arXiv papers from July 2022

Shuvendu Roy, Ali Etemad

Training deep neural networks for image recognition often requires large-scale human annotated data. To reduce the reliance of deep neural solutions on labeled data, state-of-the-art semi-supervised methods have been proposed in the literature. Nonetheless, the use of such semi-supervised methods has been quite rare in the field of facial expression recognit

Kaili Wang, Qinchen Wang, Dan Boneh

Blockchains are meant to be persistent: posted transactions are immutable and cannot be changed. When a theft takes place, there are limited options for reversing the disputed transaction, and this has led to significant losses in the blockchain ecosystem. In this paper we propose reversible versions of ERC-20 and ERC-721, the most widely used token standard

Huayu Li, Gregory Ditzler, Janet Roveda, Ao Li

Objective: Electrocardiogram (ECG) signals commonly suffer noise interference, such as baseline wander. High-quality and high-fidelity reconstruction of the ECG signals is of great significance to diagnosing cardiovascular diseases. Therefore, this paper proposes a novel ECG baseline wander and noise removal technology. Methods: We extended the diffusion mod

Vincent R. Martinez

This article is concerned with the problem of determining an unknown source of non-potential, external time-dependent perturbations of an incompressible fluid from large-scale observations on the flow field. A relaxation-based approach is proposed for accomplishing this, which leverages a nonlinear property of the equations of motions to asymptotically ensla

C. A. Dong-Páez, A. Smith, A. O. Szewciw, J. Ereza

We present the data release of the Uchuu-SDSS galaxies: a set of 32 high-fidelity galaxy lightcones constructed from the large Uchuu 2.1 trillion particle $N$-body simulation using Planck cosmology. We adopt subhalo abundance matching to populate the Uchuu-box halo catalogues with SDSS galaxy luminosities. These cubic box galaxy catalogues generated at sever

Ali Borji

Short answer: Yes, Long answer: No! Indeed, research on adversarial robustness has led to invaluable insights helping us understand and explore different aspects of the problem. Many attacks and defenses have been proposed over the last couple of years. The problem, however, remains largely unsolved and poorly understood. Here, I argue that the current formu

A. R. C. Buarque, W. S. Dias, G. M. A. Almeida, M. L. Lyra

We investigate the outbreak of anomalous quantum wavefunction amplitudes in a one-dimensional tight-binding lattice featuring correlated diagonal disorder. Such rogue-wave-like behavior is fostered by a competition between localization and mobility. The effective correlation length of the disorder is ultimately responsible for bringing the local disorder str

Sanjiv Gunasekera, Tracie Barber, Olivia Ng, Shannon Thomas

The transitional flow which initiates within the junction (anastomosis) of an arteriovenous fistula (AVF) is known to be a contributing factor in the onset of vascular disease. A novel treatment method involving the implantation of a flexible stent across the anastomosis has enabled the retention of a large proportion of functioning AVFs, despite the propens

Jędrzej Kołodziejski, Bartek Klin

We introduce the countdown $\mu$-calculus, an extension of the modal $\mu$-calculus with ordinal approximations of fixpoint operators. In addition to properties definable in the classical calculus, it can express (un)boundedness properties such as the existence of arbitrarily long sequences of specific actions. The standard correspondence with parity games a

Berhail Amel, Meftah Badreddine

In this paper, we first prove two new identities for multiplicative differentiable functions. Based on this identity, we establish a midpoint and trapezoid type inequalities for multiplicatively convex functions. Applications to special means are also given.

I. Mrozek, N. A. Shevchenko, V. N. Yarmolik

This paper presents the universal address sequence generator (UASG) for memory built-in-self-test. The studies are based on the proposed universal method for generating address sequences with the desired properties for multirun march memory tests. As a mathematical model, a modification of the recursive relation for quasi-random sequence generation is used.

