August 2022 arXiv papers — page 27

Yujia Yang, Ye Wang, Chris Manzie, Ye Pu

The application of distributed model predictive controllers (DMPC) for multi-agent systems (MASs) necessitates communication between agents, yet the consequence of communication data rates is typically overlooked. This work focuses on developing stability-guaranteed control methods for MASs with limited data rates. Initially, a distributed optimization algor

Vinod Ganesan, Anwesh Bhattacharya, Pratyush Kumar, Divya Gupta

ML-as-a-service continues to grow, and so does the need for very strong privacy guarantees. Secure inference has emerged as a potential solution, wherein cryptographic primitives allow inference without revealing users' inputs to a model provider or model's weights to a user. For instance, the model provider could be a diagnostics company that has trained a

Sojung Kim, Marcel Kleiber, Stefan Weber

The paper develops a methodology to enable microscopic models of transportation systems to be accessible for a statistical study of traffic accidents. Our approach is intended to permit an understanding not only of historical losses, but also of incidents that may occur in altered, potential future systems. Through such a counterfactual analysis, it is possi

Shu-guang Cheng, Yijia Wu, Hua Jiang, Qing-Feng Sun

The static topological fractional charge (TFC) in condensed matter systems is related to the band topology and thus has potential applications in topological quantum computation. However, the experimental measurement of these TFCs in electronic systems is quite challenging. We propose an electronic transport measurement scheme that both the charge amount and

Ken Furukawa

In this paper, we show mathematical justification of the data assimilation of nudging type in $L^p$-$L^q$ maximal regularity settings. We prove that the approximate solution of the primitive equations by data assimilation converges to the true solution with exponential order on the Besov space $B^{2/q}_{q,p}(\Omega)$ in the periodic layer domain $\Omega = \m

Jiaming Liu, Qizhe Zhang, Xiaoqi Li, Jianing Li

Neuromorphic spike data, an upcoming modality with high temporal resolution, has shown promising potential in autonomous driving by mitigating the challenges posed by high-velocity motion blur. However, training the spike depth estimation network holds significant challenges in two aspects: sparse spatial information for pixel-wise tasks and difficulties in

Yabing Wang, Jianfeng Dong, Tianxiang Liang, Minsong Zhang

Despite the recent developments in the field of cross-modal retrieval, there has been less research focusing on low-resource languages due to the lack of manually annotated datasets. In this paper, we propose a noise-robust cross-lingual cross-modal retrieval method for low-resource languages. To this end, we use Machine Translation (MT) to construct pseudo-

Hlynur Davíð Hlynsson

Although deep reinforcement learning (RL) has recently enjoyed many successes, its methods are still data inefficient, which makes solving numerous problems prohibitively expensive in terms of data. We aim to remedy this by taking advantage of the rich supervisory signal in unlabeled data for learning state representations. This thesis introduces three diffe

Jin-Feng Huang, Lin Tian

The Dicke model can exhibit quantum phase transition between the normal and the superradiant phases when the strength of the light-matter coupling exceeds the ultrastrong coupling regime. However, it is challenging to observe this phase transition in practical systems due to limited coupling strength or finite two-photon $A^{2}$ terms. Here we show that by a

Martin Glauer, Robert West, Susan Michie, Janna Hastings

We describe a novel approach to explainable prediction of a continuous variable based on learning fuzzy weighted rules. Our model trains a set of weighted rules to maximise prediction accuracy and minimise an ontology-based 'semantic loss' function including user-specified constraints on the rules that should be learned in order to maximise the explainabilit

Mingyu Mo, Qi Ye

In this paper, we study the splitting method based on alternating direction method of multipliers for support vector machine in reproducing kernel Hilbert space with lower semi-continuous loss function. If the loss function is lower semi-continuous and subanalytic, we use the Kurdyka-Lojasiewicz inequality to show that the iterative sequence induced by the s

Jan Grygar, Josef Hloušek, Jaromír Fiurášek, Miroslav Ježek

We report on direct experimental certification of the quantum non-Gaussian character of a photon-number resolving detector. The certification protocol is based on an adaptation of the existing quantum non-Gaussianity criteria for quantum states to quantum measurements. In our approach, it suffices to probe the detector with a vacuum state and two different t

Mohamed Maghenem, Diana Karaki

A dynamical system is strongly robustly safe provided that it remains safe in the presence of a continuous and positive perturbation, named robustness margin, added to both the argument and the image of the right-hand side (the dynamics). Therefore, in comparison with existing robust-safety notions, where the continuous and positive perturbation is added onl

