October 2020 arXiv papers — page 122

Lucas Ruhstorfer

Späth showed that the Alperin-McKay conjecture in the representation theory of finite groups holds if the so-called inductive Alperin-McKay condition holds for all finite simple groups. In a previous article, we showed that the Bonnafé-Rouquier equivalence for blocks of finite groups of Lie type can be lifted to include automorphisms of groups of Lie type. W

Alessandra Urbinati, Kyriaki Kalimeri, Andrea Bonanomi, Alessandro Rosina

Youth unemployment rates are still in alerting levels for many countries, among which Italy. Direct consequences include poverty, social exclusion, and criminal behaviours, while negative impact on the future employability and wage cannot be obscured. In this study, we employ survey data together with social media data, and in particular likes on Facebook Pa

Heribert Wankerl, Maike L. Stern, Ali Mahdavi, Christoph Eichler

Designing a multi-layer optical system with designated optical characteristics is an inverse design problem in which the resulting design is determined by several discrete and continuous parameters. In particular, we consider three design parameters to describe a multi-layer stack: Each layer's dielectric material and thickness as well as the total numbe

Binyan Jiang, Jailing Li, Qiwei Yao

We propose a first-order autoregressive (i.e. AR(1)) model for dynamic network processes in which edges change over time while nodes remain unchanged. The model depicts the dynamic changes explicitly. It also facilitates simple and efficient statistical inference methods including a permutation test for diagnostic checking for the fitted network models. The

Borna Salehian, Mohammad Ali Gorji, Hassan Firouzjahi, Shinji Mukohyama

We present a scenario of vector dark matter production from symmetry breaking at the end of inflation. In this model, the accumulated energy density associated with the quantum fluctuations of the dark photon accounts for the present energy density of dark matter. The inflaton is a real scalar field while a heavy complex scalar field, such as the waterfall o

Leon Yan, Nathan Banka, Parker Owan, Walter Tony Piaskowy

This work improves the positioning precision of lightweight robots with series elastic actuators (SEAs). Lightweight SEA robots, along with low-impedance control, can maneuver without causing damage in uncertain, confined spaces such as inside an aircraft wing during aircraft assembly. Nevertheless, substantial modeling uncertainties in SEA robots reduce the

Marina Fomicheva, Shuo Sun, Erick Fonseca, Chrysoula Zerva

We present MLQE-PE, a new dataset for Machine Translation (MT) Quality Estimation (QE) and Automatic Post-Editing (APE). The dataset contains eleven language pairs, with human labels for up to 10,000 translations per language pair in the following formats: sentence-level direct assessments and post-editing effort, and word-level good/bad labels. It also cont

Gauthier Anaïs, Pruvost Mickaël, Gamache Olivier, Colin Annie

A new pressure sensor array, positioned on the bottom plate of a standard torsional rheometer is presented. It is built from a unique piezo-capacitive polymeric foam, and consists of twenty-five capacitive pressure sensors (of surface 4.5$\times$4.5 mm$^2$ each) built together in a 5$\times$5 regular array. The sensor array is used to obtain a local mapping

Jiaojie Yan, Jianing Yao, Vladimir Shvarts, Rui-Rui Du

Temperature below 100 microKelvin is achieved in a customized cryogen-free dilution refrigerator with a copper-nuclear demagnetization stage. The lowest temperature of conduction electrons of the demagnetization stage is below 100 microKelvin as measured by a pulsed platinum NMR thermometer and the temperature can remain below 100 microKelvin for over 10 hou

Giancarlo D'Ambrosio, Mathew Thomas Arun, Ashwani Kushwaha, Sudhir K. Vempati

The Randall Sundrum (RS) models receive significant constraints from the neutral Kaon system. The CP violating observable $ε_K$, in Randall Sundrum scenario, requires the lightest KK gluon to be heavier than $\sim$ 24 TeV. The constraint is even stronger in the Little Randall Sundrum models (LRS), $\gtrsim$ 32 TeV. The LRS models are motivated for their poss

Robert Tjarko Lange, Henning Sprekeler

Animals are equipped with a rich innate repertoire of sensory, behavioral and motor skills, which allows them to interact with the world immediately after birth. At the same time, many behaviors are highly adaptive and can be tailored to specific environments by means of learning. In this work, we use mathematical analysis and the framework of meta-learning

Heiko Gimperlein, Bernhard Krötz, Job J. Kuit, Henrik Schlichtkrull

We formulate and prove a Paley-Wiener theorem for Harish-Chandra modules for a real reductive group. As a corollary we obtain a new and elementary proof of the Helgason conjecture.

