November 2019 arXiv papers — page 62

Gian Paolo Beretta

In the domain of nondissipative unitary Hamiltonian dynamics, the well-known Mandelstam-Tamm-Messiah time-energy uncertainty relation $τ_{F}Δ_H\ge \hbar/2$ provides a general lower bound to the characteristic time $τ_F =Δ_F/|{\rm d} \langle F\rangle/dt|$ with which the mean value of a generic quantum observable $F$ can change with respect to the width $Δ_F$

Xuhui Han, WeiKang Zheng, Benjamin E. Stahl, Jamison Burke

The Type~Ia supernova (SN~Ia) 2017cfd in IC~0511 (redshift z = 0.01209+- 0.00016$) was discovered by the Lick Observatory Supernova Search 1.6+-0.7 d after the fitted first-light time (FFLT; 15.2 d before B-band maximum brightness). Photometric and spectroscopic follow-up observations show that SN~2017cfd is a typical, normal SN~Ia with a peak luminosity MB

Thierry Huillet, Servet Martinez

Lamperti's maximal branching process is revisited, with emphasis on the description of the shape of the invariant measures in both the recurrent and transient regimes. A truncated version of this chain is exhibited, preserving the monotonicity of the original Lamperti chain supported by the integers. The Brown theory of hitting times applies to the latte

Joris Mulder, Xin Gu, Anton Olsson-Collentine, Andrew Tomarken

There has been a tremendous methodological development of Bayes factors for hypothesis testing in the social and behavioral sciences, and related fields. This development is due to the flexibility of the Bayes factor for testing multiple hypotheses simultaneously, the ability to test complex hypotheses involving equality as well as order constraints on the p

Frank Edzards, Susanne Mertens, Michael Willers

The Large Enriched Germanium Experiment for Neutrinoless $ββ$ Decay (LEGEND) is a future ton-scale experimental program that will search for neutrinoless double beta decay ($0νββ$) in the isotope $^{76}$Ge with an unprecedented sensitivity. To achieve the projected discovery sensitivity at a half-life beyond $10^{28}\,$yr after about ten years of data taking

Man-Ki Yoon, Jung-Eun Kim, Richard Bradford, Zhong Shao

This paper presents a schedule randomization algorithm that reduces the vulnerability of real-time systems to timing inference attacks which attempt to learn the timing of task execution. It utilizes run-time information readily available at each scheduling decision point to increase the level of uncertainty in task schedules, while preserving the original s

Renaud Gueroult, Jean-Marcel Rax, Nathaniel J. Fisch

The electrostatic model proposed by Poulos [Phys. Plasmas (2019), $\mathbf{26}$, 022104] to describe the electric potential distribution across and along a magnetized plasma column is used to shed light onto the ability to control perpendicular electric fields. The effective electrical connection between facing end-electrodes is shown to be conditioned upon

Nikolas Ioannou, Celestine Mendler-Dünner, Thomas Parnell

In this paper we propose a novel parallel stochastic coordinate descent (SCD) algorithm with convergence guarantees that exhibits strong scalability. We start by studying a state-of-the-art parallel implementation of SCD and identify scalability as well as system-level performance bottlenecks of the respective implementation. We then take a principled approa

Evangelos Almpanis, Emmanouil Panagiotidis, Nikolaos Stefanou, Nikolaos Papanikolaou

A thorough theoretical study of the optical properties of periodic Si nanosphere arrays is undertaken, placing particular emphasis on the synergy between electric and magnetic Mie resonances, which occur in high-refractive-index nanoparticles and can lead to a rich variety of phenomena ranging from perfect reflection to controlled diffraction. By means of sy

Jonathan DeWitt

We study the regularity of a conjugacy between an Anosov automorphism $L$ of a nilmanifold $N/Γ$ and a volume-preserving, $C^1$-small perturbation $f$. We say that $L$ is locally Lyapunov spectrum rigid if this conjugacy is $C^{1+}$ whenever $f$ is $C^{1+}$ and has the same volume Lyapunov spectrum as $L$. For $L$ with simple spectrum, we show that local Lya

Farhad Pourkamali-Anaraki, Michael B. Wakin

The high cost of acquiring labels is one of the main challenges in deploying supervised machine learning algorithms. Active learning is a promising approach to control the learning process and address the difficulties of data labeling by selecting labeled training examples from a large pool of unlabeled instances. In this paper, we propose a new data-driven