Yutaka Hashimoto, Akihito Soeda, Mio Murao

Comparison of quantum objects is a task to determine whether two unknown quantum objects are the same or different. It is one of the most basic information processing tasks for learning property of quantum objects, and comparison of quantum states, quantum channels, and quantum measurements have been investigated. In general, repeated uses of quantum objects

Lech A. Grzelak

The class of Affine (Jump) Diffusion (AD) has, due to its closed form characteristic function (ChF), gained tremendous popularity among practitioners and researchers. However, there is clear evidence that a linearity constraint is insufficient for precise and consistent option pricing. Any non-affine model must pass the strict requirement of quick calibratio

Huixu Dong, Yue Feng, Chen Qiu, Ye Pan

We propose a parallel massage robot with compliant joints based on the series elastic actuator (SEA), offering a unified force-position control approach. First, the kinematic and static force models are established for obtaining the corresponding control variables. Then, a novel force-position control strategy is proposed to separately control the force-posi

Víctor Zapatero, Wenyuan Wang, Marcos Curty

A passive quantum key distribution (QKD) transmitter generates the quantum states prescribed by a QKD protocol at random, combining a fixed quantum mechanism and a post-selection step. By avoiding the use of active optical modulators externally driven by random number generators, passive QKD transmitters offer immunity to modulator side channels and potentia

Andreas Besginow, Markus Lange-Hegermann

Data in many applications follows systems of Ordinary Differential Equations (ODEs). This paper presents a novel algorithmic and symbolic construction for covariance functions of Gaussian Processes (GPs) with realizations strictly following a system of linear homogeneous ODEs with constant coefficients, which we call LODE-GPs. Introducing this strong inducti

Wazha German, Dr Jacobus Diener

Neutron stars provide unique conditions to study cold dense nuclear matter at extreme densities. Due to these extreme conditions additional hadronic degrees of freedom are expected to be populated,including hyperons. This talk will focus on the influence of hyperons on the neutron star equation ofstate. In particular the contribution of the lambda hyperon wi

Vincent Gaudillière, Gilles Simon, Marie-Odile Berger

In computer vision, camera pose estimation from correspondences between 3D geometric entities and their projections into the image has been a widely investigated problem. Although most state-of-the-art methods exploit low-level primitives such as points or lines, the emergence of very effective CNN-based object detectors in the recent years has paved the way

Claude Godrèche, Jean-Marc Luck

This work is devoted to an in-depth analysis of arbitrary temperature protocols applied to the ferromagnetic Glauber-Ising chain launched from a disordered initial state and evolving in the low-temperature scaling regime. We focus our study on the density of domain walls and the reduced susceptibility. Both the inverse of the former observable and the latter

Zihui Wu, Haichang Gao, Bingqian Zhou, Xiaoyan Guo

In this paper, we investigate on improving the adversarial robustness obtained in adversarial training (AT) via reducing the difficulty of optimization. To better study this problem, we build a novel Bregman divergence perspective for AT, in which AT can be viewed as the sliding process of the training data points on the negative entropy curve. Based on this

Xianke Chen, Daizong Liu, Xun Yang, Xirong Li

In current text-to-video retrieval (T2VR), videos to be retrieved have been properly trimmed so that a correspondence between the videos and ad-hoc textual queries naturally exists. Note in practice that videos circulated on the Internet and social media platforms, while being relatively short, are typically rich in their content. Often, multiple scenes / ac

Kevin J Wilson

We consider the design of a two-arm superiority cluster randomised controlled trial (RCT) with a continuous outcome. We detail Bayesian inference for the analysis of the trial using a linear mixed-effects model. The treatment is compared to control using the posterior distribution for the treatment effect. We develop the form of the assurance to choose the s

Aiste Lengvenyte, Bruno Aouizerate, Valerie Aubin, Joséphine Loftus

Background: Bipolar disorder (BD) is a chronic, lifelong condition, associated with increased risk of obesity, cognitive impairment, and suicidal behaviors. Abdominal obesity and a higher risk of violent suicide attempt (SA) seem to be shared correlates with older age, BD, and male sex until middle age when menopause-related female body changes occur. This s

Carlos Javier Villagómez, Fernando Buendía, Lauro Oliver Paz-Borbón, Bernardo Fuentes

Herein, we invesgate the consequence of local voltage pulses on the adsorption state of single indigo molecules on the Cu(111) surface as well as on the atomic structure underneath the molecule. With a scanning tunneling microscope, at 5 K, intact molecules are imaged as two lobes corresponding to the electron density of each indoxyl moiety of the molecule w

