July 2022 arXiv papers — page 105

Alex Smith, Shaun Cole, Cameron Grove, Peder Norberg

The use of realistic mock galaxy catalogues is essential in the preparation of large galaxy surveys, in order to test and validate theoretical models and to assess systematics. We present an updated version of the mock catalogue constructed from the Millennium-XXL simulation, which uses a halo occupation distribution (HOD) method to assign galaxies r-band ma

Cem Anil, Yuhuai Wu, Anders Andreassen, Aitor Lewkowycz

The ability to extrapolate from short problem instances to longer ones is an important form of out-of-distribution generalization in reasoning tasks, and is crucial when learning from datasets where longer problem instances are rare. These include theorem proving, solving quantitative mathematics problems, and reading/summarizing novels. In this paper, we ru

Jian Yang, Yuwei Yin, Shuming Ma, Dongdong Zhang

Most translation tasks among languages belong to the zero-resource translation problem where parallel corpora are unavailable. Multilingual neural machine translation (MNMT) enables one-pass translation using shared semantic space for all languages compared to the two-pass pivot translation but often underperforms the pivot-based method. In this paper, we pr

Xuan Liu, Cagdas Onal, Jie Fu

Intelligent control of soft robots is challenging due to the nonlinear and difficult-to-model dynamics. One promising model-free approach for soft robot control is reinforcement learning (RL). However, model-free RL methods tend to be computationally expensive and data-inefficient and may not yield natural and smooth locomotion patterns for soft robots. In t

Jan Rais, Hendrik van Hees, Carsten Greiner

We study the temporal formation of quantum mechanical bound states within a one-dimensional attractive square-well potential, by first solving the time-independent Schroedinger equation and then study a time dependent system with an external time-dependent potential. For this we introduce Gaussian potentials with different spatial and temporal extensions, an

Filippo Pecci, Ivan Stoianov

Optimal Experiment Design for parameter estimation in water networks has been traditionally formulated to maximize either hydraulic model accuracy or spatial coverage. Because a unique sensor configuration that optimizes both objectives may not exist, these approaches inevitably result in sub-optimal configurations with respect to one of the objectives. This

Behrooz Razeghi, Flavio P. Calmon, Deniz Gunduz, Slava Voloshynovskiy

Bottleneck problems are an important class of optimization problems that have recently gained increasing attention in the domain of machine learning and information theory. They are widely used in generative models, fair machine learning algorithms, design of privacy-assuring mechanisms, and appear as information-theoretic performance bounds in various multi

Siyuan Hui, Yuqiu Zhang, Albert Hu, Edmund Song

With the advent of big data era and the development of artificial intelligence and other technologies, data security and privacy protection have become more important. Recommendation systems have many applications in our society, but the model construction of recommendation systems is often inseparable from users' data. Especially for deep learning-based rec

Wout Moltmaker, Roland van der Veen

In this paper we discuss the applications of knotoids to modelling knots in open curves and produce new knotoid invariants. We show how invariants of knotoids generally give rise to well-behaved measures of how much an open curve is knotted. We define biframed planar knotoids, and construct new invariants of these objects that can be computed in polynomial t

Jun-Zhang Wang, Xiang Liu

Very recently, the CMS Collaboration reported a peaking phenomenon existing in the di-$J/\psi$ invariant mass spectrum from $pp$ collision, by which the $X(6900)$ structure announced by the LHCb Collaboration was confirmed, but also more enhancement structures were discovered. Facing such a novel phenomenon, in this work we indicate that these new features r

Aditya Vasudevan, José A. Rodríguez-Martínez, Ignacio Romero

In this work, we study lattice structures that exhibit a bistable behavior, i. e., they can snap from one stable state to another, and are also completely reversible, capable of reverting back to its original state through a heat treatment. We design this behavior by constructing lattice structures using networks of nonlinear springs that display tension-com

Zhun Zhong, Yuyang Zhao, Gim Hee Lee, Nicu Sebe

In this paper, we consider the problem of domain generalization in semantic segmentation, which aims to learn a robust model using only labeled synthetic (source) data. The model is expected to perform well on unseen real (target) domains. Our study finds that the image style variation can largely influence the model's performance and the style features can

Al-Harith Farhad, Ioannis Sorokos, Andreas Schmidt, Mohammed Naveed Akram

Machine Learning~(ML) has provided promising results in recent years across different applications and domains. However, in many cases, qualities such as reliability or even safety need to be ensured. To this end, one important aspect is to determine whether or not ML components are deployed in situations that are appropriate for their application scope. For

