November 2022 arXiv papers — page 164

Parag Gupta, Radostin D. Simitev, David MacTaggart

Magnetic helicity is a fundamental constraint in both ideal and resistive magnetohydrodynamics. Measurements of magnetic helicity density on the Sun and other stars are used to interpret the internal behaviour of the dynamo generating the global magnetic field. In this note, we study the behaviour of the global relative magnetic helicity in three self-consis

Anna Currey, Maria Nădejde, Raghavendra Pappagari, Mia Mayer

As generic machine translation (MT) quality has improved, the need for targeted benchmarks that explore fine-grained aspects of quality has increased. In particular, gender accuracy in translation can have implications in terms of output fluency, translation accuracy, and ethics. In this paper, we introduce MT-GenEval, a benchmark for evaluating gender accur

Md Tahmid Rahman Laskar, Cheng Chen, Xue-Yong Fu, Shashi Bhushan TN

Telephone transcription data can be very noisy due to speech recognition errors, disfluencies, etc. Not only that annotating such data is very challenging for the annotators, but also such data may have lots of annotation errors even after the annotation job is completed, resulting in a very poor model performance. In this paper, we present an active learnin

Guanghui Fu, Gabriel Jimenez, Sophie Loizillon, Rosana El Jurdi

Early and accurate diagnosis of parkinsonian syndromes is critical to provide appropriate care to patients and for inclusion in therapeutic trials. The red nucleus is a structure of the midbrain that plays an important role in these disorders. It can be visualized using iron-sensitive magnetic resonance imaging (MRI) sequences. Different iron-sensitive contr

Naiyuan J. Zhang, Yibang Wang, Kenji Watanabe, Takashi Taniguchi

Due to its potential connection with nematicity, electronic anisotropy has been the subject of intense research effort on a wide variety of material platforms. The emergence of spatial anisotropy not only offers a characterization of material properties of metallic phases, which cannot be accessed via conventional transport techniques, but it also provides a

M. Crespo-Ballesteros, A. B. Matsko, M. Sumetsky

The formation of optical frequency combs (OFCs) by the parametric modulation of optical microresonators is commonly described by lumped-parameter models. However, these models do not consider the actual spatial distribution of the parametric modulation (SDPM). Here, we show that the effect of the SDPM becomes of special importance for an elongated SNAP bottl

Richard T. Baillie, Francis X. Diebold, George Kapetanios, Kun Ho Kim

We suggest a new single-equation test for Uncovered Interest Parity (UIP) based on a dynamic regression approach. The method provides consistent and asymptotically efficient parameter estimates, and is not dependent on assumptions of strict exogeneity. This new approach is asymptotically more efficient than the common approach of using OLS with HAC robust st

Zikang Leng, Yash Jain, Hyeokhyen Kwon, Thomas Plötz

Previous work has demonstrated that virtual accelerometry data, extracted from videos using cross-modality transfer approaches like IMUTube, is beneficial for training complex and effective human activity recognition (HAR) models. Systems like IMUTube were originally designed to cover activities that are based on substantial body (part) movements. Yet, life

Konstantinos Klapsas, Karolos Nikitaras, Nikolaos Ellinas, June Sig Sung

A large part of the expressive speech synthesis literature focuses on learning prosodic representations of the speech signal which are then modeled by a prior distribution during inference. In this paper, we compare different prior architectures at the task of predicting phoneme level prosodic representations extracted with an unsupervised FVAE model. We use

Miel Sharf, Daniel Zelazo

We study cluster assignment in homogeneous diffusive multi-agent networks. Given the number of clusters and agents within each cluster, we design the network graph ensuring the system will converge to the prescribed cluster configuration. Using recent results linking clustering and symmetries, we show that it is possible to design an oriented graph for which

Joel Grodstein, Michael Levin

Morphogenesis, the establishment and repair of emergent complex anatomy by groups of cells, is a fascinating and biomedically-relevant problem. One of its most fascinating aspects is that a developing embryo can reliably recover from disturbances, such as splitting into twins. While this reliability implies some type of goal-seeking error minimization over a

Kai Huang, Mingfei Cheng, Yang Wang, Bochen Wang

Few-shot segmentation (FSS) aims to segment objects of unseen classes given only a few annotated support images. Most existing methods simply stitch query features with independent support prototypes and segment the query image by feeding the mixed features to a decoder. Although significant improvements have been achieved, existing methods are still face cl

