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Predicting signatures of anisotropic resonance energy transfer in dye-functionalized nanoparticles
Resonance energy transfer (RET) is an inherently anisotropic process. Even the simplest, well-known Förster theory, based on the transition dipole-dipole coupling, implicitly incorporates the anisotropic character of RET. In this theoretical work, we study possible signatures of the fundamental anisotropic character ...
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Matrix Completion and Performance Guarantees for Single Individual Haplotyping
Single individual haplotyping is an NP-hard problem that emerges when attempting to reconstruct an organism's inherited genetic variations using data typically generated by high-throughput DNA sequencing platforms. Genomes of diploid organisms, including humans, are organized into homologous pairs of chromosomes that...
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Simulation and analysis of $γ$-Ni cellular growth during laser powder deposition of Ni-based superalloys
Cellular or dendritic microstructures that result as a function of additive manufacturing solidification conditions in a Ni-based melt pool are simulated in the present work using three-dimensional phase-field simulations. A macroscopic thermal model is used to obtain the temperature gradient $G$ and the solidificati...
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Localization of Extended Quantum Objects
A quantum system of particles can exist in a localized phase, exhibiting ergodicity breaking and maintaining forever a local memory of its initial conditions. We generalize this concept to a system of extended objects, such as strings and membranes, arguing that such a system can also exhibit localization in the pres...
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The next-to-minimal weights of binary projective Reed-Muller codes
Projective Reed-Muller codes were introduced by Lachaud, in 1988 and their dimension and minimum distance were determined by Serre and S{\o}rensen in 1991. In coding theory one is also interested in the higher Hamming weights, to study the code performance. Yet, not many values of the higher Hamming weights are known...
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Big Data Classification Using Augmented Decision Trees
We present an algorithm for classification tasks on big data. Experiments conducted as part of this study indicate that the algorithm can be as accurate as ensemble methods such as random forests or gradient boosted trees. Unlike ensemble methods, the models produced by the algorithm can be easily interpreted. The al...
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Special tilting modules for algebras with positive dominant dimension
We study a set of uniquely determined tilting and cotilting modules for an algebra with positive dominant dimension, with the property that they are generated or cogenerated (and usually both) by projective-injectives. These modules have various interesting properties, for example that their endomorphism algebras alw...
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The dynamical structure of political corruption networks
Corruptive behaviour in politics limits economic growth, embezzles public funds, and promotes socio-economic inequality in modern democracies. We analyse well-documented political corruption scandals in Brazil over the past 27 years, focusing on the dynamical structure of networks where two individuals are connected ...
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Maxent-Stress Optimization of 3D Biomolecular Models
Knowing a biomolecule's structure is inherently linked to and a prerequisite for any detailed understanding of its function. Significant effort has gone into developing technologies for structural characterization. These technologies do not directly provide 3D structures; instead they typically yield noisy and errone...
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Enhanced Quantum Synchronization via Quantum Machine Learning
We study the quantum synchronization between a pair of two-level systems inside two coupled cavities. By using a digital-analog decomposition of the master equation that rules the system dynamics, we show that this approach leads to quantum synchronization between both two-level systems. Moreover, we can identify in ...
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Engineering phonon leakage in nanomechanical resonators
We propose and experimentally demonstrate a technique for coupling phonons out of an optomechanical crystal cavity. By designing a perturbation that breaks a symmetry in the elastic structure, we selectively induce phonon leakage without affecting the optical properties. It is shown experimentally via cryogenic measu...
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Entropy generation and momentum transfer in the superconductor-normal and normal-superconductor phase transformations and the consistency of the conventional theory of superconductivity
Since the discovery of the Meissner effect the superconductor to normal (S-N) phase transition in the presence of a magnetic field is understood to be a first order phase transformation that is reversible under ideal conditions and obeys the laws of thermodynamics. The reverse (N-S) transition is the Meissner effect....
