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Spatial solitons in thermo-optical media from the nonlinear Schrodinger-Poisson equation and dark matter analogues
We analyze theoretically the Schrodinger-Poisson equation in two transverse dimensions in the presence of a Kerr term. The model describes the nonlinear propagation of optical beams in thermooptical media and can be regarded as an analogue system for a self-gravitating self-interacting wave. We compute numerically th...
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Instrument-Armed Bandits
We extend the classic multi-armed bandit (MAB) model to the setting of noncompliance, where the arm pull is a mere instrument and the treatment applied may differ from it, which gives rise to the instrument-armed bandit (IAB) problem. The IAB setting is relevant whenever the experimental units are human since free wi...
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Deep learning Inversion of Seismic Data
In this paper, we propose a new method to tackle the mapping challenge from time-series data to spatial image in the field of seismic exploration, i.e., reconstructing the velocity model directly from seismic data by deep neural networks (DNNs). The conventional way to address this ill-posed seismic inversion problem...
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Nopol: Automatic Repair of Conditional Statement Bugs in Java Programs
We propose NOPOL, an approach to automatic repair of buggy conditional statements (i.e., if-then-else statements). This approach takes a buggy program as well as a test suite as input and generates a patch with a conditional expression as output. The test suite is required to contain passing test cases to model the e...
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Parametric geometry of numbers in function fields
Parametric geometry of numbers is a new theory, recently created by Schmidt and Summerer, which unifies and simplifies many aspects of classical Diophantine approximations, providing a handle on problems which previously seemed out of reach. Our goal is to transpose this theory to fields of rational functions in one ...
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Refined open intersection numbers and the Kontsevich-Penner matrix model
A study of the intersection theory on the moduli space of Riemann surfaces with boundary was recently initiated in a work of R. Pandharipande, J. P. Solomon and the third author, where they introduced open intersection numbers in genus 0. Their construction was later generalized to all genera by J. P. Solomon and the...
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SEIRS epidemics in growing populations
An SEIRS epidemic with disease fatalities is introduced in a growing population (modelled as a super-critical linear birth and death process). The study of the initial phase of the epidemic is stochastic, while the analysis of the major outbreaks is deterministic. Depending on the values of the parameters, the follow...
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A Multi-task Selected Learning Approach for Solving New Type 3D Bin Packing Problem
This paper studies a new type of 3D bin packing problem (BPP), in which a number of cuboid-shaped items must be put into a bin one by one orthogonally. The objective is to find a way to place these items that can minimize the surface area of the bin. This problem is based on the fact that there is no fixed-sized bin ...
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Use of Docker for deployment and testing of astronomy software
We describe preliminary investigations of using Docker for the deployment and testing of astronomy software. Docker is a relatively new containerisation technology that is developing rapidly and being adopted across a range of domains. It is based upon virtualization at operating system level, which presents many adv...
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Label Embedding Network: Learning Label Representation for Soft Training of Deep Networks
We propose a method, called Label Embedding Network, which can learn label representation (label embedding) during the training process of deep networks. With the proposed method, the label embedding is adaptively and automatically learned through back propagation. The original one-hot represented loss function is co...
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On the Performance of Multi-Instrument Solar Flare Observations During Solar Cycle 24
The current fleet of space-based solar observatories offers us a wealth of opportunities to study solar flares over a range of wavelengths. Significant advances in our understanding of flare physics often come from coordinated observations between multiple instruments. Consequently, considerable efforts have been, an...
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A Feature Complete SPIKE Banded Algorithm and Solver
New features and enhancements for the SPIKE banded solver are presented. Among all the SPIKE algorithm versions, we focus our attention on the recursive SPIKE technique which provides the best trade-off between generality and parallel efficiency, but was known for its lack of flexibility. Its application was essentia...
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Dark Matter in the Local Group of Galaxies
We describe the neutrino flavor (e = electron, u = muon, t = tau) masses as m(i=e;u;t)= m + [Delta]mi with |[Delta]mij|/m < 1 and probably |[Delta]mij|/m << 1. The quantity m is the degenerate neutrino mass. Because neutrino flavor is not a quantum number, this degenerate mass appears in the neutrino equation of stat...
