July 2022 arXiv papers — page 87

Amir Zarringhalam, Saeed Shiry Ghidary, Ali Mohades Khorasani

In this paper, two semi-supervised appearance based loop closure detection technique, HGCN-FABMAP and HGCN-BoW are introduced. Furthermore an extension to the current state of the art localization SLAM algorithm, ORB-SLAM, is presented. The proposed HGCN-FABMAP method is implemented in an off-line manner incorporating Bayesian probabilistic schema for loop d

Urban Senica, Andres Forrer, Tudor Olariu, Paolo Micheletti

Recently, there has been a growing interest in integrated THz photonics for various applications in communications, spectroscopy and sensing. We present a new integrated photonic platform based on active and passive elements integrated in a double-metal, high confinement waveguide layout planarized with a low-loss polymer. An extended top metallization resul

Luisa Fermo, Domenico Mezzanotte, Donatella Occorsio

In the present paper, a Nystrom-type method for second kind Volterra integral equations is introduced and studied. The method makes use of generalized Bernstein polynomials, defined for continuous functions and based on equally spaced points. Stability and convergence are studied in the space of continuous functions, and some numerical tests illustrate the p

Naoki Ogawa, Tadashi Takayanagi, Takashi Tsuda, Takahiro Waki

In this paper, we study codimension two holography in flat spacetimes, based on the idea of the wedge holography. We propose that a region in a $d+1$ dimensional flat spacetime surrounded by two end of the world-branes, which are given by $d$ dimensional hyperbolic spaces, is dual to a conformal field theory (CFT) on a $d-1$ dimensional sphere. Similarly, we

Stefano Marchesi, Xiurui Zhao, Núria Torres-Albà, Marco Ajello

We present the multi-epoch monitoring with NuSTAR and XMM-Newton of NGC 1358, a nearby Seyfert 2 galaxy whose properties made it a promising candidate X-ray changing look AGN, i.e., a source whose column density could transition from its 2017 Compton-thick (CT-, having line-of-sight Hydrogen column density NH,los>10^24 cm^-2) state to a Compton-thin (NH,los<

Jiawei Yang, Hanbo Chen, Yuan Liang, Junzhou Huang

Detectingandsegmentingobjectswithinwholeslideimagesis essential in computational pathology workflow. Self-supervised learning (SSL) is appealing to such annotation-heavy tasks. Despite the extensive benchmarks in natural images for dense tasks, such studies are, unfortunately, absent in current works for pathology. Our paper intends to narrow this gap. We fi

Amir Zarringhalam, Saeed Shiry Ghidary, Ali Mohades Khorasani

In this paper, we introduce AE-FABMAP, a new self-supervised bag of words-based SLAM method. We also present AE-ORB-SLAM, a modified version of the current state of the art BoW-based path planning algorithm. That is, we have used a deep convolutional autoencoder to find loop closures. In the context of bag of words visual SLAM, vector quantization (VQ) is co

Alfred Galichon, Larry Samuelson, Lucas Vernet

We introduce a notion of substitutability for correspondences and establish a monotone comparative static result, unifying results such as the inverse isotonicity of M-matrices, Berry, Gandhi and Haile's identification of demand systems, monotone comparative statics, and results on the structure of the core of matching games without transfers (Gale and Shapl

Julià Cufí, Juan J. Donaire

We modify the proof of the basic lemma of a paper of Saks and Zygmund on additive functions of rectangles.

Andis Lagzdiņš, Uldis Siliņš, Mārcis Pinnis, Toms Bergmanis

Consolidated access to current and reliable terms from different subject fields and languages is necessary for content creators and translators. Terminology is also needed in AI applications such as machine translation, speech recognition, information extraction, and other natural language processing tools. In this work, we facilitate standards-based sharing

Shuhei Kitano

$W^{\sigma,p}$ estimates are studied for a class of fully nonlinear integro-differential equations of order $\sigma$, which are analogues of $W^{2,p}$ estimates by Caffarelli. We also present Aleksandrov-Bakelman-Pucci maximum principles, which are improvements of estimates proved by Guillen-Schwab, depending only on $L^p$ norms of inhomogeneous terms.