Lorenzo Sillari

Exploiting the affinity between stable generalized complex structures and symplectic structures, we explain how certain constructions coming from symplectic geometry can be performed in the generalized complex setting. We introduce generalized Luttinger surgery and generalized Gluck twist along $\mathcal{J}$-symplectic submanifolds. We also export branched c

Samuel H. C. Cabot, Gregory Laughlin

The discoveries of two Interstellar Objects (ISOs) in recent years has generated significant interest in constraining their physical properties and the mechanisms behind their formation. However, their ephemeral passages through our Solar System permitted only incomplete characterization. We investigate avenues for identifying craters that may have been prod

L. Maderer, E. Kaminski, J. A. B. Coelho, S. Bourret

In the last 70 years, geophysics has established that the Earth's outer core is an FeNi alloy containing a few percent of light elements, whose nature and amount remain controversial today. Besides the classical combinations of silicon and oxygen, hydrogen has been advocated as the only light element that could account alone for both the density and velocity

Lindsay P. Walter, Mathieu Francoeur

The effect of orientation on near-field radiative heat transfer between two complex-shaped superellipsoid particles of SiO2 is presented. The particles under study are 50 nm in radius and of variable concavity. Orientation is characterized by the degree of rotational symmetry in the two-particle systems, and the radiative conductance is calculated using the

Clara Javaherian

Carbon Nanotubes (CNs) are made of tubular graphite layers. These macromolecules have interesting features which are generally introduced in the first chapter of the thesis. In the rest of the thesis, the light conduction in metallic CNs is investigated. In chapter 2, by modeling metallic single-wall CNs as 2D free electron gas layers, we find the density of

Michael J. MacCoss, Javier Alfaro, Meni Wanunu, Danielle A. Faivre

Mammalian cells have about 30,000-fold more protein molecules than mRNA molecules. This larger number of molecules and the associated larger dynamic range have major implications in the development of proteomics technologies. We examine these implications for both liquid chromatography-tandem mass spectrometry (LC-MS/MS) and single-molecule counting and prov

A. Adıgüzel, S. Açıksöz, A. Çağlar, H. Çetinkaya

The KAHVE Laboratory, at Bo\u{g}azi\c{c}i University, Istanbul, Turkey is home to an educational proton linac project. The proton beam will originate from a 20 keV H+ source and will be delivered to a two module Radio Frequency Quadrupole (RFQ) operating at 800 MHz via a low energy beam transport (LEBT) line. Currently, the design phase being over, commissio

Xiaofeng Ren, Juncheng Wei

While the hexagonal lattice is ubiquitous in two dimensions, the body centered cubic lattice and the face centered lattice are both commonly observed in three dimensions. A geometric variational problem motivated by the diblock copolymer theory consists of a short range interaction energy and a long range interaction energy. In three dimensions, and when the

P. C. Malta, J. A. Helayël-Neto

The photon is the paradigm for a massless particle and current experimental tests set severe upper bounds on its mass. Probing such a small mass, or equivalently large Compton wavelength, is challenging at laboratory scales, but planetary or astrophysical phenomena may potentially reach much better sensitivities. In this work we consider the effect of a fini

Fanny Kassel

A cocompact lattice in a semisimple Lie group $G$ is a discrete subgroup $\Gamma$ such that the quotient $G/\Gamma$ is compact. Does such a lattice always contain a surface group, i.e. a subgroup isomorphic to the fundamental group of a compact hyperbolic surface? If so, does it contain surface subgroups close (in a precise quantitative sense) to Fuchsian su

Diogo Vaz, David R. Matos, Miguel L. Pardal, Miguel Correia

Modern distributed systems are supported by fault-tolerant algorithms, like Reliable Broadcast and Consensus, that assure the correct operation of the system even when some of the nodes of the system fail. However, the development of distributed algorithms is a manual and complex process, resulting in scientific papers that usually present a single algorithm

Mahdi Saleh, Yige Wang, Nassir Navab, Benjamin Busam

Processing 3D data efficiently has always been a challenge. Spatial operations on large-scale point clouds, stored as sparse data, require extra cost. Attracted by the success of transformers, researchers are using multi-head attention for vision tasks. However, attention calculations in transformers come with quadratic complexity in the number of inputs and

Jonah A. J. Duncan, Luc Nguyen

Let $g_0$ be a smooth Riemannian metric on a closed manifold $M^n$ of dimension $n\geq 3$. We study the existence of a smooth metric $g$ conformal to $g_0$ whose Schouten tensor $A_g$ satisfies the differential inclusion $\lambda(g^{-1}A_g)\in\Gamma$ on $M^n$, where $\Gamma\subset\mathbb{R}^n$ is a cone satisfying standard assumptions. Inclusions of this typ

Angan Mitra, Nguyen Kim Thang, Tuan-Anh Nguyen, Denis Trystram

The design of decentralized learning algorithms is important in the fast-growing world in which data are distributed over participants with limited local computation resources and communication. In this direction, we propose an online algorithm minimizing non-convex loss functions aggregated from individual data/models distributed over a network. We provide

