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Kafnets: kernel-based non-parametric activation functions for neural networks
Neural networks are generally built by interleaving (adaptable) linear layers with (fixed) nonlinear activation functions. To increase their flexibility, several authors have proposed methods for adapting the activation functions themselves, endowing them with varying degrees of flexibility. None of these approaches,...
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Unsteady Propulsion by an Intermittent Swimming Gait
Inviscid computational results are presented on a self-propelled swimmer modeled as a virtual body combined with a two-dimensional hydrofoil pitching intermittently about its leading edge. Lighthill (1971) originally proposed that this burst-and-coast behavior can save fish energy during swimming by taking advantage ...
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Modeling rooted in-trees by finite p-groups
The aim of this chapter is to provide an adequate graph theoretic framework for the description of periodic bifurcations which have recently been discovered in descendant trees of finite p-groups. The graph theoretic concepts of rooted in-trees with weighted vertices and edges perfectly admit an abstract formulation ...
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Towards Algorithmic Typing for DOT
The Dependent Object Types (DOT) calculus formalizes key features of Scala. The D$_{<: }$ calculus is the core of DOT. To date, presentations of D$_{<: }$ have used declarative typing and subtyping rules, as opposed to algorithmic. Unfortunately, algorithmic typing for full D$_{<: }$ is known to be an undecidable pro...
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Really? Well. Apparently Bootstrapping Improves the Performance of Sarcasm and Nastiness Classifiers for Online Dialogue
More and more of the information on the web is dialogic, from Facebook newsfeeds, to forum conversations, to comment threads on news articles. In contrast to traditional, monologic Natural Language Processing resources such as news, highly social dialogue is frequent in social media, making it a challenging context f...
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A new statistical method for characterizing the atmospheres of extrasolar planets
By detecting light from extrasolar planets,we can measure their compositions and bulk physical properties. The technologies used to make these measurements are still in their infancy, and a lack of self-consistency suggests that previous observations have underestimated their systemic errors.We demonstrate a statisti...
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Prioritizing network communities
Uncovering modular structure in networks is fundamental for systems in biology, physics, and engineering. Community detection identifies candidate modules as hypotheses, which then need to be validated through experiments, such as mutagenesis in a biological laboratory. Only a few communities can typically be validat...
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New ALMA constraints on the star-forming ISM at low metallicity: A 50 pc view of the blue compact dwarf galaxy SBS0335-052
Properties of the cold interstellar medium of low-metallicity galaxies are not well-known due to the faintness and extremely small scale on which emission is expected. We present deep ALMA band 6 (230GHz) observations of the nearby, low-metallicity (12 + log(O/H) = 7.25) blue compact dwarf galaxy SBS0335-052 at an un...
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On Structured Prediction Theory with Calibrated Convex Surrogate Losses
We provide novel theoretical insights on structured prediction in the context of efficient convex surrogate loss minimization with consistency guarantees. For any task loss, we construct a convex surrogate that can be optimized via stochastic gradient descent and we prove tight bounds on the so-called "calibration fu...
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Improving Sharir and Welzl's bound on crossing-free matchings through solving a stronger recurrence
Sharir and Welzl [1] derived a bound on crossing-free matchings primarily based on solving a recurrence based on the size of the matchings. We show that the recurrence given in Lemma 2.3 in Sharir and Welzl can be improve to $(2n-6s)\textbf{Ma}_{m}(P)\leq\frac{68}{3}(s+2)\textbf{Ma}_{m-1}(P)$ and $(3n-7s)\textbf{Ma}_...
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Computing eigenfunctions and eigenvalues of boundary value problems with the orthogonal spectral renormalization method
The spectral renormalization method was introduced in 2005 as an effective way to compute ground states of nonlinear Schrödinger and Gross-Pitaevskii type equations. In this paper, we introduce an orthogonal spectral renormalization (OSR) method to compute ground and excited states (and their respective eigenvalues) ...
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A Discontinuity Adjustment for Subdistribution Function Confidence Bands Applied to Right-Censored Competing Risks Data
The wild bootstrap is the resampling method of choice in survival analytic applications. Theoretic justifications rely on the assumption of existing intensity functions which is equivalent to an exclusion of ties among the event times. However, such ties are omnipresent in practical studies. It turns out that the wil...