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Effective Extensible Programming: Unleashing Julia on GPUs
GPUs and other accelerators are popular devices for accelerating compute-intensive, parallelizable applications. However, programming these devices is a difficult task. Writing efficient device code is challenging, and is typically done in a low-level programming language. High-level languages are rarely supported, o...
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Finite Time Adaptive Stabilization of LQ Systems
Stabilization of linear systems with unknown dynamics is a canonical problem in adaptive control. Since the lack of knowledge of system parameters can cause it to become destabilized, an adaptive stabilization procedure is needed prior to regulation. Therefore, the adaptive stabilization needs to be completed in fini...
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On the composition of Berezin-Toeplitz operators on symplectic manifolds
We compute the second coefficient of the composition of two Berezin-Toeplitz operators associated with the $\text{spin}^c$ Dirac operator on a symplectic manifold, making use of the full-off diagonal expansion of the Bergman kernel.
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Maximum and minimum operators of convex integrands
For given convex integrands $\gamma_{{}_{i}}: S^{n}\to \mathbb{R}_{+}$ (where $i=1, 2$), the functions $\gamma_{{}_{max}}$ and $\gamma_{{}_{min}}$ can be defined as natural way. In this paper, we show that the Wulff shape of $\gamma_{{}_{max}}$ (resp. the Wulff shape of $\gamma_{{}_{min}}$) is exactly the convex hull...
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Approximate Kernel PCA Using Random Features: Computational vs. Statistical Trade-off
Kernel methods are powerful learning methodologies that provide a simple way to construct nonlinear algorithms from linear ones. Despite their popularity, they suffer from poor scalability in big data scenarios. Various approximation methods, including random feature approximation have been proposed to alleviate the ...
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A Heuristic Search Algorithm Using the Stability of Learning Algorithms in Certain Scenarios as the Fitness Function: An Artificial General Intelligence Engineering Approach
This paper presents a non-manual design engineering method based on heuristic search algorithm to search for candidate agents in the solution space which formed by artificial intelligence agents modeled on the base of bionics.Compared with the artificial design method represented by meta-learning and the bionics meth...
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SEDIGISM: Structure, excitation, and dynamics of the inner Galactic interstellar medium
The origin and life-cycle of molecular clouds are still poorly constrained, despite their importance for understanding the evolution of the interstellar medium. We have carried out a systematic, homogeneous, spectroscopic survey of the inner Galactic plane, in order to complement the many continuum Galactic surveys a...
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Imitating Driver Behavior with Generative Adversarial Networks
The ability to accurately predict and simulate human driving behavior is critical for the development of intelligent transportation systems. Traditional modeling methods have employed simple parametric models and behavioral cloning. This paper adopts a method for overcoming the problem of cascading errors inherent in...
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Topological semimetals with double-helix nodal link
Topological nodal line semimetals are characterized by the crossing of the conduction and valence bands along one or more closed loops in the Brillouin zone. Usually, these loops are either isolated or touch each other at some highly symmetric points. Here, we introduce a new kind of nodal line semimetal, that contai...
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Artificial Intelligence Assisted Power Grid Hardening in Response to Extreme Weather Events
In this paper, an artificial intelligence based grid hardening model is proposed with the objective of improving power grid resilience in response to extreme weather events. At first, a machine learning model is proposed to predict the component states (either operational or outage) in response to the extreme event. ...
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Computing isomorphisms and embeddings of finite fields
Let $\mathbb{F}_q$ be a finite field. Given two irreducible polynomials $f,g$ over $\mathbb{F}_q$, with $\mathrm{deg} f$ dividing $\mathrm{deg} g$, the finite field embedding problem asks to compute an explicit description of a field embedding of $\mathbb{F}_q[X]/f(X)$ into $\mathbb{F}_q[Y]/g(Y)$. When $\mathrm{deg} ...
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Analysis of the current-driven domain wall motion in a ratchet ferromagnetic strip
The current-driven domain wall motion in a ratchet memory due to spin-orbit torques is studied from both full micromagnetic simulations and the one dimensional model. Within the framework of this model, the integration of the anisotropy energy contribution leads to a new term in the well known q-$\Phi$ equations, bei...
