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Acceleration and Averaging in Stochastic Mirror Descent Dynamics
We formulate and study a general family of (continuous-time) stochastic dynamics for accelerated first-order minimization of smooth convex functions. Building on an averaging formulation of accelerated mirror descent, we propose a stochastic variant in which the gradient is contaminated by noise, and study the result...
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Electrothermal Feedback in Kinetic Inductance Detectors
In Kinetic Inductance Detectors (KIDs) and other similar applications of superconducting microresonators, both the large and small-signal behaviour of the device may be affected by electrothermal feedback. Microwave power applied to read out the device is absorbed by and heats the superconductor quasiparticles, chang...
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Comparison of Modified Kneser-Ney and Witten-Bell Smoothing Techniques in Statistical Language Model of Bahasa Indonesia
Smoothing is one technique to overcome data sparsity in statistical language model. Although in its mathematical definition there is no explicit dependency upon specific natural language, different natures of natural languages result in different effects of smoothing techniques. This is true for Russian language as s...
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Social evolution of structural discrimination
Structural discrimination appears to be a persistent phenomenon in social systems. We here outline the hypothesis that it can result from the evolutionary dynamics of the social system itself. We study the evolutionary dynamics of agents with neutral badges in a simple social game and find that the badges are readily...
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Decentralized Control of a Hexapod Robot Using a Wireless Time Synchronized Network
Robots and control systems rely upon precise timing of sensors and actuators in order to operate intelligently. We present a functioning hexapod robot that walks with a dual tripod gait; each tripod is actuated using its own local controller running on a separate wireless node. We compare and report the results of op...
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Domain wall motion by localized temperature gradients
Magnetic domain wall (DW) motion induced by a localized Gaussian temperature profile is studied in a Permalloy nanostrip within the framework of the stochastic Landau-Lifshitz-Bloch equation. The different contributions to thermally induced DW motion, entropic torque and magnonic spin transfer torque, are isolated an...
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Generation of High Dynamic Range Illumination from a Single Image for the Enhancement of Undesirably Illuminated Images
This paper presents an algorithm that enhances undesirably illuminated images by generating and fusing multi-level illuminations from a single image.The input image is first decomposed into illumination and reflectance components by using an edge-preserving smoothing filter. Then the reflectance component is scaled u...
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Replace or Retrieve Keywords In Documents at Scale
In this paper we introduce, the FlashText algorithm for replacing keywords or finding keywords in a given text. FlashText can search or replace keywords in one pass over a document. The time complexity of this algorithm is not dependent on the number of terms being searched or replaced. For a document of size N (char...
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A Multi Objective Reliable Location-Inventory Capacitated Disruption Facility Problem with Penalty Cost Solve with Efficient Meta Historic Algorithms
Logistics network is expected that opened facilities work continuously for a long time horizon without any failure, but in real world problems, facilities may face disruptions. This paper studies a reliable joint inventory location problem to optimize the cost of facility locations, customers assignment, and inventor...
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Formation of Galactic Prominence in Galactic Central Region
We carried out 2.5-dimensional resistive MHD simulations to study the formation mechanism of molecular loops observed by Fukui et al. (2006) at Galactic central region. Since it is hard to form molecular loops by uplifting dense molecular gas, we study the formation mechanism of molecular gas in rising magnetic arcad...
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Joint Probabilistic Linear Discriminant Analysis
Standard probabilistic linear discriminant analysis (PLDA) for speaker recognition assumes that the sample's features (usually, i-vectors) are given by a sum of three terms: a term that depends on the speaker identity, a term that models the within-speaker variability and is assumed independent across samples, and a ...
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Adversarial Attack on Graph Structured Data
Deep learning on graph structures has shown exciting results in various applications. However, few attentions have been paid to the robustness of such models, in contrast to numerous research work for image or text adversarial attack and defense. In this paper, we focus on the adversarial attacks that fool the model ...
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Uncertainty quantification for kinetic models in socio-economic and life sciences
Kinetic equations play a major rule in modeling large systems of interacting particles. Recently the legacy of classical kinetic theory found novel applications in socio-economic and life sciences, where processes characterized by large groups of agents exhibit spontaneous emergence of social structures. Well-known e...
