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null | inputs
dict | prediction
null | prediction_agent
null | annotation
list | annotation_agent
null | multi_label
bool 1
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{
"abstract": " In this work, we extend the solid harmonics derivation, which was used by\nAckroyd et al to derive the steady-state SP$_N$ equations, to transient\nproblems. The derivation expands the angular flux in ordinary surface harmonics\nbut uses harmonic polynomials to generate additional surface spherical harmonic\nterms to be used in Galerkin projection. The derivation shows the equivalence\nbetween the SP$_N$ and the P$_N$ approximation. Also, we use the line source\nproblem and McClarren's \"box\" problem to demonstrate such equivalence\nnumerically. Both problems were initially proposed for isotropic scattering,\nbut here we add higher-order scattering moments to them. Results show that the\ndifference between the SP$_N$ and P$_N$ scalar flux solution is at the roundoff\nlevel.\n",
"title": "Mathematical and numerical validation of the simplified spherical harmonics approach for time-dependent anisotropic-scattering transport problems in homogeneous media"
}
| null | null |
[
"Physics"
] | null | true | null |
5001
| null |
Validated
| null | null |
null |
{
"abstract": " L1-norm Principal-Component Analysis (L1-PCA) of real-valued data has\nattracted significant research interest over the past decade. However, L1-PCA\nof complex-valued data remains to date unexplored despite the many possible\napplications (e.g., in communication systems). In this work, we establish\ntheoretical and algorithmic foundations of L1-PCA of complex-valued data\nmatrices. Specifically, we first show that, in contrast to the real-valued case\nfor which an optimal polynomial-cost algorithm was recently reported by\nMarkopoulos et al., complex L1-PCA is formally NP-hard in the number of data\npoints. Then, casting complex L1-PCA as a unimodular optimization problem, we\npresent the first two suboptimal algorithms in the literature for its solution.\nOur experimental studies illustrate the sturdy resistance of complex L1-PCA\nagainst faulty measurements/outliers in the processed data.\n",
"title": "L1-norm Principal-Component Analysis of Complex Data"
}
| null | null | null | null | true | null |
5002
| null |
Default
| null | null |
null |
{
"abstract": " We consider dissipation of surface waves on fluids, with a view to its\neffects on analogue gravity experiments. We begin by reviewing some general\nproperties of wave dissipation, before restricting our attention to surface\nwaves and the dissipative role played by viscosity there. Finally, with\nparticular focus on water, we consider several experimental setups inspired by\nanalogue gravity: the analogue Hawking effect, the black hole laser, the\nanalogue wormhole, and double bouncing at the wormhole entrance. Dissipative\neffects are considered in each, and we give estimates for their optimized\nexperimental parameters.\n",
"title": "Viscous dissipation of surface waves and its relevance to analogue gravity experiments"
}
| null | null | null | null | true | null |
5003
| null |
Default
| null | null |
null |
{
"abstract": " We present an approach to automate the process of discovering optimization\nmethods, with a focus on deep learning architectures. We train a Recurrent\nNeural Network controller to generate a string in a domain specific language\nthat describes a mathematical update equation based on a list of primitive\nfunctions, such as the gradient, running average of the gradient, etc. The\ncontroller is trained with Reinforcement Learning to maximize the performance\nof a model after a few epochs. On CIFAR-10, our method discovers several update\nrules that are better than many commonly used optimizers, such as Adam,\nRMSProp, or SGD with and without Momentum on a ConvNet model. We introduce two\nnew optimizers, named PowerSign and AddSign, which we show transfer well and\nimprove training on a variety of different tasks and architectures, including\nImageNet classification and Google's neural machine translation system.\n",
"title": "Neural Optimizer Search with Reinforcement Learning"
}
| null | null | null | null | true | null |
5004
| null |
Default
| null | null |
null |
{
"abstract": " Parental gametes unite to form a zygote that develops into an adult with\ngonads that, in turn, produce gametes. Interruption of this germinal cycle by\nprezygotic or postzygotic reproductive barriers can result in two independent\ncycles, each with the potential to evolve into a new species. When the\nspeciation process is complete, members of each species are fully\nreproductively isolated from those of the other. During speciation a primary\nbarrier may be supported and eventually superceded by a later appearing\nsecondary barrier. For those holding certain cases of prezygotic isolation to\nbe primary (e.g. elephant cannot copulate with mouse), the onus is to show that\nthey had not been preceded over evolutionary time by periods of postzygotic\nhybrid inviability (genically determined) or sterility (genically or\nchromosomally determined). Likewise, the onus is upon those holding cases of\nhybrid inviability to be primary (e.g. Dobzhansky-Muller epistatic\nincompatibilities), to show that they had not been preceded by periods, however\nbrief, of hybrid sterility. The latter, when acting as a sympatric barrier\ncausing reproductive isolation, can only be primary. In many cases, hybrid\nsterility may result from incompatibilities between parental chromosomes that\nattempt to pair during meiosis in the gonad of their offspring\n(Winge-Crowther-Bateson incompatibilities). While WCB incompatibilities have\nlong been observed on a microscopic scale, there is growing evidence for a role\nof dispersed finer DNA sequence differences.\n",
"title": "Hybrid Sterility Can Only be Primary When Acting as a Reproductive Barrier for Sympatric Speciation,"
}
| null | null |
[
"Quantitative Biology"
] | null | true | null |
5005
| null |
Validated
| null | null |
null |
{
"abstract": " This work investigates the application of Unmanned Aerial Vehicle (UAV)\ntechnology for measurement of rock fragmentation without placement of scale\nobjects in the scene to determine image scale. Commonly practiced image-based\nrock fragmentation analysis requires a technician to walk to a rock pile, place\na scale object of known size in the area of interest, and capture individual 2D\nimages. Our previous work has used UAV technology for the first time to acquire\nreal-time rock fragmentation data and has shown comparable quality of results;\nhowever, it still required the (potentially dangerous) placement of scale\nobjects, and continued to make the assumption that the rock pile surface is\nplanar and that the scale objects lie on the surface plane. This work improves\nour UAV-based approach to enable rock fragmentation measurement without\nplacement of scale objects and without the assumption of planarity. This is\nachieved by first generating a point cloud of the rock pile from 2D images,\ntaking into account intrinsic and extrinsic camera parameters, and then taking\n2D images for fragmentation analysis. This work represents an important step\ntowards automating post-blast rock fragmentation analysis. In experiments, a\nrock pile with known size distribution was photographed by the UAV with and\nwithout using scale objects. For fragmentation analysis without scale objects,\na point cloud of the rock pile was generated and used to compute image scale.\nComparison of the rock size distributions show that this point-cloud-based\nmethod enables producing measurements with better or comparable accuracy\n(within 10% of the ground truth) to the manual method with scale objects.\n",
"title": "Point-Cloud-Based Aerial Fragmentation Analysis for Application in the Minerals Industry"
}
| null | null | null | null | true | null |
5006
| null |
Default
| null | null |
null |
{
"abstract": " We describe DyNet, a toolkit for implementing neural network models based on\ndynamic declaration of network structure. In the static declaration strategy\nthat is used in toolkits like Theano, CNTK, and TensorFlow, the user first\ndefines a computation graph (a symbolic representation of the computation), and\nthen examples are fed into an engine that executes this computation and\ncomputes its derivatives. In DyNet's dynamic declaration strategy, computation\ngraph construction is mostly transparent, being implicitly constructed by\nexecuting procedural code that computes the network outputs, and the user is\nfree to use different network structures for each input. Dynamic declaration\nthus facilitates the implementation of more complicated network architectures,\nand DyNet is specifically designed to allow users to implement their models in\na way that is idiomatic in their preferred programming language (C++ or\nPython). One challenge with dynamic declaration is that because the symbolic\ncomputation graph is defined anew for every training example, its construction\nmust have low overhead. To achieve this, DyNet has an optimized C++ backend and\nlightweight graph representation. Experiments show that DyNet's speeds are\nfaster than or comparable with static declaration toolkits, and significantly\nfaster than Chainer, another dynamic declaration toolkit. DyNet is released\nopen-source under the Apache 2.0 license and available at\nthis http URL.\n",
"title": "DyNet: The Dynamic Neural Network Toolkit"
}
| null | null | null | null | true | null |
5007
| null |
Default
| null | null |
null |
{
"abstract": " Team semantics is the mathematical framework of modern logics of dependence\nand independence in which formulae are interpreted by sets of assignments\n(teams) instead of single assignments as in first-order logic. In order to\ndeepen the fruitful interplay between team semantics and database dependency\ntheory, we define \"Polyteam Semantics\" in which formulae are evaluated over a\nfamily of teams. We begin by defining a novel polyteam variant of dependence\natoms and give a finite axiomatisation for the associated implication problem.\nWe also characterise the expressive power of poly-dependence logic by\nproperties of polyteams that are downward closed and definable in existential\nsecond-order logic (ESO). The analogous result is shown to hold for\npoly-independence logic and all ESO-definable properties.\n",
"title": "Polyteam Semantics"
}
| null | null | null | null | true | null |
5008
| null |
Default
| null | null |
null |
{
"abstract": " An intriguing property of deep neural networks is their inherent\nvulnerability to adversarial inputs, which significantly hinders their\napplication in security-critical domains. Most existing detection methods\nattempt to use carefully engineered patterns to distinguish adversarial inputs\nfrom their genuine counterparts, which however can often be circumvented by\nadaptive adversaries. In this work, we take a completely different route by\nleveraging the definition of adversarial inputs: while deceiving for deep\nneural networks, they are barely discernible for human visions. Building upon\nrecent advances in interpretable models, we construct a new detection framework\nthat contrasts an input's interpretation against its classification. We\nvalidate the efficacy of this framework through extensive experiments using\nbenchmark datasets and attacks. We believe that this work opens a new direction\nfor designing adversarial input detection methods.\n",
"title": "Where Classification Fails, Interpretation Rises"
}
| null | null | null | null | true | null |
5009
| null |
Default
| null | null |
null |
{
"abstract": " Latent Dirichlet Allocation (LDA) models trained without stopword removal\noften produce topics with high posterior probabilities on uninformative words,\nobscuring the underlying corpus content. Even when canonical stopwords are\nmanually removed, uninformative words common in that corpus will still dominate\nthe most probable words in a topic. In this work, we first show how the\nstandard topic quality measures of coherence and pointwise mutual information\nact counter-intuitively in the presence of common but irrelevant words, making\nit difficult to even quantitatively identify situations in which topics may be\ndominated by stopwords. We propose an additional topic quality metric that\ntargets the stopword problem, and show that it, unlike the standard measures,\ncorrectly correlates with human judgements of quality. We also propose a\nsimple-to-implement strategy for generating topics that are evaluated to be of\nmuch higher quality by both human assessment and our new metric. This approach,\na collection of informative priors easily introduced into most LDA-style\ninference methods, automatically promotes terms with domain relevance and\ndemotes domain-specific stop words. We demonstrate this approach's\neffectiveness in three very different domains: Department of Labor accident\nreports, online health forum posts, and NIPS abstracts. Overall we find that\ncurrent practices thought to solve this problem do not do so adequately, and\nthat our proposal offers a substantial improvement for those interested in\ninterpreting their topics as objects in their own right.\n",
"title": "Prior matters: simple and general methods for evaluating and improving topic quality in topic modeling"
}
| null | null | null | null | true | null |
5010
| null |
Default
| null | null |
null |
{
"abstract": " The issue of the buckling mechanism in droplets stabilized by solid particles\n(armored droplets) is tackled at a mesoscopic level using dissipative particle\ndynamics simulations. We consider spherical water droplet in a decane solvent\ncoated with nanoparticle monolayers of two different types: Janus and\nhomogeneous. The chosen particles yield comparable initial three-phase contact\nangles, chosen to maximize the adsorption energy at the interface. We study the\ninterplay between the evolution of droplet shape, layering of the particles,\nand their distribution at the interface when the volume of the droplets is\nreduced. We show that Janus particles affect strongly the shape of the droplet\nwith the formation of a crater-like depression. This evolution is actively\ncontrolled by a close-packed particle monolayer at the curved interface. On the\ncontrary, homogeneous particles follow passively the volume reduction of the\ndroplet, whose shape does not deviate too much from spherical, even when a\nnanoparticle monolayer/bilayer transition is detected at the interface. We\ndiscuss how these buckled armored droplets might be of relevance in various\napplications including potential drug delivery systems and biomimetic design of\nfunctional surfaces.\n",