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Estimation of block sparsity in compressive sensing
In this paper, we consider a soft measure of block sparsity, $k_\alpha(\mathbf{x})=\left(\lVert\mathbf{x}\rVert_{2,\alpha}/\lVert\mathbf{x}\rVert_{2,1}\right)^{\frac{\alpha}{1-\alpha}},\alpha\in[0,\infty]$ and propose a procedure to estimate it by using multivariate isotropic symmetric $\alpha$-stable random projecti...
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Q-learning with UCB Exploration is Sample Efficient for Infinite-Horizon MDP
A fundamental question in reinforcement learning is whether model-free algorithms are sample efficient. Recently, Jin et al. \cite{jin2018q} proposed a Q-learning algorithm with UCB exploration policy, and proved it has nearly optimal regret bound for finite-horizon episodic MDP. In this paper, we adapt Q-learning wi...
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You Cannot Fix What You Cannot Find! An Investigation of Fault Localization Bias in Benchmarking Automated Program Repair Systems
Properly benchmarking Automated Program Repair (APR) systems should contribute to the development and adoption of the research outputs by practitioners. To that end, the research community must ensure that it reaches significant milestones by reliably comparing state-of-the-art tools for a better understanding of the...
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Acquiring Common Sense Spatial Knowledge through Implicit Spatial Templates
Spatial understanding is a fundamental problem with wide-reaching real-world applications. The representation of spatial knowledge is often modeled with spatial templates, i.e., regions of acceptability of two objects under an explicit spatial relationship (e.g., "on", "below", etc.). In contrast with prior work that...
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Design of Capacity Approaching Ensembles of LDPC Codes for Correlated Sources using EXIT Charts
This paper is concerned with the design of capacity approaching ensembles of Low-Densiy Parity-Check (LDPC) codes for correlated sources. We consider correlated binary sources where the data is encoded independently at each source through a systematic LDPC encoder and sent over two independent channels. At the receiv...
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Evolution of Morphological and Physical Properties of Laboratory Interstellar Organic Residues with Ultraviolet Irradiation
Refractory organic compounds formed in molecular clouds are among the building blocks of the solar system objects and could be the precursors of organic matter found in primitive meteorites and cometary materials. However, little is known about the evolutionary pathways of molecular cloud organics from dense molecula...
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Evaporating pure, binary and ternary droplets: thermal effects and axial symmetry breaking
The Greek aperitif Ouzo is not only famous for its specific anise-flavored taste, but also for its ability to turn from a transparent miscible liquid to a milky-white colored emulsion when water is added. Recently, it has been shown that this so-called Ouzo effect, i.e. the spontaneous emulsification of oil microdrop...
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A semianalytical approach for determining the nonclassical mechanical properties of materials
In this article, a semianalytical approach for demonstrating elastic waves propagation in nanostructures has been presented based on the modified couple-stress theory including acceleration gradients. Using the experimental results and atomic simulations, the static and dynamic length scales were calculated for sever...
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Gaussian Processes for Demand Unconstraining
One of the key challenges in revenue management is unconstraining demand data. Existing state of the art single-class unconstraining methods make restrictive assumptions about the form of the underlying demand and can perform poorly when applied to data which breaks these assumptions. In this paper, we propose a nove...
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Generalization of two Bonnet's Theorems to the relative Differential Geometry of the 3-dimensional Euclidean space
This paper is devoted to the 3-dimensional relative differential geometry of surfaces. In the Euclidean space $\R{E} ^3 $ we consider a surface $\varPhi %\colon \vect{x} = \vect{x}(u^1,u^2) $ with position vector field $\vect{x}$, which is relatively normalized by a relative normalization $\vect{y}% (u^1,u^2) $. A su...
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Some Aspects of Uniqueness Theory of Entire and Meromorphic Functions (Ph.D. thesis)
The subject of our thesis is the uniqueness theory of meromorphic functions and it is devoted to problems concerning Bruck conjecture, set sharing and related topics. The tool, we used in our discussions is classical Nevanlinna theory of meromorphic functions. In 1996, in order to find the relation between an entire ...