L. N. Driessen, I. McDonald, D. A. H. Buckley, M. Caleb

We report the discovery of the first transient with MeerKAT, MKT J170456.2$-$482100, discovered in ThunderKAT images of the low mass X-ray binary GX339$-$4. MKT J170456.2$-$482100 is variable in the radio, reaching a maximum flux density of $0.71\pm0.11\,\mathrm{mJy}$ on 2019 Oct 12, and is undetected in 15 out of 48 ThunderKAT epochs. MKT J170456.2$-$482100

Runsheng Yu, Zhenyu Shi, Xinrun Wang, Rundong Wang

Existing value-factorized based Multi-Agent deep Reinforce-ment Learning (MARL) approaches are well-performing invarious multi-agent cooperative environment under thecen-tralized training and decentralized execution(CTDE) scheme,where all agents are trained together by the centralized valuenetwork and each agent execute its policy independently. How-ever, an

Cole Butler, Jinjin Cheng, Lorena Correa, Maria Preciado-Rivas

Methicillin-resistant Staphylococcus aureus (MRSA) is a significant contributor to the growing concern of antibiotic resistant bacteria, especially given its stubborn persistence in hospitals and other health care facility settings. In combination with this characteristic of S. aureus (colloquially referred to as staph), MRSA presents an additional barrier t

Zilong Zhao, Sophie Cerf, Bogdan Robu, Nicolas Marchand

Convolutional neural networks (CNNs) are commonly used for image classification tasks, raising the challenge of their application on data flows. During their training, adaptation is often performed by tuning the learning rate. Usual learning rate strategies are time-based i.e. monotonously decreasing. In this paper, we advocate switching to a performance-bas

Sean K. Sather-Wagstaff

We investigate modules for which vanishing of Tor-modules implies finiteness of homological dimensions (e.g., projective dimension and G-dimension). In particular, we answer a question of O. Celikbas and Sather-Wagstaff about ascent properties of such modules over residually algebraic flat local ring homomorphisms. To accomplish this, we consider ascent and

Rahul Gopinath, Andreas Zeller

Fuzzing is one of the key techniques for evaluating the robustness of programs against attacks. Fuzzing has to be effective in producing inputs that cover functionality and find vulnerabilities. But it also has to be efficient in producing such inputs quickly. Random fuzzers are very efficient, as they can quickly generate random inputs; but they are not ver

Nichita Diaconu, Daniel E Worrall

Attention mechanisms, and most prominently self-attention, are a powerful building block for processing not only text but also images. These provide a parameter efficient method for aggregating inputs. We focus on self-attention in vision models, and we combine it with convolution, which as far as we know, are the first to do. What emerges is a convolution w

Lev V. Utkin, Maxim S. Kovalev, Ernest M. Kasimov

A new method for explaining the Siamese neural network is proposed. It uses the following main ideas. First, the explained feature vector is compared with the prototype of the corresponding class computed at the embedding level (the Siamese neural network output). The important features at this level are determined as features which are close to the same fea

Christian Tiefenau, Maximilian Häring, Eva Gerlitz, Emanuel von Zezschwitz

Smart speakers are gaining popularity. However, such devices can put the user's privacy at risk whenever hot-words are misinterpreted and voice data is recorded without the user's consent. To mitigate such risks, smart speakers provide privacy control mechanisms like the build-in mute button. Unfortunately, previous work indicated that such mute butt

Li-Jun Zhao, Lin Chen, Yu-Min Guo, Kai Wang

We study the trade-off relations satisfied by the genuine tripartite nonlocality in multipartite quantum systems. From the reduced three-qubit density matrices of the four-qubit generalized Greenberger-Horne-Zeilinger (GHZ) states and W states (4-qubit entangled state), we find that there exists a trade-off relation among the mean values of the Svetlichny op

Gégout-Petit Anne, Gueudin-Muller Aurélie, Karmann Clémence

We consider the problem of graph estimation in a zero-inflated Gaussian model. In this model, zero-inflation is obtained by double truncation (right and left) of a Gaussian vector. The goal is to recover the latent graph structure of the Gaussian vector with observations of the zero-inflated truncated vector. We propose a two step estimation procedure. The f

Christian Tiefenau, Maximilian Häring, Mohamed Khamis, Emanuel von Zezschwitz

Nowadays, most mobile devices support biometric authentication schemes like fingerprint or face unlock. However, these probabilistic mechanisms can only be activated in combination with a second alternative factor, usually knowledge-based authentication. In this paper, we show that this aspect can be exploited in a bypass attack. In this bypass attack, the a