Hadrien A. R. Devillepoix, Seamus Anderson, Martin C. Towner, Patrick M. Shober

On Aug 22, 2016, a bright fireball was observed by the Desert Fireball Network in South Australia. Its pre-atmosphere orbit suggests it was temporarily captured by the Earth-Moon system before impact. A search was conducted two years after the fall, and a meteorite was found after 6 days of searching. The meteorite appeared relatively fresh, had a mass consi

Roman Hahn, Christoph Feinauer, Emanuele Borgonovo

Owen and Hoyt recently showed that the effective dimension offers key structural information about the input-output mapping underlying an artificial neural network. Along this line of research, this work proposes an estimation procedure that allows the calculation of the mean dimension from a given dataset, without resampling from external distributions. The

Michael Arbel, Julien Mairal

Bilevel optimization problems involve two nested objectives, where an upper-level objective depends on a solution to a lower-level problem. When the latter is non-convex, multiple critical points may be present, leading to an ambiguous definition of the problem. In this paper, we introduce a key ingredient for resolving this ambiguity through the concept of

Wenbo Ma, Abdusalam Abdukerim, Chen Cheng, Zihao Bo

A search for interactions from solar $^8$B neutrinos elastically scattering off xenon nuclei using PandaX-4T commissioning data is reported. The energy threshold of this search is further lowered compared with the previous search for dark matter, with various techniques utilized to suppress the background that emerges from data with the lowered threshold. A

Leonard Bruns, Patric Jensfelt

Rich geometric understanding of the world is an important component of many robotic applications such as planning and manipulation. In this paper, we present a modular pipeline for pose and shape estimation of objects from RGB-D images given their category. The core of our method is a generative shape model, which we integrate with a novel initialization net

Anna Gąsior, Rafał Lutowski

Let $M$ be a real Bott manifold with K\"{a}hler structure. Using Ishida characterization \cite{I11} we give necessary and sufficient condition for the existence of the spin-structure on $M$. In proof we use the technic developed in \cite{PS16} and characteristic classes.

Sebastian Dingler

For model-based estimation methods, the modeling that is as close to reality as possible makes a vital estimation result. In simple applications, it is sufficient to model a system with a single state space model. However, there are applications in which a system changes its behavior deterministically or stochastically. A previously defined model then descri

Jelle J. Oostveen, Erik Jan van Leeuwen

We initiate the investigation of the parameterized complexity of Diameter and Connectivity in the streaming paradigm. On the positive end, we show that knowing a vertex cover of size $k$ allows for algorithms in the Adjacency List (AL) streaming model whose number of passes is constant and memory is $O(\log n)$ for any fixed $k$. Underlying these algorithms

Xiaomeng Chen, Shuai Li, Wendong Wang

In this note, we investigate partial regularity of weak solutions of the three dimensional chemotaxis-Navier-Stokes equations, and obtain the $\frac53$-dimensional Hausdorff measure of the possible singular set is vanishing at the first blow-up time. The new ingredients are to establish certain type of local energy inequality and deal with the non-scaling in

Vincent Debierre, Natalia S. Oreshkina, Igor A. Valuev, Zoltán Harman

When collecting spectroscopic data on at least four isotopes, nonlinearities in the King plot are a possible sign of Physics beyond the Standard Model. In this work, an improved approach to the search for hypothetical new interactions with isotope shift spectroscopy of few-electron ions is presented. Very careful account is taken of the small nuclear correct

Jan Flink, Robert Mischke, Kathrin Schaffert, Dominik Schneider

When using multiple software tools to analyze, visualize, or optimize models in MBSE, it is often tedious and error-prone to manually coordinate the execution of these tools and to retain their respective input and output data for later analysis. Since such tools often require expertise in their usage as well as diverse run-time environments, it is not strai

Hongli Sun, Donghui Yang, Xu Zhang

This paper is concerned at the minimization fundamental gap problem for a class of two-dimensional degenerate sub-elliptic operators. We establish existence results for weak solutions, Sobolev embedding theorem and spectral theory of sub-elliptic operators. We provide the existence and characterization theorems for extremizing potentials $V(x)$ when $V(x)$ i

Antonio Capolupo, Aniello Quaranta, Raoul Serao

We study a nonlocal generalization of two flavor fermion mixing and compute the transition probability by means of the path integral formalism. In our treatment, we delocalize only the mixing term, and consider a perturbative interaction with a small mixing angle. The oscillation formula derived reduces to the correct local form when the appropriate limit is