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Transfer Regression via Pairwise Similarity Regularization
Transfer learning methods address the situation where little labeled training data from the "target" problem exists, but much training data from a related "source" domain is available. However, the overwhelming majority of transfer learning methods are designed for simple settings where the source and target predicti...
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Star formation in a galactic outflow
Recent observations have revealed massive galactic molecular outflows that may have physical conditions (high gas densities) required to form stars. Indeed, several recent models predict that such massive galactic outflows may ignite star formation within the outflow itself. This star-formation mode, in which stars f...
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Artificial intelligence in peer review: How can evolutionary computation support journal editors?
With the volume of manuscripts submitted for publication growing every year, the deficiencies of peer review (e.g. long review times) are becoming more apparent. Editorial strategies, sets of guidelines designed to speed up the process and reduce editors workloads, are treated as trade secrets by publishing houses an...
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Invariant Bianchi type I models in $f\left(R,T\right)$ Gravity
In this paper, we search the existence of invariant solutions of Bianchi type I space-time in the context of $f\left(R,T\right)$ gravity. The exact solution of the Einstein's field equations are derived by using Lie point symmetry analysis method that yield two models of invariant universe for symmetries $X^{(1)}$ an...
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Representation theoretic realization of non-symmetric Macdonald polynomials at infinity
We study the nonsymmetric Macdonald polynomials specialized at infinity from various points of view. First, we define a family of modules of the Iwahori algebra whose characters are equal to the nonsymmetric Macdonald polynomials specialized at infinity. Second, we show that these modules are isomorphic to the dual s...
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Complex spectrogram enhancement by convolutional neural network with multi-metrics learning
This paper aims to address two issues existing in the current speech enhancement methods: 1) the difficulty of phase estimations; 2) a single objective function cannot consider multiple metrics simultaneously. To solve the first problem, we propose a novel convolutional neural network (CNN) model for complex spectrog...
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Optimal Threshold Design for Quanta Image Sensor
Quanta Image Sensor (QIS) is a binary imaging device envisioned to be the next generation image sensor after CCD and CMOS. Equipped with a massive number of single photon detectors, the sensor has a threshold $q$ above which the number of arriving photons will trigger a binary response "1", or "0" otherwise. Existing...
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Statistics of $K$-groups modulo $p$ for the ring of integers of a varying quadratic number field
For each odd prime $p$, we conjecture the distribution of the $p$-torsion subgroup of $K_{2n}(\mathcal{O}_F)$ as $F$ ranges over real quadratic fields, or over imaginary quadratic fields. We then prove that the average size of the $3$-torsion subgroup of $K_{2n}(\mathcal{O}_F)$ is as predicted by this conjecture.
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Learning Models for Shared Control of Human-Machine Systems with Unknown Dynamics
We present a novel approach to shared control of human-machine systems. Our method assumes no a priori knowledge of the system dynamics. Instead, we learn both the dynamics and information about the user's interaction from observation through the use of the Koopman operator. Using the learned model, we define an opti...
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A Feature Embedding Strategy for High-level CNN representations from Multiple ConvNets
Following the rapidly growing digital image usage, automatic image categorization has become preeminent research area. It has broaden and adopted many algorithms from time to time, whereby multi-feature (generally, hand-engineered features) based image characterization comes handy to improve accuracy. Recently, in ma...
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Look-Ahead in the Two-Sided Reduction to Compact Band Forms for Symmetric Eigenvalue Problems and the SVD
We address the reduction to compact band forms, via unitary similarity transformations, for the solution of symmetric eigenvalue problems and the computation of the singular value decomposition (SVD). Concretely, in the first case we revisit the reduction to symmetric band form while, for the second case, we propose ...
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Non-existence of a Wente's $L^\infty$ estimate for the Neumann problem
We provide a counterexample of Wente's inequality in the context of Neumann boundary conditions. We will also show that Wente's estimates fails for general boundary conditions of Robin type.
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Regular characters of classical groups over complete discrete valuation rings
Let $\mathfrak{o}$ be a complete discrete valuation ring with finide residue field $\mathsf{k}$ of odd characteristic, and let $\mathbf{G}$ be a symplectic or special orthogonal group scheme over $\mathfrak{o}$. For any $\ell\in\mathbb{N}$ let $G^\ell$ denote the $\ell$-th principal congruence subgroup of $\mathbf{G}...
