November 2020 arXiv papers — page 36

Loris Nanni, Alessandra Lumini, Stefano Ghidoni, Gianluca Maguolo

Classification of biological images is an important task with crucial application in many fields, such as cell phenotypes recognition, detection of cell organelles and histopathological classification, and it might help in early medical diagnosis, allowing automatic disease classification without the need of a human expert. In this paper we classify biomedic

Kota Hattori

We study the geometric quantization on $K3$ surfaces from the viewpoint of the spectral convergence. We take a special Lagrangian fibrations on the $K3$ surfaces and a family of hyper-K\"ahler structures tending to large complex structure limit, and show a spectral convergence of the $\bar{\partial}$-Laplacians on the prequantum line bundle to the spectral s

R. A. Lomsadze, M. R. Gochitashvili, R. Ya. Kezerashvili, M. Schulz

We study the electron-impact induced ionization of O$_{2}$ from threshold to 120 eV using the electron spectroscopy method. Our approach is simple in concept and embodies the ion source with a collision chamber and a mass spectrometer with a quadruple filter as a selector for the product ions. The combination of these two devices makes it possible to unequiv

Jesni Shamsul Shaari, Rinie N. M. Nasir, Stefano Mancini

We reformulate the notion of uncertainty of pairs of unitary operators within the context of guessing games and derive an entropic uncertainty relation for a pair of such operators. We show how distinguishable operators are compatible while maximal incompatibility of unitary operators can be connected to bases for some subspace of operators which are mutuall

Peter Robinson, Raghavendra Ramesh

The General Purpose Atomic Crosschain Transaction protocol allows composable programming across multiple Ethereum blockchains. It allows for inter-contract and inter-blockchain function calls that are both synchronous and atomic: if one part fails, the whole call execution tree of function calls is rolled back. The protocol operates on existing Ethereum bloc

Gautam Goel, Babak Hassibi

We consider measurement-feedback control in linear dynamical systems from the perspective of regret minimization. Unlike most prior work in this area, we focus on the problem of designing an online controller which competes with the optimal dynamic sequence of control actions selected in hindsight, instead of the best controller in some specific class of con

Basile Van Hoorick, Carl Vondrick

The elementary operation of cropping underpins nearly every computer vision system, ranging from data augmentation and translation invariance to computational photography and representation learning. This paper investigates the subtle traces introduced by this operation. For example, despite refinements to camera optics, lenses will leave behind certain clue

Rupert L. Frank, Simon Larson

In this short note we would like to show that one can use Davies's Hardy inequality to rederive well-known results of Lieb and Rozenblum.

Zhiwen Xiao, Xin Xu, Huanlai Xing, Shouxi Luo

Time series data usually contains local and global patterns. Most of the existing feature networks pay more attention to local features rather than the relationships among them. The latter is, however, also important yet more difficult to explore. To obtain sufficient representations by a feature network is still challenging. To this end, we propose a novel

Guosheng Fu

The auxiliary space preconditioning (ASP) technique is applied to the HDG schemes for three different elliptic problems with a parameter dependent low order term, namely, a symmetric interior penalty HDG scheme for the scalar reaction-diffusion equation, a divergence-conforming HDG scheme for a vectorial reaction-diffusion equation, and a C 0 -continuous int

Yunzhe Tao, Sahika Genc, Jonathan Chung, Tao Sun

Accelerating learning processes for complex tasks by leveraging previously learned tasks has been one of the most challenging problems in reinforcement learning, especially when the similarity between source and target tasks is low. This work proposes REPresentation And INstance Transfer (REPAINT) algorithm for knowledge transfer in deep reinforcement learni

Yanshi Wang, Jie Zhang, Qing Da, Anxiang Zeng

Estimating post-click conversion rate (CVR) accurately is crucial in E-commerce. However, CVR prediction usually suffers from three major challenges in practice: i) data sparsity: compared with impressions, conversion samples are often extremely scarce; ii) sample selection bias: conventional CVR models are trained with clicked impressions while making infer

Shu Guo, Hao Zhang, Wenxue Li, Lin Pang

The transmission matrix (TM) is a representation to describe the light scattering process through a scattering medium. The degree of control elements in TM is correlated with the capacity of evaluating enormous equations with tremendous number of unknow parameters, which seriously restricts the efficiency and accuracy of TM, and thus further confines applica

