March 2020 arXiv papers — page 133

Henri Lantéri

This book deals with functions allowing to express the dissimilarity (discrepancy) between two data fields or ''divergence functions'' with the aim of applications to linear inverse problems. Most of the divergences found in the litterature are used in the field of information theory to quantify the difference between two probability density

Jimmy Etienne, Sylvain Lefebvre

We seek to cover a parametric domain with a set of evenly spaced bands which number and widthvaries according to a density field. We propose an implicit procedural algorithm, that generates theband pattern from a pixel shader and adapts to changes to the control fields in real time. Each band isuniquely identified by an integer. This allows a wide range of t

Junyang Yuan, Yixuan Ma, Renyuan Li, Huanyu Ma

Employing recent developed magneto-optical trap recoil ion momentum spectroscopy (MOTRIMS) combining cold atom, strong laser pulse, and ultrafast technologies, we study momentum distributions of the multiply ionized cold rubidium (Rb) induced by the elliptically polarized laser pulses (35 fs, $1.3 \times 10^{15}$ W/cm$^2$). The complete vector momenta of Rbn

F. Becattini

In view of the recent polarization measurements in ultra-relativistic heavy ion collisions, we discuss the possibility of a physical meaning of the spin angular momentum in quantum field theory and relativistic hydrodynamics.

Atsushi Togo, Yuta Inoue, Isao Tanaka

We investigated phonon behavior of hexagonal close packed titanium under homogeneous shear deformation corresponding to the $\{10\bar{1}2\}$ twinning mode using first-principles calculation and phonon calculation. By this deformation, we found that a phonon mode located at a point on Brillouin zone boundary is drastically soften increasing the shear and fina

Carlo Carminati, Stefano Marmi, David Sauzin, Alfonso Sorrentino

We consider the minimal average action (Mather's $β$ function) for area preserving twist maps of the annulus. The regularity properties of this function share interesting relations with the dynamics of the system. We prove that the $β$-function associated to a standard-like twist map admits a unique $C^1$-holomorphic complex extension, which coincides wi

Junqiang Cheng, Chenglu Jia, Hui Gao, Wenjun Xu

Vehicle-to-everything (V2X) is considered as one of the most important applications of future wireless communication networks. However, the Doppler effect caused by the vehicle mobility may seriously deteriorate the performance of the vehicular communication links, especially when the channels exhibit a large number of Doppler frequency offsets (DFOs). Ortho

Mohammad Farokhiyan, Mehdi Hosseini, Abdollah Kavousi-Fard

The increase of current uniformity along of a resistive type superconductor fault current limiter (R-SFCL) in the design of this type of limiters is well perceived as an important issue. The non-uniform distribution of current in R-SFCL only increases the current in some superconducting regions, as a result, in the fault conditions, only certain parts of the

C. M. Raiteri, J. A. Acosta Pulido, M. Villata, M. I. Carnerero

4C 71.07 is a high-redshift blazar whose optical radiation is dominated by quasar-like nuclear emission. We here present the results of a spectroscopic monitoring of the source to study its unbeamed properties. We obtained 24 optical spectra at the Nordic Optical Telescope (NOT) and William Herschel Telescope (WHT) and 3 near-infrared spectra at the Telescop

Philippe Laurençot, Christoph Walker

Existence of stationary solutions to a nonlocal fourth-order elliptic obstacle problem arising from the modelling of microelectromechanical systems with heterogeneous dielectric properties is shown. The underlying variational structure of the model is exploited to construct these solutions as minimizers of a suitably regularized energy, which allows us to we

Priyanto Hidayatullah, Xueting Wang, Toshihiko Yamasaki, Tati L. E. R. Mengko

Background and Objective: Object detection is a primary research interest in computer vision. Sperm-cell detection in a densely populated bull semen microscopic observation video presents challenges such as partial occlusion, vast number of objects in a single video frame, tiny size of the object, artifacts, low contrast, and blurry objects because of the ra

Luc Trouche, Ghislaine Gueudet, Birgit Pepin

This article is an updated version of an entry of the Encyclopedia of Mathematics Education (2018). In the same time, it is the seed of the HAL collection DAD-MULTILINGUAL, constituted by the translation of this entry in various languages.The documentational approach to didactics is a theory in mathematics education. Its first aim is to understand teachers&#

Matilde Boschiero, Marco Giordani, Michele Polese, Michele Zorzi

Recent developments in robotics and communication technologies are paving the way towards the use of Unmanned Aerial Vehicles (UAVs) to provide ubiquitous connectivity in public safety scenarios or in remote areas. The millimeter wave (mmWave) spectrum, in particular, has gained momentum since the huge amount of free spectrum available at such frequencies ca

Evgeny Shchepin

The Serpinsky-Knopp curve is characterized as the only curve (up to isometry) that maps a unit segment onto a triangle of a unit area, so for any pair of points in the segment, the square of the distance between their images does not exceed four times the distance between them.

