement of it remains a challenge. While a variety of approaches are currently used to determine the exchange parameter, each has its limitations, and good agreement among them has not been achieved. To dat

Daisuke Miura, Akimasa Sakuma

We theoretically investigated magnetocrystalline anisotropy (MA) at a finite temperature $T$ in ferromagnetic metals. Assuming a Rashba-type ferromagnet with uniaxial MA, we defined the MA constants $K_\mathrm{u}(T)$ derived from several different concepts. Our purpose was to examine the equality between them and to confirm a power law between $K_\mathrm{u}(

Yingqi Liu

For a projective variety $X$ in $\mathbb{P}^{m}$ of dimension $n$, an additive action on $X$ is an effective action of $\mathbb{G}_{a}^{n}$ on $\mathbb{P}^{m}$ such that $X$ is $\mathbb{G}_{a}^{n}$-invariant and the induced action on $X$ has an open orbit. Arzhantsev and Popovskiy have classified additive actions on hyperquadrics of corank 0 or 1. In this pa

Bo Wei, Weibin Zhong, Rong Liu, Alan Wu

Decision-making is critical at each stage of drug development and making informed and transparent Go/No-Go decisions require a sound quantitative decision framework. We designed and implemented GOahead, a comprehensive web-based tool to improve how statisticians and collaborators could prospectively plan and implement the selected Go/No-Go decision approach

Yasuhiro Wakabayashi

In the first half of the present paper, we study higher-level generalizations of differential modules in positive characteristic. These objects may be regarded as ring-theoretic counterparts of vector bundles on a curve equipped with an action of the ring of (logarithmic) differential operators of finite level introduced by P. Berthelot (and C. Montagnon). T

Y. Lee, R. Skomski, X. Wang, P. P. Orth

Kagome-lattice magnets $R$Mn$_6$Sn$_6$ recently emerged as a new platform to exploit the interplay between magnetism and topological electronic states. Some of the most exciting features of this family are the dramatic dependence of the easy magnetization direction on the rare-earth specie and the kagome geometry of the Mn planes that in principle can genera

Nobutaka Nakazono

The lattice sine-Gordon equation is an integrable partial difference equation on ${\mathbb Z}^2$, which approaches the sine-Gordon equation in a continuum limit. In this paper, we show that the non-autonomous lattice sine-Gordon equation has the consistency around a broken cube property as well as its autonomous version. Moreover, we construct two new Lax pa

Hailong Dao, David Eisenbud

We study monomial ideals with linear presentation or partially linear resolution. We give combinatorial characterizations of linear presentation for square-free ideals of degree 3, and for primary ideals whose resolutions are linear except for the last step (the "almost linear" case). We also give sharp bounds on Castelnuovo-Mumford regularity and numbers of

Yuichiro Hoshi, Yasuhiro Wakabayashi

In the present paper, we give an upper bound for the generic degree of the generalized Verschiebung between the moduli spaces of rank two stable bundles with trivial determinant.

Jack Y. Qiu, Arne Grimsmo, Kaidong Peng, Bharath Kannan

Squeezing of the electromagnetic vacuum is an essential metrological technique used to reduce quantum noise in applications spanning gravitational wave detection, biological microscopy, and quantum information science. In superconducting circuits, the resonator-based Josephson-junction parametric amplifiers conventionally used to generate squeezed microwaves

Roozbeh Yousefzadeh, Xuenan Cao

Many applications affecting human lives rely on models that have come to be known under the umbrella of machine learning and artificial intelligence. These AI models are usually complicated mathematical functions that map from an input space to an output space. Stakeholders are interested to know the rationales behind models' decisions and functional behavio

Yilun Xu, Hao He, Tianxiao Shen, Tommi Jaakkola

We propose to identify directions invariant to a given classifier so that these directions can be controlled in tasks such as style transfer. While orthogonal decomposition is directly identifiable when the given classifier is linear, we formally define a notion of orthogonality in the non-linear case. We also provide a surprisingly simple method for constru

Hwichan Kim, Sangwhan Moon, Naoaki Okazaki, Mamoru Komachi

South and North Korea both use the Korean language. However, Korean NLP research has focused on South Korean only, and existing NLP systems of the Korean language, such as neural machine translation (NMT) models, cannot properly handle North Korean inputs. Training a model using North Korean data is the most straightforward approach to solving this problem,