Ryusuke Jinno, Ryosuke Sato

We study negative modes around the Coleman-de Luccia bounce solution. The conditions for the appearance of an infinite number of the negative modes do not coincide between Lagrangian and Hamiltonian formulations in the literature, and we discuss the origin of this difference in detail. We show how different choices of the variable for the fluctuation around

Andreas Bauswein, Sebastian Blacker, Georgios Lioutas, Theodoros Soultanis

This study addresses the collapse behavior of neutron star (NS) mergers expressed through the binary threshold mass M_thr for prompt black hole (BH) formation, which we determine by relativistic hydrodynamical simulations for 40 equation of state (EoS) models. M_thr can be well described by various fit formulae involving stellar parameters of nonrotating NSs

Yuan Yin, Vincent Le Guen, Jérémie Dona, Emmanuel de Bézenac

Forecasting complex dynamical phenomena in settings where only partial knowledge of their dynamics is available is a prevalent problem across various scientific fields. While purely data-driven approaches are arguably insufficient in this context, standard physical modeling based approaches tend to be over-simplistic, inducing non-negligible errors. In this

Kensuke Akita, Saul Hurwitz, Masahide Yamaguchi

We explore the potential of measurements of cosmological effects, such as neutrino spectral distortions from the neutrino decoupling and neutrino clustering in our Galaxy, via cosmic neutrino capture on tritium. We compute the precise capture rates of each neutrino species including such cosmological effects to probe them. These precise estimates of capture

Dietmar Czubak, Samuel Gaucher, Lars Oppermann, Jens Herfort

We studied metastable $α$-FeGe$_2$, a novel layered tetragonal material, embedded as a spacer layer in spin valve structures with ferromagnetic Fe$_3$Si and Co$_2$FeSi electrodes. For both types of electrodes, spin valve operation is demonstrated with a metallic transport behavior of the $α$-FeGe$_2$ spacer layer. The spin valve signals are found to increase

Muhammad Osama, Dave Zachariah, Satyam Dwivedi, Petre Stoica

We address the problem of timing-based localization in wireless networks, when an unknown fraction of data is corrupted by nonideal signal conditions. While timing-based techniques enable accurate localization, they are also sensitive to such corrupted data. We develop a robust method that is applicable to a range of localization techniques, including time-o

Paul J. Pritz, Liang Ma, Kin K. Leung

While reinforcement learning has achieved considerable successes in recent years, state-of-the-art models are often still limited by the size of state and action spaces. Model-free reinforcement learning approaches use some form of state representations and the latest work has explored embedding techniques for actions, both with the aim of achieving better g

Yannis Flet-Berliac, Reda Ouhamma, Odalric-Ambrym Maillard, Philippe Preux

Policy gradient algorithms have proven to be successful in diverse decision making and control tasks. However, these methods suffer from high sample complexity and instability issues. In this paper, we address these challenges by providing a different approach for training the critic in the actor-critic framework. Our work builds on recent studies indicating

Rong-Hua Wang, Michael X. X. Zhong

During the study of dual sequences, Sun introduced the polynomials \[ D_n(x,y)=\sum_{k=0}^{n}{n\choose k}{x\choose k}y^k\text{ and } S_n(x,y)=\sum_{k=0}^{n}\binom{n}{k}\binom{x}{k}\binom{-1-x}{k} y^k. \] Many related congruences have been established and conjectured by Sun. Here we generalize some of them by determining \[ \sum_{k=0}^{p-1}D_k(x_1,y_1)D_k(x_2

Tielin Zhang, Shuncheng Jia, Xiang Cheng, Bo Xu

Spiking Neural Networks (SNNs) contain more biologically realistic structures and biologically-inspired learning principles than those in standard Artificial Neural Networks (ANNs). SNNs are considered the third generation of ANNs, powerful on the robust computation with a low computational cost. The neurons in SNNs are non-differential, containing decayed h

Michel Gros, Bernard Le Stum, Adolfo Quirós

We introduce twisted differential calculus of negative level and prove a descent theorem: Frobenius pullback provides an equivalence between finitely presented modules endowed with a topologically quasi-nilpotent twisted connection of level minus one and those of level zero. We explain how this is related to the existence of a Cartier operator on prismatic c

Zhenzhen Sun, Yuanlong Yu

Feature selection is an important data preprocessing in data mining and machine learning which can be used to reduce the feature dimension without deteriorating model's performance. Since obtaining annotated data is laborious or even infeasible in many cases, unsupervised feature selection is more practical in reality. Though lots of methods for unsuperv

