February 2021 arXiv papers — page 11

Aurélie Boisbunon, Carlo Fanara, Ingrid Grenet, Jonathan Daeden

The Zoetrope Genetic Programming (ZGP) algorithm is based on an original representation for mathematical expressions, targeting evolutionary symbolic regression.The zoetropic representation uses repeated fusion operations between partial expressions, starting from the terminal set. Repeated fusions within an individual gradually generate more complex express

Jianqing Yang, Jianrong Zhou, Xingfen Jiang, Jinhao Tan

The China Spallation Neutron Source (CSNS) operates in pulsed mode and has a high neutron flux. This provides opportunities for energy resolved neutron imaging by using the TOF (Time Of Flight) approach. An Energy resolved neutron imaging instrument (ERNI) is being built at the CSNS but significant challenges for the detector persist because it simultaneousl

Alexander Chesnokov

A laminar flow of a thin layer of mud down an inclined plane under the action of gravity is considered. The instability of a film flow and the formation of finite amplitude waves are studied in the framework of both two-dimensional governing equations of a power-law fluid and its depth-averaged hyperbolic simplification. Conditions of roll waves existence fo

Shunsuke Yamada, Kazuhiro Yabana

We theoretically investigate high harmonic generation (HHG) from silicon thin films with thicknesses from a few atomic layers to a few hundreds of nanometers, to determine the most efficient thickness for producing intense HHG in the reflected and transmitted pulses. For this purpose, we employ a few theoretical and computational methods. The most sophistica

V. Almeida, J. J. Betancor, J. C. Fariña, L. Rodríguez-Mesa

In this paper we consider Littlewood-Paley functions defined by the semigroups associated with the operator $\mathcal{A}=-\fracΔ{2}-x\nabla$ in the inverse Gaussian setting for Banach valued functions. We characterize the uniformly convex and smooth Banach spaces by using $L^p(\mathbb{R}^n,γ_{-1})$- properties of the $\mathcal{A}$-Littlewood-Paley functions.

Alexandre Bruckert, Marc Christie, Olivier Le Meur

In the process of making a movie, directors constantly care about where the spectator will look on the screen. Shot composition, framing, camera movements or editing are tools commonly used to direct attention. In order to provide a quantitative analysis of the relationship between those tools and gaze patterns, we propose a new eye-tracking database, contai

Abdolhosein Hashemizadeh, Simon P. Driver, Luke J. M. Davies, Aaron S. G. Robotham

Using high-resolution Hubble Space Telescope imaging data, we perform a visual morphological classification of $\sim 36,000$ galaxies at $z < 1$ in the DEVILS/COSMOS region. As the main goal of this study, we derive the stellar mass function (SMF) and stellar mass density (SMD) sub-divided by morphological types. We find that visual morphological classificat

Vikrant V. Jadhav, Sindhu Pandey, Annapurni Subramaniam, Ram Sagar

King 2, one of the oldest clusters in the Milky Way, with an age of $\sim$ 6 Gyr and distance of $\sim 5700$ pc, has been observed with UVIT payload on the \textit{ASTROSAT}. With membership information derived from {\it Gaia} EDR3, the cluster is found to have 39 blue straggler stars (BSSs). We created multi-wavelength spectra-energy distributions (SED) of

Gabriele Martelli, Paolo Ciafaloni, Mauro Raggi

The PADME experiment is searching for the Dark Photon $A&#39;$ in the $e^{+}e^{-} \to γA&#39;$ process, assuming a $A&#39;$ decay into invisible particles. In extended Dark Sector models, a Dark Higgs $h&#39;$ can be produced alongside $A&#39;$ in the process $e^{+}e^{-} \to h&#39; A&#39;$. If the $h&#39;$ mass is greater than twice the $A&#39;$ mass the fin

David Hasler, Benjamin Hinrichs, Oliver Siebert

We show the existence of ground states in the massless spin boson model without any infrared regularization. Our proof is non-perturbative and relies on a compactness argument. It works for arbitrary values of the coupling constant under the hypothesis that the second derivative of the ground state energy as a function of a constant external magnetic field i

Baturay Ozgurun, Mujdat Cetin

We propose a novel method that records a single compressive hologram in a short time and extracts the depth of a scene from that hologram using a stereo disparity technique. The method is verified with numerical simulations, but there is no restriction on adapting this into an optical experiment. In the simulations, a computer-generated hologram is first sam

Hao Zhang, Miao Qiao, Jeffrey Xu Yu, Hong Cheng

In this work, we study the problem of co-optimize communication, pre-computing, and computation cost in one-round multi-way join evaluation. We propose a multi-way join approach ADJ (Adaptive Distributed Join) for complex join which finds one optimal query plan to process by exploring cost-effective partial results in terms of the trade-off between pre-compu