Ahmed Imteaj, M. Hadi Amini, Javad Mohammadi

This paper reintroduces the notion of resilience in the context of recent issues originated from climate change triggered events including severe hurricanes and wildfires. A recent example is PG&E's forced power outage to contain wildfire risk which led to widespread power disruption. This paper focuses on answering two questions: who is responsible for

Miodrag J. Mihaljevic

A problem of developing the consensus protocols in public blockchain systems which spend a combination of energy and space resources is addressed. A technique is proposed that provides a flexibility for selection of the energy and space resources which should be spent by a player participating in the consensus procedure. The technique originates from the cry

Daniel Foreman-Mackey, Will M. Farr, Manodeep Sinha, Anne M. Archibald

emcee is a Python library implementing a class of affine-invariant ensemble samplers for Markov chain Monte Carlo (MCMC). This package has been widely applied to probabilistic modeling problems in astrophysics where it was originally published, with some applications in other fields. When it was first released in 2012, the interface implemented in emcee was

Hang Zou, Chao Zhang, Samson Lasaulce, Lucas Saludjian

In this paper, an energy efficiency (EE) game in a MIMO multiple access channel (MAC) communication system is considered. The existence and the uniqueness of the Nash Equilibrium (NE) is affirmed. A bisection search algorithm is designed to find this unique NE. Despite being sub-optimal for deploying the $\varepsilon$-approximate NE of the game when the numb

Xiabi Liu, Xin Duan

Image co-segmentation is important for its advantage of alleviating the ill-pose nature of image segmentation through exploring the correlation between related images. Many automatic image co-segmentation algorithms have been developed in the last decade, which are investigated comprehensively in this paper. We firstly analyze visual/semantic cues for guidin

Riho Rästa, Ivo Heinmaa, Kenta Kimura, Tsuyoshi Kimura

The magnetic structure of the antiferromagnetic square cupola compound Ba(TiO)Cu$_4$(PO$_4$)$_4$ with the tetragonal structure is studied with 31P nuclear magnetic resonance techniques. The magnetic hyperfine shift K shows a clear splitting at the Néel temperature T$_N$ = 9.5 K, where the resonance splits into two lines when an external magnetic field is ori

Zhaohui Che, Ali Borji, Guangtao Zhai, Suiyi Ling

Deep neural networks are vulnerable to adversarial attacks.

Bo Jiang, Pengfei Sun, Jin Tang, Bin Luo

Recently, graph convolutional networks (GCNs) have shown great potential for the task of graph matching. It can integrate graph node feature embedding, node-wise affinity learning and matching optimization together in a unified end-to-end model. One important aspect of graph matching is the construction of two matching graphs. However, the matching graphs we

Josie Williams, Narges Razavian

As machine learning (ML) models, trained on real-world datasets, become common practice, it is critical to measure and quantify their potential biases. In this paper, we focus on renal failure and compare a commonly used traditional risk score, Tangri, with a more powerful machine learning model, which has access to a larger variable set and trained on 1.6 m

Ademar Crotti Junior, Fabrizio Orlandi, Declan O'Sullivan, Christian Dirschl

This paper presents our experience on building RDF knowledge graphs for an industrial use case in the legal domain. The information contained in legal information systems are often accessed through simple keyword interfaces and presented as a simple list of hits. In order to improve search accuracy one may avail of knowledge graphs, where the semantics of th

L. Besombes, H. Boukari, V. Tiwari, A. Lafuente-Sampietro

We study the emission of individual quantum dots in CdTe/ZnTe samples doped with a low concentration of Cr. In addition to dots with a photoluminescence (PL) split by the exchange interaction with a magnetic Cr atom, we observe another type of dots with a complex PL structure composed of a minimum of six lines on the exciton and biexciton and three lines on

Florian Pabst, Andreas Helbling, Jan Gabriel, Peter Weigl

The non-exponential shape of the $α$-process observed in supercooled liquids is considered as one of the hallmarks of glassy dynamics and has thus been under study for decades, but is still poorly understood. For a polar van der Waals liquid, we show here - in line with a recent theory - that dipole-dipole correlations give rise to an additional process in t

Toshihiko Matsuura, Tatsuya Harada

When domains, which represent underlying data distributions, vary during training and testing processes, deep neural networks suffer a drop in their performance. Domain generalization allows improvements in the generalization performance for unseen target domains by using multiple source domains. Conventional methods assume that the domain to which each samp

Kelechukwu Onwukamike, Stéphane Grelier, Etienne Grau, Henri Cramail

As we passed the 20th anniversary of the publication of the 12 principles of green chemistry, the sustainable modification of cellulose, being the most abundant biobased polymer, is certainly worth considering. Many researchers work on an efficient valorization of this renewable resource due to its manifold and promising application possibilities, but very o