Jannik Castenow, Jonas Harbig, Daniel Jung, Till Knollmann

This work focuses on the following question related to the Gathering problem of $n$ autonomous, mobile robots in the Euclidean plane: Is it possible to solve Gathering of robots that do not agree on any axis of their coordinate systems (disoriented robots) and see other robots only up to a constant distance (limited visibility) in $o(n^2)$ fully synchronous

Jian-Min Wang, Edi Bon

Changing-look active galactic nuclei (CL-AGNs) as a new subpopulation challenge some fundamental physics of AGNs because the timescales of the phenomenon can hardly be reconciled with accretion disk models. In this Letter{\textit{}}, we demonstrate the extreme case: close binaries of supermassive black holes (CB-SMBHs) with high eccentricities are able to tr

Abdelhaq El Khalfi, Mohammed Issoual, Najib Mahdou, Andreas Reinhart

Let $R$ be a commutative ring with nonzero identity. A. Yassine et al. defined in the paper (Yassine, Nikmehr and Nikandish, 2020), the concept of $1$-absorbing prime ideals as follows: a proper ideal $I$ of $R$ is said to be a $1$-absorbing prime ideal if whenever $xyz\in I$ for some nonunit elements $x,y,z\in R$, then either $xy\in I$ or $z\in\ I$. We use

Yanhao Wang, Francesco Fabbri, Michael Mathioudakis

We study the problem of extracting a small subset of representative items from a large data stream. In many data mining and machine learning applications such as social network analysis and recommender systems, this problem can be formulated as maximizing a monotone submodular function subject to a cardinality constraint $k$. In this work, we consider the se

Jia Li, Tomasyu Yu, Jiajin Li, Honglei Zhang

Graph Neural Networks (GNNs) and Variational Autoencoders (VAEs) have been widely used in modeling and generating graphs with latent factors. However, there is no clear explanation of what these latent factors are and why they perform well. In this work, we present Dirichlet Graph Variational Autoencoder (DGVAE) with graph cluster memberships as latent facto

Jiarui Fang, Yang Yu, Chengduo Zhao, Jie Zhou

The transformer is the most critical algorithm innovation of the Nature Language Processing (NLP) field in recent years. Unlike the Recurrent Neural Network (RNN) models, Transformers can process on dimensions of sequence lengths in parallel, therefore leading to better accuracy on long sequences. However, efficient deployments of them for online services in

Rukmini Dey, Kohinoor Ghosh, Sidharth Soundararajan

We show that the height function of Scherk's second surface decomposes into a finite sum of scaled and translated versions of itself, using an Euler Ramanujan identity. A similar result appears in R. Kamien's work on liquid crystals where he shows (using an Euler-Ramanujan identity) that the Scherk's first surface decomposes into a finite sum of

Seung-won Park

In this paper, we present Neural Glyph, a system that generates novel glyph without any training data. The generator and the classifier are trained to communicate via visual symbols as a medium, which enforces the generator to come up with a set of distinctive symbols. Our method results in glyphs that resemble the human-made glyphs, which may imply that the

Amaury Durand, François Roueff

Fractionally integrated autoregressive moving average (FIARMA) processes have been widely and successfully used to model and predict univariate time series exhibiting long range dependence. Vector and functional extensions of these processes have also been considered more recently. Here we study these processes by relying on a spectral domain approach in the

James East, Nik Ruskuc

The twisted partition monoid $\mathcal{P}_n^Φ$ is an infinite monoid obtained from the classical finite partition monoid $\mathcal{P}_n$ by taking into account the number of floating components when multiplying partitions. The main result of this paper is a complete description of the congruences on $\mathcal{P}_n^Φ$. The succinct encoding of a congruence, w

Wenhao Yu, Chenguang Zhu, Zaitang Li, Zhiting Hu

The goal of text generation is to make machines express in human language. It is one of the most important yet challenging tasks in natural language processing (NLP). Since 2014, various neural encoder-decoder models pioneered by Seq2Seq have been proposed to achieve the goal by learning to map input text to output text. However, the input text alone often p

Jennifer D'Souza, Sören Auer

Purpose: The aim of this work is to normalize the NLPCONTRIBUTIONS scheme (henceforward, NLPCONTRIBUTIONGRAPH) to structure, directly from article sentences, the contributions information in Natural Language Processing (NLP) scholarly articles via a two-stage annotation methodology: 1) pilot stage - to define the scheme (described in prior work); and 2) adju

Koki Fusejima

In this paper, we establish sufficient conditions for identifying treatment effects on continuous outcomes in endogenous and multi-valued discrete treatment settings with unobserved heterogeneity. We employ the monotonicity assumption for multi-valued discrete treatments and instruments, and our identification condition has a clear economic interpretation. I

