June 2020 arXiv papers — page 30

Aitor Villar, Alexander Lohrmann, Xueliang Bai, Tom Vergoossen

Global quantum networks for secure communication can be realised using large fleets of satellites distributing entangled photon-pairs between ground-based nodes. Because the cost of a satellite depends on its size, the smallest satellites will be most cost-effective. This paper describes a miniaturised, polarization entangled, photon-pair source operating on

Vera Steinhoff, Pascal Kerschke, Christian Grimme

When dealing with continuous single-objective problems, multimodality poses one of the biggest difficulties for global optimization. Local optima are often preventing algorithms from making progress and thus pose a severe threat. In this paper we analyze how single-objective optimization can benefit from multiobjectivization by considering an additional obje

Pranav Addepalli, Eric Wu, Douglas Bossart, Christina Lin

Intelligence analysts have long struggled with an abundance of data that must be investigated on a daily basis. In the U.S. Army, this activity involves reconciling information from various sources, a process that has been automated to a certain extent, but which remains highly manual. To promote automation, a semantic analysis prototype was designed to aid

Emmanuella Sandratra Rambeloson, John Shareshian

We show that no tree on twenty vertices with maximum degree ten has Schur positive chromatic symmetric function, thereby providing a counterexample to a conjecture from the paper "Schur and e-positivity of trees and cut vertices".

Boyan H Petkov

The present report briefly reviews the basic features of the current strategy for the protection against the health harms caused by solar ultraviolet (UV, 295 - 400 nm). The emphasis has been made upon the erythema as being the best-studied UV harm and the ability of UV irradiance to damage the deoxyribonucleic acid (DNA) molecules, which leads to carcinogen

S. M. Usman Hashmi, Muntazir Hussain, Fahad Bin Muslim, Kashif Inayat

Time synchronization in any distributed network can be achieved by using application layer protocols for time correction. Time synchronization method proposed in this article uses symbol timing recovery at the physical layer to correct application layer clock. This cross layer methodology diminishes the quantity of message trades needed by application layer

Fushing Hsieh, Elizabeth P. Chou

From two coupled Multiclass Classification (MCC) and Response Manifold Analytics (RMA) perspectives, we develop Categorical Exploratory Data Analysis (CEDA) on PITCHf/x database for the information content of Major League Baseball's (MLB) pitching dynamics. MCC and RMA information contents are represented by one collection of multi-scales pattern categor

Johanna Vorwerk, Uros Markovic, Petros Aristidou, Evangelos Vrettos

In modern power systems, shiftable loads contribute to the flexibility needed to increase robustness and ensure security. Thermal loads are among the most promising candidates for providing such service due to the large thermal storage time constants. This paper demonstrates the use of Variable-Speed Refrigeration (VSR) technology, based on brushless DC moto

J. Hidalgo, M. Schafgans

This paper addresses inference in large panel data models in the presence of both cross-sectional and temporal dependence of unknown form. We are interested in making inferences that do not rely on the choice of any smoothing parameter as is the case with the often employed "HAC" estimator for the covariance matrix. To that end, we propose a cluster

Claudia C Zanella, Andrea Capozzi, Hikari AI Yoshihara, Alice Radaelli

It was demonstrated that nonpersistent radicals can be generated in frozen solutions of metabolites such as pyruvate by irradiation with ultraviolet (UV) light, enabling radical-free dissolution DNP. Although pyruvate is endogenous, an excess of additional pyruvate may perturb metabolic processes, making it potentially unsuitable as a polarizing agent when s

Mansoor Ahmed-Rengers, Ross Anderson, Darija Halatova, Ilia Shumailov

One of the most critical security protocol problems for humans is when you are betraying a trust, perhaps for some higher purpose, and the world can turn against you if you're caught. In this short paper, we report on efforts to enable whistleblowers to leak sensitive documents to journalists more safely. Following a survey of cases where whistleblowers

Christian Aarset, Christian Pötzsche

We study local bifurcations of periodic solutions to time-periodic (systems of) integrodifference equations over compact habitats. Such infinite-dimensional discrete dynamical systems arise in theoretical ecology as models to describe the spatial dispersal of species having nonoverlapping generations. Our explicit criteria allow us to identify branchings of

Hongfei Xu, Josef van Genabith, Deyi Xiong, Qiuhui Liu

The Transformer translation model (Vaswani et al., 2017) based on a multi-head attention mechanism can be computed effectively in parallel and has significantly pushed forward the performance of Neural Machine Translation (NMT). Though intuitively the attentional network can connect distant words via shorter network paths than RNNs, empirical analysis demons

