November 2022 arXiv papers — page 165

Dinesh S Thakur

In [Tha15], we looked at two (`multiplicative' and `Carlitz-Drinfeld additive') analogs each, for the well-known basic congruences of Fermat and Wilson, in the case of polynomials over finite fields. When we look at them modulo higher powers of primes, i.e. at `supercongruences', we find interesting relations linking them together, as well as lin

Leonid A. Kurdachenko, Oleksandr O. Pypka, Igor Ya. Subbotin

Let $L$ be an algebra over a field $F$ with the binary operations $+$ and $[,]$. Then $L$ is called a left Leibniz algebra if $[[a,b],c]=[a,[b,c]]-[b,[a,c]]$ for all $a,b,c\in L$. We describe the inner structure of left Leibniz algebras having dimension 3.

Lean Wang, Lei Li, Xu Sun

Knowledge distillation (KD) is an effective framework to transfer knowledge from a large-scale teacher to a compact yet well-performing student. Previous KD practices for pre-trained language models mainly transfer knowledge by aligning instance-wise outputs between the teacher and student, while neglecting an important knowledge source, i.e., the gradient o

Sautenkov Oleg, Altamirano Cabrera Miguel, Rakhmatulin Viktor, Tsetserukou Dzmitry

Complex robotic tasks require human collaboration to benefit from their high dexterity. Frequent human-robot interaction is mentally demanding and time-consuming. Intuitive and easy-to-use robot control interfaces reduce the negative influence on workers, especially inexperienced users. In this paper, we present CobotTouch, a novel intuitive robot control in

M. Abid, A. Ayoub, J. Akram

We study the significance of Photon/Phonons bunching and antibunching on the dynamics of the quantum entanglement in the presence of coupled PT-symmetry systems with balanced/unbalanced gain and loss. We suggest a hybrid electromechanical system to realize a strong and tunable coupling between a Coplanar-Waveguide (CPW) microwave cavity and a nanomechanical

J. Hussian, M. Nouman, F. Saif, J. Akram

The scattering of a Bose-Einstein Condensate (BEC) from a Gaussian well and Gaussian barrier is investigated over a wide range of depths and heights, respectively. We compare analytical and numerical results for a BEC scattering from Gaussian Obstacles, both in the presence and in the absence of PT-symmetric potential. And we find out that the Complex Ginzbu

Paul E. Chang, Prakhar Verma, ST John, Victor Picheny

Gaussian processes (GPs) are the main surrogate functions used for sequential modelling such as Bayesian Optimization and Active Learning. Their drawbacks are poor scaling with data and the need to run an optimization loop when using a non-Gaussian likelihood. In this paper, we focus on `fantasizing' batch acquisition functions that need the ability to c

Tongtong Song, Qiang Xu, Haoyu Lu, Longbiao Wang

The bi-encoder structure has been intensively investigated in code-switching (CS) automatic speech recognition (ASR). However, most existing methods require the structures of two monolingual ASR models (MAMs) should be the same and only use the encoder of MAMs. This leads to the problem that pre-trained MAMs cannot be timely and fully used for CS ASR. In thi

David G. Jackson, Christopher A. Watson, Ernst J. W. de Mooij, Jack S. Acton

We report the discovery of three new hot Jupiters with the Next Generation Transit Survey (NGTS) as well as updated parameters for HATS-54b, which was independently discovered by NGTS. NGTS-23b, NGTS-24b and NGTS-25b have orbital periods of 4.076, 3.468, and 2.823 days and orbit G-, F- and K-type stars, respectively. NGTS-24 and HATS-54 appear close to trans

Stanislav Jendroľ, Alfréd Onderko

An $r$-hued coloring of a simple graph $G$ is a proper coloring of its vertices such that every vertex $v$ is adjacent to at least $\min\{r, °(v)\}$ differently colored vertices. The minimum number of colors needed for an $r$-hued coloring of a graph $G$, the $r$-hued chromatic number, is denoted by $χ_{r}(G)$. In this note we show that $$χ_r(G) \leq (r - 1)

Bodo Zibrowius, Michael Fischer

The quadrupole coupling constant $C_Q$ and the asymmetry parameter $η$ have been determined for two complex aluminium hydrides from $^{27}$Al NMR spectra recorded for stationary samples by using the Solomon echo sequence. The thus obtained data for KAlH4 ($C_Q=(1.30\pm0.02)$ MHz, $η=(0.64\pm0.02)$) and NaAlH4 ($C_Q=(3.11\pm0.02)$ MHz, $η<0.01$) agree very we