Perry Deng, Cooper Linsky, Matthew Wright

Visually similar characters, or homoglyphs, can be used to perform social engineering attacks or to evade spam and plagiarism detectors. It is thus important to understand the capabilities of an attacker to identify homoglyphs -- particularly ones that have not been previously spotted -- and leverage them in attacks. We investigate a deep-learning model usin

Alistair R. Milne, Cornelius Hempel, Li Li, Claire L. Edmunds

Quantum harmonic oscillators are central to many modern quantum technologies. We introduce a method to determine the frequency noise spectrum of oscillator modes through coupling them to a qubit with continuously driven qubit-state-dependent displacements. We reconstruct the noise spectrum using a series of different drive phase and amplitude modulation patt

Yoshihiro Machida, Kenichi Kasamatsu

We apply the theory of inhomogeneous Kibble-Zurek mechanism to understand quench dynamics from the Mott insulator to the superfluid in a cold Bose gases confined in both a two-dimensional optical lattice and a harmonic trap. The local quench time and the freeze-out region associated with the nonadiabatic transition take a nontrivial positional dependence due

Zhiwei Xu, Thalaiyasingam Ajanthan, Richard Hartley

Although deep learning greatly improves the performance of semantic segmentation, its success mainly lies in object central areas without accurate edges. As superpixels are a popular and effective auxiliary to preserve object edges, in this paper, we jointly learn semantic segmentation with trainable superpixels. We achieve it with fully-connected layers wit

Mehdi Rezaee, Francis Ferraro

Within the context of event modeling and understanding, we propose a new method for neural sequence modeling that takes partially-observed sequences of discrete, external knowledge into account. We construct a sequential neural variational autoencoder, which uses Gumbel-Softmax reparametrization within a carefully defined encoder, to allow for successful bac

Ernazar Abdikamalov, Giulia Pagliaroli, David Radice

We summarize our current understanding of gravitational wave emission from core-collapse supernovae. We review the established results from multi-dimensional simulations and, wherever possible, provide back-of-the-envelope calculations to highlight the underlying physical principles. The gravitational waves are predominantly emitted by protoneutron star osci

Mingzhu Shen, Feng Liang, Ruihao Gong, Yuhang Li

Quantization Neural Networks (QNN) have attracted a lot of attention due to their high efficiency. To enhance the quantization accuracy, prior works mainly focus on designing advanced quantization algorithms but still fail to achieve satisfactory results under the extremely low-bit case. In this work, we take an architecture perspective to investigate the po

Yuya Mizuno

We study an explicit description of semibricks and 2-term simple-minded collections over preprojective algebras of type $A$ via arc diagrams. We provide a bijection between the set of noncrossoing arc diagrams (resp. the set of double arc diagrams), which is in bijective correspondence with elements of the symmetric group, and the set of semibricks (resp. th

Hao-Jun Michael Shi, Yuchen Xie, Richard Byrd, Jorge Nocedal

This paper describes an extension of the BFGS and L-BFGS methods for the minimization of a nonlinear function subject to errors. This work is motivated by applications that contain computational noise, employ low-precision arithmetic, or are subject to statistical noise. The classical BFGS and L-BFGS methods can fail in such circumstances because the updatin

Thao N. N. Nguyen, Bharadwaj Veeravalli, Xuanyao Fong

Long training time hinders the potential of the deep, large-scale Spiking Neural Network (SNN) with the on-chip learning capability to be realized on the embedded systems hardware. Our work proposes a novel connection pruning approach that can be applied during the on-chip Spike Timing Dependent Plasticity (STDP)-based learning to optimize the learning time

Yingjie Bi, Javad Lavaei

The restricted isometry property (RIP) is a well-known condition that guarantees the absence of spurious local minima in low-rank matrix recovery problems with linear measurements. In this paper, we introduce a novel property named bound difference property (BDP) to study low-rank matrix recovery problems with nonlinear measurements. Using RIP and BDP jointl

Muruhan Rathinam, Mingkai Yu

We consider chemical reaction networks modeled by a discrete state and continuous in time Markov process for the vector copy number of the species and provide a novel particle filter method for state and parameter estimation based on exact observation of some of the species in continuous time. The conditional probability distribution of the unobserved states

Chao Gao, Anderson Y. Zhang

We study the phase synchronization problem with measurements $Y=z^*z^{*H}+σW\in\mathbb{C}^{n\times n}$, where $z^*$ is an $n$-dimensional complex unit-modulus vector and $W$ is a complex-valued Gaussian random matrix. It is assumed that each entry $Y_{jk}$ is observed with probability $p$. We prove that the minimax lower bound of estimating $z^*$ under the s