Xiaoran Li, Baohong Guo, Anbang Sun, Ute Ebert

In this paper, we address two main topics: steady propagation fields for positive streamers in air and streamer deceleration in fields below the steady propagation field. We generate constant-velocity positive streamers in air with an axisymmetric fluid model, by initially adjusting the applied voltage based on the streamer velocity. After an initial transie

Sarah K. Wyse, Maria M. Martignoni, May Anne Mata, Eric Foxall

In mathematical modeling, several different functional forms can often be used to fit a data set equally well, especially if the data is sparse. In such cases, these mathematically different but similar looking functional forms are typically considered interchangeable. Recent work, however, shows that similar functional responses may nonetheless result in si

Guoxiang Grayson Tong, David Kamensky, John A. Evans

We consider a stabilization method for divergence-conforming B-spline discretizations of the incompressible Navier--Stokes problem wherein jumps in high-order normal derivatives of the velocity field are penalized across interior mesh facets. We prove that this method is pressure robust, consistent, and energy stable, and we show how to select the stabilizat

Haylee N. Archer, Deidre A. Hunter, Bruce G. Elmegreen, Phil Cigan

The low metallicities of dwarf irregular galaxies (dIrr) greatly influence the formation and structure of molecular clouds. These clouds, which consist primarily of H$_2$, are typically traced by CO, but low metallicity galaxies are found to have little CO despite ongoing star formation. In order to probe the conditions necessary for CO core formation in dwa

Afaf Taik, Soumaya Cherkaoui

In the smart grid, huge amounts of consumption data are used to train deep learning models for applications such as load monitoring and demand response. However, these applications raise concerns regarding security and have high accuracy requirements. In one hand, the data used is privacy-sensitive. For instance, the fine-grained data collected by a smart me

Afaf Taik, Hajar Moudoud, Soumaya Cherkaoui

FEderated Edge Learning (FEEL) has emerged as a leading technique for privacy-preserving distributed training in wireless edge networks, where edge devices collaboratively train machine learning (ML) models with the orchestration of a server. However, due to frequent communication, FEEL needs to be adapted to the limited communication bandwidth. Furthermore,

Ryan Zhang, Jiadai Zhu, Stephen Yang, Mahdi S. Hosseini

The lack of well-annotated datasets in computational pathology (CPath) obstructs the application of deep learning techniques for classifying medical images. %Since pathologist time is expensive, dataset curation is intrinsically difficult. Many CPath workflows involve transferring learned knowledge between various image domains through transfer learning. Cur

Bing Wei, Haidong Wu, Qinghong Zhao

A well-known question of Gallai (1966) asked whether there is a vertex which passes through all longest paths of a connected graph. Although this has been verified for some special classes of graphs such as outerplanar graphs, circular arc graphs, and series-parallel graphs, the answer is negative for general graphs. In this paper, we prove among other resul

Xiaodong Wang, Zhixin Wang

For an asymptotically Poincare-Einstein manifold with a lower Ricci curvature bound, we establish a sharp inequality relating the type II Yamabe invariant of the interior and the Yamabe invariant of its conformal infinity

Q. -P. Ding, C. Dissanayake, Santanu Pakhira, W. J. Newsome

We report the results of magnetic susceptibility $\chi$ and $^1$H nuclear magnetic resonance (NMR) measurements on a three-dimensional hyper-honeycomb lattice compound [(C$_2$H$_5$)$_3$NH]$_2$Cu$_2$(C$_2$O$_4$)$_3$ (CCCO). The average value of the antiferromagnetic (AFM) exchange coupling between the Cu$^{2+}$ ($S$ = 1/2) spins was determined to be $J$~$\sim

Christopher Tran, Elena Zheleva

The Linear Threshold Model is a widely used model that describes how information diffuses through a social network. According to this model, an individual adopts an idea or product after the proportion of their neighbors who have adopted it reaches a certain threshold. Typical applications of the Linear Threshold Model assume that thresholds are either the s

Julio Guerrero, Giuseppe Orlando

In this paper, we show that a time-dependent local stochastic volatility (SLV) model can be reduced to a system of autonomous PDEs that can be solved using the Heat kernel, by means of the Wei-Norman factorization method and Lie algebraic techniques. Then, we compare the results of traditional Monte Carlo simulations with the explicit solutions obtained by s