Jaemin Yoo, Dongkyu Lee, Jimo Lee, Taehyeong Kim

Atmospheric pressure plasma (APP) generates highly reactive species that are useful for surface activations. We demonstrate a fast regeneration of iron oxides, that are popular catalysts in various industrial processes, using microwave-driven argon APP under ambient condition. The surface treatment of hematite powder by the APP with a small portion of hydrog

Ali Bereyhi, Saba Asaad, Ralf R. Müller

Oversampled adaptive sensing (OAS) is a Bayesian framework recently proposed for effective sensing of structured signals in a time-limited setting. In contrast to the conventional blind oversampling, OAS uses the prior information on the signal to construct posterior beliefs sequentially. These beliefs help in constructive oversampling which iteratively evol

Yizhong Liu, Jianwei Liu, Marcos Antonio Vaz Salles, Zongyang Zhang

Sharding is the prevalent approach to breaking the trilemma of simultaneously achieving decentralization, security, and scalability in traditional blockchain systems, which are implemented as replicated state machines relying on atomic broadcast for consensus on an immutable chain of valid transactions. Sharding is to be understood broadly as techniques for

Zhixun Cheng, Yuming Wang, Rui Liu

The Extreme-ultraviolet Variability Experiment (EVE) onboard the Solar Dynamics Observatory (SDO) detects the solar EUV spectra with high temporal cadence and spectral resolution. The wavelength shifts of emission lines provide key information of the dynamics of the Sun. However, some of EVE spectral observations are influenced by the non-uniformly distribut

Noritaka Shimizu, Tomoaki Togashi, Yutaka Utsuno

$β$-decay half-lives of neutron-rich nuclei around $N=82$ are key data to understand the $r$-process nucleosynthesis. We performed large-scale shell-model calculations in this region using a newly constructed shell-model Hamiltonian, and successfully described the low-lying spectra and half-lives of neutron-rich $N=82$ and $N=81$ isotones with $Z=42-49$ in a

Zun Li, Congyan Lang, Liqian Liang, Tao Wang

With the aim of matching a pair of instances from two different modalities, cross modality mapping has attracted growing attention in the computer vision community. Existing methods usually formulate the mapping function as the similarity measure between the pair of instance features, which are embedded to a common space. However, we observe that the relatio

Joan Josep Ferrando, Juan Antonio Sáez

The necessary and sufficient conditions for a three-dimensional Riemannian metric to admit a group of isometries of dimension $r$ acting on s-dimensional orbits are obtained. These conditions are Intrinsic, Deductive, Explicit and ALgorithmic and they offer an IDEAL labeling that improves previously known invariant studies.

Belén Maté, Stephanie Cazaux, Miguel Angel Satorre, Germán Molpeceres

Context. The diffusion of volatile species on amorphous solid water ice affects the chemistry on dust grains in the interstellar medium as well as the trapping of gases enriching planetary atmospheres or present in cometary material. Aims. The aim of the work is to provide diffusion coefficients of CH$_4$ on amorphous solid water (ASW), and to understand how

Andreas Liesenfeld, Gábor Parti, Yu-Yin Hsu, Chu-Ren Huang

This paper examines gender and age salience and (stereo)typicality in British English talk with the aim to predict gender and age categories based on lexical, phrasal and turn-taking features. We examine the SpokenBNC, a corpus of around 11.4 million words of British English conversations and identify behavioural differences between speakers that are labelle

Dmitry A. Duev, Bryce T. Bolin, Matthew J. Graham, Michael S. P. Kelley

We present Tails, an open-source deep-learning framework for the identification and localization of comets in the image data of the Zwicky Transient Facility (ZTF), a robotic optical time-domain survey currently in operation at the Palomar Observatory in California, USA. Tails employs a custom EfficientDet-based architecture and is capable of finding comets

Micha Sende, Melanie Schranz, Gianluca Prato, Etienne Brosse

Engineering swarms of cyber-physical systems (CPSs) is a complex process. We present the CPSwarm workbench that creates an automated design workflow to ease this process. This formalized workflow guides the user from modeling, to code generation, to deployment, both in simulation and on CPS hardware platforms. The workbench combines existing and emerging too

Seokgi Kim, Jihye Park, Kihong Seong, Namwoo Cho

The world today is experiencing an abundance of music like no other time, and attempts to group music into clusters have become increasingly prevalent. Common standards for grouping music were songs, artists, and genres, with artists or songs exploring similar genres of music seen as related. These clustering attempts serve critical purposes for various stak