Bhavani Shankar M. R., Kumar Vijay Mishra, Mohammad Alaee-Kerahroodi

The previous chapters have discussed the canvas of joint radar-communications (JRC), highlighting the key approaches of radar-centric, communications-centric and dual-function radar-communications systems. Several signal processing and related aspects enabling these approaches including waveform design, resource allocation, privacy and security, and intellig

David D. K. Chow

We examine properties of the Concrete (or Gumbel-softmax) distribution on the simplex. Using the natural vector space structure of the simplex, the Concrete distribution can be regarded as a transformation of the uniform distribution through a reflection and a location-scale transformation. The Fisher information is computed and the corresponding information

Yu. S. Orlov, S. V. Nikolaev, S. G. Ovchinnikov

Ultrafast quantum dynamics relaxation of a photoexcited state in a strongly correlated spin crossover system LaCoO3 under a sudden perturbation is considered with the density matrix generalized master equation. The magnetization and cobalt-oxygen bond length oscillations were found. The evolution of the electronic band structure during relaxation is calculat

Miel Sharf, Bart Besselink, Karl Henrik Johansson

Designing large-scale control systems to satisfy complex specifications is hard in practice, as most formal methods are limited to systems of modest size. Contract theory has been proposed as a modular alternative to formal methods in control, in which specifications are defined by assumptions on the input to a component and guarantees on its output. However

Kumar Vijay Mishra, Ahmet M. Elbir, Amir I. Zaghloul

Metasurfaces (MTSs) are increasingly emerging as enabling technologies to meet the demands for multi-functional, small form-factor, efficient, reconfigurable, tunable, and low-cost radio-frequency (RF) components because of their ability to manipulate waves in a sub-wavelength thickness through modified boundary conditions. They enable the design of reconfig

Luca Banetta, Francesco Leone, Carmine Anzivino, Michael S. Murillo

We present a theoretical framework to investigate the microscopic structure of concentrated hard-sphere colloidal suspensions under strong shear flows by fully taking into account the boundary-layer structure of convective diffusion. We solve the pair Smoluchowski equation with shear separately in the compressing and extensional sectors of the solid angle, b

Alessandra Feo, Emanuele Scanferla, Fulvio Celico

The contamination impact and the migration of the contaminant into the surrounding environment due to the presence of a spilled oil pipeline will cause significant damage to the natural ecosystem. For this reason, it is decisive to develop a rapid response strategy that might include accurate predictions of oil migration trajectories from numerical simulatio

Fabio Giovanneschi, Kumar Vijay Mishra, Maria Antonia Gonzalez-Huici

Traditional GPR target recognition methods include pre-processing the data by removal of noisy signatures, dewowing (high-pass filtering to remove low-frequency noise), filtering, deconvolution, migration (correction of the effect of survey geometry), and can rely on the simulation of GPR responses. The techniques usually suffer from the loss of information,

Jonathan Minz, Axel Kleidon, Nsilulu T. Mbungu, Lee M. Miller

Energy scenarios and transition pathways need estimates of technical wind energy potentials. However, the standard policy-side approach uses observed wind speeds, thereby neglecting the effects of kinetic energy (KE) removal by the wind turbines that depletes the regional wind resource, lowers wind speeds, and reduces capacity factors. The standard approach

A. Lamura

The dynamical response of a tethered semiflexible polymer with self-attractive interactions and subjected to an external force field is numerically investigated by varying stiffness and self-interaction strength. The chain is confined in two spatial dimensions and placed in contact with a heat bath described by the Brownian multiparticle collision method. Fo

Ignacio Magaña Hernandez

Alternative theories of gravity predict up to six distinct polarization modes for gravitational waves. Strong gravitational lensing of gravitational waves allows us to probe the polarization content of these signals by effectively increasing the number of observations from the same astrophysical source. The lensing time delays due to the multiple observed le

Yujie Qian, Jinhyuk Lee, Sai Meher Karthik Duddu, Zhuyun Dai

Multi-vector retrieval models improve over single-vector dual encoders on many information retrieval tasks. In this paper, we cast the multi-vector retrieval problem as sparse alignment between query and document tokens. We propose AligneR, a novel multi-vector retrieval model that learns sparsified pairwise alignments between query and document tokens (e.g.