Ferhat Yarkin, Justin P. Coon

In this paper, we propose novel modulation concepts that we call weak composition modulation (WCM) and composition modulation (CM). We use weak and strict compositions of an integer to form codewords of WCM and CM, respectively. For the proposed schemes, we depict a practical model using orthogonal frequency division multiplexing (OFDM). We also analyze the

Fábio Natali, Uyen Le, Dmitry E. Pelinovsky

Periodic waves in the modified Korteweg-de Vries (mKdV) equation are revisited in the setting of the fractional Laplacian. Two families of solutions in the local case are given by the sign-definite dnoidal and sign-indefinite cnoidal solutions. Both solutions can be characterized in the general fractional case as global minimizers of the quadratic part of th

Mohamed Ouzahra

In this paper we are concerned with the approximate controllability of a multidimensional semilinear reaction-diffusion equation governed by a multiplicative control, which is locally distributed in the reaction term. For a given initial state we provide sufficient conditions on the desirable state to be approximately reached within an arbitrarily small time

Melanie Bernhardt, Valery Vishnevskiy, Richard Rau, Orcun Goksel

Speed-of-sound has been shown as a potential biomarker for breast cancer imaging, successfully differentiating malignant tumors from benign ones. Speed-of-sound images can be reconstructed from time-of-flight measurements from ultrasound images acquired using conventional handheld ultrasound transducers. Variational Networks (VN) have recently been shown to

D. Barbato, M. Pinamonti, A. Sozzetti, K. Biazzo

With the growth of comparative exoplanetology, it is increasingly clear that investigating the relationships between inner and outer planets plays a key role in discriminating between competing formation and evolution models. To do so, it is important to probe the inner region of systems hosting long-period giants in search for undetected lower-mass planetar

Yuzhu Guo, Kang Pan, Simeng Li, Zongchang Han

Autoencoders have been widely used for dimensional reduction and feature extraction. Various types of autoencoders have been proposed by introducing regularization terms. Most of these regularizations improve representation learning by constraining the weights in the encoder part, which maps input into hidden nodes and affects the generation of features. In

Hadrien Hendrikx, Francis Bach, Laurent Massoulié

We consider the problem of training machine learning models on distributed data in a decentralized way. For finite-sum problems, fast single-machine algorithms for large datasets rely on stochastic updates combined with variance reduction. Yet, existing decentralized stochastic algorithms either do not obtain the full speedup allowed by stochastic updates, o

Kazunori Ando, Hyeonbae Kang, Yoshihisa Miyanishi

We consider the spectral structure of the Neumann--Poincaré operators defined on the boundaries of thin domains of rectangle shape in two dimensions. We prove that as the aspect ratio of the domains tends to $\infty$, or equivalently, as the domains get thinner, the spectra of the Neumann--Poincaré operators are densely distributed in the interval $[-1/2,1/2

Victor Picheny, Vincent Dutordoir, Artem Artemev, Nicolas Durrande

Many machine learning models require a training procedure based on running stochastic gradient descent. A key element for the efficiency of those algorithms is the choice of the learning rate schedule. While finding good learning rates schedules using Bayesian optimisation has been tackled by several authors, adapting it dynamically in a data-driven way is a

Yasuhiro Yao, Menandro Roxas, Ryoichi Ishikawa, Shingo Ando

We propose an unsupervised real-time dense depth completion from a sparse depth map guided by a single image. Our method generates a smooth depth map while preserving discontinuity between different objects. Our key idea is a Binary Anisotropic Diffusion Tensor (B-ADT) which can completely eliminate smoothness constraint at intended positions and directions

Stelian Ion, Dorin Marinescu, Stefan-Gicu Cruceanu

In this paper, we present a deduction of swallow water equations in the presence of vegetation based on spatial averaging techniques starting from the general principles of conservation of mass and momentum. For this purpose, we worked in the hydrostatic approximation of the pressure field and we considered certain hypotheses of kinematic and topographical n

Chenghao Li, Xiaoteng Ma, Chongjie Zhang, Jun Yang

The option framework has shown great promise by automatically extracting temporally-extended sub-tasks from a long-horizon task. Methods have been proposed for concurrently learning low-level intra-option policies and high-level option selection policy. However, existing methods typically suffer from two major challenges: ineffective exploration and unstable

