October 2022 arXiv papers — page 45

Arne Schneuing, Charles Harris, Yuanqi Du, Kieran Didi

Structure-based drug design (SBDD) aims to design small-molecule ligands that bind with high affinity and specificity to pre-determined protein targets. Generative SBDD methods leverage structural data of drugs in complex with their protein targets to propose new drug candidates. These approaches typically place one atom at a time in an autoregressive fashio

Nicola Pranzini, Guillermo García-Pérez, Esko Keski-Vakkuri, Sabrina Maniscalco

The Born rule describes the probability of obtaining an outcome when measuring an observable of a quantum system. As it can only be tested by measuring many copies of the system under consideration, it does not hold for non-replicable systems. For these systems, we give a procedure to predict the future statistics of measurement outcomes through Repeated Mea

Darius Modirrousta-Galian, Jun Korenaga

A significant fraction of super-Earths and sub-Neptunes are thought to experience an extreme loss of volatiles because of atmospheric evaporation in the early stages of their life. Though the mechanisms behind the extreme mass loss are not fully understood, two contenders have been widely discussed: photoevaporation from X-ray and ultraviolet irradiation and

Bastian Eisele, Ali Bereyhi, Ingrid Ullmann, Ralf Müller

In colocated compressive sensing MIMO radar, the measurement matrix is specified by antenna placement. To guarantee an acceptable recovery performance, this measurement matrix should satisfy certain properties, e.g., a small coherence. Prior work in the literature often employs randomized placement algorithms which optimize the prior distribution of antenna

Andrew Lee, Zhenguo Chen, Kevin Leach, Jonathan K. Kummerfeld

The standard task-oriented dialogue pipeline uses intent classification and slot-filling to interpret user utterances. While this approach can handle a wide range of queries, it does not extract the information needed to handle more complex queries that contain relationships between slots. We propose integration of relation extraction into this pipeline as a

Zachary Compton, Kathleen Hanlon, Carolyn C. Compton, Athena Aktipis

Cancer cells possess a nearly universal set of characteristics termed the hallmarks of cancer, including replicative immortality and resisting cell death. Dysregulated differentiation is present in virtually all cancers yet has not yet been described as a cancer hallmark. Like other hallmarks, dysregulated differentiation involves a breakdown of the cellular

Sarkisyan A., Vinokurov A., Solovyeva Yu., Atapin K.

We study the luminous blue variable candidate J004229.87+410551.8 in the Andromeda Galaxy. Earlier, the star displayed a spectral anomaly: although a hot emission spectrum had been detected, it had strong CaII H and K absorption lines. Subsequently the star was assumed to be a hot hypergiant or a B[e] supergiant. For the purpose of clear star classification,

Varda F. Hagh, Chloe W. Lindeman, Chi Ian Ip, Sidney R. Nagel

Bi-stable objects that are pushed between states by an external field are often used as a simple model to study memory formation in disordered materials. Such systems, called hysterons, are typically treated quasistatically. Here, we generalize hysterons to explore the effect of dynamics in a simple spring system with tunable bistability and study how the sy

I. D. Avdeev, S. V. Goupalov, M. O. Nestoklon

The Land\'e or g-factors of charge carriers in solid state systems provide invaluable information about response of quantum states to external magnetic fields and are key ingredients in description of spin-dependent phenomena in nanostructures. We report on the comprehensive theoretical analysis of electron and hole g-factors in lead chalcogenide nanocrystal

Muhammed Fatih Balın, Ümit V. Çatalyürek

Graph Neural Networks (GNNs) have received significant attention recently, but training them at a large scale remains a challenge. Mini-batch training coupled with sampling is used to alleviate this challenge. However, existing approaches either suffer from the neighborhood explosion phenomenon or have poor performance. To address these issues, we propose a

Vassily Olegovich Manturov

The aim of this article is to prove that the kernel of the map from the pure braid group $PB_{n},n\ge 4$ to the group $G_{n}^{3}$ consists of full twist braids and their exponents. The proof consists of two parts. The first part which deals with $n=4$ relies on the crucial tool in this construction having its own interest is the {\em realisability projection

Boris L. Feigin, Simon D. Lentner

Certain deformable families of vertex algebras acquire at a limit of the deformation parameter a large center, similar to affine Lie algebras at critical level. Then the vertex algebra and its representation category become a bundle over the variety defined by this large center. The zero-fibre becomes a vertex algebra, the other fibres become twisted modules