D. Rudneva, A. Zabrodin

We consider elliptic solutions of the semi-discrete BKP equation and derive equations of motion for their poles. The basic tool is the auxiliary linear problem for the wave function.

Alexander S. Kuznetsov, Galbadrakh Dagvadorj, Klaus Biermann, Marzena Szymanska

Optical parametric oscillations (OPOs) - a non-linear process involving the coherent coupling of an optically excited two particle pump state to a signal and an idler states with different energies - is a relevant mechanism for optical amplification as well as for the generation of correlated photons. OPOs require states with well-defined symmetries and ener

X. -P. Cheng, T. An, S. Frey, X. -Y. Hong

We present the observational results from the 43-GHz Very Long Baseline Array (VLBA) observations of 124 compact radio-loud active galactic nuclei (AGNs) that were conducted between 2014 November and 2016 May. The typical dimensions of the restoring beam in each image are about 0.5 mas $\times$ 0.2 mas. The highest resolution of 0.2 mas corresponds to a phys

Konstantin Lotov

If a charged particle bunch propagates near a plasma-vacuum boundary, it excites a surface wave and experiences a force caused by the boundary. For the linearly responding plasma and ultra-relativistic bunch, the spatial distribution of excited fields is calculated, and the force exerted on a short and narrow bunch is approximated by elementary functions. Th

Elisa Thauer, Alexander Ottmann, Philip Schneider, Lucas Möller

Downsizing well-established materials to the nanoscale is a key route to novel functionalities, in particular if different functionalities are merged in hybrid nanomaterials. Hybrid carbon-based hierarchical nanostructures are particularly promising for electrochemical energy storage since they combine benefits of nanosize effects, enhanced electrical conduc

S R Siva Prasad Kochi, M Ramakrishna

A new procedure to capture the shocks has been proposed and is demonstrated for the solutions of two-dimensional Euler equations using discontinuous Galerkin method and overset grids. A discontinuous Galerkin solver using a coarse grid provides the troubled cell data that is used to determine the location of the shock. An overset grid aligned to the shock is

V. V. Bobylev, A. T. Bajkova

The kinematic properties of the Scorpius-Centaurus association were studied using spatial velocities of approximately 700 young T Tauri stars. Their proper motions and trigonometric parallaxes were selected by Zari et al. from the Gaia DR2 catalog, and radial velocities were taken from various sources. The linear expansion coefficients new estimate of the as

Lan Shanquan, Chen Weiru, Liang Xiaoying, Chen Jiexiang

In two dimensional superfluid, annihilation processes of vortices are investigated by numerical simulation within the dissipative Gross-Pitaevskii equation (GPE) model. First, quantum vortex solution is obtained and its fitting function is found. Second, the simulation show that positive and negative vortices accelerate in both x,y directions, until they ann

Yun-guang Lu

It is well-known that due to the lack of a technique to obtain the a-priori $L^{\infty}$ estimate of the artificial viscosity solutions of the Cauchy problem for the one-dimensional Euler-Poisson (or hydrodynamic) model for semiconductors, where the energy equation is replaced by a pressure-density relation, over the past three decades, all solutions of this

Gerald E. Marsh

Variation in total solar irradiance is thought to have little effect on the Earth's surface temperature because of the thermal time constant--the characteristic response time of the Earth's global surface temperature to changes in forcing. This time constant is large enough to smooth annual variations but not necessarily variations having a longer pe

Alexander Gladkov, Sergey Sergeenko

We consider the second order semilinear elliptic system $Δu= p\left( x\right) v^α,$ $Δv= q\left(x\right) u^β,$ where $x \in \mathbf{R}^N,$ $N \geq 3,$ $α$ and $β$ are positive constants, $p$ and $q$ are nonnegative continuous functions. We prove that nontrivial nonnegative entire solutions fail to exist if the functions $p$ and $q$ are of slow decay.