Wei Liu, Jie Huang

In this article, we update the reference [14] in two aspects. First, we note that in order for the control law (12) in [14] to be equivalent to the control law (3) in [14], we need to assume that the samplings for all subsystems must be synchronous, i.e., we need to assume that $T_{i}=T$ for all $i=1,\cdots,N$. Second, we extend our results from periodic sam

Lauren Watson, Benedek Rozemberczki, Rik Sarkar

Private machine learning involves addition of noise while training, resulting in lower accuracy. Intuitively, greater stability can imply greater privacy and improve this privacy-utility tradeoff. We study this role of stability in private empirical risk minimization, where differential privacy is achieved by output perturbation, and establish a correspondin

Finnegan Waugh, Ralph Holz

The Bitcoin Lightning network is a mechanism to enable fast and inexpensive off-chain Bitcoin transactions using peer-to-peer (P2P) channels between nodes that can also be composed into a routing path. Although the resulting possible channel graphs are well-studied, there is no empirical data on the network's reliability in terms of being able to success

Samuel D. N. Johnson, Sean P. Cox

Management performance of five alternative stock assessment methods was evaluated by using them to set harvest levels targeting multi-species maximum yield in a multi-species flatfish fishery, including single-species and hierarchical multi-species models, and methods that pooled data across species and spatial strata, with catch outcomes of each method unde

Henning A. Fürst, Chih-Han Yeh, Dimitri Kalincev, André P. Kulosa

We report on the first coherent excitation of the highly forbidden $^2S_{1/2}\rightarrow{}^2F_{7/2}$ electric octupole (E3) transition in a single trapped ${}^{172}$Yb$^+$ ion, an isotope without nuclear spin. Using the transition in ${}^{171}$Yb$^+$ as a reference, we determine the transition frequency to be $642\,116\,784\,950\,887.6(2.4)\,$Hz. We map out

Léo Morel, Zhibin Yao, Pierre Cladé, Saïda Guellati-Khélifa

Atom interferometry relies on the separation and recombination of atom wavepackets. When the two paths overlap perfectly at the end of the interferometer, the phase is insensitive to the atomic velocity distribution. Here, we show that, when the separation and recombination is performed using a Raman transition there is a displacement of the atomic wavepacke

Johannes Kleiner

The theory of causal fermion systems is a new physical theory which aims to describe a fundamental level of physical reality. Its mathematical core is the causal action principle. In this thesis, we develop a formalism which connects the causal action principle to a suitable notion of fields on space-time. We derive field equations from the causal action pri

Dániel Lévai, Zsolt Zombori

The Lottery Ticket Hypothesis postulates that a freshly initialized neural network contains a small subnetwork that can be trained in isolation to achieve similar performance as the full network. Our paper examines several alternatives to search for such subnetworks. We conclude that incorporating a data dependent component into the pruning criterion in the

Alex Shamis, Matthew Renzelmann, Stanko Novakovic, Georgios Chatzopoulos

Transactions can simplify distributed applications by hiding data distribution, concurrency, and failures from the application developer. Ideally the developer would see the abstraction of a single large machine that runs transactions sequentially and never fails. This requires the transactional subsystem to provide opacity (strict serializability for both c

Zhenxi Zhang, Chunna Tian, Jie Li, Zhusi Zhong

Medical image segmentation is usually regarded as one of the most important intermediate steps in clinical situations and medical imaging research. Thus, accurately assessing the segmentation quality of the automatically generated predictions is essential for guaranteeing the reliability of the results of the computer-assisted diagnosis (CAD). Many researche

Zhenbin Guo, Haimin Yao

The large volume change of the silicon (Si) during lithiation and delithiation process has long been a problem impeding its application as one of the most promising anode materials for LIBs. In this paper, we proposed a conceptually new idea to address this problem simply by varying the thickness of the electrode material film. The resulting thickness-gradie

Maxime Conjard, Henning Omre

Data assimilation in models representing spatio-temporal phenomena poses a challenge, particularly if the spatial histogram of the variable appears with multiple modes. The traditional Kalman model is based on a Gaussian initial distribution and Gauss-linear dynamic and observation models. This model is contained in the class of Gaussian distribution and is

Guido Sterbini

In this Chapter we briefly recall and summarize the main linear optics concepts of the accelerators beam dynamics theory. In doing so we put our emphasis on the related computational aspects: the reader will be provided with the basic elements to write a linear optics code. To this aim, we complement the text with few practical examples and code listings.