Peng Zhang, Yawen Huang, Bingzhang Hu, Shizheng Wang

Reinforcement Learning (RL)-based control system has received considerable attention in recent decades. However, in many real-world problems, such as Batch Process Control, the environment is uncertain, which requires expensive interaction to acquire the state and reward values. In this paper, we present a cost-efficient framework, such that the RL model can

Daniel Goodair, Dan Crisan

We prove the existence and uniqueness of maximal solutions to the 3D SALT (Stochastic Advection by Lie Transport, [Holm arXiv:1410.8311]) Navier-Stokes Equation in velocity and vorticity form, on the torus and the bounded domain respectively. The current work partners the paper [Goodair et al, arXiv:2209.09137] as an application of the abstract framework pre

Z. Z. Li, Y. F. Niu, G. Colò

"Why is the EoS for tin so soft?" is a longstanding question, which prevents us from determining the nuclear incompressibility $K_\infty$ accurately. To solve this puzzle, a fully self-consistent quasiparticle random phase approximation (QRPA) plus quasiparticle-vibration coupling (QPVC) approach based on Skyrme-Hartree-Fock-Bogoliubov is developed.

Esther López, Irene Artacho, Alejandro Datas

A standardized method for measuring thermophotovoltaic (TPV) efficiency has not been yet established, which makes the reported results difficult to compare. Besides, most of the TPV efficiencies reported to date have been obtained using small view factors, i.e., large cell-to-emitter distances, so the impact of the series resistance is usually underestimated

Tobias Schnabel

Various studies in recent years have pointed out large issues in the offline evaluation of recommender systems, making it difficult to assess whether true progress has been made. However, there has been little research into what set of practices should serve as a starting point during experimentation. In this paper, we examine four larger issues in recommend

Lutz Rapp

Existing unrepeatered submarine links are increasingly upgraded to the most advanced modulation format currently available for commercial applications. Quite often the use of third-order codirectional Raman amplifiers is necessary. Power fluctuations of the involved high-power pump induces phase shifts in phase modulated signals via the nonlinear Kerr effect

Mohsin Bilal, Robert Jewsbury, Ruoyu Wang, Hammam M. AlGhamdi

Image analysis and machine learning algorithms operating on multi-gigapixel whole-slide images (WSIs) often process a large number of tiles (sub-images) and require aggregating predictions from the tiles in order to predict WSI-level labels. In this paper, we present a review of existing literature on various types of aggregation methods with a view to help

Dingzhu Wen, Xiang Jiao, Peixi Liu, Guangxu Zhu

Departing from the classic paradigm of data-centric designs, the 6G networks for supporting edge AI features task-oriented techniques that focus on effective and efficient execution of AI task. Targeting end-to-end system performance, such techniques are sophisticated as they aim to seamlessly integrate sensing (data acquisition), communication (data transmi

Ethan H. Nguyen, Haichun Yang, Zuhayr Asad, Ruining Deng

Circle representation has recently been introduced as a medical imaging optimized representation for more effective instance object detection on ball-shaped medical objects. With its superior performance on instance detection, it is appealing to extend the circle representation to instance medical object segmentation. In this work, we propose CircleSnake, a

Yi Zhang, Jitao Sang, Junyang Wang

Deep learning models often learn to make predictions that rely on sensitive social attributes like gender and race, which poses significant fairness risks, especially in societal applications, e.g., hiring, banking, and criminal justice. Existing work tackles this issue by minimizing information about social attributes in models for debiasing. However, the h

Sihao Huang, Alexander F. Siegenfeld, Andrew Gelman

Democracies employ elections at various scales to select officials at the corresponding levels of administration. The geographical distribution of political opinion, the policy issues delegated to each level, and the multilevel interactions between elections can all greatly impact the makeup of these representative bodies. This perspective is not new: the ad

Leonardo Nagami Coregliano, Fernando Granha Jeronimo, Chris Jones

Determining the maximum size $A_2(n,d)$ of a binary code of blocklength $n$ and distance $d$ remains an elusive open question even when restricted to the important class of linear codes. Recently, two linear programming hierarchies extending Delsarte's LP were independently proposed to upper bound $A_2^{\text{Lin}}(n,d)$ (the analogue of $A_2(n,d)$ for l

Peipei Tang, Bo Jiang, Chengjing Wang

Given a dissimilarity matrix, the metric nearness problem is to find the nearest matrix of distances that satisfy the triangle inequalities. This problem has wide applications, such as sensor networks, image processing, and so on. But it is of great challenge even to obtain a moderately accurate solution due to the $O(n^{3})$ metric constraints and the nonsm

George Samartzis, Nikitas Pittis

We study the necessary and sufficient conditions under which the Mean-Variance Criterion (MVC) is equivalent to the Maximum Expected Utility Criterion (MEUC), for two lotteries. Based on Chamberlain (1983), we conclude that the MVC is equivalent to the Second-order Stochastic Dominance Rule (SSDR) under any symmetric Elliptical distribution. We then discuss