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Quantitative analysis of nonadiabatic effects in dense H$_3$S and PH$_3$ superconductors
The comparison study of high pressure superconducting state of recently synthesized H$_3$S and PH$_3$ compounds are conducted within the framework of the strong-coupling theory. By generalization of the standard Eliashberg equations to include the lowest-order vertex correction, we have investigated the influence of ...
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Radio-flaring Ultracool Dwarf Population Synthesis
Over a dozen ultracool dwarfs (UCDs), low-mass objects of spectral types $\geq$M7, are known to be sources of radio flares. These typically several-minutes-long radio bursts can be up to 100\% circularly polarized and have high brightness temperatures, consistent with coherent emission via the electron cyclotron mase...
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Janus: An Uncertain Cache Architecture to Cope with Side Channel Attacks
Side channel attacks are a major class of attacks to crypto-systems. Attackers collect and analyze timing behavior, I/O data, or power consumption in these systems to undermine their effectiveness in protecting sensitive information. In this work, we propose a new cache architecture, called Janus, to enable crypto-sy...
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Predicting Adversarial Examples with High Confidence
It has been suggested that adversarial examples cause deep learning models to make incorrect predictions with high confidence. In this work, we take the opposite stance: an overly confident model is more likely to be vulnerable to adversarial examples. This work is one of the most proactive approaches taken to date, ...
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A New Taxonomy for Symbiotic EM Sensors
It is clear that the EM spectrum is now rapidly reaching saturation, especially for frequencies below 10~GHz. Governments, who influence the regulatory authorities around the world, have resorted to auctioning the use of spectrum, in a sense to gauge the importance of a particular user. Billions of USD are being paid...
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Local-ring network automata and the impact of hyperbolic geometry in complex network link-prediction
Topological link-prediction can exploit the entire network topology (global methods) or only the neighbourhood (local methods) of the link to predict. Global methods are believed the best. Is this common belief well-founded? Stochastic-Block-Model (SBM) is a global method believed as one of the best link-predictors, ...
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Emission of Circularly Polarized Terahertz Wave from Inhomogeneous Intrinsic Josephson Junctions
We have theoretically demonstrated the emission of circularly-polarized terahertz (THz) waves from intrinsic Josephson junctions (IJJs) which is locally heated by an external heat source such as the laser irradiation. We focus on a mesa-structured IJJ whose geometry is slightly deviate from a square and find that the...
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Asymmetry-Induced Synchronization in Oscillator Networks
A scenario has recently been reported in which in order to stabilize complete synchronization of an oscillator network---a symmetric state---the symmetry of the system itself has to be broken by making the oscillators nonidentical. But how often does such behavior---which we term asymmetry-induced synchronization (AI...
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Opportunistic Downlink Interference Alignment for Multi-Cell MIMO Networks
In this paper, we propose an opportunistic downlink interference alignment (ODIA) for interference-limited cellular downlink, which intelligently combines user scheduling and downlink IA techniques. The proposed ODIA not only efficiently reduces the effect of inter-cell interference from other-cell base stations (BSs...
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The Repeated Divisor Function and Possible Correlation with Highly Composite Numbers
Let n be a non-null positive integer and $d(n)$ is the number of positive divisors of n, called the divisor function. Of course, $d(n) \leq n$. $d(n) = 1$ if and only if $n = 1$. For $n > 2$ we have $d(n) \geq 2$ and in this paper we try to find the smallest $k$ such that $d(d(...d(n)...)) = 2$ where the divisor func...
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A Language Hierarchy and Kitchens-Type Theorem for Self-Similar Groups
We generalize the notion of self-similar groups of infinite tree automorphisms to allow for groups which are defined on a tree but do not act faithfully on it. The elements of such a group correspond to labeled trees which may be recognized by a tree automaton (e.g. Rabin, Büchi, etc.), or considered as elements of a...
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Distance Covariance in Metric Spaces: Non-Parametric Independence Testing in Metric Spaces (Master's thesis)
The aim of this thesis is to find a solution to the non-parametric independence problem in separable metric spaces. Suppose we are given finite collection of samples from an i.i.d. sequence of paired random elements, where each marginal has values in some separable metric space. The non-parametric independence proble...