Wenyu Zhao, Teli Ma, Xuan Gong, Baochang Zhang

Edge computing is promising to become one of the next hottest topics in artificial intelligence because it benefits various evolving domains such as real-time unmanned aerial systems, industrial applications, and the demand for privacy protection. This paper reviews recent advances on binary neural network (BNN) and 1-bit CNN technologies that are well suita

Claire E. Heaney, Yuling Li, Omar K. Matar, Christopher C. Pain

This paper presents the first classical Convolutional Neural Network (CNN) that can be applied directly to data from unstructured finite element meshes or control volume grids. CNNs have been hugely influential in the areas of image classification and image compression, both of which typically deal with data on structured grids. Unstructured meshes are frequ

Marc-Andre Brassard, Neil Causley, Nasser Krizou, Joshua A. Dijksman

We experimentally and theoretically study impacts into dense cornstarch and water suspensions. We vary impact speed as well as intruder size, shape, and mass, and we characterize the resulting dynamics using high-speed video and an onboard accelerometer. We numerically solve previously proposed models, most notably the added-mass model as well as a class of

D. Álvarez

We give a new proof of the equivalence between the existence of a complete action of a Lie algebroid on a surjective submersion and its integrability. The main tools in our approach are double Lie groupoids and multiplicative foliations, our proof relies on a simple characterization of those vacant double Lie groupoids which induce a Lie groupoid structure o

Allen H Boozer, Todd Elder

In laboratory and natural plasmas of practical interest, the spatial scale $\Delta_d$ at which magnetic field lines lose distinguishability differs enormously from the scale $a$ of magnetic reconnection across the field lines. In the solar corona, plasma resistivity gives $a/\Delta_d\sim10^{12}$, which is the magnetic Reynold number $R_m$. The traditional re

Simon J. Murphy, Meridith Joyce, Timothy R. Bedding, Timothy R. White

HD\,139614 is known to be a $\sim$14-Myr-old, possibly pre-main-sequence star in the Sco-Cen OB association in the Upper Centaurus-Lupus subgroup, with a slightly warped circumstellar disc containing ring structures hinting at one or more planets. The star's chemical abundance pattern is metal-deficient except for volatile elements, which places it in the $\

Florent Dewez, Benjamin Guedj, Arthur Talpaert, Vincent Vandewalle

Many real-world problems require to optimise trajectories under constraints. Classical approaches are based on optimal control methods but require an exact knowledge of the underlying dynamics, which could be challenging or even out of reach. In this paper, we leverage data-driven approaches to design a new end-to-end framework which is dynamics-free for opt

Bo Liu, Ming Ding, Sina Shaham, Wenny Rahayu

The newly emerged machine learning (e.g. deep learning) methods have become a strong driving force to revolutionize a wide range of industries, such as smart healthcare, financial technology, and surveillance systems. Meanwhile, privacy has emerged as a big concern in this machine learning-based artificial intelligence era. It is important to note that the p

Yiling Huang, Yutian Chen, Jason Pelecanos, Quan Wang

In recent years, Text-To-Speech (TTS) has been used as a data augmentation technique for speech recognition to help complement inadequacies in the training data. Correspondingly, we investigate the use of a multi-speaker TTS system to synthesize speech in support of speaker recognition. In this study we focus the analysis on tasks where a relatively small nu

Guy Metivier, Kevin Zumbrun

We introduce a new approach to the study of modulation of high-frequency periodic wave patterns, based on pseudodifferential analysis, multi-scale expansion, and Kreiss symmetrizer estimates like those in hyperbolic and hyperbolic-parabolic boundary-value theory. Key ingredients are local Floquet transformation as a preconditioner removing large derivatives

Sunil Philip

Let $R$ be a unital commutative ring with unit and $\mathscr{G}$ an ample groupoid. Using the topology of the groupoid $\mathscr{G}$, Steinberg defined an etale groupoid algebra $R\mathscr{G}$. These etale groupoid algebras generalize various algebras including group algebras, commutative algebras over a field generated by idempotents, traditional groupoid a

Keagan Blanchette, Saurya Das, Samantha Hergott, Saeed Rastgoo

We derive loop quantum gravity corrections to the Raychaudhuri equation in the interior of a Schwarzschild black hole and near the classical singularity. We show that the resulting effective equation implies defocusing of geodesics due to the appearance of repulsive terms. This prevents the formation of conjugate points, renders the singularity theorems inap

Felix Wimbauer, Nan Yang, Lukas von Stumberg, Niclas Zeller

In this paper, we propose MonoRec, a semi-supervised monocular dense reconstruction architecture that predicts depth maps from a single moving camera in dynamic environments. MonoRec is based on a multi-view stereo setting which encodes the information of multiple consecutive images in a cost volume. To deal with dynamic objects in the scene, we introduce a