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On the Hilbert coefficients, depth of associated graded rings and reduction numbers
Let $(R,\mathfrak{m})$ be a $d$-dimensional Cohen-Macaulay local ring, $I$ an $\mathfrak{m}$-primary ideal of $R$ and $J=(x_1,...,x_d)$ a minimal reduction of $I$. We show that if $J_{d-1}=(x_1,...,x_{d-1})$ and $\sum\limits_{n=1}^\infty\lambda{({I^{n+1}\cap J_{d-1}})/({J{I^n} \cap J_{d-1}})=i}$ where i=0,1, then dep...
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End-to-End ASR-free Keyword Search from Speech
End-to-end (E2E) systems have achieved competitive results compared to conventional hybrid hidden Markov model (HMM)-deep neural network based automatic speech recognition (ASR) systems. Such E2E systems are attractive due to the lack of dependence on alignments between input acoustic and output grapheme or HMM state...
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Tracking performance in high multiplicities environment at ALICE
In LHC Run 3, ALICE will increase the data taking rate significantly to 50\,kHz continuous read out of minimum bias Pb-Pb events. This challenges the online and offline computing infrastructure, requiring to process 50 times as many events per second as in Run 2, and increasing the data compression ratio from 5 to 20...
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Schatten class Hankel and $\overline{\partial}$-Neumann operators on pseudoconvex domains in $\mathbb{C}^n$
Let $\Omega$ be a $C^2$-smooth bounded pseudoconvex domain in $\mathbb{C}^n$ for $n\geq 2$ and let $\varphi$ be a holomorphic function on $\Omega$ that is $C^2$-smooth on the closure of $\Omega$. We prove that if $H_{\overline{\varphi}}$ is in Schatten $p$-class for $p\leq 2n$ then $\varphi$ is a constant function. A...
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Cross-Sectional Variation of Intraday Liquidity, Cross-Impact, and their Effect on Portfolio Execution
The composition of natural liquidity has been changing over time. An analysis of intraday volumes for the S&P500 constituent stocks illustrates that (i) volume surprises, i.e., deviations from their respective forecasts, are correlated across stocks, and (ii) this correlation increases during the last few hours of th...
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An investigation of pulsar searching techniques with the Fast Folding Algorithm
Here we present an in-depth study of the behaviour of the Fast Folding Algorithm, an alternative pulsar searching technique to the Fast Fourier Transform. Weaknesses in the Fast Fourier Transform, including a susceptibility to red noise, leave it insensitive to pulsars with long rotational periods (P > 1 s). This sen...
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Symplectic stability on manifolds with cylindrical ends
A famous result of Jurgen Moser states that a symplectic form on a compact manifold cannot be deformed within its cohomology class to an inequivalent symplectic form. It is well known that this does not hold in general for noncompact symplectic manifolds. The notion of Eliashberg-Gromov convex ends provides a natural...
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Making the Dzyaloshinskii-Moriya interaction visible
Brillouin light spectroscopy is a powerful and robust technique for measuring the interfacial Dzyaloshinskii-Moriya interaction in thin films with broken inversion symmetry. Here we show that the magnon visibility, i.e. the intensity of the inelastically scattered light, strongly depends on the thickness of the diele...
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Approximate Collapsed Gibbs Clustering with Expectation Propagation
We develop a framework for approximating collapsed Gibbs sampling in generative latent variable cluster models. Collapsed Gibbs is a popular MCMC method, which integrates out variables in the posterior to improve mixing. Unfortunately for many complex models, integrating out these variables is either analytically or ...
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Thermal graphene metamaterials and epsilon-near-zero high temperature plasmonics
The key feature of a thermophotovoltaic (TPV) emitter is the enhancement of thermal emission corresponding to energies just above the bandgap of the absorbing photovoltaic cell and simultaneous suppression of thermal emission below the bandgap. We show here that a single layer plasmonic coating can perform this task ...
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Ferroionic states in ferroelectric thin films
The electric coupling between surface ions and bulk ferroelectricity gives rise to a continuum of mixed states in ferroelectric thin films, exquisitely sensitive to temperature and external factors, such as applied voltage and oxygen pressure. Here we develop the comprehensive analytical description of these coupled ...
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Quantum Chebyshev's Inequality and Applications
In this paper we provide new quantum algorithms with polynomial speed-up for a range of problems for which no such results were known, or we improve previous algorithms. First, we consider the approximation of the frequency moments $F_k$ of order $k \geq 3$ in the multi-pass streaming model with updates (turnstile mo...