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A Local Faber-Krahn inequality and Applications to Schrödinger's Equation
We prove a local Faber-Krahn inequality for solutions $u$ to the Dirichlet problem for $\Delta + V$ on an arbitrary domain $\Omega$ in $\mathbb{R}^n$. Suppose a solution $u$ assumes a global maximum at some point $x_0 \in \Omega$ and $u(x_0)>0$. Let $T(x_0)$ be the smallest time at which a Brownian motion, started at...
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Étale groupoids and their $C^*$-algebras
These notes were written as supplementary material for a five-hour lecture series presented at the Centre de Recerca Mathemàtica at the Universitat Autònoma de Barcelona from the 13th to the 17th of March 2017. The intention of these notes is to give a brief overview of some key topics in the area of $C^*$-algebras a...
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Semi-classical limit of the Levy-Lieb functional in Density Functional Theory
In a recent work, Bindini and De Pascale have introduced a regularization of $N$-particle symmetric probabilities which preserves their one-particle marginals. In this short note, we extend their construction to mixed quantum fermionic states. This enables us to prove the convergence of the Levy-Lieb functional in De...
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A characterization of cellular motivic spectra
Let $ \alpha: \mathcal{C} \to \mathcal{D}$ be a symmetric monoidal functor from a stable presentable symmetric monoidal $\infty$-category $\mathcal{C} $ compactly generated by the tensorunit to a stable presentable symmetric monoidal $\infty$-category $ \mathcal{D} $ with compact tensorunit. Let $\beta: \mathcal{D} \...
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The Impedance of Flat Metallic Plates with Small Corrugations
Summarizes recent work on the wakefields and impedances of flat, metallic plates with small corrugations
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The Computer Science and Physics of Community Detection: Landscapes, Phase Transitions, and Hardness
Community detection in graphs is the problem of finding groups of vertices which are more densely connected than they are to the rest of the graph. This problem has a long history, but it is undergoing a resurgence of interest due to the need to analyze social and biological networks. While there are many ways to for...
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Characterizing the spread of exaggerated news content over social media
In this paper, we consider a dataset comprising press releases about health research from different universities in the UK along with a corresponding set of news articles. First, we do an exploratory analysis to understand how the basic information published in the scientific journals get exaggerated as they are repo...
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Aerodynamic noise from rigid trailing edges with finite porous extensions
This paper investigates the effects of finite flat porous extensions to semi-infinite impermeable flat plates in an attempt to control trailing-edge noise through bio-inspired adaptations. Specifically the problem of sound generated by a gust convecting in uniform mean steady flow scattering off the trailing edge and...
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99% of Parallel Optimization is Inevitably a Waste of Time
It is well known that many optimization methods, including SGD, SAGA, and Accelerated SGD for over-parameterized models, do not scale linearly in the parallel setting. In this paper, we present a new version of block coordinate descent that solves this issue for a number of methods. The core idea is to make the sampl...
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Tuning the effective spin-orbit coupling in molecular semiconductors
The control of spins and spin to charge conversion in organics requires understanding the molecular spin-orbit coupling (SOC), and a means to tune its strength. However, quantifying SOC strengths indirectly through spin relaxation effects has proven diffi- cult due to competing relaxation mechanisms. Here we present ...
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How Deep Are Deep Gaussian Processes?
Recent research has shown the potential utility of Deep Gaussian Processes. These deep structures are probability distributions, designed through hierarchical construction, which are conditionally Gaussian. In this paper, the current published body of work is placed in a common framework and, through recursion, sever...
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Sparse Randomized Kaczmarz for Support Recovery of Jointly Sparse Corrupted Multiple Measurement Vectors
While single measurement vector (SMV) models have been widely studied in signal processing, there is a surging interest in addressing the multiple measurement vectors (MMV) problem. In the MMV setting, more than one measurement vector is available and the multiple signals to be recovered share some commonalities such...
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Exploiting ITO colloidal nanocrystals for ultrafast pulse generation
Dynamical materials that capable of responding to optical stimuli have always been pursued for designing novel photonic devices and functionalities, of which the response speed and amplitude as well as integration adaptability and energy effectiveness are especially critical. Here we show ultrafast pulse generation b...