Adrian Ortega, Thomas Gorin, Craig S. Hamilton

We present a theoretical and numerical study of the competition between two opposite interference effects, namely interference-induced ballistic transport on one hand, and strong (Anderson) localization on the other. While the former effect allows for resistance free transport, the latter brings the transport to a complete halt. As a model system, we conside

Radovan Dermisek, Keith Hermanek, Navin McGinnis

We show that in a two Higgs doublet model type-II extended by vectorlike leptons the contributions from heavy neutral and charged Higgs bosons to the anomalous magnetic moment of the muon simultaneously feature chiral enhancement from masses of new leptons and $\tan^2 \beta$ enhancement from couplings of Higgs bosons. Assuming moderate values of new Yukawa c

Daniel Juan-Pineda, Luis Jorge Sánchez Saldaña

We provide descriptions of the Whitehead groups, and the algebraic $K$-theory groups, of the fundamental group of a connected, oriented, closed $3$-manifold in terms of Whitehead groups of their finite subgroups and certain Nil-groups. The main tools we use are: the K-theoretic Farrell-Jones isomorphism conjecture, the construction of models for the universa

Juhyun Kim

We prove that the rank of knot Floer homology detects the Hopf links, and generalize this result further to classify the links of the second smallest knot Floer homology. We also prove a knot Floer homology analog of arXiv:1910.04246v1 [math.GT] and give a partial answer to when the equality holds in the rank inequality between the knot Floer homology of a l

Valentin M. Slepukhin, Maximilian J. Grill, Qingda Hu, Elliot L. Botvinick

Bundles of stiff filaments are ubiquitous in the living world, found both in the cytoskeleton and in the extracellular medium. These bundles are typically held together by smaller cross-linking molecules. We demonstrate analytically, numerically and experimentally that such bundles can be kinked, i.e., have localized regions of high curvature that are long-l

Cheng Ma, Gyorgy Korniss, Boleslaw K. Szymanski, Jianxi Gao

Many systems may switch to an undesired state due to internal failures or external perturbations, of which critical transitions toward degraded ecosystem states are a prominent example. Resilience restoration focuses on the ability of spatially-extended systems and the required time to recover to their desired states under stochastic environmental conditions

Yushi Hu, Shane Settle, Karen Livescu

Query-by-example (QbE) speech search is the task of matching spoken queries to utterances within a search collection. In low- or zero-resource settings, QbE search is often addressed with approaches based on dynamic time warping (DTW). Recent work has found that methods based on acoustic word embeddings (AWEs) can improve both performance and search speed. H

Cong Cao, Jianshan Liao, Victor Breedveld, Eric R Weeks

We study the rheology of monodisperse and bidisperse emulsions with various droplet sizes (1 $\mu$m -- 2 $\mu$m diameter). Above a critical volume fraction $\phi_c$, these systems exhibit solid-like behavior and a yield stress can be detected. Previous experiments suggest that for small thermal particles, rheology will see a glass transition at $\phi_c = \ph

Edward Kim, Connor Onweller, Andrew O'Brien, Kathleen McCoy

Artificial neural networks (ANNs), specifically deep learning networks, have often been labeled as black boxes due to the fact that the internal representation of the data is not easily interpretable. In our work, we illustrate that an ANN, trained using sparse coding under specific sparsity constraints, yields a more interpretable model than the standard de

Mariam Alaverdian, William Gilroy, Veronica Kirgios, Xia Li

We present a preliminary study of a knowledge graph created from season one of the television show Veronica Mars, which follows the eponymous young private investigator as she attempts to solve the murder of her best friend Lilly Kane. We discuss various techniques for mining the knowledge graph for clues and potential suspects. We also discuss best practice

Chen-Huan Wu

We investigate the electronic properties of the boson mode in a three-point fermion loop. In this framwork, the single-particle excitation and the many-body local (in imaginary time and momentum space) field effects are investigated in IR or UV limits with the density fluctuation induced by external potential (or bosonic frequency). While in the limit of van

C. Reichhardt, C. J. O. Reichhardt

We numerically examine the depinning and sliding dynamics of a Wigner crystal in the presence of quenched disorder and a magnetic field. In the disorder-free limit, the Wigner crystal Hall angle is independent of crystal velocity, but when disorder is present, we find that Hall angle starts near zero at the depinning threshold and increases linearly with inc