Albert Weichselbraun, Roger Waldvogel, Andreas Fraefel, Alexander van Schie

Disturbances in the job market such as advances in science and technology, crisis and increased competition have triggered a surge in reskilling and upskilling programs. Information on suitable continuing education options is distributed across many sites, rendering the search, comparison and selection of useful programs a cumbersome task. This paper, theref

Zachary A. H. Goodwin, Vladimir I. Fal'ko

Here we investigate how charge density waves (CDW), inherent to a monolayer, are effected by creating twisted van der Waals structures. Homobilayers of metallic transition metal dichalcogenides (TMDs), at small twist angles where there is significant atomic reconstruction, are utilised as an example to investigate the interplay between the moir\'e domain str

Sribalaji C. Anand, André M. H. Teixeira, Anders Ahlén

This paper firstly addresses the problem of risk assessment under false data injection attacks on uncertain control systems. We consider an adversary with complete system knowledge, injecting stealthy false data into an uncertain control system. We then use the Value-at-Risk to characterize the risk associated with the attack impact caused by the adversary.

Rui Du, Hailiang Xie, Mengshi Hu, Narengerile

With recent advancements, the wireless local area network (WLAN) or wireless fidelity (Wi-Fi) technology has been successfully utilized to realize sensing functionalities such as detection, localization, and recognition. However, the WLANs standards are developed mainly for the purpose of communication, and thus may not be able to meet the stringent sensing

Jinbin Bai, Chunhui Liu, Feiyue Ni, Haofan Wang

Video-text retrieval is a class of cross-modal representation learning problems, where the goal is to select the video which corresponds to the text query between a given text query and a pool of candidate videos. The contrastive paradigm of vision-language pretraining has shown promising success with large-scale datasets and unified transformer architecture

Philipp Brunner, Igor Letina, Armin Schmutzler

This paper provides a novel theory of research joint ventures for financially constrained firms. When firms choose R&D portfolios, an RJV can help to coordinate research efforts, reducing investments in duplicate projects. This can free up resources, increase the variety of pursued projects and thereby increase the probability of discovering the innovation.

Reinhard Diestel, Raphael W. Jacobs, Paul Knappe, Jan Kurkofka

We present a canonical way to decompose finite graphs into highly connected local parts. The decomposition depends only on an integer parameter whose choice sets the intended degree of locality. The global structure of the graph, as determined by the relative position of these parts, is described by a coarser $\it model$. This is a simpler graph determined e

Pasquale Memmolo, Daniele Pirone, Daniele G. Sirico, Lisa Miccio

Phase-contrast tomographic flow cytometry combines quantitative 3D analysis of unstained single cells and high-throughput. A crucial issue of this method is the storage and management of the huge amount of 3D tomographic data. Here we show an effective quasi lossless compression of tomograms data through 3D Zernike descriptors, unlocking data management task

Olena Bahchedjioglou, Georgiy Shevchenko

We study the minimax identity for a non-decreasing upper-semicontinuous utility function satisfying mild growth assumption. In contrast to the classical setting, we do not impose the assumption that the utility function is concave. By considering the concave envelope of the utility function we obtain equalities and inequalities between the robust utility fun

Stepan Konenkov

We examine four identities conjectured by Hickerson which complement five modulo $9$ Kanade--Russell identities, and we build up a profile of new identities and new conjectures not unlike those found by Uncu and Zudilin.

Oskar Riedler

In this article we show the existence of closed embedded self-shrinkers in $\Bbb{R}^{n+1}$ that are topologically of type $S^1\times M$, where $M\subset S^n$ is any isoparametric hypersurface in $S^n$ for which the multiplicities of the principle curvatures agree. This yields new examples of closed self-shrinkers, for example self-shrinkers of topological ty

Cyril Elouard, Camille Lombard Latune

Originally formulated for macroscopic machines, the laws of thermodynamics were recently shown to hold for quantum systems coupled to ideal sources of work (external classical fields) and heat (systems at equilibrium). Ongoing efforts have been focusing on extending the validity of thermodynamic laws to more realistic, non-ideal energy sources. Here, we go b

Stefan Pachmajer, Oliver Werzer, Carlo Mennucci, Francesco Buatier de Mongeot

Pentacene is known to grow on isotropic silicon oxide surfaces in a substrate-induced phase with fiber textured crystallites. This growth study reports on the growth of pentacene crystallites on uniaxially oriented surfaces. Silica substrates have been treated by ion beam sputtering so that ripples with a lateral corrugation length of 38 nm and a surface rou