"title": "Buckling in Armored Droplets"
}
| null | null | null | null | true | null |
5011
| null |
Default
| null | null |
null |
{
"abstract": " Let $X$ be a separable Banach function space on the unit circle $\\mathbb{T}$\nand $H[X]$ be the abstract Hardy space built upon $X$. We show that the set of\nanalytic polynomials is dense in $H[X]$ if the Hardy-Littlewood maximal\noperator is bounded on the associate space $X'$. This result is specified to\nthe case of variable Lebesgue spaces.\n",
"title": "Density of Analytic Polynomials in Abstract Hardy Spaces"
}
| null | null | null | null | true | null |
5012
| null |
Default
| null | null |
null |
{
"abstract": " This is a theoretical paper, which is a continuation of [arXiv:1710.10597],\nit considers the non-abelian Lie algebra $\\mathcal{G}$ of Lie groups for\n$\\left[ {{X}_{i}},{{X}_{j}} \\right]=c_{ij}^{k}{{X}_{k}}\\in \\mathcal{G}$ on the\nfoundation of the GCHS, where $c_{ij}^{k}\\in {{C}^{\\infty }}\\left( U,R \\right)$\nare the structure constants. The GPWB [arXiv:1710.10597] is nonlinear bracket\napplying to the non-Euclidean space, the second order (2,0) form antisymmetric\ncurvature tensor ${{F}_{ij}}=c_{ij}^{k}{{D}_{k}}$, and Qsu quantity\n${{q}_{i}}=w_{i}^{k}{{D}_{k}}$ are accordingly obtained by using the\nnon-abelian Lie bracket. The GCHS $\\left\\{ H,f \\right\\}\\in {{C}^{\\infty\n}}\\left( M,\\mathbb{R} \\right)$ holds for the non-symplectic vector field\n$X_{H}^{M}\\in \\mathcal{G}$ and $f\\in {{C}^{\\infty }}\\left( M,\\mathbb{R}\n\\right)$ that implies the covariant evolution equation consists of two parts,\nNGHS and W dynamics along with the second order invariant operator\n$\\frac{{\\mathcal{D}^{2}}}{d{{t}^{2}}}=\\frac{{{d}^{2}}}{d{{t}^{2}}}+2w\\frac{d}{dt}+\\beta$.\n",
"title": "On non-Abelian Lie Bracket of Generalized Covariant Hamilton Systems"
}
| null | null | null | null | true | null |
5013
| null |
Default
| null | null |
null |
{
"abstract": " Topological models of empirical and formal inquiry are increasingly\nprevalent. They have emerged in such diverse fields as domain theory [1, 16],\nformal learning theory [18], epistemology and philosophy of science [10, 15, 8,\n9, 2], statistics [6, 7] and modal logic [17, 4]. In those applications, open\nsets are typically interpreted as hypotheses deductively verifiable by true\npropositional information that rules out relevant possibilities. However, in\nstatistical data analysis, one routinely receives random samples logically\ncompatible with every statistical hypothesis. We bridge the gap between\npropositional and statistical data by solving for the unique topology on\nprobability measures in which the open sets are exactly the statistically\nverifiable hypotheses. Furthermore, we extend that result to a topological\ncharacterization of learnability in the limit from statistical data.\n",
"title": "The Topology of Statistical Verifiability"
}
| null | null | null | null | true | null |
5014
| null |
Default
| null | null |
null |
{
"abstract": " Given a closed Riemannian manifold and a pair of multi-curves in it, we give\na formula relating the linking number of the later to the spectral theory of\nthe Laplace operator acting on differential one forms. As an application, we\ncompute the linking number of any two multi-geodesics of the flat torus of\ndimension 3, generalising a result of P. Dehornoy.\n",
"title": "A spectral approach to the linking number in the 3-torus"
}
| null | null | null | null | true | null |
5015
| null |
Default
| null | null |
null |
{
"abstract": " We show that a smooth interface between two insulators of opposite\ntopological Z2 indices possesses multiple surface states, both massless and\nmassive. While the massless surface state is non-degenerate, chiral and\ninsensitive to the interface potential, the massive surface states only appear\nfor a sufficiently smooth heterojunction. The surface states are particle-hole\nsymmetric and a voltage drop reveals their intrinsic relativistic nature,\nsimilarly to Landau bands of Dirac electrons in a magnetic field. We discuss\nthe relevance of the massive Dirac surface states in recent ARPES and transport\nexperiments.\n",
"title": "Volkov-Pankratov states in topological heterojunctions"
}
| null | null | null | null | true | null |
5016
| null |
Default
| null | null |
null |
{
"abstract": " The focus of this work is on estimation of the in-degree distribution in\ndirected networks from sampling network nodes or edges. A number of sampling\nschemes are considered, including random sampling with and without replacement,\nand several approaches based on random walks with possible jumps. When sampling\nnodes, it is assumed that only the out-edges of that node are visible, that is,\nthe in-degree of that node is not observed. The suggested estimation of the\nin-degree distribution is based on two approaches. The inversion approach\nexploits the relation between the original and sample in-degree distributions,\nand can estimate the bulk of the in-degree distribution, but not the tail of\nthe distribution. The tail of the in-degree distribution is estimated through\nan asymptotic approach, which itself has two versions: one assuming a power-law\ntail and the other for a tail of general form. The two estimation approaches\nare examined on synthetic and real networks, with good performance results,\nespecially striking for the asymptotic approach.\n",
"title": "Sampling-based Estimation of In-degree Distribution with Applications to Directed Complex Networks"
}
| null | null | null | null | true | null |
5017
| null |
Default
| null | null |
null |
{
"abstract": " We report on the SuperKEKB Phase I operations of the Large Angle\nBeamstrhalung Monitor (LABM). The detector is described and its performance\ncharacterized using the synchrotron radiation backgrounds from the last Beam\nLine magnets. The backgrounds are also used to determine the expected position\nof the Interaction Point (IP), and the expected background rates during Phase\nII.\n",
"title": "Phase I results with the Large Angle Beamstrahlung Monitor (LABM) with SuperKEKB beams"
}
| null | null | null | null | true | null |
5018
| null |
Default
| null | null |
null |
{
"abstract": " We study the effect of contingent movement on the persistence of cooperation\non complex networks with empty nodes. Each agent plays Prisoner's Dilemma game\nwith its neighbors and then it either updates the strategy depending on the\npayoff difference with neighbors or it moves to another empty node if not\nsatisfied with its own payoff. If no neighboring node is empty, each agent\nstays at the same site. By extensive evolutionary simulations, we show that the\nmedium density of agents enhances cooperation where the network flow of mobile\nagents is also medium. Moreover, if the movements of agents are more frequent\nthan the strategy updating, cooperation is further promoted. In scale-free\nnetworks, the optimal density for cooperation is lower than other networks\nbecause agents get stuck at hubs. Our study suggests that keeping a smooth\nnetwork flow is significant for the persistence of cooperation in ever-changing\nsocieties.\n",
"title": "Network flow of mobile agents enhances the evolution of cooperation"
}
| null | null |
[
"Quantitative Biology"
] | null | true | null |
5019
| null |
Validated
| null | null |
null |
{
"abstract": " Traditional face editing methods often require a number of sophisticated and\ntask specific algorithms to be applied one after the other --- a process that\nis tedious, fragile, and computationally intensive. In this paper, we propose\nan end-to-end generative adversarial network that infers a face-specific\ndisentangled representation of intrinsic face properties, including shape (i.e.\nnormals), albedo, and lighting, and an alpha matte. We show that this network\ncan be trained on \"in-the-wild\" images by incorporating an in-network\nphysically-based image formation module and appropriate loss functions. Our\ndisentangling latent representation allows for semantically relevant edits,\nwhere one aspect of facial appearance can be manipulated while keeping\northogonal properties fixed, and we demonstrate its use for a number of facial\nediting applications.\n",
"title": "Neural Face Editing with Intrinsic Image Disentangling"
}
| null | null | null | null | true | null |
5020
| null |
Default
| null | null |
null |
{
"abstract": " The technique of non-redundant masking (NRM) transforms a conventional\ntelescope into an interferometric array. In practice, this provides a much\nbetter constrained point spread function than a filled aperture and thus higher\nresolution than traditional imaging methods. Here we describe an NRM data\nreduction pipeline. We discuss strategies for NRM observations regarding\ndithering patterns and calibrator selection. We describe relevant image\ncalibrations and use example Large Binocular Telescope datasets to show their\neffects on the scatter in the Fourier measurements. We also describe the\nvarious ways to calculate Fourier quantities, and discuss different calibration\nstrategies. We present the results of image reconstructions from simulated\nobservations where we adjust prior images, weighting schemes, and error bar\nestimation. We compare two imaging algorithms and discuss implications for\nreconstructing images from real observations. Finally, we explore how the\ncurrent state of the art compares to next generation Extremely Large\nTelescopes.\n",
"title": "Data Reduction and Image Reconstruction Techniques for Non-Redundant Masking"
}
| null | null | null | null | true | null |
5021
| null |
Default
| null | null |
null |
{
"abstract": " We consider a gated one-dimensional (1D) quantum wire disturbed in a\ncontactless manner by an alternating electric field produced by a tip of a\nscanning probe microscope. In this schematic 1D electrons are driven not by a\npulling electric field but rather by a non-stationary spin-orbit interaction\n(SOI) created by the tip. We show that a charge current appears in the wire in\nthe presence of the Rashba SOI produced by the gate net charge and image\ncharges of 1D electrons induced on the gate (iSOI). The iSOI contributes to the\ncharge susceptibility by breaking the spin-charge separation between the\ncharge- and spin collective excitations, generated by the probe. The velocity\nof the excitations is strongly renormalized by SOI, which opens a way to\nfine-tune the charge and spin response of 1D electrons by changing the gate\npotential. One of the modes softens upon increasing the gate potential to\nenhance the current response as well as the power dissipated in the system.\n",
"title": "Dynamic transport in a quantum wire driven by spin-orbit interaction"
}
| null | null |
[
"Physics"
] | null | true | null |
5022
| null |
Validated
| null | null |
null |
{
"abstract": " In many problems of supervised tensor learning (STL), real world data such as\nface images or MRI scans are naturally represented as matrices, which are also\ncalled as second order tensors. Most existing classifiers based on tensor\nrepresentation, such as support tensor machine (STM) need to solve iteratively\nwhich occupy much time and may suffer from local minima. In this paper, we\npresent a kernel support matrix machine (KSMM) to perform supervised learning\nwhen data are represented as matrices. KSMM is a general framework for the\nconstruction of matrix-based hyperplane to exploit structural information. We\nanalyze a unifying optimization problem for which we propose an asymptotically\nconvergent algorithm. Theoretical analysis for the generalization bounds is\nderived based on Rademacher complexity with respect to a probability\ndistribution. We demonstrate the merits of the proposed method by exhaustive\nexperiments on both simulation study and a number of real-word datasets from a\nvariety of application domains.\n",
"title": "A Nonlinear Kernel Support Matrix Machine for Matrix Learning"
}
| null | null |
[
"Computer Science",
"Statistics"
] | null | true | null |
5023
| null |
Validated
| null | null |
null |
{
"abstract": " We introduce NoisyNet, a deep reinforcement learning agent with parametric\nnoise added to its weights, and show that the induced stochasticity of the\nagent's policy can be used to aid efficient exploration. The parameters of the\nnoise are learned with gradient descent along with the remaining network\nweights. NoisyNet is straightforward to implement and adds little computational\noverhead. We find that replacing the conventional exploration heuristics for\nA3C, DQN and dueling agents (entropy reward and $\\epsilon$-greedy respectively)\nwith NoisyNet yields substantially higher scores for a wide range of Atari\ngames, in some cases advancing the agent from sub to super-human performance.\n",
"title": "Noisy Networks for Exploration"
}
| null | null | null | null | true | null |
5024
| null |
Default
| null | null |
null |
{
"abstract": " The Rate Control Protocol (RCP) is a congestion control protocol that relies\non explicit feedback from routers. RCP estimates the flow rate using two forms\nof feedback: rate mismatch and queue size. However, it remains an open design\nquestion whether queue size feedback in RCP is useful, given the presence of\nrate mismatch. The model we consider has RCP flows operating over a single\nbottleneck, with heterogeneous time delays. We first derive a sufficient\ncondition for global stability, and then highlight how this condition favors\nthe design choice of having only rate mismatch in the protocol definition.\n",
"title": "Global stability of the Rate Control Protocol (RCP) and some implications for protocol design"
}
| null | null | null | null | true | null |
5025
| null |
Default
| null | null |
null |
{