Owen Ren, Mohamed Ali Boussaidi, Dmitry Voytsekhovsky, Manabu Ihara

We present a Python implementation for RS-HDMR-GPR (Random Sampling High Dimensional Model Representation Gaussian Process Regression). The method builds representations of multivariate functions with lower-dimensional terms, either as an expansion over orders of coupling or using terms of only a given dimensionality. This facilitates, in particular, recover

Cong Zhang, Guanghua Xiao, Chul Moon, Min Chen

Medical imaging is a form of technology that has revolutionized the medical field in the past century. In addition to radiology imaging of tumor tissues, digital pathology imaging, which captures histological details in high spatial resolution, is fast becoming a routine clinical procedure for cancer diagnosis support and treatment planning. Recent developme

Nikolas Dawson, Mary-Anne Williams, Marian-Andrei Rizoiu

Job security can never be taken for granted, especially in times of rapid, widespread and unexpected social and economic change. These changes can force workers to transition to new jobs. This may be because new technologies emerge or production is moved abroad. Perhaps it is a global crisis, such as COVID-19, which shutters industries and displaces labor en

David Herrera

Lin's theorem states that for all $\epsilon > 0$, there is a $\delta > 0$ such that for all $n \geq 1$ if self-adjoint contractions $A,B \in M_n(\mathbb{C})$ satisfy $\|[A,B]\|< \delta$ then there are self-adjoint contractions $A',B' \in M_n(\mathbb{C})$ with $[A',B']=0$ and $\|A-A'\|,\|B-B'\|<\epsilon$. We present fully explained and corrected details of th

Éva Jungábel

Wu and Jans introduced quasi-projective modules where they say a $\cal R$ module $\cal M$ is quasi-projective if for every submodule $\cal N$, for every homomorphism $f : {\cal M} \rightarrow {\cal M}/{\cal N}$ and every epimorphism $j: {\cal M}\rightarrow {\cal M}/{\cal N}$ there is an endomorphism $\phi$ of $\cal M$ such that $\phi\circ j=f$. We say that a

Qianni Jiang, Chong Wang, Paul Malinowski, Zhaoyu Liu

The intrinsic antiferromagnetic topological insulator MnBi$_{2}$Te$_{4}$ undergoes a metamagnetic transition in a c-axis magnetic field. It has been predicted that ferromagnetic MnBi$_{2}$Te$_{4}$ is an ideal Weyl semimetal with a single pair of Weyl nodes. Here we report measurements of quantum oscillations detected in the field-induced ferromagnetic phase

E Benitez Rodriguez, E Piceno Martinez, L M Arevalo Aguilar

Quantum nonlocality and quantum steering are fundamental correlations of quantum systems which can not be created using classical resources only. Nonlocality describes the ability to influence the possible results of measurements carried out in distant systems, in quantum steering Alice remotely steers Bob's state. Research in nonlocality and steering posses

D. Álvarez

In this work we study the integrability of quotients of quasi-Poisson manifolds. Our approach allows us to put several classical results about the integrability of Poisson quotients in a common framework. By categorifying one of the already known methods of reducing symplectic groupoids we also describe double symplectic groupoids which integrate the recentl

Robbert Fokkink, Symeon Papavassiliou, Christos Pelekis

Let $S$ and $X$ be independent random variables, assuming values in the set of non-negative integers, and suppose further that both $\mathbb{E}(S)$ and $\mathbb{E}(X)$ are integers satisfying $\mathbb{E}(S)\ge \mathbb{E}(X)$. We establish a sufficient condition for the tail probability $\mathbb{P}(S\ge \mathbb{E}(S))$ to be larger than $\mathbb{P}(S+X\ge \ma

Nicolas Brodu, James P. Crutchfield

We merge computational mechanics' definition of causal states (predictively-equivalent histories) with reproducing-kernel Hilbert space (RKHS) representation inference. The result is a widely-applicable method that infers causal structure directly from observations of a system's behaviors whether they are over discrete or continuous events or time. A structu

L. B. Zhao, K. D. Wang, K. Bartschat

The problem of photoionization of atomic hydrogen in a white-dwarf-strength magnetic field is revisited to understand the existing discrepancies in the positive-energy spectra obtained by a variety of theoretical approaches reported in the literature. Oscillator strengths for photoionization are calculated with the adiabatic-basis-expansion method developed