N. Giorgadze, Z. N. Osmanov

A particle moving on curved magnetic field lines in the wormhole metrics is considered. The dynamics of a single particle is studied on a co-rotating parameterized magnetic field line. Being interested in the force-free dynamics we choose the rotating Archimedes' spiral embedded in the generalized Ellis-Bronnikov metrics. By analysing the phase space, we exp

E. Vanzella, M. Castellano, P. Bergamini, T. Treu

We investigate the blue and optical rest-frame sizes (lambda~2300A-4000A) of three compact star-forming regions in a galaxy at z=4 strongly lensed (x30, x45, x100) by the Hubble Frontier Field galaxy cluster A2744 using GLASS-ERS JWST/NIRISS imaging at 1.15um, 1.50mu and 2.0mu with PSF < 0.1". In particular, the Balmer break is probed in detail for all multi

Pappu Kumar Yadav, J. Alex Thomasson, Stephen W. Searcy, Robert G. Hardin

The boll weevil (Anthonomus grandis L.) is a serious pest that primarily feeds on cotton plants. In places like Lower Rio Grande Valley of Texas, due to sub-tropical climatic conditions, cotton plants can grow year-round and therefore the left-over seeds from the previous season during harvest can continue to grow in the middle of rotation crops like corn (Z

Yeor Hafouta

The purpose of this paper is to provide a first class of explicit sufficient conditions for the central limit theorem and related results in the setup of non-uniformly (partially) expanding non iid random transformations, considered as stochastic processes together with some random Gibbs measure. More precisely, we prove a central limit theorem (CLT), an alm

Yunhua Ding

An overview of recent progress on searches for Lorentz- and CPT-violating signals with confined particles and antiparticles in Penning traps is presented. In the context of the Standard-Model Extension (SME), leading-order shifts in the cyclotron and anomaly frequencies of a confined particle and antiparticle due to Lorentz and CPT violation are provided. Th

Salar Arbabi, Davide Tavernini, Saber Fallah, Richard Bowden

To plan safe maneuvers and act with foresight, autonomous vehicles must be capable of accurately predicting the uncertain future. In the context of autonomous driving, deep neural networks have been successfully applied to learning predictive models of human driving behavior from data. However, the predictions suffer from cascading errors, resulting in large

Yuri Kondratiev

We propose the construction of entire functions with a given random collection of zeros. There are considered two particular cases. In the first one we are dealing with simple zeros. And the second corresponds to random zeros with random multiplicity.

Yvain Bruned, Foivos Katsetsiadis

In this work, we construct the deformed Butcher-Connes-Kreimer Hopf algebra coming from the theory of Regularity Structures as the universal envelope of a post-Lie algebra. We show that this can be done using either of the two combinatorial structures that have been proposed in the context of singular SPDEs: decorated trees and multi-indices. Our constructio

Johan Linåker, Per Runeson

Background: Open innovation highlights the potential benefits of external collaboration and knowledge-sharing, often exemplified through Open Source Software (OSS). The public sector has thus far mainly focused on the sharing of Open Government Data (OGD), often with a supply-driven approach with limited feedback-loops. We hypothesize that public sector orga

Dekrayat Almaalol, Kirill Boguslavski, Aleksi Kurkela, Michael Strickland

We establish the existence of a far-from-equilibrium attractor in weakly-coupled gauge theory undergoing 0+1d Bjorken expansion which goes beyond the energy-momentum tensor to the detailed form of the one-particle distribution function. We then demonstrate that the dynamics can be re-scaled at intermediate times and represented by universal exponents. Finall

Maryam Bajalan, Edgar Martinez-Moro, Reza Sobhani, Steve Szabo

This paper provides the Generalized Mattson Solomon polynomial for repeated-root polycyclic codes over local rings that gives an explicit decomposition of them in terms of idempotents that completes the single root study. It also states some structural properties of repeated-root polycyclic codes over finite fields in terms of matrix product codes. Both appr

Sheng-Chieh Lin, Minghan Li, Jimmy Lin

Pre-trained language models have been successful in many knowledge-intensive NLP tasks. However, recent work has shown that models such as BERT are not ``structurally ready'' to aggregate textual information into a [CLS] vector for dense passage retrieval (DPR). This ``lack of readiness'' results from the gap between language model pre-training and DPR fine-

Johan Linåker, Per Runeson

Background: By creating ecosystems around platforms of Open Source Software (OSS) and Open Data (OD), and adopting open collaborative development practices, platform providers may exploit open innovation benefits. However, adopting such practices in a traditionally closed organization is a maturity process that we hypothesize cannot be undergone without fric

