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null | prediction_agent
null | annotation
list | annotation_agent
null | multi_label
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{
"abstract": " Deep Neural Networks (DNNs) are universal function approximators providing\nstate-of- the-art solutions on wide range of applications. Common perceptual\ntasks such as speech recognition, image classification, and object tracking are\nnow commonly tackled via DNNs. Some fundamental problems remain: (1) the lack\nof a mathematical framework providing an explicit and interpretable\ninput-output formula for any topology, (2) quantification of DNNs stability\nregarding adversarial examples (i.e. modified inputs fooling DNN predictions\nwhilst undetectable to humans), (3) absence of generalization guarantees and\ncontrollable behaviors for ambiguous patterns, (4) leverage unlabeled data to\napply DNNs to domains where expert labeling is scarce as in the medical field.\nAnswering those points would provide theoretical perspectives for further\ndevelopments based on a common ground. Furthermore, DNNs are now deployed in\ntremendous societal applications, pushing the need to fill this theoretical gap\nto ensure control, reliability, and interpretability.\n",
"title": "Deep Neural Networks"
}
| null | null | null | null | true | null |
10501
| null |
Default
| null | null |
null |
{
"abstract": " The International Rosetta Mission was launched in 2004 and consists of the\norbiter spacecraft Rosetta and the lander Philae. The aim of the mission is to\nmap the comet 67P Churyumov Gerasimenko by remote sensing, to examine its\nenvironment insitu and its evolution in the inner solar system.Rosetta was the\nfirst spacecraft to rendezvous and orbit a comet, accompanying it as it passes\nthrough the inner solar system, and to deploy a lander, Philae and perform in\nsitu science on the comet surface. The primary goals of the mission were to:\ncharacterize the comets nucleus; examine the chemical, mineralogical and\nisotopic composition of volatiles and refractories; examine the physical\nproperties and interrelation of volatiles and refractories in a cometary\nnucleus; study the development of cometary activity and the processes in the\nsurface layer of the nucleus and in the coma; detail the origin of comets, the\nrelationship between cometary and interstellar material and the implications\nfor the origin of the solar system; characterize asteroids, 2867 Steins and 21\nLutetia. This paper presents a summary of mission operations and science,\nfocusing on the Rosetta orbiter component of the mission during its comet\nphase, from early 2014 up to September 2016.\n",
"title": "The Rosetta mission orbiter Science overview the comet phase"
}
| null | null |
[
"Physics"
] | null | true | null |
10502
| null |
Validated
| null | null |
null |
{
"abstract": " We describe a new cardinality estimation algorithm that is extremely\nspace-efficient. It applies one of three novel estimators to the compressed\nstate of the Flajolet-Martin-85 coupon collection process. In an\napples-to-apples empirical comparison against compressed HyperLogLog sketches,\nthe new algorithm simultaneously wins on all three dimensions of the\ntime/space/accuracy tradeoff. Our prototype uses the zstd compression library,\nand produces sketches that are smaller than the entropy of HLL, so no possible\nimplementation of compressed HLL can match its space efficiency. The paper's\ntechnical contributions include analyses and simulations of the three new\nestimators, accurate values for the entropies of FM85 and HLL, and a\nnon-trivial method for estimating a double asymptotic limit via simulation.\n",
"title": "Back to the Future: an Even More Nearly Optimal Cardinality Estimation Algorithm"
}
| null | null | null | null | true | null |
10503
| null |
Default
| null | null |
null |
{
"abstract": " Object tracking systems play important roles in tracking moving objects and\novercoming problems such as safety, security and other location-related\napplications. Problems arise from the difficulties in creating a well-defined\nand understandable description of tracking systems. Nowadays, describing such\nprocesses results in fragmental representation that most of the time leads to\ndifficulties creating documentation. Additionally, once learned by assigned\npersonnel, repeated tasks result in them continuing on autopilot in a way that\noften degrades their effectiveness. This paper proposes the modeling of\ntracking systems in terms of a new diagrammatic methodology to produce\nengineering-like schemata. The resultant diagrams can be used in documentation,\nexplanation, communication, education and control.\n",
"title": "Tracking Systems as Thinging Machine: A Case Study of a Service Company"
}
| null | null | null | null | true | null |
10504
| null |
Default
| null | null |
null |
{
"abstract": " Using the NASA/IRTF SpeX & BASS spectrometers we have obtained novel 0.7 - 13\num observations of the newly imaged HD36546 debris disk system. The SpeX\nspectrum is most consistent with the photospheric emission expected from an\nLstar ~ 20 Lsun, solar abundance A1.5V star with little/no extinction and\nexcess emission from circumstellar dust detectable beyond 4.5 um.\nNon-detections of CO emission lines and accretion signatures point to the gas\npoor circumstellar environment of a very old transition disk. Combining the\nSpeX and BASS spectra with archival WISE/AKARI/IRAS/Herschel photometery, we\nfind an outer cold dust belt at ~135K and 20 - 40 AU from the primary, likely\ncoincident with the disk imaged by Subaru (Currie et al. 2017), and a new\nsecond inner belt with temperature ~570K and an unusual, broad SED maximum in\nthe 6 - 9 um region, tracing dust at 1.1 - 2.2 AU. An SED maximum at 6 - 9 um\nhas been reported in just two other A-star systems, HD131488 and HD121191, both\nof ~10 Myr age (Melis et al. 2013). From Spitzer, we have also identified the\n~12 Myr old A7V HD148567 system as having similar 5 - 35 um excess spectral\nfeatures (Mittal et al. 2015). The Spitzer data allows us to rule out water\nemission and rule in carbonaceous materials - organics, carbonates, SiC - as\nthe source of the 6 - 9 um excess. Assuming a common origin for the 4 young\nAstar systems' disks, we suggest they are experiencing an early era of\ncarbon-rich planetesimal processing.\n",
"title": "Spectral Evidence for an Inner Carbon-Rich Circumstellar Dust Belt in the Young HD36546 A-Star System"
}
| null | null | null | null | true | null |
10505
| null |
Default
| null | null |
null |
{
"abstract": " The flyby anomaly is the unexpected variation of the asymptotic\npost-encounter velocity of a spacecraft with respect to the pre-encounter\nvelocity as it performs a slingshot manoeuvre. This effect has been detected\nin, at least, six flybys of the Earth but it has not appeared in other recent\nflybys. In order to find a pattern in these, apparently contradictory, data\nseveral phenomenological formulas have been proposed but all have failed to\npredict a new result in agreement with the observations. In this paper we use a\nmultivariate dimensional analysis approach to propose a fitting of the data in\nterms of the local parameters at perigee, as it would occur if this anomaly\ncomes from an unknown fifth force with latitude dependence. Under this\nassumption, we estimate the range of this force around 300 km.\n",
"title": "The flyby anomaly: A multivariate analysis approach"
}
| null | null | null | null | true | null |
10506
| null |
Default
| null | null |
null |
{
"abstract": " Two dimensional (2D) materials provide a unique platform for spintronics and\nvalleytronics due to the ability to combine vastly different functionalities\ninto one vertically-stacked heterostructure, where the strengths of each of the\nconstituent materials can compensate for the weaknesses of the others. Graphene\nhas been demonstrated to be an exceptional material for spin transport at room\ntemperature, however it lacks a coupling of the spin and optical degrees of\nfreedom. In contrast, spin/valley polarization can be efficiently generated in\nmonolayer transition metal dichalcogenides (TMD) such as MoS2 via absorption of\ncircularly-polarized photons, but lateral spin or valley transport has not been\nrealized at room temperature. In this letter, we fabricate monolayer\nMoS2/few-layer graphene hybrid spin valves and demonstrate, for the first time,\nthe opto-valleytronic spin injection across a TMD/graphene interface. We\nobserve that the magnitude and direction of spin polarization is controlled by\nboth helicity and photon energy. In addition, Hanle spin precession\nmeasurements confirm optical spin injection, spin transport, and electrical\ndetection up to room temperature. Finally, analysis by a one-dimensional\ndrift-diffusion model quantifies the optically injected spin current and the\nspin transport parameters. Our results demonstrate a 2D spintronic/valleytronic\nsystem that achieves optical spin injection and lateral spin transport at room\ntemperature in a single device, which paves the way for multifunctional 2D\nspintronic devices for memory and logic applications.\n",
"title": "Opto-Valleytronic Spin Injection in Monolayer MoS2/Few-Layer Graphene Hybrid Spin Valves"
}
| null | null | null | null | true | null |
10507
| null |
Default
| null | null |
null |
{
"abstract": " We consider the incompressible Euler and Navier-Stokes equations in a\nthree-dimensional moving thin domain. Under the assumption that the moving thin\ndomain degenerates into a two-dimensional moving closed surface as the width of\nthe thin domain goes to zero, we give a heuristic derivation of singular limit\nequations on the degenerate moving surface of the Euler and Navier-Stokes\nequations in the moving thin domain and investigate relations between their\nenergy structures. We also compare the limit equations with the Euler and\nNavier-Stokes equations on a stationary manifold, which are described in terms\nof the Levi-Civita connection.\n",
"title": "On singular limit equations for incompressible fluids in moving thin domains"
}
| null | null |
[
"Physics",
"Mathematics"
] | null | true | null |
10508
| null |
Validated
| null | null |
null |
{
"abstract": " Wheeled ground robots are limited from exploring extreme environments such as\ncaves, lava tubes and skylights. Small robots that utilize unconventional\nmobility through hopping, flying and rolling can overcome many roughness\nlimitations and thus extend exploration sites of interest on Moon and Mars. In\nthis paper we introduce a network of 3 kg, 0.30 m diameter ball robots\n(pit-bots) that can fly, hop and roll using an onboard miniature propulsion\nsystem. These pit-bots can be deployed from a lander or large rover. Each robot\nis equipped with a smartphone sized computer, stereo camera and laser\nrangefinder to per-form navigation and mapping. The ball robot can carry a\npayload of 1 kg or perform sample return. Our studies show a range of 5 km and\n0.7 hours flight time on the Moon.\n",
"title": "Flying, Hopping Pit-Bots for Cave and Lava Tube Exploration on the Moon and Mars"
}
| null | null | null | null | true | null |
10509
| null |
Default
| null | null |
null |
{
"abstract": " Currently, lower limb robotic rehabilitation is widely developed, However,\nthe devices used so far seem to not have a uniform criteria for their design,\nbecause, on the contrary, each developed mechanism is often presented as if it\ndoes not take into account the criteria used in previous designs. On the other\nhand, the diagnosis of lower limb from robotic devices has been little studied.\nThis chapter presents a guide for the design of robotic devices in diagnosis of\nlower limbs, taking into account the mobility of the human leg and the\ntechniques used by physiotherapists in the execution of exercises and the\nrehabilitation of rehabilitation and diagnosis tests, as well as the\nrecommendations made by various authors, among other aspects. The proposed\nguide is illustrated through a case study based on a parallel robot RPU+3UPS\nable to make movements that are applied during the processes of rehabilitation\nand diagnosis. The proposal presents advantages over some existing devices such\nas its load capacity that can support, and also allows you to restrict the\nmovement in directions required by the rehabilitation and the diagnosis\nmovements.\n",
"title": "Design of a Robotic System for Diagnosis and Rehabilitation of Lower Limbs"
}
| null | null |
[
"Computer Science",
"Physics"
] | null | true | null |
10510
| null |
Validated
| null | null |
null |
{
"abstract": " Tetrachiral materials are characterized by a cellular microstructure made by\na periodic pattern of stiff rings and flexible ligaments. Their mechanical\nbehaviour can be described by a planar lattice of rigid massive bodies and\nelastic massless beams. The periodic cell dynamics is governed by a monoatomic\nstructural model, conveniently reduced to the only active degrees-of-freedom.\nThe paper presents an explicit parametric description of the band structure\ngoverning the free propagation of elastic waves. By virtue of multiparametric\nperturbation techniques, sensitivity analyses are performed to achieve\nanalytical asymptotic approximation of the dispersion functions. The parametric\nconditions for the existence of full band gaps in the low-frequency range are\nestablished. Furthermore, the band gap amplitude is analytically assessed in\nthe admissible parameter range. In tetrachiral acoustic metamaterials, stop\nbands can be opened by the introduction of intra-ring resonators. Perturbation\nmethods can efficiently deal with the consequent enlargement of the mechanical\nparameter space. Indeed high-accuracy parametric approximations are achieved\nfor the band structure, enriched by the new optical branches related to the\nresonator frequencies. In particular, target stop bands in the metamaterial\nspectrum are analytically designed through the asymptotic solution of inverse\nspectral problems.\n",
"title": "Multi-parametric sensitivity analysis of the band structure for tetrachiral acoustic metamaterials"
}
| null | null | null | null | true | null |
10511
| null |
Default
| null | null |
null |
{
"abstract": " Twitter has provided a great opportunity for public libraries to disseminate\ninformation for a variety of purposes. Twitter data have been applied in\ndifferent domains such as health, politics, and history. There are thousands of\npublic libraries in the US, but no study has yet investigated the content of\ntheir social media posts like tweets to find their interests. Moreover,\ntraditional content analysis of Twitter content is not an efficient task for\nexploring thousands of tweets. Therefore, there is a need for automatic methods\nto overcome the limitations of manual methods. This paper proposes a\ncomputational approach to collecting and analyzing using Twitter Application\nProgramming Interfaces (API) and investigates more than 138,000 tweets from 48\nUS west coast libraries using topic modeling. We found 20 topics and assigned\nthem to five categories including public relations, book, event, training, and\nsocial good. Our results show that the US west coast libraries are more\ninterested in using Twitter for public relations and book-related events. This\nresearch has both practical and theoretical applications for libraries as well\nas other organizations to explore social media actives of their customer and\nthemselves.\n",
"title": "What do the US West Coast Public Libraries Post on Twitter?"