H. W. Ang, Z. Ong, P. Agarwal, A. H. Chan

It has been shown recently that additional information can be obtained from charged particle multiplicity distribution by investigating their modified combinants $C_j$, which exhibit periodic oscillatory behaviour. The modified combinants obtained from experimental data can be expressed in a recurrent form involving the probability of obtaining $N$ charged p

Jack Collins, Ross Brown, Jurgen Leitner, David Howard

The large demand for simulated data has made the reality gap a problem on the forefront of robotics. We propose a method to traverse the gap by tuning available simulation parameters. Through the optimisation of physics engine parameters, we show that we are able to narrow the gap between simulated solutions and a real world dataset, and thus allow more read

Mohit Lamba, Kaushik Mitra

Images captured nowadays are of varying dimensions with smartphones and DSLR's allowing users to choose from a list of available image resolutions. It is therefore imperative for forensic algorithms such as resampling detection to scale well for images of varying dimensions. However, in our experiments, we observed that many state-of-the-art forensic alg

Yuki Shikata, Yoshiko Kanada-En'yo

For study of dipole excitations, a new method of variation after $K$-projection in the framework of antisymmetrized molecular dynamics (AMD) with the deformation $β$ constraint was proposed. The method was applied to $^{10}$Be and $^{16}$O to describe low-energy dipole excitations and found to be a useful and economical approach for dipole excitations. In th

Gary P. T. Choi, Di Qiu, Lok Ming Lui

In this work, we develop a framework for shape analysis using inconsistent surface mapping. Traditional landmark-based geometric morphometrics methods suffer from the limited degrees of freedom, while most of the more advanced non-rigid surface mapping methods rely on a strong assumption of the global consistency of two surfaces. From a practical point of vi

Jinli Zhang, Tianyi Li, Roope Kokkoniemi, Chengyu Yan

We implement a broadly tunable phase shifter for microwaves based on superconducting quantum interference devices (SQUIDs) and study it both experimentally and theoretically. At different frequencies, a unit transmission coefficient, $|S_{21}|=1$, can be theoretically achieved along a curve where the phase shift is controllable by magnetic flux. The fabricat

Sarit Agami

Topological Data Analysis (TDA) is an approach to handle with big data by studying its shape. A main tool of TDA is the persistence diagram, and one can use it to compare data sets. One approach to learn on the similarity between two persistence diagrams is to use the Bottleneck and the Wasserstein distances. Another approach is to fit a parametric model for

Mingxuan Yue, Yaguang Li, Haoze Yang, Ritesh Ahuja

Identifying mobility behaviors in rich trajectory data is of great economic and social interest to various applications including urban planning, marketing and intelligence. Existing work on trajectory clustering often relies on similarity measurements that utilize raw spatial and/or temporal information of trajectories. These measures are incapable of ident

Xingyuan Xu, Mengxi Tan, Bill Corcoran, Jiayang Wu

Optical artificial neural networks (ONNs), analog computing hardware tailored for machine learning, have significant potential for ultra-high computing speed and energy efficiency. We propose a new approach to architectures for ONNs based on integrated Kerr micro-comb sources that is programmable, highly scalable and capable of reaching ultra-high speeds. We

Orest D. Artemovych, Victor A. Bovdi, Mohamed A. Salim

Let R[G] be the group ring of a group G over an associative ring R with unity such that all prime divisors of orders of elements of G are invertible in R. If R is finite and G is a Chernikov (torsion FC-) group, then each R-derivation of R[G] is inner. Similar results also are obtained for other classes of groups G and rings R.

Muhammad Nabeel Asim, Muhammad Usman Ghani, Muhammad Ali Ibrahim, Sheraz Ahmad

In order to provide benchmark performance for Urdu text document classification, the contribution of this paper is manifold. First, it pro-vides a publicly available benchmark dataset manually tagged against 6 classes. Second, it investigates the performance impact of traditional machine learning based Urdu text document classification methodologies by embed

Haijian Sun, Xiang Ma, Rose Qingyang Hu

Federated learning (FL) is an emerging machine learning technique that aggregates model attributes from a large number of distributed devices. Several unique features such as energy saving and privacy preserving make FL a highly promising learning approach for power-limited and privacy sensitive devices. Although distributed computing can lower down the info

Shuyan Zhou, Shruti Rijhwani, John Wieting, Jaime Carbonell

Cross-lingual entity linking (XEL) is the task of finding referents in a target-language knowledge base (KB) for mentions extracted from source-language texts. The first step of (X)EL is candidate generation, which retrieves a list of plausible candidate entities from the target-language KB for each mention. Approaches based on resources from Wikipedia have

Yang Yu, Wen Chen, Lili Wei

In this letter, we present a hybrid iterative decoder for non-binary low density parity check (LDPC) codes over binary erasure channel (BEC), based on which the recursion of the erasure probability is derived to design non-binary LDPC codes with convergence-optimized degree distributions. The resulting one-step decoding tree is cycle-free and achieves lower