Yunjing Shan, Junling Zhou

Let $V$ be an $n$-dimensional vector space over the finite field $\mathbb{F}_{q}$, and let $\mathcal{L}(V)=\bigcup_{0\leq k\leq n}\left[V\atop k\right]$ be the set of all subspaces of $V$. A family of subspaces $\mathcal{F}\subseteq \mathcal{L}(V)$ is $s$-union if dim$(F+F')\leq s$ holds for all $F$, $F'\in\mathcal{F}$. A family $\mathcal{F}\subseteq \mathca

Martin Knoche, Mohamed Elkadeem, Stefan Hörmann, Gerhard Rigoll

Image resolution, or in general, image quality, plays an essential role in the performance of today's face recognition systems. To address this problem, we propose a novel combination of the popular triplet loss to improve robustness against image resolution via fine-tuning of existing face recognition models. With octuplet loss, we leverage the relationship

Riccardo Zamolo, Davide Miotti, Enrico Nobile

A major obstacle to the application of the standard Radial Basis Function-generated Finite Difference (RBF-FD) meshless method is constituted by its inability to accurately and consistently solve boundary value problems involving Neumann boundary conditions (BCs). This is also due to ill-conditioning issues affecting the interpolation matrix when boundary de

Shuhei Kitano

Aleksandrov-Bakelman-Pucci maximum principles are studied for a class of fully nonlinear integro-differential equations of order $\sigma\in [2-\varepsilon_0,2)$, where $\varepsilon_0$ is a small constant depending only on given parameters. The goal of this paper is to improve an estimate of Guillen and Schwab (Arch. Ration. Mech. Anal., 206, 2012) in order t

Thai Duong Do, Van Thien Nguyen

In this article, we investigate the weighted $m-$subharmonic functions. We shall give some properties of this class and consider its relation to the $m-$Cegrell classes. We also prove an integration theorem and an almost everywhere convergence theorem for this class.

Kiyoshi Sogo, Shuhei Ohnishi

By introducing an integration factor to the differential one-form of contact dynamics, equations of motion are derived variationally, and contact Poisson bracket and contact Lagrangian are formulated. Discrete symplectic integrator, named hybrid leap-frog method, is found to be a numerical solver of equations of motion for contact dissipative systems.

Yuki Okoda, Yoko Oya, Muneaki Imai, Nami Sakai

Resolving physical and chemical structures in the vicinity of a protostar is of fundamental importance for elucidating their evolution to a planetary system. In this context, we have conducted 1.2 mm observations toward the low-mass protostellar source B335 at a resolution of 0."03 with ALMA. More than 20 molecular species including HCOOH, NH2 CHO, HNCO, CH3

Seyed Ali Hosseini Mansoori, Zahra Molaee

In this paper, we first introduce a multi-field setup of Cuscuton gravity in a curved field space manifold. Then, we show that this model allows for a regular bouncing cosmology and it does not lead to ghosts or other instabilities at the level of perturbations. More precisely, by decomposing the scalar fields perturbations into the tangential and normal com

Ke Wang, Lu Chen

In cosmology, the fine-structure constant can affect the whole ionization history. However, the previous works confine themselves to the recombination epoch and give various strong constraints on the fine-structure constant. In this paper, we also take the reionization epoch into consideration and do a consistency test of the fine-structure constant from the

Honghao Lv, Zhibo Pang, Ming Xiao, Geng Yang

More and more robot automation applications have changed to wireless communication, and network performance has a growing impact on robotic systems. This study proposes a hardware-in-the-loop (HiL) simulation methodology for connecting the simulated robot platform to real network devices. This project seeks to provide robotic engineers and researchers with t

Zhenyu Zhang, Bowen Yu, Haiyang Yu, Tingwen Liu

Building document-grounded dialogue systems have received growing interest as documents convey a wealth of human knowledge and commonly exist in enterprises. Wherein, how to comprehend and retrieve information from documents is a challenging research problem. Previous work ignores the visual property of documents and treats them as plain text, resulting in i

Pablo Rivière-Marichalar, Asunción Fuente, Gisela Esplugues, Valentine Wakelam

The sulfur abundance is poorly known in most environments. Yet, deriving the sulfur abundance is key to understanding the evolution of the chemistry from molecular clouds to planetary atmospheres. We present observations of H$_2$S 110-101 at 168.763 GHz toward the Herbig Ae star AB Aur. We aim to study the abundance of sulfuretted species toward AB Aur and t

Lê Vǎn Thành

Consider a sequence of positive integers $\{k_n,n\ge1\}$, and an array of nonnegative real numbers $\{a_{n,i},1\le i\le k_n,n\ge1\}$ satisfying $\sup_{n\ge 1}\sum_{i=1}^{k_n}a_{n,i}=C_0\in (0,\infty).$ This paper introduces the concept of $\{a_{n,i}\}$-stochastic domination. We develop some techniques concerning this concept and apply them to remove an assum