Ravi Kant Gupta, Shivani Nandgaonkar, Nikhil Cherian Kurian, Swapnil Rane

The standard diagnostic procedures for targeted therapies in lung cancer treatment involve histological subtyping and subsequent detection of key driver mutations, such as EGFR. Even though molecular profiling can uncover the driver mutation, the process is often expensive and time-consuming. Deep learning-oriented image analysis offers a more economical alt

Yusen Zhang, Zhongli Li, Qingyu Zhou, Ziyi Liu

To automatically correct handwritten assignments, the traditional approach is to use an OCR model to recognize characters and compare them to answers. The OCR model easily gets confused on recognizing handwritten Chinese characters, and the textual information of the answers is missing during the model inference. However, teachers always have these answers i

Karim Achouri, Ville Tiukuvaara, Olivier J. F. Martin

We propose a framework that connects the spatial symmetries of a metasurface to its material parameter tensors and its scattering matrix. This provides a simple yet effective way to effortlessly determine properties of a metasurface scattering response, such as chirality or asymmetric transmission, and which of its effective material parameters should be tak

Marianne Bessemoulin-Chatard, Francis Filbet

We prove the convergence of discontinuous Galerkin approximations for the Vlasov-Poisson system written as an hyperbolic system using Hermite polynomials in velocity. To obtain stability properties, we introduce a suitable weighted L 2 space, with a time dependent weight, and first prove global stability for the weighted L 2 norm and propagation of regularit

Chemseddine Ananna, Francesco Barile, Axel Boeltzig, Carlo Giulio Bruno

Nuclear reaction cross sections are essential ingredients to predict the evolution of AGB stars and understand their impact on the chemical evolution of our Galaxy. Unfortunately, the cross sections of the reactions involved are often very small and challenging to measure in laboratories on Earth. In this context, major steps forward were made with the adven

Mike Pereira, Nicolas Desassis, Denis Allard

Large or very large spatial (and spatio-temporal) datasets have become common place in many environmental and climate studies. These data are often collected in non-Euclidean spaces (such as the planet Earth) and they often present non-stationary anisotropies. This paper proposes a generic approach to model Gaussian Random Fields (GRFs) on compact Riemannian

Anupam K. Gupta, Alex Church, Nathan F. Lepora

The sense of touch is fundamental to human dexterity. When mimicked in robotic touch, particularly by use of soft optical tactile sensors, it suffers from distortion due to motion-dependent shear. This complicates tactile tasks like shape reconstruction and exploration that require information about contact geometry. In this work, we pursue a semi-supervised

Bin Lao, Peitao Liu, Xuan Zheng, Zengxing Lu

Over the past decade, utilizing spin currents in the linear response of electric field to manipulate magnetization states via spin-orbit torques (SOTs) is one of the core concepts for realizing a multitude of spintronic devices. Besides the linear regime, recently, nonlinear charge-spin conversion under the square of electric field has been recognized in a w

Wenhao Dong, Changqing Feng, Junchen Wang, Zhongtao Shen

This paper presents a novel encoding method for fine time data of a tapped delay line (TDL) time-to-digital Converter (TDC). It is based on divide-and-conquer strategy, and has the advantage of significantly reducing logic resource utilization while retaining low dead-time performance. Furthermore, the problem of high bubble depth in advanced devices can be

Raúl Pardo, Willard Rafnsson, Gregor Steinhorn, Denis Lavrov

Analysis of genetic data opens up many opportunities for medical and scientific advances. The use of phenotypic information and polygenic risk scores to analyze genetic data is widespread. Most work on genetic privacy focuses on basic genetic data such as SNP values and specific genotypes. In this paper, we introduce a novel methodology to quantify and preve

Ayana Niwa, Sho Takase, Naoaki Okazaki

Non-autoregressive (NAR) models can generate sentences with less computation than autoregressive models but sacrifice generation quality. Previous studies addressed this issue through iterative decoding. This study proposes using nearest neighbors as the initial state of an NAR decoder and editing them iteratively. We present a novel training strategy to lea

Xin Li, Yong Shi, Zhi-Yu Zhang, Jianhang Chen

Ultra-diffuse galaxies (UDGs) are as faint as dwarf galaxies but whose sizes are similar to those of spiral galaxies. A variety of formation mechanisms have been proposed, some of which could result in different disk thicknesses. In this study, we measure the radial profile of the HI scale height (h_g) and flaring angle (h_g/R) of AGC 242019 through the join