}
| null | null | null | null | true | null |
10512
| null |
Default
| null | null |
null |
{
"abstract": " Dynamic Boltzmann Machine (DyBM) has been shown highly efficient to predict\ntime-series data. Gaussian DyBM is a DyBM that assumes the predicted data is\ngenerated by a Gaussian distribution whose first-order moment (mean)\ndynamically changes over time but its second-order moment (variance) is fixed.\nHowever, in many financial applications, the assumption is quite limiting in\ntwo aspects. First, even when the data follows a Gaussian distribution, its\nvariance may change over time. Such variance is also related to important\ntemporal economic indicators such as the market volatility. Second, financial\ntime-series data often requires learning datasets generated by the generalized\nGaussian distribution with an additional shape parameter that is important to\napproximate heavy-tailed distributions. Addressing those aspects, we show how\nto extend DyBM that results in significant performance improvement in\npredicting financial time-series data.\n",
"title": "Dynamic Boltzmann Machines for Second Order Moments and Generalized Gaussian Distributions"
}
| null | null | null | null | true | null |
10513
| null |
Default
| null | null |
null |
{
"abstract": " Discussed here are the effects of basics graph transformations on the spectra\nof associated quantum graphs. In particular it is shown that under an edge\nswitch the spectrum of the transformed Schrödinger operator is interlaced\nwith that of the original one. By implication, under edge swap the spectra\nbefore and after the transformation, denoted by $\\{ E_n\\}_{n=1}^{\\infty}$ and\n$\\{\\widetilde E_n\\}_{n=1}^{\\infty}$ correspondingly, are level-2 interlaced, so\nthat $E_{n-2}\\le \\widetilde E_n\\le E_{n+2}$. The proofs are guided by\nconsiderations of the quantum graphs' discrete analogs.\n",
"title": "Edge switching transformations of quantum graphs"
}
| null | null | null | null | true | null |
10514
| null |
Default
| null | null |
null |
{
"abstract": " In this paper, we focus on applications in machine learning, optimization,\nand control that call for the resilient selection of a few elements, e.g.\nfeatures, sensors, or leaders, against a number of adversarial\ndenial-of-service attacks or failures. In general, such resilient optimization\nproblems are hard, and cannot be solved exactly in polynomial time, even though\nthey often involve objective functions that are monotone and submodular.\nNotwithstanding, in this paper we provide the first scalable,\ncurvature-dependent algorithm for their approximate solution, that is valid for\nany number of attacks or failures, and which, for functions with low curvature,\nguarantees superior approximation performance. Notably, the curvature has been\nknown to tighten approximations for several non-resilient maximization\nproblems, yet its effect on resilient maximization had hitherto been unknown.\nWe complement our theoretical analyses with supporting empirical evaluations.\n",
"title": "Resilient Monotone Submodular Function Maximization"
}
| null | null | null | null | true | null |
10515
| null |
Default
| null | null |
null |
{
"abstract": " This paper presents a laser amplifier based on an antireflection coated laser\ndiode. This laser amplifier operates without active temperature stabilisation\nat any wavelength within its gain profile without restrictions on the injection\ncurrent. Using a active feedback from an external detector to the laser current\nthe power stabilized to better than $10^{-4}$, even after additional optical\nelements such as an optical fiber and/or a polarization cleaner. This power can\nalso be modulated and tuned arbitrarily. In the absence of the seeding light,\nthe laser amplifier does not lase, thus resulting in an extremely simple setup,\nwhich requires neither an external Fabry Perot cavity for monitoring the mode\npurity nor a temperature stabilization.\n",
"title": "Antireflection Coated Semiconductor Laser Amplifier"
}
| null | null | null | null | true | null |
10516
| null |
Default
| null | null |
null |
{
"abstract": " In this paper we study entire radial solutions for the quasilinear\n$p$-Laplace equation $\\Delta_p u + k(x) f(u) = 0$ where $k$ is a radial\npositive weight and the nonlinearity behaves e.g. as\n$f(u)=u|u|^{q-2}-u|u|^{Q-2}$ with $q<Q$. In particular we focus our attention\non solutions (positive and sign changing) which are infinitesimal at infinity,\nthus providing an extension of a previous result by Tang (2001).\n",
"title": "On the structure of radial solutions for some quasilinear elliptic equations"
}
| null | null | null | null | true | null |
10517
| null |
Default
| null | null |
null |
{
"abstract": " Automatically detecting sound units of humpback whales in complex\ntime-varying background noises is a current challenge for scientists. In this\npaper, we explore the applicability of Convolution Neural Network (CNN) method\nfor this task. In the evaluation stage, we present 6 bi-class classification\nexperimentations of whale sound detection against different background noise\ntypes (e.g., rain, wind). In comparison to classical FFT-based representation\nlike spectrograms, we showed that the use of image-based pretrained CNN\nfeatures brought higher performance to classify whale sounds and background\nnoise.\n",
"title": "Bi-class classification of humpback whale sound units against complex background noise with Deep Convolution Neural Network"
}
| null | null | null | null | true | null |
10518
| null |
Default
| null | null |
null |
{
"abstract": " Given an input string s and a specific Lindenmayer system (the so-called\nFibonacci grammar), we define an automaton which is capable of (i) determining\nwhether s belongs to the set of strings that the Fibonacci grammar can generate\n(in other words, if s corresponds to a generation of the grammar) and, if so,\n(ii) reconstructing the previous generation.\n",
"title": "A model for a Lindenmayer reconstruction algorithm"
}
| null | null | null | null | true | null |
10519
| null |
Default
| null | null |
null |
{
"abstract": " The generalization of the multi-scale entanglement renormalization ansatz\n(MERA) to continuous systems, or cMERA [Haegeman et al., Phys. Rev. Lett, 110,\n100402 (2013)], is expected to become a powerful variational ansatz for the\nground state of strongly interacting quantum field theories. In this paper we\ninvestigate, in the simpler context of Gaussian cMERA for free theories, the\nextent to which the cMERA state $|\\Psi^\\Lambda\\rangle$ with finite UV cut-off\n$\\Lambda$ can capture the spacetime symmetries of the ground state\n$|\\Psi\\rangle$. For a free boson conformal field theory (CFT) in 1+1 dimensions\nas a concrete example, we build a quasi-local unitary transformation $V$ that\nmaps $|\\Psi\\rangle$ into $|\\Psi^\\Lambda\\rangle$ and show two main results. (i)\nAny spacetime symmetry of the ground state $|\\Psi\\rangle$ is also mapped by $V$\ninto a spacetime symmetry of the cMERA $|\\Psi^\\Lambda\\rangle$. However, while\nin the CFT the stress-energy tensor $T_{\\mu\\nu}(x)$ (in terms of which all the\nspacetime symmetry generators are expressed) is local, the corresponding cMERA\nstress-energy tensor $T_{\\mu\\nu}^{\\Lambda}(x) = V T_{\\mu\\nu}(x) V^{\\dagger}$ is\nquasi-local. (ii) From the cMERA, we can extract quasi-local scaling operators\n$O^{\\Lambda}_{\\alpha}(x)$ characterized by the exact same scaling dimensions\n$\\Delta_{\\alpha}$, conformal spins $s_{\\alpha}$, operator product expansion\ncoefficients $C_{\\alpha\\beta\\gamma}$, and central charge $c$ as the original\nCFT. Finally, we argue that these results should also apply to interacting\ntheories.\n",
"title": "Spacetime symmetries and conformal data in the continuous multi-scale entanglement renormalization ansatz"
}
| null | null | null | null | true | null |
10520
| null |
Default
| null | null |
null |
{
"abstract": " Geo-tags from micro-blog posts have been shown to be useful in many data\nmining applications. This work seeks to find out if the location type derived\nfrom these geo-tags can benefit input methods, which attempts to predict the\nnext word a user will input during typing. If a correlation between different\nlocation types and a change in word distribution can be found, the location\ntype information can be used to make the input method more accurate. This work\nqueried micro-blog posts from Twitter API and location type of these posts from\nGoogle Place API, forming a dataset of around 500k samples. A statistical study\non the word distribution found weak support for the assumption. An LSTM based\nprediction experiment found a 2% edge in the accuracy from language models\nleveraging location type information when compared to a baseline without that\ninformation.\n",
"title": "Augmenting Input Method Language Model with user Location Type Information"
}
| null | null | null | null | true | null |
10521
| null |
Default
| null | null |
null |
{
"abstract": " The aim of the present paper is to contribute to the development of the study\nof Cauchy problems involving Riemann-Liouville and Caputo fractional\nderivatives. Firstly existence-uniqueness results for solutions of non-linear\nCauchy problems with vector fractional multi-order are addressed. A qualitative\nresult about the behavior of local but non-global solutions is also provided.\nFinally the major aim of this paper is to introduce notions of fractional\nstate-transition matrices and to derive fractional versions of the classical\nDuhamel formula. We also prove duality theorems relying left state-transition\nmatrices with right state-transition matrices.\n",
"title": "Cauchy-Lipschitz theory for fractional multi-order dynamics -- State-transition matrices, Duhamel formulas and duality theorems"
}
| null | null | null | null | true | null |
10522
| null |
Default
| null | null |
null |
{
"abstract": " For symmetric Lévy processes, if the local times exist, the Tanaka formula\nhas already constructed via the techniques in the potential theory by Salminen\nand Yor (2007). In this paper, we study the Tanaka formula for arbitrary\nstrictly stable processes with index $\\alpha \\in (1,2)$ including spectrally\npositive and negative cases in a framework of Itô's stochastic calculus. Our\napproach to the existence of local times for such processes is different from\nBertoin (1996).\n",
"title": "Tanaka formula for strictly stable processes"
}
| null | null | null | null | true | null |
10523
| null |
Default
| null | null |
null |
{
"abstract": " We study the classical complexity of the exact Boson Sampling problem where\nthe objective is to produce provably correct random samples from a particular\nquantum mechanical distribution. The computational framework was proposed by\nAaronson and Arkhipov in 2011 as an attainable demonstration of `quantum\nsupremacy', that is a practical quantum computing experiment able to produce\noutput at a speed beyond the reach of classical (that is non-quantum) computer\nhardware. Since its introduction Boson Sampling has been the subject of intense\ninternational research in the world of quantum computing. On the face of it,\nthe problem is challenging for classical computation. Aaronson and Arkhipov\nshow that exact Boson Sampling is not efficiently solvable by a classical\ncomputer unless $P^{\\#P} = BPP^{NP}$ and the polynomial hierarchy collapses to\nthe third level.\nThe fastest known exact classical algorithm for the standard Boson Sampling\nproblem takes $O({m + n -1 \\choose n} n 2^n )$ time to produce samples for a\nsystem with input size $n$ and $m$ output modes, making it infeasible for\nanything but the smallest values of $n$ and $m$. We give an algorithm that is\nmuch faster, running in $O(n 2^n + \\operatorname{poly}(m,n))$ time and $O(m)$\nadditional space. The algorithm is simple to implement and has low constant\nfactor overheads. As a consequence our classical algorithm is able to solve the\nexact Boson Sampling problem for system sizes far beyond current photonic\nquantum computing experimentation, thereby significantly reducing the\nlikelihood of achieving near-term quantum supremacy in the context of Boson\nSampling.\n",
"title": "The Classical Complexity of Boson Sampling"
}
| null | null | null | null | true | null |
10524
| null |
Default
| null | null |
null |
{
"abstract": " We study the carrier transport and magnetic properties of group-IV-based\nferromagnetic semiconductor Ge1-xFex thin films (Fe concentration x = 2.3 - 14\n%) with and without boron (B) doping, by measuring their transport\ncharacteristics; the temperature dependence of resistivity, hole concentration,\nmobility, and the relation between the anomalous Hall conductivity versus\nconductivity. At relatively low x (= 2.3 %), the transport in the undoped\nGe1-xFex film is dominated by hole hopping between Fe-rich hopping sites in the\nFe impurity band, whereas that in the B-doped Ge1-xFex film is dominated by the\nholes in the valence band in the degenerated Fe-poor regions. As x increases (x\n= 2.3 - 14 %), the transport in the both undoped and B-doped Ge1-xFex films is\ndominated by hole hopping between the Fe-rich hopping sites of the impurity\nband. The magnetic properties of the Ge1-xFex films are studied by various\nmethods including magnetic circular dichroism, magnetization and anomalous Hall\nresistance, and are not influenced by B-doping. We show band profile models of\nboth undoped and B-doped Ge1-xFex films, which can explain the transport and\nthe magnetic properties of the Ge1-xFex films.\n",
"title": "Impurity band conduction in group-IV ferromagnetic semiconductor Ge1-xFex with nanoscale fluctuations in Fe concentration"
}
| null | null | null | null | true | null |
10525
| null |
Default
| null | null |
null |
{
"abstract": " The purpose of this note is to attract attention to the following conjecture\n(metastable $r$-fold Whitney trick) by clarifying its status as not having a\ncomplete proof, in the sense described in the paper.\nAssume that $D=D_1\\sqcup\\ldots\\sqcup D_r$ is disjoint union of $r$ disks of\ndimension $s$, $f:D\\to B^d$ a proper PL map such that $f\\partial\nD_1\\cap\\ldots\\cap f\\partial D_r=\\emptyset$, $rd\\ge (r+1)s+3$ and $d\\ge s+3$. If\nthe map $$f^r:\\partial(D_1\\times\\ldots\\times D_r)\\to\n(B^d)^r-\\{(x,x,\\ldots,x)\\in(B^d)^r\\ |\\ x\\in B^d\\}$$ extends to\n$D_1\\times\\ldots\\times D_r$, then there is a PL map $\\overline f:D\\to B^d$ such\nthat $$\\overline f=f \\quad\\text{on}\\quad D_r\\cup\\partial D\\quad\\text{and}\\quad\n\\overline fD_1\\cap\\ldots\\cap \\overline fD_r=\\emptyset.$$\n",
"title": "On the metastable Mabillard-Wagner conjecture"
}
| null | null | null | null | true | null |
10526
| null |
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| null | null |
null |
{
"abstract": " Which studies, theories, and ideas have influenced Eugene Garfield's\nscientific work? Recently, the method reference publication year spectroscopy\n(RPYS) has been introduced, which can be used to answer this and related\nquestions. Since then, several studies have been published dealing with the\nhistorical roots of research fields and scientists. The program CRExplorer\n(this http URL) was specifically developed for RPYS. In this study,\nwe use this program to investigate the historical roots of Eugene Garfield's\noeuvre.\n",
"title": "Reference Publication Year Spectroscopy (RPYS) of Eugene Garfield's publications"