Alessandro Palmas, Pietro Andronico

This paper describes how advanced deep learning based computer vision algorithms are applied to enable real-time on-board sensor processing for small UAVs. Four use cases are considered: target detection, classification and localization, road segmentation for autonomous navigation in GNSS-denied zones, human body segmentation, and human action recognition. A

Martina Boschi, Daniele Ritelli, Giulia Spaletta

Aim of this work is the study of differential equations governing non--dissipative non--linear oscillators; these arise in different physical models such as the treatment of relativistic oscillators, up to generalizations to Duffing&#39;s relativistic oscillators and in non--relativistic models which deals with cables with an attached midpoint mass, or some

Łukasz Dębowski

We present an impossibility result, called a theorem about facts and words, which pertains to a general communication system. The theorem states that the number of distinct words used in a finite text is roughly greater than the number of independent elementary persistent facts described in the same text. In particular, this theorem can be related to Zipf&#3

Józef Spałek

The electronic states of selected nanosystems are discussed within the Exact Diagonalization Ab Initio (EDABI) method. In particular, incipient Mott--Hubbard localization effects and associated with it properties analyzed in detail.

Alessandro Campa, Shamik Gupta

Sometimes the dynamics of a physical system is described by non-Hamiltonian equations of motion, and additionally, the system is characterized by long-range interactions. A concrete example is that of particles interacting with light as encountered in free-electron laser and cold-atom experiments. In this work, we study the relaxation dynamics to non-Hamilto

Irina Scherbakova, Andrey Pepelyshev, Yuri Staroselskiy, Anatoly Zhigljavsky

Real-time bidding has transformed the digital advertising landscape, allowing companies to buy website advertising space in a matter of milliseconds in the time it takes a webpage to load. Joint research between Cardiff University and Crimtan has employed statistical modelling in conjunction with machine-learning techniques on big data to develop computer al

John Gough

We dedicate this to the life and work of Robin Hudson -- a mathematical physicist who developed the peerless quantum stochastic calculus, but who also inspired generations of researchers with both his intellect and wit.

A. Hahn, R. Mirzoyan, A. Dettlaff, D. J. Fink

MAGIC is a system of two imaging atmospheric Cherenkov telescopes (IACTs) located on the Canary island of La Palma. Each telescope&#39;s imaging camera consists of 1039 photomultiplier tubes (PMTs). We developed three detector modules based on silicon photomultipliers (SiPMs) of seven pixels each that are mechanically and electronically compatible with those

Yerila Rodríguez-Martínez, Lídice Vaillant-Roca, Jaafar Ghanbaja, Sylvie Migot

Plasmonic Cu nanoparticles were in-situ grown into a Cu$_2$O semiconductor matrix by using reactive magnetron sputtering and adjusting the amount of oxygen available during the synthesis in order to prevent the oxidation of part of copper atoms landed on the film surface. Varying only the oxygen flowrate (OFR) and using a single Cu target it was possible to

Stephan Antholzer, Martin Berger, Tobias Hell

Autoencoders allow to reconstruct a given input from a small set of parameters. However, the input size is often limited due to computational costs. We therefore propose a clustering and reassembling method for volumetric point clouds, in order to allow high resolution data as input. We furthermore present an autoencoder based on the well-known FoldingNet fo

Sundeep Prabhakar Chepuri, Nir Shlezinger, Fan Liu, George C. Alexandropoulos

Integrated sensing and communications (ISAC) are envisioned to be an integral part of future wireless networks, especially when operating at the millimeter-wave (mmWave) and terahertz (THz) frequency bands. However, establishing wireless connections at these high frequencies is quite challenging, mainly due to the penetrating pathloss that prevents reliable

Jingfan Yu, Mengqian Zhang, Xi Chen, Zhixuan Fang

Play-to-earn is one of the prospective categories of decentralized applications. The play-to-earn projects combine blockchain technology with entertaining games and finance, attracting various participants. While huge amounts of capital have been poured into these projects, the new crypto niche is considered controversial, and the traditional gaming industry

C Cuny, J Dedecker, F Merlevède, M Peligrad

Let $A_n= \varepsilon_n \cdots \varepsilon_1$, where $(\varepsilon_n)_{n \geq 1}$ is a sequence of independent random matrices taking values in $ GL_d(\mathbb R)$, $d \geq 2$, with common distribution $μ$. In this paper, under standard assumptions on $μ$ (strong irreducibility and proximality), we prove Berry-Esseen type theorems for $\log ( \Vert A_n \Vert)