Junyoung Son, Jinsung Kim, Jungwoo Lim, Heuiseok Lim

The dialogue-based relation extraction (DialogRE) task aims to predict the relations between argument pairs that appear in dialogue. Most previous studies utilize fine-tuning pre-trained language models (PLMs) only with extensive features to supplement the low information density of the dialogue by multiple speakers. To effectively exploit inherent knowledge

Vestislav Apostolov

These lecture notes are written for a PhD mini-course I gave at the CIRM in Luminy in 2019. Their intended purpose was to present, in the context of smooth toric varieties, a relatively self-contained and elementary introduction to the theory of extremal K\"ahler metrics pioneered by E. Calabi in the 1980's and extensively developed in recent years. The fram

Andreas Pieper

Let $\eta$ be a polarization with connected kernel on a superspecial abelian variety $E^g$. We give a sufficient criterion which allows the computation of the theta nullvalues of any quotient of $E^g$ by a maximal isotropic subgroup scheme of $\ker(\eta)$ effectively. This criterion is satisfied in many situations studied by Li and Oort. We used our method t

Joel Honkamaa, Umair Khan, Sonja Koivukoski, Mira Valkonen

Cross-modality image synthesis is an active research topic with multiple medical clinically relevant applications. Recently, methods allowing training with paired but misaligned data have started to emerge. However, no robust and well-performing methods applicable to a wide range of real world data sets exist. In this work, we propose a generic solution to t

A. Akylas, I. Papadakis, A. Georgakakis

Our objective is to critically assess the X-ray flux variability as a tool for measuring the black hole (BH) mass in active galactic nuclei (AGN). We aim to establish a prescription for estimating BH masses based on measurements of the normalised excess variance from X-ray data. We discuss the minimum requirements in terms of the light-curve duration and X-r

Stone Yun, Alexander Wong

Deep convolutional neural network (CNN) training via iterative optimization has had incredible success in finding optimal parameters. However, modern CNN architectures often contain millions of parameters. Thus, any given model for a single architecture resides in a massive parameter space. Models with similar loss could have drastically different characteri

Vaclav Skala

Acceleration of algorithms is becoming a crucial problem, if larger data sets are to be processed. Evaluation of algorithms is mostly done by using computational geometry approach and evaluation of computational complexity. However in todays engineering problems this approach does not respect that number of processed items is always limited and a significant

Yuichiro Yoshida, Wataru Mizukami, Norio Yoshida

We present a combination of three-dimensional reference interaction site model self-consistent field (3D-RISM-SCF) theory and the variational quantum eigensolver (VQE) to consider the solvent distribution effects within the framework of quantum-classical hybrid computing. The present method, 3D-RISM-VQE, does not include any statistical errors from the solve

Ivana Pajic-Lijakovic, Milan Milivojevic

Morphogenesis, tissue regeneration and cancer invasion involve transitions in tissue morphology. These transitions, caused by collective cell migration (CCM), have been interpreted as active wetting/de-wetting transitions. This phenomenon is considered on model system such as wetting of cell aggregate on rigid substrate which includes cell aggregate movement

Francesco Foscarin, Katharina Hoedt, Verena Praher, Arthur Flexer

Current approaches for explaining deep learning systems applied to musical data provide results in a low-level feature space, e.g., by highlighting potentially relevant time-frequency bins in a spectrogram or time-pitch bins in a piano roll. This can be difficult to understand, particularly for musicologists without technical knowledge. To address this issue

Sangjun Han, Taeil Hur, Youngmi Hur

In this paper, we develop the Laplacian pyramid-like autoencoder (LPAE) by adding the Laplacian pyramid (LP) concept widely used to analyze images in Signal Processing. LPAE decomposes an image into the approximation image and the detail image in the encoder part and then tries to reconstruct the original image in the decoder part using the two components. W

Peng Zhao, Long-Fei Li, Zhi-Hua Zhou

We investigate online Markov Decision Processes (MDPs) with adversarially changing loss functions and known transitions. We choose dynamic regret as the performance measure, defined as the performance difference between the learner and any sequence of feasible changing policies. The measure is strictly stronger than the standard static regret that benchmarks

Sangdo Han

Development of methods to detect fake news (FN) in low-resource languages has been impeded by a lack of training data. In this study, we solve the problem by using only training data from a high-resource language. Our FN-detection system permitted this strategy by applying adversarial learning that transfers the detection knowledge through languages. To assi