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Sum-Product-Quotient Networks
We present a novel tractable generative model that extends Sum-Product Networks (SPNs) and significantly boosts their power. We call it Sum-Product-Quotient Networks (SPQNs), whose core concept is to incorporate conditional distributions into the model by direct computation using quotient nodes, e.g. $P(A|B) = \frac{...
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When Simpler Data Does Not Imply Less Information: A Study of User Profiling Scenarios with Constrained View of Mobile HTTP(S) Traffic
The exponential growth in smartphone adoption is contributing to the availability of vast amounts of human behavioral data. This data enables the development of increasingly accurate data-driven user models that facilitate the delivery of personalized services which are often free in exchange for the use of its custo...
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Algebraic Description of Shape Invariance Revisited
We revisit the algebraic description of shape invariance method in one-dimensional quantum mechanics. In this note we focus on four particular examples: the Kepler problem in flat space, the Kepler problem in spherical space, the Kepler problem in hyperbolic space, and the Rosen-Morse potential problem. Following the...
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Joint Smoothing, Tracking, and Forecasting Based on Continuous-Time Target Trajectory Fitting
We present a continuous time state estimation framework that unifies traditionally individual tasks of smoothing, tracking, and forecasting (STF), for a class of targets subject to smooth motion processes, e.g., the target moves with nearly constant acceleration or affected by insignificant noises. Fundamentally diff...
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Parkinson's Disease Digital Biomarker Discovery with Optimized Transitions and Inferred Markov Emissions
We search for digital biomarkers from Parkinson's Disease by observing approximate repetitive patterns matching hypothesized step and stride periodic cycles. These observations were modeled as a cycle of hidden states with randomness allowing deviation from a canonical pattern of transitions and emissions, under the ...
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Bifurcation to locked fronts in two component reaction-diffusion systems
We study invasion fronts and spreading speeds in two component reaction-diffusion systems. Using a variation of Lin's method, we construct traveling front solutions and show the existence of a bifurcation to locked fronts where both components invade at the same speed. Expansions of the wave speed as a function of th...
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Contrastive Hebbian Learning with Random Feedback Weights
Neural networks are commonly trained to make predictions through learning algorithms. Contrastive Hebbian learning, which is a powerful rule inspired by gradient backpropagation, is based on Hebb's rule and the contrastive divergence algorithm. It operates in two phases, the forward (or free) phase, where the data ar...
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A model of electrical impedance tomography on peripheral nerves for a neural-prosthetic control interface
Objective: A model is presented to evaluate the viability of using electrical impedance tomography (EIT) with a nerve cuff to record neural activity in peripheral nerves. Approach: Established modelling approaches in neural-EIT are expanded on to be used, for the first time, on myelinated fibres which are abundant in...
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Above threshold scattering about a Feshbach resonance for ultracold atoms in an optical collider
Ultracold atomic gases have realised numerous paradigms of condensed matter physics where control over interactions has crucially been afforded by tunable Feshbach resonances. So far, the characterisation of these Feshbach resonances has almost exclusively relied on experiments in the threshold regime near zero energ...
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Gaussian Process Subset Scanning for Anomalous Pattern Detection in Non-iid Data
Identifying anomalous patterns in real-world data is essential for understanding where, when, and how systems deviate from their expected dynamics. Yet methods that separately consider the anomalousness of each individual data point have low detection power for subtle, emerging irregularities. Additionally, recent de...
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Isolated resonances and nonlinear damping
We analyze isolated resonance curves (IRCs) in a single-degree-of-freedom system with nonlinear damping. The adopted procedure exploits singularity theory in conjunction with the harmonic balance method. The analysis unveils a geometrical connection between the topology of the damping force and IRCs. Specifically, we...
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UAV Aided Aerial-Ground IoT for Air Quality Sensing in Smart City: Architecture, Technologies and Implementation
As air pollution is becoming the largest environmental health risk, the monitoring of air quality has drawn much attention in both theoretical studies and practical implementations. In this article, we present a real-time, fine-grained and power-efficient air quality monitoring system based on aerial and ground sensi...
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Photoinduced vibronic coupling in two-level dissipative systems
Interaction of an electron system with a strong electromagnetic wave leads to rearrangement both the electron and vibrational energy spectra of a dissipative system. For instance, the optically coupled electron levels become split in the conditions of the ac Stark effect that gives rise to appearance of the nonadiaba...