Georgios Papas

Consider a smooth irreducible Hodge generic curve $S$ defined over $\bar{\Q}$ in the Torelli locus $T_g\subset \mathcal{A}_g$. We establish Zilber-Pink-type statements for such curves depending on their intersection with the boundary of the Baily-Borel compactification of $\mathcal{A}_g$. For example, when our curve intersects the $0$-dimensional stratum of

Alon Jacovi, Jasmijn Bastings, Sebastian Gehrmann, Yoav Goldberg

We investigate a formalism for the conditions of a successful explanation of AI. We consider "success" to depend not only on what information the explanation contains, but also on what information the human explainee understands from it. Theory of mind literature discusses the folk concepts that humans use to understand and generalize behavior. We posit that

Andrew Douglas, Prajwal Padmanabh, Scott Ransom, Alessandro Ridolfi

We report the discovery of two Black Widow millisecond pulsars in the globular cluster M28 with the MeerKAT telescope. PSR J1824$-$2452M (M28M) is a 4.78-ms pulsar in a $5.82\,$hour orbit and PSR J1824$-$2452N (M28N) is a 3.35-ms pulsar in a $4.76\,$hour orbit. Both pulsars have dispersion measures near $119.30\,$pc$\,$cm$^{-3}$ and have low mass companion s

Luke C. Rhodes, Matthias Eschrig, Timur K. Kim, Matthew D. Watson

The nature and origin of electronic nematicity remains a significant challenge in our understanding of the iron-based superconductors. This is particularly evident in the iron chalcogenide, FeSe, where it is currently unclear how the experimentally determined Fermi surface near the M point evolves from having two electron pockets in the tetragonal state to e

Nicolas Perkowski, Willem van Zuijlen

We consider the stochastic differential equation on $\mathbb{R}^d$ given by $$ \, \mathrm{d}X_t = b(t,X_t) \, \mathrm{d}t + \, \mathrm{d} B_t, $$ where $B$ is a Brownian motion and $b$ is considered to be a distribution of regularity $ > -\frac12$. We show that the martingale solution of the SDE has a transition kernel $Γ_t$ and prove upper and lower heat ke

M. A. Zubkov

Application of Wigner-Weyl calculus to the investigation of non-dissipative transport phenomena is reviewed. We focus on the quantum Hall effect, Chiral Magnetic effect, and Chiral separation effect, and discuss the role of interactions, inhomogeneity, and deviations from equilibrium.

Anurag Bishnoi, Pete L. Clark

We pursue various restricted variable generalizations of the Chevalley-Warning theorem for low degree polynomial systems over a finite field. Our first such result involves variables restricted to Cartesian products of the Vandermonde subsets of $\F_q$ defined by G\'acs-Weiner and Sziklai-Tak\'ats. We then define an invariant $\uomega(X)$ of a nonempty subse

Luming Zhao

We construct various explicit Herr complexes that compute the Galois cohomology of a $p$-adic representation of the absolute Galois group of a complete discrete valuation field of characteristic $0$ with a perfect residue field of characteristic $p$, using the associated $(\varphi,\tau)$-modules (defined by Xavier Caruso), instead of $(\varphi,\Gamma)$-modul

Károly Bezdek, Zsolt Lángi

A family of spherical caps of the 2-dimensional unit sphere $\mathbb{S}^2$ is called a totally separable packing in short, a TS-packing if any two spherical caps can be separated by a great circle which is disjoint from the interior of each spherical cap in the packing. The separable Tammes problem asks for the largest density of given number of congruent sp

Shabbir Ahmed, Fotis Kopsaftopoulos

In this work, a probabilistic damage detection and identification scheme using stochastic time series models in the context of acousto-ultrasound guided wave-based SHM is proposed, and its performance is assessed experimentally. In order to simplify the damage detection and identification process, model parameters are modified based on the singular value dec

Muhammad Umar, Saeed-Ul Hassan

This paper deploys bibliometric indices and semantic techniques for understanding to what extent research grants are likely to impact publications, research direction, and co-authorship rate of principal investigators. The novelty of this paper lies within the fact that it includes semantic analysis in the research funding evaluation process in order to effe

Boyu Wang, Jorge Mendez, Changjian Shui, Fan Zhou

Learning from multiple related tasks by knowledge sharing and transfer has become increasingly relevant over the last two decades. In order to successfully transfer information from one task to another, it is critical to understand the similarities and differences between the domains. In this paper, we introduce the notion of \emph{performance gap}, an intui