Sebastian Barria, Carlos Martinez-Ranero

Let $\mathbb{A}$ and $\mathbb{S}$ denote the double arrow of Alexandroff and the Sorgenfrey line, respectively. We show that any homeomorphism $h:^m\mathbb{A}\to^m\mathbb{A} $ is locally (outside of a nowhere dense set) a product of monotone embeddings $h_i:J_i\subseteq \mathbb{A}\to\mathbb{A} (i\in m)$ followed by a permutation of the coordinates. We also p

V. N. Murzin, L. Yu. Shchurova

Based on the concepts of the quantum field theory of virtual photons as quanta of electromagnetic interaction, we discuss the physical content of the phenomena underlying the principle of quantum uncertainties. We consider the features of the uncertainty relations and the properties of the elementary particles (electrons, protons, etc.) under the conditions

Kinyua Gikunda

Digital data collected over the decades and data currently being produced with use of information technology is vastly the unlabeled data or data without description. The unlabeled data is relatively easy to acquire but expensive to label even with use of domain experts. Most of the recent works focus on use of active learning with uncertainty metrics measur

Zhen Meng, Changyang She, Guodong Zhao, Daniele De Martini

The metaverse has the potential to revolutionize the next generation of the Internet by supporting highly interactive services with the help of Mixed Reality (MR) technologies; still, to provide a satisfactory experience for users, the synchronization between the physical world and its digital models is crucial. This work proposes a sampling, communication a

Johan Linåker, Björn Regnell

Context and motivation: Contribution Management helps firms engaged in Open Source Software (OSS) ecosystems to motivate what they should contribute and when, but also what they should focus their resources on and to what extent. Such guidelines are also referred to as contribution strategies. The motivation for developing tailored contribution strategies is

Juan Guillermo Garrido, Pedro Pérez-Aros, Emilio Vilches

In this paper, we study integral functionals defined on spaces of functions with values on general (non-separable) Banach spaces. We introduce a new class of integrands and multifunctions for which we obtain measurable selection results. Then, we provide an interchange formula between integration and infimum, which enables us to get explicit formulas for the

Vitaly Chatyrko, Alexandre Karassev

We introduce the classes of (strongly) ($\Theta$-)discrete homogeneous spaces. We discuss the relationships of these classes to other classes of spaces possessing homogeneity-related properties, such as (strongly) ($n$-)homogeneous spaces. Many examples are given distinguishing discrete homogeneity and other types of homogeneity.

Elena Cordero, Gianluca Giacchi, Luigi Rodino

We study the phase-space concentration of the so-called generalized metaplectic operators whose main examples are Schr\"odinger equations with bounded perturbations. To reach this goal, we perform a so-called $\mathcal{A}$-Wigner analysis of the previous equations, as started in Part I, cf. [14]. Namely, the classical Wigner distribution is extended by consi

Johan Linåker, Patrick Rempel, Björn Regnell, Patrick Mäder

[Context and motivation] Ecosystems developed as Open Source Software (OSS) are considered to be highly innovative and reactive to new market trends due to their openness and wide-ranging contributor base. Participation in OSS often implies opening up of the software development process and exposure towards new stakeholders. [Question/Problem] Firms consider

Ky Ho, Patrick Winkert

In this paper we present new embedding results for Musielak-Orlicz Sobolev spaces of double phase type. Based on the continuous embedding of $W^{1,\mathcal{H}}(\Omega)$ into $L^{\mathcal{H}_*}(\Omega)$, where $\mathcal{H}_*$ is the Sobolev conjugate function of $\mathcal{H}$, we present much stronger embeddings as known in the literature. Based on these resu

Johan Linåker, Krzysztof Wnuk

Requirements Engineering has recently been greatly influenced by the way how firms use Open Source Software (OSS) and Software Ecosystems (SECOs) as a part of their product development and business models. This is further emphasized by the paradigm of Open Innovation, which highlights how firms should strive to use both internal and external resources to adv

Michela Ceria, Francesco Pavese

In $\mathrm{PG}(3, q)$, $q = 2^n$, $n \ge 3$, let ${\cal A} = \{(1,t,t^{2^h},t^{2^h+1}) \mid t \in \mathbb{F}_q\} \cup \{(0,0,0,1)\}$, with $\mathrm{gcd}(n,h) = 1$, be a $(q+1)$-arc and let $G_h \simeq \mathrm{PGL}(2, q)$ be the stabilizer of $\cal A$ in $\mathrm{PGL}(4, q)$. The $G_h$-orbits on points, lines and planes of $\mathrm{PG}(3, q)$, together with