"abstract": " With the demand of high data rate and low latency in fifth generation (5G),\ndeep neural network decoder (NND) has become a promising candidate due to its\ncapability of one-shot decoding and parallel computing. In this paper, three\ntypes of NND, i.e., multi-layer perceptron (MLP), convolution neural network\n(CNN) and recurrent neural network (RNN), are proposed with the same parameter\nmagnitude. The performance of these deep neural networks are evaluated through\nextensive simulation. Numerical results show that RNN has the best decoding\nperformance, yet at the price of the highest computational overhead. Moreover,\nwe find there exists a saturation length for each type of neural network, which\nis caused by their restricted learning abilities.\n",
"title": "Performance Evaluation of Channel Decoding With Deep Neural Networks"
}
| null | null | null | null | true | null |
5026
| null |
Default
| null | null |
null |
{
"abstract": " We study two-player games with counters, where the objective of the first\nplayer is that the counter values remain bounded. We investigate the existence\nof a trade-off between the size of the memory and the bound achieved on the\ncounters, which has been conjectured by Colcombet and Loeding.\nWe show that unfortunately this conjecture does not hold: there is no\ntrade-off between bounds and memory, even for finite arenas. On the positive\nside, we prove the existence of a trade-off for the special case of thin tree\narenas. This allows to extend the theory of regular cost functions over thin\ntrees, and obtain as a corollary the decidability of cost monadic second-order\nlogic over thin trees.\n",
"title": "Trading Bounds for Memory in Games with Counters"
}
| null | null | null | null | true | null |
5027
| null |
Default
| null | null |
null |
{
"abstract": " Using Lagrangian Floer theory, we study the tropical geometry of K3 surfaces\nwith general singular fibres. In particular, we give the local models for the\ntype $I_n$, $II$, $III$ and $IV$ singular fibres in the Kodaira's\nclassification and generalize the correspondence theorem between open\nGromov-Witten invariants/tropical discs counting to these cases.\n",
"title": "On the Tropical Discs Counting on Elliptic K3 Surfaces with General Singular Fibres"
}
| null | null | null | null | true | null |
5028
| null |
Default
| null | null |
null |
{
"abstract": " The greatest integer that does not belong to a numerical semigroup $S$ is\ncalled the Frobenius number of $S$ and finding the Frobenius number is called\nthe Frobenius problem. In this paper, we introduce the Frobenius problem for\nnumerical semigroups generated by Thabit number base b and Thabit number of the\nsecond kind base b which are motivated by the Frobenius problem for Thabit\nnumerical semigroups. Also, we introduce the Frobenius problem for numerical\nsemigroups generated by Cunningham number and Fermat number base $b$\n",
"title": "The Frobenius problem for four numerical semigroups"
}
| null | null | null | null | true | null |
5029
| null |
Default
| null | null |
null |
{
"abstract": " We show that the coherence between different bacteriochlorophyll-a (BChla)\nsites in the Fenna-Mathews-Olson complex is an essential ingredient for\nexcitation energy transfer between various sites. The coherence delocalizes the\nexcitation energy, which results in the redistribution of excitation among all\nthe BChla sites in the steady state. We further show that the system remains\npartially coherent at the steady state. In our numerical simulation of the\nnon-Markovian density matrix equation, we consider both the inhomogeneity of\nthe protein environment and the effect of active vibronic modes.\n",
"title": "Coherence and its Role in Excitation Energy Transfer in Fenna-Mathews-Olson Complex"
}
| null | null | null | null | true | null |
5030
| null |
Default
| null | null |
null |
{
"abstract": " To maximize offloading gain of cache-enabled device-to-device (D2D)\ncommunications, content placement and delivery should be jointly designed. In\nthis letter, we jointly optimize caching and scheduling policies to maximize\nsuccessful offloading probability, defined as the probability that a user can\nobtain desired file in local cache or via D2D link with data rate larger than a\ngiven threshold. We obtain the optimal scheduling factor for a random\nscheduling policy that can control interference in a distributed manner, and a\nlow complexity solution to compute caching distribution. We show that the\noffloading gain can be remarkably improved by the joint optimization.\n",
"title": "Optimal Caching and Scheduling for Cache-enabled D2D Communications"
}
| null | null |
[
"Computer Science"
] | null | true | null |
5031
| null |
Validated
| null | null |
null |
{
"abstract": " Many interesting natural phenomena are sparsely distributed and discrete.\nLocating the hotspots of such sparsely distributed phenomena is often difficult\nbecause their density gradient is likely to be very noisy. We present a novel\napproach to this search problem, where we model the co-occurrence relations\nbetween a robot's observations with a Bayesian nonparametric topic model. This\napproach makes it possible to produce a robust estimate of the spatial\ndistribution of the target, even in the absence of direct target observations.\nWe apply the proposed approach to the problem of finding the spatial locations\nof the hotspots of a specific phytoplankton taxon in the ocean. We use\nclassified image data from Imaging FlowCytobot (IFCB), which automatically\nmeasures individual microscopic cells and colonies of cells. Given these\nindividual taxon-specific observations, we learn a phytoplankton community\nmodel that characterizes the co-occurrence relations between taxa. We present\nexperiments with simulated robot missions drawn from real observation data\ncollected during a research cruise traversing the US Atlantic coast. Our\nresults show that the proposed approach outperforms nearest neighbor and\nk-means based methods for predicting the spatial distribution of hotspots from\nin-situ observations.\n",
"title": "Phytoplankton Hotspot Prediction With an Unsupervised Spatial Community Model"
}
| null | null | null | null | true | null |
5032
| null |
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| null | null |
null |
{
"abstract": " In this paper we further develop the fluctuating hydrodynamics proposed in\narXiv:1511.03646 in a number of ways. We first work out in detail the classical\nlimit of the hydrodynamical action, which exhibits many simplifications. In\nparticular, this enables a transparent formulation of the action in physical\nspacetime in the presence of arbitrary external fields. It also helps to\nclarify issues related to field redefinitions and frame choices. We then\npropose that the action is invariant under a $Z_2$ symmetry to which we refer\nas the dynamical KMS symmetry. The dynamical KMS symmetry is physically\nequivalent to the previously proposed local KMS condition in the classical\nlimit, but is more convenient to implement and more general. It is applicable\nto any states in local equilibrium rather than just thermal density matrix\nperturbed by external background fields. Finally we elaborate the formulation\nfor a conformal fluid, which contains some new features, and work out the\nexplicit form of the entropy current to second order in derivatives for a\nneutral conformal fluid.\n",
"title": "Effective field theory for dissipative fluids (II): classical limit, dynamical KMS symmetry and entropy current"
}
| null | null | null | null | true | null |
5033
| null |
Default
| null | null |
null |
{
"abstract": " In Quantum Non Demolition measurements, the sequence of observations is\ndistributed as a mixture of multinomial random variables. Parameters of the\ndynamics are naturally encoded into this family of distributions. We show the\nlocal asymptotic mixed normality of the underlying statistical model and the\nconsistency of the maximum likelihood estimator. Furthermore, we prove the\nasymptotic optimality of this estimator as it saturates the usual Cramér Rao\nbound.\n",
"title": "Quantum non demolition measurements: parameter estimation for mixtures of multinomials"
}
| null | null | null | null | true | null |
5034
| null |
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| null | null |
null |
{
"abstract": " The majority of NLG evaluation relies on automatic metrics, such as BLEU . In\nthis paper, we motivate the need for novel, system- and data-independent\nautomatic evaluation methods: We investigate a wide range of metrics, including\nstate-of-the-art word-based and novel grammar-based ones, and demonstrate that\nthey only weakly reflect human judgements of system outputs as generated by\ndata-driven, end-to-end NLG. We also show that metric performance is data- and\nsystem-specific. Nevertheless, our results also suggest that automatic metrics\nperform reliably at system-level and can support system development by finding\ncases where a system performs poorly.\n",
"title": "Why We Need New Evaluation Metrics for NLG"
}
| null | null |
[
"Computer Science"
] | null | true | null |
5035
| null |
Validated
| null | null |
null |
{
"abstract": " We present constraints on the masses of extremely light bosons dubbed fuzzy\ndark matter from Lyman-$\\alpha$ forest data. Extremely light bosons with a De\nBroglie wavelength of $\\sim 1$ kpc have been suggested as dark matter\ncandidates that may resolve some of the current small scale problems of the\ncold dark matter model. For the first time we use hydrodynamical simulations to\nmodel the Lyman-$\\alpha$ flux power spectrum in these models and compare with\nthe observed flux power spectrum from two different data sets: the XQ-100 and\nHIRES/MIKE quasar spectra samples. After marginalization over nuisance and\nphysical parameters and with conservative assumptions for the thermal history\nof the IGM that allow for jumps in the temperature of up to $5000\\rm\\,K$,\nXQ-100 provides a lower limit of 7.1$\\times 10^{-22}$ eV, HIRES/MIKE returns a\nstronger limit of 14.3$\\times 10^{-22}$ eV, while the combination of both data\nsets results in a limit of 20 $\\times 10^{-22}$ eV (2$\\sigma$ C.L.). The limits\nfor the analysis of the combined data sets increases to 37.5$\\times 10^{-22}$\neV (2$\\sigma$ C.L.) when a smoother thermal history is assumed where the\ntemperature of the IGM evolves as a power-law in redshift. Light boson masses\nin the range $1-10 \\times10^{-22}$ eV are ruled out at high significance by our\nanalysis, casting strong doubts that FDM helps solve the \"small scale crisis\"\nof the cold dark matter models.\n",
"title": "First constraints on fuzzy dark matter from Lyman-$α$ forest data and hydrodynamical simulations"
}
| null | null | null | null | true | null |
5036
| null |
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| null | null |
null |
{
"abstract": " In this paper we study optimal estimates for two functionals involving the\nanisotropic $p$-torsional rigidity $T_p(\\Omega)$, $1<p<+\\infty$. More\nprecisely, we study $\\Phi(\\Omega)=\\frac{T_p(\\Omega)}{|\\Omega|M(\\Omega)}$ and\n$\\Psi(\\Omega)=\\frac{T_p(\\Omega)}{|\\Omega|[R_{F}(\\Omega)]^{\\frac{p}{p-1}}}$,\nwhere $M(\\Omega)$ is the maximum of the torsion function $u_{\\Omega}$ and\n$R_F(\\Omega)$ is the anisotropic inradius of $\\Omega$.\n",
"title": "On functionals involving the torsional rigidity related to some classes of nonlinear operators"
}
| null | null | null | null | true | null |
5037
| null |
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| null | null |
null |
{
"abstract": " We examine the kinematics of the gas in the environments of galaxies hosting\nquasars at $z\\sim2$. We employ 148 projected quasar pairs to study the\ncircumgalactic gas of the foreground quasars in absorption. The sample selects\nforeground quasars with precise redshift measurements, using emission-lines\nwith precision $\\lesssim300\\,{\\rm km\\,s^{-1}}$ and average offsets from the\nsystemic redshift $\\lesssim|100\\,{\\rm km\\,s^{-1}}|$. We stack the background\nquasar spectra at the foreground quasar's systemic redshift to study the mean\nabsorption in \\ion{C}{2}, \\ion{C}{4}, and \\ion{Mg}{2}. We find that the mean\nabsorptions exhibit large velocity widths $\\sigma_v\\approx300\\,{\\rm\nkm\\,s^{-1}}$. Further, the mean absorptions appear to be asymmetric about the\nsystemic redshifts. The mean absorption centroids exhibit small redshift\nrelative to the systemic $\\delta v\\approx+200\\,{\\rm km\\,s^{-1}}$, with large\nintrinsic scatter in the centroid velocities of the individual absorption\nsystems. We find the observed widths are consistent with gas in gravitational\nmotion and Hubble flow. However, while the observation of large widths alone\ndoes not require galactic-scale outflows, the observed offsets suggest that the\ngas is on average outflowing from the galaxy. The observed offsets also suggest\nthat the ionizing radiation from the foreground quasars is anisotropic and/or\nintermittent.\n",
"title": "Quasars Probing Quasars IX. The Kinematics of the Circumgalactic Medium Surrounding z ~ 2 Quasars"
}
| null | null | null | null | true | null |
5038
| null |
Default
| null | null |
null |
{
"abstract": " The computer-aided analysis of medical scans is a longstanding goal in the\nmedical imaging field. Currently, deep learning has became a dominant\nmethodology for supporting pathologists and radiologist. Deep learning\nalgorithms have been successfully applied to digital pathology and radiology,\nnevertheless, there are still practical issues that prevent these tools to be\nwidely used in practice. The main obstacles are low number of available cases\nand large size of images (a.k.a. the small n, large p problem in machine\nlearning), and a very limited access to annotation at a pixel level that can\nlead to severe overfitting and large computational requirements. We propose to\nhandle these issues by introducing a framework that processes a medical image\nas a collection of small patches using a single, shared neural network. The\nfinal diagnosis is provided by combining scores of individual patches using a\npermutation-invariant operator (combination). In machine learning community\nsuch approach is called a multi-instance learning (MIL).\n",