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Learning Convex Regularizers for Optimal Bayesian Denoising
We propose a data-driven algorithm for the maximum a posteriori (MAP) estimation of stochastic processes from noisy observations. The primary statistical properties of the sought signal is specified by the penalty function (i.e., negative logarithm of the prior probability density function). Our alternating direction...
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On the $L^p$ boundedness of wave operators for two-dimensional Schrödinger operators with threshold obstructions
Let $H=-\Delta+V$ be a Schrödinger operator on $L^2(\mathbb R^2)$ with real-valued potential $V$, and let $H_0=-\Delta$. If $V$ has sufficient pointwise decay, the wave operators $W_{\pm}=s-\lim_{t\to \pm\infty} e^{itH}e^{-itH_0}$ are known to be bounded on $L^p(\mathbb R^2)$ for all $1< p< \infty$ if zero is not an ...
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Data-driven Advice for Applying Machine Learning to Bioinformatics Problems
As the bioinformatics field grows, it must keep pace not only with new data but with new algorithms. Here we contribute a thorough analysis of 13 state-of-the-art, commonly used machine learning algorithms on a set of 165 publicly available classification problems in order to provide data-driven algorithm recommendat...
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Bivariate Causal Discovery and its Applications to Gene Expression and Imaging Data Analysis
The mainstream of research in genetics, epigenetics and imaging data analysis focuses on statistical association or exploring statistical dependence between variables. Despite their significant progresses in genetic research, understanding the etiology and mechanism of complex phenotypes remains elusive. Using associ...
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Revisiting Distillation and Incremental Classifier Learning
One of the key differences between the learning mechanism of humans and Artificial Neural Networks (ANNs) is the ability of humans to learn one task at a time. ANNs, on the other hand, can only learn multiple tasks simultaneously. Any attempts at learning new tasks incrementally cause them to completely forget about ...
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Intuitive Hand Teleoperation by Novice Operators Using a Continuous Teleoperation Subspace
Human-in-the-loop manipulation is useful in when autonomous grasping is not able to deal sufficiently well with corner cases or cannot operate fast enough. Using the teleoperator's hand as an input device can provide an intuitive control method but requires mapping between pose spaces which may not be similar. We pro...
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A Hierarchical Bayes Approach to Adjust for Selection Bias in Before-After Analyses of Vision Zero Policies
American cities devote significant resources to the implementation of traffic safety countermeasures that prevent pedestrian fatalities. However, the before-after comparisons typically used to evaluate the success of these countermeasures often suffer from selection bias. This paper motivates the tendency for selecti...
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Cavitation near the oscillating piezoelectric plate in water
It is known that gas bubbles on the surface bounding a fluid flow can change the coefficient of friction and affect the parameters of the boundary layer. In this paper, we propose a method that allows us to create, in the near-wall region, a thin layer of liquid filled with bubbles. It will be shown that if there is ...
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Revised Note on Learning Algorithms for Quadratic Assignment with Graph Neural Networks
Inverse problems correspond to a certain type of optimization problems formulated over appropriate input distributions. Recently, there has been a growing interest in understanding the computational hardness of these optimization problems, not only in the worst case, but in an average-complexity sense under this same...
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On Completeness Results of Hoare Logic Relative to the Standard Model
The general completeness problem of Hoare logic relative to the standard model $N$ of Peano arithmetic has been studied by Cook, and it allows for the use of arbitrary arithmetical formulas as assertions. In practice, the assertions would be simple arithmetical formulas, e.g. of a low level in the arithmetical hierar...
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Shift-Coupling of Random Rooted Graphs and Networks
In this paper, we present a result similar to the shift-coupling result of Thorisson (1996) in the context of random graphs and networks. The result is that a given random rooted network can be obtained by changing the root of another given one if and only if the distributions of the two agree on the invariant sigma-...
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Fast Automated Analysis of Strong Gravitational Lenses with Convolutional Neural Networks
Quantifying image distortions caused by strong gravitational lensing and estimating the corresponding matter distribution in lensing galaxies has been primarily performed by maximum likelihood modeling of observations. This is typically a time and resource-consuming procedure, requiring sophisticated lensing codes, s...