Chin-Ping Hu, Lupin Chun-Che Lin, Kuo-Chuan Pan, Kwan-Lok Li

We analyze the gravitational wave signals with a model-independent time-frequency analysis, which is improved from the Hilbert-Huang transform (HHT) and optimized for characterizing the frequency variability on the time-frequency map. Except for the regular HHT algorithm, i.e., obtaining intrinsic mode functions with ensemble empirical mode decomposition and

Velibor Velović, M. D. Filipović, L. Barnes, R. P. Norris

We present the discovery of highly-collimated radio jets spanning a total of 355 kpc around the nearby elliptical galaxy NGC 2663, and the possible first detection of recollimation on kiloparsec scales. The small distance to the galaxy (~28.5 Mpc) allows us to resolve portions of the jets to examine their structure. We combine multiwavelength data: radio obs

Zhaocheng Liu, Yingtao Luo, Di Zeng, Qiang Liu

Modeling users' dynamic preferences from historical behaviors lies at the core of modern recommender systems. Due to the diverse nature of user interests, recent advances propose the multi-interest networks to encode historical behaviors into multiple interest vectors. In real scenarios, the corresponding items of captured interests are usually retrieved tog

James A. Sellers, Nicolas Allen Smoot

In 2021 da Silva, Hirschhorn, and Sellers studied a wide variety of congruences for the $k$-elongated plane partition function $d_k(n)$ by various primes. They also conjectured the existence of an infinite congruence family modulo arbitrarily high powers of 2 for the function $d_7(n)$. We prove that such a congruence family exists -- indeed, for powers of 8.

Ofer Neufeld, Nicolas Tancogne-Dejean, Umberto De Giovannini, Hannes Hübener

Irradiating solids with ultrashort laser pulses is known to initiate femtosecond timescale magnetization dynamics. However, sub-femtosecond spin dynamics have not yet been observed or predicted. Here, we explore ultrafast light-driven spin dynamics in a highly non-resonant strong-field regime. Through state-of-the-art ab-initio calculations, we predict that

Maaz Amjad, Alisa Zhila, Grigori Sidorov, Andrey Labunets

With the growth of social media platform influence, the effect of their misuse becomes more and more impactful. The importance of automatic detection of threatening and abusive language can not be overestimated. However, most of the existing studies and state-of-the-art methods focus on English as the target language, with limited work on low- and medium-res

Joanna Komorniczak, Pawel Ksieniewicz

The classification problem's complexity assessment is an essential element of many topics in the supervised learning domain. It plays a significant role in meta-learning -- becoming the basis for determining meta-attributes or multi-criteria optimization -- allowing the evaluation of the training set resampling without needing to rebuild the recognition mode

Ashwin Bhaskar, M. Praveen

Constraint linear-time temporal logic (CLTL) is an extension of LTL that is interpreted on sequences of valuations of variables over an infinite domain. The atomic formulas are interpreted as constraints on the valuations. The atomic formulas can constrain valuations over a range of positions along a sequence, with the range being bounded by a parameter depe

Anwesha Maharana, Alexey Isavnin, Camilla Scolini, Nicolas Wijsen

The Flux Rope in 3D (FRi3D, Isavnin, 2016), a coronal mass ejection (CME) model with global three-dimensional (3D) geometry, has been implemented in the space weather forecasting tool EUHFORIA (Pomoell and Poedts, 2018). By incorporating this advanced flux rope model in EUHFORIA, we aim to improve the modelling of CME flank encounters and, most importantly,

Ariel Caputo, Marco Emporio, Andrea Giachetti, Marco Cristani

This paper presents the outcomes of a contest organized to evaluate methods for the online recognition of heterogeneous gestures from sequences of 3D hand poses. The task is the detection of gestures belonging to a dictionary of 16 classes characterized by different pose and motion features. The dataset features continuous sequences of hand tracking data whe

Kay Schönwald

We report on our recent calculation of massive quark form factors using a semi-numerical approach based on series expansions of the master integrals around singular and regular kinematic points and numerical matching. The methods allows to cover the whole kinematic range of negative and positive values of the virtuality $s$ with at least seven significant di

Cesar Gomez

We suggest a new conceptual frame where inflationary Cosmology is quantum mechanically described using the Hilbert space representation of the crossed product of the type $III$ factor associated with the algebra of local operators on the de Sitter static patch and the automorphism of translations in the emergent conformal time. In this formal framework scala