Salar Jafarlou, Jocelyn Lai, Zahra Mousavi, Sina Labbaf

Monitoring and understanding affective states are important aspects of healthy functioning and treatment of mood-based disorders. Recent advancements of ubiquitous wearable technologies have increased the reliability of such tools in detecting and accurately estimating mental states (e.g., mood, stress, etc.), offering comprehensive and continuous monitoring

Munirah Alotaibi, Mohamed Jleli, Maria Alessandra Ragusa, Bessem Samet

In this paper, an initial value problem for a nonlinear time-fractional Schr\"odinger equation with a singular logarithmic potential term is investigated. The considered problem involves the left/forward Hadamard-Caputo fractional derivative with respect to the time variable. Using the test function method with a judicious choice of the test function, we obt

Fernando Alonso-Fernandez, Josef Bigun

We describe a technical solution implemented at Halmstad University to automatise assessment and reporting of results of paper-based quiz exams. Paper quizzes are affordable and within reach of campus education in classrooms. Offering and taking them is accepted as they cause fewer issues with reliability and democratic access, e.g. a large number of student

Gabriel Poesia, Oleksandr Polozov, Vu Le, Ashish Tiwari

Large pre-trained language models have been used to generate code,providing a flexible interface for synthesizing programs from natural language specifications. However, they often violate syntactic and semantic rules of their output language, limiting their practical usability. In this paper, we propose Synchromesh: a framework for substantially improving t

Franklin Mingzhe Li, Cheng Lu, Zhicong Lu, Patrick Carrington

Deaf and Hard-of-Hearing (DHH) audiences have long complained about caption qualities for many online videos created by individual content creators on video-sharing platforms (e.g., YouTube). However, there lack explorations of practices, challenges, and perceptions of online video captions from the perspectives of both individual content creators and DHH au

Nazifa Rumman, Tianhong Wang, Kaitlin Jennings, Pascal Bassène

We present an optical wavefront shaping approach that allows tracking and localization of signal hidden inside or behind a scattering medium. The method combines traditional feedback based wavefront shaping together with a switch function, controlled by two different signals. A simple, in transmission imaging system is used with two detectors: one monitors t

Charles K. C. Lieou, Takeshi Egami

The coherence length of the medium-range order (MRO) in metallic liquids is known to display a Curie-Weiss temperature dependence; its inverse is linearly related to temperature, and when extrapolated from temperatures above the glass transition, the coherence length diverges at a negative temperature with a critical exponent of unity. We propose a mean-fiel

Peyman Azodi, Herschel A. Rabitz

The connection between entanglement dynamics and non-equilibrium statistics in isolated many-body quantum systems has been established both theoretically and experimentally. Many-Body Localization (MBL), a phenomenon where interacting particles in disordered (i.e., random) chains fail to thermalize, exemplifies this connection. However, the systematic proof

Bernardo Marenco, Paola Bermolen, Marcelo Fiori, Federico Larroca

Given a sequence of random (directed and weighted) graphs, we address the problem of online monitoring and detection of changes in the underlying data distribution. Our idea is to endow sequential change-point detection (CPD) techniques with a graph representation learning substrate based on the versatile Random Dot Product Graph (RDPG) model. We consider ef

Alejandro Díaz-Caro, Gilles Dowek

We present a linearity theorem for a proof language of intuitionistic multiplicative additive linear logic, incorporating addition and scalar multiplication. The proofs in this language are linear in the algebraic sense. This work is part of a broader research program aiming to define a logic with a proof language that forms a quantum programming language.

Sheng-Chun Kao, Michael Pellauer, Angshuman Parashar, Tushar Krishna

The design of DNN accelerators includes two key parts: HW resource configuration and mapping strategy. Intensive research has been conducted to optimize each of them independently. Unfortunately, optimizing for both together is extremely challenging due to the extremely large cross-coupled search space. To address this, in this paper, we propose a HW-Mapping

Sameh N. Hameedi, Amir Sagiv, Michael I. Weinstein

We consider the effect of time-periodic forcing on a one-dimensional Schr{\"o}dinger equation with a topologically protected defect (edge) mode. The unforced system models a domain-wall or dislocation defect in a periodic structure, and it supports a defect mode which bifurcates from the Dirac point (linear band crossing) of the underlying bulk medium. We st