Anike Purbawati, Johann Coraux, Jan Vogel, Abdellali Hadj-Azzem

The recent discovery of magnetic van der Waals materials has triggered a wealth of investigations in materials science, and now offers genuinely new prospects for both fundamental and applied research. Although the catalogue of van der Waals ferromagnets is rapidly expanding, most of them have a Curie temperature below 300 K, a notable disadvantage for poten

Mário J. de Oliveira

The stochastic thermodynamics provides a framework for the description of systems that are out of thermodynamic equilibrium. It is based on the assumption that the elementary constituents are acted by random forces that generate a stochastic dynamics, which is here represented by a Fokker-Planck-Kramers equation. We emphasize the role of the irreversible pro

Jerrick Wee, Nadejda Blagorodnova, Bryan Edward Penprase, Jett Pierce Facey

We present optical and infrared photometry of the classical nova V906 Car, also known as Nova Car 2018 and ASASSN-18fv, discovered by ASASS-SN survey on 16.32 March 2018 UT (MJD 58193.0). The nova reached its maximum on MJD 58222.56 at $V_{\rm{max}} = 5.84 \pm 0.09$ mag and had decline times of $t_{2,V} = 26.2 $ d and $t_{3,V} = 33.0 $ d. The data from Evrys

A. V. Giannini, V. P. Goncalves, P. V. R. G. Silva

The characteristics of the thermal radiation are investigated using a two - component model, with the hard component being described by the Color Glass Condensate formalism. The inclusive transverse momentum spectra of charged hadrons produced in proton - proton and proton - nucleus collisions at LHC energies and large - $p_T$ are estimated using the running

Deepak K. Sharma, Adrian Agreda, Julien Barthes, Gérard Colas des Francs

We report a quantitative analysis of the wavevector diagram emitted by nonlinear photoluminescence generated by a tightly focused pulsed laser beam and distributed along Au nanowire via the mediation of surface plasmon polaritions. The nonlinear photoluminescence is locally excited at key locations along the nanowire in order to understand the different cont

Mikhail Belishev, Timur Khabibullin

The dynamical system under consideration is \begin{align*} & u_{tt}-u_{xx}+Vu=0,\qquad x>0,\,\,\,t>0;\\ & u|_{t=0}=u_t|_{t=0}=0,\,\,x\geqslant 0;\quad u|_{x=0}=f,\,\,t\geqslant 0, \end{align*} where $V=V(x)$ is a matrix-valued function ({\it potential}); $f=f(t)$ is an $\mathbb R^N$-valued function of time ({\it boundary control}); $u=u^f(x,t)$ is a {\it tra

Alex Chao

An overview of dynamical systems in accelerator physics is presented with a suggestion of a few issues to be addressed. Also mentioned are a few possible developments in the future. Technical details supporting the views are not presented.

Simone Piaggesi, André Panisson

Representation learning models for graphs are a successful family of techniques that project nodes into feature spaces that can be exploited by other machine learning algorithms. Since many real-world networks are inherently dynamic, with interactions among nodes changing over time, these techniques can be defined both for static and for time-varying graphs.

Sohvi Luukkonen, Luc Belloni, Daniel Borgis, Maximilien Levesque

We assess the performance of molecular densityfunctional theory (MDFT) to predict hydration freeenergies of the small drug-like molecules benchmark,FreeSolv. MDFT in the hyper-netted chain approx-imation (HNC) coupled with a pressure correctionpredicts experimental hydration free energies of theFreeSolv database within 1 kcal/mol with an averagecomputation t

Manuel de León, Manuel Lainz, Miguel C. Muñoz-Lecanda

In this paper we combine two main topics in mechanics and optimal control theory: contact Hamiltonian systems and Pontryagin Maximum Principle. As an important result, among others, we develop a contact Pontryagin Maximum Principle that permits to deal with optimal control problems with dissipation. We also consider the Herglotz optimal control problem, whic

Houssem Sifaou, Abla Kammoun, Mohamed-Slim Alouini

Quadratic discriminant analysis (QDA) is a widely used classification technique that generalizes the linear discriminant analysis (LDA) classifier to the case of distinct covariance matrices among classes. For the QDA classifier to yield high classification performance, an accurate estimation of the covariance matrices is required. Such a task becomes all th

Xiangrong Zhu, Zi-qiang Zhang

We study the effect of chemical potential and nonconformality on the jet quenching parameter in a holographic QCD model with conformal invariance broken by a background dilaton. It turns out that the presence of chemical potential and nonconformality both increase the jet quenching parameter thus enhancing the energy loss, consistently with the findings of t