Dennis Høj, Ulrich Busk Hoff, Ulrik Lund Andersen

Micro- and nanomechanical systems with exceptionally low dissipation rates are enabling the next-generation technologies of ultra-sensitive detectors and quantum information systems. New techniques and methods for lowering the dissipation rate have in recent years been discovered and allowed for the engineering of mechanical oscillators with phononic modes t

Hao Xu, Si Yu Chen, Yen Chin Ong

We consider quantum decoherence and Landauer's principle in qubit-cavity quantum field theory (QFT) interaction, treating the qubit as the system and cavity QFT as the environment. In particular, we investigate the changes that occur in the system with a pure initial state and environment during the decoherence process, with or without energy dissipation, an

Jiaojie Yan, Yijia Wu, Shuai Yuan, Xiao Liu

Quantum information can be coded by the topologically protected edges of fractional quantum Hall (FQH) states. Investigation on FQH edges in the hope of searching and utilizing non-Abelian statistics has been a focused challenge for years. Manipulating the edges, e.g. to bring edges close to each other or to separate edges spatially, is a common and essentia

Bowen Zhao, Huanlai Xing, Xinhan Wang, Fuhong Song

Attention-based models have been widely used in many areas, such as computer vision and natural language processing. However, relevant applications in time series classification (TSC) have not been explored deeply yet, causing a significant number of TSC algorithms still suffer from general problems of attention mechanism, like quadratic complexity. In this

John Paige, Geir-Arne Fuglstad, Andrea Riebler, Jon Wakefield

Spatial aggregation with respect to a population distribution involves estimating aggregate quantities for a population based on an observation of individuals in a subpopulation. In this context, a geostatistical workflow must account for three major sources of `aggregation error': aggregation weights, fine scale variation, and finite population variation. H

Matija Kazalicki, Domagoj Vlah

Determining the rank of an elliptic curve E/Q is a hard problem, and in some applications (e.g. when searching for curves of high rank) one has to rely on heuristics aimed at estimating the analytic rank (which is equal to the rank under the Birch and Swinnerton-Dyer conjecture). In this paper, we develop rank classification heuristics modeled by deep convol

Arijit Nandi, Fatos Xhafa, Laia Subirats, Santi Fort

We present MDEAW, a multimodal database consisting of Electrodermal Activity (EDA) and Photoplethysmography (PPG) signals recorded during the exams for the course taught by the teacher at Eurecat Academy, Sabadell, Barcelona in order to elicit the emotional reactions to the students in a classroom scenario. Signals from 10 students were recorded along with t

Hye-Jin Park, Se-Heon Oh, Jing Wang, Yun Zheng

We present H I gas kinematics and star formation activities of NGC 6822, a dwarf galaxy located in the Local Group at a distance of ~ 490 kpc. We perform profile decomposition of line-of-sight velocity profiles of the H I data cube (42.4" x 12.0" spatial, corresponding to ~ 100 pc; 1.6 km s$^{-1}$ spectral) taken with the Australia Telescope Compact Array (A

Ran Wang, Beibei Zhang

We study a large deviation principle for a reflected stochastic partial differential equation on infinite spatial domain. A new sufficient condition for the weak convergence criterion proposed by Matoussi, Sabbagh and Zhang ({\it Appl. Math. Optim.} 83: 849-879, 2021) plays an important role in the proof.

O. Adriani, E. Berti, P. Betti, G. Bigongiari

The multi-TeV energy region of the cosmic-ray spectra has been recently explored by direct detection experiments that used calorimetric techniques to measure the energy of the cosmic particles. Interesting spectral features have been observed in both all-electron and nuclei spectra. However, the interpretation of the results is compromised by the disagreemen

Liang Qiao, Hui Jiang, Ying Chen, Can Li

This paper presents DavarOCR, an open-source toolbox for OCR and document understanding tasks. DavarOCR currently implements 19 advanced algorithms, covering 9 different task forms. DavarOCR provides detailed usage instructions and the trained models for each algorithm. Compared with the previous opensource OCR toolbox, DavarOCR has relatively more complete

Ying Chen, Liang Qiao, Zhanzhan Cheng, Shiliang Pu

End-to-end text spotting has attached great attention recently due to its benefits on global optimization and high maintainability for real applications. However, the input scale has always been a tough trade-off since recognizing a small text instance usually requires enlarging the whole image, which brings high computational costs. In this paper, to addres