Kristian Bredies, Enis Chenchene, Alireza Hosseini

In this paper we present a new method for solving optimization problems involving the sum of two proper, convex, lower semicontinuous functions, one of which has Lipschitz continuous gradient. The proposed method has a hybrid nature that combines the usual forward-backward and the generalized conditional gradient method. We establish a convergence rate of $o

Yingjie Song, Wei Song, Wei Zhang, Zhengchen Zhang

This paper proposes an expressive singing voice synthesis system by introducing explicit vibrato modeling and latent energy representation. Vibrato is essential to the naturalness of synthesized sound, due to the inherent characteristics of human singing. Hence, a deep learning-based vibrato model is introduced in this paper to control the vibrato&#39;s like

Muhammad Fahad, Jérôme Darmont, Cécile Favre

In the current era, many disciplines are seen devoted towards ontology development for their domains with the intention of creating, disseminating and managing resource descriptions of their domain knowledge into machine understandable and processable manner. Ontology construction is a difficult group activity that involves many people with the different exp

Charalampos Charitos, Athanase Papadopoulos

Joseph-Nicolas Delisle was one of the most important scientists at the Saint Petersburg Academy of Sciences during the first period when Euler was working there. Euler was helping him in his work on astronomy and in geography. In this paper, Delisle&#39;s geographical projection is presented and Euler&#39;s study of this projection isexplained, highlighting

Hannaneh Barahouei Pasandi, Asma Haghighat, Azin Moradbeikie, Ahmad Keshavarz

The advent of Low Power Wide Area Networks (LPWAN) has enabled the feasibility of wireless sensor networks for environmental traffic sensing across urban areas. In this study, we explore the usage of LoRaWAN end nodes as traffic sensing sensors to offer a practical traffic management solution. The monitored Received Signal Strength Indicator (RSSI) factor is

Suhas Shrinivasan, Simon Razniewski

Knowledge Bases (KBs) provide structured representation of the real-world in the form of extensive collections of facts about real-world entities, their properties and relationships. They are ubiquitous in large-scale intelligent systems that exploit structured information such as in tasks like structured search, question answering and reasoning, and hence t

Ali Golmakani, Mostafa Sadeghi, Romain Serizel

Deep latent variable generative models based on variational autoencoder (VAE) have shown promising performance for audiovisual speech enhancement (AVSE). The underlying idea is to learn a VAEbased audiovisual prior distribution for clean speech data, and then combine it with a statistical noise model to recover a speech signal from a noisy audio recording an

Jiaqiang Zhang, Farhad Keramat, Xianjia Yu, Daniel Montero Hern

Robotic systems are more connected, networked, and distributed than ever. New architectures that comply with the \textit{de facto} robotics middleware standard, ROS\,2, have recently emerged to fill the gap in terms of hybrid systems deployed from edge to cloud. This paper reviews new architectures and technologies that enable containerized robotic applicati

Erell Jamelot

We propose to analyse the discretization of the Stokes problem with nonconforming finite elements in light of the T-coercivity (cf. [1] for Helmholtz-like problems, see [2], [3] and [4] for the neutron diffusion equation). We propose explicit expressions of the stability constants. Finally, we give numerical results illustrating the importance of using diver

Tetsuya Sakai, Sijie Tao, Zhaohao Zeng

In the context of depth-$k$ pooling for constructing web search test collections, we compare two approaches to ordering pooled documents for relevance assessors: the prioritisation strategy (PRI) used widely at NTCIR, and the simple randomisation strategy (RND). In order to address research questions regarding PRI and RND, we have constructed and released th

Amin Geng, Shoumin Liu, Xumin Wang

In this paper, the correspondence between the finite dimensional representations of a simple Lie algebra and their characteristic polynomials is established, and a monoid structure on these characteristic polynomials is constructed. Furthermore, the characteristic polynomials of sl(2, C) on some classical simple Lie algebras through adjoint representations a

Indrani Pal, C. S. Stalin

While the temperature of the X-ray corona ($\rm{kT_e}$) in active galactic nuclei (AGN) are known for many sources, its variation, if any, is limited to a handful of objects. This is in part due to the requirement of good signal-to-noise X-ray spectra covering a wide range of energies. We present here results on the X-ray spectral analysis of 18 Seyferts, ha

Oliver P. Squire, Stephen A. Hodgson, Jiasheng Chen, Vitaly Fedoseev

We report the discovery of superconductivity at a pressure-induced magnetic quantum critical point in the Kondo-lattice system CeSb2, sustained up to magnetic fields that exceed the conventional Pauli limit eight-fold. Like CeRh2As2, CeSb2 is locally non-centrosymmetric around the Ce-site, but the evolution of critical fields and normal state properties as C