Sureel Shah, Sayan Koley, Filippo Malandra

Micro-Phasor Measurement Units (u-PMUs) are devices that permit monitoring voltage and current in the distribution grid with high accuracy, thus enabling a wide range of smart grid applications, such as state estimation, protection and control. These devices need to transmit the synchronous measurements of voltage and current, also known as synchrophasors, t

Radek Novotny

This manuscript is devoted to the description of the proposed Future Circular Collider (FCC) project and its physics program focused on measurements involving heavy quarks. It summarizes the report submitted to the US 2021 Snowmass Process and European Strategy on Particle Physics. The proposed electron-positron collider based on established technologies wil

Ibrahim Aliyu, Selinde van Engelenburg, Muhammed Bashir Muazu, Jinsul Kim

The internet-of-Vehicle (IoV) can facilitate seamless connectivity between connected vehicles (CV), autonomous vehicles (AV), and other IoV entities. Intrusion Detection Systems (IDSs) for IoV networks can rely on machine learning (ML) to protect the in-vehicle network from cyber-attacks. Blockchain-based Federated Forests (BFFs) could be used to train ML mo

Ferenc Iglói, Géza Tóth

We use entanglement witnesses to detect entanglement in the XY chain in thermal equilibrium and determine the temperature bound below which the state is detected as entangled. We consider the entanglement witness based on the Hamiltonian. Such a witness detects a state as entangled if its energy is smaller than the energy of separable states. We also conside

Canhui Chen, Xu Chen, Zhixuan Fang

Directed Acyclic Graph (DAG) is a popular approach to achieve scalability of blockchain networks. Due to its high efficiency in data communication and great scalability, DAG has been widely adopted in many applications such as Internet of Things (IoT) and Decentralized Finance (DeFi). DAG-based blockchain, nevertheless, faces the key challenge of transaction

Florian N. Brünig, Roland R. Netz, Julian Kappler

We introduce a generalized Langevin model system for different non-Markovian effects in the well and barrier regions of a potential, and use it to numerically study the dependence of the barrier-crossing time. In the appropriate limits, our model interpolates between the theoretical barrier-crossing-time predictions by Grote and Hynes (GH), as well as by Pol

Julia Koch, Florian Lux, Nadja Schauffler, Toni Bernhart

Speech synthesis for poetry is challenging due to specific intonation patterns inherent to poetic speech. In this work, we propose an approach to synthesise poems with almost human like naturalness in order to enable literary scholars to systematically examine hypotheses on the interplay between text, spoken realisation, and the listener's perception of poem

Daniel Etiemble

In Carry Propagate Adders, carry propagation is the critical delay. The most efficient scheme is to generate Cout0 (Cin=0) and Cout1(Cin=1) and multiplex the correct output according to Cin. For any radix, the carry output is always 0/1. We present two versions of ternary adders with Cin = (0V, Vdd/2) and Cin = (0V, Vdd) and two versions of quaternary adders

Lorenzo M. Procopio

Quantum Fisher information is the principal tool used to give the ultimate precision bound on the estimation of parameters for quantum channels. In this work, we present analytical expressions for the quantum Fisher information with three noisy channels for the case where the channels are in superposition of causal orders. We found that the quantum Fisher in

Shikun Chen, Nguyen Manh Luc

This paper describes the RRMSE (Relative Root Mean Square Error) based weights to weight the occurrences of predictive values before averaging for the ensemble voting regression. The core idea behind ensemble regression is to combine several base regression models in order to improve the prediction performance in learning problems with a numeric continuous t

Julio E Castrillon-Candas, Michael Rosenbaum, Mark Kon

Massive vector field datasets are common in multi-spectral optical and radar sensors, among many other emerging areas of application. We develop a novel stochastic functional (data) analysis approach for detecting anomalies based on the covariance structure of nominal stochastic behavior across a domain. An optimal vector field Karhunen-Loeve expansion is ap

L. C. G. Govia, P. Jurcevic, C. J. Wood, N. Kanazawa

Mid-circuit measurements are a key component in many quantum information computing protocols, including quantum error correction, fault-tolerant logical operations, and measurement based quantum computing. As such, techniques to quickly and efficiently characterize or benchmark their performance are of great interest. Beyond the measured qubit, it is also re

Claudio Bottiglieri, Felice Piccolo, Carmine Giordano, Francesco Topputo

In this paper, a practical approach to the trajectory design for asteroid exploration missions with CubeSats is presented. When applied trajectories are sought, operative concerns and uncertainties affecting the spacecraft dynamics must be considered during the design process. Otherwise, trajectories that are possible on paper might become unfeasible when re