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Crowd Science: Measurements, Models, and Methods
The increasing practice of engaging crowds, where organizations use IT to connect with dispersed individuals for explicit resource creation purposes, has precipitated the need to measure the precise processes and benefits of these activities over myriad different implementations. In this work, we seek to address thes...
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Procedural Content Generation via Machine Learning (PCGML)
This survey explores Procedural Content Generation via Machine Learning (PCGML), defined as the generation of game content using machine learning models trained on existing content. As the importance of PCG for game development increases, researchers explore new avenues for generating high-quality content with or wit...
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Automated Vulnerability Detection in Source Code Using Deep Representation Learning
Increasing numbers of software vulnerabilities are discovered every year whether they are reported publicly or discovered internally in proprietary code. These vulnerabilities can pose serious risk of exploit and result in system compromise, information leaks, or denial of service. We leveraged the wealth of C and C+...
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X-Shooter study of accretion in Chamaeleon I: II. A steeper increase of accretion with stellar mass for very low mass stars?
The dependence of the mass accretion rate on the stellar properties is a key constraint for star formation and disk evolution studies. Here we present a study of a sample of stars in the Chamaeleon I star forming region carried out using the VLT/X-Shooter spectrograph. The sample is nearly complete down to M~0.1Msun ...
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A General Model for Robust Tensor Factorization with Unknown Noise
Because of the limitations of matrix factorization, such as losing spatial structure information, the concept of low-rank tensor factorization (LRTF) has been applied for the recovery of a low dimensional subspace from high dimensional visual data. The low-rank tensor recovery is generally achieved by minimizing the ...
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Phase locking the spin precession in a storage ring
This letter reports the successful use of feedback from a spin polarization measurement to the revolution frequency of a 0.97 GeV/$c$ bunched and polarized deuteron beam in the Cooler Synchrotron (COSY) storage ring in order to control both the precession rate ($\approx 121$ kHz) and the phase of the horizontal polar...
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Learning Vertex Representations for Bipartite Networks
Recent years have witnessed a widespread increase of interest in network representation learning (NRL). By far most research efforts have focused on NRL for homogeneous networks like social networks where vertices are of the same type, or heterogeneous networks like knowledge graphs where vertices (and/or edges) are ...
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Liouville integrability of conservative peakons for a modified CH equation
The modified Camassa-Holm equation (also called FORQ) is one of numerous $cousins$ of the Camassa-Holm equation possessing non-smoth solitons ($peakons$) as special solutions. The peakon sector of solutions is not uniquely defined: in one peakon sector (dissapative) the Sobolev $H^1$ norm is not preserved, in the oth...
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State Representation Learning for Control: An Overview
Representation learning algorithms are designed to learn abstract features that characterize data. State representation learning (SRL) focuses on a particular kind of representation learning where learned features are in low dimension, evolve through time, and are influenced by actions of an agent. The representation...
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Tracking Emerges by Colorizing Videos
We use large amounts of unlabeled video to learn models for visual tracking without manual human supervision. We leverage the natural temporal coherency of color to create a model that learns to colorize gray-scale videos by copying colors from a reference frame. Quantitative and qualitative experiments suggest that ...
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Observation of topological valley transport of sound in sonic crystals
Valley pseudospin, labeling quantum states of energy extrema in momentum space, is attracting tremendous attention1-13 because of its potential in constructing new carrier of information. Compared with the non-topological bulk valley transport realized soon after predictions1-5, the topological valley transport in do...
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Equilibrium distributions and discrete Schur-constant models
This paper introduces Schur-constant equilibrium distribution models of dimension n for arithmetic non-negative random variables. Such a model is defined through the (several orders) equilibrium distributions of a univariate survival function. First, the bivariate case is considered and analyzed in depth, stressing t...
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Tempered homogeneous spaces
Let $G$ be a semisimple real Lie group with finite center and $H$ a connected closed subgroup. We establish a geometric criterion which detects whether the representation of $G$ in $L^2(G/H)$ is tempered.