Ritu Gupta, Alexander Maisuradze, Nikolai D. Zhigadlo, Hubertus Luetkens

High-quality single crystals of NdFeAsO$_{0.65}$F$_{0.35}$ (the transition temperature $T_{\rm c} \simeq 30.6$~K) were studied in zero-field (ZF) and transverse-field (TF) muon-spin rotation/relaxation ($μ$SR) experiments. An upturn in muon-spin depolarization rate at $T\lesssim 3$~K was observed in ZF-$μ$SR measurements and it was associated with the onset

Neil J. Y. Fan, Peter L. Guo, Simon C. Y. Peng, Sophie C. C. Sun

We confirm a conjecture of Monical, Tokcan and Yong on a characterization of the lattice points in the Newton polytopes of key polynomials.

Wei Lu, Xia Wu, Xiwang Cao

Let $k\leq n$ be two positive integers and $q$ a prime power. The basic question in minimal linear codes is to determine if there exists an $[n,k]_q$ minimal linear code. The first objective of this paper is to present a new sufficient and necessary condition for linear codes to be minimal. Using this condition, it is easy to construct minimal linear codes o

V. Tiwari, K. Makita, M. Arino, M. Morita

We analyse the influence of optically generated non-equilibrium phonons on the spin relaxation and effective spin temperature of an individual Cr atom inserted in a quantum dot. Using a three pulses pump-probe technique, we show that the spin relaxation measured in resonant optical pumping experiments strongly depends on the optical excitation conditions. We

D. S. Grebenkov, R. Metzler, G. Oshanin

In the scenario of the narrow escape problem (NEP) a particle diffuses in a finite container and eventually leaves it through a small "escape window" in the otherwise impermeable boundary, once it arrives to this window and over-passes an entropic barrier at the entrance to it. This generic problem is mathematically identical to that of a diffusion-m

M. Astudillo, M. M. Cavalcanti, V. N. Domingos Cavalcanti, V. H. Gonzalez Martinez

In this work we study the exact boundary controllability of a generalized wave equation in a nonsmooth domain with a nontrapping obstacle. In the more general case, this work contemplates the boundary control of a transmission problem admitting several zones of transmission. The result is obtained using the technique developed by David Russell, taking advant

Gaurav Mittal

In this paper, we discuss the inverse problem of determining a semisimple group algebra from the knowledge of rings of the type sum_{t=1}^s M_{n_t}(Ft), where j is an arbitrary integer and F_t is finite field for each t, and show that it is ill-posed. After then, we define the concept of completeness of the rings of the type sum_{t=1}^s M_{n_t}(Ft) to pose a

Cong Fang, Yihong Gu, Weizhong Zhang, Tong Zhang

Analysis of over-parameterized neural networks has drawn significant attention in recentyears. It was shown that such systems behave like convex systems under various restrictedsettings, such as for two-level neural networks, and when learning is only restricted locally inthe so-called neural tangent kernel space around specialized initializations. However,

Misbahu S. Zubair, David J. Brown, Matthew Bates, Thomas Hughes-Roberts

Visual Programming Tools (VPTs) allow users to create interactive media projects such as games and animations using visual representations of programming concepts. Although VPTs have been shown to have huge potential for teaching children with cognitive impairments including those with Autism Spectrum Condition (ASC), research has shown that existing VPTs ma

Jose J. Blanco-Pillado, Kepa Sousa, Mikel A. Urkiola

Phenomenologically interesting scalar potentials are highly atypical in generic random landscapes. We develop the mathematical techniques to generate constrained random potentials, i.e. Slepian models, which can globally represent low-probability realizations of the landscape. We give analytical as well as numerical methods to construct these Slepian models

C. G. Derntl, G. Scalari, D. Bachmann, M. Beck

The gain recovery time of a heterogeneous active region terahertz quantum cascade laser is studied by terahertz-pump,i terahertz-probe spectroscopy. The investigated active region, which is based on a bound-to-continuum optical transition with an optical phonon assisted extraction, exhibits a gain recovery time in the range of 34$\,$-$\,$50$\,$ps dependent o

J. I. Villa Hernández, L. Suescun, D. R. Sanchez, J. Grassi

The synthesis of the double perovskite Sr2FeWO6 through the direct combustion technique is reported. A complete characterization of the crystalline structure is performed from Synchrotron X-ray measurements and subsequent Rietveld analysis. The results evidence that this material crystallizes in a monoclinic structure, P21/n space group, with strong distorti