Quyu Kong, Manuel Garcia-Herranz, Ivan Dotu, Manuel Cebrian

Contact tracing has been extensively studied from different perspectives in recent years. However, there is no clear indication of why this intervention has proven effective in some epidemics (SARS) and mostly ineffective in some others (COVID-19). Here, we perform an exhaustive evaluation of random testing and contact tracing on novel superspreading random

Zeinab Toghani, Luis Gaggero

There are many possible definitions of derivatives, here we present some and present one that we have called generalized that allows us to put some of the others as a particular case of this but, what interests us is to determine that there is an infinite number of possible definitions of fractional derivatives, all are correct as differential operators each

Aviv Karnieli, Roei Remez, Ido Kaminer, Ady Arie

This comment on the Phys. Rev. A paper &#34;Nonlinear quantum effects in electromagnetic radiation of a vortex electron&#34; by Karlovets and Pupasov-Maximov [Phys. Rev. A 103, 12214 (2021)] addresses their criticism of the combined experimental and theoretical study &#34;Observing the quantum wave nature of free electrons through spontaneous emission&#34; b

A. Fraser-McKelvie, L. Cortese, J. van de Sande, J. J. Bryant

Galaxy internal structure growth has long been accused of inhibiting star formation in disc galaxies. We investigate the potential physical connection between the growth of dispersion-supported stellar structures (e.g. classical bulges) and the position of galaxies on the star-forming main sequence at $z\sim0$. Combining the might of the SAMI and MaNGA galax

Parvaneh Asghari, Seyyed Hamid Haj Seyyed Javadi

Security is one of the main issues in Internet of Things (IoT). Encryption plays a curtail role in making these systems secure. Substitution Box (S-Box) has an effective impact in block encryption methods. Due to the restricted resource capacities of IoT nodes, providing a lightweight S-Box is a challenging problem. This paper presents a key-dependent S-Box

Hechao Chen, Jiayan Yang, Junchao Hong, Haidong Li

Coronal mass ejections (CMEs) and coronal jets are two types of common solar eruptive phenomena, which often independently happen at different spatial scales. In this work, we present a stereoscopic observation of a large-scale CME flux rope arising from an unwinding blowout jet in a multipolar complex magnetic system. Based on a multi-band observational ana

Sania Gul, Muhammad Salman Khan, Syed Waqar Shah

In this paper, we formulate a blind source separation (BSS) framework, which allows integrating U-Net based deep learning source separation network with probabilistic spatial machine learning expectation maximization (EM) algorithm for separating speech in reverberant conditions. Our proposed model uses a pre-trained deep learning convolutional neural networ

Shohei Kubota, Hideaki Hayashi, Tomohiro Hayase, Seiichi Uchida

The interpretability of neural networks (NNs) is a challenging but essential topic for transparency in the decision-making process using machine learning. One of the reasons for the lack of interpretability is random weight initialization, where the input is randomly embedded into a different feature space in each layer. In this paper, we propose an interpre

Zhizhou Yu, Guohuan Xiong, Lifa Zhang

With the rapidly increasing integration density and power density in nanoscale electronic devices, the thermal management concerning heat generation and energy harvesting becomes quite crucial. Since phonon is the major heat carrier in semiconductors, thermal transport due to phonons in mesoscopic systems has attracted much attention. In quantum transport st

Sung-Hong Park, K. D. Leka, Kanya Kusano

In our earlier study of this series (Park et al. 2020, Paper I), we examined the hemispheric sign preference (HSP) of magnetic helicity flux $dH/dt$ across photospheric surfaces of 4802 samples of 1105 unique active regions (ARs) observed during solar cycle 24. Here, we investigate any association of the HSP, expressed as a degree of compliance, with flaring

Claudio Teixeira, Lucas Giusti, Jorge Soares, Joel dos Santos

The Brazilian commercial aviation system achieved the first position among Latin American countries and the fifteenth place worldwide on the Revenue Passenger-Kilometer (RPK) ranking. The availability of data regarding flight, including flight information and meteorological conditions, enables studies about the Brazilian flight system, such as flight delays

Fu-En Yang, Jing-Cheng Chang, Yuan-Hao Lee, Yu-Chiang Frank Wang

Generating videos with content and motion variations is a challenging task in computer vision. While the recent development of GAN allows video generation from latent representations, it is not easy to produce videos with particular content of motion patterns of interest. In this paper, we propose Dual Motion Transfer GAN (Dual-MTGAN), which takes image and