Sheng-Chun Kao, Xiaoyu Huang, Tushar Krishna

Dataflow/mapping decides the compute and energy efficiency of DNN accelerators. Many mappers have been proposed to tackle the intra-layer map-space. However, mappers for inter-layer map-space (aka layer-fusion map-space), have been rarely discussed. In this work, we propose a mapper, DNNFuser, specifically focusing on this layer-fusion map-space. While exist

Guy Worthey, Xiang Shi, Tathagata Pal, Hyun-chul Lee

Stellar evolution calculations with variable abundance ratios were used to gauge the effects on temperatures, luminosities, and lifetimes in various phases. Individual elements C, N, O, Mg, Si, and Fe were included. Most of the effect relevant to integrated light models is contained in the temperature variable, as opposed to the timescale or luminosity. We d

Teresa Nieves-Chinchilla, Nathalia Alzate, Hebe Cremades, Laura Rodriguez-Garcia

We investigate the effects of the evolutionary processes in the internal magnetic structure of two interplanetary coronal mass ejections (ICMEs) detected in situ between 2020 November 29 and December 1 by Parker Solar Probe (PSP). The sources of the ICMEs were observed remotely at the Sun in EUV and subsequently tracked to their coronal counterparts in white

Yanxi Chen, H. Vincent Poor

We study the problem of learning a mixture of multiple linear dynamical systems (LDSs) from unlabeled short sample trajectories, each generated by one of the LDS models. Despite the wide applicability of mixture models for time-series data, learning algorithms that come with end-to-end performance guarantees are largely absent from existing literature. There

Samyak Rajanala, Stephen Bates, Trevor Hastie, Robert Tibshirani

Out-of-bag error is commonly used as an estimate of generalisation error in ensemble-based learning models such as random forests. We present confidence intervals for this quantity using the delta-method-after-bootstrap and the jackknife-after-bootstrap techniques. These methods do not require growing any additional trees. We show that these new confidence i

Mohammadreza Soltani, Suya Wu, Yuerong Li, Jie Ding

We propose a new structured pruning framework for compressing Deep Neural Networks (DNNs) with skip connections, based on measuring the statistical dependency of hidden layers and predicted outputs. The dependence measure defined by the energy statistics of hidden layers serves as a model-free measure of information between the feature maps and the output of

Joshua Ong, David Kulpanowski, Yangxinyu Xie, Evdokia Nikolova

Emergency Medical Systems (EMS) provide crucial pre-hospital care and transportation. Faster EMS response time provides quicker pre-hospital care and thus increases survival rate. We reduce response time by providing optimal ambulance stationing and routing decisions by solving two stage stochastic and robust linear programs. Although operational research on

Piotr Żelasko, Siyuan Feng, Laureano Moro Velazquez, Ali Abavisani

The high cost of data acquisition makes Automatic Speech Recognition (ASR) model training problematic for most existing languages, including languages that do not even have a written script, or for which the phone inventories remain unknown. Past works explored multilingual training, transfer learning, as well as zero-shot learning in order to build ASR syst

Andrew Wagenmaker, Yifang Chen, Max Simchowitz, Simon S. Du

Reward-free reinforcement learning (RL) considers the setting where the agent does not have access to a reward function during exploration, but must propose a near-optimal policy for an arbitrary reward function revealed only after exploring. In the the tabular setting, it is well known that this is a more difficult problem than reward-aware (PAC) RL -- wher

Richard Nock, Mathieu Guillame-Bert

While Generative Adversarial Networks (GANs) achieve spectacular results on unstructured data like images, there is still a gap on tabular data, data for which state of the art supervised learning still favours to a large extent decision tree (DT)-based models. This paper proposes a new path forward for the generation of tabular data, exploiting decades-old

Ruinan Jin, Yu Xing, Xingkang He

As one of the most fundamental stochastic optimization algorithms, stochastic gradient descent (SGD) has been intensively developed and extensively applied in machine learning in the past decade. There have been some modified SGD-type algorithms, which outperform the SGD in many competitions and applications in terms of convergence rate and accuracy, such as

Haoyue Guo, Qian Wang, Alexander Urban, Nongnuch Artrith

Lithium thiophosphates (LPS) with the composition (Li$_2$S)$_x$(P$_2$S$_5$)$_{1-x}$ are among the most promising prospective electrolyte materials for solid-state batteries (SSBs), owing to their superionic conductivity at room temperature ($>10^{-3}$ S cm$^{-1}$), soft mechanical properties, and low grain boundary resistance. Several glass-ceramic (gc) LPS