Nancy Aggarwal

One of the noise sources that currently limits gravitational wave (GW) detectors comes from the quantum nature of the light causing uncertain amplitude and phase. Phase uncertainty limits the precision of an interferometric measurement. This measurement is also subject to quantum back-action, caused by the radiation pressure force fluctuations produced by th

Sergiy Zhuk, Jonathan P. Epperlein, Rahul Nair, Seshu Thirupati

Intra-operative identification of malignant versus benign or healthy tissue is a major challenge in fluorescence guided cancer surgery. We propose a perfusion quantification method for computer-aided interpretation of subtle differences in dynamic perfusion patterns which can be used to distinguish between normal tissue and benign or malignant tumors intra-o

Santosh Kumar Barnwal, Uma Shanker Tiwary

Repeated reading (RR) helps learners, who have little to no experience with reading fluently to gain confidence, speed and process words automatically. The benefits of repeated readings include helping all learners with fact recall, aiding identification of learners' main ideas and vocabulary, increasing comprehension, leading to faster reading as well a

Toussain Cardot, Pilar Marxer, Ivan Snozzi

The goal of this project is to build a deep-learning solution that deblurs cornea scans, used for medical examination. The spherical shape of the eye prevents ophtamologist from having completely sharp image. Provided with a stack of corneas from confocal images, our approach is to build a model that performs an upscaling of the images using an SR (Super Res

Simone Santini

These notes from a graduate class at the Unuversidad Autonoma de Madrid analyze a search behavior known as Area Resticted Search (ARS), widespread in the animal kingdom, and optimal when the resources that one is after are "patchy". In the first section we study the importance of the behavior in animal and its dependence on the dopamine as a indicato

Marc Ditzhaus, Dennis Dobler, Markus Pauly

Factorial survival designs with right-censored observations are commonly inferred by Cox regression and explained by means of hazard ratios. However, in case of non-proportional hazards, their interpretation can become cumbersome; especially for clinicians. We therefore offer an alternative: median survival times are used to estimate treatment and interactio

Behrooz Makki, Tommy Svensson, Michele Zorzi

In this paper, we propose and analyze an error-constrained data transmission approach for uplink communication using non-orthogonal multiple access (NOMA). The results are presented for the cases with hybrid automatic repeat request (HARQ) protocols where, depending on the message decoding status in the previous rounds, the decoding scheme of the receiver as

Sudhanshu Barway, Y. D. Mayya, Aitor Robleto-Orús

We report the discovery of a bar, a pseudobulge and unresolved point source in the archetype collisional ring galaxy Cartwheel using careful morphological analysis of a near-infrared (NIR) K$_s$ band image of excellent quality (seeing=0.42\arcsec) at the ESO archive. The bar is oval-shaped with a semi-major axis length of 3.23\arcsec\($\sim$2.09~kpc), with a

Théophile Carniel, Jean-Michel Dalle

We suggest the use of indicators to analyze entrepreneurial ecosystems, in a way similar to ecological indicators: simple, measurable, and actionable characteristics, used to convey relevant information to stakeholders and policymakers. We define 3 possible such indicators: Fundraising Speed, Acceleration and nth-year speed, all related to the ability of sta

Douglas Blackwell, Damiano Testa

We study factorizations of HOMFLY polynomials of certain knots and oriented links. We begin with a computer analysis of knots with at most 12 crossings, finding 17 non-trivial factorizations. Next, we give an irreducibility criterion for HOMFLY polynomials of oriented links associated to 2-connected plane graphs.

Nicolas Bousquet, Takehiro Ito, Yusuke Kobayashi, Haruka Mizuta

Let $G$ be a graph and $T_1,T_2$ be two spanning trees of $G$. We say that $T_1$ can be transformed into $T_2$ via an edge flip if there exist two edges $e \in T_1$ and $f$ in $T_2$ such that $T_2= (T_1 \setminus e) \cup f$. Since spanning trees form a matroid, one can indeed transform a spanning tree into any other via a sequence of edge flips, as observed

Xiehe Huang, Weihong Deng, Haifeng Shen, Xiubao Zhang

Deep learning technique has dramatically boosted the performance of face alignment algorithms. However, due to large variability and lack of samples, the alignment problem in unconstrained situations, \emph{e.g}\onedot large head poses, exaggerated expression, and uneven illumination, is still largely unsolved. In this paper, we explore the instincts and rea