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Adversarial Examples, Uncertainty, and Transfer Testing Robustness in Gaussian Process Hybrid Deep Networks
Deep neural networks (DNNs) have excellent representative power and are state of the art classifiers on many tasks. However, they often do not capture their own uncertainties well making them less robust in the real world as they overconfidently extrapolate and do not notice domain shift. Gaussian processes (GPs) wit...
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Elliptic regularization of the isometric immersion problem
We introduce an elliptic regularization of the PDE system representing the isometric immersion of a surface in $\mathbb R^{3}$. The regularization is geometric, and has a natural variational interpretation.
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A Debris Backwards Flow Simulation System for Malaysia Airlines Flight 370
This paper presents a system based on a Two-Way Particle-Tracking Model to analyze possible crash positions of flight MH370. The particle simulator includes a simple flow simulation of the debris based on a Lagrangian approach and a module to extract appropriated ocean current data from netCDF files. The influence of...
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End-to-End Task-Completion Neural Dialogue Systems
One of the major drawbacks of modularized task-completion dialogue systems is that each module is trained individually, which presents several challenges. For example, downstream modules are affected by earlier modules, and the performance of the entire system is not robust to the accumulated errors. This paper prese...
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Improving power of genetic association studies by extreme phenotype sampling: a review and some new results
Extreme phenotype sampling is a selective genotyping design for genetic association studies where only individuals with extreme values of a continuous trait are genotyped for a set of genetic variants. Under financial or other limitations, this design is assumed to improve the power to detect associations between gen...
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Energy network: towards an interconnected energy infrastructure for the future
The fundamental theory of energy networks in different energy forms is established following an in-depth analysis of the nature of energy for comprehensive energy utilization. The definition of an energy network is given. Combining the generalized balance equation of energy in space and the Pfaffian equation, the gen...
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Invitation to Alexandrov geometry: CAT[0] spaces
The idea is to demonstrate the beauty and power of Alexandrov geometry by reaching interesting applications with a minimum of preparation. The topics include 1. Estimates on the number of collisions in billiards. 2. Construction of exotic aspherical manifolds. 3. The geometry of two-convex sets in Euclidean space.
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Smoothing of transport plans with fixed marginals and rigorous semiclassical limit of the Hohenberg-Kohn functional
We prove rigorously that the exact N-electron Hohenberg-Kohn density functional converges in the strongly interacting limit to the strictly correlated electrons (SCE) functional, and that the absolute value squared of the associated constrained-search wavefunction tends weakly in the sense of probability measures to ...
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The extension of some D(4)-pairs
In this paper we illustrate the use of the results from [1] proving that $D(4)$-triple $\{a, b, c\}$ with $a < b < a + 57\sqrt{a}$ has a unique extension to a quadruple with a larger element. This furthermore implies that $D(4)$-pair $\{a, b\}$ cannot be extended to a quintuple if $a < b < a + 57\sqrt{a}$.
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Standards for enabling heterogeneous IaaS cloud federations
Technology market is continuing a rapid growth phase where different resource providers and Cloud Management Frameworks are positioning to provide ad-hoc solutions -in terms of management interfaces, information discovery or billing- trying to differentiate from competitors but that as a result remain incompatible be...
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Grid-based Approaches for Distributed Data Mining Applications
The data mining field is an important source of large-scale applications and datasets which are getting more and more common. In this paper, we present grid-based approaches for two basic data mining applications, and a performance evaluation on an experimental grid environment that provides interesting monitoring ca...
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Transforming acoustic characteristics to deceive playback spoofing countermeasures of speaker verification systems
Automatic speaker verification (ASV) systems use a playback detector to filter out playback attacks and ensure verification reliability. Since current playback detection models are almost always trained using genuine and played-back speech, it may be possible to degrade their performance by transforming the acoustic ...
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LoopInvGen: A Loop Invariant Generator based on Precondition Inference
We describe the LoopInvGen tool for generating loop invariants that can provably guarantee correctness of a program with respect to a given specification. LoopInvGen is an efficient implementation of the inference technique originally proposed in our earlier work on PIE (this https URL). In contrast to existing techn...