Pankaj Kushwaha, Atreyee Sinha, Ranjeev Misra, K. P. Singh

The X-ray, Ultraviolet, Optical emission from radio-quiet AGNs, black hole binaries, and other compact sources, in general, follow a lognormal flux distribution, a linear rms-flux relation, and a (broken) power-law power spectral densities (PSDs). These characteristics are normally attributed to the multiplicative combination of fluctuations in the accretion

Jingyuan Yang, Guang Liu, Yuzhao Mao, Zhiwei Zhao

Task 1 of the DSTC8-track1 challenge aims to develop an end-to-end multi-domain dialogue system to accomplish complex users' goals under tourist information desk settings. This paper describes our submitted solution, Hierarchical Context Enhanced Dialogue System (HCEDS), for this task. The main motivation of our system is to comprehensively explore the p

Hanxiao Zhang, Jingxiong Li, Mali Shen, Yaqi Wang

Segmentation of brain tumors and their subregions remains a challenging task due to their weak features and deformable shapes. In this paper, three patterns (cross-skip, skip-1 and skip-2) of distributed dense connections (DDCs) are proposed to enhance feature reuse and propagation of CNNs by constructing tunnels between key layers of the network. For better

XuZhang, ChenjunZhou, BoGu

How to discover and evaluate the true strength of models quickly and accurately is one of the key challenges in Neural Architecture Search (NAS). To cope with this problem, we propose an Architecture-Driven Weight Prediction (ADWP) approach for neural architecture search (NAS). In our approach, we first design an architecture-intensive search space and then

Michael R. R. Good, Eric V. Linder

We present a modified Schwarzschild solution for a model of evaporation of a black hole with information preservation. By drawing a direct analogy to the quantum pure accelerating mirror (dynamical Casimir effect of a 1D horizon), we derive a Schwarzschild metric with not only the usual Schwarzschild radius but an additional length scale related to the Planc

Ziniu Hu, Yuxiao Dong, Kuansan Wang, Yizhou Sun

Recent years have witnessed the emerging success of graph neural networks (GNNs) for modeling structured data. However, most GNNs are designed for homogeneous graphs, in which all nodes and edges belong to the same types, making them infeasible to represent heterogeneous structures. In this paper, we present the Heterogeneous Graph Transformer (HGT) architec

Yuepeng Wang, Rushi Shah, Abby Criswell, Rong Pan

This paper presents a new technique for migrating data between different schemas. Our method expresses the schema mapping as a Datalog program and automatically synthesizes a Datalog program from simple input-output examples to perform data migration. This approach can transform data between different types of schemas (e.g., relational-to-graph, document-to-

Masanori Adachi, Jihun Yum

We propose the concept of Diederich--Fornæss and Steinness indices on compact pseudoconvex CR manifolds of hypersurface type in terms of the D'Angelo 1-form. When the CR manifold bounds a domain in a complex manifold, under certain additional non-degeneracy condition, those indices are shown to coincide with the original Diederich--Fornæss and Steinness

Animikh Biswas, Randy Price

In this paper, we provide conditions, \emph{based solely on the observed data}, for the global well-posedness, regularity and convergence of the Azouni-Olson-Titi data assimilation algorithm (AOT algorithm) for a Leray-Hopf weak solutions of the three dimensional Navier-Stokes equations (3D NSE). The aforementioned conditions on the observations, which in th

Yerlan Amanbek, Timur Merembayev, Sanjay Srinivasan

The fracture characterization using a geostatistical tool with conditioning data is a computationally efficient tool for subsurface flow and transport applications. The main objective of the paper is to propose a framework of geostatistical method to model the fracture network. In the method, we have chosen neighborhood area to apply the Gaussian Sequential

Yimin Wang, Maoxin Liu, Wen-Long You, Stefano Chesi

We explore the quantum criticality of a two-site model combining quantum Rabi models with hopping interaction. Through a combination of analytical and numerical approaches, we find that the model allows the appearance of a superradiant quantum phase transition (QPT) even in the presence of strong $\mathbf{A}^2$ terms, preventing single-site superradiance. In

Lu Xu, Kotaro Nishimura, Yuxi Fu, Akira Suda

This paper presents the optimization of a dual-chirped optical parametric amplification (DC-OPA) scheme for producing an ultrafast intense infrared (IR) pulse. By employing a total energy of 0.77 J Ti:sapphire pump laser and type-I BBO crystals, an IR pulse energy at the center wavelength of 1.7 $μ$m exceeded 0.1 J using the optimized DC-OPA. By adjusting th