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A quantum dynamic belief model to explain the interference effects of categorization on decision making
Categorization is necessary for many decision making tasks. However, the categorization process may interfere the decision making result and the law of total probability can be violated in some situations. To predict the interference effect of categorization, some model based on quantum probability has been proposed....
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Throughput Optimal Beam Alignment in Millimeter Wave Networks
Millimeter wave communications rely on narrow-beam transmissions to cope with the strong signal attenuation at these frequencies, thus demanding precise beam alignment between transmitter and receiver. The communication overhead incurred to achieve beam alignment may become a severe impairment in mobile networks. Thi...
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Behavioural Change Support Intelligent Transportation Applications
This workshop invites researchers and practitioners to participate in exploring behavioral change support intelligent transportation applications. We welcome submissions that explore intelligent transportation systems (ITS), which interact with travelers in order to persuade them or nudge them towards sustainable tra...
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SU(2) Pfaffian systems and gauge theory
Motivated by the description of Nurowski's conformal structure for maximally symmetric homogeneous examples of bracket-generating rank 2 distributions in dimension 5, aka $(2,3,5)$-distributions, we consider a rank $3$ Pfaffian system in dimension 5 with $SU(2)$ symmetry. We find the conditions for which this Pfaffia...
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Correlation effects in superconducting quantum dot systems
We study the effect of electron correlations on a system consisting of a single-level quantum dot with local Coulomb interaction attached to two superconducting leads. We use the single-impurity Anderson model with BCS superconducting baths to study the interplay between the proximity induced electron pairing and the...
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Learning non-parametric Markov networks with mutual information
We propose a method for learning Markov network structures for continuous data without invoking any assumptions about the distribution of the variables. The method makes use of previous work on a non-parametric estimator for mutual information which is used to create a non-parametric test for multivariate conditional...
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Online Adaptive Machine Learning Based Algorithm for Implied Volatility Surface Modeling
In this work, we design a machine learning based method, online adaptive primal support vector regression (SVR), to model the implied volatility surface (IVS). The algorithm proposed is the first derivation and implementation of an online primal kernel SVR. It features enhancements that allow efficient online adaptiv...
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Hybrid control strategy for a semi active suspension system using fuzzy logic and bio-inspired chaotic fruit fly algorithm
This study proposes a control strategy for the efficient semi active suspension systems utilizing a novel hybrid PID-fuzzy logic control scheme .In the control architecture, we employ the Chaotic Fruit Fly Algorithm for PID tuning since it can avoid local minima by chaotic search. A novel linguistic rule based fuzzy ...
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On the Use of Default Parameter Settings in the Empirical Evaluation of Classification Algorithms
We demonstrate that, for a range of state-of-the-art machine learning algorithms, the differences in generalisation performance obtained using default parameter settings and using parameters tuned via cross-validation can be similar in magnitude to the differences in performance observed between state-of-the-art and ...
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Coaction functors, II
In further study of the application of crossed-product functors to the Baum-Connes Conjecture, Buss, Echterhoff, and Willett introduced various other properties that crossed-product functors may have. Here we introduce and study analogues of these properties for coaction functors, making sure that the properties are ...
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Classification of Casimirs in 2D hydrodynamics
We describe a complete list of Casimirs for 2D Euler hydrodynamics on a surface without boundary: we define generalized enstrophies which, along with circulations, form a complete set of invariants for coadjoint orbits of area-preserving diffeomorphisms on a surface. We also outline a possible extension of main notio...
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Novel Compliant omnicrawler-wheel transforming module
This paper presents a novel design of a crawler robot which is capable of transforming its chassis from an Omni crawler mode to a large-sized wheel mode using a novel mechanism. The transformation occurs without any additional actuators. Interestingly the robot can transform into a large diameter and small width whee...
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Bifurcation of solutions to Hamiltonian boundary value problems
A bifurcation is a qualitative change in a family of solutions to an equation produced by varying parameters. In contrast to the local bifurcations of dynamical systems that are often related to a change in the number or stability of equilibria, bifurcations of boundary value problems are global in nature and may not...