K. Mizuyama, T. Dieu Thuy, N. Hoang Tung, D. Quang Tam

The Jost function formalism is extended with use of the complex potential in this paper. We derive the Jost function by taking into account the dual state which is defined by the complex conjugate the complex Hamiltonian. By using the unitarity of the S-matrix which is defined by the Jost function, the optical theorem with the complex potential is also deriv

Zeng Ting, Xiang Hongxin, Xie Cheng, Yang Yun

Zero-Shot Learning (ZSL) is an emerging research that aims to solve the classification problems with very few training data. The present works on ZSL mainly focus on the mapping of learning semantic space to visual space. It encounters many challenges that obstruct the progress of ZSL research. First, the representation of the semantic feature is inadequate

C. Bacaksiz, D. Šabani, R. M. Menezes, M. V. Milošević

After the discovery of magnetism in monolayer CrI3, the magnetic properties of different 2D materials from the chromium-trihalide family are intuitively assumed to be similar, yielding magnetic anisotropy from the spin-orbit coupling on halide ligands. Here we reveal significant differences between the CrI3 and CrBr3 magnetic monolayers in their magnetic ani

Yang Wang, Yuting Qian, Meng Yang, Hongxiang Chen

The nodal line semimetals have attracted much attention due to their unique topological electronic structure and exotic physical properties. A genuine nodal line semimetal is qualified by the presence of Dirac nodes along a line in the momentum space that are protected against the spin-orbit coupling. In addition, it requires that the Dirac points lie close

Jinlin Xiang, Shane Colburn, Arka Majumdar, Eli Shlizerman

In recent years, Convolutional Neural Networks (CNNs) have enabled ubiquitous image processing applications. As such, CNNs require fast runtime (forward propagation) to process high-resolution visual streams in real time. This is still a challenging task even with state-of-the-art graphics and tensor processing units. The bottleneck in computational efficien

Cheng Xie, Ting Zeng, Hongxin Xiang, Keqin Li

New categories can be discovered by transforming semantic features into synthesized visual features without corresponding training samples in zero-shot image classification. Although significant progress has been made in generating high-quality synthesized visual features using generative adversarial networks, guaranteeing semantic consistency between the se

Mikhail Kapranov, Vadim Schechtman

Algebraic structures involving both multiplications and comultiplications (such as, e.g., bialgebras or Hopf algebras) can be encoded using PROPs (categories with PROducts and Permutations) of Adams and MacLane. To encode such structures on objects of a braided monoidal category, we need PROBs (braided analogs of PROPs). Colored PROBs correspond to multi-sor

Chun-Hsien Lin, Bing-Fei Wu

Although deep convolutional networks have achieved great performance in face recognition tasks, the challenge of domain discrepancy still exists in real world applications. Lack of domain coverage of training data (source domain) makes the learned models degenerate in a testing scenario (target domain). In face recognition tasks, classes in two domains are u

Seogkyu Jeon, Pilhyeon Lee, Kibeom Hong, Hyeran Byun

Face aging is the task aiming to translate the faces in input images to designated ages. To simplify the problem, previous methods have limited themselves only able to produce discrete age groups, each of which consists of ten years. Consequently, the exact ages of the translated results are unknown and it is unable to obtain the faces of different ages with

Kazunori Kodaka

We will introduce the notion of strong Morita equivalence for completely positive linear maps and study its basic properties. Also, we will discuss the relation between strong Morita equivalence for bounded $C^*$-bimodule linear maps and strong Morita equivalence for completely positive linear maps. Furthermore, we will show that if two unital $C^*$-algebras

Ying-Ying Li, Bo Gao, Ying Han, Bing-Kun Chen

The tunable bandgap from 0.3 eV to 2 eV of black phosphorus (BP) makes it to fill the gap in graphene. When studying the properties of BP more comprehensive, scientists have discovered that many two-dimensional materials, such as tellurene, antimonene, bismuthene, indium selenide and tin sulfide, have similar structures and properties to black phosphorus thu

Jie Zhao, Xinghua Zhu, Jianzong Wang, Jing Xiao

In federated learning (FL), fair and accurate measurement of the contribution of each federated participant is of great significance. The level of contribution not only provides a rational metric for distributing financial benefits among federated participants, but also helps to discover malicious participants that try to poison the FL framework. Previous me

Farshad Saberi-Movahed, Donald W Brenner

Water near detonation nanodiamonds (DNDs) forms a Hydrogen Bond (HB) network, whose strength influences DNDs&#39; fluorescence intensity and colloidal stability in aqueous suspensions. However, effects of dissolved ions and DND&#39;s surface chemistry on dynamics of water that manifest in rupture and formation of HBs still remain to be elucidated. Thus, we c