Matthias Wagner, Oliver Lang, Thomas Bauernfeind, Mario Huemer

Pipelined analog-to-digital converters (ADCs) are fundamental components of various signal processing systems requiring high sampling rates and a high linearity. Over the past years, calibration techniques have been intensively investigated to increase the linearity. In this work, we propose an equalization-based calibration technique which does not require

Sarina Meyer, Florian Lux, Pavel Denisov, Julia Koch

In this work, we propose a speaker anonymization pipeline that leverages high quality automatic speech recognition and synthesis systems to generate speech conditioned on phonetic transcriptions and anonymized speaker embeddings. Using phones as the intermediate representation ensures near complete elimination of speaker identity information from the input w

Nicolas P. Bauer, Jan Carl Budich, Björn Trauzettel, Alessio Calzona

We propose a novel spatially inhomogeneous setup for revealing quench-induced fractionalized excitations in entanglement dynamics. In this quench-probe setting, the region undergoing a quantum quench is tunnel-coupled to a static region, the probe.Subsequently, the time-dependent entanglement signatures of a tunable subset of excitations propagating to the p

Lazaros Mitskopoulos, Theoklitos Amvrosiadis, Arno Onken

Recordings of complex neural population responses provide a unique opportunity for advancing our understanding of neural information processing at multiple scales and improving performance of brain computer interfaces. However, most existing analytical techniques fall short of capturing the complexity of interactions within the concerted population activity.

Hemanshu Kaul, Akash Kumar, Andrew Liu, Jeffrey A. Mudrock

The chromatic polynomial of a graph $G$, denoted $P(G,m)$, is equal to the number of proper $m$-colorings of $G$ for each $m \in \mathbb{N}$. In 1990, Kostochka and Sidorenko introduced the list color function of graph $G$, denoted $P_{\ell}(G,m)$, which is a list analogue of the chromatic polynomial. The list color function threshold of $G$, denoted $\tau(G

Tongseok Lim

A cornerstone in convex analysis is the crucial relationship between functions and their convex conjugate via the Fenchel-Young inequality. In this dual variable setting, the maximal monotonicity of the contact set $ \big\{(x,y) \ \big| \ f(x) + f^*(y) = \langle x,y \rangle \big\}$ is due to the involution $f^{**} = f$ holding for convex lower-semicontinuous

Rongen Dong, Shaohua Jiang, Xinhai Hua, Yin Teng

Intelligent reflecting surface (IRS) is a revolutionary and low-cost technology for boosting the spectrum and energy efficiencies in future wireless communication network. In order to create controllable multipath transmission in the conventional line-of-sight (LOS) wireless communication environment, an IRS-aided directional modulation (DM) network is consi

Alessandro Lägeler

We employ the spectral theory of Eisenstein series to prove that the Hardy sums, integer-valued analogs of the classical Dedekind sums, are uniformly distributed in $\mathbf{Z} / m \mathbf{Z}$ for any integer $m > 1$.

Rodrigo Simas, Luis Sa-Couto, Andreas Wichert

Drawing from memory the face of a friend you have not seen in years is a difficult task. However, if you happen to cross paths, you would easily recognize each other. The biological memory is equipped with an impressive compression algorithm that can store the essential, and then infer the details to match perception. The Willshaw Memory is a simple abstract

Florian Lourens, Alfred Ludwig

A method for combinatorial sputter deposition of thin films on microparticles is presented. The method is developed for a laboratory-scale magnetron sputter system and uses a piezoelectric actuator to agitate the microparticles through oscillation. Custom-made components enable to agitate up to nine separate batches of particles simultaneously. Due to the ag

Antoine Legrand, Benoît Macq, Christophe De Vleeschouwer

JPEG-XS offers low complexity image compression for applications with constrained but reasonable bit-rate, and low latency. Our paper explores the deployment of JPEG-XS on lossy packet networks. To preserve low latency, Forward Error Correction (FEC) is envisioned as the protection mechanism of interest. Despite the JPEG-XS codestream is not scalable in esse

Rainer Picard, Sascha Trostorff

We consider skew-symmetric operators $A_{0}$ on a Hilbert space $H$ and characterise all (nonlinear) m-accretive restrictions of $A:=-A_{0}^{\ast}$ in terms of the "deficiency spaces" $\ker(1\pm A)$. The results are illustrated by several examples and applied to a partial differential equation with an impedance type boundary condition.