Ngoc C. Lê, Manh-Tuan Dao, Hoang-Linh Nguyen, Tuyet-Nhi Nguyen

Social networks play a significant role in today's world. The importance of social networks, for example Facebook or Twitter, are undeniable. However, they also have many issues. One of which is the need for a defense mechanism against fake accounts. It is obviously not a trivial task to separate fake accounts from authentic ones. In this paper, we propo

Mike Reppert, Deborah Reppert, Leonardo A. Pachon, Paul Brumer

Interaction between a quantum system and its environment can induce stationary coherences -- off-diagonal elements in the reduced system density matrix -- even at equilibrium. This work investigates the ``quantumness'' of such phenomena by examining the ability of classical and semiclassical models to describe equilibrium stationary coherence in the

Helmut Prodinger

Two new identities about Catalan numbers are treated with Zeilberger's algorithm and Watson's hypergeometric series evaluation.

Julian Bock, Robert Krajewski, Tobias Moers, Steffen Runde

Automated vehicles rely heavily on data-driven methods, especially for complex urban environments. Large datasets of real world measurement data in the form of road user trajectories are crucial for several tasks like road user prediction models or scenario-based safety validation. So far, though, this demand is unmet as no public dataset of urban road user

Iasson Karafyllis, Tarek Ahmed-Ali, Fouad Giri

We present a new approach for deriving sampled-data observers from continuous-time observers that feature an Input-to-Output Stability property with respect to the output measurement noise and exponential convergence in the noiseless case. The design approach applies to a wide class of systems and yields sampled-data observers that inherit all performance ch

E. F. Sheka, I. Natkaniec, E. U. Ipatova, Ye. A. Golubev

We carried out a joint analysis of the INS, DRIFT, and XPS spectra of a set of sp2 amorphous carbons of the highest carbonization rank representing natural substances (shungite carbon, anthraxolite, and anthracite), technical graphenes (laboratory reduced graphene oxides), and industrial products (carbon blacks). It was determined, that the DRIFT spectra of

Tianyang Zhao, Huajun Zhang, Xiaochuan Liu, Shuhan Yao

In the face of extreme events, e.g., hurricanes, the transmission systems, especially the transmission lines, are affected across time and space. To mitigate these impacts on the day-ahead market from a probabilistic perspective, a resilient unit commitment (UC) problem is formulated as a two-stage robust optimization (RO) problem. In the first stage, the st

Tobias Dornheim, Travis Sjostrom, Shigenori Tanaka, Jan Vorberger

The strongly coupled electron liquid provides a unique opportunity to study the complex interplay of strong coupling with quantum degeneracy effects and thermal excitations. To this end, we carry out extensive \textit{ab initio} path integral Monte Carlo (PIMC) simulations to compute the static structure factor, interaction energy, density response function,

V. Yu. Irkhin, Yu. N. Skryabin

The topic of the review is the application of new ideas of unconventional quantum states to the physics of condensed matter, in particular of solid state, in the context of modern field theory. A comparison is made with classical papers on many-electron theory, including the formalism of many-electron operators. The essentially many-particle nature of the gr

Yury Malyshkin

We prove almost sure convergence of the maximum degree in an evolving graph model combining a growing number of local choices with sublinear preferential attachment. At each step in the growth of the graph, a new vertex is introduced. Then we draw a random number of edges from it to existing vertices, chosen independently by the following rule. For each edge

E. G. Sergeicheva, S. S. Sosin, D. I. Gorbunov, S. Zherlitsyn

We present the magnetic phase diagram of a spin-1/2 chain antiferromagnet Sr$_2$CuO$_3$ studied by ultrasound phase-sensitive detection technique. We observe an enhanced effect of external magnetic field on the ordering temperature of the system, which is in the extreme proximity to the quantum critical point. Inside the Néel ordered phase, we detect an addi

Johan Arcile, Raymond Devillers, Hanna Klaudel

We formalise and study multi-agent timed models MAPTs (Multi-Agent with timed Periodic Tasks), where each agent is associated to a regular timed schema upon which all possibles actions of the agent rely. MAPTs allow for an accelerated semantics and a layered structure of the state space, so that it is possible to explore the latter dynamically and use heuris

Moumita Nandi, A. Thamizhavel, S. K. Dhar

We report the anisotropic magnetic properties of the ternary compound ErAl$_2$Ge$_2$. Single crystals of this compound were grown by high temperature solution growth technique,using Al:Ge eutectic composition as flux. From the powder x-ray diffraction we confirmed that ErAl$_2$Ge$_2$ crystallizes in the trigonal CaAl$_2$Si$_2$-type crystal structure. The ani