Bruno C da Silva, Zahra S Momtaz, Lucas Bruas, Jean-Luc Rouviére

Momentum resolved 4D-STEM, also called center of mass (CoM) analysis, has been used to measure the long range built-in electric field of a silicon p-n junction. The effect of different STEM modes and the trade-off between spatial resolution and electric field sensitivity are studied. Two acquisition modes are compared: nanobeam and low magnification (LM) mod

Amin Shokri Gazafroudi, Fabian Neumann, Tom Brown

It is crucial for maintaining the security of supply that transmission networks continue to operate even if a single line fails. Modeling $\mathcal{N} - 1$ security in power system capacity expansion problems introduces many extra constraints if all possible outages are accounted for, which leads to a high computational burden. Typical approaches to avoid th

Dragana Bajovic, Dusan Jakovetic, Soummya Kar

Recent works have shown that high probability metrics with stochastic gradient descent (SGD) exhibit informativeness and in some cases advantage over the commonly adopted mean-square error-based ones. In this work we provide a formal framework for the study of general high probability bounds with SGD, based on the theory of large deviations. The framework al

Myung-Hwan Jeon, Jeongyun Kim, Jee-Hwan Ryu, Ayoung Kim

6D object pose estimation aims to infer the relative pose between the object and the camera using a single image or multiple images. Most works have focused on predicting the object pose without associated uncertainty under occlusion and structural ambiguity (symmetricity). However, these works demand prior information about shape attributes, and this condit

Adi Kurniawan, Paul H. Taylor, Jana Orszaghova, Hugh Wolgamot

An apparent giant wave event having a maximum trough-to-crest height of 21 metres and a maximum zero-upcrossing period of 27 seconds was recorded by a wave buoy at a nearshore location off the southwestern coast of Australia. It appears as a group of waves which are significantly larger both in height and period than the waves preceding and following them. T

Young Won Woo, Zhenzhu Li, Young-Kwang Jung, Ji-Sang Park

The competition between corner, edge and face-sharing octahedral networks is a cause of phase inhomogeneity in metal halide perovskite thin-films. Here we probe the charged iodine vacancy distribution and transport at the junction between cubic and hexagonal polytypes of CsPbI$_3$ from first-principles materials modelling. We predict a lower defect formation

Martin Pflaumer, Constantia Alexandrou, Jacob Finkenrath, Theodoros Leontiou

We present our recent results on antiheavy-antiheavy-light-light tetraquark systems using lattice QCD. Our study of the $ \bar{b}\bar{b}us $ four-quark system with quantum numbers $ J^P=1^+ $ and the $ \bar{b}\bar{c}ud $ four-quark systems with $ I(J^P)=0(0^+) $ and $ I(J^P)=0(1^+) $ utilizes scattering operators at the sink to improve the extraction of the

Be&#39;eri Greenfeld

An important problem in combinatorial noncommutative algebra is to characterize the growth functions of finitely generated algebras (equivalently, semigroups, or hereditary languages). The growth function of every finitely generated, infinite-dimensional algebra is increasing and submultiplicative. The question of to what extent these natural necessary condi

Shuhei A. Horiguchi, Tomoharu Iwata, Taku Tsuzuki, Yosuke Ozawa

The optimization of high-dimensional black-box functions is a challenging problem. When a low-dimensional linear embedding structure can be assumed, existing Bayesian optimization (BO) methods often transform the original problem into optimization in a low-dimensional space. They exploit the low-dimensional structure and reduce the computational burden. Howe

Yao Feng, Yuhong Jiang, Hang Su, Dong Yan

Model-based reinforcement learning usually suffers from a high sample complexity in training the world model, especially for the environments with complex dynamics. To make the training for general physical environments more efficient, we introduce Hamiltonian canonical ordinary differential equations into the learning process, which inspires a novel model o

Chengdong Liang, Xiao-Lei Zhang, BinBin Zhang, Di Wu

Recently, the unified streaming and non-streaming two-pass (U2/U2++) end-to-end model for speech recognition has shown great performance in terms of streaming capability, accuracy and latency. In this paper, we present fast-U2++, an enhanced version of U2++ to further reduce partial latency. The core idea of fast-U2++ is to output partial results of the bott

Ke Yang, Sixian Wang, Jincheng Dai, Kailin Tan

In this paper, we aim to redesign the vision Transformer (ViT) as a new backbone to realize semantic image transmission, termed wireless image transmission transformer (WITT). Previous works build upon convolutional neural networks (CNNs), which are inefficient in capturing global dependencies, resulting in degraded end-to-end transmission performance especi