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Dimensional crossover of effective orbital dynamics in polar distorted 3He-A: Transitions to anti-spacetime
Topologically protected superfluid phases of $^3$He allow one to simulate many important aspects of relativistic quantum field theories and quantum gravity in condensed matter. Here we discuss a topological Lifshitz transition of the effective quantum vacuum in which the determinant of the tetrad field changes sign t...
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Low frequency spectral energy distributions of radio pulsars detected with the Murchison Widefield Array
We present low-frequency spectral energy distributions of 60 known radio pulsars observed with the Murchison Widefield Array (MWA) telescope. We searched the GaLactic and Extragalactic All-sky MWA (GLEAM) survey images for 200-MHz continuum radio emission at the position of all pulsars in the ATNF pulsar catalogue. F...
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Scalable Spectrum Allocation and User Association in Networks with Many Small Cells
A scalable framework is developed to allocate radio resources across a large number of densely deployed small cells with given traffic statistics on a slow timescale. Joint user association and spectrum allocation is first formulated as a convex optimization problem by dividing the spectrum among all possible transmi...
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On Geometry and Symmetry of Kepler Systems. I
We study the Kepler metrics on Kepler manifolds from the point of view of Sasakian geometry and Hessian geometry. This establishes a link between the problem of classical gravity and the modern geometric methods in the study of AdS/CFT correspondence in string theory.
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The collisional frequency shift of a trapped-ion optical clock
Collisions with background gas can perturb the transition frequency of trapped ions in an optical atomic clock. We develop a non-perturbative framework based on a quantum channel description of the scattering process, and use it to derive a master equation which leads to a simple analytic expression for the collision...
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Continuity properties for Born-Jordan operators with symbols in Hörmander classes and modulation spaces
We show that the Weyl symbol of a Born-Jordan operator is in the same class as the Born-Jordan symbol, when Hörmander symbols and certain types of modulation spaces are used as symbol classes. We use these properties to carry over continuity and Schatten-von Neumann properties to the Born-Jordan calculus.
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IoT Data Analytics Using Deep Learning
Deep learning is a popular machine learning approach which has achieved a lot of progress in all traditional machine learning areas. Internet of thing (IoT) and Smart City deployments are generating large amounts of time-series sensor data in need of analysis. Applying deep learning to these domains has been an impor...
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Viscous Dissipation in One-Dimensional Quantum Liquids
We develop a theory of viscous dissipation in one-dimensional single-component quantum liquids at low temperatures. Such liquids are characterized by a single viscosity coefficient, the bulk viscosity. We show that for a generic interaction between the constituent particles this viscosity diverges in the zero-tempera...
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On the existence of homoclinic type solutions of inhomogenous Lagrangian systems
We study the existence of homoclinic type solutions for second order Lagrangian systems of the type $\ddot{q}(t)-q(t)+a(t)\nabla G(q(t))=f(t)$, where $t\in\mathbb{R}$, $q\in\mathbb{R}^n$, $a\colon\mathbb{R}\to\mathbb{R}$ is a continuous positive bounded function, $G\colon\mathbb{R}^n\to\mathbb{R}$ is a $C^1$-smooth p...
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Correcting Two Deletions and Insertions in Racetrack Memory
Racetrack memory is a non-volatile memory engineered to provide both high density and low latency, that is subject to synchronization or shift errors. This paper describes a fast coding solution, in which delimiter bits assist in identifying the type of shift error, and easily implementable graph-based codes are used...
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Limits of Yang-Mills α-connections
In the spirit of recent work of Lamm, Malchiodi and Micallef in the setting of harmonic maps, we identify Yang-Mills connections obtained by approximations with respect to the Yang-Mills {\alpha}-energy. More specifically, we show that for the SU(2) Hopf fibration over the four sphere, for sufficiently small {\alpha}...
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Online Robust Principal Component Analysis with Change Point Detection
Robust PCA methods are typically batch algorithms which requires loading all observations into memory before processing. This makes them inefficient to process big data. In this paper, we develop an efficient online robust principal component methods, namely online moving window robust principal component analysis (O...
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Reactive User Behavior and Mobility Models
In this paper, we present a set of simulation models to more realistically mimic the behaviour of users reading messages. We propose a User Behaviour Model, where a simulated user reacts to a message by a flexible set of possible reactions (e.g. ignore, read, like, save, etc.) and a mobility-based reaction (visit a p...