MD Abdullah Al Nasim, Abdullah Al Munem, Maksuda Islam, Md Aminul Haque Palash

Cancer of the brain is deadly and requires careful surgical segmentation. The brain tumors were segmented using U-Net using a Convolutional Neural Network (CNN). When looking for overlaps of necrotic, edematous, growing, and healthy tissue, it might be hard to get relevant information from the images. The 2D U-Net network was improved and trained with the Br

Wilmar Cardona, M. A. Sabogal

Interesting discrepancies in cosmological parameters are challenging the success of the $\Lambda$CDM model. Direct measurements of the Hubble constant $H_0$ using Cepheid variables and supernovae turn out to be higher than inferred from the Cosmic Microwave Background (CMB). Weak galaxy lensing surveys consistently report values of the strength of matter clu

Quchen Fu, Szu-Wei Fu, Yaran Fan, Yu Wu

Meetings are an essential form of communication for all types of organizations, and remote collaboration systems have been much more widely used since the COVID-19 pandemic. One major issue with remote meetings is that it is challenging for remote participants to interrupt and speak. We have recently developed the first speech interruption analysis model, wh

Molla Basir Ahamed, Sanju Mandal

The functional equations $ f^2+g^2=1 $ and $ f^2+2\alpha fg+g^2=1 $ are respectively called Fermat-type binomial and trinomial equations. It is of interest to know about the existence and form of the solutions of general quadratic functional equations. Utilizing Nevanlinna's theory for several complex variables, in this paper, we study the existence and form

M. Euler, N. Euler, MC Nucci

We compute invariants for the two-variable M\"obius transformation. In particular we are interested in partial differential equations in two dependent and two independent variables that are kept invariant under this transformation.

Mourad El Hamri, Younès Bennani, Issam Falih

Domain adaptation arises as an important problem in statistical learning theory when the data-generating processes differ between training and test samples, respectively called source and target domains. Recent theoretical advances show that the success of domain adaptation algorithms heavily relies on their ability to minimize the divergence between the pro

Xiao Li, Brent R Logan, S M Ferdous Hossain, Erica E M Moodie

To achieve the goal of providing the best possible care to each patient, physicians need to customize treatments for patients with the same diagnosis, especially when treating diseases that can progress further and require additional treatments, such as cancer. Making decisions at multiple stages as a disease progresses can be formalized as a dynamic treatme

Rami Katz, Nuha Diab, Dmitry Batenkov

We study recovery of amplitudes and nodes of a finite impulse train from noisy frequency samples. This problem is known as super-resolution under sparsity constraints and has numerous applications. An especially challenging scenario occurs when the separation between Dirac pulses is smaller than the Nyquist-Shannon-Rayleigh limit. Despite large volumes of re

The KM3NeT collaboration

The optical data transport system of the KM3NeT neutrino telescope at the bottom of the Mediterranean Sea will provide each of the more than 6000 optical modules in the detector arrays with a point-to-point optical connection to the control stations onshore. The ARCA and ORCA detectors of KM3NeT are being installed at a depth of about 3500 m and 2500 m, resp

Long Feng, Guang Yang

We propose Deep Kronecker Network (DKN), a novel framework designed for analyzing medical imaging data, such as MRI, fMRI, CT, etc. Medical imaging data is different from general images in at least two aspects: i) sample size is usually much more limited, ii) model interpretation is more of a concern compared to outcome prediction. Due to its unique nature,

Subhadeep Dey, Abhilash Pal, Cyrine Chaabani, Oscar Koller

This paper describes Microsoft's submission to the first shared task on sign language translation at WMT 2022, a public competition tackling sign language to spoken language translation for Swiss German sign language. The task is very challenging due to data scarcity and an unprecedented vocabulary size of more than 20k words on the target side. Moreover, th

Alireza Dehlaghi-Ghadim, Ali Balador, Mahshid Helali Moghadam, Hans Hansson

With the advent of smart industry, Industrial Control Systems (ICS) are increasingly using Cloud, IoT, and other services to meet Industry 4.0 targets. The connectivity inherent in these services exposes such systems to increased cybersecurity risks. To protect ICSs against cyberattacks, intrusion detection systems and intrusion prevention systems empowered

Xing-Yan Chen, Andreas Schindewolf, Sebastian Eppelt, Roman Bause

Scattering resonances are an essential tool for controlling interactions of ultracold atoms and molecules. However, conventional Feshbach scattering resonances, which have been extensively studied in various platforms, are not expected to exist in most ultracold polar molecules due to the fast loss that occurs when two molecules approach at a close distance.