}
| null | null | null | null | true | null |
10527
| null |
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| null | null |
null |
{
"abstract": " In this paper, we focus on online representation learning in non-stationary\nenvironments which may require continuous adaptation of model architecture. We\npropose a novel online dictionary-learning (sparse-coding) framework which\nincorporates the addition and deletion of hidden units (dictionary elements),\nand is inspired by the adult neurogenesis phenomenon in the dentate gyrus of\nthe hippocampus, known to be associated with improved cognitive function and\nadaptation to new environments. In the online learning setting, where new input\ninstances arrive sequentially in batches, the neuronal-birth is implemented by\nadding new units with random initial weights (random dictionary elements); the\nnumber of new units is determined by the current performance (representation\nerror) of the dictionary, higher error causing an increase in the birth rate.\nNeuronal-death is implemented by imposing l1/l2-regularization (group sparsity)\non the dictionary within the block-coordinate descent optimization at each\niteration of our online alternating minimization scheme, which iterates between\nthe code and dictionary updates. Finally, hidden unit connectivity adaptation\nis facilitated by introducing sparsity in dictionary elements. Our empirical\nevaluation on several real-life datasets (images and language) as well as on\nsynthetic data demonstrates that the proposed approach can considerably\noutperform the state-of-art fixed-size (nonadaptive) online sparse coding of\nMairal et al. (2009) in the presence of nonstationary data. Moreover, we\nidentify certain properties of the data (e.g., sparse inputs with nearly\nnon-overlapping supports) and of the model (e.g., dictionary sparsity)\nassociated with such improvements.\n",
"title": "Neurogenesis-Inspired Dictionary Learning: Online Model Adaption in a Changing World"
}
| null | null | null | null | true | null |
10528
| null |
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| null | null |
null |
{
"abstract": " Recent pump-probe experiments reported an enhancement of superconducting\ntransport along the $c$-axis of underdoped YBa$_2$Cu$_3$O$_{6+\\delta}$ (YBCO),\ninduced by a mid-infrared optical pump pulse tuned to a specific lattice\nvibration. To understand this transient non-equilibrium state, we develop a\npump-probe formalism for a stack of Josephson junctions, and we consider the\ntunneling strengths in presence of modulation with an ultrashort optical pulse.\nWe demonstrate that a transient enhancement of the Josephson coupling can be\nobtained for pulsed excitation and that this can be even larger than in a\ncontinuously driven steady-state. Especially interesting is the conclusion that\nthe effect is largest when the material is parametrically driven at a frequency\nimmediately above the plasma frequency, in agreement with what is found\nexperimentally. For bilayer Josephson junctions, an enhancement similar to that\nexperimentally is predicted below the critical temperature $T_c$. This model\nreproduces the essential features of the enhancement measured below $T_c$. To\nreproduce the experimental results above $T_c$, we will explore extensions of\nthis model, such as in-plane and amplitude fluctuations, elsewhere.\n",
"title": "Transiently enhanced interlayer tunneling in optically driven high $T_c$ superconductors"
}
| null | null | null | null | true | null |
10529
| null |
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| null | null |
null |
{
"abstract": " With the advent of modern communications systems, much attention has been put\non developing methods for securely transferring information between\nconstituents of wireless sensor networks. To this effect, we introduce a\nmathematical programming formulation for the key management problem, which\nbroadly serves as a mechanism for encrypting communications. In particular, an\ninteger programming model of the q-Composite scheme is proposed and utilized to\ndistribute keys among nodes of a network whose topology is known. Numerical\nexperiments demonstrating the effectiveness of the proposed model are conducted\nusing using a well-known optimization solver package. An illustrative example\ndepicting an optimal encryption for a small-scale network is also presented.\n",
"title": "An Integer Programming Formulation of the Key Management Problem in Wireless Sensor Networks"
}
| null | null | null | null | true | null |
10530
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| null | null |
null |
{
"abstract": " Neural Style Transfer based on Convolutional Neural Networks (CNN) aims to\nsynthesize a new image that retains the high-level structure of a content\nimage, rendered in the low-level texture of a style image. This is achieved by\nconstraining the new image to have high-level CNN features similar to the\ncontent image, and lower-level CNN features similar to the style image. However\nin the traditional optimization objective, low-level features of the content\nimage are absent, and the low-level features of the style image dominate the\nlow-level detail structures of the new image. Hence in the synthesized image,\nmany details of the content image are lost, and a lot of inconsistent and\nunpleasing artifacts appear. As a remedy, we propose to steer image synthesis\nwith a novel loss function: the Laplacian loss. The Laplacian matrix\n(\"Laplacian\" in short), produced by a Laplacian operator, is widely used in\ncomputer vision to detect edges and contours. The Laplacian loss measures the\ndifference of the Laplacians, and correspondingly the difference of the detail\nstructures, between the content image and a new image. It is flexible and\ncompatible with the traditional style transfer constraints. By incorporating\nthe Laplacian loss, we obtain a new optimization objective for neural style\ntransfer named Lapstyle. Minimizing this objective will produce a stylized\nimage that better preserves the detail structures of the content image and\neliminates the artifacts. Experiments show that Lapstyle produces more\nappealing stylized images with less artifacts, without compromising their\n\"stylishness\".\n",
"title": "Laplacian-Steered Neural Style Transfer"
}
| null | null | null | null | true | null |
10531
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| null | null |
null |
{
"abstract": " A quantized physical framework, called the five-anchor model, is developed\nfor a general understanding of the working mechanism of ion channels. According\nto the hypotheses of this model, the following two basic physical principles\nare assigned to each anchor: the polarity change induced by an electron\ntransition and the mutual repulsion and attraction induced by an electrostatic\nforce. Consequently, many unique phenomena, such as fast and slow inactivation,\nthe stochastic gating pattern and constant conductance of a single ion channel,\nthe difference between electrical and optical stimulation (optogenetics), nerve\nconduction block and the generation of an action potential, become intrinsic\nfeatures of this physical model. Moreover, this model also provides a\nfoundation for the probability equation used to calculate the results of\nelectrical stimulation in our previous C-P theory.\n",
"title": "A quantized physical framework for understanding the working mechanism of ion channels"
}
| null | null | null | null | true | null |
10532
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| null | null |
null |
{
"abstract": " Reinforcement learning has emerged as a promising methodology for training\nrobot controllers. However, most results have been limited to simulation due to\nthe need for a large number of samples and the lack of automated-yet-safe data\ncollection methods. Model-based reinforcement learning methods provide an\navenue to circumvent these challenges, but the traditional concern has been the\nmismatch between the simulator and the real world. Here, we show that control\npolicies learned in simulation can successfully transfer to a physical system,\ncomposed of three Phantom robots pushing an object to various desired target\npositions. We use a modified form of the natural policy gradient algorithm for\nlearning, applied to a carefully identified simulation model. The resulting\npolicies, trained entirely in simulation, work well on the physical system\nwithout additional training. In addition, we show that training with an\nensemble of models makes the learned policies more robust to modeling errors,\nthus compensating for difficulties in system identification.\n",
"title": "Reinforcement learning for non-prehensile manipulation: Transfer from simulation to physical system"
}
| null | null |
[
"Computer Science"
] | null | true | null |
10533
| null |
Validated
| null | null |
null |
{
"abstract": " We construct a contour function for the entanglement entropies in generic\nharmonic lattices. In one spatial dimension, numerical analysis are performed\nby considering harmonic chains with either periodic or Dirichlet boundary\nconditions. In the massless regime and for some configurations where the\nsubsystem is a single interval, the numerical results for the contour function\nare compared to the inverse of the local weight function which multiplies the\nenergy-momentum tensor in the corresponding entanglement hamiltonian, found\nthrough conformal field theory methods, and a good agreement is observed. A\nnumerical analysis of the contour function for the entanglement entropy is\nperformed also in a massless harmonic chain for a subsystem made by two\ndisjoint intervals.\n",
"title": "A contour for the entanglement entropies in harmonic lattices"
}
| null | null | null | null | true | null |
10534
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{
"abstract": " Topic discovery has witnessed a significant growth as a field of data mining\nat large. In particular, time-evolving topic discovery, where the evolution of\na topic is taken into account has been instrumental in understanding the\nhistorical context of an emerging topic in a dynamic corpus. Traditionally,\ntime-evolving topic discovery has focused on this notion of time. However,\nespecially in settings where content is contributed by a community or a crowd,\nan orthogonal notion of time is the one that pertains to the level of expertise\nof the content creator: the more experienced the creator, the more advanced the\ntopic. In this paper, we propose a novel time-evolving topic discovery method\nwhich, in addition to the extracted topics, is able to identify the evolution\nof that topic over time, as well as the level of difficulty of that topic, as\nit is inferred by the level of expertise of its main contributors. Our method\nis based on a novel formulation of Constrained Coupled Matrix-Tensor\nFactorization, which adopts constraints well-motivated for, and, as we\ndemonstrate, are essential for high-quality topic discovery. We qualitatively\nevaluate our approach using real data from the Physics and also Programming\nStack Exchange forum, and we were able to identify topics of varying levels of\ndifficulty which can be linked to external events, such as the announcement of\ngravitational waves by the LIGO lab in Physics forum. We provide a quantitative\nevaluation of our method by conducting a user study where experts were asked to\njudge the coherence and quality of the extracted topics. Finally, our proposed\nmethod has implications for automatic curriculum design using the extracted\ntopics, where the notion of the level of difficulty is necessary for the proper\nmodeling of prerequisites and advanced concepts.\n",
"title": "A Constrained Coupled Matrix-Tensor Factorization for Learning Time-evolving and Emerging Topics"
}
| null | null | null | null | true | null |
10535
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| null | null |
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{
"abstract": " It is well known that finite commutative association schemes in the sense of\nthe monograph of Bannai and Ito lead to finite commutative hypergroups with\npositive dual convolutions and even dual hypergroup structures. In this paper\nwe present several discrete generalizations of association schemes which also\nlead to associated hypergroups. We show that discrete commutative hypergroups\nassociated with such generalized association schemes admit dual positive\nconvolutions at least on the support of the Plancherel measure. We hope that\nexamples for this theory will lead to the existence of new dual positive\nproduct formulas in near future.\n",
"title": "Generalized Commutative Association Schemes, Hypergroups, and Positive Product Formulas"
}
| null | null | null | null | true | null |
10536
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| null | null |
null |
{
"abstract": " Until recently almost nothing was known about the evolution of magnetic\nfields found in upper main sequence Ap/Bp stars during their long main sequence\nlifetime. We are thus studying magnetic Ap/Bp stars in open clusters in order\nto obtain observational evidence of how the properties of Ap/Bp magnetic stars,\nsuch as field strength and structure, evolve with age during the main sequence.\nOne important aspect of this study is to search for the very rare examples of\nhot magnetic stars in short-period binary systems among magnetic cluster\nmembers. In this paper we characterize the object BD-19~5044L, which is both a\nmember of the open cluster IC 4725 = M~25, and a short-period SB2 system\ncontaining a magnetic primary star. We have obtained a series of intensity and\ncircular polarisation spectra distributed through the orbital and rotation\ncycles of BD-19 5044L with the ESPaDOnS spectropolarimeter at CFHT. We find\nthat the orbit of BD-19 5044L AB is quite eccentric (e = 0.477), with a period\nof 17.63 d. The primary is a magnetic Bp star with a variable longitudinal\nmagnetic field, a polar field strength of ~1400 G and a low obliquity, while\nthe secondary is probably a hot Am star and does not appear to be magnetic. The\nrotation period of the primary (5.04 d) is not synchronised with the orbit, but\nthe rotation angular velocity is close to being synchronised with the orbital\nangular velocity of the secondary at periastron, perhaps as a result of tidal\ninteractions. The periastron separation is small enough (about 12 times the\nradius of the primary star) that BD-19 5044L may be one of the very rare known\ncases of a tidally interacting SB2 binary system containing a magnetic Ap/Bp\nstar.\n",
"title": "BD-19 5044L: discovery of a short-period SB2 system with a magnetic Bp primary in the open cluster IC 4725"
}
| null | null |
[
"Physics"
] | null | true | null |
10537
| null |
Validated
| null | null |
null |
{