Xiaoyu Li

Recently, Stochastic Gradient Descent (SGD) and its variants have become the dominant methods in the large-scale optimization of machine learning (ML) problems. A variety of strategies have been proposed for tuning the step sizes, ranging from adaptive step sizes to heuristic methods to change the step size in each iteration. Also, momentum has been widely e

Misak M. Sargsian, Frank Vera

We demonstrate that a paradigm shift from considering the deuteron as a system of bound proton and neutron to considering it as a pseudo-vector system in which we observe proton and neutron, results in a possibility of probing a new "incomplete" P-state like structure on the light-front (LF), at extremely large internal momenta, which can be achieved in high

Amine Ahriche

In this work, we present a scotogenic model, where the neutrino mass is generated at one-loop diagrams. The standard model (SM) is extended by three singlet Majorana fermions and two inert scalar doublets instead of one doublet as in the minimal scotogenic model. The model scalar sector includes two CP-even, two CP-odd and two charged scalars in addition to

Johan Linåker, Björn Regnell, Hussan Munir

In recent years Open Innovation (OI) has gained much attention and made firms aware that they need to consider the open environment surrounding them. To facilitate this shift Requirements Engineering (RE) needs to be adapted in order to manage the increase and complexity of new requirements sources as well as networks of stakeholders. In response we build on

Nirjhar Bhattacharjee, Krishnamurthy Mahalingam, Alexandria Will-Cole, Yuyi Wei

Combining topological insulators (TIs) and magnetic materials in heterostructures is crucial for advancing spin-based electronics. Magnetic insulators (MIs) can be deposited on TIs using the spin-spray process, which is a unique non-vacuum, low-temperature growth process. TIs have highly reactive surfaces that oxidize upon exposure to atmosphere, making it c

Mohammad Hossein Samavatian, Saikat Majumdar, Kristin Barber, Radu Teodorescu

DNNs are known to be vulnerable to so-called adversarial attacks that manipulate inputs to cause incorrect results that can be beneficial to an attacker or damaging to the victim. Recent works have proposed approximate computation as a defense mechanism against machine learning attacks. We show that these approaches, while successful for a range of inputs, a

Dakota J. Thompson, Amro M. Farid

As one of the most pressing challenges of the 21st century, global climate change demands a host of changes across four critical energy infrastructures: the electric grid, the natural gas system, the oil system, and the coal system. Unfortunately, these four systems are often studied individually, and rarely together as integrated systems. Instead, holistic

Tinko Bartels, Vissarion Fisikopoulos, Martin Weiser

Geometric predicates are at the core of many algorithms, such as the construction of Delaunay triangulations, mesh processing and spatial relation tests. These algorithms have applications in scientific computing, geographic information systems and computer-aided design. With floating-point arithmetic, these geometric predicates can incur round-off errors th

Michael Xieyang Liu, Andrew Kuznetsov, Yongsung Kim, Joseph Chee Chang

Consumers conducting comparison shopping, researchers making sense of competitive space, and developers looking for code snippets online all face the challenge of capturing the information they find for later use without interrupting their current flow. In addition, during many learning and exploration tasks, people need to externalize their mental context,

Xuan Lin, Gabriel Fernandez, Yeting Liu, Taoyuanmin Zhu

In this paper we present a motion planner for LIMMS, a modular multi-agent, multi-modal package delivery platform. A single LIMMS unit is a robot that can operate as an arm or leg depending on how and what it is attached to, e.g., a manipulator when it is anchored to walls within a delivery vehicle or a quadruped robot when 4 are attached to a box. Coordinat

Chi-Kwong Li

For an $n\times n$ complex matrix $C$, the $C$-numerical range of a bounded linear operator $T$ acting on a Hilbert space of dimension at least $n$ is the set of complex numbers ${\rm tr}(CX^*TX)$, where $X$ is a partial isometry satisfying $X^*X = I_n$. It is shown that $${\bf cl}(W_C(T)) = \cap \{{\bf cl}(W_C(U)): U \hbox{ is a unitary dilation of } T\}$$

Hugo Parlier, Dragomir Šarić

We study quasisymmetric maps, which act on the boundary of the hyperbolic plane, by looking at their action on the Farey triangulation. Our main results identify exactly which quasisymmetric maps correspond to pinched lambda lengths in terms of shearing coordinates and, separately, in terms of (simultaneous) flip distance of the Farey triangulation and its i