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How Much Chemistry Does a Deep Neural Network Need to Know to Make Accurate Predictions?
The meteoric rise of deep learning models in computer vision research, having achieved human-level accuracy in image recognition tasks is firm evidence of the impact of representation learning of deep neural networks. In the chemistry domain, recent advances have also led to the development of similar CNN models, suc...
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Accelerated Computing in Magnetic Resonance Imaging -- Real-Time Imaging Using Non-Linear Inverse Reconstruction
Purpose: To develop generic optimization strategies for image reconstruction using graphical processing units (GPUs) in magnetic resonance imaging (MRI) and to exemplarily report about our experience with a highly accelerated implementation of the non-linear inversion algorithm (NLINV) for dynamic MRI with high frame...
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Exploiting Color Name Space for Salient Object Detection
In this paper, we will investigate the contribution of color names for salient object detection. Each input image is first converted to the color name space, which is consisted of 11 probabilistic channels. By exploring the topological structure relationship between the figure and the ground, we obtain a saliency map...
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Possibility to realize spin-orbit-induced correlated physics in iridium fluorides
Recent theoretical predictions of "unprecedented proximity" of the electronic ground state of iridium fluorides to the SU(2) symmetric $j_{\mathrm{eff}}=1/2$ limit, relevant for superconductivity in iridates, motivated us to investigate their crystal and electronic structure. To this aim, we performed high-resolution...
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Numerical Investigation of Unsteady Aerodynamic Effects on Thick Flatback Airfoils
The unsteady characteristics of the flow over thick flatback airfoils have been investigated by means of CFD calculations. Sandia airfoils which have 35% maximum thickness with three different trailing edge thicknesses were selected. The calculations provided good results compared with available experimental data wit...
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Development of a passive Rehabilitation Robot for the wrist joint through the implementation of an Arduino UNO microcontroller
In this research was implemented the use of an Arduino UNO R3 microcontroller to control the movements of a prototype robotic functional developed to perform rehabilitation exercises in the wrist joint; This device can be used to assist the physiatrist to rehabilitate the tendinitis, synovitis, rheumatoid arthritis a...
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PHOEG Helps Obtaining Extremal Graphs
Extremal Graph Theory aims to determine bounds for graph invariants as well as the graphs attaining those bounds. We are currently developping PHOEG, an ecosystem of tools designed to help researchers in Extremal Graph Theory. It uses a big relational database of undirected graphs and works with the convex hull of th...
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Crime Prediction by Data-Driven Green's Function method
We develop an algorithm that forecasts cascading events, by employing a Green's function scheme on the basis of the self-exciting point process model. This method is applied to open data of 10 types of crimes happened in Chicago. It shows a good prediction accuracy superior to or comparable to the standard methods wh...
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DZ Cha: a bona fide photoevaporating disc
DZ Cha is a weak-lined T Tauri star (WTTS) surrounded by a bright protoplanetary disc with evidence of inner disc clearing. Its narrow $\Ha$ line and infrared spectral energy distribution suggest that DZ Cha may be a photoevaporating disc. We aim to analyse the DZ Cha star + disc system to identify the mechanism driv...
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A Bayesian Filtering Algorithm for Gaussian Mixture Models
A Bayesian filtering algorithm is developed for a class of state-space systems that can be modelled via Gaussian mixtures. In general, the exact solution to this filtering problem involves an exponential growth in the number of mixture terms and this is handled here by utilising a Gaussian mixture reduction step afte...
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Efficient Use of Limited-Memory Accelerators for Linear Learning on Heterogeneous Systems
We propose a generic algorithmic building block to accelerate training of machine learning models on heterogeneous compute systems. Our scheme allows to efficiently employ compute accelerators such as GPUs and FPGAs for the training of large-scale machine learning models, when the training data exceeds their memory c...
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Fast Autonomous Flight in Warehouses for Inventory Applications
The past years have shown a remarkable growth in use-cases for micro aerial vehicles (MAVs). Conceivable indoor applications require highly robust environment perception, fast reaction to changing situations, and stable navigation, but reliable sources of absolute positioning like GNSS or compass measurements are una...