"abstract": " We use ultradeep 20 cm data from the Karl G. Jansky Very Large Array and 850\nmicron data from SCUBA-2 and the Submillimeter Array of an 124 arcmin^2 region\nof the Chandra Deep Field-north to analyze the high radio power (P_20cm>10^31\nerg s^-1 Hz^-1) population. We find that 20 (42+/-9%) of the spectroscopically\nidentified z>0.8 sources have consistent star formation rates (SFRs) inferred\nfrom both submillimeter and radio observations, while the remaining sources\nhave lower (mostly undetected) submillimeter fluxes, suggesting that active\ngalactic nucleus (AGN) activity dominates the radio power in these sources. We\ndevelop a classification scheme based on the ratio of submillimeter flux to\nradio power versus radio power and find that it agrees with AGN and\nstar-forming galaxy classifications from Very Long Baseline Interferometry. Our\nresults provide support for an extremely rapid drop in the number of high SFR\ngalaxies above about a thousand solar masses per year (Kroupa initial mass\nfunction) and for the locally determined relation between X-ray luminosity and\nradio power for star-forming galaxies applying at high redshifts and high radio\npowers. We measure far-infrared (FIR) luminosities and find that some AGNs lie\non the FIR-radio correlation, while others scatter below. The AGNs that lie on\nthe correlation appear to do so based on their emission from the AGN torus. We\nmeasure a median radio size of 1.0+/-0.3 arcsecond for the star-forming\ngalaxies. The radio sizes of the star-forming galaxies are generally larger\nthan those of the AGNs.\n",
"title": "A Submillimeter Perspective on the GOODS Fields (SUPER GOODS) - II. The High Radio Power Population in the GOODS-N"
}
| null | null | null | null | true | null |
10538
| null |
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| null | null |
null |
{
"abstract": " This paper begins with a theoretical explanation of why spacetime is\ndiscrete. The derivation shows that there exists an elementary length which is\nessentially Planck's length. We then show how the existence of this length\naffects time dilation in special relativity. We next consider the symmetry\ngroup for discrete spacetime. This symmetry group gives a discrete version of\nthe usual Lorentz group. However, it is much simpler and is actually a discrete\nversion of the rotation group. From the form of the symmetry group we deduce a\npossible explanation for the structure of elementary particle classes.\nEnergy-momentum space is introduced and mass operators are defined. Discrete\nversions of the Klein-Gordon and Dirac equations are derived. The final section\nconcerns discrete quantum field theory. Interaction Hamiltonians and scattering\noperators are considered. In particular, we study the scalar spin~0 and spin~1\nbosons as well as the spin~$1/2$ fermion cases\n",
"title": "Discrete Spacetime Quantum Field Theory"
}
| null | null | null | null | true | null |
10539
| null |
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| null | null |
null |
{
"abstract": " In both H.264 and HEVC, context-adaptive binary arithmetic coding (CABAC) is\nadopted as the entropy coding method. CABAC relies on manually designed\nbinarization processes as well as handcrafted context models, which may\nrestrict the compression efficiency. In this paper, we propose an arithmetic\ncoding strategy by training neural networks, and make preliminary studies on\ncoding of the intra prediction modes in HEVC. Instead of binarization, we\npropose to directly estimate the probability distribution of the 35 intra\nprediction modes with the adoption of a multi-level arithmetic codec. Instead\nof handcrafted context models, we utilize convolutional neural network (CNN) to\nperform the probability estimation. Simulation results show that our proposed\narithmetic coding leads to as high as 9.9% bits saving compared with CABAC.\n",
"title": "Neural network-based arithmetic coding of intra prediction modes in HEVC"
}
| null | null | null | null | true | null |
10540
| null |
Default
| null | null |
null |
{
"abstract": " Information-Centric Networking is a promising networking paradigm that\novercomes many of the limitations of current networking architectures. Various\nresearch efforts investigate solutions for securing ICN. Nevertheless, most of\nthese solutions relax security requirements in favor of network performance. In\nparticular, they weaken end-user privacy and the architecture's tolerance to\nsecurity breaches in order to support middleboxes that offer services such as\ncaching and content replication. In this paper, we adapt TLS, a widely used\nsecurity standard, to an ICN context. We design solutions that allow session\nreuse and migration among multiple stakeholders and we propose an extension\nthat allows authorized middleboxes to lawfully and transparently intercept\nsecured communications.\n",
"title": "Securing Information-Centric Networking without negating Middleboxes"
}
| null | null | null | null | true | null |
10541
| null |
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| null | null |
null |
{
"abstract": " Deep Gaussian Processes (DGPs) are hierarchical generalizations of Gaussian\nProcesses that combine well calibrated uncertainty estimates with the high\nflexibility of multilayer models. One of the biggest challenges with these\nmodels is that exact inference is intractable. The current state-of-the-art\ninference method, Variational Inference (VI), employs a Gaussian approximation\nto the posterior distribution. This can be a potentially poor unimodal\napproximation of the generally multimodal posterior. In this work, we provide\nevidence for the non-Gaussian nature of the posterior and we apply the\nStochastic Gradient Hamiltonian Monte Carlo method to generate samples. To\nefficiently optimize the hyperparameters, we introduce the Moving Window MCEM\nalgorithm. This results in significantly better predictions at a lower\ncomputational cost than its VI counterpart. Thus our method establishes a new\nstate-of-the-art for inference in DGPs.\n",
"title": "Inference in Deep Gaussian Processes using Stochastic Gradient Hamiltonian Monte Carlo"
}
| null | null | null | null | true | null |
10542
| null |
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| null | null |
null |
{
"abstract": " This paper develops meshless methods for probabilistically describing\ndiscretisation error in the numerical solution of partial differential\nequations. This construction enables the solution of Bayesian inverse problems\nwhile accounting for the impact of the discretisation of the forward problem.\nIn particular, this drives statistical inferences to be more conservative in\nthe presence of significant solver error. Theoretical results are presented\ndescribing rates of convergence for the posteriors in both the forward and\ninverse problems. This method is tested on a challenging inverse problem with a\nnonlinear forward model.\n",
"title": "Probabilistic Numerical Methods for PDE-constrained Bayesian Inverse Problems"
}
| null | null | null | null | true | null |
10543
| null |
Default
| null | null |
null |
{
"abstract": " This note is a collection of several discussions of the paper \"Beyond\nsubjective and objective in statistics\", read by A. Gelman and C. Hennig to the\nRoyal Statistical Society on April 12, 2017, and to appear in the Journal of\nthe Royal Statistical Society, Series A.\n",
"title": "Some discussions on the Read Paper \"Beyond subjective and objective in statistics\" by A. Gelman and C. Hennig"
}
| null | null | null | null | true | null |
10544
| null |
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| null | null |
null |
{
"abstract": " New physics has traditionally been expected in the high-$p_T$ region at\nhigh-energy collider experiments. If new particles are light and\nweakly-coupled, however, this focus may be completely misguided: light\nparticles are typically highly concentrated within a few mrad of the beam line,\nallowing sensitive searches with small detectors, and even extremely\nweakly-coupled particles may be produced in large numbers there. We propose a\nnew experiment, ForwArd Search ExpeRiment, or FASER, which would be placed\ndownstream of the ATLAS or CMS interaction point (IP) in the very forward\nregion and operated concurrently there. Two representative on-axis locations\nare studied: a far location, $400~\\text{m}$ from the IP and just off the beam\ntunnel, and a near location, just $150~\\text{m}$ from the IP and right behind\nthe TAN neutral particle absorber. For each location, we examine leading\nneutrino- and beam-induced backgrounds. As a concrete example of light,\nweakly-coupled particles, we consider dark photons produced through light meson\ndecay and proton bremsstrahlung. We find that even a relatively small and\ninexpensive cylindrical detector, with a radius of $\\sim 10~\\text{cm}$ and\nlength of $5-10~\\text{m}$, depending on the location, can discover dark photons\nin a large and unprobed region of parameter space with dark photon mass $m_{A'}\n\\sim 10~\\text{MeV} - 1~\\text{GeV}$ and kinetic mixing parameter $\\epsilon \\sim\n10^{-7} - 10^{-3}$. FASER will clearly also be sensitive to many other forms of\nnew physics. We conclude with a discussion of topics for further study that\nwill be essential for understanding FASER's feasibility, optimizing its design,\nand realizing its discovery potential.\n",
"title": "FASER: ForwArd Search ExpeRiment at the LHC"
}
| null | null | null | null | true | null |
10545
| null |
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| null | null |
null |
{
"abstract": " Changes in the structure of observed social and complex networks' structure\ncan indicate a significant underlying change in an organization, or reflect the\nresponse of the network to an external event. Automatic detection of change\npoints in evolving networks is rudimentary to the research and the\nunderstanding of the effect of such events on networks. Here we present an\neasy-to-implement and fast framework for change point detection in temporal\nevolving networks. Unlike previous approaches, our method is size agnostic, and\ndoes not require either prior knowledge about the network's size and structure,\nnor does it require obtaining historical information or nodal identities over\ntime. We use both synthetic data derived from dynamic models and two real\ndatasets: Enron email exchange and Ask-Ubuntu forum. Our framework succeeds\nwith both precision and recall and outperforms previous solutions\n",
"title": "Size Agnostic Change Point Detection Framework for Evolving Networks"
}
| null | null | null | null | true | null |
10546
| null |
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| null | null |
null |
{
"abstract": " According to the Wiener-Hopf factorization, the characteristic function\n$\\varphi$ of any probability distribution $\\mu$ on $\\mathbb{R}$ can be\ndecomposed in a unique way as\n\\[1-s\\varphi(t)=[1-\\chi_-(s,it)][1-\\chi_+(s,it)]\\,,\\;\\;\\;|s|\\le1,\\,t\\in\\mathbb{R}\\,,\\]\nwhere $\\chi_-(e^{iu},it)$ and $\\chi_+(e^{iu},it)$ are the characteristic\nfunctions of possibly defective distributions in\n$\\mathbb{Z}_+\\times(-\\infty,0)$ and $\\mathbb{Z}_+\\times[0,\\infty)$,\nrespectively.\nWe prove that $\\mu$ can be characterized by the sole data of the upward\nfactor $\\chi_+(s,it)$, $s\\in[0,1)$, $t\\in\\mathbb{R}$ in many cases including\nthe cases where:\n1) $\\mu$ has some exponential moments;\n2) the function $t\\mapsto\\mu(t,\\infty)$ is completely monotone on\n$(0,\\infty)$;\n3) the density of $\\mu$ on $[0,\\infty)$ admits an analytic continuation on\n$\\mathbb{R}$.\nWe conjecture that any probability distribution is actually characterized by\nits upward factor. This conjecture is equivalent to the following: {\\it Any\nprobability measure $\\mu$ on $\\mathbb{R}$ whose support is not included in\n$(-\\infty,0)$ is determined by its convolution powers $\\mu^{*n}$, $n\\ge1$\nrestricted to $[0,\\infty)$}. We show that in many instances, the sole knowledge\nof $\\mu$ and $\\mu^{*2}$ restricted to $[0,\\infty)$ is actually sufficient to\ndetermine $\\mu$. Then we investigate the analogous problem in the framework of\ninfinitely divisible distributions.\n",
"title": "On distributions determined by their upward, space-time Wiener-Hopf factor"
}
| null | null | null | null | true | null |
10547
| null |
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| null | null |
null |
{
"abstract": " The local crystal structures of many perovskite-structured materials deviate\nfrom the average space group symmetry. We demonstrate, from lattice-dynamics\ncalculations based on quantum chemical force constants, that all the\ncaesium-lead and caesium-tin halide perovskites exhibit vibrational\ninstabilities associated with octahedral titling in their high-temperature\ncubic phase. Anharmonic double-well potentials are found for zone-boundary\nphonon modes in all compounds with barriers ranging from 108 to 512 meV. The\nwell depth is correlated with the tolerance factor and the chemistry of the\ncomposition, but is not proportional to the imaginary harmonic phonon\nfrequency. We provide quantitative insights into the thermodynamic driving\nforces and distinguish between dynamic and static disorder based on the\npotential-energy landscape. A positive band gap deformation (spectral\nblueshift) accompanies the structural distortion, with implications for\nunderstanding the performance of these materials in applications areas\nincluding solar cells and light-emitting diodes.\n",
"title": "Spontaneous Octahedral Tilting in the Cubic Inorganic Caesium Halide Perovskites CsSnX$_3$ and CsPbX$_3$ (X = F, Cl, Br, I)"
}
| null | null | null | null | true | null |
10548
| null |
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| null | null |
null |
{
"abstract": " The ordering of a multilayer consisting of DSPC bilayers on a silica sol\nsubstrate is studied within the model-independent approach to the\nreconstruction of profiles of the electron density from X-ray reflectometry\ndata. It is found that the electroporation of bilayers in the field of anion\nsilica nanoparticles significantly accelerates the process of their saturation\nwith Na+ and H2O, which explains both a relatively small time of formation of\nthe structure of the multilayer of 10^5 - 7x10^5 s and ~13 % excess of the\nelectron density in it.\n",
"title": "Kinetics of the Phospholipid Multilayer Formation at the Surface of the Silica Sol"
}
| null | null | null | null | true | null |
10549
| null |
Default
| null | null |
null |
{
"abstract": " Deep reinforcement learning (RL) has proven a powerful technique in many\nsequential decision making domains. However, Robotics poses many challenges for\nRL, most notably training on a physical system can be expensive and dangerous,\nwhich has sparked significant interest in learning control policies using a\nphysics simulator. While several recent works have shown promising results in\ntransferring policies trained in simulation to the real world, they often do\nnot fully utilize the advantage of working with a simulator. In this work, we\nexploit the full state observability in the simulator to train better policies\nwhich take as input only partial observations (RGBD images). We do this by\nemploying an actor-critic training algorithm in which the critic is trained on\nfull states while the actor (or policy) gets rendered images as input. We show\nexperimentally on a range of simulated tasks that using these asymmetric inputs\nsignificantly improves performance. Finally, we combine this method with domain\nrandomization and show real robot experiments for several tasks like picking,\npushing, and moving a block. We achieve this simulation to real world transfer\nwithout training on any real world data.\n",
"title": "Asymmetric Actor Critic for Image-Based Robot Learning"
}
| null | null | null | null | true | null |
10550
| null |
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| null | null |
null |
{