Éva Jungábel

A structure $\cal S$ is quasi-projective if for every structure $\cal T$, for every homomorphism $f : {\cal S} \rightarrow {\cal T}$ and every epimorphism $j: {\cal S}\rightarrow {\cal T}$ there is an endomorphism $\phi$ of $\cal S$ such that $\phi\circ j=f$. In this paper, we characterise the quasi-projective posets and lattices of arbitrary cardinalities,

Amin Mivehchi, Qiang Zhang, Melike Kurt, Daniel B. Quinn

Scaling laws for the thrust production and power consumption of a purely pitching hydrofoil in ground effect are presented. For the first time, ground effect scaling laws based on physical insights capture the propulsive performance over a wide range of biologically-relevant Strouhal numbers, dimensionless amplitudes, and dimensionless ground distances. This

Danil F. Kornovan, Roman S. Savelev, Yuri S. Kivshar, Mihail I. Petrov

We introduce a novel physical mechanism for achieving giant quality factors ($Q$-factors) in finite-length periodic arrays of subwavelength optical resonators. The underlying physics is based on interference between the band-edge mode and another standing mode in the array, and the formation of spatially localized states with dramatically suppressed radiativ

Andrei Shubin

We continue to study the distribution of prime numbers $p$, satisfying the condition $\{ p^{\alpha} \} \in I \subset [0; 1)$, in arithmetic progressions. In the paper, we prove an analogue of Bombieri-Vinogradov theorem for $0 < \alpha < 1/9$ with the level of distribution $\theta = 2/5 - (3/5) \alpha$, which improves the previous result corresponding to $\t

Charles Herrmann, Chen Wang, Richard Strong Bowen, Emil Keyder

Image stitching is typically decomposed into three phases: registration, which aligns the source images with a common target image; seam finding, which determines for each target pixel the source image it should come from; and blending, which smooths transitions over the seams. As described in [1], the seam finding phase attempts to place seams between pixel

Qian Xie, Li Jin

Classical queuing network control strategies typically rely on accurate knowledge of model data, i.e., arrival and service rates. However, such data are not always available and may be time-variant. To address this challenge, we consider a class of model data-independent (MDI) control policies that only rely on traffic state observation and network topology.

David Biertimpel, Sindi Shkodrani, Anil S. Baslamisli, Nóra Baka

Instance segmentation methods require large datasets with expensive and thus limited instance-level mask labels. Partially supervised instance segmentation aims to improve mask prediction with limited mask labels by utilizing the more abundant weak box labels. In this work, we show that a class agnostic mask head, commonly used in partially supervised instan

Eduardo Dominguez, Roberto Mulet, Carlos Lopetegui

We exploit the Quantum Cluster Variational Method (QCVM) to study the $J_1$-$J_2$ model for quantum Ising spins. We first describe the QCVM and discuss how it is related to other Mean Field approximations. The phase diagram of the model is studied at the level of the Kikuchi approximation in square lattices as a function of the ratio between $g = J_2/J_1$ ,

Carlos H. C. Pena, Mateus G. Machado, Mariana S. Barros, José D. P. Silva

The IEEE Very Small Size Soccer (VSSS) is a robot soccer competition in which two teams of three small robots play against each other. Traditionally, a deterministic coach agent will choose the most suitable strategy and formation for each adversary's strategy. Therefore, the role of a coach is of great importance to the game. In this sense, this paper propo

Charles Herrmann, Chen Wang, Richard Strong Bowen, Emil Keyder

Panorama creation is one of the most widely deployed techniques in computer vision. In addition to industry applications such as Google Street View, it is also used by millions of consumers in smartphones and other cameras. Traditionally, the problem is decomposed into three phases: registration, which picks a single transformation of each source image to al

Peter J. Forrester

The eigenvalue probability density function (PDF) for the Gaussian unitary ensemble has a well known analogy with the Boltzmann factor for a classical log-gas with pair potential $- \log | x - y|$, confined by a one-body harmonic potential. A generalisation is to replace the pair potential by $- \log |\sinh (\pi (x-y)/L) |$. The resulting PDF first appeared

Florin Spineanu, Madalina Vlad

We discuss a possible perspective on the process of transition from the layer of sheared poloidal rotation in the H-mode to a set of discrete filaments that concentrate vorticity and current density. They may be precursors of the Edge Localized Modes.