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Trespassing the Boundaries: Labeling Temporal Bounds for Object Interactions in Egocentric Video
Manual annotations of temporal bounds for object interactions (i.e. start and end times) are typical training input to recognition, localization and detection algorithms. For three publicly available egocentric datasets, we uncover inconsistencies in ground truth temporal bounds within and across annotators and datas...
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Dynamical transport measurement of the Luttinger parameter in helical edges states of 2D topological insulators
One-dimensional (1D) electron systems in the presence of Coulomb interaction are described by Luttinger liquid theory. The strength of Coulomb interaction in the Luttinger liquid, as parameterized by the Luttinger parameter K, is in general difficult to measure. This is because K is usually hidden in powerlaw depende...
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Controlling thermal emission of phonon by magnetic metasurfaces
Our experiment shows that the thermal emission of phonon can be controlled by magnetic resonance (MR) mode in a metasurface (MTS). Through changing the structural parameter of metasurface, the MR wavelength can be tuned to the phonon resonance wavelength. This introduces a strong coupling between phonon and MR, which...
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Distributed Average Tracking of Heterogeneous Physical Second-order Agents With No Input Signals Constraint
This paper addresses distributed average tracking of physical second-order agents with heterogeneous nonlinear dynamics, where there is no constraint on input signals. The nonlinear terms in agents' dynamics are heterogeneous, satisfying a Lipschitz-like condition that will be defined later and is more general than t...
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Bound states of the two-dimensional Dirac equation for an energy-dependent hyperbolic Scarf potential
We study the two-dimensional massless Dirac equation for a potential that is allowed to depend on the energy and on one of the spatial variables. After determining a modified orthogonality relation and norm for such systems, we present an application involving an energy-dependent version of the hyperbolic Scarf poten...
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Beyond Planar Symmetry: Modeling human perception of reflection and rotation symmetries in the wild
Humans take advantage of real world symmetries for various tasks, yet capturing their superb symmetry perception mechanism with a computational model remains elusive. Motivated by a new study demonstrating the extremely high inter-person accuracy of human perceived symmetries in the wild, we have constructed the firs...
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Sharp Threshold of Blow-up and Scattering for the fractional Hartree equation
We consider the fractional Hartree equation in the $L^2$-supercritical case, and we find a sharp threshold of the scattering versus blow-up dichotomy for radial data: If $ M[u_{0}]^{\frac{s-s_c}{s_c}}E[u_{0}<M[Q]^{\frac{s-s_c}{s_c}}E[Q]$ and $M[u_{0}]^{\frac{s-s_c}{s_c}}\|u_{0}\|^2_{\dot H^s}<M[Q]^{\frac{s-s_c}{s_c}}...
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GP-SUM. Gaussian Processes Filtering of non-Gaussian Beliefs
This work studies the problem of stochastic dynamic filtering and state propagation with complex beliefs. The main contribution is GP-SUM, a filtering algorithm tailored to dynamic systems and observation models expressed as Gaussian Processes (GP), and to states represented as a weighted sum of Gaussians. The key at...
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A Dynamic Programming Principle for Distribution-Constrained Optimal Stopping
We consider an optimal stopping problem where a constraint is placed on the distribution of the stopping time. Reformulating the problem in terms of so-called measure-valued martingales allows us to transform the marginal constraint into an initial condition and view the problem as a stochastic control problem; we es...
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Spectral algebra models of unstable v_n-periodic homotopy theory
We give a survey of a generalization of Quillen-Sullivan rational homotopy theory which gives spectral algebra models of unstable v_n-periodic homotopy types. In addition to describing and contextualizing our original approach, we sketch two other recent approaches which are of a more conceptual nature, due to Arone-...
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The length of excitable knots
The FitzHugh-Nagumo equation provides a simple mathematical model of cardiac tissue as an excitable medium hosting spiral wave vortices. Here we present extensive numerical simulations studying long-term dynamics of knotted vortex string solutions for all torus knots up to crossing number 11. We demonstrate that Fitz...