Takuma Udagawa, Akiko Aizawa

Common grounding is the process of creating, repairing and updating mutual understandings, which is a fundamental aspect of natural language conversation. However, interpreting the process of common grounding is a challenging task, especially under continuous and partially-observable context where complex ambiguity, uncertainty, partial understandings and mi

Jan Gieseler, Philipp Oleynik, Heli Hietala, Rami Vainio

The Radiation Monitor (RADMON) on-board Aalto-1 CubeSat is an energetic particle detector that fulfills the requirements of small size, low power consumption and low budget. Aalto-1 was launched on 23 June 2017 to a sun-synchronous polar orbit with 97.4° inclination and an average altitude of somewhat above 500 km. RADMON has been measuring integral particle

B. F. Bohlender, A. Michel, J. Jacoby, M. Iberler

A plasma window (PW) is a device for separating two areas of different pressures while letting particle beams pass with little to no loss. It has been introduced by A. Hershcovitch. In the course of this publication, the properties of a PW with apertures of 3.3 mm and 5.0 mm are presented. Especially the link between the pressure properties relevant for appl

Marvin Göbel, Claudius Gros

We introduce and study a non-conserving sandpile model, the autonomously adapting sandpile (AAS) model, for which a site topples whenever it has two or more grains, distributing three or two grains randomly on its neighboring sites, respectively with probability $p$ and $(1-p)$. The toppling process is independent of the actual number of grains $z_i$ of the

Holger Dette, Tim Kutta

Detecting structural changes in functional data is a prominent topic in statistical literature. However not all trends in the data are important in applications, but only those of large enough influence. In this paper we address the problem of identifying relevant changes in the eigenfunctions and eigenvalues of covariance kernels of $L^2[0,1]$-valued time s

Michel Ledoux, Jie-Xiang Zhu

This article is a continuation of the papers [8,9] in which the optimal matching problem, and the related rates of convergence of empirical measures for Gaussian samples are addressed. A further step in both the dimensional and Kantorovich parameters is achieved here, proving that, given $X_1, \ldots, X_n$ independent random variables with common distributio

Boumediene Abdellaoui, Ireneo Peral, Ana Primo

In this work, we are interested on the study of the Fujita exponent and the meaning of the blow-up for the Fractional Cauchy problem with the Hardy potential, namely, \begin{equation*} u_t+(-Δ)^s u=λ\dfrac{u}{|x|^{2s}}+u^{p}\inn\ren,\\ u(x,0)=u_{0}(x)\inn\ren, \end{equation*} where $N> 2s$, $0<s<1$, $(-Δ)^s$ is the fractional laplacian of order $2s$, $ł>0$,

David Jakob Stonner

Werner states are defined as bipartite qudit states that remain unchanged under application of arbitrary unitary operators acting on both subsystems simultaneously. Their preparation is a crucial ingredient in entanglement distillation protocols. This thesis deals with an iterative approach to prepare Werner states asymptotically, using random unitary operat

Julius O. Smith

A simple approach to microphone- and speaker-arrays is described in which the microphone array is regarded as a sampling grid for the acoustic field, and the corresponding speaker-array is treated as a &#34;spatial digital to analog converter&#34; that reconstructs the acoustic field from its spatial samples. Advantages of this approach include ease of under

Wen-Yen Chang, Wen-Huan Chiang, Shao-Hao Lu, Tingfan Wu

The data efficiency of learning-based algorithms is more and more important since high-quality and clean data is expensive as well as hard to collect. In order to achieve high model performance with the least number of samples, active learning is a technique that queries the most important subset of data from the original dataset. In active learning domain,

Arvind Nagarajan, Koen van Erve, Giampiero Gerini

A coupled dielectric-metal metasurface (CDMM) consisting of amorphous silicon (a-$\textit{Si}$) rings and subwavelength holes in $\textit{Au}$ layer separated by a $\textit{SiO}_{2}$ layer is presented. The design parameters of the CDMM is numerically optimized to have a polarization independent peak transmittance of 0.55 at 1540 nm with a Full Width at Half

Ronivon Dias, Pedro Neto, Irvayne Ibiapina, Guilherme Avelino e Otavio Castro

The technical debt (TD) metaphor is widely used to encapsulate numerous software quality problems. She describes the trade-off between the short term benefit of taking a shortcut during the design or implementation phase of a software product (for example, in order to meet a deadline) and the long term consequences of taking said shortcut, which may affect t

Sergey Mozgovoy

Given a locally free coherent sheaf on a smooth algebraic surface, we consider the Quot-scheme parametrizing zero-dimensional quotients of the sheaf and find the corresponding motivic class in the Grothendieck ring of algebraic varieties.