Marcus Riesmeier, Frank Woittennek

Late-lumping feedback design for infinite-dimensional linear systems with unbounded input operators is considered. The proposed scheme is suitable for the approximation of backstepping and flatness-based designs and relies on a decomposition of the feedback into a bounded and an unbounded part. Approximation applies to the bounded part only, while the unboun

Kosio Beshkov, Jonas Verhellen, Mikkel Elle Lepperød

Artificial and biological agents cannon learn given completely random and unstructured data. The structure of data is encoded in the metric relationships between data points. In the context of neural networks, neuronal activity within a layer forms a representation reflecting the transformation that the layer implements on its inputs. In order to utilize the

Panu Lahti

In a complete metric space equipped with a doubling measure and supporting a $(1,1)$-Poincaré inequality, we show that every set satisfying a suitable capacitary density condition is removable for Newton-Sobolev functions.

Mattie Tesfaldet, Derek Nowrouzezahrai, Christopher Pal

Recent extensions of Cellular Automata (CA) have incorporated key ideas from modern deep learning, dramatically extending their capabilities and catalyzing a new family of Neural Cellular Automata (NCA) techniques. Inspired by Transformer-based architectures, our work presents a new class of $\textit{attention-based}$ NCAs formed using a spatially localized$

Ruming Zhang

The perfectly matched layer (PML) is a very popular tool in the truncation of wave scattering in unbounded domains. In Chandler-Wilde & Monk et al. 2009, the author proposed a conjecture that for scattering problems with rough surfaces, the PML converges exponentially with respect to the PML parameter in any compact subset. In the author's previous paper

Yizhou Zhao, Hua Sun

A collection of $K$ random variables are called $(K,n)$-MDS if any $n$ of the $K$ variables are independent and determine all remaining variables. In the MDS variable generation problem, $K$ users wish to generate variables that are $(K,n)$-MDS using a randomness variable owned by each user. We show that to generate $1$ bit of $(K,n)$-MDS variables for each

Qinfeng Li, Changyou Wang

Let $μ>0$ be a fixed constant, and we prove that minimizers to the following energy functional \begin{align*} E_f(u,Ω):=\int_Ω|\nabla u|^2+μP(Ω) \end{align*}exist among pairs $(Ω,u)$ such that $Ω$ is an $M$-uniform domain with finite perimeter and fixed volume, and $u \in H^1(Ω,\mathbb{S}^2)$ with $u =ν_Ω$, the measure-theoretical outer unit normal, almost e

Pavel Kuriščák, Pedro Rossa, Horácio Fernandes, João Nuno Silva

Remote Controlled laboratories is a teaching and learning tool that increasingly becomes fundamental in the teaching and learning processes at all the levels. A study of available systems highlights a series of limitations on the used programming languages, overall architecture and network communication patterns that, that hinder these systems to be further

T. Lévèque, C. Fallet, J. Lefebve, A. Piquereau

A strong potential gain for space applications is expected from the anticipated performances of inertial sensors based on cold atom interferometry (CAI) that measure the acceleration of freely falling independent atoms by manipulating them with laser light. In this context, CNES and its partners initiated a phase 0 study, called CARIOQA, in order to develop

Hayoung Seong, Junseon Kim, Won-Yong Shin, Howon Lee

Massive Internet of Things (IoT) networks have a wide range of applications, including but not limited to the rapid delivery of emergency and disaster messages. Although various benchmark algorithms have been developed to date for message delivery in such applications, they pose several practical challenges such as insufficient network coverage and/or highly

Mikhail Danilov

There are several experimental indications of sterile neutrinos with a mass in the 1 eV ballpark and many experiments are trying to clarify the situation. During 6 years the DANSS experiment collected more than 6 million Inverse Beta Decay (IBD) events and measured the background level during 4 reactor-off periods. Data were collected at 3 distances (10.9 m,

Zhiyong Su, Chao Chu, Long Chen, Yong Li

Objective geometry quality assessment of point clouds is essential to evaluate the performance of a wide range of point cloud-based solutions, such as denoising, simplification, reconstruction, and watermarking. Existing point cloud quality assessment (PCQA) methods dedicate to assigning absolute quality scores to distorted point clouds. Their performance is