"abstract": " In this thesis, we study the interplay of phase separation and wetting in\nmulticomponent systems. For this purpose, we have examined the phase separation\npattern of a binary mixture (AB) in presence of stationary spherical particles\n(C) which prefers one of the components of the binary (say, A). Binary AB is\ncomposed of critical composition(50:50) and off-critical compositions(60:40,\n40:60). Particle sizes of 8 units and 16 units are used in the simulations. Two\ntypes of particle loading are used, 5\\% and 10\\%. We have employed a ternary\nform of Cahn-Hilliard equation to incorporate immobile fillers in our system.\nTo elucidate the effect of wetting on phase separation we have designed three\nsets of $\\chi_{ij}$ and $\\kappa_{ij}$ to include the effects of neutral\npreference, weak preference and strong preference of the particle for one of\nthe binary components. If the particles are preferentially wetted by one of the\ncomponents then early stage microstructures show transient concentric alternate\nlayers of preferred and non-preferred phases around the particles. When\nparticles are neutral to binary components then such a ring pattern does not\nform. At late times, neutral preference between particles and binary components\nyields a continuous morphology whereas preferential wetting produces isolated\ndomains of non-preferred phases dispersed in a continuous matrix of preferred\nphase. For off-critical compositions, if minor component wets the particle then\na bicontinuous morphology results whereas if major component wets the network a\ndroplet morphology is seen. When majority component wets the particle, a\npossibility of double phase separation is reported. In such alloys phase\nseparation starts near the particle surface and propagates to the bulk at\nintermediate to late times forming spherical or nearly spherical droplets of\nthe minor component.\n",
"title": "Effects of particles on spinodal decomposition: A Phase field study"
}
| null | null |
[
"Physics"
] | null | true | null |
10551
| null |
Validated
| null | null |
null |
{
"abstract": " We consider a spatial stochastic model of wireless cellular networks, where\nthe base stations (BSs) are deployed according to a simple and stationary point\nprocess on $\\mathbb{R}^d$, $d\\ge2$. In this model, we investigate tail\nasymptotics of the distribution of signal-to-interference ratio (SIR), which is\na key quantity in wireless communications. In the case where the path-loss\nfunction representing signal attenuation is unbounded at the origin, we derive\nthe exact tail asymptotics of the SIR distribution under an appropriate\nsufficient condition. While we show that widely-used models based on a Poisson\npoint process and on a determinantal point process meet the sufficient\ncondition, we also give a counterexample violating it. In the case of bounded\npath-loss functions, we derive a logarithmically asymptotic upper bound on the\nSIR tail distribution for the Poisson-based and $\\alpha$-Ginibre-based models.\nA logarithmically asymptotic lower bound with the same order as the upper bound\nis also obtained for the Poisson-based model.\n",
"title": "Tail asymptotics of signal-to-interference ratio distribution in spatial cellular network models"
}
| null | null | null | null | true | null |
10552
| null |
Default
| null | null |
null |
{
"abstract": " A reinsurance contract should address the conflicting interests of the\ninsurer and reinsurer. Most of existing optimal reinsurance contracts only\nconsiders the interests of one party. This article combines the proportional\nand stop-loss reinsurance contracts and introduces a new reinsurance contract\ncalled proportional-stop-loss reinsurance. Using the balanced loss function,\nunknown parameters of the proportional-stop-loss reinsurance have been\nestimated such that the expected surplus for both the insurer and reinsurer are\nmaximized. Several characteristics for the new reinsurance are provided.\n",
"title": "An Optimal Combination of Proportional and Stop-Loss Reinsurance Contracts From Insurer's and Reinsurer's Viewpoints"
}
| null | null | null | null | true | null |
10553
| null |
Default
| null | null |
null |
{
"abstract": " We show the problem of counting homomorphisms from the fundamental group of a\nhomology $3$-sphere $M$ to a finite, non-abelian simple group $G$ is\n#P-complete, in the case that $G$ is fixed and $M$ is the computational input.\nSimilarly, deciding if there is a non-trivial homomorphism is NP-complete. In\nboth reductions, we can guarantee that every non-trivial homomorphism is a\nsurjection. As a corollary, for any fixed integer $m \\ge 5$, it is NP-complete\nto decide whether $M$ admits a connected $m$-sheeted covering.\nOur construction is inspired by universality results in topological quantum\ncomputation. Given a classical reversible circuit $C$, we construct $M$ so that\nevaluations of $C$ with certain initialization and finalization conditions\ncorrespond to homomorphisms $\\pi_1(M) \\to G$. An intermediate state of $C$\nlikewise corresponds to a homomorphism $\\pi_1(\\Sigma_g) \\to G$, where\n$\\Sigma_g$ is a pointed Heegaard surface of $M$ of genus $g$. We analyze the\naction on these homomorphisms by the pointed mapping class group\n$\\text{MCG}_*(\\Sigma_g)$ and its Torelli subgroup $\\text{Tor}_*(\\Sigma_g)$. By\nresults of Dunfield-Thurston, the action of $\\text{MCG}_*(\\Sigma_g)$ is as\nlarge as possible when $g$ is sufficiently large; we can pass to the Torelli\ngroup using the congruence subgroup property of $\\text{Sp}(2g,\\mathbb{Z})$. Our\nresults can be interpreted as a sharp classical universality property of an\nassociated combinatorial $(2+1)$-dimensional TQFT.\n",
"title": "Computational complexity and 3-manifolds and zombies"
}
| null | null | null | null | true | null |
10554
| null |
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| null | null |
null |
{
"abstract": " The use of semi-autonomous and autonomous robotic assistants to aid in care\nof the elderly is expected to ease the burden on human caretakers, with\nsmall-stage testing already occurring in a variety of countries. Yet, it is\nlikely that these robots will need to request human assistance via\nteleoperation when domain expertise is needed for a specific task. As\ndeployment of robotic assistants moves to scale, mapping these requests for\nhuman aid to the teleoperators themselves will be a difficult online\noptimization problem. In this paper, we design a system that allocates requests\nto a limited number of teleoperators, each with different specialities, in an\nonline fashion. We generalize a recent model of online job scheduling with a\nworst-case competitive-ratio bound to our setting. Next, we design a scalable\nmachine-learning-based teleoperator-aware task scheduling algorithm and show,\nexperimentally, that it performs well when compared to an omniscient optimal\nscheduling algorithm.\n",
"title": "Learning to Schedule Deadline- and Operator-Sensitive Tasks"
}
| null | null | null | null | true | null |
10555
| null |
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| null | null |
null |
{
"abstract": " We start by asking an interesting yet challenging question, \"If an eyewitness\ncan only recall the eye features of the suspect, such that the forensic artist\ncan only produce a sketch of the eyes (e.g., the top-left sketch shown in Fig.\n1), can advanced computer vision techniques help generate the whole face\nimage?\" A more generalized question is that if a large proportion (e.g., more\nthan 50%) of the face/sketch is missing, can a realistic whole face\nsketch/image still be estimated. Existing face completion and generation\nmethods either do not conduct domain transfer learning or can not handle large\nmissing area. For example, the inpainting approach tends to blur the generated\nregion when the missing area is large (i.e., more than 50%). In this paper, we\nexploit the potential of deep learning networks in filling large missing region\n(e.g., as high as 95% missing) and generating realistic faces with\nhigh-fidelity in cross domains. We propose the recursive generation by\nbidirectional transformation networks (r-BTN) that recursively generates a\nwhole face/sketch from a small sketch/face patch. The large missing area and\nthe cross domain challenge make it difficult to generate satisfactory results\nusing a unidirectional cross-domain learning structure. On the other hand, a\nforward and backward bidirectional learning between the face and sketch domains\nwould enable recursive estimation of the missing region in an incremental\nmanner (Fig. 1) and yield appealing results. r-BTN also adopts an adversarial\nconstraint to encourage the generation of realistic faces/sketches. Extensive\nexperiments have been conducted to demonstrate the superior performance from\nr-BTN as compared to existing potential solutions.\n",
"title": "r-BTN: Cross-domain Face Composite and Synthesis from Limited Facial Patches"
}
| null | null | null | null | true | null |
10556
| null |
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| null | null |
null |
{
"abstract": " We consider several (related) notions of geometric regularity in the context\nof limit sets of geometrically finite Kleinian groups and associated\nPatterson-Sullivan measures. We begin by computing the upper and lower\nregularity dimensions of the Patterson-Sullivan measure, which involves\ncontrolling the relative measure of concentric balls. We then compute the\nAssouad and lower dimensions of the limit set, which involves controlling local\ndoubling properties. Unlike the Hausdorff, packing, and box-counting\ndimensions, we show that the Assouad and lower dimensions are not necessarily\ngiven by the Poincaré exponent.\n",
"title": "Regularity of Kleinian limit sets and Patterson-Sullivan measures"
}
| null | null | null | null | true | null |
10557
| null |
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| null | null |
null |
{
"abstract": " Sleep condition is closely related to an individual's health. Poor sleep\nconditions such as sleep disorder and sleep deprivation affect one's daily\nperformance, and may also cause many chronic diseases. Many efforts have been\ndevoted to monitoring people's sleep conditions. However, traditional\nmethodologies require sophisticated equipment and consume a significant amount\nof time. In this paper, we attempt to develop a novel way to predict\nindividual's sleep condition via scrutinizing facial cues as doctors would.\nRather than measuring the sleep condition directly, we measure the\nsleep-deprived fatigue which indirectly reflects the sleep condition. Our\nmethod can predict a sleep-deprived fatigue rate based on a selfie provided by\na subject. This rate is used to indicate the sleep condition. To gain deeper\ninsights of human sleep conditions, we collected around 100,000 faces from\nselfies posted on Twitter and Instagram, and identified their age, gender, and\nrace using automatic algorithms. Next, we investigated the sleep condition\ndistributions with respect to age, gender, and race. Our study suggests among\nthe age groups, fatigue percentage of the 0-20 youth and adolescent group is\nthe highest, implying that poor sleep condition is more prevalent in this age\ngroup. For gender, the fatigue percentage of females is higher than that of\nmales, implying that more females are suffering from sleep issues than males.\nAmong ethnic groups, the fatigue percentage in Caucasian is the highest\nfollowed by Asian and African American.\n",
"title": "Large-Scale Sleep Condition Analysis Using Selfies from Social Media"
}
| null | null | null | null | true | null |
10558
| null |
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| null | null |
null |
{
"abstract": " Motivated by the recent result of Farhi we show that for each $n\\equiv \\pm\n1\\pmod{6}$ the title Diophantine equation has at least two solutions in\nintegers. As a consequence, we get that each (even) perfect number is a sum of\nthree cubes of integers. Moreover, we present some computational results\nconcerning the considered equation and state some questions and conjectures.\n",
"title": "A note on the Diophantine equation $2^{n-1}(2^{n}-1)=x^3+y^3+z^3$"
}
| null | null | null | null | true | null |
10559
| null |
Default
| null | null |
null |
{
"abstract": " In the context of music production, distortion effects are mainly used for\naesthetic reasons and are usually applied to electric musical instruments. Most\nexisting methods for nonlinear modeling are often either simplified or\noptimized to a very specific circuit. In this work, we investigate deep\nlearning architectures for audio processing and we aim to find a general\npurpose end-to-end deep neural network to perform modeling of nonlinear audio\neffects. We show the network modeling various nonlinearities and we discuss the\ngeneralization capabilities among different instruments.\n",
"title": "Modeling of nonlinear audio effects with end-to-end deep neural networks"
}
| null | null | null | null | true | null |
10560
| null |
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| null | null |
null |
{
"abstract": " In this paper, we consider adaptive decision-making problems for stochastic\nstate estimation with partial observations. First, we introduce the concept of\nweak adaptive submodularity, a generalization of adaptive submodularity, which\nhas found great success in solving challenging adaptive state estimation\nproblems. Then, for the problem of active diagnosis, i.e., discrete state\nestimation via active sensing, we show that an adaptive greedy policy has a\nnear-optimal performance guarantee when the reward function possesses this\nproperty. We further show that the reward function for group-based active\ndiagnosis, which arises in applications such as medical diagnosis and state\nestimation with persistent sensor faults, is also weakly adaptive submodular.\nFinally, in experiments of state estimation for an aircraft electrical system\nwith persistent sensor faults, we observe that an adaptive greedy policy\nperforms equally well as an exhaustive search.\n",
"title": "Weak Adaptive Submodularity and Group-Based Active Diagnosis with Applications to State Estimation with Persistent Sensor Faults"
}
| null | null | null | null | true | null |
10561
| null |
Default
| null | null |
null |
{
"abstract": " Many machine learning problems can be formulated as consensus optimization\nproblems which can be solved efficiently via a cooperative multi-agent system.\nHowever, the agents in the system can be unreliable due to a variety of\nreasons: noise, faults and attacks. Providing erroneous updates leads the\noptimization process in a wrong direction, and degrades the performance of\ndistributed machine learning algorithms. This paper considers the problem of\ndecentralized learning using ADMM in the presence of unreliable agents. First,\nwe rigorously analyze the effect of erroneous updates (in ADMM learning\niterations) on the convergence behavior of multi-agent system. We show that the\nalgorithm linearly converges to a neighborhood of the optimal solution under\ncertain conditions and characterize the neighborhood size analytically. Next,\nwe provide guidelines for network design to achieve a faster convergence. We\nalso provide conditions on the erroneous updates for exact convergence to the\noptimal solution. Finally, to mitigate the influence of unreliable agents, we\npropose \\textsf{ROAD}, a robust variant of ADMM, and show its resilience to\nunreliable agents with an exact convergence to the optimum.\n",