Ziji Xiang, Lu Chen, Kuan-Wen Chen, Colin Tinsman

Within condensed-matter systems, strong electronic interactions often lead to exotic quantum phases. A recent manifestation of this is the unexpected observation of magnetic quantum oscillations and metallic thermal transport, both properties of systems with Fermi surfaces of itinerant quasiparticles, in the Kondo insulators SmB6 and YbB$_{12}$. To understan

Andrea Galeotti, Benjamin Golub, Sanjeev Goyal, Rithvik Rao

Consider a coordination game played on a network, where agents prefer taking actions closer to those of their neighbors and to their own ideal points in action space. We explore how the welfare outcomes of a coordination game depend on network structure and the distribution of ideal points throughout the network. To this end, we imagine a benevolent or adver

Victor Pacheco-Peña, Nader Engheta

Controlling amplitude, phase and polarization of electromagnetic waves is key for a full manipulation of wave-matter interactions. The Brewster angle is one of the important features in this context. Here, we exploit metamaterial concepts with a time-modulated permittivity to propose the temporal equivalent of the spatial Brewster angle, a concept we call te

Haitong Ma, Xiangteng Zhang, Shengbo Eben Li, Ziyu Lin

Receding horizon control (RHC) is a popular procedure to deal with optimal control problems. Due to the existence of state constraints, optimization-based RHC often suffers the notorious issue of infeasibility, which strongly shrinks the region of controllable state. This paper proposes a generalized control barrier function (CBF) to enlarge the feasible reg

Zixing Song, Xiangli Yang, Zenglin Xu, Irwin King

Semi-supervised learning (SSL) has tremendous value in practice due to its ability to utilize both labeled data and unlabelled data. An important class of SSL methods is to naturally represent data as graphs such that the label information of unlabelled samples can be inferred from the graphs, which corresponds to graph-based semi-supervised learning (GSSL)

Shuchang Liu, Fei Sun, Yingqiang Ge, Changhua Pei

Slate recommendation generates a list of items as a whole instead of ranking each item individually, so as to better model the intra-list positional biases and item relations. In order to deal with the enormous combinatorial space of slates, recent work considers a generative solution so that a slate distribution can be directly modeled. However, we observe

Ashish Shrivastava, Alan Gatherer, Tong Sun, Sushma Wokhlu

Over the last decade the relative latency of access to shared memory by multicore increased as wire resistance dominated latency and low wire density layout pushed multiport memories farther away from their ports. Various techniques were deployed to improve average memory access latencies, such as speculative pre-fetching and branch-prediction, often leading

Yi-Ling Chen, Chun-Chung Chen, Yu-Ying Mei, Ning Zhou

Using miniscope recordings of calcium fluorescence signals in the CA1 region of the hippocampus of mice, we monitor the neural activity of hippocampal regions while the animals are freely moving in an open chamber. Using a data-driven statistical modeling approach, the statistical properties of the recorded data are mapped to spin-glass models with pairwise

Zhiqing Wei, Yadong Zhao, Xinyi Liu, Zhiyong Feng

Location fingerprint (LF) has been widely applied in indoor positioning. However, the existing studies on LF mostly focus on the fingerprint of WiFi below 6 GHz, bluetooth, ultra wideband (UWB), etc. The LF with millimeter-wave (mmWave) was rarely addressed. Since mmWave has the characteristics of narrow beam, fast signal attenuation and wide bandwidth, etc.

Fawwaz Batayneh, Cecilia González-Tokman

In \cite{J}, Jabłoński proved that a piecewise expanding $C^{2}$ multidimensional Jabłoński map admits an absolutely continuous invariant probability measure (ACIP). In \cite{BL}, Boyarsky and Lou extended this result to the case of i.i.d. compositions of the above maps, with an on average expanding condition. We generalize these results to the (quenched) se

Shenjian Chen, Stephen Lars Olsen

The Standard Model (SM) of particle physics, comprised of the unified electro-weak (EW) and Quantum Chromodynamic (QCD) theories, accurately explains almost all experimental results related to the micro-world, and has made a number of predictions for previously unseen particles, most notably the Higgs scalar boson, that were subsequently discovered. As a res

Junde Li, Mahabubul Alam, Swaroop Ghosh

Quantum Approximate Optimization Algorithm (QAOA) is a promising hybrid quantum-classical algorithm for solving combinatorial optimization problems. However, it cannot overcome qubit limitation for large-scale problems. Furthermore, the execution time of QAOA scales exponentially with the problem size. We propose a Divide-and-Conquer QAOA (DC-QAOA) to addres