Euisung Park

Let $X \subset \P^r$ be a linearly normal variety defined by a very ample line bundle $L$ on a projective variety $X$. Recently it is shown in \cite{HLMP} that there are many cases where $(X,L)$ satisfies property $\textsf{QR} (3)$ in the sense that the homogeneous ideal $I(X,L)$ of $X$ is generated by quadratic polynomials of rank $3$. The locus $\Phi_3 (X,

Trupti Padiya, Frank Löffler, Friederike Klan

Interoperability issues concerning observational data have gained attention in recent times. Automated data integration is important when it comes to the scientific analysis of observational data from different sources. However, it is hampered by various data interoperability issues. We focus exclusively on semantic interoperability issues for observational

Robin Witthaus

We extend Colmez's functor defined for $\operatorname{GL}_2(\mathbf{Q}_p)$ to the category of finitely generated smooth admissible mod-$p$ representations of the two-fold metaplectic cover of $\operatorname{GL}_2(\mathbf{Q}_p)$. We compute the images of the absolutely irreducible genuine objects and obtain a bijection between the genuine supersingular repres

Robin Witthaus

Half-integral weight modular forms are naturally viewed as automorphic forms on the so-called metaplectic covering of $\operatorname{GL}_2(\mathbf{A}_{\mathbf{Q}})$ -- a central extension by the roots of unity $\mu_2$ in $\mathbf{Q}$. For an odd prime number $p$, we give a complete classification of the smooth irreducible genuine mod-$p$ representations of t

Omar Zamzam, Haleh Akrami, Richard Leahy

The problem of learning from positive and unlabeled data (A.K.A. PU learning) has been studied in a binary (i.e., positive versus negative) classification setting, where the input data consist of (1) observations from the positive class and their corresponding labels, (2) unlabeled observations from both positive and negative classes. Generative Adversarial

Kengo Matsumoto

We introduce the notion of K-theoretic duality for extensions of separable unital nuclear $C^*$-algebras by using K-homology long exact sequence and cyclic six term exact sequence for K-theory groups of extensions. We then prove that the Toeplitz extension $\mathcal{T}_A$ of a Cuntz-Krieger algebra $\mathcal{O}_A$ is the K-theoretic dual of the Toeplitz exte

Olga V. Sapunova, Natalia L. Borodkova, Georgii N. Zastenker, Yuri I. Yermolaev

Experimental investigations of the fine plasma structure of interplanetary shocks are extremely difficult to conduct due to their small thickness and high speed relative to the spacecraft. We study the variations in the parameters of twice-ionized helium ions (4He++ ions or {\alpha}-particles) in the solar wind plasma during the passage of interplanetary sho

Congwei Xie, Abudukadi Tudi, Artem R. Oganov

In this work, the polar tetrahedron [PN$_2$O$_2$] was revealed as a new deep-ultraviolet (deep-UV) nonlinear optically active unit. Accordingly, a thermodynamically stable compound (PNO) consisting of the polar [PN$_2$O$_2$] units was predicted and suggested as a promising candidate of deep-UV nonlinear optical (NLO) material. Compared with other deep-UV mat

Sumit S. Pakhare, Prashant M. Gade

We study coupled Gauss maps in one dimension and observe a transition to band periodic state with 2 bands. This is a periodic state with period-2 in a coarse-grained sense. This state does not show any long-range order in space. We compute two different order parameters to quantify the transition a) Flipping rate $F(t)$ which measures departures from period-

E. Miyazaki, T. Kemmochi, T. Sogabe, S. -L. Zhang

For fourth-order geometric evolution equations for planar curves with the dissipation of the bending energy, including the Willmore and the Helfrich flows, we consider a numerical approach. In this study, we construct a structure-preserving method based on a discrete variational derivative method. Furthermore, to prevent the vertex concentration that may lea

Yongsung Park, Florian Meyer, Peter Gerstoft

This paper presents a Bayesian estimation method for sequential direction finding. The proposed method estimates the number of directions of arrivals (DOAs) and their DOAs performing operations on the factor graph. The graph represents a statistical model for sequential beamforming. At each time step, belief propagation predicts the number of DOAs and their

Man Ho Chan, Chak Man Lee, Chi Wai Yu

In the past three decades, many stars orbiting about the supermassive black hole (SMBH) at the Galactic Centre (Sgr A*) were identified. Their orbital nature can give stringent constraints for the mass of the SMBH. In particular, the star S2 has completed at least one period since our first detection of its position, which can provide rich information to exa