Amir Miraki, Hamid Saeedi-Sourck, Nicola Marchetti, Arman Farhang

In this paper, we present a structure for two-channel spline graph filter bank with spectral sampling (SGFBSS) on arbitrary undirected graphs. Our proposed structure has many desirable properties; namely, perfect reconstruction, critical sampling in spectral domain, flexibility in choice of shape and cut-off frequency of the filters, and low complexity imple

Anindya Bhaduri, Christopher S. Meyer, John W. Gillespie, Bazle Z. Haque

Discrete response of structures is often a key probabilistic quantity of interest. For example, one may need to identify the probability of a binary event, such as, whether a structure has buckled or not. In this study, an adaptive domain-based decomposition and classification method, combined with sparse grid sampling, is used to develop an efficient classi

Chengyue Gong, Dilin Wang, Qiang Liu

Semi-supervised learning (SSL) is a key approach toward more data-efficient machine learning by jointly leverage both labeled and unlabeled data. We propose AlphaMatch, an efficient SSL method that leverages data augmentations, by efficiently enforcing the label consistency between the data points and the augmented data derived from them. Our key technical c

Chengyue Gong, Dilin Wang, Meng Li, Vikas Chandra

Data augmentation (DA) is an essential technique for training state-of-the-art deep learning systems. In this paper, we empirically show data augmentation might introduce noisy augmented examples and consequently hurt the performance on unaugmented data during inference. To alleviate this issue, we propose a simple yet highly effective approach, dubbed \emph

Mostafa Jahanifar, Neda Zamani Tajeddin, Meisam Hasani, Babak Shekarchi

Tendon injuries like tendinopathies, full and partial thickness tears are prevalent, and the supraspinatus tendon (SST) is the most vulnerable ones in the rotator cuff. Early diagnosis of SST tendinopathies is of high importance and hard to achieve using ultrasound imaging. In this paper, an automatic tendinopathy recognition framework based on convolutional

Faustino Prieto, José María Sarabia, Enrique Calderín-Ojeda

In this paper, we analyzed how business age and mortality are related during the first years of life, and tested the different hypotheses proposed in the literature. For that, we used data on U.S. business establishments, with 1-year resolution in the range of age of 0-5 years, in the period 1977-2016, published by the United States Census Bureau. First, we

Lin Chen, Biswajit Basu, Calin-I Martin

We numerically investigate the flow structure of periodic steady water waves of fixed relative mass flux propagating on rotational flows with piece-wise constant vorticity. We show that for wave solutions along the global bifurcation diagram the stagnation point can first occur internally or at the bottom, and then again occurs at the crest with further incr

Jiayue Qi, Josef Schicho

A phylogenetic tree is a tree with a fixed set of leaves that has no vertices of degree two. In this paper, we axiomatically define four other discrete structures on the set of leaves. We prove that each of these structures is an equivalent representation of a phylogenetic tree.

Sandra Carillo, Maria Grazia Naso, Elena Vuk, Federico Zullo

We investigate the possibility to obtain a thermal diode with functionally graded Si-Ge alloys. A wire with variable section is considered. After the introduction of a formula giving the thermal conductivity of the wire as a function of the species content and of the diameter of the wire, numerical and analytical results are presented supporting the impracti

Felipe Godoy

Humor is a natural and fundamental component of human interactions. When correctly applied, humor allows us to express thoughts and feelings conveniently and effectively, increasing interpersonal affection, likeability, and trust. However, understanding the use of humor is a computationally challenging task from the perspective of humor-aware language proces

Bryce Sandlund, Lingyi Zhang

We show the $O(\log n)$ time extract minimum function of efficient priority queues can be generalized to the extraction of the $k$ smallest elements in $O(k \log(n/k))$ time (we define $\log(x)$ as $\max(\log_2(x), 1)$.), which we prove optimal for comparison-based priority queues with $o(\log n)$ time insertion. We show heap-ordered tree selection (Kaplan e

Camila Olarte Parra, Ingeborg Waernbaum, Staffan Schön, Els Goetghebeur

Numerous tutorials and research papers focus on methods in either survival analysis or causal inference, leaving common complications in medical studies unaddressed. In practice one must handle problems jointly, without the luxury of ignoring essential features of the data structure. In this paper, we follow incident cases of end-stage renal disease and exam

Giovanni Punzi

The frequentist definition of sensitivity of a search for new phenomena proposed in arXiv:0308063 has been utilized in a number of published experimental searches. In most cases, the simple approximate formula for the common problem of Poisson counts with background has been deemed adequate for the purpose. There are however many problems nowadays in which m

Chao Peng, Junqi Xie, Sylvester Joosten, Zein-Eddine Meziani

The solenoidal large intensity device (SoLID) at Jefferson Lab will push the boundaries of luminosity for a large-acceptance detector, which necessitates the use of a light-gas threshold Cherenkov counter for online event selection. Due to the high luminosity, the single-photon background rate in this counter can exceed 160 kHz/cm$^2$ at the photosensors. Th