Xiaoping Shi, Meiqian Chen, Yucheng Dong

At the end of April 20, 2020, there were only a few new COVID-19 cases remaining in China, whereas the rest of the world had shown increases in the number of new cases. It is of extreme importance to develop an efficient statistical model of COVID-19 spread, which could help in the global fight against the virus. We propose a clustering-segmented autoregress

Faycal Znidi, Hamzeh Davarikia, Heena Rathore

Coherent groups of generators, i.e., machines with perfectly correlated rotor angles, play an important role in power system stability analysis. This paper introduces a real-time methodology based on hierarchical clustering techniques for discovering the degree of coherency among generators using the synchronization coefficient and the correlation coefficien

Xingran Xu, Huawen Xu, S. Mandal, R. Banerjee

The non-Hermitian skin effect can be realized through asymmetric hopping between forward and backward directions, where all the modes of the system are localized at one edge of a finite 1D lattice. However, achieving such an asymmetric hopping in optical systems is far from trivial. Here we show theoretically that in a finite chain of 1D exciton-polariton mi

Junxiao Xue, Xiangyan Kong, Bowei Dong, Mingliang Xu

The problem of mixed static and dynamic obstacle avoidance is essential for path planning in highly dynamic environment. However, the paths formed by grid edges can be longer than the true shortest paths in the terrain since their headings are artificially constrained. Existing methods can hardly deal with dynamic obstacles. To address this problem, we propo

Jonathan R. Lamontagne, Martin Jasek, Jared D. Smith

The Peace-Athabasca Delta (PAD) of northwestern Alberta is one of the largest inland freshwater deltas in the world, laying at the confluence of the Peace and Athabasca Rivers. The PAD is recognized as a having unique ecological significance and periodic ice jam flooding from both rivers is an important feature of its current ecology. Past studies have debat

Senthil Hariharan Arul, Dinesh Manocha

We present a decentralized collision avoidance method for dense environments that is based on buffered Voronoi cells (BVC) and reciprocal velocity obstacles (RVO). Our approach is designed for scenarios with large number of close proximity agents and provides passive-friendly collision avoidance guarantees. The Voronoi cells are superimposed with RVO cones t

Luyan Liu, Zhiwei Wen, Songwei Liu, Hong-Yu Zhou

Considering the scarcity of medical data, most datasets in medical image analysis are an order of magnitude smaller than those of natural images. However, most Network Architecture Search (NAS) approaches in medical images focused on specific datasets and did not take into account the generalization ability of the learned architectures on unseen datasets as

Ashoke De, Sumanta Acharya

A Thickened Flame (TF) modeling approach is combined with a Large Eddy Simulation (LES) methodology to model premixed combustion and the accuracy of these model predictions is evaluated by comparing with the piloted premixed stoichiometric methane-air flame data of Chen et al. [Combust. Flame 107 (1996) 233-244] at a Reynolds number Re = 24,000. In the TF mo

Elise F. Palzer, Christine Wendt, Russell Bowler, Craig P. Hersh

Analyzing multi-source data, which are multiple views of data on the same subjects, has become increasingly common in molecular biomedical research. Recent methods have sought to uncover underlying structure and relationships within and/or between the data sources, and other methods have sought to build a predictive model for an outcome using all sources. Ho

Alok Mishra, Gaurav Kumar, Ashoke De

Most of the turbulence models in practice are based on the assumption of a linear relation between Reynolds stresses and mean flow strain rates which generally provides a good approximation in case of attached and fully turbulent flows. A two dimensional numerical study has been carried out over NACA 0021 with k-ωSST model with non-linear correction at Re =

Rahul Kumar Soni, Ashoke De

The strut based injector has been found to be one of the most promising injector designs for supersonic combustor, offering en-hanced mixing of fuel and air. The mixing and flow field characteristics of the straight (SS) & tapered strut (TS), with fixed ramp an-gle and height at freestream Mach number 2 in conjunction with fuel injection at Mach 2.3 have bee

Ruixiang Fei, Shuaiqin Yu, Yan Lu, Linghan Zhu

Generating and controlling spin current (SC) are of central interest in spin physics and applications. To date, the spin-orbit interaction (SOI) is an established pathway to generate SC through the spin-charge current conversion. We predict an efficient spin-light conversion via the Rashba and higher-order cubic Dresselhaus SOIs in ferroelectrics. Different

Jiang Yang, Zhaoming Yuan, Zhi Zhou

We develop and analyze a class of maximum bound preserving schemes for approximately solving Allen--Cahn equations. We apply a $k$th-order single-step scheme in time (where the nonlinear term is linearized by multi-step extrapolation), and a lumped mass finite element method in space with piecewise $r$th-order polynomials and Gauss--Lobatto quadrature. At ea