Salman Beigi, Milad M. Goodarzi

Operator-valued Schatten spaces were introduced by G. Pisier as a noncommutative counterpart of vector-valued $\ell_p$-spaces. This family of operator spaces forms an interpolation scale which makes it a powerful and convenient tool in a variety of applications. In particular, as the norms coming from this family naturally appear in the definition of certain

Junkai Man, Ruitian Wu, Chenglin Zhang, Xin Tong

Visualizing big data can provide valuable insights into social science research. In this project, we focused on visualizing the potential gender gap in the global film industry over the past 100 years. We profiled the differences both for the actors/actresses and male/female movie audiences and analyzed the IMDb data of the most popular 10,000 movies (the co

Carlo Condo

Guessing Random Additive Noise Decoding (GRAND) is a universal decoding algorithm that can be used to perform maximum likelihood decoding. It attempts to find the errors introduced by the channel by generating a sequence of possible error vectors in order of likelihood of occurrence and applying them to the received vector. Ordered reliability bits GRAND (OR

P. T. Nhung, D. T. Hoai, P. Darriulat, P. N. Diep

We use archival ALMA observations of the CO(2-1) and SiO(5-4) molecular line emissions of AGB star R Hya to illustrate the relative contributions of rotation, expansion and line broadening to the morphology and kinematics of the circumstellar envelope (CSE) within some ~70 au (~0.5 arcsec) from the centre of the star. We give evidence for rotation and import

Biswajit Pabi, Atindra Nath Pal

Understanding the transport characteristics at the atomic limit is the prerequisite for futuristic nano-electronic applications. Among various experimental procedures, mechanically controllable break junction (MCBJ) is one of the well adopted experimental technique to study and control the atomic or molecular scale devices. Here, we present the details of th

Shu-Yen Pan

It is known that irreducible cuspidal characters satisfy the preservation principle in the Howe correspondences of finite reductive dual pairs. In this article, we generalize the preservation principle to any irreducible characters of classical groups.

Mingyang Yi, Ruoyu Wang, Jiachen Sun, Zhenguo Li

Recently, generalization on out-of-distribution (OOD) data with correlation shift has attracted great attentions. The correlation shift is caused by the spurious attributes that correlate to the class label, as the correlation between them may vary in training and test data. For such a problem, we show that given the class label, the models that are conditio

Misbah Shafi, Rakesh Kumar Jha, Sanjeev Jain

Smartphones with the platforms of applications are gaining extensive attention and popularity. The enormous use of different applications has paved the way to numerous security threats. The threats are in the form of attacks such as permission control attacks, phishing attacks, spyware attacks, botnets, malware attacks, privacy leakage attacks. Moreover, oth

He Song

We consider biased random walk on regular tree and we obtain the spectral radius, first return probability and $n$-step transition probability.

Zhongren Chen, Xinyue Xu, Shengyi Jiang, Hao Wang

Small subgraphs (graphlets) are important features to describe fundamental units of a large network. The calculation of the subgraph frequency distributions has a wide application in multiple domains including biology and engineering. Unfortunately due to the inherent complexity of this task, most of the existing methods are computationally intensive and ine

Misbah Shafi, Rakesh Kumar Jha

This paper introduces a systematic and novel mechanism for devising a security attack in the WCN (Wireless Communication Network). The proposed model involves the implementation of the AD (Artificial Dust) by the intruder, followed by the execution of the HD (Half-Duplex) attack. The communication network is based on the deployment of urban and rural scenari

S. J. Paul, S. Moran, M. Arratia, A. El Alaoui

We present the first measurement of di-hadron angular correlations in electron-nucleus scattering. The data were taken with the CLAS detector and a 5.0 GeV electron beam incident on deuterium, carbon, iron, and lead targets. Relative to deuterium, the nuclear yields of charged-pion pairs show a strong suppression for azimuthally opposite pairs, no suppressio

Martán Ceresa, César Sánchez

Blockchains are maintained by a network of participants that run algorithms designed to maintain collectively a distributed machine tolerant to Byzantine attacks. From the point of view of users, blockchains provide the illusion of centralized computers that perform trustable verifiable computations, where all computations are deterministic and the results c

Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang

Hypergraph neural networks (HNNs) using neural networks to encode hypergraphs provide a promising way to model higher-order relations in data and further solve relevant prediction tasks built upon such higher-order relations. However, higher-order relations in practice contain complex patterns and are often highly irregular. So, it is often challenging to de

Zhou Liu, Yujun Li, Zhengying Liu, Lin Li

Automatic theorem proving with deep learning methods has attracted attentions recently. In this paper, we construct an automatic proof system for trigonometric identities. We define the normalized form of trigonometric identities, design a set of rules for the proof and put forward a method which can generate theoretically infinite trigonometric identities.