Shaghayegh Tavassoli, Carlos Diego Nascimento Damasceno, Ramtin Khosravi, Mohammad Reza Mousavi

Behavioral models enable the analysis of the functionality of software product lines (SPL), e.g., model checking and model-based testing. Model learning aims at constructing behavioral models for software systems in some form of a finite state machine. Due to the commonalities among the products of an SPL, it is possible to reuse the previously learned model

Riccardo Barbano, Johannes Leuschner, Javier Antorán, Bangti Jin

We investigate adaptive design based on a single sparse pilot scan for generating effective scanning strategies for computed tomography reconstruction. We propose a novel approach using the linearised deep image prior. It allows incorporating information from the pilot measurements into the angle selection criteria, while maintaining the tractability of a co

Umesh Kumar Verma, G. Ambika

We report the emergence of explosive synchronization in a multiplex network where oscillators on the first layer are coupled with attractive coupling and those on the second layer, coupled with repulsive coupling. With Stuart-Landau and FitzHugh-Nagumo oscillators as the nodal dynamics, we consider non-local and mean-field intralayer couplings. We establish

David Towers, Matthew Forshaw, Amir Atapour-Abarghouei, Andrew Stephen McGough

It is a sad reflection of modern academia that code is often ignored after publication -- there is no academic 'kudos' for bug fixes / maintenance. Code is often unavailable or, if available, contains bugs, is incomplete, or relies on out-of-date / unavailable libraries. This has a significant impact on reproducibility and general scientific progress. Neural

Varun Ojha, Jon Timmis, Giuseppe Nicosia

We present a comprehensive global sensitivity analysis of two single-objective and two multi-objective state-of-the-art global optimization evolutionary algorithms as an algorithm configuration problem. That is, we investigate the quality of influence hyperparameters have on the performance of algorithms in terms of their direct effect and interaction effect

Kristof M. Bal, Erik C. Neyts

We calculate bubble nucleation rates in a Lennard-Jones fluid through explicit molecular dynamics simulations. Our approach -- based on a recent free energy method (dubbed reweighted Jarzynski sampling), transition state theory, and a simple recrossing correction -- allows us to probe a fairly wide range of rates in several superheated and cavitation regimes

Jun Wang, Abhir Bhalerao, Yulan He

Radiology report generation (RRG) aims to describe automatically a radiology image with human-like language and could potentially support the work of radiologists, reducing the burden of manual reporting. Previous approaches often adopt an encoder-decoder architecture and focus on single-modal feature learning, while few studies explore cross-modal feature i

Vladimir M. Kaganer, Oleg V. Konovalov, Gabriele Calabrese, David van Treeck

GaN nanowires (NWs) grown by molecular beam epitaxy on Ti films sputtered on Al$_{2}$O$_{3}$ are studied by X-ray diffraction (XRD) and grazing incidence small-angle X-ray scattering (GISAXS). XRD, performed both in symmetric Bragg reflection and at grazing incidence, reveals Ti, Ti$_{3}$O, Ti$_{3}$Al, and TiO$_x$N$_y$ crystallites with in-plane and out-of-p

Lorenzo Brasco, María del Mar González, Mikel Ispizua

Motivated by the connection between the first eigenvalue of the Dirichlet-Laplacian and the torsional rigidity, the aim of this paper is to find a physically coherent and mathematically interesting new concept for boundary torsional rigidity, closely related to the Steklov eigenvalue. From a variational point of view, such a new object corresponds to the sha

Sisi Miao, Lukas Rapp, Laurent Schmalen

We propose an improved soft-aided decoding scheme for product codes that approaches the decoding performance of conventional soft-decision TPD with only a 0.2 dB gap while keeping the complexity and internal decoder data flow similarly low as in hard decision decoders.

Diyi Jin, Jianjun Liu, Jinlong Yang, Zebin Wu

Hyperspectral image super-resolution addresses the problem of fusing a low-resolution hyperspectral image (LR-HSI) and a high-resolution multispectral image (HR-MSI) to produce a high-resolution hyperspectral image (HR-HSI). Tensor analysis has been proven to be an efficient method for hyperspectral image processing. However, the existing tensor-based method

Javier Galbally, Julian Fierrez-Aguilar, Joaquin Rodriguez-Gonzalez, Fernando Alonso-Fernandez

A new method to generate gummy fingers is presented. A medium-size fake fingerprint database is described and two different fingerprint verification systems are evaluated on it. Three different scenarios are considered in the experiments, namely: enrollment and test with real fingerprints, enrollment and test with fake fingerprints, and enrollment with real