Henri Kauhanen

People tend to align their use of language to the linguistic behaviour of their own ingroup and to simultaneously diverge from the language use of outgroups. This paper proposes to model this phenomenon of sociolinguistic identity maintenance as an evolutionary game in which individuals play the field and the dynamics are supplied by a multi-population exten

Leo Alcock, Sualeh Asif, Jeffrey Bosboom, Josh Brunner

When can $n$ given numbers be combined using arithmetic operators from a given subset of $\{+, -, \times, \div\}$ to obtain a given target number? We study three variations of this problem of Arithmetic Expression Construction: when the expression (1) is unconstrained; (2) has a specified pattern of parentheses and operators (and only the numbers need to be

Chao Peng, Ajitha Rajan

Android Apps are frequently updated, every couple of weeks, to keep up with changing user, hardware and business demands. Correctness of App updates is checked through extensive testing. Recent research has proposed tools for automated GUI event generation in Android Apps. These techniques, however, are not efficient at checking App updates as the generated

Tri Huynh, Simon Kornblith, Matthew R. Walter, Michael Maire

Self-supervised representation learning has made significant leaps fueled by progress in contrastive learning, which seeks to learn transformations that embed positive input pairs nearby, while pushing negative pairs far apart. While positive pairs can be generated reliably (e.g., as different views of the same image), it is difficult to accurately establish

G. S. Romo-Cárdenas, M. A. Cosío-León, G. J. Avilés-Rodriguez, N. Isiodoro-Carballo

This work reports on the design, implementation and evaluation of a survey used as a remote sanitary filter, which was applied in the Adventist Educational System of Baja California. During the SARS-CoV-2 sanitary contingency. This with the intention of acquiring information safely and in real time. Allowing to safeguard the integrity of the educational comm

Truc Lam Bui, Krishnendu Chatterjee, Tushar Gautam, Andreas Pavlogiannis

The verification of concurrent programs remains an open challenge due to the non-determinism in inter-process communication. One algorithmic problem in this challenge is the consistency verification of concurrent executions. Consistency verification under a reads-from map allows to compute the reads-from (RF) equivalence between concurrent traces, with direc

Emanuel H. Rubensson, Elias Rudberg, Anastasia Kruchinina, Anton G. Artemov

We present a C++ header-only parallel sparse matrix library, based on sparse quadtree representation of matrices using the Chunks and Tasks programming model. The library implements a number of sparse matrix algorithms for distributed memory parallelization that are able to dynamically exploit data locality to avoid movement of data. This is demonstrated for

Anna Marie Bohmann, Markus Szymik

The algebraic K-theory of Lawvere theories is a conceptual device to elucidate the stable homology of the symmetry groups of algebraic structures such as the permutation groups and the automorphism groups of free groups. In this paper, we fully address the question of how Morita equivalence classes of Lawvere theories interact with algebraic K-theory. On the

Sourangsu Banerji, Apratim Majumder, Alex Hamrick, Rajesh Menon

In this work, we demonstrate three ultra-compact integrated-photonics devices, which are designed via a machine-learning algorithm coupled with finite-difference time-domain (FDTD) modeling. Through digitizing the design domain into "binary pixels" these digital metamaterials are readily manufacturable as well. By showing a variety of devices (beamsplitters

M. F. Gonzalez-Zalba, S. de Franceschi, E. Charbon, T. Meunier

Complementary metal-oxide semiconductor (CMOS) technology has radically reshaped the world by taking humanity to the digital age. Cramming more transistors into the same physical space has enabled an exponential increase in computational performance, a strategy that has been recently hampered by the increasing complexity and cost of miniaturization. To conti

Krishna Chitti, Joao Vieira, Behrooz Makki

In this paper, we study an application of deep learning to uplink multiuser detection (MUD) for non-orthogonal multiple access (NOMA) scheme based on Welch bound equality spread multiple access (WSMA). Several non-cooperating users, each with its own preassigned NOMA signature sequence (SS), transmit over the same resource. These SSs have low correlation amo

Jean-François Tremblay, Travis Manderson, Aurélio Noca, Gregory Dudek

Dynamics modeling in outdoor and unstructured environments is difficult because different elements in the environment interact with the robot in ways that can be hard to predict. Leveraging multiple sensors to perceive maximal information about the robot's environment is thus crucial when building a model to perform predictions about the robot's dynamics wit