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Consistency of Dirichlet Partitions
A Dirichlet $k$-partition of a domain $U \subseteq \mathbb{R}^d$ is a collection of $k$ pairwise disjoint open subsets such that the sum of their first Laplace-Dirichlet eigenvalues is minimal. A discrete version of Dirichlet partitions has been posed on graphs with applications in data analysis. Both versions admit ...
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Experimental investigation of the wake behind a rotating sphere
The wake behind a sphere, rotating about an axis aligned with the streamwise direction, has been experimentally investigated in a low-velocity water tunnel using LIF visualizations and PIV measurements. The measurements focused on the evolution of the flow regimes that appear depending on two control parameters, name...
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Test results of a prototype device to calibrate the Large Size Telescope camera proposed for the Cherenkov Telescope Array
A Large Size air Cherenkov Telescope (LST) prototype, proposed for the Cherenkov Telescope Array (CTA), is under construction at the Canary Island of La Palma (Spain) this year. The LST camera, which comprises an array of about 500 photomultipliers (PMTs), requires a precise and regular calibration over a large dynam...
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Extended superalgebras from twistor and Killing spinors
The basic first-order differential operators of spin geometry that are Dirac operator and twistor operator are considered. Special types of spinors defined from these operators such as twistor spinors and Killing spinors are discussed. Symmetry operators of massless and massive Dirac equations are introduced and rele...
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The Physics of Eccentric Binary Black Hole Mergers. A Numerical Relativity Perspective
Gravitational wave observations of eccentric binary black hole mergers will provide unequivocal evidence for the formation of these systems through dynamical assembly in dense stellar environments. The study of these astrophysically motivated sources is timely in view of electromagnetic observations, consistent with ...
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Joint Computation and Communication Cooperation for Mobile Edge Computing
This paper proposes a novel joint computation and communication cooperation approach in mobile edge computing (MEC) systems, which enables user cooperation in both computation and communication for improving the MEC performance. In particular, we consider a basic three-node MEC system that consists of a user node, a ...
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Propagating wave correlations in complex systems
We describe a novel approach for computing wave correlation functions inside finite spatial domains driven by complex and statistical sources. By exploiting semiclassical approximations, we provide explicit algorithms to calculate the local mean of these correlation functions in terms of the underlying classical dyna...
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Cost-Effective Cache Deployment in Mobile Heterogeneous Networks
This paper investigates one of the fundamental issues in cache-enabled heterogeneous networks (HetNets): how many cache instances should be deployed at different base stations, in order to provide guaranteed service in a cost-effective manner. Specifically, we consider two-tier HetNets with hierarchical caching, wher...
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Experimental demonstration of a Josephson magnetic memory cell with a programmable π-junction
We experimentally demonstrate the operation of a Josephson magnetic random access memory unit cell, built with a Ni_80Fe_20/Cu/Ni pseudo spin-valve Josephson junction with Nb electrodes and an integrated readout SQUID in a fully planarized Nb fabrication process. We show that the parallel and anti-parallel memory sta...
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On the Dynamics of Supermassive Black Holes in Gas-Rich, Star-Forming Galaxies: the Case for Nuclear Star Cluster Coevolution
We introduce a new model for the formation and evolution of supermassive black holes (SMBHs) in the RAMSES code using sink particles, improving over previous work the treatment of gas accretion and dynamical evolution. This new model is tested against a suite of high-resolution simulations of an isolated, gas-rich, c...
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A Concave Optimization Algorithm for Matching Partially Overlapping Point Sets
Point matching refers to the process of finding spatial transformation and correspondences between two sets of points. In this paper, we focus on the case that there is only partial overlap between two point sets. Following the approach of the robust point matching method, we model point matching as a mixed linear as...
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Adaptive Mesh Refinement in Analog Mesh Computers
The call for efficient computer architectures has introduced a variety of application-specific compute engines to the heterogeneous computing landscape. One particular engine, the analog mesh computer, has been well received due to its ability to efficiently solve partial differential equations by eliminating the ite...
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On the local view of atmospheric available potential energy
The possibility of constructing Lorenz's concept of available potential energy (APE) from a local principle has been known for some time, but has received very little attention so far. Yet, the local APE framework offers the advantage of providing a positive definite local form of potential energy, which like kinetic...