"title": "Robust Decentralized Learning Using ADMM with Unreliable Agents"
}
| null | null |
[
"Computer Science",
"Statistics"
] | null | true | null |
10562
| null |
Validated
| null | null |
null |
{
"abstract": " During the last decade, the information technology industry has adopted a\ndata-driven culture, relying on online metrics to measure and monitor business\nperformance. Under the setting of big data, the majority of such metrics\napproximately follow normal distributions, opening up potential opportunities\nto model them directly without extra model assumptions and solve big data\nproblems via closed-form formulas using distributed algorithms at a fraction of\nthe cost of simulation-based procedures like bootstrap. However, certain\nattributes of the metrics, such as their corresponding data generating\nprocesses and aggregation levels, pose numerous challenges for constructing\ntrustworthy estimation and inference procedures. Motivated by four real-life\nexamples in metric development and analytics for large-scale A/B testing, we\nprovide a practical guide to applying the Delta method, one of the most\nimportant tools from the classic statistics literature, to address the\naforementioned challenges. We emphasize the central role of the Delta method in\nmetric analytics by highlighting both its classic and novel applications.\n",
"title": "Applying the Delta method in metric analytics: A practical guide with novel ideas"
}
| null | null | null | null | true | null |
10563
| null |
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| null | null |
null |
{
"abstract": " Estimating the Domain of Attraction (DA) of non-polynomial systems is a\nchallenging problem. Taylor expansion is widely adopted for transforming a\nnonlinear analytic function into a polynomial function, but the performance of\nTaylor expansion is not always satisfactory. This paper provides solvable ways\nfor estimating the DA via Chebyshev approximation. Firstly, for Chebyshev\napproximation without the remainder, higher order derivatives of Lyapunov\nfunctions are used for estimating the DA, and the largest estimate is obtained\nby solving a generalized eigenvalue problem. Moreover, for Chebyshev\napproximation with the remainder, an uncertain polynomial system is\nreformulated, and a condition is proposed for ensuring the convergence to the\nlargest estimate with a selected Lyapunov function. Numerical examples\ndemonstrate that both accuracy and efficiency are improved compared to Taylor\napproximation.\n",
"title": "Chebyshev Approximation and Higher Order Derivatives of Lyapunov Functions for Estimating the Domain of Attraction"
}
| null | null | null | null | true | null |
10564
| null |
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| null | null |
null |
{
"abstract": " This article is devoted to the problem of predicting the value taken by a\nrandom permutation $\\Sigma$, describing the preferences of an individual over a\nset of numbered items $\\{1,\\; \\ldots,\\; n\\}$ say, based on the observation of\nan input/explanatory r.v. $X$ e.g. characteristics of the individual), when\nerror is measured by the Kendall $\\tau$ distance. In the probabilistic\nformulation of the 'Learning to Order' problem we propose, which extends the\nframework for statistical Kemeny ranking aggregation developped in\n\\citet{CKS17}, this boils down to recovering conditional Kemeny medians of\n$\\Sigma$ given $X$ from i.i.d. training examples $(X_1, \\Sigma_1),\\; \\ldots,\\;\n(X_N, \\Sigma_N)$. For this reason, this statistical learning problem is\nreferred to as \\textit{ranking median regression} here. Our contribution is\ntwofold. We first propose a probabilistic theory of ranking median regression:\nthe set of optimal elements is characterized, the performance of empirical risk\nminimizers is investigated in this context and situations where fast learning\nrates can be achieved are also exhibited. Next we introduce the concept of\nlocal consensus/median, in order to derive efficient methods for ranking median\nregression. The major advantage of this local learning approach lies in its\nclose connection with the widely studied Kemeny aggregation problem. From an\nalgorithmic perspective, this permits to build predictive rules for ranking\nmedian regression by implementing efficient techniques for (approximate) Kemeny\nmedian computations at a local level in a tractable manner. In particular,\nversions of $k$-nearest neighbor and tree-based methods, tailored to ranking\nmedian regression, are investigated. Accuracy of piecewise constant ranking\nmedian regression rules is studied under a specific smoothness assumption for\n$\\Sigma$'s conditional distribution given $X$.\n",
"title": "Ranking Median Regression: Learning to Order through Local Consensus"
}
| null | null | null | null | true | null |
10565
| null |
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| null | null |
null |
{
"abstract": " We examine whether an extended scenario of a two-scalar-field model, in which\na mixed kinetic term of canonical and phantom scalar fields is involved, admits\nthe Bianchi type I metric, which is homogeneous but anisotropic spacetime, as\nits power-law solutions. Then we analyze the stability of the anisotropic\npower-law solutions to see whether these solutions respect the cosmic no-hair\nconjecture or not during the inflationary phase. In addition, we will also\ninvestigate a special scenario, where the pure kinetic terms of canonical and\nphantom fields disappear altogether in field equations, to test again the\nvalidity of cosmic no-hair conjecture. As a result, the cosmic no-hair\nconjecture always holds in both these scenarios due to the instability of the\ncorresponding anisotropic inflationary solutions.\n",
"title": "Anisotropic power-law inflation in a two-scalar-field model with a mixed kinetic term"
}
| null | null | null | null | true | null |
10566
| null |
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| null | null |
null |
{
"abstract": " We address the key open problem of a higher dimensional generalization of the\nSachdev-Ye-Kitaev (SYK) model. We construct a model on a lattice of SYK dots\nwith non-random intersite hopping. The crucial feature of the resulting band\ndispersion is the presence of a Lifshitz point where two bands touch with a\ntunable powerlaw divergent density of states (DOS). For a certain regime of the\npowerlaw exponent, we obtain a new class of interaction-dominated non-Fermi\nliquid (NFL) states, which exhibits exciting features such as a\nzero-temperature scaling symmetry, an emergent (approximate) time\nreparameterization invariance, a powerlaw entropy-temperature relationship, and\na fermion dimension that depends continuously on the DOS exponent. Notably, we\nfurther demonstrate that these NFL states are fast scramblers with a Lyapunov\nexponent $\\lambda_L\\propto T$, although they do not saturate the upper bound of\nchaos, rendering them truly unique.\n",
"title": "Higher-dimensional SYK Non-Fermi Liquids at Lifshitz transitions"
}
| null | null |
[
"Physics"
] | null | true | null |
10567
| null |
Validated
| null | null |
null |
{
"abstract": " Sparse additive modeling is a class of effective methods for performing\nhigh-dimensional nonparametric regression. In this work we show how shape\nconstraints such as convexity/concavity and their extensions, can be integrated\ninto additive models. The proposed sparse difference of convex additive models\n(SDCAM) can estimate most continuous functions without any a priori smoothness\nassumption. Motivated by a characterization of difference of convex functions,\nour method incorporates a natural regularization functional to avoid\noverfitting and to reduce model complexity. Computationally, we develop an\nefficient backfitting algorithm with linear per-iteration complexity.\nExperiments on both synthetic and real data verify that our method is\ncompetitive against state-of-the-art sparse additive models, with improved\nperformance in most scenarios.\n",
"title": "Convex-constrained Sparse Additive Modeling and Its Extensions"
}
| null | null | null | null | true | null |
10568
| null |
Default
| null | null |
null |
{
"abstract": " We present a performance analysis appropriate for comparing algorithms using\ndifferent numerical discretizations. By taking into account the total\ntime-to-solution, numerical accuracy with respect to an error norm, and the\ncomputation rate, a cost-benefit analysis can be performed to determine which\nalgorithm and discretization are particularly suited for an application. This\nwork extends the performance spectrum model in Chang et. al. 2017 for\ninterpretation of hardware and algorithmic tradeoffs in numerical PDE\nsimulation. As a proof-of-concept, popular finite element software packages are\nused to illustrate this analysis for Poisson's equation.\n",
"title": "Comparative study of finite element methods using the Time-Accuracy-Size (TAS) spectrum analysis"
}
| null | null | null | null | true | null |
10569
| null |
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| null | null |
null |
{
"abstract": " The Riesz-Sobolev inequality provides an upper bound, in integral form, for\nthe convolution of indicator functions of subsets of Euclidean space. We\nformulate and prove a sharper form of the inequality. This can be equivalently\nphrased as a stability result, quantifying an inverse theorem of Burchard that\ncharacterizes cases of equality.\n",
"title": "A sharpened Riesz-Sobolev inequality"
}
| null | null | null | null | true | null |
10570
| null |
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| null | null |
null |
{
"abstract": " We study the problem of defining maps on link Floer homology induced by\nunoriented link cobordisms. We provide a natural notion of link cobordism,\ndisoriented link cobordism, which tracks the motion of index zero and index\nthree critical points. Then we construct a map on unoriented link Floer\nhomology associated to a disoriented link cobordism. Furthermore, we give a\ncomparison with Oszváth-Stipsicz-Szabó's and Manolescu's constructions of\nlink cobordism maps for an unoriented band move.\n",
"title": "Unoriented Cobordism Maps on Link Floer Homology"
}
| null | null |
[
"Mathematics"
] | null | true | null |
10571
| null |
Validated
| null | null |
null |
{
"abstract": " Recent advances have enabled 3d object reconstruction approaches using a\nsingle off-the-shelf RGB-D camera. Although these approaches are successful for\na wide range of object classes, they rely on stable and distinctive geometric\nor texture features. Many objects like mechanical parts, toys, household or\ndecorative articles, however, are textureless and characterized by minimalistic\nshapes that are simple and symmetric. Existing in-hand scanning systems and 3d\nreconstruction techniques fail for such symmetric objects in the absence of\nhighly distinctive features. In this work, we show that extracting 3d hand\nmotion for in-hand scanning effectively facilitates the reconstruction of even\nfeatureless and highly symmetric objects and we present an approach that fuses\nthe rich additional information of hands into a 3d reconstruction pipeline,\nsignificantly contributing to the state-of-the-art of in-hand scanning.\n",
"title": "3D Object Reconstruction from Hand-Object Interactions"
}
| null | null | null | null | true | null |
10572
| null |
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| null | null |
null |
{
"abstract": " We investigate the long-time stability of the Sun-Jupiter-Saturn-Uranus\nsystem by considering a planar secular model, that can be regarded as a major\nrefinement of the approach first introduced by Lagrange. Indeed, concerning the\nplanetary orbital revolutions, we improve the classical circular approximation\nby replacing it with a solution that is invariant up to order two in the\nmasses; therefore, we investigate the stability of the secular system for\nrather small values of the eccentricities. First, we explicitly construct a\nKolmogorov normal form, so as to find an invariant KAM torus which approximates\nvery well the secular orbits. Finally, we adapt the approach that is at basis\nof the analytic part of the Nekhoroshev's theorem, so as to show that there is\na neighborhood of that torus for which the estimated stability time is larger\nthan the lifetime of the Solar System. The size of such a neighborhood,\ncompared with the uncertainties of the astronomical observations, is about ten\ntimes smaller.\n",
"title": "Secular dynamics of a planar model of the Sun-Jupiter-Saturn-Uranus system; effective stability into the light of Kolmogorov and Nekhoroshev theories"
}
| null | null | null | null | true | null |
10573
| null |
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| null | null |
null |
{
"abstract": " We consider variants on the classical Berz sublinearity theorem, using only\nDC, the Axiom of Dependent Choices, rather than AC, the Axiom of Choice which\nBerz used. We consider thinned versions, in which conditions are imposed on\nonly part of the domain of the function -- results of quantifier-weakening\ntype. There are connections with classical results on subadditivity. We close\nwith a discussion of the extensive related literature.\n",
"title": "Variants on the Berz sublinearity theorem"
}
| null | null | null | null | true | null |
10574
| null |
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| null | null |
null |
{
"abstract": " There has been a long standing interest in understanding `Social Influence'\nboth in Social Sciences and in Computational Linguistics. In this paper, we\npresent a novel approach to study and measure interpersonal influence in daily\ninteractions. Motivated by the basic principles of influence, we attempt to\nidentify indicative linguistic features of the posts in an online knitting\ncommunity. We present the scheme used to operationalize and label the posts\nwith indicator features. Experiments with the identified features show an\nimprovement in the classification accuracy of influence by 3.15%. Our results\nillustrate the important correlation between the characteristics of the\nlanguage and its potential to influence others.\n",
"title": "Linguistic Markers of Influence in Informal Interactions"
}
| null | null | null | null | true | null |
10575
| null |
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| null | null |
null |
{
"abstract": " With a core-periphery structure of networks, core nodes are densely\ninterconnected, peripheral nodes are connected to core nodes to different\nextents, and peripheral nodes are sparsely interconnected. Core-periphery\nstructure composed of a single core and periphery has been identified for\nvarious networks. However, analogous to the observation that many empirical\nnetworks are composed of densely interconnected groups of nodes, i.e.,\ncommunities, a network may be better regarded as a collection of multiple cores\nand peripheries. We propose a scalable algorithm to detect multiple\nnon-overlapping groups of core-periphery structure in a network. We illustrate\nour algorithm using synthesised and empirical networks. For example, we find\ndistinct core-periphery pairs with different political leanings in a network of\npolitical blogs and separation between international and domestic subnetworks\nof airports in some single countries in a world-wide airport network.\n",