Michele Governale, Bibek Bhandari, Fabio Taddei, Ken-Ichiro Imura

We present a theoretical study of a nanowire made of a three-dimensional topological insulator. The bulk topological insulator is described by a continuum-model Hamiltonian, and the cylindrical-nanowire geometry is modelled by a hard-wall boundary condition. We provide the secular equation for the eigenergies of the systems (both for bulk and surface states)

Wolfgang Altmannshofer, Brian Maddock

A two Higgs doublet model with flavorful Yukawa structure, in which the two doublets give mass to the third and the first two generations respectively, is combined with the twin Higgs mechanism to stabilize the Higgs mass against radiative corrections. We consider both a mirror twin and fraternal twin setup. We identify Higgs signal strength measurements and

Jessica Van Brummelen, Kevin Weng, Phoebe Lin, Catherine Yeo

Vast improvements in natural language understanding and speech recognition have paved the way for conversational interaction with computers. While conversational agents have often been used for short goal-oriented dialog, we know little about agents for developing computer programs. To explore the utility of natural language for programming, we conducted a s

Diogo Pacheco, Alessandro Flammini, Filippo Menczer

Propaganda, disinformation, manipulation, and polarization are the modern illnesses of a society increasingly dependent on social media as a source of news. In this paper, we explore the disinformation campaign, sponsored by Russia and allies, against the Syria Civil Defense (a.k.a. the White Helmets). We unveil coordinated groups using automatic retweets an

Qian Chen, Mengzhe Chen, Bo Li, Wen Wang

With the increased applications of automatic speech recognition (ASR) in recent years, it is essential to automatically insert punctuation marks and remove disfluencies in transcripts, to improve the readability of the transcripts as well as the performance of subsequent applications, such as machine translation, dialogue systems, and so forth. In this paper

Jérôme Nicolas, Simone Assali, Samik Mukherjee, Andriy Lotnyk

Controlling the growth kinetics from the vapor phase has been a powerful paradigm enabling a variety of metastable epitaxial semiconductors such as Sn-containing group IV semiconductors (Si)GeSn. In addition to its importance for emerging photonic and optoelectronic applications, this class of materials is also a rich platform to highlight the interplay betw

Yuanyuan Zhang, Zhengdao Yuan, Qinghua Guo, Zhongyong Wang

Grant-free non-orthogonal multiple access (NOMA) is promising to achieve low latency massive access in Internet of Things (IoT) applications. In grant-free NOMA, pilot signals are often used for user activity detection (UAD) and channel estimation (CE) prior to multiuser detection (MUD) of active users. However, the pilot overhead makes the communications in

Chenglu Jia, Hui Gao, Na Chen, Yuan He

Recently, intelligent reflecting surface (IRS) assisted mmWave networks are emerging, which bear the potential to address the blockage issue of the millimeter wave (mmWave) communication in a more cost-effective way. In particular, IRS is built by passive and programmable electromagnetic elements that can manipulate the mmWave propagation channel into a more

Qian Chen, Zhu Zhuo, Wen Wang, Qiuyun Xu

Spoken language understanding (SLU) is a key component of task-oriented dialogue systems. SLU parses natural language user utterances into semantic frames. Previous work has shown that incorporating context information significantly improves SLU performance for multi-turn dialogues. However, collecting a large-scale human-labeled multi-turn dialogue corpus f

Aditeya Pandey, Yixuan Zhang, John A. Guerra-Gomez, Andrea G. Parker

In the task abstraction phase of the visualization design process, including in "design studies", a practitioner maps the observed domain goals to generalizable abstract tasks using visualization theory in order to better understand and address the users needs. We argue that this manual task abstraction process is prone to errors due to designer bias

Lu Wen, Jingliang Duan, Shengbo Eben Li, Shaobing Xu

Reinforcement learning (RL) is attracting increasing interests in autonomous driving due to its potential to solve complex classification and control problems. However, existing RL algorithms are rarely applied to real vehicles for two predominant problems: behaviours are unexplainable, and they cannot guarantee safety under new scenarios. This paper present

Fernando C. Marques, Rafael Montezuma, André Neves

In this article we prove the strong Morse inequalities for the area functional in codimension one, assuming that the ambient dimension satisfies $3 \leq (n + 1) \leq 7$, in both the closed and the boundary cases.