Satoshi Iihama, Kazuaki Ishibashi, Shigemi Mizukami

The manipulation of magnetization in a metallic ferromagnet by using optical helicity has been much attracted attention for future opto-spintronic devices. The optical helicity induced torques on the magnetization, {\it optical spin torque}, have been observed in ferromagnetic thin films recently. However, the interfacial effect of the optical spin torque in

Dwyer S. Deighan, Scott E. Field, Collin D. Capano, Gaurav Khanna

Gravitational-wave detection strategies are based on a signal analysis technique known as matched filtering. Despite the success of matched filtering, due to its computational cost, there has been recent interest in developing deep convolutional neural networks (CNNs) for signal detection. Designing these networks remains a challenge as most procedures adopt

Liu Tao, Anna C. Green, Paul Fulda

Higher-order Laguerre-Gauss (LG) modes have previously been investigated as a candidate for reducing test-mass thermal noise in ground-based gravitational-wave detectors like Advanced LIGO. It has been shown however that LG modes' fragility against mirror surface figure imperfections limits their compatibility with the current state-of-the-art test masse

Chao-Lin Kuo

In an earlier paper, a new class of thin-shell cavities were proposed to evade the steep frequency scaling of conventional axion haloscopes. In this follow-up work, we see that a generalized conic geometry enables robust frequency-tuning for these large-volume cm-wave cavities. The frequency-defining dimension of a conic shell-cavity changes symmetrically an

Xinghao Yang, Weifeng Liu, Shengli Zhang, Wei Liu

Real world traffic sign recognition is an important step towards building autonomous vehicles, most of which highly dependent on Deep Neural Networks (DNNs). Recent studies demonstrated that DNNs are surprisingly susceptible to adversarial examples. Many attack methods have been proposed to understand and generate adversarial examples, such as gradient based

Mathew W. Bub, Erich Poppitz, Samuel S. Y. Wong

We study confining strings in ${\cal{N}}=1$ supersymmetric $SU(N_c)$ Yang-Mills theory in the semiclassical regime on $\mathbb{R}^{1,2} \times \mathbb{S}^1$. Static quarks are expected to be confined by double strings composed of two domain walls - which are lines in $\mathbb{R}^2$ - rather than by a single flux tube. Each domain wall carries part of the qua

Junru Ma, Jinquan Luo

Symbol-pair codes are proposed to guard against pair-errors in symbol-pair read channels. The minimum symbol-pair distance plays a vital role in determining the error-correcting capability and the constructions of symbol-pair codes with largest possible minimum symbol-pair distance is of great importance. Maximum distance separable (\,MDS\,) symbol-pair code

Aishwarya Sarkar, Jien Zhang, Chaoqun Lu, Ali Jannesari

Due to limited evidence and complex causes of regional climate change, the confidence in predicting fluvial floods remains low. Understanding the fundamental mechanisms intrinsic to geo-spatiotemporal information is crucial to improve the prediction accuracy. This paper demonstrates a hybrid neural network architecture - HydroDeep, that couples a process-bas

Xin Feng, Wenjie Pei, Zihui Jia, Fanglin Chen

Restoring the clean background from the superimposed images containing a noisy layer is the common crux of a classical category of tasks on image restoration such as image reflection removal, image deraining and image dehazing. These tasks are typically formulated and tackled individually due to the diverse and complicated appearance patterns of noise layers

Jurick Lahiri, Mehdi Moemeni, Jessica Kline, Ilias Magoulas

Two-photon excitation is an attractive means for controlling chemistry in both space and time. Isoenergetic one- and two-photon excitations (OPE and TPE) in non-centrosymmetric molecules are often assumed to reach the same excited state and, hence, to produce similar excited-state reactivity. We compare the solvent-to-solute excited-state proton transfer of

Guillem Cazassus, Christopher M. Herald, Paul Kirk, Artem Kotelskiy

The earring tangle consists of four strands 4pt x [0,1] inside S^2 x [0,1] and one meridian around one of the strands. Equipping this tangle with a nontrivial SO(3) bundle, we show that its traceless SU(2) flat moduli space is topologically a smooth genus three surface. We also show that the restriction map from this surface to the traceless flat moduli spac

Donghao Wang

This is the third paper of this series. In \cite{Wang20}, we defined the monopole Floer homology for any pair $(Y,ω)$, where $Y$ is a compact oriented 3-manifold with toroidal boundary and $ω$ is a suitable closed 2-form viewed as a decoration. In this paper, we establish a gluing theorem for this Floer homology when two such 3-manifolds are glued suitably a