Beixiang Fang, Wei Xiang, Feng Xiao

In this paper we are concerned with the local well-posedness of the unsteady potential flows near a space corner of right angle, which could be formulated as an initial-boundary value problem of a hyperbolic equation of second order in a cornered-space domain. The corner singularity is the key difficulty in establishing the local well-posedness of the proble

Be&#39;eri Greenfeld

Resco and Small gave the first example of an affine Noetherian algebra which is not finitely presented. It is shown that their algebra has no finite-dimensional filtrations whose associated graded algebras are Noetherian, affirming their prediction. A modification of their example yields countable fields over which `almost all&#39; (that is, a co-countable c

Woo-Ri Ko, Minsu Jang, Jaeyeon Lee, Jaehong Kim

To provide effective and enjoyable human-robot interaction, it is important for social robots to exhibit nonverbal behaviors, such as a handshake or a hug. However, the traditional approach of reproducing pre-coded motions allows users to easily predict the reaction of the robot, giving the impression that the robot is a machine rather than a real agent. The

Jiao Sun, Thibault Sellam, Elizabeth Clark, Tu Vu

Evaluation metrics that are not robust to dialect variation make it impossible to tell how well systems perform for many groups of users, and can even penalize systems for producing text in lower-resource dialects. However, currently, there exists no way to quantify how metrics respond to change in the dialect of a generated utterance. We thus formalize dial

Wei Li, Wolfgang Karl Härdle, Stefan Lessmann

There has been intensive research regarding machine learning models for predicting bankruptcy in recent years. However, the lack of interpretability limits their growth and practical implementation. This study proposes a data-driven explainable case-based reasoning (CBR) system for bankruptcy prediction. Empirical results from a comparative study show that t

Yusuke Higuchi, Etsuo Segawa

We consider the Grover walk on the infinite graph in which an internal finite subgraph receives the inflow from the outside with some frequency and also radiates the outflow to the outside. To characterize the stationary state of this system, which is represented by a function on the arcs of the graph, we introduce a kind of discrete gradient operator twiste

Justin Presley, Xi Wang, Tym Brandel, Xusheng Ai

Today&#39;s big data science communities manage their data publication and replication at the application layer. These communities utilize myriad mechanisms to publish, discover, and retrieve datasets - the result is an ecosystem of either centralized, or otherwise a collection of ad-hoc data repositories. Publishing datasets to centralized repositories can

Koki Tsubota, Hiroaki Akutsu, Kiyoharu Aizawa

Deep image compression performs better than conventional codecs, such as JPEG, on natural images. However, deep image compression is learning-based and encounters a problem: the compression performance deteriorates significantly for out-of-domain images. In this study, we highlight this problem and address a novel task: universal deep image compression. This

Guowei Yu

Consider the planar restricted $(N+1)$-body problem with trajectories of the $N(\ge 2)$ primaries forming a collision-free periodic solution of the $N$-body problem, for any positive energy $h$ and directions $θ_{\pm} \in [0, 2π)$, we prove that starting from any initial position $x$ at any initial time $t_x$, there are hyperbolic solutions $γ^{\pm}|_{[t_x,

Shanqing Yu, Yijun Wu, Ran Gan, Jiajun Zhou

Most of the existing knowledge graphs are not usually complete and can be complemented by some reasoning algorithms. The reasoning method based on path features is widely used in the field of knowledge graph reasoning and completion on account of that its have strong interpretability. However, reasoning methods based on path features still have several probl

Siqi Bao, Huang He, Jun Xu, Hua Lu

Recently, the practical deployment of open-domain dialogue systems has been plagued by the knowledge issue of information deficiency and factual inaccuracy. To this end, we introduce PLATO-K based on two-stage dialogic learning to strengthen internal knowledge memorization and external knowledge exploitation. In the first stage, PLATO-K learns through massiv

Chenyue Zhang, Yiran He, Hoi-To Wai

This paper considers learning a product graph from multi-attribute graph signals. Our work is motivated by the widespread presence of multilayer networks that feature interactions within and across graph layers. Focusing on a product graph setting with homogeneous layers, we propose a bivariate polynomial graph filter model. We then consider the topology inf

Eunseok Hwang, Dukjae Jang, Kiwan Park, Motohiko Kusakabe

We explore the effects of electromagnetic (EM) fluctuations in plasmas on solar neutrino fluxes exploiting the fluctuation-dissipation theorem. We find that the EM spectrum in the solar core is enhanced by the EM fluctuations due to the high density of the Sun, which increases the radiation energy density and pressure. By the EM fluctuations involving the mo