Youngook Choi, Hristo Iliev, Seonja Kim

For $\gamma \geq 7$ and $g \geq 6\gamma + 5$, we construct a family $\mathcal{F}^{\prime}$ of curves lying on cones in $\mathbb{P}^{g-3\gamma+1}$ over smooth non-degenerate curves of genus $\gamma$ and degree $g-2\gamma$ in $\mathbb{P}^{g-3\gamma+1}$. We show that $\dim \mathcal{F}^{\prime} = 2g-\gamma-1 + (g-3\gamma+1)^2$. For a general curve $X^{\prime}$ f

István Kovács

A finite simple graph $\Gamma$ is called a Nest graph if it is regular of valency $6$ and admits an automorphism $\rho$ with two orbits of the same length such that at least one of the subgraphs induced by these orbits is a cycle. We say that $\Gamma$ is core-free if no non-trivial subgroup of the group generated by $\rho$ is normal in $\mathrm{Aut}(\Gamma)$

Isroil A. Ikromov, Akbar R. Safarov

In this paper we consider the problem on uniform estimates for generalized oscillatory integrals given by Mittag- Leffler functions with the homogeneous polynomial phase. We obtain a variant of Ricci-Stein Lemma and invariant estimates for corresponding integrals.

Yue-Xin Huang, Z. Y. Chen, Xiaolong Feng, Shengyuan A. Yang

Real Clifford algebras play a fundamental role in the eight real Altland-Zirnbauer symmetry classes and the classification tables of topological phases. Here, we present another elegant realization of real Clifford algebras in the $d$-dimensional spinless rectangular lattices with $\pi$ flux per plaquette. Due to the $T$-invariant flux configuration, real Cl

Bhavya Peshavaria, Sagar Kavaiya, Dhaval K. Patel

This paper presents the extension of the idea of spectrum sharing in the vehicular networks towards the Heterogeneous Vehicular Network(HetVNET) based on multi-agent reinforcement learning. Here, the multiple vehicle-to-vehicle(V2V) links reuse the spectrum of other vehicle-to-interface(V2I) and also those of other networks. The fast-changing environment in

Hong Wang

This is a survey article, from the viewpoint of the completeness of the Marsden- Weinstein reduction, to introduce briefly some recent developments of the symmetric reductions and Hamilton-Jacobi theory of the regular controlled Hamiltonian systems, the nonholonomic controlled Hamiltonian systems and the controlled magnetic Hamiltonian systems. These researc

Junjie Hu, Chenyou Fan, Mete Ozay, Hualie Jiang

We study data-free knowledge distillation (KD) for monocular depth estimation (MDE), which learns a lightweight model for real-world depth perception tasks by compressing it from a trained teacher model while lacking training data in the target domain. Owing to the essential difference between image classification and dense regression, previous methods of da

Qingqiang Sun, Xuemin Lin, Ying Zhang, Wenjie Zhang

Network alignment task, which aims to identify corresponding nodes in different networks, is of great significance for many subsequent applications. Without the need for labeled anchor links, unsupervised alignment methods have been attracting more and more attention. However, the topological consistency assumptions defined by existing methods are generally

Yi Lin, Luyan Liu, Kai Ma, Yefeng Zheng

Automated methods for Cobb angle estimation are of high demand for scoliosis assessment. Existing methods typically calculate the Cobb angle from landmark estimation, or simply combine the low-level task (e.g., landmark detection and spine segmentation) with the Cobb angle regression task, without fully exploring the benefits from each other. In this study,

Guanming Xiong, Junwei Bao, Wen Zhao, Youzheng Wu

This study investigates the task of knowledge-based question generation (KBQG). Conventional KBQG works generated questions from fact triples in the knowledge graph, which could not express complex operations like aggregation and comparison in SPARQL. Moreover, due to the costly annotation of large-scale SPARQL-question pairs, KBQG from SPARQL under low-reso

Esha Sadia Nasir, Arshi Perviaz, Muhammad Moazam Fraz

Instance segmentation of nuclei and glands in the histology images is an important step in computational pathology workflow for cancer diagnosis, treatment planning and survival analysis. With the advent of modern hardware, the recent availability of large-scale quality public datasets and the community organized grand challenges have seen a surge in automat

Bo-Shi Zou, Ming-Kun Xie, Sheng-Jun Huang

Partial label learning (PLL) is a typical weakly supervised learning framework, where each training instance is associated with a candidate label set, among which only one label is valid. To solve PLL problems, typically methods try to perform disambiguation for candidate sets by either using prior knowledge, such as structure information of training data, o