A-Ming Liu, Jin Guo, Tongsuo Wu

For positive integers $d<n$, let $[n]_d=\{A\in 2^{[n]}\mid |A|=d\}$ where $[n]=:\{1,2,\ldots, n\}$. For a pure $f$-simplicial complex $Δ$ such that ${\rm dim}(Δ)={\rm dim}(Δ^c)$ and $\mathcal{F}(Δ)\cap \mathcal{F}(Δ^c)=\emptyset$, we prove that the facet ideal $I(Δ)$ is Cohen-Macaulay if and only if it has linear resolution. For a $d$-dimensional pure $f$-si

Gheorghe Craciun, Jiaxin Jin, Polly Y. Yu

A reaction network together with a choice of rate constants uniquely gives rise to a system of differential equations, according to the law of mass-action kinetics. On the other hand, different networks can generate the same dynamical system under mass-action kinetics. Therefore, the problem of identifying &#34;the&#34; underlying network of a dynamical syst

Nathan Chapelier-Laget

Let $W$ be an irreducible Weyl group and $W_a$ its affine Weyl group. In this article we show that there exists a bijection between $W_a$ and the integral points of an affine variety, denoted $\widehat{X}_{W_a}$, which we call the Shi variety of $W_a$. In order to do so, we use Jian-Yi Shi&#39;s characterization of alcoves in affine Weyl groups. We then stud

Wei-Hung Weng, Jonathan Deaton, Vivek Natarajan, Gamaleldin F. Elsayed

Class imbalance is a common problem in medical diagnosis, causing a standard classifier to be biased towards the common classes and perform poorly on the rare classes. This is especially true for dermatology, a specialty with thousands of skin conditions but many of which have low prevalence in the real world. Motivated by recent advances, we explore few-sho

Abhinav Palia, Caroline Devlin, Megan Yelorda

Any program that is designed to accomplish certain objectives, needs to establish program level controls pertaining to the overall goal. A critical aspect that determines the success of a program is the quality of the controls and their effectiveness in accomplishing the goal. Traditional Control Maturity Models primarily focus on the efficiency, management,

Jessica Liebig, Kamran Najeebullah, Raja Jurdak, Ahmad El Shoghri

Novel coronavirus disease (COVID-19) has spread across the world at an unprecedented pace, reaching over 200 countries and territories in less than three months. In response, many governments denied entry to travellers arriving from various countries affected by the virus. While several industries continue to experience economic losses due to the imposed int

Yong Yu

Energy saving and carbon emission reduction in buildings is one of the key measures in combating climate change. Heating, Ventilation, and Air Conditioning (HVAC) system account for the majority of the energy consumption in the built environment, and among which, the chiller plant constitutes the top portion. The optimization of chiller system power consumpt

Akshat Gupta, Sai Krishna Rallabandi, Alan W Black

Tremendous progress in speech and language processing has brought language technologies closer to daily human life. Voice technology has the potential to act as a horizontal enabling layer across all aspects of digitization. It is especially beneficial to rural communities in scenarios like a pandemic. In this work we present our initial exploratory work tow

Konstantinos Demertzis, Lykourgos Magafas, Dimitrios Tsiotas

The global crisis caused by the COVID-19 pandemic, in conjunction with the economic consequences and the collapse of health systems, has raised serious concerns in Europe, which is the most affected continent by the pandemic since it recorded 2,388,694 cases and 190,091 deaths (39.6% of the worldwide total), of which 71.7% (136,238) are in the United Kingdom

Behram Wali, Asad Khattak

With the advent of seemingly unstructured big data, and through seamless integration of computation and physical components, cyber-physical systems (CPS) provide an innovative way to enhance safety and resiliency of transport infrastructure. This study focuses on real world microscopic driving behavior and its relevance to school zone safety expanding the ca

Jim C. Visschers, Emma Wilson, Thomas Conneely, Andrey Mudrov

We present different computational approaches for the rapid extraction of the signal parameters of discretely sampled damped sinusoidal signals. We compare time- and frequency-domain-based computational approaches in terms of their accuracy and precision and computational time required in estimating the frequencies of such signals, and observe a general trad

Moktari Mostofa, Fariborz Taherkhani, Jeremy Dawson, Nasser M. Nasrabadi

Cross-spectral iris recognition is emerging as a promising biometric approach to authenticating the identity of individuals. However, matching iris images acquired at different spectral bands shows significant performance degradation when compared to single-band near-infrared (NIR) matching due to the spectral gap between iris images obtained in the NIR and