"title": "Deep Learning with Permutation-invariant Operator for Multi-instance Histopathology Classification"
}
| null | null | null | null | true | null |
5039
| null |
Default
| null | null |
null |
{
"abstract": " Inspired by Katok's examples of Finsler metrics with a small number of closed\ngeodesics, we present two results on Reeb flows with finitely many periodic\norbits. The first result is concerned with a contact-geometric description of\nmagnetic flows on the 2-sphere found recently by Benedetti. We give a simple\ninterpretation of that work in terms of a quaternionic symmetry. In the second\npart, we use Hamiltonian circle actions on symplectic manifolds to produce\ncompact, connected contact manifolds in dimension at least five with\narbitrarily large numbers of periodic Reeb orbits. This contrasts sharply with\nrecent work by Cristofaro-Gardiner, Hutchings and Pomerleano on Reeb flows in\ndimension three. With the help of Hamiltonian plugs and a surgery construction\ndue to Laudenbach we reprove a result of Cieliebak: one can produce Hamiltonian\nflows in dimension at least five with any number of periodic orbits; in\ndimension three, with any number greater than one.\n",
"title": "Reeb dynamics inspired by Katok's example in Finsler geometry"
}
| null | null | null | null | true | null |
5040
| null |
Default
| null | null |
null |
{
"abstract": " The crystal structure, magnetic ordering, and electrical resistivity of\nTlFe1.6Se2 were studied at high pressures. Below ~7 GPa, TlFe1.6Se2 is an\nantiferromagnetically ordered semiconductor with a ThCr2Si2-type structure. The\ninsulator-to-metal transformation observed at a pressure of ~ 7 GPa is\naccompanied by a loss of magnetic ordering and an isostructural phase\ntransition. In the pressure range ~ 7.5 - 11 GPa a remarkable downturn in\nresistivity, which resembles a superconducting transition, is observed below 15\nK. We discuss this feature as the possible onset of superconductivity\noriginating from a phase separation in a small fraction of the sample in the\nvicinity of the magnetic transition.\n",
"title": "Pressure-induced magnetic collapse and metallization of $\\mathrm{TlF}{\\mathrm{e}}_{1.6}\\mathrm{S}{\\mathrm{e}}_{2}$"
}
| null | null | null | null | true | null |
5041
| null |
Default
| null | null |
null |
{
"abstract": " We present a machine learning-based approach to lossy image compression which\noutperforms all existing codecs, while running in real-time.\nOur algorithm typically produces files 2.5 times smaller than JPEG and JPEG\n2000, 2 times smaller than WebP, and 1.7 times smaller than BPG on datasets of\ngeneric images across all quality levels. At the same time, our codec is\ndesigned to be lightweight and deployable: for example, it can encode or decode\nthe Kodak dataset in around 10ms per image on GPU.\nOur architecture is an autoencoder featuring pyramidal analysis, an adaptive\ncoding module, and regularization of the expected codelength. We also\nsupplement our approach with adversarial training specialized towards use in a\ncompression setting: this enables us to produce visually pleasing\nreconstructions for very low bitrates.\n",
"title": "Real-Time Adaptive Image Compression"
}
| null | null | null | null | true | null |
5042
| null |
Default
| null | null |
null |
{
"abstract": " In the context of dynamic emission tomography, the conventional processing\npipeline consists of independent image reconstruction of single time frames,\nfollowed by the application of a suitable kinetic model to time activity curves\n(TACs) at the voxel or region-of-interest level. The relatively new field of 4D\nPET direct reconstruction, by contrast, seeks to move beyond this scheme and\nincorporate information from multiple time frames within the reconstruction\ntask. Existing 4D direct models are based on a deterministic description of\nvoxels' TACs, captured by the chosen kinetic model, considering the photon\ncounting process the only source of uncertainty. In this work, we introduce a\nnew probabilistic modeling strategy based on the key assumption that activity\ntime course would be subject to uncertainty even if the parameters of the\nunderlying dynamic process were known. This leads to a hierarchical Bayesian\nmodel, which we formulate using the formalism of Probabilistic Graphical\nModeling (PGM). The inference of the joint probability density function arising\nfrom PGM is addressed using a new gradient-based iterative algorithm, which\npresents several advantages compared to existing direct methods: it is flexible\nto an arbitrary choice of linear and nonlinear kinetic model; it enables the\ninclusion of arbitrary (sub)differentiable priors for parametric maps; it is\nsimpler to implement and suitable to integration in computing frameworks for\nmachine learning. Computer simulations and an application to real patient scan\nshowed how the proposed approach allows us to weight the importance of the\nkinetic model, providing a bridge between indirect and deterministic direct\nmethods.\n",
"title": "Probabilistic Graphical Modeling approach to dynamic PET direct parametric map estimation and image reconstruction"
}
| null | null |
[
"Statistics"
] | null | true | null |
5043
| null |
Validated
| null | null |
null |
{
"abstract": " We investigate perturbative thermodynamic geometry of nonextensive ideal\nClassical, Bose and Fermi gases.We show that the intrinsic statistical\ninteraction of nonextensive Bose (Fermi) gas is attractive (repulsive) similar\nto the extensive case but the value of thermodynamic curvature is changed by\nnonextensive parameter. In contrary to the extensive ideal classical gas, the\nnonextensive one may be divided to two different regimes. According to\ndeviation parameter of the system to the nonextensive case, one can find a\nspecial value of fugacity, $z^{*}$, where the sign of thermodynamic curvature\nis changed. Therefore, we argue that the nonextensive parameter induces an\nattractive (repulsive) statistical interaction for $z<z^{*}$ ($z>z^{*}$) for an\nideal classical gas. Also, according to the singular point of thermodynamic\ncurvature, we consider the condensation of nonextensive Boson gas.\n",
"title": "Perturbative Thermodynamic Geometry of Nonextensive Ideal Classical, Bose and Fermi Gases"
}
| null | null | null | null | true | null |
5044
| null |
Default
| null | null |
null |
{
"abstract": " We offer two new Mellin transform evaluations for the Riemann zeta function\nin the region $0<\\Re(s)<1.$ Some discussion is offered in the way of evaluating\nsome further Fourier integrals involving the Riemann xi function.\n",
"title": "On some mellin transforms for the Riemann zeta function in the critical strip"
}
| null | null |
[
"Mathematics"
] | null | true | null |
5045
| null |
Validated
| null | null |
null |
{
"abstract": " Given a constant vector field $Z$ in Minkowski space, a timelike surface is\nsaid to have a canonical null direction with respect to $Z$ if the projection\nof $Z$ on the tangent space of the surface gives a lightlike vector field. In\nthis paper we describe these surfaces in the ruled case. For example when the\nMinkowski space has three dimensions then a surface with a canonical null\ndirection is minimal and flat. On the other hand, we describe several\nproperties in the non ruled case and we partially describe these surfaces in\nfour-dimensional Minkowski space. We give different ways for building these\nsurfaces in four-dimensional Minkowski space and we finally use the Gauss map\nfor describe another properties of these surfaces.\n",
"title": "Timelike surfaces in Minkowski space with a canonical null direction"
}
| null | null | null | null | true | null |
5046
| null |
Default
| null | null |
null |
{
"abstract": " In this paper, a class of neutral type competitive neural networks with mixed\ntime-varying delays and leakage delays on time scales is proposed. Based on the\nexponential dichotomy of linear dynamic equations on time scales, Banach's\nfixed point theorem and the theory of calculus on time scales, some sufficient\nconditions that are independent of the backwards graininess function of the\ntime scale are obtained for the existence and global exponential stability of\nalmost periodic solutions for this class of neural networks. The obtained\nresults are completely new and indicate that both the continuous time and the\ndiscrete time cases of the networks share the same dynamical behavior. Finally,\nan examples is given to show the effectiveness of the obtained results.\n",
"title": "The existence and global exponential stability of almost periodic solutions for neutral type CNNs on time scales"
}
| null | null |
[
"Mathematics"
] | null | true | null |
5047
| null |
Validated
| null | null |
null |
{
"abstract": " While students may find spline interpolation easily digestible, based on\ntheir familiarity with continuity of a function and its derivatives, some of\nits inherent value may be missed when students only see it applied to standard\ndata interpolation exercises. In this paper, we offer alternatives where\nstudents can qualitatively and quantitatively witness the resulting dynamical\ndifferences when objects are driven through a fluid using different spline\ninterpolation methods. They say, seeing is believing; here we showcase the\ndifferences between linear and cubic spline interpolation using examples from\nfluid pumping and aquatic locomotion. Moreover, students can define their own\ninterpolation functions and visualize the dynamics unfold. To solve the\nfluid-structure interaction system, the open source software IB2d is used. In\nthat vein, all simulation codes, analysis scripts, and movies are provided for\nstreamlined use.\n",
"title": "Fluid-Structure Interaction for the Classroom: Interpolation, Hearts, and Swimming!"
}
| null | null |
[
"Quantitative Biology"
] | null | true | null |
5048
| null |
Validated
| null | null |
null |
{
"abstract": " We present a Monte Carlo (MC) grid-based model for the drying of drops of a\nnanoparticle suspension upon a heterogeneous surface. The model consists of a\ngeneralised lattice-gas in which the interaction parameters in the Hamiltonian\ncan be varied to model different properties of the materials involved. We show\nhow to choose correctly the interactions, to minimise the effects of the\nunderlying grid so that hemispherical droplets form. We also include the\neffects of surface roughness to examine the effects of contact-line pinning on\nthe dynamics. When there is a `lid' above the system, which prevents\nevaporation, equilibrium drops form on the surface, which we use to determine\nthe contact angle and how it varies as the parameters of the model are changed.\nThis enables us to relate the interaction parameters to the materials used in\napplications. The model has also been applied to drying on heterogeneous\nsurfaces, in particular to the case where the suspension is deposited on a\nsurface consisting of a pair of hydrophilic conducting metal surfaces that are\neither side of a band of hydrophobic insulating polymer. This situation occurs\nwhen using inkjet printing to manufacture electrical connections between the\nmetallic parts of the surface. The process is not always without problems,\nsince the liquid can dewet from the hydrophobic part of the surface, breaking\nthe bridge before the drying process is complete. The MC model reproduces the\nobserved dewetting, allowing the parameters to be varied so that the conditions\nfor the best connection can be established. We show that if the hydrophobic\nportion of the surface is located at a step below the height of the\nneighbouring metal, the chance of dewetting of the liquid during the drying\nprocess is significantly reduced.\n",
"title": "Modelling the evaporation of nanoparticle suspensions from heterogeneous surfaces"
}
| null | null | null | null | true | null |
5049
| null |
Default
| null | null |
null |
{
"abstract": " Image retargeting aims to resize an image to one with a prescribed aspect\nratio. Simple scaling inevitably introduces unnatural geometric distortions on\nthe important content of the image. In this paper, we propose a simple and yet\neffective method to resize an image, which preserves the geometry of the\nimportant content, using the Beltrami representation. Our algorithm allows\nusers to interactively label content regions as well as line structures. Image\nresizing can then be achieved by warping the image by an orientation-preserving\nbijective warping map with controlled distortion. The warping map is\nrepresented by its Beltrami representation, which captures the local geometric\ndistortion of the map. By carefully prescribing the values of the Beltrami\nrepresentation, images with different complexity can be effectively resized.\nOur method does not require solving any optimization problems and tuning\nparameters throughout the process. This results in a simple and efficient\nalgorithm to solve the image retargeting problem. Extensive experiments have\nbeen carried out, which demonstrate the efficacy of our proposed method.\n",
"title": "Image retargeting via Beltrami representation"
}
| null | null |
[
"Computer Science"
] | null | true | null |
5050
| null |
Validated
| null | null |
null |
{
"abstract": " In this paper, the optimal power flow (OPF) problem is augmented to account\nfor the costs associated with the load-following control of a power network.\nLoad-following control costs are expressed through the linear quadratic\nregulator (LQR). The power network is described by a set of nonlinear\ndifferential algebraic equations (DAEs). By linearizing the DAEs around a known\nequilibrium, a linearized OPF that accounts for steady-state operational\nconstraints is formulated first. This linearized OPF is then augmented by a set\nof linear matrix inequalities that are algebraically equivalent to the\nimplementation of an LQR controller. The resulting formulation, termed LQR-OPF,\nis a semidefinite program which furnishes optimal steady-state setpoints and an\noptimal feedback law to steer the system to the new steady state with minimum\nload-following control costs. Numerical tests demonstrate that the setpoints\ncomputed by LQR-OPF result in lower overall costs and frequency deviations\ncompared to the setpoints of a scheme where OPF and load-following control are\nconsidered separately.\n",