Akira Imakura, Masateru Kihira, Yukihiko Okada, Tetsuya Sakurai

Recently, data collaboration (DC) analysis has been developed for privacy-preserving integrated analysis across multiple institutions. DC analysis centralizes individually constructed dimensionality-reduced intermediate representations and realizes integrated analysis via collaboration representations without sharing the original data. To construct the colla

Markus Bier, Maximilian Mußotter, S. Dietrich

The structures of dilute electrolyte solutions close to non-uniformly charged planar substrates are systematically studied within the entire spectrum of microscopic to macroscopic length scales by means of a unified classical density functional theory (DFT) approach. This is in contrast to previous investigations, which are applicable either to short or to l

Yuan Fang, Huali Zhang, Ding Wang, Guowei Yang

Hund's metals are multi-orbital systems with $3d$ or $4d$ electrons exhibiting both itinerant character and local moments, and they feature Kondo-like screenings of local orbital and spin moments, with suppressed coherence temperature driven by Hund's coupling $J_H$. They often exhibit magnetic order at low temperature, but how the interaction between the Ko

Gideon Kowadlo, Abdelrahman Ahmed, Amir Mayan, David Rawlinson

Continual learning and few-shot learning are important frontiers in progress toward broader Machine Learning (ML) capabilities. Recently, there has been intense interest in combining both. One of the first examples to do so was the Continual few-shot Learning (CFSL) framework of Antoniou et al. arXiv:2004.11967. In this study, we extend CFSL in two ways that

Alice Devillers, Cheryl E. Praeger

In this paper we develop several general methods for analysing flag-transitive point-imprimitive $2$-designs, which give restrictions on both the automorphisms and parameters of such designs. These constitute a tool-kit for analysing these designs and their groups. We apply these methods to complete the classification of flag-transitive, point-imprimitive $2

Anastasiia Tkalich, Darja Smite, Nina Haugland Andersen, Nils Brede Moe

Psychological safety is a precondition for learning and success in software teams. Companies such as SavingsBank, which is discussed in this article, have developed good practices to facilitate psychological safety, most of which depend on face-to-face interaction. However, what happens to psychological safety when working remotely? In this article, we explo

Yu Zhang, Shuaifei Chen, Jiayi Zhang

Cell-free massive multiple-input-multiple-output is promising to meet the stringent quality-of-experience (QoE) requirements of railway wireless communications by coordinating many successional access points (APs) to serve the onboard users coherently. A key challenge is how to deliver the desired contents timely due to the radical changing propagation envir

Zhu Liu, A. Malyali, M. Krumpe, D. Homan

(Abridged) In this paper, we present the results of an exceptional repeating X-ray nuclear transient, eRASSt J045650.3-203750 (hereafter J0456-20), uncovered by SRG/eROSITA in a quiescent galaxy at redshift of z~0.077. The main results are: 1) J0456-20 cycles through four distinctive phases: an X-ray rising phase leading into an X-ray plateau phase which las

Miho Katsuragawa, Shiu-Hang Lee, Hirokazu Odaka, Aya Bamba

One of the outstanding mysteries surrounding the rich diversity found in supernova remnants (SNRs) is the recent discovery of over-ionized or recombining plasma from a number of dynamically evolved objects. To help decipher its formation mechanism, we have developed a new simulation framework capable of modeling the time evolution of the ionization state of

S. M. Koksbang

For a flat $\Lambda$CDM universe, the dipole of the luminosity distance can be utilized to measure the Hubble parameter. It is here shown that this is not the case in more general settings where curvature and cosmic backreaction is permitted. This implies that a discordance between $H(z)$ measurements obtained using such dipole luminosity distance data and "

Jihwan Won

Federated learning is a model for privacy without revealing private data by transfer models instead of personal and private data from local client devices. While, in the global model, it's crucial to recognize each local data is normal. This paper suggests one method to separate normal locals and abnormal locals by Euclidean similarity clustering of vectors

Mahathir Almashor, Ejaz Ahmed, Benjamin Pick, Sharif Abuadbba

The daily deluge of alerts is a sombre reality for Security Operations Centre (SOC) personnel worldwide. They are at the forefront of an organisation's cybersecurity infrastructure, and face the unenviable task of prioritising threats amongst a flood of abstruse alerts triggered by their Security Information and Event Management (SIEM) systems. URLs found wi

Yunyao Mao, Wengang Zhou, Zhenbo Lu, Jiajun Deng

In 3D action recognition, there exists rich complementary information between skeleton modalities. Nevertheless, how to model and utilize this information remains a challenging problem for self-supervised 3D action representation learning. In this work, we formulate the cross-modal interaction as a bidirectional knowledge distillation problem. Different from

Sunyo Moon, Seungkook Park

In this paper, we provide an explicit formula for the rank of the walk matrix of the extended Dynkin graph $\tilde{D}_n$.