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The Bane of Low-Dimensionality Clustering
In this paper, we give a conditional lower bound of $n^{\Omega(k)}$ on running time for the classic k-median and k-means clustering objectives (where n is the size of the input), even in low-dimensional Euclidean space of dimension four, assuming the Exponential Time Hypothesis (ETH). We also consider k-median (and k...
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Blue-detuned magneto-optical trap
We present the properties and advantages of a new magneto-optical trap (MOT) where blue-detuned light drives `type-II' transitions that have dark ground states. Using $^{87}$Rb, we reach a radiation-pressure-limited density exceeding $10^{11}$cm$^{-3}$ and a temperature below 30$\mu$K. The phase-space density is high...
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Polishness of some topologies related to word or tree automata
We prove that the Büchi topology and the automatic topology are Polish. We also show that this cannot be fully extended to the case of a space of infinite labelled binary trees; in particular the Büchi and the Muller topologies are not Polish in this case.
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Emulating satellite drag from large simulation experiments
Obtaining accurate estimates of satellite drag coefficients in low Earth orbit is a crucial component in positioning and collision avoidance. Simulators can produce accurate estimates, but their computational expense is much too large for real-time application. A pilot study showed that Gaussian process (GP) surrogat...
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Rescaling and other forms of unsupervised preprocessing introduce bias into cross-validation
Cross-validation of predictive models is the de-facto standard for model selection and evaluation. In proper use, it provides an unbiased estimate of a model's predictive performance. However, data sets often undergo a preliminary data-dependent transformation, such as feature rescaling or dimensionality reduction, p...
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Causal Inference on Discrete Data via Estimating Distance Correlations
In this paper, we deal with the problem of inferring causal directions when the data is on discrete domain. By considering the distribution of the cause $P(X)$ and the conditional distribution mapping cause to effect $P(Y|X)$ as independent random variables, we propose to infer the causal direction via comparing the ...
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A Class of Exponential Sequences with Shift-Invariant Discriminators
The discriminator of an integer sequence s = (s(i))_{i>=0}, introduced by Arnold, Benkoski, and McCabe in 1985, is the function D_s(n) that sends n to the least integer m such that the numbers s(0), s(1), ..., s(n-1) are pairwise incongruent modulo m. In this note we present a class of exponential sequences that have...
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Contraction par Frobenius et modules de Steinberg
For a reductive group G defined over an algebraically closed field of positive characteristic, we show that the Frobenius contraction functor of G-modules is right adjoint to the Frobenius twist of the modules tensored with the Steinberg module twice. It follows that the Frobenius contraction functor preserves inject...
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SafeDrive: A Robust Lane Tracking System for Autonomous and Assisted Driving Under Limited Visibility
We present an approach towards robust lane tracking for assisted and autonomous driving, particularly under poor visibility. Autonomous detection of lane markers improves road safety, and purely visual tracking is desirable for widespread vehicle compatibility and reducing sensor intrusion, cost, and energy consumpti...
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On the analysis of personalized medication response and classification of case vs control patients in mobile health studies: the mPower case study
In this work we provide a couple of contributions to the analysis of longitudinal data collected by smartphones in mobile health applications. First, we propose a novel statistical approach to disentangle personalized treatment and "time-of-the-day" effects in observational studies. Under the assumption of no unmeasu...
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Exponential Integrators in Time-Dependent Density Functional Calculations
The integrating factor and exponential time differencing methods are implemented and tested for solving the time-dependent Kohn--Sham equations. Popular time propagation methods used in physics, as well as other robust numerical approaches, are compared to these exponential integrator methods in order to judge the re...
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A Distributed Scheduling Algorithm to Provide Quality-of-Service in Multihop Wireless Networks
Control of multihop Wireless networks in a distributed manner while providing end-to-end delay requirements for different flows, is a challenging problem. Using the notions of Draining Time and Discrete Review from the theory of fluid limits of queues, an algorithm that meets delay requirements to various flows in a ...