Dimitrij Tschodu, Jürgen Lippoldt, Pablo Gottheil, Anne-Sophie Wegscheider

Cancer prognosis can be regarded as estimating the risk of future outcomes from multiple variables. In prognostic signatures, these variables represent expressions of genes that are summed up to calculate a risk score. However, it is a natural phenomenon in living systems that the whole is more than the sum of its parts. We hypothesize that the prognostic po

Ayaka Ishikawa

This paper gives the quantum walks determined by graph zeta functions. The result enables us to obtain the characteristic polynomial of the transition matrix of the quantum walk, and it determines the behavior of the quantum walk. We treat finite graphs allowing multi-edges and multi-loops.

Xinyan Zhang, Jialin Chen, Ruoxi Chen, Chan Wang

The judicious design of electromagnetic boundary provides a crucial route to control light-matter interactions, and it is thus fundamental to basic science and practical applications. General design approaches rely on the manipulation of bulk properties of superstrate or substrate and on the modification of boundary geometries. Due to the recent advent of me

Hazrat Ali, Shafaq Murad, Zubair Shah

Generative models are becoming popular for the synthesis of medical images. Recently, neural diffusion models have demonstrated the potential to generate photo-realistic images of objects. However, their potential to generate medical images is not explored yet. In this work, we explore the possibilities of synthesis of medical images using neural diffusion m

Jian Wang, Xi Wang, Chaoqun Ma, Lei Kou

With the advent of the electric power big data era, semantic interoperability and interconnection of power data have received extensive attention. Knowledge graph technology is a new method describing the complex relationships between concepts and entities in the objective world, which is widely concerned because of its robust knowledge inference ability. Es

Hiroki Kanagawa, Yusuke Ijima

This paper proposes weight regularization for a faster neural vocoder. Pruning time-consuming DNN modules is a promising way to realize a real-time vocoder on a CPU (e.g. WaveRNN, LPCNet). Regularization that encourages sparsity is also effective in avoiding the quality degradation created by pruning. However, the orders of weight matrices must be contiguous

Reza Dastbasteh, Petr Lisonek

We introduce new sufficient conditions for permutation and monomial equivalence of linear cyclic codes over various finite fields. We recall that monomial equivalence and isometric equivalence are the same relation for linear codes over finite fields. A necessary and sufficient condition for the monomial equivalence of linear cyclic codes through a shift map

M. K. Horton

Learning about density functional approximations (DFAs), or approximations for the exchange-correlation functional, can be intimidating. Density Functional Theory is now one of the primary simulation tools for the practicing chemist or materials scientist, and its accuracy relies upon an appropriate choice of DFA. Over the past decades, there has been extens

Wangtao Lu, Liwei Xu, Tao Yin, Lu Zhang

Based on the perfectly matched layer (PML) technique, this paper develops a high-accuracy boundary integral equation (BIE) solver for acoustic scattering problems in locally defected layered media in both two and three dimensions. The original scattering problem is truncated onto a bounded domain by the PML. Assuming the vanishing of the scattered field on t

Reza Dastbasteh, Petr Lisonek

We present new constructions of binary quantum codes from quaternary linear Hermitian self-dual codes. Our main ingredients for these constructions are nearly self-orthogonal cyclic or duadic codes over F_4. An infinite family of $0$-dimensional binary quantum codes is provided. We give minimum distance lower bounds for our quantum codes in terms of the mini

Jinxiang Lai, Siqian Yang, Guannan Jiang, Xi Wang

Few-shot learning problem focuses on recognizing unseen classes given a few labeled images. In recent effort, more attention is paid to fine-grained feature embedding, ignoring the relationship among different distance metrics. In this paper, for the first time, we investigate the contributions of different distance metrics, and propose an adaptive fusion sc

Kamalakar Thakare, Yash Raghuwanshi, Debi Prosad Dogra, Heeseung Choi

Unsupervised approaches for video anomaly detection may not perform as good as supervised approaches. However, learning unknown types of anomalies using an unsupervised approach is more practical than a supervised approach as annotation is an extra burden. In this paper, we use isolation tree-based unsupervised clustering to partition the deep feature space

Kuan-Hao Huang, Varun Iyer, Anoop Kumar, Sriram Venkatapathy

Syntactically controlled paraphrase generation has become an emerging research direction in recent years. Most existing approaches require annotated paraphrase pairs for training and are thus costly to extend to new domains. Unsupervised approaches, on the other hand, do not need paraphrase pairs but suffer from relatively poor performance in terms of syntac