Luca Quaroni

Photothermal-Induced Resonance (PTIR) spectroscopy and imaging with infrared light has seen increasing application in molecular spectroscopy of biological samples. The appeal of the technique lies in its capability to provide information about IR light absorption at a spatial resolution better than allowed by light diffraction, typically below 100 nm. In the

Alexander Kukush, Igor Mandel

A criterion is proposed for testing hypothesis about the nature of the error variance in the dependent variable in linear model, which separates correctly and incorrectly specified models. In the former only measurement errors determine the variance (i.e., dependent variable is correctly explained by independent ones, up to measurement errors), while in the

John W. Blanchard, Teng Wu, James Eills, Yinan Hu

Zero- to ultralow-field nuclear magnetic resonance (ZULF NMR) is an alternative spectroscopic method to high-field NMR, in which samples are studied in the absence of a large magnetic field. Unfortunately, there is a large barrier to entry for many groups, because operating the optical magnetometers needed for signal detection requires some expertise in atom

Lizhen Lin, Brian St. Thomas, Walter W. Piegorsch, James Scott

Shape-constrained inference has wide applicability in bioassay, medicine, economics, risk assessment, and many other fields. Although there has been a large amount of work on monotone-constrained univariate curve estimation, multivariate shape-constrained problems are much more challenging, and fewer advances have been made in this direction. With a focus on

Feilong Song, Chenjiang Qian, Yunuan Wang, Feng Zhang

Hybrid Perovskites have shown a great potential for applications in photovoltaics and light-emitting devices with high efficiency. Interaction between defect-induced trapped excitons and phonons plays an important role in understanding the emerging phenomena for such an excellent figure-of-merit. Here we demonstrate hot polarons with narrow linewidth in $\ma

Philipp Oleynik, Rami Vainio, Arttu Punkkinen, Oleksiy Dudnik

RADMON is a small radiation monitor designed and assembled by students of the University of Turku and the University of Helsinki. It is flown on-board Aalto-1, a 3-unit CubeSat in low Earth orbit at about 500 km altitude. The detector unit of the instrument consists of two detectors, a Si solid-state detector and a CsI(Tl) scintillator, and utilizes the \tex

Jakob Cordes, Andreas Schadschneider, Antoine Tordeux

Classical second order models of pedestrian dynamics, like the social-force model, suffer from various unrealistic behaviors in the dynamics, e.g. backward motion, oscillations and overlapping of pedestrians. These effects are not related to the discretization of the equations of motion, but intrinsic to the dynamics. They are the consequence of strong inert

C. Mackay, M. Dominik, I. A. Steele, C. Snodgrass

GravityCam is a new concept of ground-based imaging instrument capable of delivering significantly sharper images from the ground than is normally possible without adaptive optics. Advances in optical and near infrared imaging technologies allow images to be acquired at high speed without significant noise penalty. Aligning these images before they are combi

Marcela Carvalho, Bertrand Le Saux, Pauline Trouvé-Peloux, Frédéric Champagnat

Aerial or satellite imagery is a great source for land surface analysis, which might yield land use maps or elevation models. In this investigation, we present a neural network framework for learning semantics and local height together. We show how this joint multi-task learning benefits to each task on the large dataset of the 2018 Data Fusion Contest. More

Craig Mackay

It is widely believed that adaptive optics only has a role in correcting turbulent wavefronts on large telescopes using very bright reference stars. Unfortunately these are very scarce and many astronomical targets require wavefront correction to work over much of the sky. We therefore need to be able to use very much fainter reference objects. Laser guide s

José Ignacio Cogolludo-Agustín, Tamás László, Jorge Martín-Morales, András Némethi

We prove that if (C,0) is a reduced curve germ on a rational surface singularity (X,0) then its delta invariant can be recovered by a concrete expression associated with the embedded topological type of the pair (X,C). Furthermore, we also identify it with another (a priori) embedded analytic invariant, which is motivated by the theory of adjoint ideals. Fin

Fedor V. Fomin, Torstein J. F. Strømme

With the introduction of the graph-theoretic time-inconsistent planning model due to Kleinberg and Oren, it has been possible to investigate the computational complexity of how a task designer best can support a present-biased agent in completing the task. In this paper, we study the complexity of finding a choice reduction for the agent; that is, how to rem