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A Multi-task Deep Learning Architecture for Maritime Surveillance using AIS Data Streams
In a world of global trading, maritime safety, security and efficiency are crucial issues. We propose a multi-task deep learning framework for vessel monitoring using Automatic Identification System (AIS) data streams. We combine recurrent neural networks with latent variable modeling and an embedding of AIS messages...
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The CCI30 Index
We describe the design of the CCI30 cryptocurrency index.
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Training Probabilistic Spiking Neural Networks with First-to-spike Decoding
Third-generation neural networks, or Spiking Neural Networks (SNNs), aim at harnessing the energy efficiency of spike-domain processing by building on computing elements that operate on, and exchange, spikes. In this paper, the problem of training a two-layer SNN is studied for the purpose of classification, under a ...
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An Effective Training Method For Deep Convolutional Neural Network
In this paper, we propose the nonlinearity generation method to speed up and stabilize the training of deep convolutional neural networks. The proposed method modifies a family of activation functions as nonlinearity generators (NGs). NGs make the activation functions linear symmetric for their inputs to lower model ...
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A Multi-Layer K-means Approach for Multi-Sensor Data Pattern Recognition in Multi-Target Localization
Data-target association is an important step in multi-target localization for the intelligent operation of un- manned systems in numerous applications such as search and rescue, traffic management and surveillance. The objective of this paper is to present an innovative data association learning approach named multi-...
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Investigation of Monaural Front-End Processing for Robust ASR without Retraining or Joint-Training
In recent years, monaural speech separation has been formulated as a supervised learning problem, which has been systematically researched and shown the dramatical improvement of speech intelligibility and quality for human listeners. However, it has not been well investigated whether the methods can be employed as t...
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Average treatment effects in the presence of unknown interference
We investigate large-sample properties of treatment effect estimators under unknown interference in randomized experiments. The inferential target is a generalization of the average treatment effect estimand that marginalizes over potential spillover effects. We show that estimators commonly used to estimate treatmen...
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Spatial localization for nonlinear dynamical stochastic models for excitable media
Nonlinear dynamical stochastic models are ubiquitous in different areas. Excitable media models are typical examples with large state dimensions. Their statistical properties are often of great interest but are also very challenging to compute. In this article, a theoretical framework to understand the spatial locali...
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Nonlinear photoionization of transparent solids: a nonperturbative theory obeying selection rules
We provide a nonperturbative theory for photoionization of transparent solids. By applying a particular steepest-descent method, we derive analytical expressions for the photoionization rate within the two-band structure model, which consistently account for the $selection$ $rules$ related to the parity of the number...
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Quantifying the Model Risk Inherent in the Calibration and Recalibration of Option Pricing Models
We focus on two particular aspects of model risk: the inability of a chosen model to fit observed market prices at a given point in time (calibration error) and the model risk due to recalibration of model parameters (in contradiction to the model assumptions). In this context, we follow the approach of Glasserman an...
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CN rings in full protoplanetary disks around young stars as probes of disk structure
Bright ring-like structure emission of the CN molecule has been observed in protoplanetary disks. We investigate whether such structures are due to the morphology of the disk itself or if they are instead an intrinsic feature of CN emission. With the intention of using CN as a diagnostic, we also address to which phy...
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A Trio Neural Model for Dynamic Entity Relatedness Ranking
Measuring entity relatedness is a fundamental task for many natural language processing and information retrieval applications. Prior work often studies entity relatedness in static settings and an unsupervised manner. However, entities in real-world are often involved in many different relationships, consequently en...
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Dynamic k-Struve Sumudu Solutions for Fractional Kinetic Equations
In this present study, we investigate solutions for fractional kinetic equations, involving k-Struve functions using Sumudu transform. The methodology and results can be considered and applied to various related fractional problems in mathematical physics.
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Does mitigating ML's impact disparity require treatment disparity?
Following related work in law and policy, two notions of disparity have come to shape the study of fairness in algorithmic decision-making. Algorithms exhibit treatment disparity if they formally treat members of protected subgroups differently; algorithms exhibit impact disparity when outcomes differ across subgroup...