Yuxuan Zhao, Samuel W. K. Wong

The number of confirmed COVID-19 cases reached over 1.3 million in Ontario, Canada by June 4, 2022. The continued spread of the virus underlying COVID-19 has been spurred by the emergence of variants since the initial outbreak in December, 2019. Much attention has thus been devoted to tracking and modelling the transmission of COVID-19. Compartmental models

Paul Kilgarriff, Remi Lemoy, Geoffrey Caruso

The difference of a city's artificial land use (ALU) radial profile to the average ALU profile is examined for 585 European cities. Using Urban Atlas 2012 data, a radial (or monocentric) approach is used to calculate a city's land use profile in relation to distance to the city centre. A scaling law is used which controls for city size and population. As a c

Yizhou Li, Yusuke Monno, Masatoshi Okutomi

Removing raindrops in images has been addressed as a significant task for various computer vision applications. In this paper, we propose the first method using a Dual-Pixel (DP) sensor to better address the raindrop removal. Our key observation is that raindrops attached to a glass window yield noticeable disparities in DP's left-half and right-half images,

Mohit Daga

We give a closed form formula to determine the size of a k-respecting cut. Further, we show that for any k, the size of the k-respecting cut can be found only using the size of 2-respecting cuts.

Krunoslav Lehman Pavasovic, Jonas Rothfuss, Andreas Krause

Meta-learning aims to extract useful inductive biases from a set of related datasets. In Bayesian meta-learning, this is typically achieved by constructing a prior distribution over neural network parameters. However, specifying families of computationally viable prior distributions over the high-dimensional neural network parameters is difficult. As a resul

Yufeng Yang, Ashutosh Pandey, DeLiang Wang

It has been shown that the intelligibility of noisy speech can be improved by speech enhancement algorithms. However, speech enhancement has not been established as an effective frontend for robust automatic speech recognition (ASR) in noisy conditions compared to an ASR model trained on noisy speech directly. The divide between speech enhancement and ASR im

Philipp Kratzer, Marc Toussaint, Jim Mainprice

Numerical optimization has become a popular approach to plan smooth motion trajectories for robots. However, when sharing space with humans, balancing properly safety, comfort and efficiency still remains challenging. This is notably the case because humans adapt their behavior to that of the robot, raising the need for intricate planning and prediction. In

Jian-Hua Zeng, Su Yi, Liang He

We investigate the ground state properties of an ultracold atom system consisting of many-body polarons, quasiparticles formed by impurity atoms in optical lattices immersing in a Bose-Einstein condensate. We find the nearest-neighbor attractive interaction between polarons can give rise to rich physics that is peculiar to this system. In a relatively shallo

Li Yan, Zhoufeng Wang, Yao Cheng

The local discontinuous Galerkin (LDG) method is studied for a third-order singularly perturbed problem of the convection-diffusion type. Based on a regularity assumption for the exact solution, we prove almost $O(N^{-(k+1/2)})$ (up to a logarithmic factor) energy-norm convergence uniformly in the perturbation parameter. Here, $k\geq 0$ is the maximum degree

Jaehan Bae, Andrea Isella, Zhaohuan Zhu, Rebecca Martin

Recent spatially-resolved observations of protoplanetary disks revealed a plethora of substructures, including concentric rings and gaps, inner cavities, misalignments, spiral arms, and azimuthal asymmetries. This is the major breakthrough in studies of protoplanetary disks since Protostars and Planets VI and is reshaping the field of planet formation. Howev

Alexey Kutalev

Following the invention in 2017 of the EWC method, several methods have been proposed to calculate the importance of neural network weights for use in the EWC method. Despite the significant difference in calculating the importance of weights, they all proved to be effective. Accordingly, a reasonable question arises as to how similar the importances of the

Alkis Kalavasis, Konstantinos Stavropoulos, Manolis Zampetakis

We study the problem of covering and learning sums $X = X_1 + \cdots + X_n$ of independent integer-valued random variables $X_i$ (SIIRVs) with unbounded, or even infinite, support. De et al. at FOCS 2018, showed that the maximum value of the collective support of $X_i$'s necessarily appears in the sample complexity of learning $X$. In this work, we address t