Shaily, J. K. Singh, Joao R. L. Santos, M. Zeyauddin

We study an isotropic flat FLRW-model in Scale-covariant theory of gravity $ f_{\gamma \delta}(\phi) $ \cite{Canuto:1977zz} which is explained in terms of ordinary and covariant differentiation of scalar field $ \phi $. As we know the deceleration parameter is time-dependent, so we consider the deceleration parameter $ q $ as the function of $ t $. Using thi

Kristoffer Knutsen Wickstrøm, Eirik Agnalt Østmo, Keyur Radiya, Karl Øyvind Mikalsen

Deep learning-based approaches for content-based image retrieval (CBIR) of CT liver images is an active field of research, but suffers from some critical limitations. First, they are heavily reliant on labeled data, which can be challenging and costly to acquire. Second, they lack transparency and explainability, which limits the trustworthiness of deep CBIR

Xianzhe Dai, Yihan Li

In this paper we study the asymptotic behavior of the spectral flow of a one-parameter family $\{D_s\}$ of Dirac operators acting on the spinor bunldle $S$ twisted by a vector bundle $E$ of rank $k$, with the parameter $s\in [0,r]$ when $r$ gets sufficiently large. Our method uses the variation of eta invariant and local index theory technique. The key is a

Birthe Schrinski, Yoon Jun Chan, Björn Schrinski

We study decoherence, diffusion, friction, and how they thermalize a planar rotor in the presence of an external potential. Representing the quantum master equation in terms of auxiliary Wigner functions in periodic phase space not only illustrates the thermalization process in a concise way, but also allows for an efficient numerical evaluation of the open

Javier Galbally, Fernando Alonso-Fernandez, Julian Fierrez, Javier Ortega-Garcia

A new fingerprint parameterization for liveness detection based on quality measures is presented. The novel feature set is used in a complete liveness detection system and tested on the development set of the LivDET competition, comprising over 4,500 real and fake images acquired with three different optical sensors. The proposed solution proves to be robust

Zijie Wu, Zhen Zhu, Junping Du, Xiang Bai

In this paper, we aim to devise a universally versatile style transfer method capable of performing artistic, photo-realistic, and video style transfer jointly, without seeing videos during training. Previous single-frame methods assume a strong constraint on the whole image to maintain temporal consistency, which could be violated in many cases. Instead, we

Iver H. Brevik, Moshe M. Chaichian

Axion electrodynamics is based upon the Lagrangian of the electromagnetic (EM) field plus its interaction with the axions, and is accordingly a physically open system. It means that the four-divergence of the EM energy-momentum tensor is different from zero, implying in turn that the total EM energy and momentum (when integrated over all space) do not consti

Ryutaro Tanno, Melanie F. Pradier, Aditya Nori, Yingzhen Li

Prediction failures of machine learning models often arise from deficiencies in training data, such as incorrect labels, outliers, and selection biases. However, such data points that are responsible for a given failure mode are generally not known a priori, let alone a mechanism for repairing the failure. This work draws on the Bayesian view of continual le

Maria Cairoli, André van den Doel, Berber Postma, Tim Offermans

A comprehensive approach to protect river water quality is needed within the European Water Framework Directive. Non-target screening of a complete chemical fingerprint of the aquatic ecosystem is essential, to identify chemicals of emerging concern and to reveal their suspicious dynamic patterns in river water. This requires a new combination of two measure

Casper Farret Jentink, Annelies Mortier, Frans Snik, Patrick Dorval

We present a description of A dual-Beam pOlarimetric Robotic Aperture for the Sun (ABORAS), to serve as a Solar input with a dedicated Stokes V polarimeter for the HARPS3 high-resolution spectrograph. ABORAS has three main science drivers: trying to understand the physics behind stellar variability, tracking the long-term stability of HARPS3, and serve as a

Disha Hou, Yuhai Liu, Toshihiro Sato, Wenan Guo

The quantum spin Hall state can be understood in terms of spontaneous O(3) symmetry breaking. Topological skyrmion configurations of the O(3) order parameter vector carry a charge 2e, and as shown previously, when they condense, a superconducting state is generated. We show that this topological route to superconductivity survives easy-plane anisotropy. Upon

Pengfei Wang, Xiaocan Zeng, Lu Chen, Fan Ye

Entity Matching (EM), which aims to identify whether two entity records from two relational tables refer to the same real-world entity, is one of the fundamental problems in data management. Traditional EM assumes that two tables are homogeneous with the aligned schema, while it is common that entity records of different formats (e.g., relational, semi-struc