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Topological Terms and Phases of Sigma Models
We study boundary conditions of topological sigma models with the goal of generalizing the concepts of anomalous symmetry and symmetry protected topological order. We find a version of 't Hooft's anomaly matching conditions on the renormalization group flow of boundaries of invertible topological sigma models and dis...
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A commuting-vector-field approach to some dispersive estimates
We prove the pointwise decay of solutions to three linear equations: (i) the transport equation in phase space generalizing the classical Vlasov equation, (ii) the linear Schrodinger equation, (iii) the Airy (linear KdV) equation. The usual proofs use explicit representation formulae, and either obtain $L^1$---$L^\in...
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The connected countable spaces of Bing and Ritter are topologically homogeneous
Answering a problem posed by the second author on Mathoverflow, we prove that the connected countable Hausdorff spaces constructed by Bing and Ritter are topologically homogeneous.
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Dynamic Graph Convolutional Networks
Many different classification tasks need to manage structured data, which are usually modeled as graphs. Moreover, these graphs can be dynamic, meaning that the vertices/edges of each graph may change during time. Our goal is to jointly exploit structured data and temporal information through the use of a neural netw...
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Robust and Efficient Parametric Spectral Estimation in Atomic Force Microscopy
An atomic force microscope (AFM) is capable of producing ultra-high resolution measurements of nanoscopic objects and forces. It is an indispensable tool for various scientific disciplines such as molecular engineering, solid-state physics, and cell biology. Prior to a given experiment, the AFM must be calibrated by ...
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A Robotic Auto-Focus System based on Deep Reinforcement Learning
Considering its advantages in dealing with high-dimensional visual input and learning control policies in discrete domain, Deep Q Network (DQN) could be an alternative method of traditional auto-focus means in the future. In this paper, based on Deep Reinforcement Learning, we propose an end-to-end approach that can ...
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Wall modeling via function enrichment: extension to detached-eddy simulation
We extend the approach of wall modeling via function enrichment to detached-eddy simulation. The wall model aims at using coarse cells in the near-wall region by modeling the velocity profile in the viscous sublayer and log-layer. However, unlike other wall models, the full Navier-Stokes equations are still discretel...
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Existence and uniqueness of periodic solution of nth-order Equations with delay in Banach space having Fourier type
The aim of this work is to study the existence of a periodic solutions of nth-order differential equations with delay d dt x(t) + d 2 dt 2 x(t) + d 3 dt 3 x(t) + ... + d n dt n x(t) = Ax(t) + L(xt) + f (t). Our approach is based on the M-boundedness of linear operators, Fourier type, B s p,q-multipliers and Besov spa...
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A proof of Hilbert's theorem on ternary quartic forms with the ladder technique
This paper proposes a totally constructive approach for the proof of Hilbert's theorem on ternary quartic forms. The main contribution is the ladder technique, with which the Hilbert's theorem is proved vividly.
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Data-driven Job Search Engine Using Skills and Company Attribute Filters
According to a report online, more than 200 million unique users search for jobs online every month. This incredibly large and fast growing demand has enticed software giants such as Google and Facebook to enter this space, which was previously dominated by companies such as LinkedIn, Indeed and CareerBuilder. Recent...
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The universal DAHA of type $(C_1^\vee,C_1)$ and Leonard pairs of $q$-Racah type
A Leonard pair is a pair of diagonalizable linear transformations of a finite-dimensional vector space, each of which acts in an irreducible tridiagonal fashion on an eigenbasis for the other one. Let $\mathbb F$ denote an algebraically closed field, and fix a nonzero $q \in \mathbb F$ that is not a root of unity. Th...
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Deep Learning for Computational Chemistry
The rise and fall of artificial neural networks is well documented in the scientific literature of both computer science and computational chemistry. Yet almost two decades later, we are now seeing a resurgence of interest in deep learning, a machine learning algorithm based on multilayer neural networks. Within the ...
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Causal Interventions for Fairness
Most approaches in algorithmic fairness constrain machine learning methods so the resulting predictions satisfy one of several intuitive notions of fairness. While this may help private companies comply with non-discrimination laws or avoid negative publicity, we believe it is often too little, too late. By the time ...