Aaron Wang

Composed of amino acid chains that influence how they fold and thus dictating their function and features, proteins are a class of macromolecules that play a central role in major biological processes and are required for the structure, function, and regulation of the body's tissues. Understanding protein functions is vital to the development of therapeutics

Hyesung Jo, Dae Han Wi, Taegu Lee, Yongmin Kwon

Nanomaterials with core-shell architectures are prominent examples of strain-engineered materials, where material properties can be designed by fine-tuning the misfit strain at the interface. Here, we elucidate the full 3D atomic structure of Pd@Pt core-shell nanoparticles at the single-atom level via atomic electron tomography. Full 3D displacement fields a

Andrey A. Popov, Arash Sarshar, Austin Chennault, Adrian Sandu

A rapidly growing area of research is the use of machine learning approaches such as autoencoders for dimensionality reduction of data and models in scientific applications. We show that the canonical formulation of autoencoders suffers from several deficiencies that can hinder their performance. Using a meta-learning approach, we reformulate the autoencoder

Chung-Ru Lee

When employing Feynman path integrals to compute propagators in quantum physics, the concept of summing over the set of all paths is not always naive. In fact, an auxiliary phase often has to be included as a weight for each summand. In this article we discuss the nature of those phase factors for the various types of boundary conditions including all three

Xiangmeng Wang, Qian Li, Dianer Yu, Guandong Xu

Counterfactual explanations interpret the recommendation mechanism via exploring how minimal alterations on items or users affect the recommendation decisions. Existing counterfactual explainable approaches face huge search space and their explanations are either action-based (e.g., user click) or aspect-based (i.e., item description). We believe item attrib

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

The cotton boll weevil, Anthonomus grandis Boheman is a serious pest to the U.S. cotton industry that has cost more than 16 billion USD in damages since it entered the United States from Mexico in the late 1800s. This pest has been nearly eradicated; however, southern part of Texas still faces this issue and is always prone to the pest reinfestation each yea

Yifei Jin, Lisa J. Kewley, Ralph S. Sutherland

We create a photoionization model embedded in the turbulent ISM by using the state-of-the-art Messenger Monte-Carlo MAPPINGS~V code (M$^3$) in conjunction with the CMFGEN stellar atmosphere model. We show that the turbulent ISM causes the inhomogeneity of electron temperature and density within the nebula. The fluctuation in the turbulent ISM creates complex

Javier Aramayona, Julio Aroca, María Cumplido, Rachel Skipper

A Cantor surface $\mathcal C_d$ is a non-compact surface obtained by gluing copies of a fixed compact surface $Y^d$ (a block), with $d+1$ boundary components, in a tree-like fashion. For a fixed subgroup $H<Map(Y^d)$ , we consider the subgroup $\mathfrak B_d(H)<Map(\mathcal C_d)$ whose elements eventually send blocks to blocks and act like an element of $H$;

Siddhant Arora, Siddharth Dalmia, Xuankai Chang, Brian Yan

End-to-end (E2E) models are becoming increasingly popular for spoken language understanding (SLU) systems and are beginning to achieve competitive performance to pipeline-based approaches. However, recent work has shown that these models struggle to generalize to new phrasings for the same intent indicating that models cannot understand the semantic content

Chin-En Hsu, Yung-Ting Lee, Chieh-Chun Wang, Chang-Yu Lin

Silicon and germanium are the well-known materials used to manufacture electronic devices for the integrated circuits but they themselves are not considered as promising options for interconnecting the devices due to their semiconducting nature. We have discovered that both Si and Ge atoms can form unexpected metallic monolayer structures which are more stab

D. Bhanu Prakash, D. K. K. Vamsi

This paper consists of a detailed and novel stochastic optimal control analysis of a coupled non-linear dynamical system. The state equations are modeled as additional food provided prey-predator system with Holling Type-III functional response for predator and intra-specific competition among predators. We firstly discuss the optimal control problem as a La

Ji Liu, Daxiang Dong, Xi Wang, An Qin

Although more layers and more parameters generally improve the accuracy of the models, such big models generally have high computational complexity and require big memory, which exceed the capacity of small devices for inference and incurs long training time. In addition, it is difficult to afford long training time and inference time of big models even in h