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How production networks amplify economic growth
Technological improvement is the most important cause of long-term economic growth, but the factors that drive it are still not fully understood. In standard growth models technology is treated in the aggregate, and a main goal has been to understand how growth depends on factors such as knowledge production. But an ...
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The Minimal Resolution Conjecture on a general quartic surface in $\mathbb P^3$
Mustaţă has given a conjecture for the graded Betti numbers in the minimal free resolution of the ideal of a general set of points on an irreducible projective algebraic variety. For surfaces in $\mathbb P^3$ this conjecture has been proven for points on quadric surfaces and on general cubic surfaces. In the latter c...
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Exact density functional obtained via the Levy constrained search
A stochastic minimization method for a real-space wavefunction, $\Psi({\bf r}_{1},{\bf r}_{2}\ldots{\bf r}_{n})$, constrained to a chosen density, $\rho({\bf r})$, is developed. It enables the explicit calculation of the Levy constrained search $F[\rho]=\min_{\Psi\rightarrow\rho}\langle\Psi|\hat{T}+\hat{V}_{ee}|\Psi\...
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Compile-Time Symbolic Differentiation Using C++ Expression Templates
Template metaprogramming is a popular technique for implementing compile time mechanisms for numerical computing. We demonstrate how expression templates can be used for compile time symbolic differentiation of algebraic expressions in C++ computer programs. Given a positive integer $N$ and an algebraic function of m...
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On Multilingual Training of Neural Dependency Parsers
We show that a recently proposed neural dependency parser can be improved by joint training on multiple languages from the same family. The parser is implemented as a deep neural network whose only input is orthographic representations of words. In order to successfully parse, the network has to discover how linguist...
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Autocommuting probability of a finite group
Let $G$ be a finite group and $\Aut(G)$ the automorphism group of $G$. The autocommuting probability of $G$, denoted by $\Pr(G, \Aut(G))$, is the probability that a randomly chosen automorphism of $G$ fixes a randomly chosen element of $G$. In this paper, we study $\Pr(G, \Aut(G))$ through a generalization. We obtain...
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Inside-Out Planet Formation. IV. Pebble Evolution and Planet Formation Timescales
Systems with tightly-packed inner planets (STIPs) are very common. Chatterjee & Tan proposed Inside-Out Planet Formation (IOPF), an in situ formation theory, to explain these planets. IOPF involves sequential planet formation from pebble-rich rings that are fed from the outer disk and trapped at the pressure maximum ...
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SilhoNet: An RGB Method for 3D Object Pose Estimation and Grasp Planning
Autonomous robot manipulation often involves both estimating the pose of the object to be manipulated and selecting a viable grasp point. Methods using RGB-D data have shown great success in solving these problems. However, there are situations where cost constraints or the working environment may limit the use of RG...
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Collapsed Tetragonal Phase Transition in LaRu$_2$P$_2$
The structural properties of LaRu$_2$P$_2$ under external pressure have been studied up to 14 GPa, employing high-energy x-ray diffraction in a diamond-anvil pressure cell. At ambient conditions, LaRu$_2$P$_2$ (I4/mmm) has a tetragonal structure with a bulk modulus of $B=105(2)$ GPa and exhibits superconductivity at ...
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Bayesian Nonparametric Unmixing of Hyperspectral Images
Hyperspectral imaging is an important tool in remote sensing, allowing for accurate analysis of vast areas. Due to a low spatial resolution, a pixel of a hyperspectral image rarely represents a single material, but rather a mixture of different spectra. HSU aims at estimating the pure spectra present in the scene of ...
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Dynamical control of electron-phonon interactions with high-frequency light
This work addresses the one-dimensional problem of Bloch electrons when they are rapidly driven by a homogeneous time-periodic light and linearly coupled to vibrational modes. Starting from a generic time-periodic electron-phonon Hamiltonian, we derive a time-independent effective Hamiltonian that describes the strob...
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Controlling the thermoelectric effect by mechanical manipulation of the electron's quantum phase in atomic junctions
The thermoelectric voltage developed across an atomic metal junction (i.e., a nanostructure in which one or a few atoms connect two metal electrodes) in response to a temperature difference between the electrodes, results from the quantum interference of electrons that pass through the junction multiple times after b...