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Cosmological solutions in generalized hybrid metric-Palatini gravity
We construct exact solutions representing a Friedmann-Lemaître-Robsertson-Walker (FLRW) universe in a generalized hybrid metric-Palatini theory. By writing the gravitational action in a scalar-tensor representation, the new solutions are obtained by either making an ansatz on the scale factor or on the effective pote...
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Ultimate Boundedness for Switched Systems with Multiple Equilibria Under Disturbances
In this paper, we investigate the robustness to external disturbances of switched discrete and continuous systems with multiple equilibria. It is shown that if each subsystem of the switched system is Input-to-State Stable (ISS), then under switching signals that satisfy an average dwell-time bound, the solutions are...
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The two-to-infinity norm and singular subspace geometry with applications to high-dimensional statistics
The singular value matrix decomposition plays a ubiquitous role throughout statistics and related fields. Myriad applications including clustering, classification, and dimensionality reduction involve studying and exploiting the geometric structure of singular values and singular vectors. This paper provides a novel ...
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Variational Bayesian Complex Network Reconstruction
Complex network reconstruction is a hot topic in many fields. A popular data-driven reconstruction framework is based on lasso. However, it is found that, in the presence of noise, it may be inefficient for lasso to determine the network topology. This paper builds a new framework to cope with this problem. The key i...
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Renormalization of the two-dimensional stochastic nonlinear wave equations
We study the two-dimensional stochastic nonlinear wave equations (SNLW) with an additive space-time white noise forcing. In particular, we introduce a time-dependent renor- malization and prove that SNLW is pathwise locally well-posed. As an application of the local well-posedness argument, we also establish a weak u...
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Generation of High-Purity Millimeter-Wave Orbital Angular Momentum Modes Using Horn Antenna: Theory and Implementation
Twisted electromagnetic waves, of which the helical phase front is called orbital angular momentum (OAM), have been recently explored for quantum information, high speed communication and radar detections. In this context, generation of high purity waves carrying OAM is of great significance and challenge from low fr...
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CFT: A Cluster-based File Transfer Scheme for Highway
Effective file transfer between vehicles is fundamental to many emerging vehicular infotainment applications in the highway Vehicular Ad Hoc Networks (VANETs), such as content distribution and social networking. However, due to fast mobility, the connection between vehicles tends to be short-lived and lossy, which ma...
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Empirical priors and posterior concentration rates for a monotone density
In a Bayesian context, prior specification for inference on monotone densities is conceptually straightforward, but proving posterior convergence theorems is complicated by the fact that desirable prior concentration properties often are not satisfied. In this paper, I first develop a new prior designed specifically ...
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PeerReview4All: Fair and Accurate Reviewer Assignment in Peer Review
We consider the problem of automated assignment of papers to reviewers in conference peer review, with a focus on fairness and statistical accuracy. Our fairness objective is to maximize the review quality of the most disadvantaged paper, in contrast to the commonly used objective of maximizing the total quality over...
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CT Image Reconstruction in a Low Dimensional Manifold
Regularization methods are commonly used in X-ray CT image reconstruction. Different regularization methods reflect the characterization of different prior knowledge of images. In a recent work, a new regularization method called a low-dimensional manifold model (LDMM) is investigated to characterize the low-dimensio...
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Deep Unsupervised Clustering Using Mixture of Autoencoders
Unsupervised clustering is one of the most fundamental challenges in machine learning. A popular hypothesis is that data are generated from a union of low-dimensional nonlinear manifolds; thus an approach to clustering is identifying and separating these manifolds. In this paper, we present a novel approach to solve ...
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Enabling a Pepper Robot to provide Automated and Interactive Tours of a Robotics Laboratory
The Pepper robot has become a widely recognised face for the perceived potential of social robots to enter our homes and businesses. However, to date, commercial and research applications of the Pepper have been largely restricted to roles in which the robot is able to remain stationary. This restriction is the resul...