Andreas Ketterer, Otfried Gühne

In the course of the last decades entropic uncertainty relations have attracted much attention not only due to their fundamental role as manifestation of non-classicality of quantum mechanics, but also as major tools for applications of quantum information theory. Amongst the latter are protocols for the detection of quantum correlations or for the secure di

Steffen Börm, Sven Christophersen, Ronald Kriemann

A new method to construct task graphs for \mcH-matrix arithmetic is introduced, which uses the information associated with all tasks of the standard recursive \mcH-matrix algorithms, e.g., the block index set of the matrix blocks involved in the computation. Task refinement, i.e., the replacement of tasks by sub-computations, is then used to proceed in the \

Mo Zhou, Zhenxing Niu, Le Wang, Zhanning Gao

For visual-semantic embedding, the existing methods normally treat the relevance between queries and candidates in a bipolar way -- relevant or irrelevant, and all &#34;irrelevant&#34; candidates are uniformly pushed away from the query by an equal margin in the embedding space, regardless of their various proximity to the query. This practice disregards rel

Yibo Yang, Hongyang Li, Xia Li, Qijie Zhao

The panoptic segmentation task requires a unified result from semantic and instance segmentation outputs that may contain overlaps. However, current studies widely ignore modeling overlaps. In this study, we aim to model overlap relations among instances and resolve them for panoptic segmentation. Inspired by scene graph representation, we formulate the over

Arman Arian, Ozgur Yilmaz

Compressed sensing (CS) is a signal acquisition paradigm to simultaneously acquire and reduce dimension of signals that admit sparse representations. When such a signal is acquired according to the principles of CS, the measurements still take on values in the continuum. In today&#39;s &#34;digital&#34; world, a subsequent quantization step, where these meas

Ramtine Tofighi-Shirazi, Irina Mariuca Asavoae, Philippe Elbaz-Vincent

The ability to efficiently detect the software protections used is at a prime to facilitate the selection and application of adequate deob-fuscation techniques. We present a novel approach that combines semantic reasoning techniques with ensemble learning classification for the purpose of providing a static detection framework for obfuscation transformations

Rok Blagus, Jakob Peterlin, Janez Stare

Model checking plays an important role in linear regression as model misspecification seriously affects the validity and efficiency of regression analysis. In practice, model checking is often performed by subjectively evaluating the plot of the model&#39;s residuals. This approach is objectified by constructing a random process from the model&#39;s residual

Francesco Puosi, Antonio Tripodo, Dino Leporini

Many systems, including polymers and molecular liquids, when adequately cooled and/or compressed, solidify into a disordered solid, i.e., a glass. The~transition is not abrupt, featuring progressive decrease of the microscopic mobility and huge slowing down of the relaxation.} A~distinctive aspect of glass-forming materials is the microscopic dynamical heter

Mikkel N. Lund, Emil Knudstrup, Victor Silva Aguirre, Sarbani Basu

We revisit the analysis of the bright multiplanet system K2-93, discovered with data taken by the K2 mission. This system contains five identified planets ranging in size from sub-Neptune to Jupiter size. The K2 data available at the discovery of the system only showed single transits for the three outer planets, which allowed weak constraints to be put on t

Tao Gui, Lizhi Qing, Qi Zhang, Jiacheng Ye

Multi-task learning (MTL) has received considerable attention, and numerous deep learning applications benefit from MTL with multiple objectives. However, constructing multiple related tasks is difficult, and sometimes only a single task is available for training in a dataset. To tackle this problem, we explored the idea of using unsupervised clustering to c

Ahmed Awad Albishri, Syed Jawad Hussain Shah, Anthony Schmiedler, Seung Suk Kang

In recent years, Deep Learning (DL) has shown promising results in conducting AI tasks such as computer vision and image segmentation. Specifically, Convolutional Neural Network (CNN) models in DL have been applied to prevention,detection, and diagnosis in predictive medicine. Image segmentation plays a significant role in disease detection and prevention.Ho

Javor K. Novev, Amin Doostmohammadi, Andreas Zöttl, Julia M. Yeomans

We use mesoscale simulations to gain insight into the digestion of biopolymers by studying the break-up dynamics of polymer aggregates (boluses) bound by physical cross-links. We investigate aggregate evolution, establishing that the linking bead fraction and the interaction energy are the main parameters controlling stability with respect to diffusion. We s

Mohammadreza Kasaei, Nuno Lau, Artur Pereira

Keeping the stability can be counted as the essential ability of a humanoid robot to step out of the laboratory to work in our real environment. Since humanoid robots have similar kinematic to a human, humans expect these robots to be robustly capable of stabilizing even in a challenging situation like while a severe push is applied. This paper presents a ro