Ah-Young Jee, Tsvi Tlusty, Steve Granick

Molecular agitation more rapid than thermal Brownian motion is reported for cellular environments, motor proteins, synthetic molecular motors, enzymes, and common chemical reactions, yet that chemical activity couples to molecular motion contrasts with generations of accumulated knowledge about diffusion at equilibrium. To test the limits of this idea, a cri

Jakub Kvapil

The latest results on charm-tagged jets and open-charm production obtained with \mbox{ALICE} at the LHC are presented. The baryon-to-meson ratios for $\mathrm{Λ^+_c}$, $\mathrm{Σ^{0,+,++}_c}$ and $\mathrm{Ξ^{0,+}_c}$ measured in pp collisions at $\sqrt{s}=13\ \mathrm{TeV}$ are discussed. The measurements of the jet-momentum fraction carried by the $\mathrm{D

Bettina Wagner, Johanna Heine

We present the synthesis and characterization of (15-crown-5)BiI$_3$ (1) and (15-crown-5)BiI$_3$*0.5TIE (2), a halogen bonded adduct with tetraiodoethylene (TIE), a typical halogen bond donor. Our results show that crown ether complexes of main group metal halides can be employed as halogen bond acceptors for the synthesis of new supramolecular aggregates an

Jiayang Wu, Yunyi Yang, Yuning Zhang, Yang Qu

Polarizers and polarization selective resonant cavities (e.g., ring resonators, gratings), are key components for applications to photography, coherent optical detection, polarization-division-multiplexing, optical sensing and liquid crystal displays. We demonstrate waveguide polarizers and polarization discriminating micro-ring resonators (MRRs) by integrat

Christopher Hahne, Andrew Lumsdaine, Amar Aggoun, Vladan Velisavljevic

Plenoptic cameras are receiving increasing attention in scientific and commercial applications because they capture the entire structure of light in a scene, enabling optical transforms (such as focusing) to be applied computationally after the fact, rather than once and for all at the time a picture is taken. In many settings, real-time interactive performa

Jan O. Stenflo

The evolution of the wave function in quantum mechanics is deterministic like that of classical waves. Only when we bring in observers the fundamentally different quantum reality emerges. Similarly the introduction of observers changes the nature of spacetime by causing a split between past and future, concepts that are not well defined in the observer-free

Jens Dittrich, Marcel Maltry

This is an experience report on teaching the undergrad lecture Big Data Engineering at Saarland University in summer term 2020 online. We describe our teaching philosophy, the tools used, what worked and what did not work. As we received extremely positive feedback from the students, in the future, we will continue to use the same teaching model for other le

Boris N. Oreshkin, Peter A. Bakulev

Adaptive algorithms based on sample matrix inversion belong to an important class of algorithms used in radar target detection to overcome prior uncertainty of interference covariance. Sample matrix inversion problem is generally ill conditioned. Moreover, the contamination of the empirical covariance matrix by the useful signal leads to significant degradat

Dimiter Prodanov

The dramatic outbreak of the coronavirus disease 2019 (COVID-19) pandemics and its ongoing progression boosted the scientific community&#39;s interest in epidemic modeling and forecasting. The SIR (Susceptible-Infected-Removed) model is a simple mathematical model of epidemic outbreaks, yet for decades it evaded the efforts of the community to derive an expl

Joshua Hunte, Martin Neil, Norman Fenton

Product risk assessment is the overall process of determining whether a product, which could be anything from a type of washing machine to a type of teddy bear, is judged safe for consumers to use. There are several methods used for product risk assessment, including RAPEX, which is the primary method used by regulators in the UK and EU. However, despite its

Hao Zhou, Kaushik Bhattacharya

We present an approach to solving problems in micromechanics that is amenable to massively parallel calculations through the use of graphical processing units and other accelerators. The problems lead to nonlinear differential equations that are typically second order in space and first order in time. This combination of nonlinearity and nonlocality makes su

Yahia Hamdi, Hanen Akouaydi, Houcine Boubaker, Adel M. Alimi

This work is part of an innovative e-learning project allowing the development of an advanced digital educational tool that provides feedback during the process of learning handwriting for young school children (three to eight years old). In this paper, we describe a new method for children handwriting quality analysis. It automatically detects mistakes, giv

Yuzhen Chen, Menghan Hu, Chunjun Hua, Guangtao Zhai

Coronavirus Disease 2019 (COVID-19) has spread all over the world since it broke out massively in December 2019, which has caused a large loss to the whole world. Both the confirmed cases and death cases have reached a relatively frightening number. Syndrome coronaviruses 2 (SARS-CoV-2), the cause of COVID-19, can be transmitted by small respiratory droplets