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The Ensemble Kalman Filter: A Signal Processing Perspective
The ensemble Kalman filter (EnKF) is a Monte Carlo based implementation of the Kalman filter (KF) for extremely high-dimensional, possibly nonlinear and non-Gaussian state estimation problems. Its ability to handle state dimensions in the order of millions has made the EnKF a popular algorithm in different geoscienti...
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Simultaneous Transmit and Receive Operation in Next Generation IEEE 802.11 WLANs: A MAC Protocol Design Approach
Full-duplex (FD) technology is likely to be adopted in various legacy communications standards. The IEEE 802.11ax working group has been considering a simultaneous transmit and receive (STR) mode for the next generation wireless local area networks (WLANs). Enabling STR mode (FD communication mode) in 802.11 networks...
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Transfer Learning-Based Crack Detection by Autonomous UAVs
Unmanned Aerial Vehicles (UAVs) have recently shown great performance collecting visual data through autonomous exploration and mapping in building inspection. Yet, the number of studies is limited considering the post processing of the data and its integration with autonomous UAVs. These will enable huge steps onwar...
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A Separation Between Run-Length SLPs and LZ77
In this paper we give an infinite family of strings for which the length of the Lempel-Ziv'77 parse is a factor $\Omega(\log n/\log\log n)$ smaller than the smallest run-length grammar.
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A Model that Predicts the Material Recognition Performance of Thermal Tactile Sensing
Tactile sensing can enable a robot to infer properties of its surroundings, such as the material of an object. Heat transfer based sensing can be used for material recognition due to differences in the thermal properties of materials. While data-driven methods have shown promise for this recognition problem, many fac...
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The Value of Inferring the Internal State of Traffic Participants for Autonomous Freeway Driving
Safe interaction with human drivers is one of the primary challenges for autonomous vehicles. In order to plan driving maneuvers effectively, the vehicle's control system must infer and predict how humans will behave based on their latent internal state (e.g., intentions and aggressiveness). This research uses a simp...
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Long range scattering for nonlinear Schrödinger equations with critical homogeneous nonlinearity in three space dimensions
In this paper, we consider the final state problem for the nonlinear Schrödinger equation with a homogeneous nonlinearity of the critical order which is not necessarily a polynomial. In [10], the first and the second authors consider one- and two-dimensional cases and gave a sufficient condition on the nonlinearity f...
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SegMap: 3D Segment Mapping using Data-Driven Descriptors
When performing localization and mapping, working at the level of structure can be advantageous in terms of robustness to environmental changes and differences in illumination. This paper presents SegMap: a map representation solution to the localization and mapping problem based on the extraction of segments in 3D p...
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The Hesse curve of a Lefschtz pencil of plane curves
We prove that for a generic Lefschetz pencil of plane curves of degree $d\geq 3$ there exists a curve $H$ (called the Hesse curve of the pencil) of degree $6(d-1)$ and genus $3(4d^2-13d+8)+1$, and such that: $(i)$ $H$ has $d^2$ singular points of multiplicity three at the base points of the pencil and $3(d-1)^2$ ordi...
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Markov State Models from short non-Equilibrium Simulations - Analysis and Correction of Estimation Bias
Many state of the art methods for the thermodynamic and kinetic characterization of large and complex biomolecular systems by simulation rely on ensemble approaches, where data from large numbers of relatively short trajectories are integrated. In this context, Markov state models (MSMs) are extremely popular because...
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Principal series for general linear groups over finite commutative rings
We construct, for any finite commutative ring $R$, a family of representations of the general linear group $\mathrm{GL}_n(R)$ whose intertwining properties mirror those of the principal series for $\mathrm{GL}_n$ over a finite field.
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Constraining Radon Backgrounds in LZ
The LZ dark matter detector, like many other rare-event searches, will suffer from backgrounds due to the radioactive decay of radon daughters. In order to achieve its science goals, the concentration of radon within the xenon should not exceed $2\mu$Bq/kg, or 20 mBq total within its 10 tonnes. The LZ collaboration i...
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Single-particle dispersion in stably stratified turbulence
We present models for single-particle dispersion in vertical and horizontal directions of stably stratified flows. The model in the vertical direction is based on the observed Lagrangian spectrum of the vertical velocity, while the model in the horizontal direction is a combination of a continuous-time eddy-constrain...