Hideyasu Yamashita

The Berezin--Simon (BS) quantization is a rigorous version of the ``operator formalism'' of quantization procedure. The goal of the paper is to present a rigorous real-time (not imaginary-time) path-integral formalism corresponding to the BS operator formalism of quantization; Here we consider the classical systems whose phase space $M$ is a (possibly non-co

G. Sharma, R. Paul, K. Deka, R. Moulick

In this study, the physics of sheath formation in a collisional two-electron temperature plasma in the presence of an oblique external magnetic field has been investigated. At first, a comparative study among the fluid electron model, Boltzmann electron model and the nonextensive electron model has been carried out and a suitable range of nonextensive parame

Jingjing Sun, Shouqiang Du, Yuanyuan Chen, Yimin Wei

In view of the KS-tensor complementarity problem, the sparse solution of this problem is studied. Due to the nonconvexity and noncontinuity of the l_0-norm, it is a NP hard problem to find the sparse solution of the KS-tensor complementarity problem. In order to solve this problem, we transform it into a polynomial programming problem with constraints. Then

Evan T. R. Rosenman, Santiago Olivella, Kosuke Imai

We provide the largest compiled publicly available dictionaries of first, middle, and last names for the purpose of imputing race and ethnicity using, for example, Bayesian Improved Surname Geocoding (BISG). The dictionaries are based on the voter files of six Southern states that collect self-reported racial data upon voter registration. Our data cover a mu

D. Gola, S. Nidhan, J. L. Ortiz-Tarin, H. Pham

Nonlinearity of density stratification modulates buoyancy effects. We report results from a body-inclusive large eddy simulation (LES) of a wake in nonlinear stratification, specifically for a circular disk at diameter-based Reynolds number ($Re$) of $5000$. Five density profiles are considered; the benchmark has linear stratification and the other four have

Siddharth Maharana, Ramya M. Anche, A. N. Ramaprakash, Bhushan Joshi

The Wide-Area Linear Optical Polarimeter (WALOP)-South instrument is an upcoming wide-field and high-accuracy optical polarimeter to be used as a survey instrument for carrying out the Polar-Areas Stellar Imaging in Polarization High Accuracy Experiment (PASIPHAE) program. Designed to operate as a one-shot four-channel and four-camera imaging polarimeter, it

Kousik Rajesh, Eklavya Jain, Prakash Kotecha

The electric vehicle routing problem (EVRP) has garnered great interest from researchers and industrialists in an attempt to move from fuel-based vehicles to healthier and more efficient electric vehicles (EVs). While it seems that the EVRP should not be much different from traditional vehicle routing problems (VRPs), challenges like limited cruising time, l

Shicheng Wan, Zhenqiang Ye, Wensheng Gan, Jiahui Chen

High utility itemset mining approaches discover hidden patterns from large amounts of temporal data. However, an inescapable problem of high utility itemset mining is that its discovered results hide the quantities of patterns, which causes poor interpretability. The results only reflect the shopping trends of customers, which cannot help decision makers qua

Ahammed Ullah

An abundance of real-world problems manifest as covering edges and/or vertices of a graph with cliques that are optimized for some objectives. We consider different structural parameters of graph, and design fixed-parameter tractable algorithms for a number of clique cover problems. Using a set representation of graph, we introduce a framework for computing

Hongyan Gu, Mohammad Haeri, Shuo Ni, Christopher Kazu Williams

This work presents a mitosis detection method with only one vanilla Convolutional Neural Network (CNN). Our method consists of two steps: given an image, we first apply a CNN using a sliding window technique to extract patches that have mitoses; we then calculate each extracted patch's class activation map to obtain the mitosis's precise location. To increas

N. E. Mavromatos, Sarben Sarkar, A. Soto

A nonperturbative Schwinger-Dyson analysis of mass generation is presented for a non-Hermitian PT-symmetric field theory in four dimensions of an axion coupled to a Dirac fermion.The model is motivated by phenomenological considerations.The axion has a quartic self-coupling $\lambda$ and a Yukawa coupling $g$ to the fermion. The Schwinger-Dyson equations are