S. Molendi, S. De Grandi, M. Rossetti, I. Bartalucci

In this work we address the issue of whether the division of clusters in cool cores (CCs) and non-cool cores (NCCs) is due to a primordial difference or to how clusters evolve across cosmic time. Our first goal is to establish if spectra from the central regions of a subclass of NCCs known as cool core remnants (CCRs) are consistent with having a small but s

Maarten Sap, Ronan LeBras, Daniel Fried, Yejin Choi

Social intelligence and Theory of Mind (ToM), i.e., the ability to reason about the different mental states, intents, and reactions of all people involved, allow humans to effectively navigate and understand everyday social interactions. As NLP systems are used in increasingly complex social situations, their ability to grasp social dynamics becomes crucial.

Jing Yi, Weize Chen, Yujia Qin, Yankai Lin

Delta tuning (DET, also known as parameter-efficient tuning) is deemed as the new paradigm for using pre-trained language models (PLMs). Up to now, various DETs with distinct design elements have been proposed, achieving performance on par with fine-tuning. However, the mechanisms behind the above success are still under-explored, especially the connections

Jackson P. Lautier, Stella Grosser, Jessica Kim, Hyewon Kim

Pharmaceutical researchers are continually searching for techniques to improve both drug development processes and patient outcomes. An area of recent interest is the potential for machine learning (ML) applications within pharmacology. One such application not yet given close study is the unsupervised clustering of plasma concentration-time curves, hereafte

Xavier Mootoo, Paul Skoufranis

Various notions of joint majorization are examined in continuous matrix algebras. The relative strengths of these notions are established via proofs and examples. In addition, the closed convex hulls of joint unitary orbits are completely characterized in continuous matrix algebras via notions of joint majorization. Some of these characterizations are extend

Bin Guo, Duong H. Phong

This is an introduction to a particular class of auxiliary complex Monge-Amp\`ere equations which had been instrumental in $L^\infty$ estimates for fully non-linear equations and various questions in complex geometry. The essential comparison inequalities are reviewed and shown to apply in many contexts. Adapted to symplectic geometry, with the auxiliary equ

Shrigyan Brahmachari, Rohan Narayan Rajmohan, Suhail Ahmad Rather, Arul Lakshminarayan

TThe problem of finding the resource free, closest local unitary, to any bipartite unitary gate $U$ is addressed. Previously discussed as a measure of nonlocality, the distance $K_D(U)$ to the nearest product unitary has implications for circuit complexity and related quantities. Dual unitaries, currently of great interest in models of complex quantum many-b

Stefano Ciaci

A Banach space is locally almost square if, for every $y$ in its unit sphere, there exists a sequence $(x_n)$ in its unit sphere such that $\lim\|y\pm x_n\|=1$. A Banach space is weakly almost square if, in addition, we require the sequence $(x_n)$ to be weakly null. It is known that these two properties are distinct, so we aim to investigate if local almost

Lukas Bode, Michael Weinmann, Reinhard Klein

Extracting high-level structural information from 3D point clouds is challenging but essential for tasks like urban planning or autonomous driving requiring an advanced understanding of the scene at hand. Existing approaches are still not able to produce high-quality results consistently while being fast enough to be deployed in scenarios requiring interacti

Junyi Li, Tianyi Tang, Wayne Xin Zhao, Jian-Yun Nie

We study the text generation task under the approach of pre-trained language models (PLMs). Typically, an auto-regressive (AR) method is adopted for generating texts in a token-by-token manner. Despite many advantages of AR generation, it usually suffers from inefficient inference. Therefore, non-autoregressive (NAR) models are proposed to generate all targe

Agatha Atkarskaya

In this paper we prove that small cancellation rings under some natural restrictions are non-amenable and contain non-commutative free associative algebra.