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Analyzing Hypersensitive AI: Instability in Corporate-Scale Machine Learning
Predictive geometric models deliver excellent results for many Machine Learning use cases. Despite their undoubted performance, neural predictive algorithms can show unexpected degrees of instability and variance, particularly when applied to large datasets. We present an approach to measure changes in geometric mode...
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Role of the orbital degree of freedom in iron-based superconductors
Almost a decade has passed since the serendipitous discovery of the iron-based high temperature superconductors (FeSCs) in 2008. The question of how much similarity the FeSCs have with the copper oxide high temperature superconductors emerged since the initial discovery of long-range antiferromagnetism in the FeSCs i...
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Perpetual points: New tool for localization of co-existing attractors in dynamical systems
Perpetual points (PPs) are special critical points for which the magnitude of acceleration describing dynamics drops to zero, while the motion is still possible (stationary points are excluded), e.g. considering the motion of the particle in the potential field, at perpetual point it has zero acceleration and non-zer...
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Loss Functions in Restricted Parameter Spaces and Their Bayesian Applications
A squared error loss remains the most commonly used loss function for constructing a Bayes estimator of the parameter of interest. It, however, can lead to sub-optimal solutions when a parameter is defined on a restricted space. It can also be an inappropriate choice in the context when an overestimation and/or under...
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When Slepian Meets Fiedler: Putting a Focus on the Graph Spectrum
The study of complex systems benefits from graph models and their analysis. In particular, the eigendecomposition of the graph Laplacian lets emerge properties of global organization from local interactions; e.g., the Fiedler vector has the smallest non-zero eigenvalue and plays a key role for graph clustering. Graph...
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Colored Image Encryption and Decryption Using Chaotic Lorenz System and DCT2
In this paper, a scheme for the encryption and decryption of colored images by using the Lorenz system and the discrete cosine transform in two dimensions (DCT2) is proposed. Although chaos is random, it has deterministic features that can be used for encryption; further, the same sequences can be produced at the tra...
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Self-Gluing formula of the monopole invariant and its application
Given a $4$-manifold $\hat{M}$ and two homeomorphic surfaces $\Sigma_1, \Sigma_2$ smoothly embedded in $\hat{M}$ with genus more than 1, we remove the neighborhoods of the surfaces and obtain a new $4$-manifold $M$ from gluing two boundaries $S^1 \times \Sigma_1$ and $S^1 \times \Sigma_1.$ In this artice, we prove a ...
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An aptamer-biosensor for azole class antifungal drugs
This report describes the development of an aptamer for sensing azole antifungal drugs for therapeutic drug monitoring. Modified Synthetic Evolution of Ligands through Exponential Enrichment (SELEX) was used to discover a DNA aptamer recognizing azole class antifungal drugs. This aptamer undergoes a secondary structu...
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Notes on "Einstein metrics on compact simple Lie groups attached to standard triples"
In the paper "Einstein metrics on compact simple Lie groups attached to standard triples", the authors introduced the definition of standard triples and proved that every compact simple Lie group $G$ attached to a standard triple $(G,K,H)$ admits a left-invariant Einstein metric which is not naturally reductive excep...
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Harmonic quasi-isometric maps II : negatively curved manifolds
We prove that a quasi-isometric map, and more generally a coarse embedding, between pinched Hadamard manifolds is within bounded distance from a unique harmonic map.
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Platform independent profiling of a QCD code
The supercomputing platforms available for high performance computing based research evolve at a great rate. However, this rapid development of novel technologies requires constant adaptations and optimizations of the existing codes for each new machine architecture. In such context, minimizing time of efficiently po...
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DeepGauge: Multi-Granularity Testing Criteria for Deep Learning Systems
Deep learning (DL) defines a new data-driven programming paradigm that constructs the internal system logic of a crafted neuron network through a set of training data. We have seen wide adoption of DL in many safety-critical scenarios. However, a plethora of studies have shown that the state-of-the-art DL systems suf...
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