Yi Zhou, Lei Huang, Tianfei Zhou, Ling Shao

Chest X-rays are an important and accessible clinical imaging tool for the detection of many thoracic diseases. Over the past decade, deep learning, with a focus on the convolutional neural network (CNN), has become the most powerful computer-aided diagnosis technology for improving disease identification performance. However, training an effective and robus

Alex Suhan, Davide Libenzi, Ailing Zhang, Parker Schuh

Domain-specific optimizing compilers have demonstrated significant performance and portability benefits, but require programs to be represented in their specialized IRs. Existing frontends to these compilers suffer from the &#34;language subset problem&#34; where some host language features are unsupported in the subset of the user&#39;s program that interac

Zhiqian Zhou, Pengming Zhu, Zhiwen Zeng, Junhao Xiao

It is still an open and challenging problem for mobile robots navigating along time-efficient and collision-free paths in a crowd. The main challenge comes from the complex and sophisticated interaction mechanism, which requires the robot to understand the crowd and perform proactive and foresighted behaviors. Deep reinforcement learning is a promising solut

T. Yong, A. I. Abdalla, M. A. Cappelli

We report on time-resolved measurements of electron number density by continuous-wave laser absorption in a low-energy nanosecond-scale laser-produced spark in atmospheric pressure air. Laser absorption is a result of free-free and bound-free electron excitation, with the absorption coefficient modeled and evaluated using estimates of the time-variation in e

Yu Shen, Laura Zheng, Manli Shu, Weizi Li

For safety of autonomous driving, vehicles need to be able to drive under various lighting, weather, and visibility conditions in different environments. These external and environmental factors, along with internal factors associated with sensors, can pose significant challenges to perceptual data processing, hence affecting the decision-making and control

Jian Peng, Rishi Pillai, Marie Romedenne, Bruce A. Pint

Although of practical importance, there is no established modeling framework to accurately predict high-temperature cyclic oxidation kinetics of multi-component alloys due to the inherent complexity. We present a data analytics approach to predict the oxidation rate constant of NiCr-based alloys as a function of composition and temperature with a highly cons

Jiajia Yu, Rongjie Lai, Wuchen Li, Stanley Osher

In this paper, we propose an efficient and flexible algorithm to solve dynamic mean-field planning problems based on an accelerated proximal gradient method. Besides an easy-to-implement gradient descent step in this algorithm, a crucial projection step becomes solving an elliptic equation whose solution can be obtained by conventional methods efficiently. B

Shangkun Weng, Zihao Zhang

In this paper, we investigate two dimensional subsonic and subsonic-sonic spiral flows outside a porous body. The existence and uniqueness of the subsonic spiral flow are obtained via variational formulation. The optimal decay rate at far fields is also derived by the Kelvin&#39;s transformation and some elliptic estimates. By extracting spiral subsonic solu

Jacopo Simoni, Stefano Sanvito

The total angular momentum of a close system is a conserved quantity, which should remain constant in time for any excitation experiment once the pumping signal has extinguished. Such conservation, however, is never satisfied in practice in any real-time first principles description of the demagnetization process. Furthermore, there is a growing experimental

Adam Paszke, Brennan Saeta

Multidimensional arrays (NDArrays) are a central abstraction in modern scientific computing environments. Unfortunately, they can make reasoning about programs harder as the number of different array shapes used in an execution of a program is usually very large, and they rarely appear explicitly in program text. To make things worse, many operators make imp

Javier González-Trejo, Diego Mercado-Ravell, Israel Becerra, Rafael Murrieta-Cid

Autonomous landing of Unmanned Aerial Vehicles (UAVs) in crowded scenarios is crucial for successful deployment of UAVs in populated areas, particularly in emergency landing situations where the highest priority is to avoid hurting people. In this work, a new visual-based algorithm for identifying Safe Landing Zones (SLZ) in crowded scenarios is proposed, co

Linda Valeri, Cécile Proust-Lima, Weijia Fan, Jarvis T. Chen

We propose a novel methodology to quantify the effect of stochastic interventions on non-terminal time-to-events that lie on the pathway between an exposure and a terminal time-to-event outcome. Investigating these effects is particularly important in health disparities research when we seek to quantify inequities in timely delivery of treatment and its impa

Liang Chen, Peng Jin, Jing Yang, Yang Li

To obtain the accurate transient states of the big scale natural gas pipeline networks under the bad data and non-zero mean noises conditions, a robust Kalman filter-based dynamic state estimation method is proposed using the linearized gas pipeline transient flow equations in this paper. Firstly, the dynamic state estimation model is built. Since the gas pi