Wenhan Zhu, Guangtao Zhai, Zongxi Han, Xiongkuo Min

Smartphone is the superstar product in digital device market and the quality of smartphone camera photos (SCPs) is becoming one of the dominant considerations when consumers purchase smartphones. How to evaluate the quality of smartphone cameras and the taken photos is urgent issue to be solved. To bridge the gap between academic research accomplishment and

David Schaich, Raghav G. Jha, Anosh Joseph

We present initial results from ongoing lattice investigations into the thermal phase structure of the Berenstein--Maldacena--Nastase deformation of maximally supersymmetric Yang--Mills quantum mechanics. The phase diagram of the theory depends on both the temperature $T$ and the deformation parameter $μ$, through the dimensionless ratios $T / μ$ and $g \equ

Saurav Manchanda, Khoa Doan, Pranjul Yadav, S. Sathiya Keerthi

This paper addresses the classic problem of regression, which involves the inductive learning of a map, $y=f(x,z)$, $z$ denoting noise, $f:\mathbb{R}^n\times \mathbb{R}^k \rightarrow \mathbb{R}^m$. Recently, Conditional GAN (CGAN) has been applied for regression and has shown to be advantageous over the other standard approaches like Gaussian Process Regress

ZhaoXin Huan, Yulong Wang, Xiaolu Zhang, Lin Shang

Neural networks are vulnerable to adversarial examples, which are malicious inputs crafted to fool pre-trained models. Adversarial examples often exhibit black-box attacking transferability, which allows that adversarial examples crafted for one model can fool another model. However, existing black-box attack methods require samples from the training data di

Arnulf Jentzen, Timo Welti

In spite of the accomplishments of deep learning based algorithms in numerous applications and very broad corresponding research interest, at the moment there is still no rigorous understanding of the reasons why such algorithms produce useful results in certain situations. A thorough mathematical analysis of deep learning based algorithms seems to be crucia

Hirohisa Oda, Kohei Nishio, Takayuki Kitasaka, Hizuru Amano

This paper presents a visualization method of intestine (the small and large intestines) regions and their stenosed parts caused by ileus from CT volumes. Since it is difficult for non-expert clinicians to find stenosed parts, the intestine and its stenosed parts should be visualized intuitively. Furthermore, the intestine regions of ileus cases are quite ha

Tetsuo Inoshita, Yuichi Nakatani, Katsuhiko Takahashi, Asuka Ishii

The major approaches of transfer learning in computer vision have tried to adapt the source domain to the target domain one-to-one. However, this scenario is difficult to apply to real applications such as video surveillance systems. As those systems have many cameras installed at each location regarded as source domains, it is difficult to identify the prop

Hong Zhang, Zheyang Wu

Combining dependent tests of significance has broad applications but the $p$-value calculation is challenging. Current moment-matching methods (e.g., Brown's approximation) for Fisher's combination test tend to significantly inflate the type I error rate at the level less than 0.05. It could lead to significant false discoveries in big data analyses.

Junnan Li, Caiming Xiong, Richard Socher, Steven Hoi

Training deep object detectors requires significant amount of human-annotated images with accurate object labels and bounding box coordinates, which are extremely expensive to acquire. Noisy annotations are much more easily accessible, but they could be detrimental for learning. We address the challenging problem of training object detectors with noisy annot

Shigeo Kawata

The document describes a numerical algorithm for plasms and fluids by the Lagrange method, in which the spatial meshes follow the plasma and fluid behavior. Through the mesh wall the plasma and the fluid do not escape. The 3D Lagrange code is originally designed to simulate a Gold cone plasma, which is relevant to confine an imploding fuel in the cone in ine

Hongkai Chen, Nicola Paoletti, Scott A. Smolka, Shan Lin

Even though model predictive control (MPC) is currently the main algorithm for insulin control in the artificial pancreas (AP), it usually requires complex online optimizations, which are infeasible for resource-constrained medical devices. MPC also typically relies on state estimation, an error-prone process. In this paper, we introduce a novel approach to

Anton Tsitsulin, Marina Munkhoeva, Bryan Perozzi

Graph comparison is a fundamental operation in data mining and information retrieval. Due to the combinatorial nature of graphs, it is hard to balance the expressiveness of the similarity measure and its scalability. Spectral analysis provides quintessential tools for studying the multi-scale structure of graphs and is a well-suited foundation for reasoning

Wenbiao Zhao, Xuehu Zhu, Lixing Zhu

The research described herewith investigates detecting change points of means and of variances in a sequence of observations. The number of change points can be divergent at certain rate as the sample size goes to infinity. We define a MOSUM-based objective function for this purpose. Unlike all existing MOSUM-based methods, the novel objective function exhib