Fritz Webering, Sarah Kleinjohann, Nils Stanislawski, Holger Blume

Inertial measurement units (IMUs) are used in medical applications for many different purposes. However, an IMU's measurement accuracy can degrade over time, entailing re-calibration. In their 2014 paper, Tedaldi et al. presented an IMU calibration method that does not require external precision equipment or complex procedures. This allows end-users or perso

Nicolas Biver, Neil Dello Russo, Cyrielle Opitom, Martin Rubin

The composition of cometary ices provides key information on the thermal and chemical properties of the outer parts of the protoplanetary disk where they formed 4.6 Gy ago. This chapter reviews our knowledge of composition of cometary comae based on remote spectroscopy and in-situ investigations techniques. Cometary comae can be dominated by water vapour, CO

Elmer Bergman, Lasse Leskelä

This article discusses random hypergraphs with varying hyperedge sizes, admitting large hyperedges with size tending to infinity, and heavy-tailed limiting hyperedge size distributions. The main result describes a threshold for the random hypergraph to be connected with high probability, and shows that the average hyperedge size suffices to characterise conn

Petr A. Golovach, Giannos Stamoulis, Dimitrios M. Thilikos

A linkage in a graph $G$ of size $k$ is a subgraph $L$ of $G$ whose connected components are $k$ paths. The pattern of a linkage of size $k$ is the set of $k$ pairs formed by the endpoints of these paths. A consequence of the Unique Linkage Theorem is the following: there exists a function $f:\mathbb{N}\to\mathbb{N}$ such that if a plane graph $G$ contains a

Jagnyashini Debadarshini, Sudipta Saha, Subhransu Ranjan Samantaray

A Home Area Network (HAN) is considered to be a significant component of Advanced Metering Infrastructure (AMI) and has been studied well in many works. It binds all the electrical components installed in a defined premise together for their close monitoring and management. However, HAN has been realized so far mostly as a centralized system. Therefore, like

Elisa Gugliotta, Marco Dinarelli

In this paper we present the final result of a project on Tunisian Arabic encoded in Arabizi, the Latin-based writing system for digital conversations. The project led to the creation of two integrated and independent resources: a corpus and a NLP tool created to annotate the former with various levels of linguistic information: word classification, translit

A. Revelli, M. Moretti Sala, G. Monaco, M. Magnaterra

The mixed-valent iridate Ba3InIr2O9 has been discussed as a promising candidate for quantum spin-liquid behavior. The compound exhibits Ir$^{4.5+}$ ions in face-sharing IrO6 octahedra forming Ir2O9 dimers with three t2g holes per dimer. Our results establish Ba3InIr2O9 as a cluster Mott insulator. Strong intra-dimer hopping delocalizes the three t2g holes in

Bartosz Uniejewski, Katarzyna Maciejowska

This paper develops a novel, fully automated forecast averaging scheme, which combines LASSO estimation method with Principal Component Averaging (PCA). LASSO-PCA (LPCA) explores a pool of predictions based on a single model but calibrated to windows of different sizes. It uses information criteria to select tuning parameters and hence reduces the impact of

Kanghao Chen, Weixian Lei, Rong Zhang, Shen Zhao

Imbalanced training data is a significant challenge for medical image classification. In this study, we propose a novel Progressive Class-Center Triplet (PCCT) framework to alleviate the class imbalance issue particularly for diagnosis of rare diseases, mainly by carefully designing the triplet sampling strategy and the triplet loss formation. Specifically,

Rebeka Kropivšek Leskovar, Tadej Petrič

An important factor in developing control models for human-robot collaboration is how acceptable they are to their human partners. One such method for creating acceptable control models is to attempt to mimic human-like behaviour in robots so that their actions appear more intuitive to humans. To investigate how task complexity affects human perception and a

Rebeka Kropivšek Leskovar, Jernej Čamernik, Tadej Petrič

A question that many researchers in social robotics are addressing is how to create more human-like behaviour in robots to make the collaboration between a human and a robot more intuitive to the human partner. In order to develop a human-like collaborative robotic system, however, human collaboration must first be better understood. Human collaboration is s

Oleksiy V. Dudnik, Janusz Sylwester, Miroslaw Kowalinski, Piotr Podgorski

We analyze variations of high-energy charged particle populations filling various magnetospheric regions under, inside, and outside of the Van Allen inner and outer electron radiation belts in May 2009. The study is based on the experimental data obtained from the STEP-F and the SphinX instruments placed close to each other aboard the low-Earth circular orbi