Khrystyna Serhiyenko, Melissa Sherman-Bennett

Leclerc constructed a conjectural cluster structure on Richardson varieties in simply laced types using cluster categories. We show that in type A, his conjectural cluster structure is in fact a cluster structure. We do this by comparing Leclerc's construction with another cluster structure on type A Richardson varieties due to Ingermanson. Ingermanson's con

Luca Galimberti, Anastasis Kratsios, Giulia Livieri

Several non-linear operators in stochastic analysis, such as solution maps to stochastic differential equations, depend on a temporal structure which is not leveraged by contemporary neural operators designed to approximate general maps between Banach space. This paper therefore proposes an operator learning solution to this open problem by introducing a dee

Marcin Patecki, Alex Fomin, Daniele Mirarchi, Stefano Redaelli

The Large Hadron Collider (LHC) at the European Organization for Nuclear Research (CERN) is the world's largest and most powerful particle accelerator colliding beams of protons and lead ions at energies up to 7 ZTeV, Z is the atomic number. ALICE is one of the detector experiments optimised for heavy-ion collisions. A fixed-target experiment in ALICE is bei

Mayank Narang, Apurva V. Oza, Kaustubh Hakim, Manoj Puravankara

We conducted the first dedicated search for signatures of exoplanet-exomoon interactions using the Giant Metrewave Radio Telescope (GMRT) as part of the radio-loud exoplanet-exomoon survey (RLEES). Due to stellar tidal heating, irradiation, and subsequent atmospheric escape, candidate `exo-Io' systems are expected to emit up to $10^6$ times more plasma flux

Simon Geirnaert, Tom Francart, Alexander Bertrand

In brain-computer interface or neuroscience applications, generalized canonical correlation analysis (GCCA) is often used to extract correlated signal components in the neural activity of different subjects attending to the same stimulus. This allows quantifying the so-called inter-subject correlation or boosting the signal-to-noise ratio of the stimulus-fol

Petros N. Tamvakis, Chairi Kiourt, Alexandra D. Solomou, George Ioannakis

Plant phenotyping refers to a quantitative description of the plants properties, however in image-based phenotyping analysis, our focus is primarily on the plants anatomical, ontogenetical and physiological properties.This technique reinforced by the success of Deep Learning in the field of image based analysis is applicable to a wide range of research areas

Graziano Gentili, Luisa Simonutti, Daniele C. Struppa

We show how the birth of perspective painting in the Italian Renaissance led to a new way of interpreting space that resulted in the creation of projective geometry. Unlike other works on this subject, we explicitly show how the craft of the painters implied the introduction of new points and lines (points and lines at infinity) and their projective coordina

Pekka Heinämäki, Pekka Teerikorpi, Marian Douspis, Pasi Nurmi

Generally the dynamical state of superclusters is poorly known. We study properties of superclusters and select a sample of quasi-spherical superclusters, the dynamics of which can be studied using the $\Lambda$ significance diagram. We extracted our supercluster sample with an adaptive local threshold density method from the Sloan Digital Sky Survey Data Re

Shan Li, Ming Huang, Yongfeng Song, Bo Lan

This work presents theoretical and numerical models for the backscattering of two-dimensional Rayleigh waves by an elastic inclusion, with the host material being isotropic and the inclusion having arbitrary shape and crystallographic symmetry. The theoretical model is developed based on the reciprocity theorem using the far-field Green's function and the Bo

Şahin Kürekci, S. Süleyman Kahraman, Emre Yüce

When light passes through a multimode fiber, two-dimensional random intensity patterns are formed due to the complex interference within the fiber. The extreme sensitivity of speckle patterns to the frequency of light paved the way for high-resolution multimode fiber spectrometers. However, this approach requires expensive IR cameras and impedes the integrat

Mary Hewitt, Hamish Cunningham

Voice control in the smart home is commonplace, enabling the convenient control of smart home Internet of Things hubs, gateways and devices, along with information seeking dialogues. Cloud-based voice assistants are used to facilitate the interaction, yet privacy concerns surround the cloud analysis of data. To what extent can voice control be performed usin

Holger R. Roth, Yan Cheng, Yuhong Wen, Isaac Yang

Federated learning (FL) enables building robust and generalizable AI models by leveraging diverse datasets from multiple collaborators without centralizing the data. We created NVIDIA FLARE as an open-source software development kit (SDK) to make it easier for data scientists to use FL in their research and real-world applications. The SDK includes solutions

Linda Lastrico, Nuno Ferreira Duarte, Alessandro Carfì, Francesco Rea

As humans, we have a remarkable capacity for reading the characteristics of objects only by observing how another person carries them. Indeed, how we perform our actions naturally embeds information on the item features. Collaborative robots can achieve the same ability by modulating the strategy used to transport objects with their end-effector. A contribut