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Pili mediated intercellular forces shape heterogeneous bacterial microcolonies prior to multicellular differentiation
Microcolonies are aggregates of a few dozen to a few thousand cells exhibited by many bacteria. The formation of microcolonies is a crucial step towards the formation of more mature bacterial communities known as biofilms, but also marks a significant change in bacterial physiology. Within a microcolony, bacteria for...
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Accurate Inference for Adaptive Linear Models
Estimators computed from adaptively collected data do not behave like their non-adaptive brethren. Rather, the sequential dependence of the collection policy can lead to severe distributional biases that persist even in the infinite data limit. We develop a general method -- $\mathbf{W}$-decorrelation -- for transfor...
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Distribution on Warp Maps for Alignment of Open and Closed Curves
Alignment of curve data is an integral part of their statistical analysis, and can be achieved using model- or optimization-based approaches. The parameter space is usually the set of monotone, continuous warp maps of a domain. Infinite-dimensional nature of the parameter space encourages sampling based approaches, w...
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Unbiased and Consistent Nested Sampling via Sequential Monte Carlo
We introduce a new class of sequential Monte Carlo methods called Nested Sampling via Sequential Monte Carlo (NS-SMC), which reframes the Nested Sampling method of Skilling (2006) in terms of sequential Monte Carlo techniques. This new framework allows convergence results to be obtained in the setting when Markov cha...
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Cuntz semigroups of compact-type Hopf C*-algebras
The classical Cuntz semigroup has an important role in the study of C*-algebras, being one of the main invariants used to classify recalcitrant C*-algebras up to isomorphism. We consider C*-algebras that have Hopf algebra structure, and find additional structure in their Cuntz semigroups, thus generalizing the equiva...
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City-Scale Intelligent Systems and Platforms
As of 2014, 54% of the earth's population resides in urban areas, and it is steadily increasing, expecting to reach 66% by 2050. Urban areas range from small cities with tens of thousands of people to megacities with greater than 10 million people. Roughly 12% of the global population today lives in 28 megacities, an...
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A simulated comparison between profile and areal surface parameters: $R_a$ as an estimate of $S_a$
Direct comparison of areal and profile roughness measurement values is not advisable due to fundamental differences in the measurement techniques. However researchers may wish to compare between laboratories with differing equipment, or against literature values. This paper investigates how well the profile arithmeti...
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The VLA-COSMOS 3 GHz Large Project: Continuum data and source catalog release
We present the VLA-COSMOS 3 GHz Large Project based on 384 hours of observations with the Karl G. Jansky Very Large Array (VLA) at 3 GHz (10 cm) toward the two square degree Cosmic Evolution Survey (COSMOS) field. The final mosaic reaches a median rms of 2.3 uJy/beam over the two square degrees at an angular resoluti...
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DeepSource: Point Source Detection using Deep Learning
Point source detection at low signal-to-noise is challenging for astronomical surveys, particularly in radio interferometry images where the noise is correlated. Machine learning is a promising solution, allowing the development of algorithms tailored to specific telescope arrays and science cases. We present DeepSou...
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Co-design of aperiodic sampled-data min-jumping rules for linear impulsive, switched impulsive and sampled-data systems
Co-design conditions for the design of a jumping-rule and a sampled-data control law for impulsive and impulsive switched systems subject to aperiodic sampled-data measurements are provided. Semi-infinite discrete-time Lyapunov-Metzler conditions are first obtained. As these conditions are difficult to check and gene...
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Coalescence of Two Impurities in a Trapped One-dimensional Bose Gas
We study the ground state of a one-dimensional (1D) trapped Bose gas with two mobile impurity particles. To investigate this set-up, we develop a variational procedure in which the coordinates of the impurity particles are slow-like variables. We validate our method using the exact results obtained for small systems....
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Rust Distilled: An Expressive Tower of Languages
Rust represents a major advancement in production programming languages because of its success in bridging the gap between high-level application programming and low-level systems programming. At the heart of its design lies a novel approach to ownership that remains highly programmable. In this talk, we will describ...