Erik W. Martin, Jesse B. Hopkins, Tanja Mittag

The condensation of biomolecules into biomolecular condensates via liquid-liquid phase separation (LLPS) is a ubiquitous mechanism that drives cellular organization. To enable these functions, biomolecules have evolved to drive LLPS and facilitate partitioning into biomolecular condensates. Determining the molecular features of proteins that encode LLPS will

Katsuhsia Taguchi, Daisuke Oshima, Yusuke Yamaguchi, Tatsuki Hashimoto

We theoretically investigate the spin Hall conductivity (SHC) in topological Dirac semimetals (TDSMs) whose Dirac points are protected by rotational symmetry. On the basis of a general phase diagram of the system with time-reversal, inversion and four-fold rotational symmetries, we reveal that the SHC is sensitive to the phase to which the system belong. The

Devi Parikh

As a lay user creates an art piece using an interactive generative art tool, what, if anything, do the choices they make tell us about them and their preferences? These preferences could be in the specific generative art form (e.g., color palettes, density of the piece, thickness or curvatures of any lines in the piece); predicting them could lead to a smart

Sina Sajjadi, Mohammad Reza Ejtehadi, Fakhteh Ghanbarnejad

We first propose a quantitative approach to detect high risk outbreaks of independent and coinfective SIR dynamics on three empirical networks: a school, a conference and a hospital contact network. This measurement is based on the k-means clustering method and identifies proper samples for calculating the mean outbreak size and the outbreak probability. The

Masakazu Yoshimura, Murilo M. Marinho, Kanako Harada, Mamoru Mitsuishi

Surgical robots are used to perform minimally invasive surgery and alleviate much of the burden imposed on surgeons. Our group has developed a surgical robot to aid in the removal of tumors at the base of the skull via access through the nostrils. To avoid injuring the patients, a collision-avoidance algorithm that depends on having an accurate model for the

Paolo Alba, Rene Bellwied, Valentina Mantovani-Sarti, Jacquelyn Noronha-Hostler

We study chemical freeze-out parameters for heavy-ion collisions by performing two different thermal analyses. We analyze results from thermal fits for particle yields, as well as, net-charge fluctuations in order to characterize the chemical freeze-out. The Hadron Resonance Gas (HRG) model is employed for both methods. By separating the light hadrons from t

Mario E. Villanueva, Colin Jones, Boris Houska

This paper introduces a framework for solving time-autonomous nonlinear infinite horizon optimal control problems, under the assumption that all minimizers satisfy Pontryagin's necessary optimality conditions. In detail, we use methods from the field of symplectic geometry to analyze the eigenvalues of a Koopman operator that lifts Pontryagin's diffe

Elizabeth Harris, Bishnu Lamichhane, Quoc Thong Le Gia

We compare a recently proposed multivariate spline based on mixed partial derivatives with two other standard splines for the scattered data smoothing problem. The splines are defined as the minimiser of a penalised least squares functional. The penalties are based on partial differentiation operators, and are integrated using the finite element method. We c

Arnab Paul, Mamdudul Haque Khan, M. Muktadir Rahman, Tanvir Zaman Khan

With a view to managing the increasing traffic in computer networks, round robin arbiter has been proposed to work with packet switching system to have increased speed in providing access and scheduling. Round robin arbiter is a doorway to a particular bus based on request along with equal priority and gives turns to devices connected to it in a cyclic order

Amartya Shankha Biswas, Michal Dory, Mohsen Ghaffari, Slobodan Mitrović

Over the past decade, there has been increasing interest in distributed/parallel algorithms for processing large-scale graphs. By now, we have quite fast algorithms -- usually sublogarithmic-time and often $poly(\log\log n)$-time, or even faster -- for a number of fundamental graph problems in the massively parallel computation (MPC) model. This model is a w

Jeet Mohapatra, Ching-Yun Ko, Tsui-Wei, Weng

The fragility of modern machine learning models has drawn a considerable amount of attention from both academia and the public. While immense interests were in either crafting adversarial attacks as a way to measure the robustness of neural networks or devising worst-case analytical robustness verification with guarantees, few methods could enjoy both scalab

Diego Granziol, Xingchen Wan, Samuel Albanie, Stephen Roberts

We analyse and explain the increased generalisation performance of iterate averaging using a Gaussian process perturbation model between the true and batch risk surface on the high dimensional quadratic. We derive three phenomena \latestEdits{from our theoretical results:} (1) The importance of combining iterate averaging (IA) with large learning rates and r