"title": "Coupling Load-Following Control with OPF"
}
| null | null | null | null | true | null |
5051
| null |
Default
| null | null |
null |
{
"abstract": " Let $ \\mathbb{A}$ be a cellular algebra over a field $\\mathbb{F}$ with a\ndecomposition of the identity $ 1_{\\mathbb{A}} $ into orthogonal idempotents $\ne_i$, $i \\in I$ (for some finite set $I$) satisfying some properties. We\ndescribe the entire Loewy structure of cell modules of the algebra $ \\mathbb{A}\n$ by using the representation theory of the algebra $ e_i \\mathbb{A} e_i $ for\neach $ i $. Moreover, we also study the block theory of $\\mathbb{A}$ by using\nthis decomposition.\n",
"title": "A cellular algebra with specific decomposition of the unity"
}
| null | null | null | null | true | null |
5052
| null |
Default
| null | null |
null |
{
"abstract": " The discrete Frenet equation entails a local framing of a discrete, piecewise\nlinear polygonal chain in terms of its bond and torsion angles. In particular,\nthe tangent vector of a segment is akin the classical O(3) spin variable. Thus\nthere is a relation to the lattice Heisenberg model, that can be used to model\nphysical properties of the chain. On the other hand, the Heisenberg model is\nclosely related to the discrete nonlinear Schrödinger (DNLS) equation. Here\nwe apply these interrelations to develop a perspective on discrete chains\ndynamics: We employ the properties of a discrete chain in terms of a spinorial\nrepresentation of the discrete Frenet equation, to introduce a bi-hamiltonian\nstructure for the discrete nonlinear Schrödinger equation (DNLSE), which we\nthen use to produce integrable chain dynamics.\n",
"title": "On relation between discrete Frenet frames and the bi-Hamiltonian structure of the discrete nonlinear Schrödinger equation"
}
| null | null | null | null | true | null |
5053
| null |
Default
| null | null |
null |
{
"abstract": " In 1902, P. Stäckel proved the existence of a transcendental function\n$f(z)$, analytic in a neighbourhood of the origin, and with the property that\nboth $f(z)$ and its inverse function assume, in this neighbourhood, algebraic\nvalues at all algebraic points. Based on this result, in 1976, K. Mahler raised\nthe question of the existence of such functions which are analytic in\n$\\mathbb{C}$. Recently, the authors answered positively this question. In this\npaper, we prove a much stronger version of this result by considering other\nsubsets of $\\mathbb{C}$.\n",
"title": "A stronger version of a question proposed by K. Mahler"
}
| null | null | null | null | true | null |
5054
| null |
Default
| null | null |
null |
{
"abstract": " We consider classifiers for high-dimensional data under the strongly spiked\neigenvalue (SSE) model. We first show that high-dimensional data often have the\nSSE model. We consider a distance-based classifier using eigenstructures for\nthe SSE model. We apply the noise reduction methodology to estimation of the\neigenvalues and eigenvectors in the SSE model. We create a new distance-based\nclassifier by transforming data from the SSE model to the non-SSE model. We\ngive simulation studies and discuss the performance of the new classifier.\nFinally, we demonstrate the new classifier by using microarray data sets.\n",
"title": "Distance-based classifier by data transformation for high-dimension, strongly spiked eigenvalue models"
}
| null | null | null | null | true | null |
5055
| null |
Default
| null | null |
null |
{
"abstract": " We establish a dictionary between group field theory (thus, spin networks and\nrandom tensors) states and generalized random tensor networks. Then, we use\nthis dictionary to compute the Rényi entropy of such states and recover the\nRyu-Takayanagi formula, in two different cases corresponding to two different\ntruncations/approximations, suggested by the established correspondence.\n",
"title": "Group Field theory and Tensor Networks: towards a Ryu-Takayanagi formula in full quantum gravity"
}
| null | null | null | null | true | null |
5056
| null |
Default
| null | null |
null |
{
"abstract": " We examine the behavior of accelerated gradient methods in smooth nonconvex\nunconstrained optimization, focusing in particular on their behavior near\nstrict saddle points. Accelerated methods are iterative methods that typically\nstep along a direction that is a linear combination of the previous step and\nthe gradient of the function evaluated at a point at or near the current\niterate. (The previous step encodes gradient information from earlier stages in\nthe iterative process.) We show by means of the stable manifold theorem that\nthe heavy-ball method method is unlikely to converge to strict saddle points,\nwhich are points at which the gradient of the objective is zero but the Hessian\nhas at least one negative eigenvalue. We then examine the behavior of the\nheavy-ball method and other accelerated gradient methods in the vicinity of a\nstrict saddle point of a nonconvex quadratic function, showing that both\nmethods can diverge from this point more rapidly than the steepest-descent\nmethod.\n",
"title": "Behavior of Accelerated Gradient Methods Near Critical Points of Nonconvex Functions"
}
| null | null | null | null | true | null |
5057
| null |
Default
| null | null |
null |
{
"abstract": " Currently, two main approaches exist to distinguish differential\nsusceptibility from diathesis-stress and vantage sensitivity in genotype x\nenvironment interaction (GxE) research: Regions of significance (RoS) and\ncompetitive-confirmatory approaches. Each is limited by their\nsingle-gene/single-environment foci given that most phenotypes are the product\nof multiple interacting genetic and environmental factors. We thus addressed\nthese two concerns in a recently developed R package (LEGIT) for constructing\nGxE interaction models with latent genetic and environmental scores using\nalternating optimization. Herein we test, by means of computer simulation,\ndiverse GxE models in the context of both single and multiple genes and\nenvironments. Results indicate that the RoS and competitive-confirmatory\napproaches were highly accurate when the sample size was large, whereas the\nlatter performed better in small samples and for small effect sizes. The\nconfirmatory approach generally had good accuracy (a) when effect size was\nmoderate and N >= 500 and (b) when effect size was large and N >= 250, whereas\nRoS performed poorly. Computational tools to determine the type of GxE of\nmultiple genes and environments are provided as extensions in our LEGIT R\npackage.\n",
"title": "Distinguishing differential susceptibility, diathesis-stress and vantage sensitivity: beyond the single gene and environment model"
}
| null | null | null | null | true | null |
5058
| null |
Default
| null | null |
null |
{
"abstract": " We obtain a weak type $(1,1)$ estimate for a maximal operator associated with\nthe classical rough homogeneous singular integrals $T_{\\Omega}$. In particular,\nthis provides a different approach to a sparse domination for $T_{\\Omega}$\nobtained recently by Conde-Alonso, Culiuc, Di Plinio and Ou.\n",
"title": "A weak type estimate for rough singular integrals"
}
| null | null | null | null | true | null |
5059
| null |
Default
| null | null |
null |
{
"abstract": " The Internet of things (IoT) is still in its infancy and has attracted much\ninterest in many industrial sectors including medical fields, logistics\ntracking, smart cities and automobiles. However as a paradigm, it is\nsusceptible to a range of significant intrusion threats. This paper presents a\nthreat analysis of the IoT and uses an Artificial Neural Network (ANN) to\ncombat these threats. A multi-level perceptron, a type of supervised ANN, is\ntrained using internet packet traces, then is assessed on its ability to thwart\nDistributed Denial of Service (DDoS/DoS) attacks. This paper focuses on the\nclassification of normal and threat patterns on an IoT Network. The ANN\nprocedure is validated against a simulated IoT network. The experimental\nresults demonstrate 99.4% accuracy and can successfully detect various DDoS/DoS\nattacks.\n",
"title": "Threat analysis of IoT networks Using Artificial Neural Network Intrusion Detection System"
}
| null | null | null | null | true | null |
5060
| null |
Default
| null | null |
null |
{
"abstract": " In this paper, we study the ability to make the short-term prediction of the\nexchange price fluctuations towards the United States dollar for the Bitcoin\nmarket. We use the data of realized volatility collected from one of the\nlargest Bitcoin digital trading offices in 2016 and 2017 as well as order\ninformation. Experiments are performed to evaluate a variety of statistical and\nmachine learning approaches.\n",
"title": "An experimental study of Bitcoin fluctuation using machine learning methods"
}
| null | null | null | null | true | null |
5061
| null |
Default
| null | null |
null |
{
"abstract": " Hydroclimatic processes are characterized by heterogeneous spatiotemporal\ncorrelation structures and marginal distributions that can be continuous,\nmixed-type, discrete or even binary. Simulating exactly such processes can\ngreatly improve hydrological analysis and design. Yet this challenging task is\naccomplished often by ad hoc and approximate methodologies that are devised for\nspecific variables and purposes. In this study, a single framework is proposed\nallowing the exact simulation of processes with any marginal and any\ncorrelation structure. We unify, extent, and improve of a general-purpose\nmodelling strategy based on the assumption that any process can emerge by\ntransforming a parent Gaussian process with a specific correlation structure. A\nnovel mathematical representation of the parent-Gaussian scheme provides a\nconsistent and fully general description that supersedes previous specific\nparameterizations, resulting in a simple, fast and efficient simulation\nprocedure for every spatiotemporal process. In particular, introducing a simple\nbut flexible procedure we obtain a parametric expression of the correlation\ntransformation function, allowing to assess the correlation structure of the\nparent-Gaussian process that yields the prescribed correlation of the target\nprocess after marginal back transformation. The same framework is also\napplicable for cyclostationary and multivariate modelling. The simulation of a\nvariety of hydroclimatic variables with very different correlation structures\nand marginals, such as precipitation, stream flow, wind speed, humidity,\nextreme events per year, etc., as well as a multivariate application,\nhighlights the flexibility, advantages, and complete generality of the proposed\nmethodology.\n",
"title": "A unified theory for exact stochastic modelling of univariate and multivariate processes with continuous, mixed type, or discrete marginal distributions and any correlation structure"
}
| null | null | null | null | true | null |
5062
| null |
Default
| null | null |
null |
{
"abstract": " The guiding influence of some of Stanley Mandelstam's key contributions to\nthe development of theoretical high energy physics is discussed, from the\nmotivation for the study of the analytic properties of the scattering matrix\nthrough to dual resonance models and their evolution into string theory.\n",
"title": "The Guiding Influence of Stanley Mandelstam, from S-Matrix Theory to String Theory"
}
| null | null | null | null | true | null |
5063
| null |
Default
| null | null |
null |
{
"abstract": " Accretion of gas and interaction of matter and radiation are at the heart of\nmany questions pertaining to black hole (BH) growth and coevolution of massive\nBHs and their host galaxies. To answer them it is critical to quantify how the\nionizing radiation that emanates from the innermost regions of the BH accretion\nflow couples to the surrounding medium and how it regulates the BH fueling. In\nthis work we use high resolution 3-dimensional (3D) radiation-hydrodynamic\nsimulations with the code Enzo, equipped with adaptive ray tracing module\nMoray, to investigate radiation-regulated BH accretion of cold gas. Our\nsimulations reproduce findings from an earlier generation of 1D/2D simulations:\nthe accretion powered UV and X-ray radiation forms a highly ionized bubble,\nwhich leads to suppression of BH accretion rate characterized by quasi-periodic\noutbursts. A new feature revealed by the 3D simulations is the highly turbulent\nnature of the gas flow in vicinity of the ionization front. During quiescent\nperiods between accretion outbursts, the ionized bubble shrinks in size and the\ngas density that precedes the ionization front increases. Consequently, the 3D\nsimulations show oscillations in the accretion rate of only ~2-3 orders of\nmagnitude, significantly smaller than 1D/2D models. We calculate the energy\nbudget of the gas flow and find that turbulence is the main contributor to the\nkinetic energy of the gas but corresponds to less than 10% of its thermal\nenergy and thus does not contribute significantly to the pressure support of\nthe gas.\n",
"title": "Radiation-driven turbulent accretion onto massive black holes"
}
| null | null | null | null | true | null |
5064
| null |
Default
| null | null |
null |
{
"abstract": " The log-determinant of a kernel matrix appears in a variety of machine\nlearning problems, ranging from determinantal point processes and generalized\nMarkov random fields, through to the training of Gaussian processes. Exact\ncalculation of this term is often intractable when the size of the kernel\nmatrix exceeds a few thousand. In the spirit of probabilistic numerics, we\nreinterpret the problem of computing the log-determinant as a Bayesian\ninference problem. In particular, we combine prior knowledge in the form of\nbounds from matrix theory and evidence derived from stochastic trace estimation\nto obtain probabilistic estimates for the log-determinant and its associated\nuncertainty within a given computational budget. Beyond its novelty and\ntheoretic appeal, the performance of our proposal is competitive with\nstate-of-the-art approaches to approximating the log-determinant, while also\nquantifying the uncertainty due to budget-constrained evidence.\n",