Dong Yang, Ziyue Xu, Wenqi Li, Andriy Myronenko

The recent outbreak of COVID-19 has led to urgent needs for reliable diagnosis and management of SARS-CoV-2 infection. As a complimentary tool, chest CT has been shown to be able to reveal visual patterns characteristic for COVID-19, which has definite value at several stages during the disease course. To facilitate CT analysis, recent efforts have focused o

Thomas Groß

Internet Users' Information Privacy Concerns (IUIPC-10) is one of the most endorsed privacy concern scales. It is widely used in the evaluation of human factors of PETs and the investigation of the privacy paradox. Even though its predecessor Concern For Information Privacy (CFIP) has been evaluated independently and the instrument itself seen some scrutiny,

Alekzander Kosakowski, Mukremin Kilic, Warren R. Brown

We present the Apache Point Observatory BG40 broadband and simultaneous Gemini $r$-band and $i$-band high-speed follow-up photometry observations and analysis of the 40.5 minute period eclipsing detached double-degenerate binary SDSS J082239.54$+$304857.19. Our APO data spans over 318 days and includes 13 primary eclipses, from which we precisely measure the

Ilia Pirashvili

The aim of this paper is to study the points and localising subcategories of the topos of $M$-sets, for a finite monoid $M$. We show that the points of this topos can be fully classified using the idempotents of $M$. We introduce a topology on the iso-classes of these points, which differs from the classical topology introduced in SGA4. Likewise, the localis

David A. Kopriva, Gregor J. Gassner, Jan Nordström

We use the behavior of the $L_{2}$ norm of the solutions of linear hyperbolic equations with discontinuous coefficient matrices as a surrogate to infer stability of discontinuous Galerkin spectral element methods (DGSEM). Although the $L_{2}$ norm is not bounded by the initial data for homogeneous and dissipative boundary conditions for such systems, the $L_

Ruikang Zhong, Xiao Liu, Yuanwei Liu, Yue Chen

A communication enabled indoor intelligent robots (IRs) service framework is proposed, where non-orthogonal multiple access (NOMA) technique is adopted to enable highly reliable communications. In cooperation with the ultramodern indoor channel model recently proposed by the International Telecommunication Union (ITU), the Lego modeling method is proposed, w

Anshuman Misra, Ajay D. Kshemkalyani

Testing for causality between events in distributed executions is a fundamental problem. Vector clocks solve this problem but do not scale well. The probabilistic Bloom clock can determine causality between events with lower space, time, and message-space overhead than vector clock; however, predictions suffer from false positives. We give the protocol for t

Thomas Lavastida, Benjamin Moseley, R. Ravi, Chenyang Xu

We propose a new model for augmenting algorithms with predictions by requiring that they are formally learnable and instance robust. Learnability ensures that predictions can be efficiently constructed from a reasonable amount of past data. Instance robustness ensures that the prediction is robust to modest changes in the problem input, where the measure of

Thibaut Vidal

The vehicle routing problem is one of the most studied combinatorial optimization topics, due to its practical importance and methodological interest. Yet, despite extensive methodological progress, many recent studies are hampered by the limited access to simple and efficient open-source solution methods. Given the sophistication of current algorithms, reim

Igor Samokhin, Tatiana Yakushkina, Alexander S. Bratus

Consider a mathematical model of evolutionary adaptation of fitness landscape and mutation matrix as a reaction to population changes. As a basis, we use an open quasispecies model, which is modified to include explicit death flow. We assume that evolutionary parameters of mutation and selection processes vary in a way to maximize the mean fitness of the sys

Mikko Kiviranta

We suggest a SQUID amplifier configuration with improved power efficiency, for applications where cooling budgets are limited, in particular superconducting detector array readouts in space observatories. The suggested two-SQUID configuration keeps one SQUID in a zero-voltage state during a half-cycle of the input while the other SQUID generates voltage. For

Charilaos Mylonas, Eleni Chatzi

In this work, a novel approach for the construction and training of time series models is presented that deals with the problem of learning on large time series with non-equispaced observations, which at the same time may possess features of interest that span multiple scales. The proposed method is appropriate for constructing predictive models for non-stat

Damir Vrabac, Raphael Stern, Philip E. Paré

In this paper we present the discrete-time networked SIR and SEIR models and present assumptions under which they are well defined. We analyze the limiting behavior of the models and present necessary and sufficient conditions for estimating the spreading parameters from data. We illustrate these results via simulation.