Adnan Qayyum, Muhammad Atif Butt, Hassan Ali, Muhammad Usman

Metaverse is expected to emerge as a new paradigm for the next-generation Internet, providing fully immersive and personalised experiences to socialize, work, and play in self-sustaining and hyper-spatio-temporal virtual world(s). The advancements in different technologies like augmented reality, virtual reality, extended reality (XR), artificial intelligenc

Jiakuan Fan, Haoyue Wang, Wei Wang, Ming Gao

In open source project governance, there has been a lot of concern about how to measure developers' contributions. However, extremely sparse work has focused on enabling developers to improve their contributions, while it is significant and valuable. In this paper, we introduce a deep reinforcement learning framework named Open Source Software(OSS) Mentor, w

Stephen McKean

Because the problem of Apollonius is generally considered over the reals, it suffers from variance of number: there are at most eight circles simultaneously tangent to a given trio of circles, but some configurations have fewer than eight tangent circles. This issue arises over other non-closed fields as well. Using the tools of enriched enumerative geometry

Olaf Borsboom, Thijs de Mooy, Mauro Salazar, Theo Hofman

This paper introduces a framework to systematically optimize the control and design of an electric vehicle transmission, connecting powertrain sizing studies to detailed gearbox design methods. To this end, we first create analytical models of individual components: gears, shafts, bearings, clutches, and synchronizers. Second, we construct a transmission by

Barnabás Janzer, J. Robert Johnson, Imre Leader

What is the smallest number of random transpositions (meaning that we swap given pairs of elements with given probabilities) that we can make on an $n$-point set to ensure that each element is uniformly distributed -- in the sense that the probability that $i$ is mapped to $j$ is $1/n$ for all $i$ and $j$? And what if we insist that each pair is uniformly di

Theodosios Chatzistergos, Natalie A. Krivova, Ilaria Ermolli

First such observations were made in 1892 and since then various sites around the world have carried out regular observations, with Kodaikanal, Meudon, Mt Wilson, and Coimbra being some of the most prominent ones. By now, Ca II K observations from over 40 different sites allow an almost complete daily coverage of the last century. Ca II K images provide dire

Pedro Bicudo, Nuno Cardoso, Lasse Mueller, Marc Wagner

We investigate $I = 0$ bottomonium bound states and resonances in S, P, D and F waves using lattice QCD static-static-light-light potentials. We consider five coupled channels, one confined quarkonium and four open $B^{(*)}\bar{B}^{(*)}$ and $B^{(*)}_s\bar{B}^{(*)}_s$ meson-meson channels and use the Born-Oppenheimer approximation and the emergent wave metho

Verena Biener, Jens Grubert

In this paper, we describe the results of replicating one of our studies from two years ago which compares two techniques for transferring content across multiple screens in VR. Results from the previous study have shown that a combined gaze and touch input can outperform a bimanual touch-only input in terms of task completion time, simulator sickness, task

B. Blok, J. Mehl

We study the contribution of color correlations to Double Parton Scattering (DPS). We show that there is a specific class of Feynman diagrams related to so called 1 \textrightarrow{} 2 processes when the contribution of these color correlations is not Sudakov suppressed with the transverse scales. The split scale increases with the transverse scale Q, with c

Tsz Kin Lam, Eva Hasler, Felix Hieber

Customer feedback can be an important signal for improving commercial machine translation systems. One solution for fixing specific translation errors is to remove the related erroneous training instances followed by re-training of the machine translation system, which we refer to as instance-specific data filtering. Influence functions (IF) have been shown

Surajit Basak, Przemysław Piekarz, Andrzej Ptok

Iron-based superconductors, with the ThCr$_{2}$Si$_{2}$-type tetragonal structure (122 family), due to the iron arsenide/selenide layers exhibit several characteristic electronic properties. For example, multiband character mosty associated with the $d$-orbitals of iron and the quasi-two-dimensional (2D) cylindrical Fermi surface. Moreover, external hydrosta

Ziqi Liang

Recurrent Neural Networks (RNNs) have become the standard modeling technique for sequence data, and are used in a number of novel text-to-speech models. However, training a TTS model including RNN components has certain requirements for GPU performance and takes a long time. In contrast, studies have shown that CNN-based sequence synthesis technology can gre

Jing-Yuan Xia, Zhixiong Yang, Tong Qiu, Huaizhang Liao

Multi-user multiple-input multiple-output (MU-MIMO) beamforming design is typically formulated as a non-convex weighted sum rate (WSR) maximization problem that is known to be NP-hard. This problem is solved either by iterative algorithms, which suffer from slow convergence, or more recently by using deep learning tools, which require time-consuming pre-trai