Johannes Voigt, Holger Jäkel, Laurent Schmalen

Recursive projection aggregation (RPA) decoding as introduced in [1] is a novel decoding algorithm which performs close to the maximum likelihood decoder for short-length Reed-Muller codes. Recently, an extension to RPA decoding, called sparse multi-decoder RPA (SRPA), has been proposed [2]. The SRPA approach makes use of multiple pruned RPA decoders to lowe

Mingqi Li, Fei Ding, Dan Zhang, Long Cheng

Pre-trained multilingual language models play an important role in cross-lingual natural language understanding tasks. However, existing methods did not focus on learning the semantic structure of representation, and thus could not optimize their performance. In this paper, we propose Multi-level Multilingual Knowledge Distillation (MMKD), a novel method for

Takuya Fujimura, Tomoki Toda

Deep neural network (DNN)-based speech enhancement usually uses a clean speech as a training target. However, it is hard to collect large amounts of clean speech because the recording is very costly. In other words, the performance of current speech enhancement has been limited by the amount of training data. To relax this limitation, Noisy-target Training (

Xu Zhang, Donghai Ji

The Umehara algebra is studied with motivation on the problem of the non-existence of common complex submanifolds. In this paper, we prove some new results in Umehara algebra and obtain some applications. In particular, if a complex manifolds admits a holomorphic polynomial isometric immersion to one indefinite complex space form, then it cannot admits a hol

Dominic T. Meiers, Maximilian Rothammer, Maximilian Maier, Cordt Zollfrank

The great flexibility of direct laser writing arises from the possibility to fabricate precise three-dimensional structures on very small scales as well as the broad range of applicable materials. However, there is still a vast number of promising materials which are currently inaccessible requiring the continuous development of novel photoresists. Here, a n

Alberto Quintana, Abigail A. Firme, Christopher J. Jensen, Dongxing Zheng

Magneto-ionics has emerged as a promising approach to manipulate magnetic properties, not only by drastically reducing power consumption associated with electric current based devices but also by enabling novel functionalities. To date, magneto-ionics have been mostly explored in oxygen-based systems, while there is a surge of interests in alternative ionic

Tsun-An Hsieh, Chao-Han Huck Yang, Pin-Yu Chen, Sabato Marco Siniscalchi

This study addresses the speech enhancement (SE) task within the causal inference paradigm by modeling the noise presence as an intervention. Based on the potential outcome framework, the proposed causal inference-based speech enhancement (CISE) separates clean and noisy frames in an intervened noisy speech using a noise detector and assigns both sets of fra

Ying Hu, Remi Moreau, Falei Wang

The present paper is devoted to the study of backward stochastic differential equations with mean reflection formulated by Briand et al. [7]. We investigate the solvability of a generalized mean reflected BSDE, whose driver also depends on the distribution of the solution term $Y$. Using a fixed-point argument, BMO martingale theory and the $θ$-method, we es

Alessandro Torrielli

This is the extended write-up of a series of lectures on the duality between the Sine-Gordon model and the Thirring model. Prepared for the London Theory Institute (LonTI) - Fall 2022: a PhD-level mini-course, with exercises and a guide to the literature.

Ali Behravan, Vijaya Yajnanarayana, Musa Furkan Keskin, Hui Chen

Among the key differentiators of 6G compared to 5G will be the increased emphasis on radio based positioning and sensing. These will be utilized not only for conventional location-aware services and for enhancing communication performance, but also to support new use case families with extreme performance requirements. This paper presents a unified vision fr

Amira Guesmi, Ihsen Alouani, Khaled N. Khasawneh, Mouna Baklouti

Machine-learning architectures, such as Convolutional Neural Networks (CNNs) are vulnerable to adversarial attacks: inputs crafted carefully to force the system output to a wrong label. Since machine-learning is being deployed in safety-critical and security-sensitive domains, such attacks may have catastrophic security and safety consequences. In this paper

Caleb M. H. Camrud, Timothy H. McNicholl

Within the framework of computable infinitary continuous logic, we develop a system of hyperarithmetic numerals. These numerals are infinitary sentences in a metric language $L$ that have the same truth value in every interpretation of $L$. We prove that every hyperarithmetic real can be represented by a hyperarithmetic numeral at the same level of complexit

Michal Edelstein, Hila Peleg, Shachar Itzhaky, Mirela Ben-Chen

We propose an approach for generating crochet instructions (patterns) from an input 3D model. We focus on Amigurumi, which are knitted stuffed toys. Given a closed triangle mesh, and a single point specified by the user, we generate crochet instructions, which when knitted and stuffed result in a toy similar to the input geometry. Our approach relies on cons