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Game Theory for Multi-Access Edge Computing: Survey, Use Cases, and Future Trends
Game Theory (GT) has been used with significant success to formulate, and either design or optimize, the operation of many representative communications and networking scenarios. The games in these scenarios involve, as usual, diverse players with conflicting goals. This paper primarily surveys the literature that ha...
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General description of spin motion in storage rings in presence of oscillating horizontal fields
The general theoretical description of the influence of oscillating horizontal magnetic and quasimagnetic fields on the spin evolution in storage rings is presented. Previous results are generalized to the case when both of the horizontal components of the oscillating field are nonzero and the vector of this field ci...
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Simultaneous active parameter estimation and control using sampling-based Bayesian reinforcement learning
Robots performing manipulation tasks must operate under uncertainty about both their pose and the dynamics of the system. In order to remain robust to modeling error and shifts in payload dynamics, agents must simultaneously perform estimation and control tasks. However, the optimal estimation actions are often not t...
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An exploratory factor analysis model for slum severity index in Mexico City
In Mexico, 25 per cent of the urban population now lives in informal settlements with varying degree of depravity. Although some informal neighbourhoods have contributed to the upward mobility of the inhabitants, the majority still lack basic services. Mexico City and the conurbation around it, form a mega city of 21...
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An Estimate of the First Eigenvalue of a Schrödinger Operator on Closed Surfaces
Based on the work of Schoen-Yau, we derive an estimate of the first eigenvalue of a Schrödinger Operator (the Jaocbi operator of minimal surfaces in flat 3-spaces) on surfaces.
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Ease.ml: Towards Multi-tenant Resource Sharing for Machine Learning Workloads
We present ease.ml, a declarative machine learning service platform we built to support more than ten research groups outside the computer science departments at ETH Zurich for their machine learning needs. With ease.ml, a user defines the high-level schema of a machine learning application and submits the task via a...
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Computation on Encrypted Data using Data Flow Authentication
Encrypting data before sending it to the cloud protects it against hackers and malicious insiders, but requires the cloud to compute on encrypted data. Trusted (hardware) modules, e.g., secure enclaves like Intel's SGX, can very efficiently run entire programs in encrypted memory. However, it already has been demonst...
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Analytic and Numerical Analysis of Singular Cauchy integrals with exponential-type weights
Let $I=(c,d)$, $c < 0 < d$, $Q\in C^1: I\rightarrow[0,\infty)$ be a function with given regularity behavior on $I$. Write $w:=\exp(-Q)$ on $I$ and assume that $\int_I x^nw^2(x)dx<\infty$ for all $n=0,1,2,\ldots$. For $x\in I$, we consider the problem of the analytic and numerical approximation of the Cauchy principal...
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Observation of a new field-induced phase transition and its concomitant quantum critical fluctuations in CeCo(In$_{1-x}$Zn$_x$)$_5$
We demonstrate a close connection between observed field-induced antiferromagnetic (AFM) order and quantum critical fluctuation (QCF) in the Zn7%-doped heavy-fermion superconductor CeCoIn5. Magnetization, specific heat, and electrical resistivity at low temperatures all show the presence of new field-induced AFM orde...
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Two-dimensional magneto-optical trap as a source for cold strontium atoms
We report on the realization of a transversely loaded two-dimensional magneto-optical trap serving as a source for cold strontium atoms. We analyze the dependence of the source's properties on various parameters, in particular the intensity of a pushing beam accelerating the atoms out of the source. An atomic flux ex...
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Loading a linear Paul trap to saturation from a magneto-optical trap
We present experimental measurements of the steady-state ion number in a linear Paul trap (LPT) as a function of the ion-loading rate. These measurements, taken with (a) constant Paul trap stability parameter $q$, (b) constant radio-frequency (rf) amplitude, or (c) constant rf frequency, show nonlinear behavior. At t...
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Early warning signals in plant disease outbreaks
Summary 1. Infectious disease outbreaks in plants threaten ecosystems, agricultural crops and food trade. Currently, several fungal diseases are affecting forests worldwide, posing a major risk to tree species, habitats and consequently ecosystem decay. Prediction and control of disease spread are difficult, mainly d...