Nathan Bucki, Junseok Lee, Mark W. Mueller

We present RAPPIDS: a novel collision checking and planning algorithm for multicopters that is capable of quickly finding local collision-free trajectories given a single depth image from an onboard camera. The primary contribution of this work is a new pyramid-based spatial partitioning method that enables rapid collision detection between candidate traject

Sergey Fomin, Kiyoshi Igusa, Kyungyong Lee

We show that for any positive integer $n$, there exists a quiver $Q$ with $O(n^2)$ vertices and $O(n^2)$ edges such that any quiver on $n$ vertices is a full subquiver of a quiver mutation equivalent to $Q$. We generalize this statement to skew-symmetrizable matrices and obtain other related results. In particular, we show that any quiver is a full subquiver

Dasom Lee, Shu Yang, Lin Dong, Xiaofei Wang

Complementary features of randomized controlled trials (RCTs) and observational studies (OSs) can be used jointly to estimate the average treatment effect of a target population. We propose a calibration weighting estimator that enforces the covariate balance between the RCT and OS, therefore improving the trial-based estimator's generalizability. Exploi

Xingyou Song, Yuxiang Yang, Krzysztof Choromanski, Ken Caluwaerts

Learning adaptable policies is crucial for robots to operate autonomously in our complex and quickly changing world. In this work, we present a new meta-learning method that allows robots to quickly adapt to changes in dynamics. In contrast to gradient-based meta-learning algorithms that rely on second-order gradient estimation, we introduce a more noise-tol

X. Luan, J. -B. Béguin, A. P. Burgers, Z. Qin

Integrating nanophotonics and cold atoms has drawn increasing interest in recent years due to diverse applications in quantum information science and the exploration of quantum many-body physics. For example, dispersion-engineered photonic crystal waveguides (PCWs) permit not only stable trapping and probing of ultracold neutral atoms via interactions with g

Jose J. Bouza, Chun-Hao Yang, David Vaillancourt, Baba C. Vemuri

Geometric deep learning has attracted significant attention in recent years, in part due to the availability of exotic data types for which traditional neural network architectures are not well suited. Our goal in this paper is to generalize convolutional neural networks (CNN) to the manifold-valued image case which arises commonly in medical imaging and com

A. Rancati, N. Pournaghavi, M. F. Islam, A. Debernardi

Using first-principles density functional theory calculations, combined with a topological analysis, we have investigated the electronic properties of $Cd_3As_2$ and $Na_3Bi$ Dirac topological semimetals doped with non-magnetic and magnetic impurities. Our systematic analysis shows that the selective breaking of the inversion, rotational and time-reversal sy

Kyle Willick, Jonathan Baugh

Suspended carbon nanotubes are known to support self-driven oscillations due to electromechanical feedback under certain conditions, including low temperatures and high mechanical quality factors. Prior reports identified signatures of such oscillations in Kondo or high-bias transport regimes. Here, we observe self-driven oscillations that give rise to signi

Marius Hobbhahn, Agustinus Kristiadi, Philipp Hennig

In Bayesian Deep Learning, distributions over the output of classification neural networks are often approximated by first constructing a Gaussian distribution over the weights, then sampling from it to receive a distribution over the softmax outputs. This is costly. We reconsider old work (Laplace Bridge) to construct a Dirichlet approximation of this softm

Nicholas C. White, Sandra M. Troian, Jeffrey B. Jewell, Curt J. Cutler

Direct detection of dark energy or modified gravity may finally be within reach due to ultrasensitive instrumentation such as atom interferometry capable of detecting incredibly small scale accelerations. Forecasts, constraints and measurement bounds can now too perhaps be estimated from accurate numerical simulations of the fifth force and its Laplacian fie

Anna Y. Q. Ho, D. A. Perley, S. R. Kulkarni, D. Z. J. Dong

We present ZTF18abvkwla (the "Koala"), a fast blue optical transient discovered in the Zwicky Transient Facility (ZTF) One-Day Cadence (1DC) Survey. ZTF18abvkwla has a number of features in common with the groundbreaking transient AT2018cow: blue colors at peak ($g-r\approx-0.5$ mag), a short rise time from half-max of under two days, a decay time to

Chris Godsil, Maxwell Levit, Olha Silina

A certain signed adjacency matrix of the hypercube, which Hao Huang used last year to resolve the sensitivity conjecture, is closely related to the unique, 4-cycle free, 2-fold cover of the hypercube. We develop a framework in which this connection is a natural first example of the relationship between group labeled adjacency matrices with few eigenvalues, a