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GdRh$_2$Si$_2$: An exemplary tetragonal system for antiferromagnetic order with weak in-plane anisotropy
The anisotropy of magnetic properties commonly is introduced in textbooks using the case of an antiferromagnetic system with Ising type anisotropy. This model presents huge anisotropic magnetization and a pronounced metamagnetic transition and is well-known and well-documented both, in experiments and theory. In cont...
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A Kullback-Leibler Divergence-based Distributionally Robust Optimization Model for Heat Pump Day-ahead Operational Schedule in Distribution Networks
For its high coefficient of performance and zero local emissions, the heat pump (HP) has recently become popular in North Europe and China. However, the integration of HPs may aggravate the daily peak-valley gap in distribution networks significantly.
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Towards Optimally Decentralized Multi-Robot Collision Avoidance via Deep Reinforcement Learning
Developing a safe and efficient collision avoidance policy for multiple robots is challenging in the decentralized scenarios where each robot generate its paths without observing other robots' states and intents. While other distributed multi-robot collision avoidance systems exist, they often require extracting agen...
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Metropolis-Hastings Algorithms for Estimating Betweenness Centrality in Large Networks
Betweenness centrality is an important index widely used in different domains such as social networks, traffic networks and the world wide web. However, even for mid-size networks that have only a few hundreds thousands vertices, it is computationally expensive to compute exact betweenness scores. Therefore in recent...
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Learning Flexible and Reusable Locomotion Primitives for a Microrobot
The design of gaits for robot locomotion can be a daunting process which requires significant expert knowledge and engineering. This process is even more challenging for robots that do not have an accurate physical model, such as compliant or micro-scale robots. Data-driven gait optimization provides an automated alt...
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Statistical comparison of (brain) networks
The study of random networks in a neuroscientific context has developed extensively over the last couple of decades. By contrast, techniques for the statistical analysis of these networks are less developed. In this paper, we focus on the statistical comparison of brain networks in a nonparametric framework and discu...
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Sensitivity analysis using perturbed-law based indices for quantiles and application to an industrial case
In this paper, we present perturbed law-based sensitivity indices and how to adapt them for quantile-oriented sensitivity analysis. We exhibit a simple way to compute these indices in practice using an importance sampling estimator for quantiles. Some useful asymptotic results about this estimator are also provided. ...
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The Robustness of LWPP and WPP, with an Application to Graph Reconstruction
We show that the counting class LWPP [FFK94] remains unchanged even if one allows a polynomial number of gap values rather than one. On the other hand, we show that it is impossible to improve this from polynomially many gap values to a superpolynomial number of gap values by relativizable proof techniques. The first...
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Time- and spatially-resolved magnetization dynamics driven by spin-orbit torques
Current-induced spin-orbit torques (SOTs) represent one of the most effective ways to manipulate the magnetization in spintronic devices. The orthogonal torque-magnetization geometry, the strong damping, and the large domain wall velocities inherent to materials with strong spin-orbit coupling make SOTs especially ap...
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Giant Planets Can Act As Stabilizing Agents on Debris Disks
We have explored the evolution of a cold debris disk under the gravitational influence of dwarf planet sized objects (DPs), both in the presence and absence of an interior giant planet. Through detailed long-term numerical simulations, we demonstrate that, when the giant planet is not present, DPs can stir the eccent...
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Definition of geometric space around analytic fractal trees using derivative coordinate funtions
The concept of derivative coordinate functions proved useful in the formulation of analytic fractal functions to represent smooth symmetric binary fractal trees [1]. In this paper we introduce a new geometry that defines the fractal space around these fractal trees. We present the canonical and degenerate form of thi...
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To Pool or Not To Pool? Revisiting an Old Pattern
We revisit the well-known object-pool design pattern in Java. In the last decade, the pattern has attracted a lot of criticism regarding its validity when used for light-weight objects that are only meant to hold memory rather than any other resources (database connections, sockets etc.) and in fact, common opinion h...
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Quenching of supermassive black hole growth around the apparent maximum mass
Recent quasar surveys have revealed that supermassive black holes (SMBHs) rarely exceed a mass of $M_{\rm BH} \sim {\rm a~few}\times10^{10}~M_{\odot}$ during the entire cosmic history. It has been argued that quenching of the BH growth is caused by a transition of a nuclear accretion disk into an advection dominated ...
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