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Predicting the Gender of Indonesian Names
We investigated a way to predict the gender of a name using character-level Long-Short Term Memory (char-LSTM). We compared our method with some conventional machine learning methods, namely Naive Bayes, logistic regression, and XGBoost with n-grams as the features. We evaluated the models on a dataset consisting of ...
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Exploring Students Blended Learning Through Social Media
Information technology (IT) has been used widely in many aspects of our daily life. After discuss politics related aspects for some articles. In this article author would like to discuss social media for students learning environment. Social media as a leading application on the internet has changed many aspects of l...
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Thompson Sampling for a Fatigue-aware Online Recommendation System
In this paper we consider an online recommendation setting, where a platform recommends a sequence of items to its users at every time period. The users respond by selecting one of the items recommended or abandon the platform due to fatigue from seeing less useful items. Assuming a parametric stochastic model of use...
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Finding Large Primes
In this paper we present and expand upon procedures for obtaining large d digit prime number to an arbitrary probability. We use a layered approach. The first step is to limit the pool of random number to exclude numbers that are obviously composite. We first remove any number ending in 1,3,7 or 9. We then exclude nu...
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D-optimal Designs for Multinomial Logistic Models
We consider optimal designs for general multinomial logistic models, which cover baseline-category, cumulative, adjacent-categories, and continuation-ratio logit models, with proportional odds, non-proportional odds, or partial proportional odds assumption. We derive the corresponding Fisher information matrices in t...
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Rover Descent: Learning to optimize by learning to navigate on prototypical loss surfaces
Learning to optimize - the idea that we can learn from data algorithms that optimize a numerical criterion - has recently been at the heart of a growing number of research efforts. One of the most challenging issues within this approach is to learn a policy that is able to optimize over classes of functions that are ...
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Reordering of the Logistic Map with a Nonlinear Growth Rate
In the well known logistic map, the parameter of interest is weighted by a coefficient that decreases linearly when this parameter increases. Since such a linear decrease forms a specific case, we consider the more general case where this coefficient decreases nonlinearly as in a hyperbolic tangent relaxation of a sy...
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Tensor network factorizations: Relationships between brain structural connectomes and traits
Advanced brain imaging techniques make it possible to measure individuals' structural connectomes in large cohort studies non-invasively. The structural connectome is initially shaped by genetics and subsequently refined by the environment. It is extremely interesting to study relationships between structural connect...
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Model-free prediction of noisy chaotic time series by deep learning
We present a deep neural network for a model-free prediction of a chaotic dynamical system from noisy observations. The proposed deep learning model aims to predict the conditional probability distribution of a state variable. The Long Short-Term Memory network (LSTM) is employed to model the nonlinear dynamics and a...
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Robust XVA
We introduce an arbitrage-free framework for robust valuation adjustments. An investor trades a credit default swap portfolio with a risky counterparty, and hedges credit risk by taking a position in the counterparty bond. The investor does not know the expected rate of return of the counterparty bond, but he is conf...
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Rarefaction Waves for the Toda Equation via Nonlinear Steepest Descent
We apply the method of nonlinear steepest descent to compute the long-time asymptotics of the Toda lattice with steplike initial data corresponding to a rarefaction wave.
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IRA codes derived from Gruenbaum graph
In this paper, we consider coding of short data frames (192 bits) by IRA codes. A new interleaver for the IRA codes based on a Gruenbaum graph is proposed. The difference of the proposed algorithm from known methods consists in the following: permutation is performed by using a match smaller interleaver which is deri...
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Three- and four-electron integrals involving Gaussian geminals: fundamental integrals, upper bounds and recurrence relations
We report the three main ingredients to calculate three- and four-electron integrals over Gaussian basis functions involving Gaussian geminal operators: fundamental integrals, upper bounds, and recurrence relations. In particular, we consider the three- and four-electron integrals that may arise in explicitly-correla...
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HARP: Hierarchical Representation Learning for Networks
We present HARP, a novel method for learning low dimensional embeddings of a graph's nodes which preserves higher-order structural features. Our proposed method achieves this by compressing the input graph prior to embedding it, effectively avoiding troublesome embedding configurations (i.e. local minima) which can p...