Kristy Hecht, David González-Ovejero, Dimitrios L. Sounas, Mario Junior Mencagli

Time-varying networks, consisting of lumped elements, such as resistors, capacitors, and inductors, actively modulated in time, have introduced a host of novel wave phenomena and witnessed a remarkable development during recent years. This paper investigates the scattering from a time varying capacitor and how such a load can be fully reflectionless when the

Zhifeng Tang, Zhuo Sun, Nan Yang, Xiangyun Zhou

In this paper, we analyze the average age of information (AoI) and the average peak AoI (PAoI) of a multiuser mobile edge computing (MEC) system where a base station (BS) generates and transmits computation-intensive packets to user equipments (UEs). In this MEC system, we focus on three computing schemes: (i) The local computing scheme where all computation

Hadi Jahanshahi, Mucahit Cevik, Kianoush Mousavi, Ayşe Başar

Bug triaging is a critical task in any software development project. It entails triagers going over a list of open bugs, deciding whether each is required to be addressed, and, if so, which developer should fix it. However, the manual bug assignment in issue tracking systems (ITS) offers only a limited solution and might easily fail when triagers must handle

Reza Bradrania, Davood Pirayesh Neghab

Changes in market conditions present challenges for investors as they cause performance to deviate from the ranges predicted by long-term averages of means and covariances. The aim of conditional asset allocation strategies is to overcome this issue by adjusting portfolio allocations to hedge changes in the investment opportunity set. This paper proposes a n

Anu T. S., Tara Raveendran

Massive multiple-input multiple-output (MIMO) communication systems have drawn significant interest recently in next-generation wireless communications. The use of a large number of antennas in massive MIMO makes the estimation of channel state information very challenging. Accurate channel state information is essential in capitalizing the advantages of the

Haolin Deng, Yanan Zhang, Yangfan Zhang, Wangyang Ying

Event extraction (EE) is crucial to downstream tasks such as new aggregation and event knowledge graph construction. Most existing EE datasets manually define fixed event types and design specific schema for each of them, failing to cover diverse events emerging from the online text. Moreover, news titles, an important source of event mentions, have not gain

Rachael Tappenden, Martin Takáč

This work shows that applying Gradient Descent (GD) with a fixed step size to minimize a (possibly nonconvex) quadratic function is equivalent to running the Power Method (PM) on the gradients. The connection between GD with a fixed step size and the PM, both with and without fixed momentum, is thus established. Consequently, valuable eigen-information is av

Jaime Calles, José Cantarero, Juan Omar Gómez, Gustavo Ortega

We improve the existing lower bounds on the order of counterexamples to a conjecture by P. Schmid, determine some properties of the possible counterexamples of minimum order for each prime, and the isomorphism type of the center of the Frattini subgroup for the counterexamples of order 256. We also show that nonabelian metacyclic p-groups, nonabelian groups

Arka Daw, Kyongmin Yeo, Anuj Karpatne, Levente Klein

Inferring the source information of greenhouse gases, such as methane, from spatially sparse sensor observations is an essential element in mitigating climate change. While it is well understood that the complex behavior of the atmospheric dispersion of such pollutants is governed by the Advection-Diffusion equation, it is difficult to directly apply the gov

Hongsong Feng, Guowei Wei

The human {\it ether-a-go-go} (hERG) potassium channel (K$_\text{v}11.1$) plays a critical role in mediating cardiac action potential. The blockade of this ion channel can potentially lead fatal disorder and/or long QT syndrome. Many drugs have been withdrawn because of their serious hERG-cardiotoxicity. It is crucial to assess the hERG blockade activity in

Huaibo Zhao, Shinya Fujie, Tetsuji Ogawa, Jin Sakuma

During conversations, humans are capable of inferring the intention of the speaker at any point of the speech to prepare the following action promptly. Such ability is also the key for conversational systems to achieve rhythmic and natural conversation. To perform this, the automatic speech recognition (ASR) used for transcribing the speech in real-time must

Yun Cai, Hong Gu, Toby Kenney

Non-Negative Matrix Factorization (NMF) is a widely used dimension reduction method that factorizes a non-negative data matrix into two lower dimensional non-negative matrices: One is the basis or feature matrix which consists of the variables and the other is the coefficients matrix which is the projections of data points to the new basis. The features can

Jie Bai, Xin Fang, Jianwu Fang, Jianru Xue

Pedestrian crossing is one of the most typical behavior which conflicts with natural driving behavior of vehicles. Consequently, pedestrian crossing prediction is one of the primary task that influences the vehicle planning for safe driving. However, current methods that rely on the practically collected data in real driving scenes cannot depict and cover al

Konstantin M. Dyakonov

We discuss the geometry of the unit ball -- specifically, the structure of its extreme points (if any) -- in subspaces of $L^1$ and $L^\infty$ on the circle that are formed by functions with prescribed spectral gaps. A similar issue is considered for kernels of Toeplitz operators in $H^\infty$.