"title": "Bayesian Inference of Log Determinants"
}
| null | null | null | null | true | null |
5065
| null |
Default
| null | null |
null |
{
"abstract": " In numerical simulations, artificial terms are applied to the evolution\nequations for stability. To prove their validity, these terms are thoroughly\ntested in test problems where the results are well known. However, they are\nseldom tested in production-quality simulations at high resolution where they\ninteract with a plethora of physical and numerical algorithms. We test three\nartificial resistivities in both the Orszag-Tang vortex and in a star formation\nsimulation. From the Orszag-Tang vortex, the Price et. al. (2017) artificial\nresistivity is the least dissipative thus captures the density and magnetic\nfeatures; in the star formation algorithm, each artificial resistivity\nalgorithm interacts differently with the sink particle to produce various\nresults, including gas bubbles, dense discs, and migrating sink particles. The\nstar formation simulations suggest that it is important to rely upon physical\nresistivity rather than artificial resistivity for convergence.\n",
"title": "Investigating prescriptions for artificial resistivity in smoothed particle magnetohydrodynamics"
}
| null | null | null | null | true | null |
5066
| null |
Default
| null | null |
null |
{
"abstract": " Humanoid robots are increasingly demanded to operate in interactive and\nhuman-surrounded environments while achieving sophisticated locomotion and\nmanipulation tasks. To accomplish these tasks, roboticists unremittingly seek\nfor advanced methods that generate whole-body coordination behaviors and\nmeanwhile fulfill various planning and control objectives. Undoubtedly, these\ngoals pose fundamental challenges to the robotics and control community. To\ntake an incremental step towards reducing the performance gap between\ntheoretical foundations and real implementations, we present a planning and\ncontrol framework for the humanoid, especially legged robots, for achieving\nhigh performance and generating agile motions. A particular concentration is on\nthe robust, optimal and real-time performance. This framework constitutes three\nhierarchical layers: First, we present a robust optimal phase-space planning\nframework for dynamic legged locomotion over rough terrain. This framework is a\nhybrid motion planner incorporating a series of pivotal components. Second, we\ntake a step toward formally synthesizing high-level reactive planners for\nwhole-body locomotion in constrained environments. We formulate a two-player\ntemporal logic game between the contact planner and its possibly-adversarial\nenvironment. Third, we propose a distributed control architecture for the\nlatency-prone humanoid robotic systems. A central experimental phenomenon is\nobserved that the stability of high impedance distributed controllers is highly\nsensitive to damping feedback delay but much less to stiffness feedback delay.\nWe pursue a detailed analysis of the distributed controllers where damping\nfeedback effort is executed in proximity to the control plant, and stiffness\nfeedback effort is implemented in a latency-prone centralized control process.\n",
"title": "A Planning and Control Framework for Humanoid Systems: Robust, Optimal, and Real-time Performance"
}
| null | null | null | null | true | null |
5067
| null |
Default
| null | null |
null |
{
"abstract": " Conventional automatic speech recognition (ASR) typically performs\nmulti-level pattern recognition tasks that map the acoustic speech waveform\ninto a hierarchy of speech units. But, it is widely known that information loss\nin the earlier stage can propagate through the later stages. After the\nresurgence of deep learning, interest has emerged in the possibility of\ndeveloping a purely end-to-end ASR system from the raw waveform to the\ntranscription without any predefined alignments and hand-engineered models.\nHowever, the successful attempts in end-to-end architecture still used\nspectral-based features, while the successful attempts in using raw waveform\nwere still based on the hybrid deep neural network - Hidden Markov model\n(DNN-HMM) framework. In this paper, we construct the first end-to-end\nattention-based encoder-decoder model to process directly from raw speech\nwaveform to the text transcription. We called the model as \"Attention-based\nWav2Text\". To assist the training process of the end-to-end model, we propose\nto utilize a feature transfer learning. Experimental results also reveal that\nthe proposed Attention-based Wav2Text model directly with raw waveform could\nachieve a better result in comparison with the attentional encoder-decoder\nmodel trained on standard front-end filterbank features.\n",
"title": "Attention-based Wav2Text with Feature Transfer Learning"
}
| null | null | null | null | true | null |
5068
| null |
Default
| null | null |
null |
{
"abstract": " The phenomenon of amplitude death has been explored using a variety of\ndifferent coupling strategies in the last two decades. In most of the work, the\nbasic coupling arrangement is considered to be static over time, although many\nrealistic systems exhibit significant changes in the interaction pattern as\ntime varies. In this article, we study the emergence of amplitude death in a\ndynamical network composed of time-varying interaction amidst a collection of\nrandom walkers in a finite region of three dimensional space. We consider an\noscillator for each walker and demonstrate that depending upon the network\nparameters and hence the interaction between them, global oscillation in the\nnetwork gets suppressed. In this framework, vision range of each oscillator\ndecides the number of oscillators with which it interacts. In addition, with\nthe use of an appropriate feedback parameter in the coupling strategy, we\narticulate how the suppressed oscillation can be resurrected in the systems'\nparameter space. The phenomenon of amplitude death and the resurgence of\noscillation is investigated taking limit cycle and chaotic oscillators for\nbroad ranges of parameters, like interaction strength k between the entities,\nvision range r and the speed of movement v.\n",
"title": "Amplitude death and resurgence of oscillation in network of mobile oscillators"
}
| null | null | null | null | true | null |
5069
| null |
Default
| null | null |
null |
{
"abstract": " A novel approach to quintessential inflation model building is studied,\nwithin the framework of $\\alpha$-attractors, motivated by supergravity\ntheories. Inflationary observables are in excellent agreement with the latest\nCMB observations, while quintessence explains the dark energy observations\nwithout any fine-tuning. The model is kept intentionally minimal, avoiding the\nintroduction of many degrees of freedom, couplings and mass scales. In stark\ncontrast to $\\Lambda$CDM, for natural values of the parameters, the model\nattains transient accelerated expansion, which avoids the future horizon\nproblem, while it maintains the field displacement mildly sub-Planckian such\nthat the flatness of the quintessential tail is not lifted by radiative\ncorrections and violations of the equivalence principle (fifth force) are under\ncontrol. In particular, the required value of the cosmological constant is near\nthe eletroweak scale. Attention is paid to the reheating of the Universe, which\navoids gravitino overproduction and respects nucleosynthesis constraints.\nKination is treated in a model independent way. A spike in gravitational waves,\ndue to kination, is found not to disturb nucleosynthesis as well.\n",
"title": "Quintessential Inflation with $α$-attractors"
}
| null | null | null | null | true | null |
5070
| null |
Default
| null | null |
null |
{
"abstract": " We present a study of the low temperature phases of the antiferromagnetic\nextended classical Heisenberg model in the kagome lattice, up to third nearest\nneighbors. First, we focus on the degenerate lines in the boundaries of the\nwell-known staggered chiral phases. These boundaries have either semi-extensive\nor extensive degeneracy, and we discuss the partial selection of states by\nthermal fluctuations. Then, we study the model under an external magnetic field\non these lines and in the staggered chiral phases. We pay particular attention\nto the highly frustrated point, where the three exchange couplings are equal.\nWe show that this point can me mapped to a model with spin liquid behavior and\nnon-zero chirality. Finally, we explore the effect of Dzyaloshinskii-Moriya\n(DM) interactions in two ways: an homogeneous and a staggered DM interaction.\nIn both cases, there is a rich low temperature phase diagram, with different\nspontaneously broken symmetries and non trivial chiral phases.\n",
"title": "Degenerate and chiral states in the extended Heisenberg model in the kagome lattice"
}
| null | null |
[
"Physics"
] | null | true | null |
5071
| null |
Validated
| null | null |
null |
{
"abstract": " Objective: Numerous glucose prediction algorithm have been proposed to\nempower type 1 diabetes (T1D) management. Most of these algorithms only account\nfor input such as glucose, insulin and carbohydrate, which limits their\nperformance. Here, we present a novel glucose prediction algorithm which, in\naddition to standard inputs, accounts for meal absorption and physical exercise\ninformation to enhance prediction accuracy. Methods: a compartmental model of\nglucose-insulin dynamics combined with a deconvolution technique for state\nestimation is employed for glucose prediction. In silico data corresponding\nfrom the 10 adult subjects of UVa-Padova simulator, and clinical data from 10\nadults with T1D were used. Finally, a comparison against a validated glucose\nprediction algorithm based on a latent variable with exogenous input (LVX)\nmodel is provided. Results: For a prediction horizon of 60 minutes, accounting\nfor meal absorption and physical exercise improved glucose forecasting\naccuracy. In particular, root mean square error (mg/dL) went from 26.68 to\n23.89, p<0.001 (in silico data); and from 37.02 to 35.96, p<0.001 (clinical\ndata - only meal information). Such improvement in accuracy was translated into\nsignificant improvements on hypoglycaemia and hyperglycaemia prediction.\nFinally, the performance of the proposed algorithm is statistically superior to\nthat of the LVX algorithm (26.68 vs. 32.80, p<0.001 (in silico data); 37.02 vs.\n49.17, p<0.01 (clinical data). Conclusion: Taking into account meal absorption\nand physical exercise information improves glucose prediction accuracy.\n",
"title": "Enhancing Blood Glucose Prediction with Meal Absorption and Physical Exercise Information"
}
| null | null | null | null | true | null |
5072
| null |
Default
| null | null |
null |
{
"abstract": " We derive and compare the fractions of cool-core clusters in the {\\em Planck}\nEarly Sunyaev-Zel'dovich sample of 164 clusters with $z \\leq 0.35$ and in a\nflux-limited X-ray sample of 100 clusters with $z \\leq 0.30$, using {\\em\nChandra} observations. We use four metrics to identify cool-core clusters: 1)\nthe concentration parameter: the ratio of the integrated emissivity profile\nwithin 0.15 $r_{500}$ to that within $r_{500}$, and 2) the ratio of the\nintegrated emissivity profile within 40 kpc to that within 400 kpc, 3) the\ncuspiness of the gas density profile: the negative of the logarithmic\nderivative of the gas density with respect to the radius, measured at 0.04\n$r_{500}$, and 4) the central gas density, measured at 0.01 $r_{500}$. We find\nthat the sample of X-ray selected clusters, as characterized by each of these\nmetrics, contains a significantly larger fraction of cool-core clusters\ncompared to the sample of SZ selected clusters (44$\\pm$7\\% vs. 28$\\pm$4\\% using\nthe concentration parameter in the 0.15--1.0 $r_{500}$ range, 61$\\pm$8\\% vs.\n36$\\pm$5\\% using the concentration parameter in the 40--400 kpc range,\n64$\\pm$8\\% vs. 38$\\pm$5\\% using the cuspiness, and 53$\\pm$7\\% vs. 39$\\pm$5\\%\nusing the central gas density). Qualitatively, cool-core clusters are more\nX-ray luminous at fixed mass. Hence, our X-ray flux-limited sample, compared to\nthe approximately mass-limited SZ sample, is over-represented with cool-core\nclusters. We describe a simple quantitative model that uses the excess\nluminosity of cool-core clusters compared to non-cool-core clusters at fixed\nmass to successfully predict the observed fraction of cool-core clusters in\nX-ray selected samples.\n",
"title": "The fraction of cool-core clusters in X-ray vs. SZ samples using Chandra observations"
}
| null | null | null | null | true | null |
5073
| null |
Default
| null | null |
null |
{
"abstract": " Online Multi-Object Tracking (MOT) from videos is a challenging computer\nvision task which has been extensively studied for decades. Most of the\nexisting MOT algorithms are based on the Tracking-by-Detection (TBD) paradigm\ncombined with popular machine learning approaches which largely reduce the\nhuman effort to tune algorithm parameters. However, the commonly used\nsupervised learning approaches require the labeled data (e.g., bounding boxes),\nwhich is expensive for videos. Also, the TBD framework is usually suboptimal\nsince it is not end-to-end, i.e., it considers the task as detection and\ntracking, but not jointly. To achieve both label-free and end-to-end learning\nof MOT, we propose a Tracking-by-Animation framework, where a differentiable\nneural model first tracks objects from input frames and then animates these\nobjects into reconstructed frames. Learning is then driven by the\nreconstruction error through backpropagation. We further propose a\nReprioritized Attentive Tracking to improve the robustness of data association.\nExperiments conducted on both synthetic and real video datasets show the\npotential of the proposed model.\n",
"title": "Tracking by Animation: Unsupervised Learning of Multi-Object Attentive Trackers"
}
| null | null | null | null | true | null |
5074
| null |
Default
| null | null |
null |
{