Debanjan Datta, Sathappan Muthiah, John Simeone, Amelia Meadows

Timber and forest products made from wood, like furniture, are valuable commodities, and like the global trade of many highly-valued natural resources, face challenges of corruption, fraud, and illegal harvesting. These grey and black market activities in the wood and forest products sector are not limited to the countries where the wood was harvested, but e

Charles F. F. Karney

The algorithms given in Karney, J. Geodesy 87, 43-55 (2013), to compute geodesics on terrestrial ellipsoids are extended to apply to ellipsoids of revolution with arbitrary eccentricity. For the direct and inverse geodesic problems, this entails implementing the formulation in terms of elliptic integrals given by Legendre and Cayley. The integral for the are

David A. Buchta, Stuart J. Laurence, Tamer A. Zaki

A nonlinear ensemble-variational (EnVar) data assimilation is performed in order to estimate the unknown flow field over a slender cone at Mach-6, from isolated wall-pressure measurements. The cost functional accounts for discrepancies in wall-pressure spectra and total intensity between the experiment and the prediction using direct numerical simulations (D

Terry Fuller

Generalizing work of I. Baykur, K. Hayano, and N. Monden (arXiv:1903.02906), we construct infinite families of symplectic 4-dimensional manifolds, obtained as total spaces of Lefschetz pencils constructed by explicit monodromy factorizations. Then, generalizing work of the author (arXiv:2108.04868), we show that each of these manifolds is diffeomorphic to a

Junliang Wang, Shunsuke Ota, Hermann Edlbauer, Baptiste Jadot

The synthesis of single-cycle, compressed optical and microwave pulses sparked novel areas of fundamental research. In the field of acoustics, however, such a generation has not been introduced yet. For numerous applications, the large spatial extent of surface acoustic waves (SAW) causes unwanted perturbations and limits the accuracy of physical manipulatio

Johan Linåker, Per Runeson, Anneke Zuiderwijk, Amanda Brock

High-quality data has become increasingly important to software engineers in designing and implementing today's software, for example, as an input to machine-learning algorithms and visualisation- and analytics-based features. Open data - i.e., data shared under a licence that gives users the right to study, process, and distribute the data to anyone and for

Johan Linåker, Husan Munir, Per Runeson, Björn Regnell

Context. Innovation is promoted in companies to help them stay competitive. Four types of innovation are defined: product, process, business, and organizational. Objective. We want to understand the perception of the innovation concept in industry, and particularly how the innovation types relate to each other. Method. We launched a survey at a branch of a m

Hussan Munir, Johan Linåker, Krzysztof Wnuk, Per Runeson

Despite growing interest of Open Innovation (OI) in Software Engineering (SE), little is known about what triggers software organizations to adopt it and how this affects SE practices. OI can be realized in numerous of ways, including Open Source Software (OSS) involvement. Outcomes from OI are not restricted to product innovation but also include process in

Aravind Battaje, Oliver Brock

A gaze-fixating robot perceives distance to the fixated object and relative positions of surrounding objects immediately, accurately, and robustly. We show how fixation, which is the act of looking at one object while moving, exploits regularities in the geometry of 3D space to obtain this information. These regularities introduce rotation-translation coupli

Ying Li, Patrick Lambrix

The quality of ontologies in terms of their correctness and completeness is crucial for developing high-quality ontology-based applications. Traditional debugging techniques repair ontologies by removing unwanted axioms, but may thereby remove consequences that are correct in the domain of the ontology. In this paper we propose an interactive approach to mit

Jiaming Qiu, Ruiqi Wang, Ayan Chakrabarti, Roch Guerin

This paper considers a setting where embedded devices are used to acquire and classify images. Because of limited computing capacity, embedded devices rely on a parsimonious classification model with uneven accuracy. When local classification is deemed inaccurate, devices can decide to offload the image to an edge server with a more accurate but resource-int

N. V. Kitov, M. V. Volkov

We show that it is co-NP-hard to check whether a given semigroup identity holds in the twisted Brauer monoid $\mathcal{B}^\tau_n$ with $n\ge5$.