Yan Gao, Chenggang Bai, Quan Quan

In order to guide the multi-agent system in a cluttered environment, a connected quadrangle virtual tube is designed for all agents to keep moving within it, whose basis is called the single trapezoid virtual tube. There is no obstacle inside the tube, namely the area inside the tube can be seen as a safety zone. Then, a distributed swarm controller is propo

Sebastian Nielebock, Paul Blockhaus, Jacob Krüger, Frank Ortmeier

Developers build on Application Programming Interfaces (APIs) to reuse existing functionalities of code libraries. Despite the benefits of reusing established libraries (e.g., time savings, high quality), developers may diverge from the API's intended usage; potentially causing bugs or, more specifically, API misuses. Recent research focuses on developing te

Lujun Huang, Bin Jia, Artem S Pilipchuk, Yankei Chiang

Bound states in the continuum (BICs) provide a viable way of achieving high-Q resonances in both photonics and acoustics. In this work, we proposed a general method of constructing Friedrich-Wintgen (FW) BICs and accidental BICs in a coupled acoustic waveguide-resonator system. We demonstrated that FW BICs can be achieved with arbitrary two degenerate resona

Panos Pantidis, Mostafa E. Mobasher

We present a new Integrated Finite Element Neural Network framework (I-FENN), with the objective to accelerate the numerical solution of nonlinear computational mechanics problems. We leverage the swift predictive capability of neural networks (NNs) and we embed them inside the finite element stiffness function, to compute element-level state variables and t

Rozhin Yasaei, Sina Faezi, Mohammad Abdullah Al Faruque

The globalization of the Integrated Circuit (IC) supply chain has moved most of the design, fabrication, and testing process from a single trusted entity to various untrusted third-party entities worldwide. The risk of using untrusted third-Party Intellectual Property (3PIP) is the possibility for adversaries to insert malicious modifications known as Hardwa

Eunsun Kim, Ian P. Roberts, Jeffrey G. Andrews

The extension of wide area wireless connectivity to low-earth orbit (LEO) satellite communication systems demands a fresh look at the effects of in-orbit base stations, sky-to-ground propagation, and cell planning. A multi-beam LEO satellite delivers widespread coverage by forming multiple spot beams that tessellate cells over a given region on the surface o

Florian Albrecht, Shadi Fatayer, Iago Pozo, Ivano Tavernelli

Controlling selectivity of reactions is a quest in chemistry. Here, we demonstrate reversible and selective bond formation and dissociation promoted by tip-induced reduction-oxidation reactions on a surface. Molecular rearrangements leading to different constitutional isomers are selected by the polarity and magnitude of applied voltage pulses from the tip o

Tatsuya Yatagawa, Yutaka Ohtake, Hiromasa Suzuki

Traditional algorithms of point set registration minimizing point-to-plane distances often achieve a better estimation of rigid transformation than those minimizing point-to-point distances. Nevertheless, recent deep-learning-based methods minimize the point-to-point distances. In contrast to these methods, this paper proposes the first deep-learning-based a

Jungho Ahn, Jinha Kim, O-joung Kwon

Let $\mathcal{F}$ be a family of graphs, and let $p,r$ be nonnegative integers. The \textsc{$(p,r,\mathcal{F})$-Covering} problem asks whether for a graph $G$ and an integer $k$, there exists a set $D$ of at most $k$ vertices in $G$ such that $G^p\setminus N_G^r[D]$ has no induced subgraph isomorphic to a graph in $\mathcal{F}$, where $G^p$ is the $p$-th pow

Ziqiang Li, Yongxin Ge, Jiaruo Yu, Zhongming Chen

With video-level labels, weakly supervised temporal action localization (WTAL) applies a localization-by-classification paradigm to detect and classify the action in untrimmed videos. Due to the characteristic of classification, class-specific background snippets are inevitably mis-activated to improve the discriminability of the classifier in WTAL. To allev

Xiaogang Xu, Hengshuang Zhao

Existing automatic data augmentation (DA) methods either ignore updating DA's parameters according to the target model's state during training or adopt update strategies that are not effective enough. In this work, we design a novel data augmentation strategy called "Universal Adaptive Data Augmentation" (UADA). Different from existing methods, UADA would ad

Sai Sirisha Nadiminti, Pranav Kant Gaur, Abhilash Bhardwaj

Indian vehicle number plates have wide variety in terms of size, font, script and shape. Development of Automatic Number Plate Recognition (ANPR) solutions is therefore challenging, necessitating a diverse dataset to serve as a collection of examples. However, a comprehensive dataset of Indian scenario is missing, thereby, hampering the progress towards publ

Bargav Jayaraman, Esha Ghosh, Melissa Chase, Sambuddha Roy

Pre-trained large language models, such as GPT\nobreakdash-2 and BERT, are often fine-tuned to achieve state-of-the-art performance on a downstream task. One natural example is the ``Smart Reply'' application where a pre-trained model is tuned to provide suggested responses for a given query message. Since the tuning data is often sensitive data such as emai

David R. Wood

We determine which properties of 2-layer drawings characterise bipartite graphs of bounded pathwidth.