Xavier Coiteux-Roy, Stefan Wolf

In line with advances in recent years about realizing cryptographic functionalities in an information-theoretically secure way from physical phenomena and laws, we propose here to obtain useful tasks from the sole assumption of limited free energy. Specifically, based on that assumption -- resulting in a setting loosely related to Maurer's bounded-storage mo

Laurent Condat, Ivan Agarský, Peter Richtárik

In distributed optimization, a large number of machines alternate between local computations and communication with a coordinating server. Communication, which can be slow and costly, is the main bottleneck in this setting. To reduce this burden and therefore accelerate distributed gradient descent, two strategies are popular: 1) communicate less frequently;

M. Amir Bazrafshan, Farhad Khoeini

Thermoelectrics as a way to use waste heat, is essential in electronic industries, but its low performance at operational temperatures makes it inappropriate in practical applications. Tailoring graphene can change its properties. In this work, we are interested in studying the transport properties of S-shape graphene structures with the single vacancy (SV)

Danijel Krizmanic

For moving average processes with random coefficients and heavy-tailed innovations that are weakly dependent in the sense of strong mixing and local dependence condition $D'$ we study joint functional convergence of partial sums and maxima. Under the assumption that all partial sums of the series of coefficients are a.s. bounded between zero and the sum of t

Ana Budisa, Xiaozhe Hu, Miroslav Kuchta, Kent-Andre Mardal

We introduce the software toolbox HAZniCS for solving interface-coupled multiphysics problems. HAZniCS is a suite of modules that combines the well-known FEniCS framework for finite element discretization with solver and graph library HAZmath. The focus of the paper is on the design and implementation of a pool of robust and efficient solver algorithms which

Maximilian Bundscherer, Thomas H. Schmitt, Sebastian Bayerl, Thomas Auerbach

This paper describes a machine learning approach to determine the abrasive belt wear of wide belt sanders used in industrial processes based on acoustic data, regardless of the sanding process-related parameters, Feed speed, Grit Size, and Type of material. Our approach utilizes Decision Tree, Random Forest, k-nearest Neighbors, and Neural network Classifier

S. S. Kuptsov, M. V. Ioffe, S. N. Manida, S. A. Paston

We study a perturbation theory for embedding gravity equations in a background for which corrections to the embedding function are linear with respect to corrections to the flat metric. The arbitrariness remaining after solving the linearized field equations is fixed by an assumption that the solution is static in the second order. A nonlinear differential e

Kuan-Chen Wang, Kai-Chun Liu, Sheng-Yu Peng, Yu Tsao

Electrocardiogram (ECG) artifact contamination often occurs in surface electromyography (sEMG) applications when the measured muscles are in proximity to the heart. Previous studies have developed and proposed various methods, such as high-pass filtering, template subtraction and so forth. However, these methods remain limited by the requirement of reference

Yiming Ju, Yuanzhe Zhang, Kang Liu, Jun Zhao

The opaqueness of deep NLP models has motivated the development of methods for interpreting how deep models predict. Recently, work has introduced hierarchical attribution, which produces a hierarchical clustering of words, along with an attribution score for each cluster. However, existing work on hierarchical attribution all follows the connecting rule, li

P. Gallés, K. Takats, M. Hernández-Cabronero, D. Berga

IQUAFLOW is a new image quality framework that provides a set of tools to assess image quality. The user can add custom metrics that can be easily integrated. Furthermore, iquaflow allows to measure quality by using the performance of AI models trained on the images as a proxy. This also helps to easily make studies of performance degradation of several modi

Evgeniy Boyko, Ivan C. Christov

We analyze the steady non-Newtonian fluid-structure interaction between the flow of an Oldroyd-B fluid and a deformable channel. Specifically, we provide a theoretical framework for calculating the leading-order effect of the fluid's viscoelasticity on the flow rate-pressure drop relation and on the deformation of the channel's elastic wall. We first identif

Simon Sekavčnik, Janis Nötzel

Quantum communication technology offers several advanced strategies. However, their practical use is often times not yet well understood. In this work we therefore analyze the concept of a futuristic large-scale robotic factory, where each robot has a computing unit associated to it. The computing unit assists the robot with large computational tasks that ha