H. Sakabayashi, R. Okazaki

The layered cobaltite [Ca$_2$CoO$_3$]$_{0.62}$[CoO$_2$], often expressed as the approximate formula Ca$_3$Co$_4$O$_9$, is a promising candidate for efficient oxide thermoelectrics but an origin of its unusual thermoelectric transport is still in debate. Here we investigate \textit{in-plane} anisotropy of the transport properties in a broad temperature range

Yury Zemlyanskiy, Sudeep Gandhe, Ruining He, Bhargav Kanagal

This paper explores learning rich self-supervised entity representations from large amounts of the associated text. Once pre-trained, these models become applicable to multiple entity-centric tasks such as ranked retrieval, knowledge base completion, question answering, and more. Unlike other methods that harvest self-supervision signals based merely on a lo

Bertrand J. Guillou, J. Peter May, Mona Merling, Angélica M. Osorno

We prove a multiplicative version of the equivariant Barratt-Priddy-Quillen theorem, starting from the additive version proven in arXiv:1207.3459. The proof uses a multiplicative elaboration of an additive equivariant infinite loop space machine that manufactures orthogonal $G$-spectra from symmetric monoidal $G$-categories. The new machine produces highly s

Tiangang Cui, Olivier Zahm

Identifying a low-dimensional informed parameter subspace offers a viable path to alleviating the dimensionality challenge in the sampled-based solution to large-scale Bayesian inverse problems. This paper introduces a novel gradient-based dimension reduction method in which the informed subspace does not depend on the data. This permits an online-offline co

Brennan Saeta, Denys Shabalin, Marc Rasi, Brad Larson

Swift for TensorFlow is a deep learning platform that scales from mobile devices to clusters of hardware accelerators in data centers. It combines a language-integrated automatic differentiation system and multiple Tensor implementations within a modern ahead-of-time compiled language oriented around mutable value semantics. The resulting platform has been v

Vassos Hadzilacos, Xing Hu, Sam Toueg

In a seminal work, Golab et al. showed that a randomized algorithm that works with atomic objects may lose some of its properties if we replace the atomic objects that it uses with linearizable objects. It was not known whether the properties that can be lost include the important property of termination (with probability 1). In this paper, we first show tha

Octavio Arizmendi, Jorge Fernandez Hidalgo

We give a bound for the graph energy with given maximal degree in terms of the second and fourth moments of a graph. In the case in which the graph is $d$-regular we obtain the bound that is given in Van Dam, E. et al. (2014). through elementary methods.

François Bachoc, Nicolas Durrande, Didier Rullière, Clément Chevalier

Kriging is a widely employed technique, in particular for computer experiments, in machine learning or in geostatistics. An important challenge for Kriging is the computational burden when the data set is large. This article focuses on a class of methods aiming at decreasing this computational cost, consisting in aggregating Kriging predictors based on small

Alexandre Payez, Steven Dewitte, Nicolas Clerbaux

Geostationary observations offer the unique opportunity to resolve the diurnal cycle of the Earth&#39;s Radiation Budget at the top of the atmosphere (TOA), crucial for climate-change studies. However, a drawback of the continuous temporal coverage of the geostationary orbit is the fixed viewing geometry. As a consequence, imperfections in the angular distri

Yan Sun, Qifan Song, Faming Liang

Deep learning has been the engine powering many successes of data science. However, the deep neural network (DNN), as the basic model of deep learning, is often excessively over-parameterized, causing many difficulties in training, prediction and interpretation. We propose a frequentist-like method for learning sparse DNNs and justify its consistency under t

Sina Pourjabar, Gwan S. Choi

This paper presents a partially parallel low-density parity-check (LDPC) decoder designed for the 5G New Radio (NR) standard. The design is using a multi-block parallel architecture with a flooding schedule. The decoder can support any code rates and code lengths up to the lifting size Zmax= 96. To compensate for the dropped throughput associated with the sm

Louis Sica

It is not generally known, that the inequality that Bell derived using three random variables must be identically satisfied by any three corresponding data sets of plus and minus 1s that are writable on paper.This surprising fact is not immediately obvious from Bell&#39;s inequality derivation based on causal random variables, but follows immediately if the

Antoine Georges, Jernej Mravlje

We consider non-Fermi liquids in which the inelastic scattering rate has an intrinsic particle-hole asymmetry and obeys $ω/T$ scaling. We show that, in contrast to Fermi liquids, this asymmetry influences the low-temperature behaviour of the thermopower even in the presence of impurity scattering. Implications for the unconventional sign and temperature depe