Lukas Gehring

This article is about the convex solution $u$ of the Monge--Ampère equation on an at least 2-dimensional open bounded convex domain with Dirichlet boundary data and nonnegative bounded right-hand side. For convex functions with zero boundary data, an Alexandrov maximum principle $|u(x)| \leq C \operatorname{dist}(x,\partialΩ)^α$ is equivalent to (uniform) Hö

Simon-Christian Klein, Philipp Öffner

In this paper, we propose a novel development in the context of entropy stable finite-volume/finite-difference schemes. In the first part, we focus on the construction of high-order entropy conservative fluxes. Already in [LMR2002], the authors have generalized the second order accurate entropy conservative numerical fluxes proposed by Tadmor to high-order (

MohammadJavad Salehi, Mohammad NaseriTehrani, Antti Tölli

Coded caching (CC) techniques have been shown to be conveniently applicable in multi-input multi-output (MIMO) systems. In a $K$-user network with spatial multiplexing gains of $L$ at the transmitter and $G$ at every receiver, if each user can cache a fraction $γ$ of the file library, a total number of $GKγ+ L$ data streams can be served in parallel. In this

Weiyao Wang, Byung-Hak Kim, Varun Ganapathi

Recent advances in self-supervised learning (SSL) using large models to learn visual representations from natural images are rapidly closing the gap between the results produced by fully supervised learning and those produced by SSL on downstream vision tasks. Inspired by this advancement and primarily motivated by the emergence of tabular and structured doc

Jan Tóth, Ondřej Kuželka

We consider the task of weighted first-order model counting (WFOMC) used for probabilistic inference in the area of statistical relational learning. Given a formula $ϕ$, domain size $n$ and a pair of weight functions, what is the weighted sum of all models of $ϕ$ over a domain of size $n$? It was shown that computing WFOMC of any logical sentence with at mos

Runze Li, Faguang Yan, Yongcheng Deng, Yu Sheng

Rapid electron transport in the quantum well triggers many novel physical phenomena and becomes a critical point for the high-speed electronics. Here, we found electrical properties of the titanium oxide changed from semiconducting to metallic as the degree of oxidation decreased and Schottky quantum well was formed at the interface. We take the asymmetry in

B. Paroli, G. Martini, M. A. C. Potenza, M. Siano

Among several approaches to tackle the problem of energy consumption in modern computing systems, two solutions are currently investigated: one consists of artificial neural networks (ANNs) based on photonic technologies, the other is a different paradigm compared to ANNs and it is based on random networks of nonlinear nanoscale junctions resulting from the

Satu I. Inkinen, Mikael A. K. Brix, Miika T. Nieminen, Simon Arridge

Multi-energy computed tomography (CT) with photon counting detectors (PCDs) enables spectral imaging as PCDs can assign the incoming photons to specific energy channels. However, PCDs with many spectral channels drastically increase the computational complexity of the CT reconstruction, and bespoke reconstruction algorithms need fine-tuning to varying noise

Francesco Finazzi, Frank Yannick Massoda Tchoussi

Smartphone-based earthquake early warning systems implemented by citizen science initiatives are characterized by a significant variability in their smartphone network geometry. This has an direct impact on the earthquake detection capability and performance of the system. Here, a simulation framework based on the Monte Carlo method is implemented for making

Tian Chong, Yuxin Dong, Guilin Yang

In this paper, we investigate the stability problem of subelliptic harmonic maps with potential. First, we derive the first and second variation formulas for subelliptic harmonic maps with potential. As a result, it is proved that a subelliptic harmonic map with potential is stable if the target manifold has nonpositive curvature and the Hessian of the poten

Yakini Tchouka, Jean-François Couchot, David Laiymani

Unstructured textual data is at the heart of healthcare systems. For obvious privacy reasons, these documents are not accessible to researchers as long as they contain personally identifiable information. One way to share this data while respecting the legislative framework (notably GDPR or HIPAA) is, within the medical structures, to de-identify it, i.e. to

Zheng Li, Mauricio Pradena Miquel, Pedro Pinacho-Davidson

Despite the fact that outside is becoming the frontier of indoor workplaces, a large amount of real-world work like road construction has to be done by outdoor human activities in open areas. Given the promise of the smart workplace in various aspects including productivity and safety, we decided to employ smart workplace technologies for a collaborative out

Yongzhi Su, Yan Di, Fabian Manhardt, Guangyao Zhai

Despite monocular 3D object detection having recently made a significant leap forward thanks to the use of pre-trained depth estimators for pseudo-LiDAR recovery, such two-stage methods typically suffer from overfitting and are incapable of explicitly encapsulating the geometric relation between depth and object bounding box. To overcome this limitation, we