Ji Xin, Raphael Tang, Zhiying Jiang, Yaoliang Yu

There exists a wide variety of efficiency methods for natural language processing (NLP) tasks, such as pruning, distillation, dynamic inference, quantization, etc. We can consider an efficiency method as an operator applied on a model. Naturally, we may construct a pipeline of multiple efficiency methods, i.e., to apply multiple operators on the model sequen

Thomas Lidbetter, Yifan Xie

We consider a search and rescue game introduced recently by the first author. An immobile target or targets (for example, injured hikers) are hidden on a graph. The terrain is assumed to dangerous, so that when any given vertex of the graph is searched, there is a certain probability that the search will come to an end, otherwise with the complementary {\em

Polina O. Kofman, Oleh V. Ivakhnenko, Sergey N. Shevchenko, Franco Nori

The approach by Ettore Majorana for non-adiabatic transitions between two quasi-crossing levels is revisited. We rederive the transition probability, known as the Landau-Zener-St\"{u}ckelberg-Majorana formula, and introduce Majorana's approach to modern readers. This result typically referred as the Landau-Zener formula, was published by Majorana before Land

Hlér Kristjánsson, Yan Zhong, Anthony Munson, Giulio Chiribella

Large-scale communication networks, such as the internet, rely on routing packets of data through multiple intermediate nodes to transmit information from a sender to a receiver. In this paper, we develop a model of a quantum communication network that routes information simultaneously along multiple paths passing through intermediate stations. We demonstrat

Immaculate Wanza, Irad Kamuti, David Gichohi, Kinyua Gikunda

In this new era of social media, social networks are becoming increasingly important sources of user-generated content on the internet. These kinds of information resources, which include a lot of people's feelings, opinions, feedback, and reviews, are very useful for big businesses, markets, politics, journalism, and many other fields. Politics is one of th

Abdalkarim Mohtasib, Gerhard Neumann, Heriberto Cuayahuitl

Learning robotic tasks in the real world is still highly challenging and effective practical solutions remain to be found. Traditional methods used in this area are imitation learning and reinforcement learning, but they both have limitations when applied to real robots. Combining reinforcement learning with pre-collected demonstrations is a promising approa

Viet Hung Hoang, Kilian Raschel, Pierre Tarrago

We consider discrete (time and space) random walks confined to the quarter plane, with jumps only in directions $(i,j)$ with $i+j \geq 0$ and small negative jumps, i.e., $i,j \geq -1$. These walks are called singular, and were recently intensively studied from a combinatorial point of view. In this paper, we show how the compensation approach introduced in t

A. V. Ivanov, D. V. Vassilevich

We study the $\eta$-invariant of a Dirac operator on a manifold with boundary subject to local boundary conditions with the help of heat kernel methods. In even dimensions, we relate this invariant to $\eta$-invariants of a boundary Dirac operator, while in odd dimension, it is expressed through the index of boundary operators. We stress the necessity of the

Xiaoyuan Guo, Jiali Duan, C. -C. Jay Kuo, Judy Wawira Gichoya

Language modality within the vision language pretraining framework is innately discretized, endowing each word in the language vocabulary a semantic meaning. In contrast, visual modality is inherently continuous and high-dimensional, which potentially prohibits the alignment as well as fusion between vision and language modalities. We therefore propose to "d

Ivan Zakazov, Vladimir Shaposhnikov, Iaroslav Bespalov, Dmitry V. Dylov

Generalizability of deep learning models may be severely affected by the difference in the distributions of the train (source domain) and the test (target domain) sets, e.g., when the sets are produced by different hardware. As a consequence of this domain shift, a certain model might perform well on data from one clinic, and then fail when deployed in anoth

Amjad Nadeem

Metamaterials have great potential to construct ultrathin, miniaturized, and cost-effective microwave and optical devices for future wireless communication systems. Here, a dual-band meta-absorber comprising four arrows-shaped unit cells is investigated. The absorption features are numerically studied and analyzed in a microwave frequency spectrum from 28 -

Pooja Yadav, Mamta Kamra

We establish some common fixed point results for four transformations in vector S-metric spaces by using the notion of weakly compatibility (WC) and occasionally weakly compatibility (OWC). The first theorem is proved by using the concept of CLR (p,q) property (common limit range property w.r.t. transformations p and q) and weakly compatiblity whereas second

Sophie Hermann, Matthias Schmidt

We address the consequences of invariance properties of the free energy of spatially inhomogeneous quantum many-body systems. We consider a specific position-dependent transformation of the system that consists of a spatial deformation and a corresponding locally resolved change of momenta. This operator transformation is canonical and hence equivalent to a