"title": "Finding multiple core-periphery pairs in networks"
}
| null | null | null | null | true | null |
10576
| null |
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| null | null |
null |
{
"abstract": " Central limit theorems play an important role in the study of statistical\ninference for stochastic processes. However, when the nonparametric local\npolynomial threshold estimator, especially local linear case, is employed to\nestimate the diffusion coefficients of diffusion processes, the adaptive and\npredictable structure of the estimator conditionally on the $\\sigma-$field\ngenerated by diffusion processes is destroyed, the classical central limit\ntheorem for martingale difference sequences can not work. In this paper, we\nproved the central limit theorems of local polynomial threshold estimators for\nthe volatility function in diffusion processes with jumps. We believe that our\nproof for local polynomial threshold estimators provides a new method in this\nfields, especially local linear case.\n",
"title": "Central Limit Theorems of Local Polynomial Threshold Estimators for Diffusion Processes with Jumps"
}
| null | null | null | null | true | null |
10577
| null |
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| null | null |
null |
{
"abstract": " In the first half of this manuscript, we begin with a brief review of\ncombinatorial hives as introduced by Knutson and Tao, and focus on a conjecture\nby Danilov and Koshevoy for generating such a hive from Hermitian matrix pairs\nthrough an optimization scheme. We examine a proposal by Appleby and Whitehead\nin the spirit of this conjecture and analytically elucidate an obstruction in\ntheir construction for guaranteeing hive generation, while detailing stronger\nconditions under which we can produce hives with almost certain probability. We\nprovide the first mapping of this prescription onto a practical algorithmic\nspace that enables us to produce affirming computational results and open a new\narea of research into the analysis of the random geometries and curvatures of\nhive surfaces from select matrix ensembles.\nThe second part of this manuscript concerns Littlewood-Richardson\ncoefficients and methods of estimating them from the hive construction. We\nillustrate experimental confirmation of two numerical algorithms that we\nprovide as tools for the community: one as a rounded estimator on the\ncontinuous hive polytope volume following a proposal by Narayanan, and the\nother as a novel construction using a coordinate hit-and-run on the hive\nlattice itself. We compare the advantages of each, and include numerical\nresults on their accuracies for some tested cases.\n",
"title": "Honey from the Hives: A Theoretical and Computational Exploration of Combinatorial Hives"
}
| null | null | null | null | true | null |
10578
| null |
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| null | null |
null |
{
"abstract": " A rapid and anisotropic modification of the Fermi-surface shape can be\nassociated with abrupt changes in crystalline lattice geometry or in the\nmagnetic state of a material. In this study we show that such an electronic\ntopological transition is at the basis of the formation of an unusual\npressure-induced tetragonal ferromagnetic phase in Fe$_{1.08}$Te. Around 2 GPa,\nthe orthorhombic and incommensurate antiferromagnetic ground-state of\nFe$_{1.08}$Te is transformed upon increasing pressure into a tetragonal\nferromagnetic state via a conventional first-order transition. On the other\nhand, an isostructural transition takes place from the paramagnetic\nhigh-temperature state into the ferromagnetic phase as a rare case of a `type\n0' transformation with anisotropic properties. Electronic-structure\ncalculations in combination with electrical resistivity, magnetization, and\nx-ray diffraction experiments show that the electronic system of Fe$_{1.08}$Te\nis instable with respect to profound topological transitions that can drive\nfundamental changes of the lattice anisotropy and the associated magnetic\norder.\n",
"title": "Pressure-induced ferromagnetism due to an anisotropic electronic topological transition in Fe1.08Te"
}
| null | null | null | null | true | null |
10579
| null |
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| null | null |
null |
{
"abstract": " In visual exploration and analysis of data, determining how to select and\ntransform the data for visualization is a challenge for data-unfamiliar or\ninexperienced users. Our main hypothesis is that for many data sets and common\nanalysis tasks, there are relatively few \"data slices\" that result in effective\nvisualizations. By focusing human users on appropriate and suitably transformed\nparts of the underlying data sets, these data slices can help the users carry\ntheir task to correct completion.\nTo verify this hypothesis, we develop a framework that permits us to capture\nexemplary data slices for a user task, and to explore and parse\nvisual-exploration sequences into a format that makes them distinct and easy to\ncompare. We develop a recommendation system, DataSlicer, that matches a\n\"currently viewed\" data slice with the most promising \"next effective\" data\nslices for the given exploration task. We report the results of controlled\nexperiments with an implementation of the DataSlicer system, using four common\nanalytical task types. The experiments demonstrate statistically significant\nimprovements in accuracy and exploration speed versus users without access to\nour system.\n",
"title": "DataSlicer: Task-Based Data Selection for Visual Data Exploration"
}
| null | null |
[
"Computer Science"
] | null | true | null |
10580
| null |
Validated
| null | null |
null |
{
"abstract": " Convolutional operator learning is increasingly gaining attention in many\nsignal processing and computer vision applications. Learning kernels has mostly\nrelied on so-called local approaches that extract and store many overlapping\npatches across training signals. Due to memory demands, local approaches have\nlimitations when learning kernels from large datasets -- particularly with\nmulti-layered structures, e.g., convolutional neural network (CNN) -- and/or\napplying the learned kernels to high-dimensional signal recovery problems. The\nso-called global approach has been studied within the \"synthesis\" signal model,\ne.g., convolutional dictionary learning, overcoming the memory problems by\ncareful algorithmic designs. This paper proposes a new convolutional analysis\noperator learning (CAOL) framework in the global approach, and develops a new\nconvergent Block Proximal Gradient method using a Majorizer (BPG-M) to solve\nthe corresponding block multi-nonconvex problems. To learn diverse filters\nwithin the CAOL framework, this paper introduces an orthogonality constraint\nthat enforces a tight-frame (TF) filter condition, and a regularizer that\npromotes diversity between filters. Numerical experiments show that, for tight\nmajorizers, BPG-M significantly accelerates the CAOL convergence rate compared\nto the state-of-the-art method, BPG. Numerical experiments for sparse-view\ncomputational tomography show that CAOL using TF filters significantly improves\nreconstruction quality compared to a conventional edge-preserving regularizer.\nFinally, this paper shows that CAOL can be useful to mathematically model a\nCNN, and the corresponding updates obtained via BPG-M coincide with core\nmodules of the CNN.\n",
"title": "Convolutional Analysis Operator Learning: Acceleration, Convergence, Application, and Neural Networks"
}
| null | null | null | null | true | null |
10581
| null |
Default
| null | null |
null |
{
"abstract": " The construction of permutation trinomials over finite fields attracts\npeople's interest recently due to their simple form and some additional\nproperties. Motivated by some results on the construction of permutation\ntrinomials with Niho exponents, by constructing some new fractional polynomials\nthat permute the set of the $(q+1)$-th roots of unity in $\\mathbb F_{q^2}$, we\npresent several classes of permutation trinomials with Niho exponents over\n$\\mathbb F_{q^2}$, where $q=5^k$.\n",
"title": "Several Classes of Permutation Trinomials over $\\mathbb F_{5^n}$ From Niho Exponents"
}
| null | null | null | null | true | null |
10582
| null |
Default
| null | null |
null |
{
"abstract": " Recent observations identify a valley in the radius distribution of small\nexoplanets, with planets in the range $1.5-2.0\\,{\\rm R}_{\\oplus}$ significantly\nless common than somewhat smaller or larger planets. This valley may suggest a\nbimodal population of rocky planets that are either engulfed by massive gas\nenvelopes that significantly enlarge their radius, or do not have detectable\natmospheres at all. One explanation of such a bimodal distribution is\natmospheric erosion by high-energy stellar photons. We investigate an\nalternative mechanism: the luminosity of the cooling rocky core, which can\ncompletely erode light envelopes while preserving heavy ones, produces a\ndeficit of intermediate sized planets. We evolve planetary populations that are\nderived from observations using a simple analytical prescription, accounting\nself-consistently for envelope accretion, cooling and mass loss, and\ndemonstrate that core-powered mass loss naturally reproduces the observed\nradius distribution, regardless of the high-energy incident flux. Observations\nof planets around different stellar types may distinguish between\nphotoevaporation, which is powered by the high-energy tail of the stellar\nradiation, and core-powered mass loss, which depends on the bolometric flux\nthrough the planet's equilibrium temperature that sets both its cooling and\nmass-loss rates.\n",
"title": "Core-powered mass loss and the radius distribution of small exoplanets"
}
| null | null | null | null | true | null |
10583
| null |
Default
| null | null |
null |
{
"abstract": " The Sparsity of the Gradient (SoG) is a robust autofocusing criterion for\nholography, where the gradient modulus of the complex refocused hologram is\ncalculated, on which a sparsity metric is applied. Here, we compare two\ndifferent choices of sparsity metrics used in SoG, specifically, the Gini index\n(GI) and the Tamura coefficient (TC), for holographic autofocusing on\ndense/connected or sparse samples. We provide a theoretical analysis predicting\nthat for uniformly distributed image data, TC and GI exhibit similar behavior,\nwhile for naturally sparse images containing few high-valued signal entries and\nmany low-valued noisy background pixels, TC is more sensitive to distribution\nchanges in the signal and more resistive to background noise. These predictions\nare also confirmed by experimental results using SoG-based holographic\nautofocusing on dense and connected samples (such as stained breast tissue\nsections) as well as highly sparse samples (such as isolated Giardia lamblia\ncysts). Through these experiments, we found that ToG and GoG offer almost\nidentical autofocusing performance on dense and connected samples, whereas for\nnaturally sparse samples, GoG should be calculated on a relatively small region\nof interest (ROI) closely surrounding the object, while ToG offers more\nflexibility in choosing a larger ROI containing more background pixels.\n",
"title": "Comparison of Gini index and Tamura coefficient for holographic autofocusing based on the edge sparsity of the complex optical wavefront"
}
| null | null |
[
"Physics"
] | null | true | null |
10584
| null |
Validated
| null | null |
null |
{
"abstract": " The purpose of this note is to propose a new approach for the probabilistic\ninterpretation of Hamilton-Jacobi-Bellman equations associated with stochastic\nrecursive optimal control problems, utilizing the representation theorem for\ngenerators of backward stochastic differential equations. The key idea of our\napproach for proving this interpretation consists of transmitting the signs\nbetween the solution and generator via the identity given by representation\ntheorem. Compared with existing methods, our approach seems to be more\napplicable for general settings. This can also be regarded as a new application\nof such representation theorem.\n",
"title": "Probabilistic interpretation of HJB equations by the representation theorem for generators of BSDEs"
}
| null | null | null | null | true | null |
10585
| null |
Default
| null | null |
null |
{
"abstract": " Image semantic segmentation is more and more being of interest for computer\nvision and machine learning researchers. Many applications on the rise need\naccurate and efficient segmentation mechanisms: autonomous driving, indoor\nnavigation, and even virtual or augmented reality systems to name a few. This\ndemand coincides with the rise of deep learning approaches in almost every\nfield or application target related to computer vision, including semantic\nsegmentation or scene understanding. This paper provides a review on deep\nlearning methods for semantic segmentation applied to various application\nareas. Firstly, we describe the terminology of this field as well as mandatory\nbackground concepts. Next, the main datasets and challenges are exposed to help\nresearchers decide which are the ones that best suit their needs and their\ntargets. Then, existing methods are reviewed, highlighting their contributions\nand their significance in the field. Finally, quantitative results are given\nfor the described methods and the datasets in which they were evaluated,\nfollowing up with a discussion of the results. At last, we point out a set of\npromising future works and draw our own conclusions about the state of the art\nof semantic segmentation using deep learning techniques.\n",
"title": "A Review on Deep Learning Techniques Applied to Semantic Segmentation"
}
| null | null | null | null | true | null |
10586
| null |
Default
| null | null |
null |
{
"abstract": " While all kinds of mixed data -from personal data, over panel and scientific\ndata, to public and commercial data- are collected and stored, building\nprobabilistic graphical models for these hybrid domains becomes more difficult.\nUsers spend significant amounts of time in identifying the parametric form of\nthe random variables (Gaussian, Poisson, Logit, etc.) involved and learning the\nmixed models. To make this difficult task easier, we propose the first\ntrainable probabilistic deep architecture for hybrid domains that features\ntractable queries. It is based on Sum-Product Networks (SPNs) with piecewise\npolynomial leave distributions together with novel nonparametric decomposition\nand conditioning steps using the Hirschfeld-Gebelein-Rényi Maximum\nCorrelation Coefficient. This relieves the user from deciding a-priori the\nparametric form of the random variables but is still expressive enough to\neffectively approximate any continuous distribution and permits efficient\nlearning and inference. Our empirical evidence shows that the architecture,\ncalled Mixed SPNs, can indeed capture complex distributions across a wide range\nof hybrid domains.\n",
"title": "Sum-Product Networks for Hybrid Domains"
}
| null | null | null | null | true | null |
10587
| null |
Default
| null | null |
null |
{