Abolfazl Tarizadeh, Mohsen Aghajani

In this paper, a combination of algebraic and topological methods are applied to obtain new and structural results on harmonic rings. Especially, it is shown that if a Gelfand ring $A$ modulo its Jacobson radical is a zero dimensional ring, then $A$ is a clean ring. It is also proved that, for a given Gelfand ring $A$, then the retraction map Spec$(A)\righta

Irina Higgins, Le Chang, Victoria Langston, Demis Hassabis

Deep supervised neural networks trained to classify objects have emerged as popular models of computation in the primate ventral stream. These models represent information with a high-dimensional distributed population code, implying that inferotemporal (IT) responses are also too complex to interpret at the single-neuron level. We challenge this view by mod

Ekaterina I. Marchenko, Sergey A. Fateev, Andrey A. Petrov, Vadim V. Korolev

We describe a first open-access database of experimentally investigated hybrid organic-inorganic materials with two-dimensional (2D) perovskite-like crystal structure. The database includes 515 compounds, containing 180 different organic cations, 10 metals (Pb, Sn, Bi, Cd, Cu, Fe, Ge, Mn, Pd, Sb) and 3 halogens (I, Br, Cl) known so far and will be regularly

A. N. Kumar, P. Vellaisamy, F. Viens

In this article, we obtain, for the total variance distance, the error bounds between Poisson and convolution of power series distributions via Stein's method. This provides a unified approach to many known discrete distributions. Several Poisson limit theorems follow as corollaries from our bounds. As applications, we compare the Poisson approximation r

Martin Held, Stefan de Lorenzo

We present a simple wavefront-like approach for computing multiplicatively weighted Voronoi diagrams of points and straight-line segments in the Euclidean plane. If the input sites may be assumed to be randomly weighted points then the use of a so-called overlay arrangement [Har-Peled&Raichel, Discrete Comput. Geom. 53:547-568, 2015] allows to achieve an exp

Kha-Hung Nguyen, Hieu V. Nguyen, Van-Phuc Bui, Oh-Soon Shin

This paper considers a downlink (DL) system where non-orthogonal multiple access (NOMA) beamforming and dynamic user pairing are jointly optimized to maximize the minimum throughput of all DL users. The resulting problem belongs to a class of mixed-integer non-convex optimization. To solve the problem, we first relax the binary variables to continuous ones,

Gemma Massonis, Julio R. Banga, Alejandro F. Villaverde

The recent coronavirus disease (COVID-19) outbreak has dramatically increased the public awareness and appreciation of the utility of dynamic models. At the same time, the dissemination of contradictory model predictions has highlighted their limitations. If some parameters and/or state variables of a model cannot be determined from output measurements, its

R. J. Hudspith, B. Colquhoun, A. Francis, R. Lewis

We perform an $n_f=2+1$ lattice study of a number of channels where past claims exist in the literature for the existence of strong-interaction-stable light-heavy tetraquarks. We find no evidence for any such deeply-bound states, beyond the $J^P=1^+$, $I=0$ $ud\bar{b}\bar{b}$ and $I=1/2$ $ls\bar{b}\bar{b}$ states already identified in earlier lattice studies

J. Szeftel, A. Khater

A general hamiltonian $H$ of electrons in finite concentration, interacting via any two-body coupling inside a crystal of arbitrary dimension, is considered. For simplicity and without loss of generality, a one-band model is used to account for the electron-crystal interaction. The electron motion is described in the Hilbert space $S_ϕ$, spanned by a basis o

Yi Guo, Shunan Guo, Zhuochen Jin, Smiti Kaul

Event sequence data record series of discrete events in the time order of occurrence. They are commonly observed in a variety of applications ranging from electronic health records to network logs, with the characteristics of large-scale, high-dimensional, and heterogeneous. This high complexity of event sequence data makes it difficult for analysts to manua

Yuhsiang M. Tsai, Terry Cojean, Tobias Ribizel, Hartwig Anzt

With AMD reinforcing their ambition in the scientific high performance computing ecosystem, we extend the hardware scope of the Ginkgo linear algebra package to feature a HIP backend for AMD GPUs. In this paper, we report and discuss the porting effort from CUDA, the extension of the HIP framework to add missing features such as cooperative groups, the perfo

Jing Guo, Yuming Liu, Yu Ye, Zhen Zhang

Let $A$ be a representation-finite self-injective algebra over an algebraically closed field $k$. We give a new characterization for an orthogonal system in the stable module category $A$-$\stmod$ to be a simple-minded system. As a by-product, we show that every Nakayama-stable orthogonal system in $A$-$\stmod$ extends to a simple-minded system.