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Mixed penalization in convolutive nonnegative matrix factorization for blind speech dereverberation
When a signal is recorded in an enclosed room, it typically gets affected by reverberation. This degradation represents a problem when dealing with audio signals, particularly in the field of speech signal processing, such as automatic speech recognition. Although there are some approaches to deal with this issue tha...
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Using Contour Trees in the Analysis and Visualization of Radio Astronomy Data Cubes
The current generation of radio and millimeter telescopes, particularly the Atacama Large Millimeter Array (ALMA), offers enormous advances in observing capabilities. While these advances represent an unprecedented opportunity to advance scientific understanding, the increased complexity in the spatial and spectral s...
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The Price of BitCoin: GARCH Evidence from High Frequency Data
This is the first paper that estimates the price determinants of BitCoin in a Generalised Autoregressive Conditional Heteroscedasticity framework using high frequency data. Derived from a theoretical model, we estimate BitCoin transaction demand and speculative demand equations in a GARCH framework using hourly data ...
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Application of a unified Kenmotsu-type formula for surfaces in Euclidean or Lorentzian three-space
Kenmotsu's formula describes surfaces in Euclidean 3-space by their mean curvature functions and Gauss maps. In Lorentzian 3-space, Akutagawa-Nishikawa's formula and Magid's formula are Kenmotsu-type formulas for spacelike surfaces and for timelike surfaces, respectively. We apply them to a few problems concerning ro...
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A Vector Matroid-Theoretic Approach in the Study of Structural Controllability Over F(z)
In this paper, the structural controllability of the systems over F(z) is studied using a new mathematical method-matroids. Firstly, a vector matroid is defined over F(z). Secondly, the full rank conditions of [sI-A|B] are derived in terms of the concept related to matroid theory, such as rank, base and union. Then t...
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From cold Fermi fluids to the hot QGP
Strongly coupled quantum fluids are found in different forms, including ultracold Fermi gases or tiny droplets of extremely hot Quark-Gluon Plasma. Although the systems differ in temperature by many orders of magnitude, they exhibit a similar almost inviscid fluid dynamical behavior. In this work, we summarize some o...
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Decomposition method related to saturated hyperball packings
In this paper we study the problem of hyperball (hypersphere) packings in $3$-dimensional hyperbolic space. We introduce a new definition of the non-compact saturated ball packings and describe to each saturated hyperball packing, a new procedure to get a decomposition of 3-dimensional hyperbolic space $\HYP$ into tr...
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Dynamic interdependence and competition in multilayer networks
From critical infrastructure, to physiology and the human brain, complex systems rarely occur in isolation. Instead, the functioning of nodes in one system often promotes or suppresses the functioning of nodes in another. Despite advances in structural interdependence, modeling interdependence and other interactions ...
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Applications of L systems to group theory
L systems generalise context-free grammars by incorporating parallel rewriting, and generate languages such as EDT0L and ET0L that are strictly contained in the class of indexed languages. In this paper we show that many of the languages naturally appearing in group theory, and that were known to be indexed or contex...
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'Senator, We Sell Ads': Analysis of the 2016 Russian Facebook Ads Campaign
One of the key aspects of the United States democracy is free and fair elections that allow for a peaceful transfer of power from one President to the next. The 2016 US presidential election stands out due to suspected foreign influence before, during, and after the election. A significant portion of that suspected i...
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On the k-Means/Median Cost Function
In this work, we study the $k$-means cost function. The (Euclidean) $k$-means problem can be described as follows: given a dataset $X \subseteq \mathbb{R}^d$ and a positive integer $k$, find a set of $k$ centers $C \subseteq \mathbb{R}^d$ such that $\Phi(C, X) \stackrel{def}{=} \sum_{x \in X} \min_{c \in C} ||x - c||...
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Secure and Reconfigurable Network Design for Critical Information Dissemination in the Internet of Battlefield Things (IoBT)
The Internet of things (IoT) is revolutionizing the management and control of automated systems leading to a paradigm shift in areas such as smart homes, smart cities, health care, transportation, etc. The IoT technology is also envisioned to play an important role in improving the effectiveness of military operation...
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