Dhuruva Priyan G M, Abhik Singla, Shalabh Bhatnagar

Hindsight Experience Replay (HER) is one of the efficient algorithm to solve Reinforcement Learning tasks related to sparse rewarded environments.But due to its reduced sample efficiency and slower convergence HER fails to perform effectively. Natural gradients solves these challenges by converging the model parameters better. It avoids taking bad actions th

Ahmad Berjaoui

Continual learning could shift the machine learning paradigm from data centric to model centric. A continual learning model needs to scale efficiently to handle semantically different datasets, while avoiding unnecessary growth. We introduce hash-routed convolutional neural networks: a group of convolutional units where data flows dynamically. Feature maps a

P. G. Romeo, Sneha K K

In this paper we discuss generalized group, provides some interesting examples. Further we introduce a generalized module as a module like structure obtained from a generalized group and discuss some of its properties and we also describes generalized module groupoids.

Xiaoying Zhuang, Hongwei Guo, Naif Alajlan, Timon Rabczuk

In this paper, we present a deep autoencoder based energy method (DAEM) for the bending, vibration and buckling analysis of Kirchhoff plates. The DAEM exploits the higher order continuity of the DAEM and integrates a deep autoencoder and the minimum total potential principle in one framework yielding an unsupervised feature learning method. The DAEM is a spe

Sitong Mao, Jiaxin Chen, Xiao Shen, Fu-lai Chung

Domain adaptation refers to the learning scenario that a model learned from the source data is applied on the target data which have the same categories but different distribution. While it has been widely applied, the distribution discrepancy between source data and target data can substantially affect the adaptation performance. The problem has been recent

Enes Krijestorac, Agon Memedi, Takamasa Higuchi, Seyhan Ucar

In this work, we propose the use of hybrid offloading of computing tasks simultaneously to edge servers (vertical offloading) via LTE communication and to nearby cars (horizontal offloading) via V2V communication, in order to increase the rate at which tasks are processed compared to local processing. Our main contribution is an optimized resource assignment

Shouhuai Xu

Secure group communications are a mechanism facilitating protected transmission of messages from a sender to multiple receivers, and many emerging applications in both wired and wireless networks need the support of such a mechanism. There have been many secure group communication schemes in wired networks, which can be directly adopted in, or appropriately

Shouhuai Xu

Cybersecurity Dynamics is new concept that aims to achieve the modeling, analysis, quantification, and management of cybersecurity from a holistic perspective, rather than from a building-blocks perspective. It is centered at modeling and analyzing the attack-defense interactions in cyberspace, which cause a ``natural&#39;&#39; phenomenon -- the evolution of

Hongwei Guo, Xiaoying Zhuang, Xiaoyu Meng, Timon Rabczuk

In this work, the hybrid intelligent computing method, which combines efficient Jaya algorithm with classical Runge-Kutta method is applied to solve the Falkner-Skan equations with various wedge angles, which is the fundamental equation for a variety of computational fluid mechanical problems. With some coordinate transformation, the Falkner-Skan boundary la

F. Antonacci, C. Costantini, F. D&#39;Ippoliti, M. Papi

We propose a new model for the joint evolution of the European inflation rate, the European Central Bank official interest rate and the short-term interest rate, in a stochastic, continuous time setting. We derive the valuation equation for a contingent claim and show that it has a unique solution. The contingent claim payoff may depend on all three economic

Halis Yilmaz

The Hirota equation is an integrable higher order nonlinear Schrödinger type equation which describes the propagation of ultrashort light pulses in optical fibers. We present a standard Darboux transformation for the Hirota equation and then construct its quasideterminant solutions. The multisoliton and breather solutions of the Hirota equation are given exp

Hermano Frid, Daniel Marroquin, João F. C. Nariyoshi

It has been known, since the pioneering works by Serre, Hoff, Vaĭgant-Kazhikhov, Lions and Feireisl, among others, the regularizing properties of the effective viscous flux and its characterization as the function whose gradient is the gradient part in the Hodge decomposition of the Newtonian force of the fluid, when the shear viscosity of the fluid is const

Maya Abo Dominguez, William La, James C. Boerkoel

Automated scheduling is potentially a very useful tool for facilitating efficient, intuitive interactions between a robot and a human teammate. However, a current gapin automated scheduling is that it is not well understood how to best represent the timing uncertainty that human teammates introduce. This paper attempts to address this gap by designing an onl