"abstract": " Incremental improvements in accuracy of Convolutional Neural Networks are\nusually achieved through use of deeper and more complex models trained on\nlarger datasets. However, enlarging dataset and models increases the\ncomputation and storage costs and cannot be done indefinitely. In this work, we\nseek to improve the identification and verification accuracy of a\ntext-independent speaker recognition system without use of extra data or deeper\nand more complex models by augmenting the training and testing data, finding\nthe optimal dimensionality of embedding space and use of more discriminative\nloss functions. Results of experiments on VoxCeleb dataset suggest that: (i)\nSimple repetition and random time-reversion of utterances can reduce prediction\nerrors by up to 18%. (ii) Lower dimensional embeddings are more suitable for\nverification. (iii) Use of proposed logistic margin loss function leads to\nunified embeddings with state-of-the-art identification and competitive\nverification accuracies.\n",
"title": "Unified Hypersphere Embedding for Speaker Recognition"
}
| null | null | null | null | true | null |
10588
| null |
Default
| null | null |
null |
{
"abstract": " This paper describes a method for learning low-dimensional approximations of\nnonlinear dynamical systems, based on neural-network approximations of the\nunderlying Koopman operator. Extended Dynamic Mode Decomposition (EDMD)\nprovides a useful data-driven approximation of the Koopman operator for\nanalyzing dynamical systems. This paper addresses a fundamental problem\nassociated with EDMD: a trade-off between representational capacity of the\ndictionary and over-fitting due to insufficient data. A new neural network\narchitecture combining an autoencoder with linear recurrent dynamics in the\nencoded state is used to learn a low-dimensional and highly informative\nKoopman-invariant subspace of observables. A method is also presented for\nbalanced model reduction of over-specified EDMD systems in feature space.\nNonlinear reconstruction using partially linear multi-kernel regression aims to\nimprove reconstruction accuracy from the low-dimensional state when the data\nhas complex but intrinsically low-dimensional structure. The techniques\ndemonstrate the ability to identify Koopman eigenfunctions of the unforced\nDuffing equation, create accurate low-dimensional models of an unstable\ncylinder wake flow, and make short-time predictions of the chaotic\nKuramoto-Sivashinsky equation.\n",
"title": "Linearly-Recurrent Autoencoder Networks for Learning Dynamics"
}
| null | null | null | null | true | null |
10589
| null |
Default
| null | null |
null |
{
"abstract": " The Dip Test of Unimodality and Silverman's Critical Bandwidth Test are two\npopular tests to determine if an unknown density contains more than one mode.\nWhile the tests can be easily run in R, they are not included in SAS software.\nWe provide implementations of the Dip Test and Silverman Test as macros in the\nSAS software, capitalizing on the capability of SAS to execute R code\ninternally. Descriptions of the macro parameters, installation steps, and\nsample macro calls are provided, along with an appendix for troubleshooting. We\nillustrate the use of the macros on data simulated from one or more Gaussian\ndistributions as well as on the famous $\\textit{iris}$ dataset.\n",
"title": "Macros to Conduct Tests of Multimodality in SAS"
}
| null | null |
[
"Statistics"
] | null | true | null |
10590
| null |
Validated
| null | null |
null |
{
"abstract": " In the first part of this paper we present a formalization in Agda of the\nJames construction in homotopy type theory. We include several fragments of\ncode to show what the Agda code looks like, and we explain several techniques\nthat we used in the formalization. In the second part, we use the James\nconstruction to give a constructive proof that $\\pi_4(\\mathbb{S}^3)$ is of the\nform $\\mathbb{Z}/n\\mathbb{Z}$ (but we do not compute the $n$ here).\n",
"title": "The James construction and $π_4(\\mathbb{S}^3)$ in homotopy type theory"
}
| null | null | null | null | true | null |
10591
| null |
Default
| null | null |
null |
{
"abstract": " Inelastic neutron scattering measurements on the itinerant antiferromagnet\n(AFM) CaCo$_{\\mathrm{2}-y}$As$_{2}$ at a temperature of 8 K reveal two\northogonal planes of scattering perpendicular to the Co square lattice in\nreciprocal space, demonstrating the presence of effective one-dimensional spin\ninteractions. These results are shown to arise from near-perfect bond\nfrustration within the $J_1$-$J_2$ Heisenberg model on a square lattice with\nferromagnetic $J_1$, and hence indicate that the extensive previous\nexperimental and theoretical study of the $J_1$-$J_2$ Heisenberg model on\nlocal-moment square spin lattices should be expanded to include itinerant spin\nsystems.\n",
"title": "Effective One-Dimensional Coupling in the Highly-Frustrated Square-Lattice Itinerant Magnet CaCo$_{\\mathrm{2}-y}$As$_{2}$"
}
| null | null | null | null | true | null |
10592
| null |
Default
| null | null |
null |
{
"abstract": " We study the problem of finding the maximum of a function defined on the\nnodes of a connected graph. The goal is to identify a node where the function\nobtains its maximum. We focus on local iterative algorithms, which traverse the\nnodes of the graph along a path, and the next iterate is chosen from the\nneighbors of the current iterate with probability distribution determined by\nthe function values at the current iterate and its neighbors. We study two\nalgorithms corresponding to a Metropolis-Hastings random walk with different\ntransition kernels: (i) The first algorithm is an exponentially weighted random\nwalk governed by a parameter $\\gamma$. (ii) The second algorithm is defined\nwith respect to the graph Laplacian and a smoothness parameter $k$. We derive\nconvergence rates for the two algorithms in terms of total variation distance\nand hitting times. We also provide simulations showing the relative convergence\nrates of our algorithms in comparison to an unbiased random walk, as a function\nof the smoothness of the graph function. Our algorithms may be categorized as a\nnew class of \"descent-based\" methods for function maximization on the nodes of\na graph.\n",
"title": "Graph-Based Ascent Algorithms for Function Maximization"
}
| null | null | null | null | true | null |
10593
| null |
Default
| null | null |
null |
{
"abstract": " The models of collective decision-making considered in this paper are\nnonlinear interconnected cooperative systems with saturating interactions.\nThese systems encode the possible outcomes of a decision process into different\nsteady states of the dynamics. In particular, they are characterized by two\nmain attractors in the positive and negative orthant, representing two choices\nof agreement among the agents, associated to the Perron-Frobenius eigenvector\nof the system. In this paper we give conditions for the appearance of other\nequilibria of mixed sign. The conditions are inspired by Perron-Frobenius\ntheory and are related to the algebraic connectivity of the network. We also\nshow how all these equilibria must be contained in a solid disk of radius given\nby the norm of the equilibrium point which is located in the positive orthant.\n",
"title": "Multiequilibria analysis for a class of collective decision-making networked systems"
}
| null | null | null | null | true | null |
10594
| null |
Default
| null | null |
null |
{
"abstract": " This paper focuses on the recognition of Activities of Daily Living (ADL)\napplying pattern recognition techniques to the data acquired by the\naccelerometer available in the mobile devices. The recognition of ADL is\ncomposed by several stages, including data acquisition, data processing, and\nartificial intelligence methods. The artificial intelligence methods used are\nrelated to pattern recognition, and this study focuses on the use of Artificial\nNeural Networks (ANN). The data processing includes data cleaning, and the\nfeature extraction techniques to define the inputs for the ANN. Due to the low\nprocessing power and memory of the mobile devices, they should be mainly used\nto acquire the data, applying an ANN previously trained for the identification\nof the ADL. The main purpose of this paper is to present a new method\nimplemented with ANN for the identification of a defined set of ADL with a\nreliable accuracy. This paper also presents a comparison of different types of\nANN in order to choose the type for the implementation of the final method.\nResults of this research probes that the best accuracies are achieved with Deep\nLearning techniques with an accuracy higher than 80%.\n",
"title": "Pattern Recognition Techniques for the Identification of Activities of Daily Living using Mobile Device Accelerometer"
}
| null | null | null | null | true | null |
10595
| null |
Default
| null | null |
null |
{
"abstract": " Monitoring structural changes in ferroelectric thin films during electric\nfield-induced polarization switching is important for a full microscopic\nunderstanding of the coupled motion of charges, atoms and domain walls. We\ncombine standard ferroelectric test-cycles with time-resolved x-ray diffraction\nto investigate the response of a nanoscale ferroelectric oxide capacitor upon\ncharging, discharging and switching. Piezoelectric strain develops during the\nelectronic RC time constant and additionally during structural domain-wall\ncreep. The complex atomic motion during ferroelectric polarization reversal\nstarts with a negative piezoelectric response to the charge flow triggered by\nvoltage pulses. Incomplete screening limits the compressive strain. The\npiezoelectric modulation of the unit cell tweaks the energy barrier between the\ntwo polarization states. Domain wall motion is evidenced by a broadening of the\nin-plane components of Bragg reflections. Such simultaneous measurements on a\nworking device elucidate and visualize the complex interplay of charge flow and\nstructural motion and challenges theoretical modelling.\n",
"title": "Simultaneous dynamic characterization of charge and structural motion during ferroelectric switching"
}
| null | null | null | null | true | null |
10596
| null |
Default
| null | null |
null |
{
"abstract": " In this work, we aim to explore connections between dynamical systems\ntechniques and combinatorial optimization problems. In particular, we construct\nheuristic approaches for the traveling salesman problem (TSP) based on\nembedding the relaxed discrete optimization problem into appropriate manifolds.\nWe explore multiple embedding techniques -- namely, the construction of new\ndynamical systems on the manifold of orthogonal matrices and associated\nProcrustes approximations of the TSP cost function. Using these dynamical\nsystems, we analyze the local neighborhood around the optimal TSP solutions\n(which are equilibria) using computations to approximate the associated\n\\emph{stable manifolds}. We find that these flows frequently converge to\nundesirable equilibria. However, the solutions of the dynamical systems and the\nassociated Procrustes approximation provide an interesting biasing approach for\nthe popular Lin--Kernighan heuristic which yields fast convergence. The\nLin--Kernighan heuristic is typically based on the computation of edges that\nhave a `high probability' of being in the shortest tour, thereby effectively\npruning the search space. Our new approach, instead, relies on a natural\nrelaxation of the combinatorial optimization problem to the manifold of\northogonal matrices and the subsequent use of this solution to bias the\nLin--Kernighan heuristic. Although the initial cost of computing these edges\nusing the Procrustes solution is higher than existing methods, we find that the\nProcrustes solution, when coupled with a homotopy computation, contains\nvaluable information regarding the optimal edges. We explore the Procrustes\nbased approach on several TSP instances and find that our approach often\nrequires fewer $k$-opt moves than existing approaches. Broadly, we hope that\nthis work initiates more work in the intersection of dynamical systems theory\nand combinatorial optimization.\n",
"title": "Continuous Relaxations for the Traveling Salesman Problem"
}
| null | null |
[
"Computer Science",
"Mathematics"
] | null | true | null |
10597
| null |
Validated
| null | null |
null |
{
"abstract": " Octonion algebras over rings are, in contrast to those over fields, not\ndetermined by their norm forms. Octonion algebras whose norm is isometric to\nthe norm q of a given algebra C are twisted forms of C by means of the\nAut(C)-torsor O(q) ->O(q)/Aut(C). We show that, over any commutative unital\nring, these twisted forms are precisely the isotopes C(a,b) of C, with\nmultiplication given by x*y=(xa)(by), for unit norm octonions a,b of C. The\nlink is provided by the triality phenomenon, which we study from new and\nclassical perspectives. We then study these twisted forms using the interplay,\nthus obtained, between torsor geometry and isotope computations, thus obtaining\nnew results on octonion algebras over e.g. rings of (Laurent) polynomials.\n",
"title": "Isotopes of Octonion Algebras, G2-Torsors and Triality"
}
| null | null | null | null | true | null |
10598
| null |
Default
| null | null |
null |
{
"abstract": " Two fundamental approaches to information averaging are based on linear and\nlogarithmic combination, yielding the arithmetic average (AA) and geometric\naverage (GA) of the fusing initials, respectively. In the context of target\ntracking, the two most common formats of data to be fused are random variables\nand probability density functions, namely $v$-fusion and $f$-fusion,\nrespectively. In this work, we analyze and compare the second order statistics\n(including variance and mean square error) of AA and GA in terms of both\n$v$-fusion and $f$-fusion. The case of weighted Gaussian mixtures representing\nmultitarget densities in the presence of false alarms and misdetection (whose\nweight sums are not necessarily unit) is also considered, the result of which\nappears significantly different from that for a single target. In addition to\nexact derivation, exemplifying analysis and illustrations are provided.\n",
"title": "Second Order Statistics Analysis and Comparison between Arithmetic and Geometric Average Fusion"
}
| null | null |
[
"Computer Science",
"Mathematics",
"Statistics"
] | null | true | null |
10599
| null |
Validated
| null | null |
null |
{
"abstract": " An atomic transition can be addressed by a single tooth of an optical\nfrequency comb if the excited state lifetime ($\\tau$) is significantly longer\nthan the pulse repetition period ($T_\\mathrm{r}$). In the crossover regime\nbetween fully-resolved and unresolved comb teeth ($\\tau \\lessapprox\nT_\\mathrm{r}$), we observe Doppler cooling of a pre-cooled trapped atomic ion\nby a single tooth of a frequency-doubled optical frequency comb. We find that\nfor initially hot ions, a multi-tooth effect gives rise to lasing of the ion's\nharmonic motion in the trap, verified by acoustic injection locking. The gain\nsaturation of this phonon laser action leads to a comb of steady-state\noscillation amplitudes, allowing hot ions to be loaded directly into the trap\nand laser cooled to crystallization despite the presence of hundreds of\nblue-detuned teeth.\n",
"title": "Phonon lasing from optical frequency comb illumination of a trapped ion"
}
| null | null |
[
"Physics"
] | null | true | null |
10600
| null |
Validated
| null | null |
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