Gennady Eremin

Dyck paths are among the most heavily studied Catalan families. This paper is a continuation of [2]. In the paper we are dealing with the numbering of Dyck paths, the terms of the OEIS sequence A036991 or Dyck numbers. We consider triplets of terms of the form (t-4, t-2, t) (t is the senior term); triplets cover 80% of A036991. Triplets include all Mersenne

Yulu Tian, Deng-Shan Wang, Liang Zhao

In this paper, we study the existence of ground state solutions to the following p-Laplacian equation in some dimension $N\geq3$ with an $L^2$ constraint: \begin{equation*} \begin{cases} -Δ_{p}u+{\vert u\vert}^{p-2}u=f(u)-μu \quad \text{ in } \mathbb{R}^N,\\ {\Vert u\Vert}^2_{L^2(\mathbb{R}^N)}=m,\\ u\in W^{1,p}(\mathbb{R}^N)\cap L^2(\mathbb{R}^N), \end{case

Alberto Ceria, Huijuan Wang

Human social interactions are typically recorded as time-specific dyadic interactions, and represented as evolving (temporal) networks, where links are activated/deactivated over time. However, individuals can interact in groups of more than two people. Such group interactions can be represented as higher-order events of an evolving network. Here, we propose

Kevin Ginsburger

Due to the limitation of available labeled data, medical image segmentation is a challenging task for deep learning. Traditional data augmentation techniques have been shown to improve segmentation network performances by optimizing the usage of few training examples. However, current augmentation approaches for segmentation do not tackle the strong texture

Xiang Zhang

We show that every codimension one partially hyperbolic diffeomorphism must support on $\mathbb{T}^{n}$. It is locally uniquely integrable and derived from a linear codimension one Anosov diffeomorphism. Moreover, this system is intrinsically ergodic, and the A. Katok's conjecture about the existence of ergodic measures with intermediate entropies holds

Pritam Ranjan, Joseph Resch, Abhyuday Mandal

Computer simulators are often used as a substitute of complex real-life phenomena which are either expensive or infeasible to experiment with. This paper focuses on how to efficiently solve the inverse problem for an expensive to evaluate time series valued computer simulator. The research is motivated by a hydrological simulator which has to be tuned for ge

Paolo Giordano, Lorenzo Luperi Baglini

We prove that Picard-Lindelöf iterations for an arbitrary smooth normal Cauchy problem for PDE converge if we assume a suitable Weissinger-like sufficient condition. This condition includes both a large class of non-analytic PDE or initial conditions, and more classical real analytic functions. The proof is based on a Banach fixed point theorem for contracti

Yujie Wu, Sharon Curhan, Bernard Rosner, Gary Curhan

Epidemiologic and medical studies often rely on evaluators to obtain measurements of exposures or outcomes for study participants, and valid estimates of associations depends on the quality of data. Even though statistical methods have been proposed to adjust for measurement errors, they often rely on unverifiable assumptions and could lead to biased estimat

Berend Ringeling

For a prime $p$ larger than $7$, the Eisenstein series of weight $p-1$ has some remarkable congruence properties modulo $p$. Those imply, for example, that the $j$-invariants of its zeros (which are known to be real algebraic numbers in the interval $[0,1728]$), are at most quadratic over the field with $p$ elements and are congruent modulo $p$ to the zeros

Enrico Del Re, Cristina Olaverri-Monreal

Understanding human driving behavior is crucial to develop autonomous vehicles' algorithms. However, most low level automation, such as the one in advanced driving assistance systems (ADAS), is based on objective safety measures, which are not always aligned with what the drivers perceive as safe and their correspondent driving behavior. Finding the brid

Ziad El Jamous, Kemal Davaslioglu, Yalin E. Sagduyu

This paper presents a deep reinforcement learning (DRL) solution for power control in wireless communications, describes its embedded implementation with WiFi transceivers for a WiFi network system, and evaluates the performance with high-fidelity emulation tests. In a multi-hop wireless network, each mobile node measures its link quality and signal strength

Ricardo Guerrero, Christoph Lattemann, Simon Michalke, Dominik Siemon

Personal services can be found in sectors such as education, retail, hospitality, and craftsmanship. As of today, personal service firms lack the know-how and experience on how to implement processes and practices to effectively build digital business ecosystems. This becomes an obstacle for these kinds of firms to overcome the challenges of todays digital a