Christopher Drovandi, David J Nott, David T Frazier

Likelihood-free methods are an essential tool for performing inference for implicit models which can be simulated from, but for which the corresponding likelihood is intractable. However, common likelihood-free methods do not scale well to a large number of model parameters. A promising approach to high-dimensional likelihood-free inference involves estimati

Zhengkai Jiang, Yuxi Li, Ceyuan Yang, Peng Gao

Unsupervised Domain Adaptation (UDA) aims to adapt the model trained on the labeled source domain to an unlabeled target domain. In this paper, we present Prototypical Contrast Adaptation (ProCA), a simple and efficient contrastive learning method for unsupervised domain adaptive semantic segmentation. Previous domain adaptation methods merely consider the a

D. Wu

The safety of single-vehicle autonomous driving technology is limited due to the limits of perception capability of on-board sensors. In contrast, vehicle-road collaboration technology can overcome those limits and improve the traffic safety and efficiency, by expanding the sensing range, improving the perception accuracy, and reducing the response time. How

Seonghyuk Im, Jaehoon Kim, Younjin Kim, Hong Liu

For a given graph $H$, its subdivisions carry the same topological structure. The existence of $H$-subdivisions within a graph $G$ has deep connections with topological, structural and extremal properties of $G$. One prominent example of such a connection, due to Bollob\'{a}s and Thomason and independently Koml\'os and Szemer\'edi, asserts that the average d

Hui Shi, Yupeng Gu, Yitong Zhou, Bo Zhao

User embeddings (vectorized representations of a user) are essential in recommendation systems. Numerous approaches have been proposed to construct a representation for the user in order to find similar items for retrieval tasks, and they have been proven effective in industrial recommendation systems as well. Recently people have discovered the power of usi

Felipe Costa Farias, Teresa Bernarda Ludermir, Carmelo José Albanez Bastos-Filho

The model selection procedure is usually a single-criterion decision making in which we select the model that maximizes a specific metric in a specific set, such as the Validation set performance. We claim this is very naive and can perform poor selections of over-fitted models due to the over-searching phenomenon, which over-estimates the performance on tha

Hosseinali Salemi, Danial Davarnia

Over the past decade, decision diagrams (DDs) have been used to model and solve integer programming and combinatorial optimization problems. Despite successful performance of DDs in solving various discrete optimization problems, their extension to model mixed integer programs (MIPs) such as those appearing in energy applications has been lacking. More broad

Baichuan Huang, Abdeslam Boularias, Jingjin Yu

We propose a novel Parallel Monte Carlo tree search with Batched Simulations (PMBS) algorithm for accelerating long-horizon, episodic robotic planning tasks. Monte Carlo tree search (MCTS) is an effective heuristic search algorithm for solving episodic decision-making problems whose underlying search spaces are expansive. Leveraging a GPU-based large-scale s

Angxiu Ni

To generalize the backpropagation method to both discrete-time and continuous-time hyperbolic chaos, we introduce the adjoint shadowing operator $\mathcal{S}$ acting on covector fields. We show that $\mathcal{S}$ can be equivalently defined as: (a) $\mathcal{S}$ is the adjoint of the linear shadowing operator $S$; (b) $\mathcal{S}$ is given by a `split then

Simin Shekarpaz, Mohammad Azizmalayeri, Mohammad Hossein Rohban

In this paper, we propose the physics informed adversarial training (PIAT) of neural networks for solving nonlinear differential equations (NDE). It is well-known that the standard training of neural networks results in non-smooth functions. Adversarial training (AT) is an established defense mechanism against adversarial attacks, which could also help in ma

John Tan Chong Min, Mehul Motani

Modern deep neural networks require a significant amount of computing time and power to train and deploy, which limits their usage on edge devices. Inspired by the iterative weight pruning in the Lottery Ticket Hypothesis, we propose DropNet, an iterative pruning method which prunes nodes/filters to reduce network complexity. DropNet iteratively removes node