Jing Guo, Yuming Liu, Yu Ye, Zhen Zhang

Recently, we obtained in [7] a new characterization for an orthogonal system to be a simple-minded system in the stable module category of any representation-finite self-injective algebra. In this paper, we apply this result to give an explicit construction of simple-minded systems over self-injective Nakayama algebras.

Justin Lizama

A new loss function is proposed for neural networks on classification tasks which extends the hinge loss by assigning gradients to its critical points. We will show that for a linear classifier on linearly separable data with fixed step size, the margin of this modified hinge loss converges to the $\ell_2$ max-margin at the rate of $\mathcal{O}( 1/t )$. This

Rasool Fakoor, Jonas Mueller, Nick Erickson, Pratik Chaudhari

Automated machine learning (AutoML) can produce complex model ensembles by stacking, bagging, and boosting many individual models like trees, deep networks, and nearest neighbor estimators. While highly accurate, the resulting predictors are large, slow, and opaque as compared to their constituents. To improve the deployment of AutoML on tabular data, we pro

Davide Straninger

Due to age-related hearing loss, elderly people often struggle with following the language on TV. Because they form an increasing part of the audience, this problem will become even more important in the future and needs to be addressed by research and development. Object-based audio is a promising approach to solve this issue as it offers the possibility of

M. Sajjad Edalatzadeh

Robot arms with lighter weight can reduce unnecessary energy consumption which is desirable in robotic industry. However, lightweight arms undergo undesirable elastic deformation. In this paper, the planar motion of a lightweight flexible arm is investigated. In order to obtain a precise mathematical model, the axial displacement and nonlinear curvature of f

Erdi Kuşdemir, Caroline Chèze, Raffaella Calarco

We present a detailed investigation of the mechanisms at play for the incorporation of In and Mg on the GaN(0001) surface during plasma-assisted molecular beam epitaxy (PAMBE). First, we have studied the kinetics of In desorption in the presence of Mg either without or with N supply from the plasma cell by quadrupole mass spectrometry (QMS) in the line of si

Erion Çano, Riccardo Coppola, Eleonora Gargiulo, Marco Marengo

Driving and music listening are two inseparable everyday activities for millions of people today in the world. Considering the high correlation between music, mood and driving comfort and safety, it makes sense to use appropriate and intelligent music recommendations based on the mood of drivers and songs in the context of car driving. The objective of this

Richard Schoeffauer, Gerhard Wunder

In a batch of synchronized queues, customers can only be serviced all at once or not at all, implying that service remains idle if at least one queue is empty. We propose that a batch of $n$ synchronized queues in a discrete-time setting is quasi-stable for $n \in \{2,3\}$ and unstable for $n \geq 4$. A correspondence between such systems and a random-walk-l

Futo Tomizawa, Yohei Sawada

Prediction of spatio-temporal chaotic systems is important in various fields, such as Numerical Weather Prediction (NWP). While data assimilation methods have been applied in NWP, machine learning techniques, such as Reservoir Computing (RC), are recently recognized as promising tools to predict spatio-temporal chaotic systems. However, the sensitivity of th

K. T. Huber, V. Moulton, G. E. Scholz

Introgression is an evolutionary process in which genes or other types of genetic material are introduced into a genome. It is an important evolutionary process that can, for example, play a fundamental role in speciation. Recently the concept of an overlaid species forest was introduced to represent introgression histories. Basically this approach takes a p

Manuela Aguiar, Ana Dias

We consider weighted coupled cell networks, that is networks where the interactions between any two cells have an associated weight that is a real valued number. Weighted networks are ubiquitous in real-world applications. We consider a dynamical systems perspective by associating to each network a set of continuous dynamical systems, the ones that respect t

Weinan Lin, Baishun Yang, Andy Paul Chen, Xiaohan Wu

We report on the study of both perpendicular magnetic anisotropy (PMA) and Dzyaloshinskii-Moriya interaction (DMI) at an oxide/ferromagnetic metal (FM) interface, i.e. BaTiO3 (BTO)/CoFeB. Thanks to the functional properties of the BTO film and the capability to precisely control its growth, we are able to distinguish the dominant role of the oxide terminatio

Özlem Tuğfe Demir, Emil Björnson

We consider large-scale fading precoding (LSFP), which is a two-layer precoding scheme in the downlink of multi-cell massive MIMO (multiple-input multiple-output) systems to suppress inter-cell interference. We obtain the closed-form spectral efficiency (SE) with LSFP at the central network controller and maximum ratio precoding at the base stations (BSs) us