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The time geography of segregation during working hours
Understanding segregation is essential to develop planning tools for building more inclusive cities. Theoretically, segregation at the work place has been described as lower compared to residential segregation given the importance of skill complementarity among other productive factors shaping the economies of cities...
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Improving Protein Gamma-Turn Prediction Using Inception Capsule Networks
Protein gamma-turn prediction is useful in protein function studies and experimental design. Several methods for gamma-turn prediction have been developed, but the results were unsatisfactory with Matthew correlation coefficients (MCC) around 0.2-0.4. One reason for the low prediction accuracy is the limited capacity...
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Image transformations on locally compact spaces
An image is here defined to be a set which is either open or closed and an image transformation is structure preserving in the following sense: It corresponds to an algebra homomorphism for each singly generated algebra. The results extend parts of results of J.F. Aarnes on quasi-measures, -states, -homomorphisms, an...
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From Half-metal to Semiconductor: Electron-correlation Effects in Zigzag SiC Nanoribbons From First Principles
We performed electronic structure calculations based on the first-principles many-body theory approach in order to study quasiparticle band gaps, and optical absorption spectra of hydrogen-passivated zigzag SiC nanoribbons. Self-energy corrections are included using the GW approximation, and excitonic effects are inc...
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Non-exponential decoherence of radio-frequency resonance rotation of spin in storage rings
Precision experiments, such as the search for electric dipole moments of charged particles using radiofrequency spin rotators in storage rings, demand for maintaining the exact spin resonance condition for several thousand seconds. Synchrotron oscillations in the stored beam modulate the spin tune of off-central part...
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On the fundamental group of semi-Riemannian manifolds with positive curvature operator
This paper presents an investigation of the relation between some positivity of the curvature and the finiteness of fundamental groups in semi-Riemannian geometry. We consider semi-Riemannian submersions $\pi : (E, g) \rightarrow (B, -g_{B}) $ under the condition with $(B, g_{B})$ Riemannian, the fiber closed Riemann...
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Flow-Sensitive Composition of Thread-Modular Abstract Interpretation
We propose a constraint-based flow-sensitive static analysis for concurrent programs by iteratively composing thread-modular abstract interpreters via the use of a system of lightweight constraints. Our method is compositional in that it first applies sequential abstract interpreters to individual threads and then co...
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Momentum Control of Humanoid Robots with Series Elastic Actuators
Humanoid robots may require a degree of compliance at the joint level for improving efficiency, shock tolerance, and safe interaction with humans. The presence of joint elasticity, however, complexifies the design of balancing and walking controllers. This paper proposes a control framework for extending momentum bas...
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SRN: Side-output Residual Network for Object Symmetry Detection in the Wild
In this paper, we establish a baseline for object symmetry detection in complex backgrounds by presenting a new benchmark and an end-to-end deep learning approach, opening up a promising direction for symmetry detection in the wild. The new benchmark, named Sym-PASCAL, spans challenges including object diversity, mul...
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Time-Optimal Trajectories of Generic Control-Affine Systems Have at Worst Iterated Fuller Singularities
We consider in this paper the regularity problem for time-optimal trajectories of a single-input control-affine system on a n-dimensional manifold. We prove that, under generic conditions on the drift and the controlled vector field, any control u associated with an optimal trajectory is smooth out of a countable set...
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Wikipedia for Smart Machines and Double Deep Machine Learning
Very important breakthroughs in data centric deep learning algorithms led to impressive performance in transactional point applications of Artificial Intelligence (AI) such as Face Recognition, or EKG classification. With all due appreciation, however, knowledge blind data only machine learning algorithms have severe...
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A binary main belt comet
The asteroids are primitive solar system bodies which evolve both collisionally and through disruptions due to rapid rotation [1]. These processes can lead to the formation of binary asteroids [2-4] and to the release of dust [5], both directly and, in some cases, through uncovering frozen volatiles. In a sub-set of ...
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Dynamic Clustering Algorithms via Small-Variance Analysis of Markov Chain Mixture Models
Bayesian nonparametrics are a class of probabilistic models in which the model size is inferred from data. A recently developed methodology in this field is small-variance asymptotic analysis, a mathematical technique for deriving learning algorithms that capture much of the flexibility of Bayesian nonparametric infe...
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