Alexander Volberg

This note contains some estimates for tail spaces on Hamming cube. We use analytic paraproduct operator for that purpose. We also show several types of Bernstein--Markov inequalities for Banach space valued functions on Hamming cube. Here the novelty is in getting rid of some irritating logarithms and in proving Bernstein--Markov inequalities for $|\nabla f|

S. Chatterjee, B. S. Sanjeev

Diseased conditions are a consequence of some abnormality that are associated with clinical conditions in numerous cells and tissues affecting various organs. The common role of EBV (Epstein-Barr virus) in causing infectious mononucleosis (IM) affecting B-cells and epithelial cells and the development of EBV-associated cancers has been an area of active rese

Maurice de Gosson, Charlyne de Gosson

We use the notion of polar duality from convex geometry and the theory of Lagrangian planes from symplectic geometry to construct a fiber bundle over ellipsoids that can be viewed as a quantum-mechanical substitute for the classical symplectic phase space. The total space of this fiber bundle consists of geometric quantum states, products of convex bodies ca

J. Polman, L. B. F. M. Waters, M. Min, Y. Miguel

The high cosmic abundance and the intermediate volatility and chemical properties of sulfur allow the use of sulfur-bearing species as a tracer of the chemical processes in the atmospheres of hot Jupiter exoplanets. Nevertheless, despite its properties and relevance as a tracer of the giant planets' formation history, little attention has been paid to this s

Pingal Dasgupta, Han-Sheng Wang, Guo-Liang Ma

We calculate the longitudinal flow decorrelation coefficients, i.e., $r_n(\eta,\eta_r)$ for $n=2,3$, in the presence of hydro-like flow and the global momentum conservation (GMC) constraint. The longitudinal flow decorrelation is weakened due to the GMC constraint. The GMC effect is sensitive to the total number of particles involved in GMC, the average long

Shohreh Deldari, Hao Xue, Aaqib Saeed, Daniel V. Smith

Self-Supervised Learning (SSL) is a new paradigm for learning discriminative representations without labelled data and has reached comparable or even state-of-the-art results in comparison to supervised counterparts. Contrastive Learning (CL) is one of the most well-known approaches in SSL that attempts to learn general, informative representations of data.

G. B. Alaverdyan

The properties of hadron-quark hybrid stars are studied when the quark phase is described in terms of a local SU(3) Nambu--Jona-Lasinio (NJL) model taking into account the contribution of the vector and axial-vector interaction between the quarks, and the hadronic phase, in the relativistic mean field (RMF) model. For different values of the vector coupling

Brian Xiang, Abdelrahman Abdelmonsef

The main challenges of using electroencephalogram (EEG) signals to make eye-tracking (ET) predictions are the differences in distributional patterns between benchmark data and real-world data and the noise resulting from the unintended interference of brain signals from multiple sources. Increasing the robustness of machine learning models in predicting eye-

Mayank Katare, Mahesh Raveendranatha Panicker, A N Madhavanunni, Gayathri Malamal

In the recent past, there have been many efforts to accelerate adaptive beamforming for ultrasound (US) imaging using neural networks (NNs). However, most of these efforts are based on static models, i.e., they are trained to learn a single adaptive beamforming approach (e.g., minimum variance distortionless response (MVDR)) assuming that they result in the

Fatemeh Azadi, Heshaam Faili, Mohammad Javad Dousti

Translation Quality Estimation (QE) is the task of predicting the quality of machine translation (MT) output without any reference. This task has gained increasing attention as an important component in the practical applications of MT. In this paper, we first propose XLMRScore, which is a cross-lingual counterpart of BERTScore computed via the XLM-RoBERTa (

Kizito Salako, Xingyu Zhao

When assessing a software-based system, the results of Bayesian statistical inference on operational testing data can provide strong support for software reliability claims. For inference, this data (i.e. software successes and failures) is often assumed to arise in an independent, identically distributed (i.i.d.) manner. In this paper we show how conservati

Sergio A. Balanya, Juan Maroñas, Daniel Ramos

In this paper, we study the post-hoc calibration of modern neural networks, a problem that has drawn a lot of attention in recent years. Many calibration methods of varying complexity have been proposed for the task, but there is no consensus about how expressive these should be. We focus on the task of confidence scaling, specifically on post-hoc methods th

Kuniaki Nagayama

Phase-plate transmission electron microscopy has recently regressed since a report that Volta phase-plate phase-contrast is less sensitive than non-phase-plate phase contrast, which leads to conventional defocusing phase-contrast. What about Hilbert phase-plate phase-contrast? We report that the Hilbert phase-plate method can survive if two experiments using