Hugo Roussille

The recent first detection of gravitational waves (GWs) from binary black hole mergers has spurred a renewed interest in possible deviations from General Relativity (GR), since they could be detected in the GWs emitted by such systems. Of particular interest is the ringdown phase of a binary black hole merger, which can be described by linear perturbations a

Carol Mak, Fabian Zaiser, Luke Ong

A challenging problem in probabilistic programming is to develop inference algorithms that work for arbitrary programs in a universal probabilistic programming language (PPL). We present the nonparametric involutive Markov chain Monte Carlo (NP-iMCMC) algorithm as a method for constructing MCMC inference algorithms for nonparametric models expressible in uni

Gabriel S. Gama, Nícolas S. Rosa, Valdir Grassi

Several SLAM methods benefit from the use of semantic information. Most integrate photometric methods with high-level semantics such as object detection and semantic segmentation. We propose that adding a semantic segmentation decoder in a shared encoder architecture would help the descriptor decoder learn semantic information, improving the feature extracto

Jinali Zhang, Yinpeng Dong, Jun Zhu, Jihong Zhu

Previous work has shown that 3D point cloud classifiers can be vulnerable to adversarial examples. However, most of the existing methods are aimed at white-box attacks, where the parameters and other information of the classifiers are known in the attack, which is unrealistic for real-world applications. In order to improve the attack performance of the blac

Kong Aik Lee, Tomi Kinnunen, Daniele Colibro, Claudio Vair

This manuscript describes the I4U submission to the 2020 NIST Speaker Recognition Evaluation (SRE'20) Conversational Telephone Speech (CTS) Challenge. The I4U's submission was resulted from active collaboration among researchers across eight research teams - I$^2$R (Singapore), UEF (Finland), VALPT (Italy, Spain), NEC (Japan), THUEE (China), LIA (Fra

Jan Švec, Luboš Šmídl, Jan Lehečka

The paper presents a method for spoken term detection based on the Transformer architecture. We propose the encoder-encoder architecture employing two BERT-like encoders with additional modifications, including convolutional and upsampling layers, attention masking, and shared parameters. The encoders project a recognized hypothesis and a searched term into

Chinmoy Nath Saha, Abhishek Vaidya, A F M Anhar Uddin Bhuiyan, Lingyu Meng

This letter reports high-performance $\mathrmβ Ga2O3 thin channel MOSFETs with T-gate and degenerately doped source/drain contacts regrown by MOCVD. Gate length scaling (LG= 160-200 nm) leads to a peak drain current (ID,MAX) of 285 mA/mm and peak trans-conductance (gm) of 52 mS/mm at 10 V drain bias with 23.5 Ohm mm on resistance (Ron). A low metal/n+ contac

Dirren van Vlijmen, Alex Kolmus, Zhuoran Liu, Zhengyu Zhao

We introduce ShortcutGen, a new data poisoning attack that generates sample-dependent, error-minimizing perturbations by learning a generator. The key novelty of ShortcutGen is the use of a randomly-initialized discriminator, which provides spurious shortcuts needed for generating poisons. Different from recent, iterative methods, our ShortcutGen can generat

Gaoyuan Cheng, Jie Xu

This paper studies a multi-antenna network integrated sensing and communication (ISAC) system, in which a set of multi-antenna base stations (BSs) employ the coordinated transmit beamforming to serve their respectively associated single-antenna communication users (CUs), and at the same time reuse the reflected information signals to perform joint target det

Guillaume Bagan, Quentin Deschamps, Eric Duchêne, Bastien Durain

Positional games have been introduced by Hales and Jewett in 1963 and have been extensively investigated in the literature since then. These games are played on a hypergraph where two players alternately select an unclaimed vertex of it. In the Maker-Breaker convention, if Maker manages to fully take a hyperedge, she wins, otherwise, Breaker is the winner. I

Lina Chen, Shicheng Xu

The volume entropy of a compact metric measure space is known to be the exponential growth rate of the measure lifted to its universal cover at infinity. For a compact Riemannian $n$-manifold with a negative lower Ricci curvature bound and a upper diameter bound, it was known that it admits an almost maximal volume entropy if and only if it is diffeomorphic

Adrian Muntean

Having in mind as target audience beginner researchers working in the field of cultural heritage, we present succinctly the concept of two-scale modeling of reaction-diffusion problems as it fits to scenarios where the action of the carbonation reaction is relevant. We briefly review well-known contributions concerning multiscale concrete carbonation process