Arthur Sousa de Sena, Pedro H. J. Nardelli, Daniel Benevides da Costa, Petar Popovski

The polarization domain provides an extra degree of freedom (DoF) for improving the performance of multiple-input multiple-output (MIMO) systems. This paper takes advantage of this additional DoF to alleviate practical issues of successive interference cancellation (SIC) in rate-splitting multiple access (RSMA) schemes. Specifically, we propose three dual-po

Kripa Dristi Dihingia, Swagata Saikia, N. Yedukondalu, Supriya Saha

MXenes are rapidly emerging two-dimensional (2D) materials with thickness, composition, and functionalization-dependent outstanding properties having applications in diverse fields. To disclose nano-spintronic applications of 2D-double transition metal (DTM) carbide and nitride-based pristine and surface-functionalized MXenes (M&#39;2M&#34;X2Tx, M&#39; and M

A. Y. Matsuura, Timothy G. Mattson

Quantum computing represents a paradigm shift for computation requiring an entirely new computer architecture. However, there is much that can be learned from traditional classical computer engineering. In this paper, we describe the Parallel Research Kernels (PRK), a tool that was very useful for designing classical parallel computing systems. The PRK are s

Kazuhisa Hoshi, Hiroto Arima, Noriyuki Kataoka, Masayuki Ochi

We report transport properties for layered BiCh2-based (Ch = S, Se) superconductors LaO1-xFxBiS2-ySey (x = 0.2, 0.5, y = 0-1.05) and the observation of weak antilocalization (WAL). Electrical resistivity and Hall coefficients for the Se-poor samples increase with decreasing temperature. The increase becomes less pronounced with increasing Se concentration in

Amir Ahmadi-Javid, Mahla Meskar

This paper presents a new approach for formulating the delivery problem by drones with general energy consumption models where the drones visit a set of places to deliver parcels to customers. Drones can perform multiple trips that start and end at a central depot while visiting several customers along their paths. The problem determines the routing and sche

Yi Chang, Yun Guo, Yuntong Ye, Changfeng Yu

Most of the existing learning-based deraining methods are supervisedly trained on synthetic rainy-clean pairs. The domain gap between the synthetic and real rain makes them less generalized to complex real rainy scenes. Moreover, the existing methods mainly utilize the property of the image or rain layers independently, while few of them have considered thei

Yixuan Pei, Zhiwu Qing, Jun Cen, Xiang Wang

Recent incremental learning for action recognition usually stores representative videos to mitigate catastrophic forgetting. However, only a few bulky videos can be stored due to the limited memory. To address this problem, we propose FrameMaker, a memory-efficient video class-incremental learning approach that learns to produce a condensed frame for each se

Mohammed Y. Abdelsadek, Gunes Karabulut Kurt, Halim Yanikomeroglu

The ultra-dense deployment of interconnected satellites will characterize future low Earth orbit (LEO) mega-constellations. Exploiting this towards a more efficient satellite network (SatNet), this paper proposes a novel LEO SatNet architecture based on distributed massive multiple-input multiple-output (DM-MIMO) technology allowing ground user terminals to

Yunling Shi, Jie Guan, Junfeng Xiao, Huai Zhang

A large amount of data has been accumulated. with the development of the Internet industry. Many problems have been exposed with data explosion: 1. The contradiction between data privacy and data collaborations; 2. The contradiction between data ownership and the right of data usage; 3. The legality of data collection and data usage; 4. The relationship betw

Mengyang Zhao, Yang Liu, Jing Li, Xinhua Zeng

Video anomaly detection (VAD) remains a challenging task in the pattern recognition community due to the ambiguity and diversity of abnormal events. Existing deep learning-based VAD methods usually leverage proxy tasks to learn the normal patterns and discriminate the instances that deviate from such patterns as abnormal. However, most of them do not take fu

Kaiwen Yang, Yanchao Sun, Jiahao Su, Fengxiang He

Data augmentation is a critical contributing factor to the success of deep learning but heavily relies on prior domain knowledge which is not always available. Recent works on automatic data augmentation learn a policy to form a sequence of augmentation operations, which are still pre-defined and restricted to limited options. In this paper, we show that a p