"abstract": " Generating novel graph structures that optimize given objectives while\nobeying some given underlying rules is fundamental for chemistry, biology and\nsocial science research. This is especially important in the task of molecular\ngraph generation, whose goal is to discover novel molecules with desired\nproperties such as drug-likeness and synthetic accessibility, while obeying\nphysical laws such as chemical valency. However, designing models to find\nmolecules that optimize desired properties while incorporating highly complex\nand non-differentiable rules remains to be a challenging task. Here we propose\nGraph Convolutional Policy Network (GCPN), a general graph convolutional\nnetwork based model for goal-directed graph generation through reinforcement\nlearning. The model is trained to optimize domain-specific rewards and\nadversarial loss through policy gradient, and acts in an environment that\nincorporates domain-specific rules. Experimental results show that GCPN can\nachieve 61% improvement on chemical property optimization over state-of-the-art\nbaselines while resembling known molecules, and achieve 184% improvement on the\nconstrained property optimization task.\n",
"title": "Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation"
}
| null | null | null | null | true | null |
5075
| null |
Default
| null | null |
null |
{
"abstract": " Given their small mobility coefficient in liquid argon with respect to the\nelectrons, the ions spend a considerably longer time in the active volume. We\nstudied the effects of the positive ion current in a liquid argon time\nprojection chamber, in the context of massive argon experiments for neutrino\nphysics. The constant recombination between free ions and electrons produces a\nquenching of the charge signal and a constant emission of photons, uncorrelated\nin time and space to the physical interactions. The predictions evidence some\npotential concerns for multi-ton argon detectors, particularly when operated on\nsurface\n",
"title": "Impact of the positive ion current on large size neutrino detectors and delayed photon emission"
}
| null | null |
[
"Physics"
] | null | true | null |
5076
| null |
Validated
| null | null |
null |
{
"abstract": " We address the problem of constructing of coding schemes for the channels\nwith high-order modulations. It is known, that non-binary LDPC codes are\nespecially good for such channels and significantly outperform their binary\ncounterparts. Unfortunately, their decoding complexity is still large. In order\nto reduce the decoding complexity we consider multilevel coding schemes based\non non-binary LDPC codes (NB-LDPC-MLC schemes) over smaller fields. The use of\nsuch schemes gives us a reasonable gain in complexity. At the same time the\nperformance of NB-LDPC-MLC schemes is practically the same as the performance\nof LDPC codes over the field matching the modulation order. In particular by\nmeans of simulations we showed that the performance of NB-LDPC-MLC schemes over\nGF(16) is the same as the performance of non-binary LDPC codes over GF(64) and\nGF(256) in AWGN channel with QAM64 and QAM256 accordingly. We also perform a\ncomparison with binary LDPC codes.\n",
"title": "On Multilevel Coding Schemes Based on Non-Binary LDPC Codes"
}
| null | null | null | null | true | null |
5077
| null |
Default
| null | null |
null |
{
"abstract": " We propose and demonstrate a self-coupled microring resonator for resonance\nsplitting by mutual mode coupling of cavity mode and counter-propagating mode\nin Silicon-on-Insulator platform The resonator is constructed with a\nself-coupling region that can excite counter-propagating mode. We\nexperimentally study the effect of self-coupling on the resonance splitting,\nresonance extinction, and quality-factor evolution and stability. Based on the\ncoupling, we achieve 72% of FSR splitting for a cavity with FSR 2.1 nm with <\n5% variation in the cavity quality factor. The self-coupled resonance splitting\nshows highly robust spectral characteristic that can be exploited for sensing\nand optical signal processing.\n",
"title": "Tunable coupling-induced resonance splitting in self-coupled Silicon ring cavity with robust spectral characteristics"
}
| null | null | null | null | true | null |
5078
| null |
Default
| null | null |
null |
{
"abstract": " We report measurements of the $^{115}$In $7p_{1/2}$ and $7p_{3/2}$ scalar and\ntensor polarizabilities using two-step diode laser spectroscopy in an atomic\nbeam. The scalar polarizabilities are one to two orders of magnitude larger\nthan for lower lying indium states due to the close proximity of the $7p$ and\n$6d$ states. For the scalar polarizabilities, we find values (in atomic units)\nof $1.811(4) \\times 10^5$ $a_0^3$ and $2.876(6) \\times 10^5$ $a_0^3$ for the\n$7p_{1/2}$ and $7p_{3/2}$ states respectively. We estimate the smaller tensor\npolarizability component of the $7p_{3/2}$ state to be $-1.43(18) \\times 10^4$\n$a_0^3$. These measurements represent the first high-precision benchmarks of\ntransition properties of such high excited states of trivalent atomic systems.\nWe also present new ab initio calculations of these quantities and other In\npolarizabilities using two high-precision relativistic methods to make a global\ncomparison of the accuracies of the two approaches. The precision of the\nexperiment is sufficient to differentiate between the two theoretical methods\nas well as to allow precise determination of the indium $7p-6d$ matrix\nelements. The results obtained in this work are applicable to other heavier and\nmore complicated systems, and provide much needed guidance for the development\nof even more precise theoretical approaches.\n",
"title": "High-precision measurements and theoretical calculations of indium excited-state polarizabilities"
}
| null | null | null | null | true | null |
5079
| null |
Default
| null | null |
null |
{
"abstract": " We consider the 3D equation $u_{yy} = u_{tx} + u_yu_{xx} - u_xu_{xy}$ and its\n2D reductions: (1) $u_{yy} = (u_y+y)u_{xx}-u_xu_{xy}-2$ (which is equivalent to\nthe Gibbons-Tsarev equation) and (2) $u_{yy} = (u_y+2x)u_{xx} + (y-u_x)u_{xy}\n-u_x$. Using reduction of the known Lax pair for the 3D equation, we describe\nnonlocal symmetries of~(1) and~(2) and show that the Lie algebras of these\nsymmetries are isomorphic to the Witt algebra.\n",
"title": "2D reductions of the equation $u_{yy} = u_{tx} + u_yu_{xx} - u_xu_{xy}$ and their nonlocal symmetries"
}
| null | null | null | null | true | null |
5080
| null |
Default
| null | null |
null |
{
"abstract": " We first present an empirical study of the Belief Propagation (BP) algorithm,\nwhen run on the random field Ising model defined on random regular graphs in\nthe zero temperature limit. We introduce the notion of maximal solutions for\nthe BP equations and we use them to fix a fraction of spins in their ground\nstate configuration. At the phase transition point the fraction of\nunconstrained spins percolates and their number diverges with the system size.\nThis in turn makes the associated optimization problem highly non trivial in\nthe critical region. Using the bounds on the BP messages provided by the\nmaximal solutions we design a new and very easy to implement BP scheme which is\nable to output a large number of stable fixed points. On one side this new\nalgorithm is able to provide the minimum energy configuration with high\nprobability in a competitive time. On the other side we found that the number\nof fixed points of the BP algorithm grows with the system size in the critical\nregion. This unexpected feature poses new relevant questions on the physics of\nthis class of models.\n",
"title": "An improved Belief Propagation algorithm finds many Bethe states in the random field Ising model on random graphs"
}
| null | null |
[
"Computer Science",
"Physics"
] | null | true | null |
5081
| null |
Validated
| null | null |
null |
{
"abstract": " The study of surnames as both linguistic and geographical markers of the past\nhas proven valuable in several research fields spanning from biology and\ngenetics to demography and social mobility. This article builds upon the\nexisting literature to conceive and develop a surname origin classifier based\non a data-driven typology. This enables us to explore a methodology to describe\nlarge-scale estimates of the relative diversity of social groups, especially\nwhen such data is scarcely available. We subsequently analyze the\nrepresentativeness of surname origins for 15 socio-professional groups in\nFrance.\n",
"title": "Large-scale diversity estimation through surname origin inference"
}
| null | null | null | null | true | null |
5082
| null |
Default
| null | null |
null |
{
"abstract": " Let $\\mathfrak l:= \\mathfrak q(n)\\times\\mathfrak q(n)$, where $\\mathfrak\nq(n)$ denotes the queer Lie superalgebra. The associative superalgebra $V$ of\ntype $Q(n)$ has a left and right action of $\\mathfrak q(n)$, and hence is\nequipped with a canonical $\\mathfrak l$-module structure. We consider a\ndistinguished basis $\\{D_\\lambda\\}$ of the algebra of $\\mathfrak l$-invariant\nsuper-polynomial differential operators on $V$, which is indexed by strict\npartitions of length at most $n$. We show that the spectrum of the operator\n$D_\\lambda$, when it acts on the algebra $\\mathscr P(V)$ of super-polynomials\non $V$, is given by the factorial Schur $Q$-function of Okounkov and Ivanov.\nThis constitutes a refinement and a new proof of a result of Nazarov, who\ncomputed the top-degree homogeneous part of the Harish-Chandra image of\n$D_\\lambda$. As a further application, we show that the radial projections of\nthe spherical super-polynomials corresponding to the diagonal symmetric pair\n$(\\mathfrak l,\\mathfrak m)$, where $\\mathfrak m:=\\mathfrak q(n)$, of\nirreducible $\\mathfrak l$-submodules of $\\mathscr P(V)$ are the classical Schur\n$Q$-functions.\n",
"title": "Schur $Q$-functions and the Capelli eigenvalue problem for the Lie superalgebra $\\mathfrak q(n)$"
}
| null | null | null | null | true | null |
5083
| null |
Default
| null | null |
null |
{
"abstract": " In this work we focus on a novel completion of the well-known Brans-Dicke\ntheory that introduces an interaction between the dark energy and dark matter\nsectors, known as complete Brans-Dicke (CBD) theory. We obtain viable\ncosmological accelerating solutions that fit Supernovae observations with great\nprecision without any scalar potential $V(\\phi)$. We use these solutions to\nexplore the impact of the CBD theory on the large scale structure by studying\nthe dynamics of its linear perturbations. We observe a growing behavior of the\nlensing potential $\\Phi_{+}$ at late-times, while the growth rate is actually\nsuppressed relatively to $\\Lambda$CDM, which allows the CBD theory to provide a\ncompetitive fit to current RSD measurements of $f\\sigma_{8}$. However, we also\nobserve that the theory exhibits a pathological change of sign in the effective\ngravitational constant concerning the perturbations on sub-horizon scales that\ncould pose a challenge to its validity.\n",
"title": "Dynamics of cosmological perturbations in modified Brans-Dicke cosmology with matter-scalar field interaction"
}
| null | null | null | null | true | null |
5084
| null |
Default
| null | null |
null |
{
"abstract": " Speech emotion recognition is an important and challenging task in the realm\nof human-computer interaction. Prior work proposed a variety of models and\nfeature sets for training a system. In this work, we conduct extensive\nexperiments using an attentive convolutional neural network with multi-view\nlearning objective function. We compare system performance using different\nlengths of the input signal, different types of acoustic features and different\ntypes of emotion speech (improvised/scripted). Our experimental results on the\nInteractive Emotional Motion Capture (IEMOCAP) database reveal that the\nrecognition performance strongly depends on the type of speech data independent\nof the choice of input features. Furthermore, we achieved state-of-the-art\nresults on the improvised speech data of IEMOCAP.\n",
"title": "Attentive Convolutional Neural Network based Speech Emotion Recognition: A Study on the Impact of Input Features, Signal Length, and Acted Speech"
}
| null | null | null | null | true | null |
5085
| null |
Default
| null | null |
null |
{
"abstract": " We present a quantitative analysis of human word association pairs and study\nthe types of relations presented in the associations. We put our main focus on\nthe correlation between response types and respondent characteristics such as\noccupation and gender by contrasting syntagmatic and paradigmatic associations.\nFinally, we propose a personalised distributed word association model and show\nthe importance of incorporating demographic factors into the models commonly\nused in natural language processing.\n",
"title": "Men Are from Mars, Women Are from Venus: Evaluation and Modelling of Verbal Associations"
}
| null | null | null | null | true | null |
5086
| null |
Default
| null | null |
null |
{
"abstract": " Recent observations show a population of active galaxies with milliarcseconds\noffsets between optical and radio emission. Such offsets can be an indication\nof extreme phenomena associated with supermassive black holes including\nrelativistic jets, binary supermassive black holes, or even recoiling\nsupermassive black holes. However, the multi-wavelength structure of active\ngalaxies at a few milliarcseconds cannot be fathomed with direct observations.\nWe propose using strong gravitational lensing to elucidate the multi-wavelength\nstructure of sources. When sources are located close to the caustic of lensing\ngalaxy, even small offset in the position of the sources results in a drastic\ndifference in the position and magnification of mirage images. We show that the\nangular offset in the position of the sources can be amplified more than 50\ntimes in the observed position of mirage images. We find that at least 8% of\nthe observed gravitationally lensed quasars will be in the caustic\nconfiguration. The synergy between SKA and Euclid will provide an ideal set of\nobservations for thousands of gravitationally lensed sources in the caustic\nconfiguration, which will allow us to elucidate the multi-wavelength structure\nfor a large ensemble of sources, and study the physical origin of radio\nemissions, their connection to supermassive black holes, and their cosmic\nevolution.\n",