Yasin Yazici, Chuan-Sheng Foo, Stefan Winkler, Kim-Hui Yap

We examine two key questions in GAN training, namely overfitting and mode drop, from an empirical perspective. We show that when stochasticity is removed from the training procedure, GANs can overfit and exhibit almost no mode drop. Our results shed light on important characteristics of the GAN training procedure. They also provide evidence against prevailin

Chiranjib Sur

Attention mechanism has gained huge popularity due to its effectiveness in achieving high accuracy in different domains. But attention is opportunistic and is not justified by the content or usability of the content. Transformer like structure creates all/any possible attention(s). We define segregating strategies that can prioritize the contents for the app

Chiranjib Sur

Video captioning works on the two fundamental concepts, feature detection and feature composition. While modern day transformers are beneficial in composing features, they lack the fundamental problems of selecting and understanding of the contents. As the feature length increases, it becomes increasingly important to include provisions for improved capturin

H. Cakir, N. S. Oreshkina, I. A. Valuev, V. Debierre

A means to extract the fine-structure constant $α$ from precision spectroscopic data on one-electron ions is presented. We show that in an appropriately weighted difference of the bound-electron $g$ factor and the ground state energy, nuclear structural effects can be effectively suppressed. This method is anticipated to deliver an independent value of $α$ v

Zhigang Li

In this paper, we mainly consider about the existence and uniqueness of global weak solutions for the two-component Novikov system. We first recall some results and definitions of strong solutions and weak solutions for the system, then by using the method of approximation of smooth solutions, we prove the existence and uniqueness of global weak solutions of

Pasquale Davide Schiavone, Davide Rossi, Alfio Di Mauro, Frank Gurkaynak

A wide range of Internet of Things (IoT) applications require powerful, energy-efficient and flexible end-nodes to acquire data from multiple sources, process and distill the sensed data through near-sensor data analytics algorithms, and transmit it wirelessly. This work presents Arnold: a 0.5 V to 0.8 V, 46.83 uW/MHz, 600 MOPS fully programmable RISC-V Micr

Usha Srinivasan, Rangachari Kidambi

We present SPEC-RE, a new algorithm to sort complex eigenvalues, generated as the solutions to algebraic equations, whose coefficients are analytic functions of one or many, possibly complex parameters. The fact that the eigenvalues are analytic functions of the parameters, with atmost algebraic singularities, is used in formulating the algorithm. Several ex

Manon Flageat, Antoine Cully

Quality-Diversity optimisation algorithms enable the evolution of collections of both high-performing and diverse solutions. These collections offer the possibility to quickly adapt and switch from one solution to another in case it is not working as expected. It therefore finds many applications in real-world domain problems such as robotic control. However

Hirotaka Ito, Amir Levinson, Ehud Nakar

Strong explosion of a compact star surrounded by a thick stellar wind drives a fast ($>0.1c$) radiation mediated shock (RMS) that propagates in the wind, and ultimately breaks out gradually once photons start escaping from the shock transition layer. In exceptionally strong or aspherical explosions the shock velocity may even be relativistic. The properties

Frank Schweitzer, Yan Zhang, Giona Casiraghi

We investigate a multi-agent model of firms in an R\&D network. Each firm is characterized by its knowledge stock $x_{i}(t)$, which follows a non-linear dynamics. It can grow with the input from other firms, i.e., by knowledge transfer, and decays otherwise. Maintaining interactions is costly. Firms can leave the network if their expected knowledge growth is

Severin Gsponer, Luca Costabello, Chan Le Van, Sumit Pai

Sequence classification is the supervised learning task of building models that predict class labels of unseen sequences of symbols. Although accuracy is paramount, in certain scenarios interpretability is a must. Unfortunately, such trade-off is often hard to achieve since we lack human-independent interpretability metrics. We introduce a novel sequence lea

Diana Cholakova, Desislava Glushkova, Slavka Tcholakova, Nikolai Denkov

We describe several unexpected phenomena, caused by a solid-solid phase transition (gel-to-crystal) typical for all main classes of lipid substances - phospholipids, triglycerides, diglycerides, alkanes, etc. We discovered that this transition leads to spontaneous formation of a network of nanopores, spreading across the entire lipid structure. These nanopor

Noe Elisa

In spite of the fact that e-government agency (ega) in Tanzania emphasize on the use of ICT within public institutions in Tanzania, accessibility, usability and web security vulnerabilities are still not considered by the majority of web developers. The main objective of this study is to assess the usability, accessibility and web security vulnerabilities of