Jonas Lidal, Jeroen Danon

Superconductor--semiconductor hybrid devices are currently attracting much attention, fueled by the fact that strong spin--orbit interaction in combination with induced superconductivity can lead to exotic physics with potential applications in fault-tolerant quantum computation. The detailed nature of the spin dynamics in such systems is, however, often str

Berkay Neşeli, Hamza Kurt, Mirbek Turduev

With the discovery of self-accelerating beams, possibility of obtaining curved light beams in free space has been realized. These special beams paved the way for many new applications as well as the exploration of novel beam types. Recently, great research effort has been conducted to realize different types of curved beams such as photonic hook and airy bea

John Hughes

In this article I recommend a better point estimator for Krippendorff's Alpha agreement coefficient, and develop a jackknife variance estimator that leads to much better interval estimation than does the customary bootstrap procedure or an alternative bootstrap procedure. Having developed the new methodology, I analyze nominal data previously analyzed by Kri

Vera Serganova, Alexander Sherman

We present a general theorem which computes the cohomology of a homological vector field on global sections of vector bundles over smooth affine supervarieties. The hypotheses and results have the clear flavor of a localization theorem.

Shyam Murthy, Srinivas Vivek

Privacy preservation in Ride-Hailing Services (RHS) is intended to protect privacy of drivers and riders. pRide, published in IEEE Trans. Vehicular Technology 2021, is a prediction based privacy-preserving RHS protocol to match riders with an optimum driver. In the protocol, the Service Provider (SP) homomorphically computes Euclidean distances between encry

Ayaka Ishikawa, Hideaki Morita

We consider the generalized weighted zeta function for a finite digraph, and show that it has the Ihara expression, a determinant expression of graph zeta functions, with a certain specified definition for inverse arcs. A finite digraph in this paper allows multi-arcs or multi-loops.

Miroslav Mitev, Thuy M. Pham, Arsenia Chorti, Andre Noll Barreto

A large spectrum of technologies are collectively dubbed as physical layer security (PLS), ranging from wiretap coding, secret key generation (SKG), authentication using physical unclonable functions (PUFs), localization / RF fingerprinting, anomaly detection monitoring the physical layer (PHY) and hardware. Despite the fact that the fundamental limits of PL

Guoce Xin, Yue Zhou

It is well-known that the famous Selberg integral is equivalent to the Morris constant term identity. In 1998, Baker and Forrester conjectured a generalization of the $q$-Morris constant term identity. This conjecture was proved and extended by K\'{a}rolyi, Nagy, Petrov and Volkov in 2015. In this paper, we obtain two symmetric function generalizations of th

A. Loureiro, L. Whiteway, E. Sellentin, J. S. Lafaurie

We present a field-based signal extraction of weak lensing from noisy observations on the curved and masked sky. We test the analysis on a simulated Euclid-like survey, using a Euclid-like mask and noise level. To make optimal use of the information available in such a galaxy survey, we present a Bayesian method for inferring the angular power spectra of the

Knut Bjarte Haus, Gereon Quick

We construct a geometric cycle model for a Hodge filtered extension of complex cobordism for every smooth manifold with a filtration on its de Rham complex with complex coefficients. Using a refinement of the Pontryagin-Thom construction, we construct an explicit isomorphism between our geometric model and the abstract model of Hodge filtered complex cobordi

Ina Dormuth, Tiantian Liu, Jin Xu, Markus Pauly

Studies to compare the survival of two or more groups using time-to-event data are of high importance in medical research. The gold standard is the log-rank test, which is optimal under proportional hazards. As the latter is no simple regularity assumption, we are interested in evaluating the power of various statistical tests under different settings includ

Robert J. Ridgway, Maria Zamyatina, Nathan J. Mayne, James Manners

Stellar flares present challenges to the potential habitability of terrestrial planets orbiting M dwarf stars through inducing changes in the atmospheric composition and irradiating the planet's surface in large amounts of ultraviolet light. To examine their impact, we have coupled a general circulation model with a photochemical kinetics scheme to examine t

Misha Gromov

We prove the existence of locally distance increasing maps with it controllable small curvatures

Yuhang Gai, Jiwen Zhang, Dan Wu, Ken Chen

Traditional control methods of robotic peg-in-hole assembly rely on complex contact state analysis. Reinforcement learning (RL) is gradually becoming a preferred method of controlling robotic peg-in-hole assembly tasks. However, the training process of RL is quite time-consuming because RL methods are always globally connected, which means all state componen