"title": "Galaxies as High-Resolution Telescopes"
}
| null | null | null | null | true | null |
5087
| null |
Default
| null | null |
null |
{
"abstract": " We show that if $X$ is an abelian variety of dimension $g \\geq 1$ and\n${\\mathcal E}$ is an M-regular coherent sheaf on $X$, the Castelnuovo-Mumford\nregularity of ${\\mathcal E}$ with respect to an ample and globally generated\nline bundle ${\\mathcal O}(1)$ on $X$ is at most $g$, and that equality is\nobtained when ${\\mathcal E}^{\\vee}(1)$ is continuously globally generated. As\nan application, we give a numerical characterization of ample semihomogeneous\nvector bundles for which this bound is attained.\n",
"title": "Continuous CM-regularity of semihomogeneous vector bundles"
}
| null | null | null | null | true | null |
5088
| null |
Default
| null | null |
null |
{
"abstract": " In the first chapter, we will present a computation of the square value of\nthe module of L functions associated to a Dirichlet character. This computation\nsuggests to ask if a certain ring of arithmetic multiplicative functions exists\nand if it is unique. This search has led to the construction of that ring in\nchapter two. Finally, in the third chapter, we will present some propositions\nassociated with this ring. The result below is one of the main results of this\nwork :\nFor F and G two completely multiplicative functions, $ s $ a complex number\nsuch as the dirichlet series $ D(F,s) $ and $ D(G,s) $ converge :\n$ \\forall F,G \\in \\mathbb{M}_{c} : D(F,s) \\times D(G,s) = D(F \\times G,2s)\n\\times D(F \\square G,s) $\nwhere the operation $ \\square $ is defined in chapter two as the sum of the\npreviously mentioned ring. Here are some similar versions, with $ s = x+iy $ :\n$ \\forall F, G \\in \\mathbb{M}_{c} : ~ D(F,s) \\times D(G,\\overline{s}) = D(F\n\\times G,2x) \\times D(\\frac{F}{\\text{Id}_{e}^{iy}} \\square\n\\frac{G}{\\text{Id}_{e}^{-iy}}, x) $\n$ \\forall F, G \\in \\mathbb{M}_{c} : ~ |D(F,s)|^{2} = D(|F|^{2},2x) \\times\nD(\\frac{F}{\\text{Id}_{e}^{iy}} \\square \\overline{\\frac{F}{\\text{Id}_{e}^{iy}}},\nx) $\n",
"title": "Factorisation of the product of Dirichlet series of completely multiplicative functions"
}
| null | null | null | null | true | null |
5089
| null |
Default
| null | null |
null |
{
"abstract": " Many inverse problems involve two or more sets of variables that represent\ndifferent physical quantities but are tightly coupled with each other. For\nexample, image super-resolution requires joint estimation of the image and\nmotion parameters from noisy measurements. Exploiting this structure is key for\nefficiently solving these large-scale optimization problems, which are often\nill-conditioned.\nIn this paper, we present a new method called Linearize And Project (LAP)\nthat offers a flexible framework for solving inverse problems with coupled\nvariables. LAP is most promising for cases when the subproblem corresponding to\none of the variables is considerably easier to solve than the other. LAP is\nbased on a Gauss-Newton method, and thus after linearizing the residual, it\neliminates one block of variables through projection. Due to the linearization,\nthis block can be chosen freely. Further, LAP supports direct, iterative, and\nhybrid regularization as well as constraints. Therefore LAP is attractive,\ne.g., for ill-posed imaging problems. These traits differentiate LAP from\ncommon alternatives for this type of problem such as variable projection\n(VarPro) and block coordinate descent (BCD). Our numerical experiments compare\nthe performance of LAP to BCD and VarPro using three coupled problems whose\nforward operators are linear with respect to one block and nonlinear for the\nother set of variables.\n",
"title": "LAP: a Linearize and Project Method for Solving Inverse Problems with Coupled Variables"
}
| null | null | null | null | true | null |
5090
| null |
Default
| null | null |
null |
{
"abstract": " This paper proposes a method based on signal injection to obtain the\nsaturated current-flux relations of a PMSM from locked-rotor experiments. With\nrespect to the classical method based on time integration, it has the main\nadvantage of being completely independent of the stator resistance; moreover,\nit is less sensitive to voltage biases due to the power inverter, as the\ninjected signal may be fairly large.\n",
"title": "Obtaining the Current-Flux Relations of the Saturated PMSM by Signal Injection"
}
| null | null | null | null | true | null |
5091
| null |
Default
| null | null |
null |
{
"abstract": " In this paper, we introduce Durrmeyer type modification of Meyer-Konig-Zeller\noperators based on (p,q)-integers. Rate of convergence of these operators are\nexplored with the help of Korovkin type theorems. We establish some direct\nresults for proposed operators. We also obtain statistical approximation\nproperties of operators. In last section, we show rate of convergence of\n(p,q)-Meyer-Konig-Zeller Durrmeyer operators for some functions by means of\nMatlab programming.\n",
"title": "Approximation properties of (p,q)-Meyer-Konig-Zeller Durrmeyer operators"
}
| null | null | null | null | true | null |
5092
| null |
Default
| null | null |
null |
{
"abstract": " We present Deep Graph Infomax (DGI), a general approach for learning node\nrepresentations within graph-structured data in an unsupervised manner. DGI\nrelies on maximizing mutual information between patch representations and\ncorresponding high-level summaries of graphs---both derived using established\ngraph convolutional network architectures. The learnt patch representations\nsummarize subgraphs centered around nodes of interest, and can thus be reused\nfor downstream node-wise learning tasks. In contrast to most prior approaches\nto unsupervised learning with GCNs, DGI does not rely on random walk\nobjectives, and is readily applicable to both transductive and inductive\nlearning setups. We demonstrate competitive performance on a variety of node\nclassification benchmarks, which at times even exceeds the performance of\nsupervised learning.\n",
"title": "Deep Graph Infomax"
}
| null | null | null | null | true | null |
5093
| null |
Default
| null | null |
null |
{
"abstract": " Under investigation in this paper is the nonisospectral and variable\ncoefficients modified Kortweg-de Vries (vc-mKdV) equation, which manifests in\ndiverse areas of physics such as fluid dynamics, ion acoustic solitons and\nplasma mechanics. With the degrees of restriction reduced, a simplified\nconstraint is introduced, under which the vc-mKdV equation is an integrable\nsystem and the spectral flow is time-varying. The Darboux transformation for\nsuch equation is constructed, which gives rise to the generation of variable\nkinds of solutions including the double-breather coherent structure, periodical\nsoliton-breather and localized solitons and breathers. In addition, the effect\nof variable coefficients and initial phases is discussed in terms of the\nsoliton amplitude, polarity, velocity and width, which might provide feasible\nsoliton management with certain conditions taken into account.\n",
"title": "Solitons and breathers for nonisospectral mKdV equation with Darboux transformation"
}
| null | null | null | null | true | null |
5094
| null |
Default
| null | null |
null |
{
"abstract": " We study the problem of detecting an abrupt change to the signal covariance\nmatrix. In particular, the covariance changes from a \"white\" identity matrix to\nan unknown spiked or low-rank matrix. Two sequential change-point detection\nprocedures are presented, based on the largest and the smallest eigenvalues of\nthe sample covariance matrix. To control false-alarm-rate, we present an\naccurate theoretical approximation to the average-run-length (ARL) and expected\ndetection delay (EDD) of the detection, leveraging the extreme eigenvalue\ndistributions from random matrix theory and by capturing a non-negligible\ntemporal correlation in the sequence of scan statistics due to the sliding\nwindow approach. Real data examples demonstrate the good performance of our\nmethod for detecting behavior change of a swarm.\n",
"title": "Sequential detection of low-rank changes using extreme eigenvalues"
}
| null | null | null | null | true | null |
5095
| null |
Default
| null | null |
null |
{
"abstract": " In this paper, we argue that the future of Artificial Intelligence research\nresides in two keywords: integration and embodiment. We support this claim by\nanalyzing the recent advances of the field. Regarding integration, we note that\nthe most impactful recent contributions have been made possible through the\nintegration of recent Machine Learning methods (based in particular on Deep\nLearning and Recurrent Neural Networks) with more traditional ones (e.g.\nMonte-Carlo tree search, goal babbling exploration or addressable memory\nsystems). Regarding embodiment, we note that the traditional benchmark tasks\n(e.g. visual classification or board games) are becoming obsolete as\nstate-of-the-art learning algorithms approach or even surpass human performance\nin most of them, having recently encouraged the development of first-person 3D\ngame platforms embedding realistic physics. Building upon this analysis, we\nfirst propose an embodied cognitive architecture integrating heterogenous\nsub-fields of Artificial Intelligence into a unified framework. We demonstrate\nthe utility of our approach by showing how major contributions of the field can\nbe expressed within the proposed framework. We then claim that benchmarking\nenvironments need to reproduce ecologically-valid conditions for bootstrapping\nthe acquisition of increasingly complex cognitive skills through the concept of\na cognitive arms race between embodied agents.\n",
"title": "Embodied Artificial Intelligence through Distributed Adaptive Control: An Integrated Framework"
}
| null | null | null | null | true | null |
5096
| null |
Default
| null | null |
null |
{
"abstract": " Several theories of the glass transition propose that the structural\nrelaxation time {\\tau}{\\alpha} is controlled by a growing static length scale\n{\\xi} that is determined by the free energy landscape but not by the local\ndynamical rules governing its exploration. We argue, based on recent\nsimulations using particle-radius-swap dynamics, that only a modest factor in\nthe increase in {\\tau}{\\alpha} on approach to the glass transition may stem\nfrom the growth of a static length, with a vastly larger contribution\nattributable instead to a slowdown of local dynamics. This reinforces arguments\nthat we base on the observed strong coupling of particle diffusion and density\nfluctuations in real glasses\n",
"title": "Does a growing static length scale control the glass transition?"
}
| null | null | null | null | true | null |
5097
| null |
Default
| null | null |
null |
{
"abstract": " In 1983 Takeuchi showed that up to conjugation there are exactly 4 arithmetic\nsubgroups of $\\textrm{PSL}_2 (\\mathbb{R})$ with signature $(1; \\infty)$.\nShinichi Mochizuki gave a purely geometric characterization of the\ncorresponding arithmetic $(1; \\infty)$-curves, which also arise naturally in\nthe context of his recent work on inter-universal Teichmüller theory.\nUsing Bely\\u{\\i} maps, we explicitly determine the canonical models of these\ncurves. We also study their arithmetic properties and modular interpretations.\n",
"title": "Canonical models of arithmetic $(1; \\infty)$ curves"
}
| null | null |
[
"Mathematics"
] | null | true | null |
5098
| null |
Validated
| null | null |
null |
{
"abstract": " A large variety of dynamical systems, such as chemical and biomolecular\nsystems, can be seen as networks of nonlinear entities. Prediction, control,\nand identification of such nonlinear networks require knowledge of the state of\nthe system. However, network states are usually unknown, and only a fraction of\nthe state variables are directly measurable. The observability problem concerns\nreconstructing the network state from this limited information. Here, we\npropose a general optimization-based approach for observing the states of\nnonlinear networks and for optimally selecting the observed variables. Our\nresults reveal several fundamental limitations in network observability, such\nas the trade-off between the fraction of observed variables and the observation\nlength on one side, and the estimation error on the other side. We also show\nthat owing to the crucial role played by the dynamics, purely graph- theoretic\nobservability approaches cannot provide conclusions about one's practical\nability to estimate the states. We demonstrate the effectiveness of our methods\nby finding the key components in biological and combustion reaction networks\nfrom which we determine the full system state. Our results can lead to the\ndesign of novel sensing principles that can greatly advance prediction and\ncontrol of the dynamics of such networks.\n",
"title": "State observation and sensor selection for nonlinear networks"
}
| null | null |
[
"Computer Science",
"Mathematics"
] | null | true | null |
5099
| null |
Validated
| null | null |
null |
{
"abstract": " Run-length encoding Burrows-Wheeler Transformed strings, resulting in\nRun-Length BWT (RLBWT), is a powerful tool for processing highly repetitive\nstrings. We propose a new algorithm for online RLBWT working in run-compressed\nspace, which runs in $O(n\\lg r)$ time and $O(r\\lg n)$ bits of space, where $n$\nis the length of input string $S$ received so far and $r$ is the number of runs\nin the BWT of the reversed $S$. We improve the state-of-the-art algorithm for\nonline RLBWT in terms of empirical construction time. Adopting the dynamic list\nfor maintaining a total order, we can replace rank queries in a dynamic wavelet\ntree on a run-length compressed string by the direct comparison of labels in a\ndynamic list. The empirical result for various benchmarks show the efficiency\nof our algorithm, especially for highly repetitive strings.\n",
"title": "A Faster Implementation of Online Run-Length Burrows-Wheeler Transform"
}
| null | null | null | null | true | null |
5100
| null |
Default
| null | null |
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